Identify gene expression profiles in freshwater mussels under thermal stress

janua y 2024 UMinho | 2024 Iden i y gene exp ession p o iles in eshwa e mussels unde he mal s ess Bea iz Fe ei a da Sil a Uni e si y o Minho School o Enginee ing Bea iz Fe ei a da Sil a Iden i y gene exp ession p o iles in eshwa e mussels unde he mal s ess Uni e si y o Minho School o Enginee ing Bea iz Fe ei a da Sil a Iden i y gene exp ession p o iles in eshwa e mussels unde he mal s ess Mas e s Disse a ion Mas e ’s in Bioin o ma ics Disse a ion supe ised by Elsa Ma ia B anco F ou e And ade Ronaldo Gomes de Sousa janua y 2024 ii DIREITOS DE AUTOR E CONDIÇÕES DE UTILIZAÇÃO DO TRABALHO POR TERCEIROS Es e é um abalho académico que pode se u ilizado po e cei os desde que espei adas as eg as de boas p á icas in e nacionalmen e acei es, no que diz espei o aos di ei os de au o e di ei os conexos. Assim, o p esen e documen o pode se u ilizado nos e mos p e is os na licença abaixo indicada. Caso o u ilizado ca eça de pe missão pa a pode aze um uso do abalho em condições não p e is as no licenciamen o indicado, de e á con ac a o au o , a a és do Reposi ó iUM da Uni e sidade do Minho. Licença concedida aos u ilizado es des e abalho A ibuição-NãoCome cial-SemDe i ações CC BY-NC-ND h ps://c ea i ecommons.o g/licenses/by-nc-nd/4.0/ iii AGRADECIMENTOS Começo po ag adece aos meus o ien ado es, P o esso Ronaldo Sousa e Dou o a Elsa F ou e, pela o ien ação que me p es a am du an e a ealização des e abalho, em pa icula à Dou o a Elsa F ou e, pelo seu apoio, p eocupação e mo i ação cons an e. Além disso, os meus since os ag adecimen os ão pa a o Dou o And é San os po me e apoiado em udo do início ao im do meu pe cu so. Fica ambém um especial ob igado à es an e equipa do Ciima , pelo ambien e acolhedo que p opo ciona am du an e es a es adia, e, em pa icula , ao Rui Pin o, po me e auxiliado em odas as minhas dú idas sob e o desen ol imen o do código. Que o ambém ag adece aos meus pais, em mui o, po me e em dado a possibilidade de ealiza es a disse ação. Um ob igada, po semp e ac edi a em em mim, mesmo quando eu p óp ia não ac edi ei. Ao meu i mão, que nada pe cebia da minha a éa e que sabia a minha disse ação de ás pa a a en e, um ob igada. Ao Diogo, com quem pa ilhei odas as minhas us ações e i ó ias nes a jo nada, um ob igado po se es um pila e po semp e ac edi a es em mim. Como um e úgio ex a nos momen os de maio s ess o am odos os meus amigos, que semp e me de am o ças e ajuda am a descon ai quando assim necessi a a. Não me pode ei esquece ambém das minhas g andes amigas do secundá io, And eia Ta ei a, Ana Mo a e Bea iz Ma ins, que semp e me apoia am e me de am uma mo i ação ex a. A odos eles, o meu eno me ob igado! O abalho desen ol ido nes a disse ação es á inco po ado no p oje o: EdgeOmics - F eshwa e Bi al es a he edge: Adap a ion genomics unde clima e-change scena ios (h p://doi.o g/10.54499/PTDC/CTA-AMB/3065/2020). i DECLARAÇÃO DE INTEGRIDADE Decla o e a uado com in eg idade na elabo ação do p esen e abalho académico e con i mo que não eco i à p á ica de plágio nem a qualque o ma de u ilização inde ida ou alsi icação de in o mações ou esul ados em nenhuma das e apas conducen e à sua elabo ação. Mais decla o que conheço e que espei ei o Código de Condu a É ica da Uni e sidade do Minho. Abs ac Due o global clima e change, he empe a u es o s eams and i e s a e inc easing, nega i ely a ec ing aqua ic li e, including bi al e species. F eshwa e mussels a e i al componen s o i e s, s eams, and lake ecosys ems, pa icipa ing in essen ial ecological oles such as nu ien cycling, and inc easing wa e quali y. Fu he mo e, hey se e as essen ial ecosys em enginee s, p o iding habi a o o he o ganisms and suppo ing in ica e ood webs. Besides hei biological impo ance, eshwa e mussels a e poo ly s udied in e ms o genomics. In he p esen wo k, he Ibe ian dolphin eshwa e mussel Unio delphinus Spengle , 1793 (Bi al ia: Unionoida) was used as a model species o in es iga e he e ec s o clima e change in eshwa e mussels. The p ima y objec i e o his hesis was o de e mine he gene exp ession pa e ns in a model species o eshwa e mussels unde he e ec s o he mal s ess exace ba ed by clima e change, wi h an o e all goal o unde s anding he po en ial consequences o eshwa e mussel popula ions. Two di e en ecological expe imen s we e pe o med: ch onic and acu e. The ch onic expe imen s whe e empe a u es we e g adually inc eased o simula e a scena io o p og essi e inc easing empe a u es. The acu e expe imen s whe e empe a u es we e apidly inc eased o eplica e he e ec s o a b ie e ex eme clima ic e en . To achie e his main goal, a comp ehensi e bioin o ma ic pipeline ocused on ansc ip omics analysis was de eloped using he R Bioconduc o package o gene a e he di e en ial gene exp ession p o iles o hese indi iduals unde he mal s ess. The bioin o ma ic me hodology o his wo k di e s om he pas s udies, by de eloping an R code compila ion o h ee me hods, EdgeR, limma, and DESeq2 o di e en ial gene exp ession analysis in hese o ganisms. The ou pu o he p esen wo k p o ides a comp ehensi e o e iew o gene exp ession p o ile esponses o U. delphinus unde clima e change scena ios. Addi ionally, he esul s e ealed a wide ange o pa hways and he co esponding genes ha a e impac ed by he mal s ess, wi h a pa icula emphasis on he up- egula ion o he genes ATP6V1A, ATP6V0A1, ATP6V0A, and ATP6V1. In he ch onic expe imen s, and high empe a u es, mussels exp essed hese genes and, in e es ingly, all he pa hways ha hese genes included appea ed up- egula ed. The disco e ed genes and pa hways p o ide i al insigh s in o hese o ganisms’ adap a ion ac ics and iden i y p ospec i e a ge s o moni o ing and conse a ion e o s. Keywo ds: F eshwa e mussels; ansc ip omics; bioin o ma ics; gene exp ession; clima e change. i Resumo De ido às al e ações climá icas globais, a empe a u a dos ios e ibei os es á a aumen a , a ec ando a ida aquá ica, incluindo as espécies de bi al es. Os mexilhões de água doce são componen es dos ios, ibei os e lagos, pa icipando em unções i ais dos ecossis emas, como a eciclagem de nu ien es e melho ando a qualidade da água. Além disso, a uam como engenhei os de ecossis emas, p o idenciando habi a a ou os o ganismos e azendo pa e de eias alimen a es complexas. Apesa da sua impo ância biológica, os mexilhões de água doce são pouco es udados em e mos genómicos. No p esen e abalho, o mexilhão de água doce Unio delphinus Spengle , 1793 (Bi al ia: Unionoida) é u i-lizado como espécie modelo pa a in es iga os e ei os das mudanças climá icas em mexilhões de água doce. O obje i o p incipal des a disse ação oi de e mina os pad ões de exp essão gené ica numa es-pécie modelo de mexilhões de água doce sob os e ei os de s ess é mico exace bado pelas mudanças climá icas, com o obje i o ge al de comp ende as consequências pa a populações de mexilhões de água doce. Duas expe iências o am ealizadas: c ónica e aguda. As expe iências c ónicas onde a empe a u a oi g adualmen e aumen ada pa a simula um cená io de aumen o p og es-si o da empe a u a. As expe iências agudas onde a empe a u a oi aumen ada apidamen e de modo a ep oduzi os e ei os de um ex emo climá ico b e e. De modo a a ingi esse obje i o, uma pipeline de bioin o má ica ocada na análise ansc ip ómica oi desen ol ido usando o paco e R Bioconduc o pa a ge a os pe is di e enciais de exp essão gené ica desses indi íduos sob s ess é mico. A me odologia bioin o má ica des e abalho di e e dos es udos an e io es, po desen ol e uma compilação de código em R de ês mé odos, EdgeR, limma e DESeq2 pa a análise di e encial de exp essão gené ica nesses o ganismos. O esul ado do p esen e abalho o nece uma isão ab angen e das espos as do pe il de exp essão gené ica de U. delphinus num cená io de mudanças climá icas. Os esul ados e ela am uma ampla gama de ias e os genes co esponden es elacionados com o s ess é mico, com ên ase pa icula na egulação posi i a dos genes ATP6V1A, ATP6V0A1, ATP6V0A e ATP6V1. Nas expe iências c ónicas, a uma empe a u a ele ada, os mexilhões exp essa am es es genes e, cu iosamen e, odas as ias que es es genes incluíam pa eciam eguladas posi i amen e. Os genes e ias descobe os o necem in o mações i ais sob e adap ação des es o ganismos e iden i icam al os po enciais pa a es o ços de conse ação. Pala as-cha e: Mexilhões de água doce; ansc ip ómica; bioin o má ica; exp essão gené ica; al e ações climá ica. Con en s 1 In oduc ion 1 1.1 Con ex /mo i a ion .................................. 1 1.2 Objec i es ...................................... 2 1.3 Thesis S uc u e ................................... 2 2 S a e o he A 4 2.1 T ansc ip omics .................................... 4 2.1.1 A b ie his o y ................................ 4 2.1.2 Nex Gene a ion Sequencing ......................... 6 2.2 RNA Sequencing ................................... 11 2.2.1 RNA-Seq wo k low .............................. 11 2.2.2 Applica ions o RNA-Seq da a ......................... 15 2.2.3 Di e en ial gene exp ession analysis ..................... 17 2.3 F eshwa e mussels as a model o ganism ....................... 20 2.4 The e ec s o clima e change on eshwa e ecosys ems ................ 22 2.4.1 Physiological p ocesses ............................ 23 2.4.2 Phenological p ocesses ............................ 24 2.4.3 Gene ic a ia ion ............................... 25 2.5 Bioin o ma ics In eg a ion ............................... 26 3 Me hodologies 28 3.1 B ie o e iew ..................................... 28 3.1.1 Sampling and labo a o y acclima iza ion ................... 28 3.1.2 Ecological Expe imen ............................ 28 3.1.3 RNA ex ac ion and NGS sequencing ..................... 30 3.2 Bioin o ma ics .................................... 30 ii 20 Veen diag am o he compa isons No h 20 °C ∩25 °C ∩30 °C and Sou h 20 °C ∩ 25 °C ∩30 °C. ................................... 53 21 Volcano plo and hea map o he compa a i e analysis o No h s Sou h a he empe - a u e o 20 ºC o ch onic expe imen s. The olcano plo includes he o al numbe o DGEs, along wi h he down- egula ed and up- egula ed numbe o DGEs. The blue poin s ep esen he down- egula ed genes and he ed ones he up- egula ed genes. ..... 54 22 Volcano plo and hea map o he compa a i e analysis o No h s Sou h a he empe - a u e o 25 ºC o ch onic expe imen s. The olcano plo includes he o al numbe o DGEs, along wi h he down- egula ed and up- egula ed numbe o DGEs. The blue poin s ep esen he down- egula ed genes and he ed ones he up- egula ed genes. ..... 54 23 Volcano plo and hea map o he compa a i e analysis o No h s Sou h a he empe - a u e o 30 ºC o ch onic expe imen s. The olcano plo includes he o al numbe o DGEs, along wi h he down- egula ed and up- egula ed numbe o DGEs. The blue poin s ep esen he down- egula ed genes and he ed ones he up- egula ed genes. ..... 55 24 Volcano plo and hea map o he compa a i e analysis o No h s Sou h ch onic ex- pe imen s. The olcano plo includes he o al numbe o DGEs, along wi h he down- egula ed and up- egula ed numbe o DGEs. The blue poin s ep esen he down- egula ed genes and he ed ones he up- egula ed genes. ............... 55 25 Es ima ed dispe sion plo s o acu e expe imen s, using h ee dis inc me hods: EdgeR, limma, DESeq2. ................................... 56 26 Volcano plo and hea map o acu e expe imen s o he compa a i e analysis: No h s Sou h. Along wi h he olcano plo is ep esen ed he o al numbe o DGEs, along wi h he down- egula ed and up- egula ed numbe o DGEs. Each da a poin on he plo co esponds o a unique gene. The blue poin s ep esen he down- egula ed genes and he ed ones he up- egula ed genes. ......................... 57 27 O e iew o g: P o ile esul s in ch onic expe imen s a h ee empe a u es (20 ºC, 25 ºC, and 30 ºC), highligh ing s a is ically signi ican en ichmen s, and empe a u e- speci ic pa e ns. ................................... 58 28 O e iew o g: P o ile esul s in ch onic expe imen s in he compa a i e analysis o No h s Sou h, highligh ing s a is ically signi ican en ichmen s, and empe a u e-speci ic pa - e ns. ......................................... 59 xi 29 O e iew o g: P o ile esul s in acu e expe imen s, highligh ing s a is ically signi ican en ichmen s, empe a u e-speci ic pa e ns. ...................... 69 30 RNA concen a ion (ng/µl) and quali y measu emen s (OD260/280 a io alues) o acu e expe imen s. The blue able ep esen s he no he n popula ion and he o ange able he sou he n popula ion. .............................105 31 RNA concen a ion (ng/µl) and quali y measu emen s (OD260/280 a io alues) o ch onic expe imen s. The blue able ep esen s he no he n popula ion and he o ange able he sou he n popula ion. .............................106 x Lis o Tables 1 So wa e packages mos ly used o iden i y gene exp ession. .............. 19 2 Compa a i e analysis conduc ed in ch onic and acu e expe imen s using bo h DEApp and R/Bioconduc o package. The compa isons highligh ed in blue we e pe o med exclusi ely using he R/Bioconduc o packages. .................... 36 3 Alignmen a e o each ead sample o ch onic expe imen s agains he Unio delphinus e e ence genome. Samples we e named acco ding o wo a iables: popula ion and empe a u e. No h popula ion samples we e accessed wi h ”N” and sou h popula ions wi h ”S”, and nex o his i s le e wi h he empe a u e. In he case o ch onic expe i- men s, i can be 20, 25, o 30. Following he empe a u e a e he eplica es, which a e i e pe condi ion, and a e ep esen ed by ”G1”, ”G2”, ”G3”, ”G4” and ”G5”. ..... 44 4 Alignmen a es o each ead sample o acu e expe imen agains he Unio delphinus e e ence genome. Samples we e named acco ding o wo a iables: popula ion and empe a u e. No h popula ion samples we e accessed wi h ”N” and sou h popula ions wi h ”S”, and nex o his i s le e wi h he empe a u e. In he case o ch onic expe - imen s, can be 20, 25, o 30. Following he empe a u e a e he eplica es, which a e i e pe condi ion, and a e ep esen ed by ”G1”, ”G2”, ”G3”, ”G4” and ”G5”. ..... 45 5 Numbe o DGEs using he so wa e DEApp and R/Bioconduc o code in all he com- pa a i e analyses de eloped using he h ee me hods, EdgeR, Limma, and DESeq2, and numbe o DGEs esul ing om he o e lap o he h ee me hods in he analysis ha showed consis ency in he esul s. ........................... 52 6 Numbe o DGEs using he so wa e DEApp and R/Bioconduc o code in he compa a i e analysis de eloped using he h ee me hods, EdgeR, Limma, and DESeq2, and numbe o DGEs esul ing om he o e lap o he h ee me hods in he analysis ha showed consis ency in he esul s. ............................... 57 x i 7 Gene On ology (GO) Molecula Func ion (GO: MF), he da abase o manually anno a ed p o ein complexes (CORUM), Cellula Componen (GO: CC), Human Pheno ype On ology (HP) and Reac ome pa hways (REAC) en ichmen analysis o he compa a i e ou pu analysis o No h s Sou h a he empe a u e o 20 ºC in ch onic expe imen s, using g: P o ile . ........................................ 60 8 Gene On ology (GO) Molecula Func ion (GO: MF), Biological P ocesses (GO: BP), Cel- lula Componen (GO: CC), and he da abase o manually anno a ed p o ein complexes (CORUM) en ichmen analysis o he compa a i e ou pu analysis o No h s Sou h a he empe a u e o 25 ºC in ch onic expe imen s, using g: P o ile . ........... 62 9 Gene On ology (GO) Molecula Func ion (MF), Biological P ocess (BP), Cellula Compo- nen s (CC), Kyo o Encyclopedia o Genes and Genomes (KEGG), and Reac ome (REAC) en ichmen analysis o he compa a i e ou pu analysis o No h s Sou h a he empe - a u e o 30 ºC in ch onic expe imen s, using g: P o ile . ................ 66 10 Gene On ology (GO) Molecula Func ion (MF), Biological P ocess (BP), Cellula Compo- nen s (CC), Kyo o Encyclopedia o Genes and Genomes (KEGG), and Reac ome (REAC) en ichmen analysis o he compa a i e ou pu analysis o No h s Sou h in ch onic expe imen s, using g: P o ile . ............................. 71 11 Gene On ology (GO) Molecula Func ion (GO: MF), Biological P ocesses (GO: BP), Cellula Componen (GO: CC), Reac ome (REAC), and P o ein da abases (CORUM) en ichmen analysis o he compa a i e ou pu analysis o No h s Sou h in acu e expe imen s, using g: P o ile . ...................................... 72 12 Lis o go e ms and hei associa e gene names and desc ip ions o he compa a i e analysis o ch onic expe imen s in he empe a u e o 20 ºC. ..............110 13 Lis o go e ms and hei associa e gene names and desc ip ions o he compa a i e analysis o ch onic expe imen s in he empe a u e o 25 ºC. ..............111 14 Lis o go e ms and hei associa e gene names and desc ip ions o he compa a i e analysis o ch onic expe imen s in he empe a u e o 30 ºC. ..............112 15 Lis o go e ms and hei associa e gene names and desc ip ions o he compa a i e analysis o No h s Sou h o ch onic expe imen s. ...................115 16 Lis o go e ms and hei associa e gene names and desc ip ions o he compa a i e analysis o acu e expe imen s. .............................117 x ii x iii Chap e 1 In oduc ion 1.1 Con ex /mo i a ion Clima e change is an escala ing global p oblem, a ec ing all li ing o ganisms ac oss ecosys ems (1). F eshwa e mussels a e no excep ion and a e inc easingly ulne able o en i onmen al s esso s, including clima e change. These o ganisms, as i al componen s o i e s, s eams, and lakes ecosys ems, play essen ial ecological oles such as nu ien cycling and inc easing wa e quali y (2;3). Mo eo e , hey se e as essen ial ecosys em enginee s, p o iding habi a o o he o ganisms and suppo ing in ica e ood webs (4). F eshwa e mussels also se e as c i ical en i onmen al change indica o s, o e ing insigh s in o his o ical and cu en condi ions by, o example, analyzing hei shells, and o ecas ing impending wa e quali y shi s (5). Bi al es, and in pa icula eshwa e mussels, a e s ill poo ly s udied in e ms o genomics, wi h mos s udies s ill ocusing on species wi h conside able comme cial alue (6). This lack o in o ma ion could be wo isome gi en he ecological oles o bi al es and also because p edic ions a e c ucial o ale ing scien is s and esea che s abou po en ial haza ds in he u u e, p o iding a way o suppo he link be ween biological changes a di e en le els ( om indi iduals o ecosys ems) and clima e change (7). Bioin o ma ics ools and o he molecula app oaches a e widely used o s udy he gene ic a ia ion among o ganisms. Gi en he c ucial ecological impo ance and poo conse a ion s a us o many eshwa e mussel species, his axonomic g oup canno be dis ega ded conside ing his esea ch opic. In his con ex , RNA-Sequencing (RNA-Seq) echnology eme ges as an in aluable ool o in es iga ing he in ica e molecula esponses o eshwa e mussels o he mal s ess, shedding ligh on hei adap i e mechanisms unde clima e change scena ios. This in ol es iden i ying which genes a e up- egula ed o down- egula ed in esponse o luc ua ing empe a u es. Ul ima ely, he insigh s gained om his esea ch will enhance he unde s anding o how clima e change impac s eshwa e mussels and will p o ide aluable knowledge o implemen ing e ec i e s a egies o conse e and manage hese o ganisms in a apidly changing 1 en i onmen . 1.2 Objec i es The main goal o his mas e ’s hesis was o de e mine he gene exp ession pa e ns on eshwa e mussels, using he species o U. delphinus Spengle , 1793 as a model o ganism, unde he e ec s o clima e change. A comp ehensi e bioin o ma ic pipeline ocused on ansc ip omics analysis was de eloped o gene a e he di e en ial gene exp ession p o iles o hese indi iduals unde he mal s ess. The s udy ocuses on he applica ion o di e se bioin o ma ics ools and me hodologies. To achie e his goal he ollowing speci ic objec i es we e se up: ◦Conduc a e iew o he cu en s a e o knowledge and ele an concep s, laying he ounda ion o subsequen s ages o he s udy. ◦Pe o m da a p e-p ocessing gene a ed by sequencing, which in ol es quali y con ol and il e ing he aw sequencing da a. ◦Execu e ead mapping o he e e ence genome, enabling he accu a e alignmen o sequencing eads. ◦In es iga e di e en ial gene exp ession, aiming o iden i y genes ha exhibi signi ican changes in exp ession unde he mal s ess condi ions. ◦Unde ake a compa a i e analysis o gene exp ession p o iles, compa ing di e en expe imen al condi ions o gain insigh s in o how U. delphinus esponds o clima e-induced he mal s ess. ◦Conduc an en ichmen analysis o elucida e he biological p ocesses and pa hways ha a e signi ican ly impac ed by empe a u e-induced s ess in eshwa e mussels. 1.3 Thesis S uc u e Chap e 2. S a e o he A This chap e e ised he backg ound in o ma ion and li e a u e. Chap e 3. Me hodologies This chap e desc ibed he da a p ocessing me hods used in each ask o he s udy. 2 Chap e 4. Resul s and Discussion This chap e desc ibed key indings ob ained h ough he CIIMAR clus e , and R/Bioconduc o package, discussing hei main implica ions. Chap e 5. Conclusion The inal chap e summa izes he main indings and concludes he esea ch. 3 Chap e 2 S a e o he A 2.1 T ansc ip omics Genomic app oaches ha e been ecognized as undamen al ools o s udy biodi e si y (8;9). Genomics ools, such as, ansc ip omics a e key esou ces o unde s and indi iduals’ e olu iona y and adap i e cha ac e is ics (10). T ansc ip omics ep esen s one o he mos de eloped a eas in he pos -genomic age (11) and e e s o he s udy o he whole ansc ip ome (12). The ansc ip ome, which encompasses p o ein-coding messenge RNA (mRNA) and non-coding RNA [ncRNA: ibosomal RNA ( RNA), ans e RNA ( RNA), and o he ncRNAs], ep esen s he en i e se o ibonucleic acid (RNA) ansc ip s in a pa icula cell ype o issue a a ce ain de elopmen al s age and/o unde a speci ic physiological en i onmen (13;14). Consequen ly, ansc ip omic analyses a e an e ec i e me hod o link he ela ionship be ween geno ype and pheno ype (15). The applica ion o ansc ip omic app oaches allows no only o quan i y changes in exp ession le el o each gene, bu also o map, anno a e, and de e mine he unc ional s uc u e o each gene in he genome (16;17). Howe e , he complexi y o s udying he ansc ip ome has led o he need o he de elopmen and ad ancemen o new and mo e e ec i e high- h oughpu me hods. O e he las decades, se e al echnologies ha e been de eloped o s udy ansc ip omes. 2.1.1 A b ie his o y O e he las 60 yea s, sequencing echnologies ha e ad anced signi ican ly. I began wi h he ad en o i s -gene a ion sequencing, hen led o nex -gene a ion sequencing (NGS), and ad anced u he in o he domain o hi d-gene a ion sequencing echnologies (Figu e 1) (18). The disco e y o deoxy ibonucleic acid’s (DNA) double helix s uc u e, in 1953 by Wa son and C ick (19), se ed as he ounda ion o a new ield o s udy ha ocuses on he molecula biology o he cell (20;21). Building upon his ounda ional knowledge, in 1975, Sange sequencing, a low- h oughpu me hod, was eleased (22). The i s -gene a ion 4 sequencing echnology, also e e ed o as Sange sequencing o dideoxy chain- e mina ion sequencing, has been used o single-s anded DNA sequencing (DNA-Seq) (23) and i has been employed in di e se ields wi h an accu acy o a ound 99.99% (24). Sange sequencing emains use ul, due o i s p ac ical applica ions and has become a ’gold s anda d’ me hod (25;26), encou aging scien is s o s udy genomic code in li ing o ganisms (27). Al hough o he sequencing me hods eme ged a ound he same ime (e.g. Maxam and Gilbe in 1977 (28)), none we e able o exceed Sange sequencing. In he same yea , Sange was capable o sequencing he i s genome, bac e iophage ϕX 174, which is 5375 bases in leng h (29). In subsequen yea s, F ede ick Sange ’s esea ch g oup conduc ed he comple ion o a ious genome sequences (30). The in oduc ion o he comple e Human Genome P ojec (HGP) was a big s ep in he ield o genomics (31). I was epo ed in 1990, and o o e a decade, i was de eloped a g ea cos and wi h in ense human e o (29). The goal o HGP was o map and sequence he en i e human genome (32). Sange sequencing played a signi ican ole in his p ojec , leading o he iden i ica ion o housands o genes (33). As he HGP p oceeded, i became clea ha o imp o e gene ic analysis and ha e quick access o ools o e alua e gene exp ession da a (34), he e was a need o as e , g ea e h oughpu and cheape echnologies (35). This led o he de elopmen o DNA mic oa ays in he la e 1990s (36). One o he majo applica ions o DNA mic oa ays is o measu e gene exp ession le els (35). DNA mic oa ays use housands o nucleic acid sequences a ached o a su ace o assess he ela i e concen a ion o nucleic acid sequences in a mix u e by hyb idiza ion and subsequen de ec ion o he hyb idiza ion e en s (37). This echnology allowed esea che s o simul aneously analyze he exp ession o housands o genes in a single expe imen (38). The comple ion o he i s human genome was only he beginning o he mode n DNA sequencing e a, which esul ed in u he in en ion and imp o ed de elopmen owa ds new ad anced high- h oughpu DNA sequencing s a egies known as ”high- h oughpu nex -gene a ion sequencing” (HT- NGS o simply NGS) (39). In he 2000s, NGS echnologies ma ked a e olu iona y ad ancemen in genomics and ansc ip omics (40). NGS p o ided a high- h oughpu , cos -e ec i e way o sequence en i e genomes and ansc ip omes (41). RNA Sequencing was one o he mos signi ican ly ad anced app oaches led by NGS. The e o e, i opened up new app oaches o s udying gene exp ession, al e na i e splicing, and non-coding RNAs wi h unp eceden ed de ail. Nowadays, his echnology is widely used as esea che s can comp ehensi ely analyze he ansc ip ome. While bo h RNA-Seq and mic oa ays ha e hei me i s and may be chosen based on speci ic esea ch goals, he lexibili y, sensi i i y, and abili y o unco e p e iously unknown aspec s o he ansc ip ome ha e posi ioned RNA-Seq as he p e e ed choice o many ansc ip omics s udies in he 21s cen u y (16;42). This echnology has played an impo an ole in ad ancing he 5 (100). The gene a ion o a sequencing lib a y o RNA-Seq analysis is a complica ed and mul i- s ep p ocedu e ha can esul in subs an ial a iance (104). Ribosomal RNA is e y abundan and mus be emo ed om o al RNA be o e sequencing o enable e ec i e ansc ip /gene iden- i ica ion. S anda d me hods including poly-A- ailed mRNA selec ion (PA) o RNA deple ion (RD) a e commonly used o sol e his issue (Figu e 3) (105). Mi ochond ial RNA selec ion is use ul o analyzing gene exp ession a he mRNA le el because i selec s polyadenyla ed mRNA molecules (106). Ribosomal RNA deple ion elimina es RNA molecules and is used o en ich a wide spec um o RNA species o he han mRNA and educe sequencing cos s (107). Nex -gene a ion sequencing o cDNA enables quali a i e and quan i a i e ansc ip ome s udies. I may also be used o iden i y new genes mo e p ecisely, cha ac e ize al e na i e splicing o usion ansc ip s, and de ec RNA edi s and mu a ions (13). Figu e 3: RNA-Seq sample p epa a ion wo k low. Adap ed om Pease e al. (2010). 2. Compu a ional Biology • Quali y con ol o sequence eads As p e iously s a ed, high- h oughpu sequence s may c ea e massi e olumes o da a in a sin- gle un. Be o e s udying he collec ed sequences, i is necessa y o assess lib a y quali y and sequencing pe o mance. As a esul , he low-quali y bases mus be elimina ed p io o any align- men o assembly o he eads. Base calling on any o he egula ly used NGS pla o ms migh be 12 hampe ed by low-quali y s a ing ma e ial, chemical mis akes, o ins umen laws. Quali y Con ol (QC) ypically conside s duplica ion a e, as mos sequences a e expec ed o occu only once when he uni e se is la ge han he sample size (108); RNA abundance, which should be low; s and speci ici y, de ined as he numbe o eads mapping o known ansc ibed egions a he expec ed s and; co e age con inui y a anno a ed ansc ip s, and pe o mance a 5’ and 3’ ends, de ined as ag eemen wi h known end anno a ion (109). • Mapping eads A e il e ing he eads om he aw cDNA sequence eads, he sho -sequenced eads mus be mapped o a e e ence genome (genome mapping) o ansc ip ome ( ansc ip ome mapping), de- pending on he a ailabili y (110). As a esul , he p ima y pu pose o his s ep is o ind he loca ions whe e each ead occu s on a speci ic e e ence (111). Mapping he eads o he e e ence da a can be di icul since millions o small eads mus be mapped o genomes ha a e o en qui e big. This means ha mapping me hods mus be ex emely e icien in e ms o Cen al P ocessing Uni (CPU) and memo y use (112). Fu he mo e, because epea ed sequences accoun o mo e han 50% o he genome in complex species (113), mapping echniques mus be capable o handling nume - ous mapping si es. Read alignmen agains he genome is slowe han agains he ansc ip ome because i mus accoun o all non-coding loca ions (Figu e 4) (114). Va ious alignmen p og ams ha can do spliced alignmen s, including TopHa 2 (115), SOAPSplice (116), and Bla (117). Align- e s such as Bow ie 2 (118), BWA (119), and o he s, on he o he hand, specialize in he alignmen o sho eads o a e e ence. Figu e 4: Mapping o a pai ed-end ead wi h di e en e e ence iles: genome and ansc ip ome. On he le , i ep esen s an alignmen o a pai ed-end ead o he genome. The ead needs o be mapped ac oss in ons (spliced alignmen ). On he igh , an alignmen o a pai ed-end ead o he ansc ip ome. Adap ed om Deshpande e al. (2023). 13 Resea che s o en use a mapping echnique o analyze ansc ip ome da a o species wi h known e e ence genomes. Howe e , his echnique is ine ec i e when he e e ence sequence is una ail- able o incomple e (120). Thus, a de no o assembly is equi ed o gi e a easible app oach o ansc ip ome analysis in species wi h unsequenced genomes (121). I is equi ed when a high- quali y e e ence genome is una ailable, such as o many non-model species, when analyzing complex mic obial communi ies, in me a ansc ip ome in es iga ions, o when examining uncul u - able mic oo ganisms (122). The use o de no o assembly o sho sequence eads in o ansc ip s, allows esea che s o ebuild he sequences o he whole ansc ip ome, iden i y and ca alog all exp essed genes, di e en ia e iso o ms, and cap u e ansc ip exp ession le els (123). The ou pu ile o he e e enced mappe s is in Sequence Alignmen /Map (SAM) o ma and p o ides in o ma ion abou bo h aligned and non-aligned eads (124). This ile p o ides in o ma ion on he genomic po ion whe e he ead was mapped and i s espec i e sco e o aligned eads (125). • Exp ession quan i ica ion and no maliza ion Following he mapping o RNA-Seq eads, he da a mus be ans o med in o a quan i a i e measu e o gene exp ession (126). Fo eads ha we e mapped o he ansc ip ome, he easies solu ion is o add he numbe o eadings ha all wi hin he coo dina es o each elemen (127). On he o he hand, o eads ha we e aligned o he genome, he measu emen s o gene exp ession mus be pe o med by HTSeq package (128). I also equi es no maliza ion o each sequencing un o elim- ina e he po en ial genes ha seem o be di e en ially exp essed. The eads pe kilobase me hod is one me hod o no malizing RNA-Seq da a (129). The ansc ip pe million mapped (RPKM) measu e no malizes a ansc ip ’s ead by bo h i s leng h and i s size as well as he o e all amoun o mapped eads in he sample (100). Likewise, he agmen s pe kilobase o he ansc ip s pe million mapped (FPKM) s a is ic is used o no malize pai ed-end da a and i ob ains es ima es o meaning ul exp essions (130). 3. Sys ems Biology Once he eads ha e been aligned o assembled, esea che s ace a as amoun o da a gene a ed h ough high- h oughpu echniques. This is whe e di e en ial gene exp ession (DGE) analysis can be applied. Di e en ial gene exp ession analysis is a compu a ional s a egy ha aims o measu e and disco e genes whose exp ession le els change signi ican ly be ween wo o mo e expe imen al condi ions (131). This s udy assis s esea che s in iden i ying genes ha a e up egula ed o down- 14 egula ed unde ce ain condi ions, o e ing i al insigh s in o biological p ocesses, disease causes, o he apeu ic esponses (132). Figu e 5: RNA-Seq wo k low. Adap ed om Han e al.(2015), EMBL e al.(2022). 2.2.2 Applica ions o RNA-Seq da a T ansc ip omics has applica ions in a wide ange o scien i ic ields, om undamen al esea ch o medicine and bio echnology (133). As he knowledge o ansc ip omics g ows, p iceless new in o ma ion on he complex molecula p ocesses eme ges. • Diagnos ics and disease p o iling In he pas yea s, ansc ip omics has g adually eme ged as a use ul ool o a e disease diag- nosis and disco e y (134). T ansc ip ional s a si es ha e been ex ensi ely ound using RNA-Seq me hods (135). Gene usions, allele-speci ic exp ession, and disease- ela ed Single Nucleo ide Poly- mo phisms (SNP) can be de ec ed using RNA-Seq (136). Since hese egula o y componen s ha e a key ole in human illness, he iden i ica ion o hese polymo phisms is c ucial o he in e p e a ion o disease associa ion s udies. In he con ex o cance , i pe mi s he de ec ion and ca ego iza- ion o dis inc cance ypes based on gene exp ession pa e ns (137;138). In addi ion o cance , ansc ip omics is use ul in disease sub yping. Diabe es and Alzheime ’s a e equen ly he e oge- neous diseases wi h se e al molecula sub ypes (139). T ansc ip ome analysis has been widely 15 employed o analyze umou he e ogenei y, ca ego izing umou s in o molecula subg oups, and de eloping signa u es ha p edic he apeu ic esponse and pa ien ou comes (140). Fu he mo e, ansc ip omics is a he o e on o bioma ke disco e y, cons an ly e ealing new ma ke s ha migh inc ease diagnos ic accu acy and p ognosis p edic ion (141). • Responses o en i onmen T ansc ip omics ep esen s an e ec i e me hod o s udying how o ganisms espond o en i on- men al changes and s esses (142). High- h oughpu echnologies allow moni o ing eac ions in minu e de ail, exposing he genes and pa hways ha allow adap abili y and su i al (143). S udying he en i e mRNA e lec s ac i ely exp essed genes in a cell, and consequen ly p o ides answe s on how o espond o changes in he ex e nal en i onmen (144). Signi ican e o has been di ec ed owa ds cha ac e izing shi s in mRNA abundance igge ed by changes in key en i onmen al a i- ables such as empe a u e (145), salini y (146), oxygen (147), and pH (148). T ansc ip omics has been u ilized e ec i ely in he ield o en i onmen al physiology o add ess a wide a ie y o conce ns in ol ing how o i o ganisms can acclima ize o adap o he abio ic ci cums ances associa ed wi h li ing in dis inc en i onmen s (149). Fo example, ansc ip omics helps clima e change s udies by exposing how changing gene exp ession impac s ecosys ems and species. This knowledge is c i i- cal o conse a ion e o s and echniques ha aid species in adap ing o changing en i onmen al condi ions (150). • Human and pa hogen ansc ip omes T ansc ip omics is an e ec i e echnique o s udying hos and pa hogen mechanisms in in ec ious illnesses (151). RNA-Seq o human pa hogens is a p o en me hod o analyzing gene exp ession a ia ions, inding no el i ulence ac o s, p edic ing d ug esis ance, and exposing hos -pa hogen immunological in e ac ions (152;153;154). Dual RNA-Seq has ecen ly been u ilized o cha - ac e ize he RNA exp ession in he pa hogen and hos h oughou he in ec ion p ocess (155). Resea che s may use hese me hods o unde s and how i uses a ack hos cellula machine y, exposing he s a egies pa hogens use o escape he immune sys em and es ablish in ec ion. This unde s anding is c i ical o c ea ing medicines ha dis up hese e o s. • Gene disco e y and anno a ion The c ea ion o la ge-scale ansc ip ome da a, such as RNA-Seq, is he i s s ep owa ds gene disco e y (156). T ansc ip omics o e s he po en ial o disco e new genes, including p e iously 16 undisco e ed o poo ly cha ac e ized genes (157). T ansc ip omics is c ucial in he p ocess o gene anno a ion because i p o ides da a on gene exp ession pa e ns and iso o ms, which can be u ilized o in e hei unc ions and egula o y oles (97). Compa a i e analysis acili a es unc ional ca ego iza ion o genes, allowing genes o be classi ied based on hei oles in biological p ocesses and ac i i ies (158). T ansc ip omic da a may also be used o map genes on o es ablished biological pa hways, o e ing in o ma ion on hei pa icipa ion in ce ain cellula p ocesses and signalling cascades. Fu he mo e, gene anno a ion con ibu es o a be e knowledge o gene egula ion (159). • Non-coding RNA The impo ance o ncRNAs in gene egula ion and hei unc ions in nume ous biological p ocesses and diso de s has been highligh ed h ough ansc ip omics (160). Mic oRNAs a e sho ncRNAs ha play an impo an ole in pos - ansc ip ional egula ion (161). T ansc ip omic in es iga ions aid in he iden i ica ion o pa icula mic oRNA a ge genes, e ealing in o ma ion on hei oles in p ocesses like de elopmen , immunology, and cance (162). Long non-coding RNAs (lncRNAs) a e ano he ype o non-coding RNA ha has been widely explo ed using ansc ip omics (163). They ha e a ole in gene egula ion and ha e been linked o a a ie y o illnesses (164). 2.2.3 Di e en ial gene exp ession analysis One o he mos common uses o RNA-Seq da a is DGE analysis. This echnique is used in a ious RNA-Seq da a p ocessing applica ions, enabling he iden i ica ion o genes ha a e di e en ially exp essed be ween wo o mo e condi ions (165). The ob ained da a om RNA-Seq echnology is submi ed o s a is ical and bioin o ma ics me hods o igo ously in e p e ing he as amoun o da a gene a ed h ough high- h oughpu echniques o iden i y di e en ially exp essed genes (166). Di e en so wa e o DGE analysis apply dis inc app oaches o no malizing da a, and hei pe o mance a ies depending on he ype o expe imen al da a and he numbe o sample eplica es (167). Speci ic ools ha e been de eloped o de e mine which genes a e di e en ially exp essed. Table 1 shows se e al so wa e o DGE analysis, wi h he di e en no maliza ions used, ead coun dis ibu ion, and di e en ial exp ession le els. The mos common and e icien used s a is ical packages a e EdgeR, DESeq2, and Limma (168). edgeR (169) uses empi ical Bayes es ima ion and p ecise es ing based on a nega i e binomial model o de e mine di e en ial exp ession. The so wa e was c ea ed o analyze ials wi h a minimal numbe o duplica es. An empi ical Bayes app oach, in pa icula , is u ilized o educe he deg ee o o e dispe sion among genes by bo owing in o ma ion among genes. To measu e di e en ial exp ession o each gene, 17 an exac es simila o Fishe ’s exac es bu ailo ed o o e dispe sed da a is u ilized. The T immed Mean o M- alues (TMM) no maliza ion app oach is employed by de aul o accoun o di e ences in sequencing dep hs be ween samples, whils he Benjamini-Hochbe g p ocedu e is u ilized o egula e he alse disco e y a e (FDR) (170). DESeq2 (171) employs a Wald es o signi icance es ing: he sh unken es ima e o Log old change (logFC) is di ided by i s s anda d e o , yielding a z-s a is ic ha is compa ed o a con en ional no mal dis ibu ion. The Wald es allows he assessmen o indi idual coe icien s o con as s o coe icien s wi hou ha ing o build a simpli ied model like he likelihood a io es , bu he likelihood a io es is s ill an op ion in DESeq2. The Wald es P alues om he subse o genes ha pass an independen il e ing s ep a e co ec ed o mul iple es ing using he Benjamini-Hochbe g (BH) app oach. DESeq and edgeR pe o m simila ly in di e en ially exp essed, howe e , DESeq has been p o en o ha e mo e conse a i e FDRs, compa ed o EdgeR (131). Limma (172) is p edica ed on linea modelling. I was c ea ed o analyze mic oa ay da a, bu i has also ecen ly been expanded o RNA-Seq da a. Acco ding o he Limma use guide, he cu en ecommenda ion is o use he edgeR package’s TMM no maliza ion and he so-called ’ oom’-con e sion, which essen ially ans o ms he no malized coun s o loga i hmic (base 2) scale and es ima es hei mean- a iance ela ionship o assign a weigh o each obse a ion be o e linea modelling (173). The Benjamini-Hochbe g echnique is employed by de aul o es ima e he FDR (170). As a inal s ep, he di e en ially exp essed genes esul ing om he s a is ical es ing may be classi ied in o common pa hways. This app oach inds di e en ially ac i e pa hways and, e en ually, he possibili y o linking molecula in o ma ion ( ansc ip ome) wi h an o ganism’s pheno ype (ac i e pa hways) (179). The app oaches used o analyze he beha io o di e en ially exp essed genes and conca ena e hem in o cellula pa hways make use o pa hway in o ma ion accessible in public sou ces such as he Gene On ol- ogy (GO) (180) o he Kyo o Encyclopaedia o Genes and Genomes (KEGG) (181). This is accomplished by associa ing pa hway in o ma ion in hese da abases wi h gene exp ession pa e ns, esul ing in he ans o ma ion o a lis o indi idual genes in o a collec ion o pa hways. 18 Table 1: So wa e packages mos ly used o iden i y gene exp ession. Me hod No maliza ion Read coun dis ibu ion Di e en ial exp ession es Re e ence edgeR TMM/Uppe qua ile/ RLE (DESeq-like)/None Nega i e binomial dis ibu ion Exac es (169) DESeq DESeq sizeFac o s Nega i e binomial dis ibu ion Exac es (174) baySeq Scaling ac o s (quan ile/TMM/ o al) Nega i e binomial dis ibu ion Assesses he pos e io p obabili ies ia empi ical Bayesian (175) SAMseq (sam ) SAMseq Nonpa ame ic me hod Wilcoxon ank s a is ic and a esampling s a egy (176) Limma TMM oom ans o ma ion o coun s Empi ical Bayes me hod (172) Cu di 2 (Cu links) Geome ic (DESeq-like/qua ile /classic- pkm) Be a nega i e binomial dis ibu ion - es (177) EBSeq DESeq median no maliza ion Nega i e binomial dis ibu ion E alua es he pos e io p obabili y ia empi ical Bayesian me hods (178) 19 2.3 F eshwa e mussels as a model o ganism Molluscs cons i u e one o he ancien and mos di e se g oups o in e eb a es, wi h o e 90,000 de- sc ibed species. I is es ima ed ha 50.000 o 55.000 a e ma ine, 25.000 o 30.000 e es ial, and 6.000 o 7.000 eshwa e species (182). Bi al ia is he second mos di e se class o Mollusca a e Gas opoda, wi h a ound 20,000 species (183). A g ea pa o hem - clams, oys e s, scallops, and mussels - a e a i al sou ce o ood and aw ma e ials (pea ls and nac e, o example) o humans, and ha e a signi ican economic alue (184). O a o al o 1209 known species o eshwa e bi al es, 1178 in eg a e a single o de (i.e., Unionida) di ided in o eigh amilies: Unionidae , Ma ga i i e idae , Hy iidae , Myce opodidae , I idinidae , E he iidae (all Unionida), Sphae iidae and Cy enidae (bo h Vene ida) (185). F eshwa e mussels, om he o de Unionida, a e dis ibu ed all o e he globe (excep An a c ica), inhabi ing i e s, lakes, and e en a i icial s uc u es (e.g., channels) (186). Figu e 6: Unio delphinus in he Sabo Ri e (Po ugal). Pho o c edi : Ronaldo Sousa. Besides he economic alue and se ices p o ided o humans, hese animals a e esponsible o impo an ecosys em unc ions (187). Heal hy mussel beds a e essen ial in eshwa e ecosys ems, as hey a e impo an il e eede s, capable o emo ing pa icles om he wa e column o he ben hos, being in his way esponsible o wa e pu i ica ion (188;187). F eshwa e mussels ac i ely pa icipa e in he p ocess o nu ien cycling, inc easing wa e quali y and po en ially pa icipa ing in he nu ien educ ion p ocess (2;3). Fu he mo e, hey a e an impo an g oup o ecosys em enginee s, p o iding habi a o o he o ganisms and suppo o ood webs (4). F eshwa e mussels can ac as c ucial biomoni o s o en i onmen al change, p o iding in o ma ion abou his o ical (using shells, o example) and cu en condi ions and keeping ack o impending changes in wa e quali y (189;190). 20 Addi ionally, eshwa e mussels a e ascina ing because o hei unique li e cycle. F eshwa e mussel’s li e cycle inco po a es pa en al ca e and la al pa asi ism (Figu e 7). The pa asi ic s age is a unique cha ac e is ic o eshwa e mussels ha dis inguishes hem om all o he g oups o bi al es (191). Thei li e cycle includes a ee-li ing adul and a sho - e m la al s age called glochidium (192). Glochidia a e obliga e pa asi es p esen on he gills o ins o ish (and a ely o he e eb a es)(193). The in e ac ion be ween he eshwa e mussel and hei ish hos s hei impo an o he mussel popula ion, mos ly because o glochidia’s educed li espan and i s limi ed dispe sal capaci y. Howe e , hese in e ac ions can also con ibu e o he eshwa e mussels’ poo conse a ion s a us, as hei complica ed li e cycle makes hem pa icula ly ulne able o changing en i onmen al condi ions (191). Figu e 7: Scheme o eshwa e mussel’s li e cycle. Adap ed om Modes o e al. (2018) . Unio delphinus is endemic o he Ibe ian Peninsula and is p esen in a wide di e si y o habi a s, om small o la ge i e s, subjec ed o a g ea a ie y o ecological condi ions, anging om oligo ophic wa e s o semia id and mo e eu ophic s eams (194). The genus Unio is pa o he bigges eshwa e mussel amily (i.e., Unionidae), which comp ises 674 ou o 840 species (195). Unio delphinus is one o he species inside his amily and i s dis ibu ion comp ises all majo A lan ic Ibe ian Ri e basins. Fu he mo e, mos eshwa e mussel species a e dec easing a a ca as ophic a e wo ldwide. O e he las 30 yea s, eshwa e biodi e si y has dec eased as e han in e es ial o ma ine ecosys ems 21 Chap e 3 Me hodologies 3.1 B ie o e iew The wo k de eloped in his mas e ’s hesis is pa o he p ojec : EdgeOmics - F eshwa e Bi al es a he edge: Adap a ion genomics unde clima e-change scena ios (h p://doi.o g/10.54499/PTDC/ CTA-AMB/3065/2020). Hence, p e ious wo k was done p io o he beginning o he hesis, which includes animal sampling, ecological expe imen s, RNA ex ac ion, and sequencing. 3.1.1 Sampling and labo a o y acclima iza ion A o al o o y indi iduals o U. delphinus we e collec ed in June 2022. Twen y indi iduals om he Rabaçal Ri e , No h o Po ugal, and wen y indi iduals om he same species om he Guadiana Ri e , Sou h o Po ugal. Indi iduals we e anspo ed ali e o he Uni e si y o Minho (Ecology Labo a o y in IB-S - Ins i u e o Science and Inno a ion o Bio-Sus ainabili y o he Uni e si y o Minho) whe e he ecological expe imen s we e conduc ed. A he lab, mussels we e placed in anks (20cm/30cm) o acclima iza ion o a a ge empe a u e o 15ºC. Fo ha , he ini ial empe a u e o each ank was inc eased o dec eased by abou ∼2.5◦C d−1un il he a ge empe a u e was eached. A e his, indi iduals we e main ained a he acclima ized empe a u e o wo weeks, being ed daily wi h a solu ion o Chlo ella (phy oplank on species). 3.1.2 Ecological Expe imen Two di e en ypes o empe a u e exposu e expe imen s we e pe o med: acu e and ch onic (Figu e 9 and 10, espec i ely). Fo he acu e expe imen , a o al o en indi iduals, i e om he No he n popula ion and i e om he Sou he n popula ion we e used. The acu e expe imen consis ed o a C i ical he mal maxima me hodology 28 (CTM) expe imen , whe e 35ºC was es ablished as he maximum empe a u e. B ie ly, s a ing a he acclima ed empe a u e, indi iduals we e subjec ed o a apid p og essi e empe a u e inc emen (0,3 ºC/min) un il ei he he a ge empe a u e was eached o indi iduals exhibi ed ex eme gaping beha io (i.e., adduc o muscles elaxed, man le edges and syphons spli , and he oo becomes pa ially o ully ex ended (256)). When ei he o hese condi ions was eached, he expe imen was inished, and gill issue samples we e collec ed and s o ed in RNAla e S abiliza ion Solu ion (The moFishe ) a 4ºC o 24h and hen placed a -80ºC. Figu e 9: Unio delphinus used in he acu e expe imen s. The ch onic expe imen s las ed o wo weeks and in ol ed a o al o hi y indi iduals, i een o each popula ion. As men ioned, he indi iduals s a ed a he acclima iza ion empe a u e and subsequen ly, he empe a u e was g adually inc eased ∼1◦C d−1un il i eached 30ºC. Du ing his pe iod o g adual inc ease in empe a u e, h ee dis inc sampling s ages we e de ined, i.e. 20ºC, 25ºC, and 30ºC. A each empe a u e ea men , i e indi iduals om each popula ion we e collec ed, gill issues sampled, and placed in RNAla e as desc ibed abo e. All he issues we e s o ed a 80ºC, a CIIMAR (In e disciplina y Cen e o Ma ine and En i onmen al Resea ch). Figu e 10: Unio delphinus used in ch onic expe imen s. 29 3.1.3 RNA ex ac ion and NGS sequencing To al RNA was ex ac ed om he gill o all he sampled indi iduals, om each expe imen , om he wo popula ions (No h and Sou h) using he NZYTech o al RNA isola ion ki . RNA concen a ion (ng/µl) and quali y measu emen s (OD260/280 a io alues) we e ob ained using a DeNo ix DS-11 Se ies Spec opho ome e /Fluo ome e . Due o he pai ed-end eads used in he p esen wo k, he ex ac ed o al RNA om he ou een samples was sen o Mac ogen, Inc. o build s and-speci ic lib a ies. The inse size was 250–300bp, and sequenced using 150bp pai ed-end eads on he Illumina HiSeq 4000 pla o m. 3.2 Bioin o ma ics A diag am illus a ing he pipeline used in his wo k is ep esen ed in Figu e 11. The me hods o qual- i y con ol, alignmen , and measu emen o he le el o gene exp ession we e ca ied ou using a high- pe o mance clus e a CIIMAR. The code de eloped in hese asks co esponds o a se ies o commands execu ed wi hin a Singula i y con aine en i onmen . Singula i y is a con aine iza ion ool ha allows he package and un applica ions and hei dependencies in isola ed en i onmen s. Figu e 11: Bioin o ma ic me hodological o e iew: ligh blue boxes ep esen he inpu /ou pu iles, da k blue boxes ep esen asks and ools o pe o m he analysis and g een boxes ep esen he sou ces iles. 30 3.2.1 P ocessing aw da a Raw sequencing eads unde wen a ho ough comp ehensi e quali y assessmen using FASTQC so wa e wi h he de aul pa ame e s ( e sion 0.11.8, h p://www.bioin o ma ics.bab aham.ac.uk/ p ojec s/ as qc/). This so wa e sys ema ically e alua es a ious aspec s o sequencing da a, including base quali y sco es, sequence leng h dis ibu ion, guanine-cy osine con en (GC-con en ), and he p esence o po en ial sequencing a e ac s. Following he ini ial quali y assessmen , an addi ional p ep ocessing s ep was applied o imp o e he o e all quali y o he eads. Poo -quali y bases, ela ed o sequencing e o s o echnical issues, we e emo ed om he aw eads using T immoma ic, wi h he PE - h eads 28 -ph ed33 pa ame e s ( e sion 0.38). T immoma ic employs a ange o quali y il e s and imming pa ame e s o enhance he accu acy and eliabili y o he sequence da a by elimina ing low- quali y egions (257). A e imming he eads, FASTQC was applied again. The ou pu o each FASTQC un is a se o HTML o ma epo s o each sample. 3.3 Mapping Reads The il e ed U. delphinus eads we e mapped o he U. delphinus e e ence genome assembly (a ailable a NCBI unde accession numbe GCA_029339505.1) (232) using he so wa e HISAT2 wi h he pa ame e s –d a -q -p 30 -x ( e sion 2.2.1). HISAT2 ep esen s a as and sensi i e alignmen ool o mapping NGS eads o a e e ence genome. P e iously, be o e ini ia ing he mapping p ocess, he e e ence anno a ion ile was con e ed in o a Gene al Fea u e Fo ma (GTF). This con e sion was ca ied ou using he so wa e AGAT, employing he sc ip aga _con e _sp_gx 2gx .pl o seamless ile o ma ansi ion ( e sion 1.0.0) and indexed wi h he so wa e HISAT2 wi h he de aul pa ame e s ( e sion 2.2.1). Con e ing he e e ence genome ile o ma o GTF has se e al ad an ages, including a mo e compac ep esen a ion and a clea e illus a ion o he hie a chical link be ween genes, ansc ip s, and exons. This o ma is mo e sui able o bioin o ma ics analysis and ools. A e he ile con e sion, ou commands we e pe o med, wo o gene a ing he ex ac ed splice si es ile, ano he one o he exons ile, and a las command o pe o m HISAT2-build. Fo he i s wo commands, he gene anno a ion ile o U. delphinus was used. To pe o m he indexing, HISAT2-build was used wi h he pa ame e s -p 30 –ss –exon ( e sion 2.2.1). HISAT2-build cons uc s an HISAT2 index using he ex ac ed splice si es and he exons iles om he se o DNA sequences in he e e ence ile. The ou pu o he HISAT2-build is a summa y ile (summa y. x ) ha con ains in o ma ion abou he genome index. This ile p o ides s a is ics and de ails abou he index, such as he o al numbe o sequences and 31 o al sequence leng h. These iles a e essen ial o he HISAT2 alignmen p ocess, and hey collec i ely p o ide a comp ehensi e index o he e e ence genome o ansc ip ome. Once he index is buil , he o iginal sequence FASTA ile is no longe used by Hisa 2. The ou pu o HISAT2 is one bam ile o each se o pai ed-end ead iles. 3.3.1 Exp ession quan i ica ion Following RNA-Seq ead alignmen , he da a was quan i ied using he so wa e S ing ie wi h he pa ame e s -e -B -p 30 -G ( e sion 2.1.2) and p epDE.py o ge he ead coun s pe gene. S ingTie is a so wa e ool o assembling ansc ip s and quan i ying gene and iso o m exp ession om RNA-Seq da a. I assembles aligned eads (o en in BAM o ma ) in o ansc ip s o gene models. I measu es he le els o exp ession o a ious ansc ip s, e ealing how much each ansc ip is exp essed in di e en samples o si ua ions. p epDE.py is a Py hon sc ip ha is equen ly used in conjunc ion wi h o he ools o p epa e da a o downs eam DGE analysis. I aids in he o ganiza ion o ou pu om ools such as S ingTie in o a o ma app op ia e o DGE. Wi h he gene anno a ion ile o U. delphinus i was possible o pe o m his ask. 3.4 Di e en ial exp ession Gene coun s p oduced by p epDE.py we e employed in he di e en ial exp ession analysis, which se es he pu pose o iden i ying genes ha exhibi di e en ial exp ession ac oss he s udy condi ions. To ca y ou his analysis, i was used wo dis inc me hodologies: one in ol ed he use o an online ool, DEApp, while he o he en ailed he de elopmen o code in he R/Bioconduc o package. 3.4.1 DEApp Th ee me hods a ailable in DEApp we e used: edgeR, limma- oom, and DESeq2 (h ps://gi hub. com/yan-c i/DEApp). In he ’DE Analysis Fil e ing C i e ia’ pa ame e s o he so wa e, i was se FDR adjus ed p- alue, wi h he alues 0.05 and 1.5 o p- alue o FDR adjus ed p- alue and Fold Change, espec i ely. This so wa e p o es i s u ili y by enabling he compa ison o wo condi ions using a speci ic me hod o he simul aneous compa ison o wo condi ions using wo o h ee me hods. This so wa e enables he isualiza ion o he ou pu h ough g aphic ep esen a ions, such as an MDS plo , a olcano plo , a een diag am, and a lis o genes ha a e di e en ially exp essed, i.e., up and down- egula ed. Since combining he h ee me hods has been shown o p oduce he mos compelling esul s (258;259), o his wo k, he lis o genes esul ing om he o e lap o he h ee me hods was used. The use o hese genes 32 can o e se e al bene i s such as obus ness and eliabili y. Each me hod is based on i s s a is ical model and assump ions and i is possible o c oss- alida e he esul s and lessen he isk o making conclusions based on assump ions ha may no hold o he indi idual da ase by employing a ious app oaches. The ou pu indings will be mo e eliable i all h ee app oaches ag ee on a g oup o di e en ially exp essed genes. Also, he use o he h ee me hods may educe alse posi i es and alse nega i es. By combining esul s om mul iple me hods, i is possible o educe he isk o alse posi i es and alse nega i es. Genes ha a e consis en ly iden i ied as di e en ially exp essed by mul iple me hods a e less likely o be alse disco e ies. 3.4.2 R/Bioconduc o package A code in a R/Bioconduc o package was de eloped o each me hod (edgeR ( e sion 3.40.2), limma- oom ( e sion 3.54.2), and DESeq2 (1.38.2)). De eloping code o e s he capabili y o compa e wo o mo e condi ions a he same ime, a ea u e no possible h ough DEApp. This ea u e p o ides signi ican ad- an ages, especially in e ms o lexibili y and manipula ing mul iple condi ions a he same ime, enabling a mo e comp ehensi e explo a ion o he da a. The sc ip ’s de elopmen p og essed h ough he subsequen s eps: •Read da a Two iles we e uploaded o he analysis: coun Da a and colDa a. The coun Da a ile consis s o a ma ix con aining gene exp ession alues o all genes and samples. On he o he hand, colDa a is a da a ame ha p o ides comp ehensi e in o ma ion abou he indi idual samples. This in o ma ion includes sample name o ID and condi ion o ea men . A DGE lis objec was c ea ed wi h he wo iles and calcula ed he Coun Pe Million (CPM) alues. •Da a p e-p ocessing Da a p e-p ocessing was pe o med, including il e ing ou low-coun genes and no malizing he da a. Two s eps o il e ing da a we e implemen ed. Fi s , a minimum CPM h eshold was se o one. Genes wi h CPM alues below his h eshold we e conside ed as lowly exp essed and excluded om u he analysis. The second s ep in ol ed a equi emen ha genes mus mee his CPM h eshold in a minimum numbe o samples o be e ained. This minimum sample h eshold, gTh eshold, was se o i e because each condi ion has i e samples. Genes ha did no mee he CPM h eshold in a leas i e samples we e excluded. Following he il e ing s ep, he da a was no malized o accoun o a ia ions in lib a y size and sequencing dep h ac oss samples. The TMM 33 no maliza ion me hod was employed o calcula e no maliza ion ac o s in he h ee me hods. This me hod is essen ial o making he da a di ec ly compa able and o enabling accu a e di e en ial exp ession analysis. •S a is ical Analysis This s ep in ol ed he iden i ica ion o di e en ially exp essed genes ac oss expe imen al condi ions o ea men s. Di e en ial gene exp ession analysis was pe o med using he R/Bioconduc o pack- ages EdgeR, Limma-Voom, and DESeq2. These packages o e obus s a is ical me hods. Fo he h ee me hods. The common s ep o each me hod was o c ea e a design ma ix. Nex , o EdgeR a gene alized linea model (GLM) app oach was applied o e alua e di e ences in gene exp essions be ween di e en condi ions. The glmFi unc ion was used o i ing he GLM o he da a. In limma, he oom unc ion was applied o he da a. This ans o ma ion is an in eg al pa o he Limma me hodology, as i con e s coun da a in o a o ma sui able o linea modeling. The nex s ep in ol es i ing linea models o he da a using he lmFi unc ion. These linea models ake in o accoun he design ma ix, p o iding a amewo k o unde s and he ela ionships be ween he samples and he de ined g oups. The con as s. i unc ion was applied o compu e he desi ed con as s, ollowed by empi ical Bayes mode a ion using he eBayes unc ion. Fo DESeq2 he ounda ion o he analysis begins wi h he c ea ion o a DESeqDa aSe ma ix. DESeq2 employs a nega i e binomial dis ibu ion model o accoun o he inhe en coun na u e o he da a. The DESeq unc ion was applied o he DESeqDa aSe , using he Wald es as he chosen me hod o hypo hesis es ing. •Mul iple Tes ing Co ec ion Mul iple es ing co ec ion is a c ucial conside a ion in any analysis in ol ing a high numbe o genes, helping o manage he educ ion o FDR. To con ol he FDR, bo h EdgeR and Limma employed he BH co ec ion me hod. In EdgeR, he opTags unc ion was u ilized wi h speci ic pa ame e se ings, including n = In , adjus . me hod = ”BH”, and so .by = ”none”. Addi ionally, o u he e ine he esul s, EdgeR applied h esholds o e aining genes wi h FDR < 0.05 and |log2FoldChange| ≥ 1.00. Fo Limma, he opTable unc ion was employed wi h he ollowing pa ame e con igu a ions: numbe =In , adjus =”BH”, and ‘so .by=”none”. These se ings ensu ed ha he FDR was e ec- i ely con olled, and he mos signi ican esul s we e epo ed o u he analysis. In Limma, a simila il e ing app oach was implemen ed as EdgeR wi h he same pa ame e s. In DESeq2, he p- alues ob ained by he Wald es a e co ec ed o mul iple es ing using he BH me hod by de aul . 34 •O e lap be ween me hods A e ge ing he lis o genes ha we e di e en ially exp essed o each me hod, simila o he DEApp analysis, an o e lap o he h ee lis s was pe o med o ha e a inal lis wi h he genes ha we e common o he h ee me hods. Fo he o e lap, i was se he alues o logFC and padj o he me hod limma. 3.4.3 Compa a i e Analysis Table 2 ep esen s he compa a i e analysis conduc ed in ch onic and acu e expe imen s using bo h DEApp and R code. All he compa isons in he able we e ep oduced using he code in R, bu only i e: No h 20 ºC s Sou h 20 ºC, No h 25 ºC s Sou h 25 ºC, No h 30 ºC s Sou h 30 ºC, No h s Sou h (ch onic and acu e) we e ep oduced wi h DEApp. The wo compa a i e analyses ep esen ed in he able in blue we e de eloped exclusi ely wi h R code because hey use mo e han wo condi ions a he same ime and, hus a e no possible h ough DEApp. These compa a i e analyses, No h 20 ºC ∩25ºC ∩30ºC and Sou h 20 ºC ∩25ºC ∩30ºC, co espond o he in e sec ion o he wo indi idual compa isons o each popula ion (20 s 25 and 20 s 30) wi h he con ol o he empe a u e o 20 ºC. This analysis aims o unde s and how genes inc ease o dec ease in exp ession wi hin he popula ion. The ou pu o bo h, he so wa e DEApp and R/Bioconduc o package, is a able, which ep esen s each gene ha is di e en ially exp essed o he condi ion ha is being analyzed. Fo each gene, he ou pu able con ains in o ma ion abou he mean exp ession le el as a join es ima e om bo h condi ions and es ima ed sepa a ely o each condi ion, he old change om he i s o he second condi ion, he loga i hm ( o basis 2) o he FC, he p- alue o s a is ical signi icance o his change and he p- alue adjus ed wi h BH p ocedu e ha con ols he pe cen age o FDR. 35 Table 2: Compa a i e analysis conduc ed in ch onic and acu e expe imen s using bo h DEApp and R/Bio- conduc o package. The compa isons highligh ed in blue we e pe o med exclusi ely using he R/Biocon- duc o packages. Compa ison Desc ip ion Ch onic expe imen s No h 20 ºC s Sou h 20ºC Compa ison o gene exp ession be ween No h and Sou h popula ion a 20ºC. No h 25 ºC s Sou h 25 ºC Compa ison o gene exp ession be ween No h and Sou h popula ion a 25 ºC. No h 30 ºC s Sou h 30ºC Compa ison o gene exp ession be ween No h and Sou h popula ion a 30 ºC. No h s Sou h Global compa ison o gene exp ession be ween No h and Sou h popula ion. No h 20 ºC ∩25ºC ∩30ºC Compa ison o gene exp ession a di e en empe a u es wi hin he No h popula ion. Sou h 20ºC ∩25ºC ∩30ºC Compa ison o gene exp ession a di e en empe a u es wi hin he Sou h popula ion. Acu e expe imen s No h s Sou h Compa ison o gene exp ession be ween No h and Sou h popula ion. 36 3.5 En ichmen Analysis The unc ional en ichmen analysis was pe o med using g:P o ile ( e sion e110_eg57_p18_4b54a898) wi h g:GOS mul iple es ing co ec ion me hod applying a signi icance h eshold o 0.05 (260). Be o e in oducing he lis o genes in g:P o ile we pe o med a p o ein BLAST (BLASTP), wi h he pa ame e s -max_ a ge _seqs 1 -max_hsps 1 -e alue 1e-5, agains he e e ence p o eins om he genome o Homo sapiens since he genome o U. delphinus was no a ailable. A FASTA ile con aining he p o eins o Homo sapiens was downloaded om Ensembl. A e he BLAST, wo lis s we e used: up and down- egula ed gene ids o Homo sapiens ha esul ed om he BLAST. g:P o ile is a powe ul bioin o ma ic ool and web se e used o gene and p o ein se en ichmen analysis (260). I p esen s di e en ca ego ies depending on he aim, such as g:GOS , g:Con e , g:OR h and g:SNPense. Fo his wo k, g:GOS was used, which pe o ms unc ional p o iling, speci ying Homo sapiens (Human) as he model o ganism. The human genome is one o he mos ex ensi ely s udied and well-known genomes in genomics. In consequence, he human genome is well-anno a ed, meaning ha he loca ions and unc ions o many human genes ha e been iden i ied and cha ac e ized. The ca ego y used in his wo k maps genes o known unc ional in o ma ion sou ces and de ec s s a is ically signi i- can ly en iched e ms. g:P o ile suppo s a ious anno a ion da abases, including GO, KEGG pa hways, Reac ome, and many mo e. These da abases help in associa ing he inpu gene o p o ein lis wi h known biological unc ions and pa hways. g:P o ile employs s a is ical me hods o assess he en ichmen o inpu genes o p o eins in a ious biological ca ego ies. I calcula es p- alues and en ichmen sco es o de e mine he signi icance o he associa ions. g:P o ile gene a es epo s ha lis he en iched e ms, associa ed s a is ics, and isualiza ions. 37 Table 3: Alignmen a e o each ead sample o ch onic expe imen s agains he Unio delphinus e e ence genome. Samples we e named acco ding o wo a iables: popula ion and empe a u e. No h popula ion samples we e accessed wi h ”N” and sou h popula ions wi h ”S”, and nex o his i s le e wi h he empe a u e. In he case o ch onic expe imen s, i can be 20, 25, o 30. Following he empe a u e a e he eplica es, which a e i e pe condi ion, and a e ep esen ed by ”G1”, ”G2”, ”G3”, ”G4” and ”G5”. No h Samples Alignmen Ra e (%) Sou h Samples Alignmen Ra e (%) Con ol N20G1 91.36 S20G1 94.14 N20G2 93.07 S20G2 91.42 N20G3 92.26 S20G3 91.91 N20G4 91.67 S20G4 92.86 N20G5 94.60 S20G5 92.14 T ea men N25G1 94.02 S25G1 93.96 N25G2 94.29 S25G2 91.50 N25G3 92.50 S25G3 91.36 N25G4 93.88 S25G4 92.04 N25G5 95.32 S25G5 92.57 N30G1 93.43 S30G1 92.71 N30G2 94.43 S30G2 95.06 N30G3 93.50 S30G3 94.02 N30G4 94.19 S30G4 92.86 N30G5 94.13 S30G5 92.82 44 Table 4: Alignmen a es o each ead sample o acu e expe imen agains he Unio delphinus e e ence genome. Samples we e named acco ding o wo a iables: popula ion and empe a u e. No h popula ion samples we e accessed wi h ”N” and sou h popula ions wi h ”S”, and nex o his i s le e wi h he empe a u e. In he case o ch onic expe imen s, can be 20, 25, o 30. Following he empe a u e a e he eplica es, which a e i e pe condi ion, and a e ep esen ed by ”G1”, ”G2”, ”G3”, ”G4” and ”G5”. No h Samples Alignmen Ra es (%) Sou h Samples Alignmen Ra es (%) NG1 94.79 SG1 93.45 NG2 94.80 SG2 93.50 NG3 94.77 SG3 93.18 NG4 94.51 SG4 93.07 NG5 94.93 SG5 90.48 4.4 Di e en ial Exp ession - DEApp and R code Ganse e al. (2015) in es iga ed he e ec s o inc easing wa e empe a u es on he physiological p o- cesses o ou species o eshwa e mussels in No h Ame ica (208). This s udy is he only e e ence ha is cu en ly a ailable in he li e a u e on he cu en subjec , and as such, i p o ides a s anda d compa ison o he p esen wo k. In hei esea ch, mussels unde wen exposu e o ou dis inc empe a- u e ea men s—20 ºC, 25 ºC, 30 ºC, and 35 ºC—each eplica ed i e imes in a andomized app oach, wi h he 20 ºC ea men se ing as he baseline con ol. The p esen wo k’s labo a o y expe imen de- sign uses he same empe a u e condi ions as Ganse e al. (2015), p o iding a eliable and compa able me hodology. The wo in es iga ions employ he same empe a u es, bu he p esen wo k di e ges by ca - ego izing hem in o wo sepa a e expe imen s: ch onic and acu e. As desc ibed, he ch onic expe imen s las ed o wo weeks and employed g adually inc easing empe a u es,i.e., 20 ºC, 25 ºC, and 30 ºC, while he acu e expe imen s speci ically used a empe a u e o 35 ºC. This change allows a comp ehensi e explo a ion o he consequences o sho - e m e sus p olonged he mal s ess on eshwa e mussels, expanding he unde s anding o hei gene ic esponses o inc easing empe a u es caused by clima e change. Bo h expe imen s we e designed o ec ea e he e en s o hea wa es bu wi h di e en du a ions. The ch onic expe imen s we e conduc ed g adually o simula e he p og essi ely inc easing empe a u es, which means a p olonga ed ex eme e en , while he acu e expe imen s we e designed o eplica e he e ec s o a b ie e ex eme e en . The ollowing analyses explo ed in his sec ion we e p oduced sepa a ely o each expe imen . 45 The sou ce code de eloped in he R/Bioconduc o package p esen in his chap e is a ailable in he co esponding Gi Hub eposi o y: h ps://gi hub.com/bea izsil a16/DGE_Analysis. The eposi o y con ains all he g aphical ep esen a ions and he code associa ed. 4.4.1 Da a p e-p ocessing • Ch onic expe imen s The ini ial coun o eads was signi ican ly educed om 39,060 o 22,696. This educ ion in ead coun s e lec s he emo al o low-quali y o non- ele an da a, ensu ing he e en ion o high-quali y, in- o ma i e eads o he subsequen analyses. The boxplo (Figu e 16. A) and MDS plo (Figu e 16. B) shown in Figu e 16 e eal he p esence o he ’N20G4’ sample as an ou lie wi hin he No h popula ion a a empe a u e o 20 ºC. Ou lie s can dis o s a is ical measu emen s and may p o ide inco ec esul s. I was deemed necessa y o exclude he N20G4 sample om he subsequen analysis. Remo ing his ou lie p oduced a se ies o epe cussions. The no maliza ion h esholds we e adjus ed o he modi ied da ase , wi h a alue o 4 o accoun o he emaining samples in he impac ed condi ion. The isual ep esen a ions a e exclusion a e shown in Figu e 17. The c edibili y o he s udy indings is s eng hened by he ca e ul ea men and iden i ica ion o ou lie s, which gua an ees ha he analyses ha ollow a e based on a mo e accu a e and ep esen a i e da ase (261). • Acu e Expe imen s Fo he acu e expe imen s, he same p ocedu e was applied, and he ini ial coun eads we e educed om 39,060 o 18,509. A ho ough s udy o he no malized da a is p esen ed in Figu e 18, which also includes a boxplo (Figu e 18. A) and an MDS plo (Figu e 18. B). These g aphical depic ions ac as isual con i ma ions, p o ide s ong p oo ha he da a is eliable, and accu a ely cap u e he sub le ies o he expe imen al se up. The eliabili y and consis ency o he indings in he acu e expe imen a e suppo ed by he dec eased coun eadings and he well-o ganized pa e ns shown in he boxplo and MDS plo , con ibu ing o he o e all obus ness o he analy ical app oach. 46 (A) (B) Figu e 16: Boxplo (Figu e 16. A) and MDS plo (Figu e 16. B) o no malized samples dis ibu ion o ch onic da a, wi h N20G4 sample. A boxplo is a ep esen a ion in which i is possible o isualize da ase dis ibu ion, highligh ing he in e qua ile ange (box), median (line), and da a ange (whiske s). An MDS plo p ojec s mul idimensional da a in o a simpli ied space, e lec ing simila i ies and dissimila i ies be- ween poin s. P oximi y indica es simila i y, acili a ing pa e n disco e y. Bo h ep esen a ions e eal he p esence o he ’N20G4’ sample as an ou lie wi hin he No h popula ion a a empe a u e o 20 ºC. Ou lie s can dis o s a is ical measu emen s and may p o ide inco ec esul s. I was deemed necessa y o exclude he N20G4 sample om he subsequen analysis. 47 (A) (B) Figu e 17: Boxplo (Figu e 17. A) and MDS plo (Figu e 17. B) o no malized samples dis ibu ion o ch onic da a, wi hou N20G4 sample. A boxplo is a ep esen a ion in which i is possible o isualize da ase dis ibu ion, highligh ing he in e qua ile ange (box), median (line), and da a ange (whiske s). An MDS plo p ojec s mul idimensional da a in o a simpli ied space, e lec ing simila i ies and dissimila i ies be ween poin s. P oximi y indica es simila i y, acili a ing pa e n disco e y. 48 (A) (B) Figu e 18: Boxplo (Figu e 18. A) and MDS plo (Figu e 18. B) o no malized samples dis ibu ion o acu e da a. A boxplo is a ep esen a ion in which i is possible o isualize da ase dis ibu ion, highligh ing he in e qua ile ange (box), median (line), and da a ange (whiske s). An MDS plo p ojec s mul idimensional da a in o a simpli ied space, e lec ing simila i ies and dissimila i ies be ween poin s. P oximi y indica es simila i y, acili a ing pa e n disco e y. 49 4.4.2 Compa a i e analysis In ecen yea s, an inc easing amoun o esea ch has adop ed a me hodology o examine DGE, u ilizing he mos commonly used echniques such as edgeR, limma, and DESeq2 (259;262). Combining se e al analy ical echniques is a powe ul s a egy ha acili a es a deepe obus in es iga ion o gene exp ession pa e ns and a mo e sophis ica ed comp ehension o hei biological meaning (263). Since each me hod has i s ad an ages and limi a ions, he use o edgeR, limma, and DESeq2 simul aneously imp o es he o e all analy ical dep h o he s udy while making he analysis o gene exp ession mo e obus and e ec i e. Un il oday, he simul aneous use o hese h ee app oaches has ne e been applied in a s udy using eshwa e mussels. The p esen wo k ills his gap by in es iga ing eshwa e mussel gene exp ession pa e ns using he h ee me hods a he same ime. The combina ion o edgeR, limma, and DESeq2 is a new way o s udy di e en ial gene exp ession in eshwa e mussels, di e ging om he adi ional me hodologies ha ha e been employed in pas s udies (249;243). The alues o FDR and p.adj in he ou pu o he o e lap we e ob ained using he limma me hod. Se - e al s udies, using RNA-seq da a, ha e consis en ly epo ed ha limma when compa ed o o he me hods, p oduces supe io esul s and is o en conside ed he mos balanced me hod (264;265). Limma uses a solid s a is ical app oach by employing an empi ical Bayes mode a ion echnique. Fu he mo e, limma is lexible and can handle di e en expe imen al designs, e en hose wi h mul iple ac o s (266). In addic- ion o i s lexibili y, limma in eg a es buil -in me hods o co ec e o s ha may a ise when simul aneously es ing nume ous genes (267). I s obus pe o mance and balanced app oach make i a widely a o ed choice o gene exp ession analysis, con ibu ing o he eliabili y and accu acy o he ob ained esul s. Simila o he sec ion abo e, he ollowing analysis was di ided in o wo di e en expe imen s, ch onic and acu e. 50 Ch onic Expe imen s Figu e 19 ep esen s he es ima ed dispe sion plo s, o ch onic expe imen s, esul ing om applying h ee dis inc me hods—edgeR, limma, and DESeq2. Dispe sion plo s a e essen ial o comp ehending how gene exp ession a ies be ween samples and a e c i ical o he p ecision o di e en ial exp ession analysis. The dispe sion plo s p o ide in o ma ion abou he deg ee o a iabili y wi hin he da ase by showing he sp ead o exp ession le els o each gene. Examining hese g aphs helps de e mine i he selec ed s a is ical echniques adequa ely cap u e he in insic biological a iabili y and echnological noise in he expe imen da a, which is he case o he esul s he e p esen ed, i.e. he s a is ics i he da a. Figu e 19: Es ima ed dispe sion plo s o ch onic expe imen s, using h ee dis inc me hods: EdgeR, limma, DESeq2. Table 5 p o ides an o e iew o he numbe o DGEs ob ained in wo di e en s ages o he ch onic expe imen s analysis. The i s pa illus a es all he compa a i e analyses wi h bo h DEApp and R/Bio- conduc o packages using he h ee me hods sepa a ely. Addi ionally, he second pa shows he numbe o DGEs ob ained h ough he o e lap be ween he h ee me hods using exclusi ely he R/Bioconduc o package. In he able, he numbe o DGEs in he wo analyses (No h 20 ºC ∩25 ºC ∩30 ºC and Sou h 20 ºC ∩25 ºC ∩30 ºC) in DEApp is no ep esen ed, since his so wa e does no allow he use o h ee condi ions a he same ime. 51 Table 5: Numbe o DGEs using he so wa e DEApp and R/Bioconduc o code in all he compa a i e analyses de eloped using he h ee me hods, EdgeR, Limma, and DESeq2, and numbe o DGEs esul ing om he o e lap o he h ee me hods in he analysis ha showed consis ency in he esul s. Compa isons Numbe o DGEs EdgeR Limma DESeq2 DEApp R code DEApp R code DEApp R code No h 20 °C s Sou h 20 °C 641 538 166 169 850 1115 No h 25 °C s Sou h 25 °C 1523 1527 746 718 1605 1912 No h 30 °C s Sou h 30 °C 2924 2853 2093 2090 2758 3259 No h s Sou h 2891 2891 1936 3030 1815 3095 No h 20 °C ∩25 °C ∩30 °C - 75 - 38 - 37 Sou h 20 °C ∩25 °C ∩30 °C - 534 - 266 - 77 O e lap be ween he h ee me hods using R code No h 20 °C s Sou h 20 °C 130 No h 25 °C s Sou h 25 °C 594 No h 30 °C s Sou h 30 °C 1609 No h s Sou h 2150 The ob ained esul s align wi h expec a ions. As shown in Table 5, he numbe o DGEs in he com- pa isons is simila o he numbe p oduced by he R code. The simila i y be ween he obse ed alues highligh s he obus ness and consis ency o he analy ical echniques used in his wo k and he alida ion o he app oach using Rcode. The simila i y is a consequence o he use o he same me hods, pa am- e e s, and h esholds in he wo app oaches, which lead o consis en indings in he analysis o DGE o his s udy. Howe e , in he analysis o Sou h 20 °C ∩25 °C ∩30 °C he numbe o DGE o he me hods EdgeR, limma, and DESeq2 was 534, 266, and 77, espec i ely. When pe o ming he o e lap be ween he h ee me hods, as shown in Figu e 20, he numbe o he DGE is oo low. In he No he n popula ion, only 2 DGEs a e esul ing om he o e lap, while in he Sou he n popula ion, he numbe is 32. Fu he mo e, when examining he Venn diag ams, a lack o DGE in he o e lap be ween DESeq2 and Limma was obse ed. This obse a ion aligns wi h he well-documen ed conse a i e beha iou o he DESeq2 me hod, which ends o be cau ious in decla ing genes as di e en ially exp essed (268). These esul s a e consis en wi h some s udies ha con i m ha DESeq2 is ex emely conse a i e and consequen ly loses sensi i i y compa ed o he o he me hods (269;270). Indeed, his ea u e is no uni e sally applied o e e y analysis. In ac , in he es o he compa a i e analyses ep esen ed, DESeq2 demons a ed a no able ad an age, success ully iden i ying a g ea e numbe o di e en ially exp essed 52 genes, as illus a ed in Table 5. This a ibu e o DESeq2 comp o es i s sensi i i y, which is di e en in he speci ic con ex . Depending on he expe imen ’s ci cums ances and pa ame e se ings, DESeq2 may exhibi highe sensi i i y, esul ing in he de ec ion o ei he an inc eased o dec eased numbe o genes as di e en ially exp essed. The esul s highligh he complex beha io o DESeq2, demons a ing i s ex eme sensi i i y in ce ain si ua ions and i s conse a i e cha ac e in o he s. These indings emphasize he signi icance o employing h ee me hods, as each has been shown o exhibi ce ain limi a ions (271). The e o e he compa isons Sou h 20 °C ∩25 °C ∩30 °C and No h 20 °C ∩25 °C ∩30 °C we e excluded om he u he analysis. Figu e 20: Veen diag am o he compa isons No h 20 °C ∩25 °C ∩30 °C and Sou h 20 °C ∩25 °C ∩30 °C. Fo each compa a i e analysis a olcano plo and a hea map (Figu e 21 o 24) we e employed, o isualize he esul s. Volcano plo s we e used o show impo ance wi h s a is ical signi icance and old change c i e ia speci ied. Complemen ing he olcano plo s, hea maps we e pe o med o p o ide a com- p ehensi e o e iew o he di e en ial exp ession o each compa a i e analysis. 53 Reac ome The Me abolism o inges ed SeMe , Sec, MeSec in o H2Se pa hway (padj: 2.549 ×10−2) is an in eg al componen o Selenium Me abolism and Selenop o ein. Selenium co esponds o a i al ace mine al o human heal h, including an ioxida i e and an i-in lamma o y p ope ies (275). The down- egula ion o his pa hway may poin o a decline in he me abolism o amino acids ha include selenium (SeMe , Sec, and MeSec) in o hyd ogen selenide (H2Se). In he p esen wo k, i was ound ha he genes glucosaminyl (N-ace yl) ans e ase 3 (GCNT3), pescadillo ibosomal biogenesis ac o 1 (PES1), and cys a hionine gamma-lyase (CTH) a e in ol ed in he pa hways desc ibed abo e. Cu en ly, and as a as we know, no published s udies speci ically in es iga es he co ela ion be ween hese genes esul ing om his pa hway, and he impac s o ising empe a u es on eshwa e mussels. These indings highligh he impo ance o his wo k in elucida ing p e iously undisco e ed genes in his ield o s udy. Table 7: Gene On ology (GO) Molecula Func ion (GO: MF), he da abase o manually anno a ed p o ein complexes (CORUM), Cellula Componen (GO: CC), Human Pheno ype On ology (HP) and Reac ome pa h- ways (REAC) en ichmen analysis o he compa a i e ou pu analysis o No h s Sou h a he empe a u e o 20 ºC in ch onic expe imen s, using g: P o ile . Sou ce Te m ID Te m Name Gene Name padj (up- egula ed) padj (down- egula ed) GO:MF GO:0003829 β-1,3-galac osyl-O- glycosyl-glycop o ein β-1,6-N-ace yl glucosaminyl ans e ase ac i i y GCNT3 GCNT1 2.291 ×10−3 CORUM CORUM:7197 Me hionine adenosyl- ans e ase α1β- 1 MAT1A 4.982 ×10−2 GO:CC GO:0030686 90S p e ibosome PES1 NOL6 4.807 ×10−2 HP HP:0010068 B oad i s me a a sal NEK1 FGFR2 4.967 ×10−2 REAC R-HSA-2408508 Me abolism o inges ed SeMe ,Sec, MeSec in o H2Se CTH NNMT 2.549 ×10−2 60 • No h s Sou h 25 ºC Table 8 lis s he mos signi ican on ology e ms wi h hei co esponding padj alues, using g: P o ile . The lis o sou ce go: e ms encompasses ou dis inc ca ego ies o on ology e ms: Molecula Func ion (GO: MF), Biological P ocesses (GO: BP), Cellula Componen (GO: CC), and he da abase o manually anno a ed p o ein complexes (CORUM). Table 8 includes some o he genes in ol ed in each pa hway. Sec ion B.02 shows a de ailed lis o go e ms and he espec i e Ensembl ID, gene name, and desc ip ion o he compa a i e analysis a 25 ºC. Molecula Func ion The e m GO:0016823 (hyd olase ac i i y ac ing on acid ca bon-ca bon bonds in ke onic sub- s ances) was iden i ied wi h he padj alue o 4.999 ×10−2. The educ ion in he exp ession o genes linked o hyd olase ac i i y implies a possible con ibu ion o he speci ic deg ada ion o ce ain subs ances (276). The a ge ed molecules could unc ion as ene gy s o es o ake pa in me abolic p ocesses ha a e essen ial o eshwa e mussels’ su i al. The down- egula ion sugges s a ac ical eac ion o lessen he e ec s o en i onmen al s ess. This pa hway may help mussels p oduce signal molecules o dealing wi h s ess. In he p esen wo k, i was ound ha he genes uma ylace oace a e hyd olase domain con aining 1 (FAHD1) and uma ylace oace a e hyd olase (FAH) pa icipa e in his pa hway. Cu en ly, and as a as we know, no published s udies speci ically in es iga es he co ela ion be ween hese genes esul ing om his pa hway, and he impac s o ising empe a u es on eshwa e mussels. These indings highligh he impo ance o his wo k in elucida ing p e iously undisco e ed genes in his ield o s udy. Biological P ocesses The egula ion o i al-induced cy oplasmic pa e n ecogni ion pa hway (padj: 1.794×10−2) e e s o he biological mechanisms by which cells de ec and eac o i al in ec ions. The up- egula ion o his pa hway migh indica e an imp o ed immune esponse o any i al in ec ions b ough on by s ess (277). In he p esen wo k, i was ound ha he gene oll-like ecep o 6 (TLR6) is in ol ed in his pa hway. Wu e al., 2023 desc ibed his gene in a compa a i e ansc ip omic analysis o a ma ine mussel du ing high- empe a u es (278). The pa hway demons a ing a signi ican padj alue includes cilium mo emen in ol ed in cell mo il- i y (padj: 2.566 ×10−2). Cilia o cilium a e hai -like p ojec ions ha eme ge om he su ace o ce ain li ing cells and a e in ol ed in a ious cellula unc ions such as mo emen and senso y p ocesses (279). The down- egula ion o his pa hway sugges s ha he mussels a e delibe a ely 61 changing how hey mo e and pe cei e he en i onmen , appea ing o be less sensi i e o empe a- u e changes as a esul o hei dec eased exp ession. Mo eo e , inc eased sensi i i y o en i onmen al s imuli is shown by he up- egula ion o genes in- ol ed in he cy osolic pa e n ecogni ion ecep o signaling pa hway (padj: 1.720 ×10−3). The up- egula ion o his pa hway sugges s ha he o ganism is becoming mo e esponsi e o po en ial h ea s (280). This heigh ened sensi i i y may be a p o ec i e measu e ha migh be necessa y o deal wi h challenges a ising om changing en i onmen al condi ions, such as inc easing empe - a u es, whe e a s onge immune esponse is equi ed. Bení ez e al., 2023 and E l e al., 2019 epo ed he genes in e e on induced wi h helicase C domain 1 (IFIH1) and solu e ca ie amily 15 membe 4 (SLC15A4) as di e en ially egula ed genes in he s udy o inc easing empe a u es on bi al es, espec i ely (281;282). The p esen wo k, also epo s hese genes ela i e o his pa hway. Cellula Componen s The pa hway dyneim complex (padj: 1.227 ×10−4) is esponsible o o ce gene a ion and mo ili y owa ds he minus ends o mic o ubules (MTs) (283). Mo o p o eins a e essen ial o he ope a ion o s uc u es like cilia and lagella as well as o in acellula anspo and o ganelle placemen . Dynein is in ol ed in he anspo o esicles and o ganelles owa d he mic o ubule-o ganizing cen e o he cell cen e (284). The down- egula ion o his pa hway may sugges ha in acellula anspo and o ganelle placemen may be a ec ed. Table 8: Gene On ology (GO) Molecula Func ion (GO: MF), Biological P ocesses (GO: BP), Cellula Compo- nen (GO: CC), and he da abase o manually anno a ed p o ein complexes (CORUM) en ichmen analysis o he compa a i e ou pu analysis o No h s Sou h a he empe a u e o 25 ºC in ch onic expe imen s, using g: P o ile . Sou ce Te m ID Te m Name Gene Name padj (up- egula ed) padj (down- egula ed) GO:MF GO:0016823 hyd olase ac i i y, ac ing on acid ca bon-ca bon bonds, in ke onic subs ances FAHD1 FAH 4.999 ×10−2 GO:BP GO:0039531 egula ion o i al-induced cy oplasmic pa e n ecogni ion BIRC2 TLR6 1.794 ×10−2 Con inued in he nex page. 62 Sou ce Te m ID Te m Name Gene Name padj (up- egula ed) padj (down- egula ed) GO:BP GO:0035082 axoneme assembly CFAP206 DRC1 1.579 ×10−3 GO:BP GO:0001578 mic o ubule bundle o ma ion TEKT2 DNAJB13 8.994 ×10−3 GO:BP GO:0016823 cy osolic pa e n ecogni ion ecep o signaling pa hway IFIH1 SLC15A4 1.720 ×10−3 GO:BP GO:0060294 cilium mo emen in ol ed in cell mo ili y TEKT4 CFAP206 2.566 ×10−2 GO:CC GO:0097228 spe m p incipal piece CFAP206 CFAP20 9.234 ×10−3 GO:CC GO:0005879 axonemal mic o ubule ENKUR RIBC2 1.340 ×10−10 GO:CC GO:0030286 dynein complex DRC1 DYNLT2B 1.227 ×10−4 GO:CC GO:0005881 cy oplasmic mic o ubule TEKT4 CFAP206 1.421 ×10−6 CORUM CORUM:5529 TRAF2-cIAP1/BIRC2 complex BIRC2 TRAF2 2.394 ×10−2 • No h s Sou h 30 ºC Table 9 lis s he mos signi ican on ology e ms wi h hei co esponding padj alues, using g: P o- ile . The lis o sou ce go: e ms encompasses i e dis inc ca ego ies o on ology e ms: Molecula Func ion (MF), Biological P ocess (BP), Cellula Componen s (CC), Kyo o Encyclopedia o Genes and Genomes (KEGG), and Reac ome (REAC). Table 9 includes some o he genes in ol ed in each pa hway. Sec ion B.03 shows a de ailed lis o go e ms and he espec i e Ensembl ID, gene name, and desc ip ion o he compa a i e analysis a 30 ºC. Molecula Func ion Ele a ed empe a u es can dis up he p ocess o p o ein olding, leading o he mis olding and agg ega ion o p o eins. The up egula ion o he p o ein olding chape one pa hway (padj: 9.084 × 10−3) sugges s an adap i e s a egy o p ese e p ope p o ein con o ma ion, p e en agg ega ion, and ensu e he unc ional in eg i y o essen ial cellula p o eins unde empe a u e-induced s ess. Hu e al. (2022) and Tan e al. (2023) iden i ied nume ous genes including, hea shock p o ein amily A (Hsp70) membe 4 (HSPA4) and hea shock p o ein amily B (small) membe 6 (HSPB6) 63 espec i ely, as di e en ially exp essed in he s udy o bi al es exposed o he mal s ess (285;286). The wo men ioned genes we e de ec ed in he p esen s udy, and a e linked o he p o ein olding chape one pa hway. Biological P ocesses The Golgi lumen acidi ica ion pa hway (padj: 1.418 ×10−5) is impo an o enzyme ac i a ion and p o ein anspo o occu (287). Cells may up- egula e his mechanism when empe a u es ise o main ain op imal Golgi unc ion and he up- egula ion obse ed may in luence p o ein p ocessing and sec e ion. In he p esen wo k, i was ound ha he genes ATPase H+ anspo ing V0 subuni a1 (ATP6V1A) and ATPase H+ anspo ing accesso y p o ein 1 (ATP6AP1) a e in ol ed in his pa hway. Ba e e al., 2022 desc ibed hese genes ela i e o molecula esponses in he mussel My ilus edulis in esponse o he mal s ess (288). The acuola acidi ica ion pa hway eme ges wi h a low padj alue o 2.281 ×10−3. Vacuola acidi ica ion is a homeos a ic p ocess ha egula es in acellula pH, ion, chemical balance, and p o ein ecycling, all o which a e essen ial o op imal cellula unc ion (289). When exposed o highe empe a u es, o ganisms inc ease acuola acidi y as pa o hei esponse mechanism (290). The up- egula ion o his pa hway may sugges e iciency in he p ocess o elimina ion o me abolic exposu e o highe empe a u es. In addi ion, he amino acid ac i a ion pa hway eme ges wi h a e y low padj alue o 5.068 ×10−9. Mo eo e , amino acids a e he basic building elemen s o p o eins (291). The demand o p o ein syn hesis equen ly ises when an o ganism is exposed o highe empe a u es (292). The up- egula ion o his pa hway may sugges an e ec i e amino acid u iliza ion, gua an eeing an adequa e supply o p o ein syn hesis. Fu he mo e, he cellula esponse o leucine, an impo an amino acid, eme ges wi h he padj alue o 4.359 ×10−2. Leucine is essen ial o p o ein syn hesis and cellula me abolism (293). Cells may up- egula e hei sensi i i y o leucine as empe a u es ise o suppo inc eased me abolic ac i i y (294). This pa hway may be up- egula ed as a cellula mechanism o add ess he inc eased demand o ene gy and biosyn he ic ac i i ies associa ed wi h highe empe a u es. KEGG The up- egula ion o he collec ing duc acid sec e ion pa hway (padj: 1.813 ×10−3) sugges s an adap i e esponse o ising empe a u es. Acid sec e ion in he collec ing duc s is c i ical o main aining acid-base homeos asis, which is equi ed o cellula ac i i y (295). The ac i a ion o 64 his pa hway may indica e an inc eased capaci y o elimina e excess acids. Wa m empe a u es equen ly cause me abolic changes, and ac i a ion o he a y acid deg ada ion pa hway (padj: 7.081 ×10−4) indica es he o ganism’s eliance on al e na e ene gy sou ces. The a y acid deg ada ion is a ca abolic p ocess ha uses a y acids o c ea e ene gy (296). This adap a ion enables he o ganism o op imize i s ene gy me abolism in esponse o inc eased empe a u e s ess, gua an eeing a s eady supply o ene gy o c i ical cellula unc ions. Alonso e al., 2020 desc ibed he gene cy och ome P450 amily 2 sub amily U membe 1 (CYP2U1) in ol ed in his pa hway in he species o Physella acu a (297). In he p esen wo k, his gene was also ound. P o ein syn hesis, a c ucial biological unc ion, depends on he aminoacyl- RNA biosyn hesis pa h- way (padj: 2.688 ×10−10) (298). The up egula ion o his p ocess in he se ing o high empe - a u es shows ha he e is a g ea e equi emen o p o ein syn hesis o suppo di e se cellula ac i i ies, such as s ess esponse and epai mechanisms. Inc eased aminoacyl- RNA biosyn hesis may help he o ganism c ea e p o eins equi ed o hea adap a ion and esis ance (299). The compa a i e analysis o No h s Sou h a he empe a u e o 30 ºC demons a ed a pa - e n o genes ela ed o he acuola ATPase (V-ATPase) complex, including ATP6V1A, ATP6V0A1, ATP6V0A, and ATP6V1F. These genes a e p esen in se e al pa hways such as ATPase ac i i y, cou- pled o ansmemb ane mo emen o ions, o a ional mechanism, endosomal lumen acidi ica ion, Golgi lumen acidi ica ion, synap ic esicle lumen acidi ica ion, p o ein impo in o mi ochond ial ma ix, lysosomal lumen acidi ica ion, acuola acidi ica ion, p o on- anspo ing V- ype ATPase, V1 domaincomplex and Collec ing duc acid sec e ion. In e es ingly, all hese pa hways a e up- egula ed. The acuola ATPases (V-ATPases) a e a so o p o on pump ha links ATP hyd olysis o p o on anspo wi hin cells and ac oss he plasma memb ane. They pa icipa e in a wide ange o cellula unc ions, including memb ane a ic, p o ein p ocessing and deg ada ion, and small molecule linked anspo , as well as physiological p ocesses including u ine acidi y and bone eso p ion (300). 65 Table 9: Gene On ology (GO) Molecula Func ion (MF), Biological P ocess (BP), Cellula Componen s (CC), Kyo o Encyclopedia o Genes and Genomes (KEGG), and Reac ome (REAC) en ichmen analysis o he compa a i e ou pu analysis o No h s Sou h a he empe a u e o 30 ºC in ch onic expe imen s, using g: P o ile . Sou ce Te m ID Te m Name Gene Name padj (up- egula ed) padj (down- egula ed) GO:MF GO:0010854 adenyla e cyclase egula o ac i i y CALM3 GRM7 3.627 ×10−2 GO:MF GO:0050135 NAD(P)+ nucleosidase ac i i y TLR2 TLR4 3.694 ×10−4 GO:MF GO:0022848 ace ylcholine-ga ed monoa omic ca ion-selec i e channel CHRNA3 CHRNA2 2.146 ×10−2 GO:MF GO:0044769 ATPase ac i i y, coupled o ansmemb ane mo emen o ions, o a ional mechanism ATP6V0A1 ATP6V1A 5.787 ×10−5 GO:MF GO:0016875 ligase ac i i y, o ming ca bon-oxygen bonds RARS1 WARS1 6.280 ×10−10 GO:MF GO:0044183 p o ein olding chape one HSPA4 HSPB6 9.084 ×10−3 GO:BP GO:0061795 Golgi lumen acidi ica ion ATP6V1A ATP6AP1 1.418 ×10−5 GO:BP GO:0036295 cellula esponse o inc eased oxygen le els CAV1 1.942 ×10−2 GO:BP GO:0048388 endosomal lumen acidi ica ion ATP6V0A1 ATP6V1F 2.780 ×10−5 GO:BP GO:0043201 esponse o leucine LARS1 RRAGD 4.359 ×10−2 GO:BP GO:0097401 synap ic esicle lumen acidi ica ion ATP6V1A ATP6AP1 2.339 ×10−6 Con inued in he nex page. 66 Sou ce Te m ID Te m Name Gene Name padj (up- egula ed) padj (down- egula ed) GO:BP GO:0030150 p o ein impo in o mi ochond ial ma ix ATP6V1A ATP6AP1 1.191 ×10−2 GO:BP GO:0007042 lysosomal lumen acidi ica ion ATP6V1A ATP6AP1 1.175 ×10−3 GO:BP GO:0007035 acuola acidi ica ion ATP6V1A ATP6AP1 2.281 ×10−3 GO:BP GO:0043038 amino acid ac i a ion RARS1 WARS1 5.068 ×10−9 GO:CC GO:0035354 Toll-like ecep o 1-Toll-like ecep o 2 p o ein complex TLR2 TLR1 4.439 ×10−2 GO:CC GO:0033180 p o on- - anspo ing V- ype ATPase, V1 domaincomplex ATP6V1A ATP6V1D 7.555 ×10−4 GO:CC GO:0017101 aminoacyl- RNA syn he ase mul ienzyme complex RARS1 FARSB 1.271 ×10−3 KEGG KEGG:04966 Collec ing duc acid sec e ion ATP6V0A ATP6V1A 1.813 ×10−3 KEGG KEGG:00071 Fa y acid deg ada ion CYP2U1 ECI1 7.081 ×10−4 KEGG KEGG:00970 Aminoacyl- RNA biosyn hesis RARS1 MARS1 2.688 ×10−10 REAC R-HSA-629597 Highly calcium pe meable ACh ecep o s CHRNA3 CHRNA2 1.584 ×10−3 • No h s Sou h Table 10 lis s he mos signi ican on ology e ms wi h hei co esponding padj alues, using g: P o- ile . The lis o sou ce go: e ms encompasses i e dis inc ca ego ies o on ology e ms: Molecula Func ion (MF), Biological P ocess (BP), Cellula Componen s (CC), and Kyo o Encyclopedia o Genes and Genomes (KEGG). Table 10 includes some o he genes in ol ed in each pa hway. Sec ion B.04 shows a de ailed lis o go e ms and he espec i e Ensembl ID, gene name, and desc ip ion o he compa a i e analysis o No h s Sou h. 67 Molecula Func ion The a yl sul o ans e ase ac i i y pa hway (padj: 9.486 ×10−3) e e s o he enzyma ic ac i i y o a yl sul o ans e ases. These enzymes ans e a sul a e g oup o a yl compounds, playing a ole in he me abolism and de oxi ica ion o a ious subs ances (301). The up- egula ion o his pa hway may sugges a dynamic cellula esponse aimed a educing he impac s o s ess-induced al e a ions. Biological P ocesses Mac oau ophagy is a cellula p ocess ha deg ades and ecycles cellula componen s (302). Nega- i e egula ion o mac oau ophagy pa hway (padj: 1.051 ×10−2) implies ha his p ocess is being supp essed. The mal s ess-induced up- egula ion may e lec a cellula mechanism o p io i ize o he asks o e sel -deg ada ion du ing s ess ul si ua ions. The alcohol ca abolic p ocess pa hway (padj: 2.339 ×10−6) e e s o he deg ada ion o alcohol molecules. The up- egula ion o his pa hway du ing he mal s ess migh sugges an inc eased me abolic demand o al e ed ene gy equi emen s associa ed wi h he s ess esponse. The memb ane depola iza ion pa hway (padj: 1.392 ×10−3) is he p ocess by which he elec ical po en ial ac oss a cell memb ane changes. The mal s ess-induced up- egula ion may imply a cel- lula esponse a ge ed a changing memb ane cha ac e is ics, po en ially o adap o he s esso . KEGG The ATP-binding casse e (ABC) anspo e s pa hway (padj: 3.295 ×10−4) is a widesp ead su- pe amily o in eg al memb ane p o eins ha a e esponsible o he ATP-powe ed ansloca ion o se e al subs a es ac oss memb anes (303). The up- egula ion o his pa hway may indica e an inc eased cellula equi emen o ac i e anspo o molecules ac oss cell memb anes. In he p esen wo k, i was ound ha he genes sul o ans e ase amily 1A membe 2 (SULT1A2), ing inge p o ein 41 (RNF41), glyce ol kinase 5 (GK5) and pu ine gic ecep o P2X 4 (P2RX4) a e in ol ed in he pa hways desc ibed abo e. Cu en ly, and as a as we know, no published s udies speci ically in es iga es he co ela ion be ween hese genes esul ing om his pa hway, and he impac s o ising empe a u es on eshwa e mussels. These indings highligh he impo ance o his wo k in elucida ing p e iously undisco e ed genes in his ield o s udy. 68 Acu e expe imen s Figu e 27, p o ides an o e iew o g: P o ile esul s om acu e expe imen s. The images p o ide a clea isualiza ion o molecula dynamics in he p esen analysis. Figu e 29: O e iew o g: P o ile esul s in acu e expe imen s, highligh ing s a is ically signi ican en ich- men s, empe a u e-speci ic pa e ns. Table 11 lis s he mos signi ican on ology e ms wi h hei co esponding p- alues, using g: P o ile in he acu e expe imen s. The lis o sou ce on ology e ms encompasses ou dis inc ca ego ies: Molecula Func ion (GO: MF), Biological P ocesses (GO: BP), Cellula Componen (GO: CC), Reac ome (REAC), and P o ein da abases (CORUM). Table 11 includes some o he genes in ol ed in each pa hway. Sec ion B.05 shows a de ailed lis o he go e ms and he espec i e Ensembl ID, gene name, and desc ip ion o he compa a i e analysis o acu e expe imen s. Molecula Func ion The p o ein disul ide isome ase ac i i y pa hway (padj: 8.697 ×10−3) e e s o a p o ein disul ide isome ase’s molecula unc ion. P o ein disul ide isome ases (PDIs) p omo e co ec p o ein olding by ca alyzing he ea angemen o disul ide links wi hin p o eins (304). The up- egula ion o his pa hway may indica e a g ea e necessi y o app op ia e p o ein olding and disul ide bond ea angemen . In he p esen wo k, i was ound ha he genes p o ein disul ide isome ase amily A membe 6 (PDIA6) and p o ein disul ide isome ase amily A membe 4 (PDIA4) a e in ol ed in his pa hway. Kong e al., 2022 desc ibed hese genes ela i e o molecula esponses in he bi al e Sinono acula cons ic a unde he mal s ess (305). The oxido educ ase ac i i y, ac ing on single dono s by inco po a ing molecula oxygen pa hway (padj: 3.441 ×10−2) ope a es on single dono s o inco po a e molecula oxygen in o he eac ion. This enzyme pa icipa es in oxida ion- educ ion p ocesses in which oxygen is a eac an . The up- egula ion o his pa hway may sugges an inc ease in he demand o molecula oxygen p ocesses. 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Yildiz, “S uc u e and mechanics o dynein mo o s,” Annual e iew o biophysics , ol. 50, pp. 549–574, 2021. 101 16 singula i y exec /sha e/apps/singula i y/hisa _ 2.2.1.simg 17 ex ac _splice_si es.py 18 Ude_anno a ion_so ed.g > Ude_g .ss 19 20 singula i y exec /sha e/apps/singula i y/hisa _ 2 .2.1.simg 21 ex ac _exons.py Ude_anno a ion_so ed.g > Ude_g .exons 22 23 singula i y exec /sha e/apps/singula i y/hisa _ 2 .2.1.simg 24 hisa 2 -build -p 30 --ss Ude_g .ss --exon Ude_g .exons 25 Ude_SM. a index_Ude 26 exi A.0.4 HISAT2 1#!/bin/bash 2#$ -pe smp 32 3#$ -N H2Mapp 4#$ -cwd 5#$ -j y 6#$ -S /bin/bash 7#$ -l h=!(compu e -0-15) 8#$ -o H2Mapp -s do.ou pu 1 9#$ -e H2Mapp -s de .ou pu 10 #$ - 1-2 11 12 #Hisa 2 13 INFILE1=$(head -n $SGE_TASK_ID Con igFile1. x | ail -n1|cu - 1) 14 INFILE2=$(head -n $SGE_TASK_ID Con igFile1. x | ail -n1|cu - 2) 15 INFILE3=$(head -n $SGE_TASK_ID Con igFile1. x | ail -n1|cu - 3) 16 INFILE4=$(head -n $SGE_TASK_ID Con igFile1. x | ail -n1|cu - 4) 17 INFILE5=$(head -n $SGE_TASK_ID Con igFile1. x | ail -n1|cu - 5) 18 INFILE6=$(head -n $SGE_TASK_ID Con igFile1. x | ail -n1|cu - 6) 19 INFILE7=$(head -n $SGE_TASK_ID Con igFile1. x | ail -n1|cu - 7) 20 INFILE8=$(head -n $SGE_TASK_ID Con igFile1. x | ail -n1|cu - 8) 21 INFILE9=$(head -n $SGE_TASK_ID Con igFile1. x | ail -n1|cu - 9) 22 INFILE10=$(head -n $SGE_TASK_ID Con igFile1. x | ail -n1|cu - 10) 23 INFILE11=$(head -n $SGE_TASK_ID Con igFile1. x | ail -n1|cu - 11) 24 25 26 #singula i y exec /sha e/apps/singula i y/pigz_ 2.4.simgpigz 27 -p 30 -d $INFILE10 28 #singula i y exec /sha e/apps/singula i y/pigz_ 2.4.simg pigz 29 -p 30 -d $INFILE11 30 31 singula i y exec /sha e/apps/singula i y/hisa _ 2.2.1.simg hisa 2 32 --d a -q -p 30 -x index_Ude -1 $INFILE1 -2 $INFILE2 -S $INFILE3 33 34 singula i y exec /sha e/apps/singula i y/o ca -6.simg sam ools 35 iew -@ 30 -Sb $INFILE3 > $INFILE4 36 108 37 singula i y exec /sha e/apps/singula i y/o ca -6.simg sam ools 38 so -@ 30 $INFILE4 -o $INFILE5 39 40 singula i y exec /sha e/apps/singula i y/o ca -6.simg sam ools 41 index $INFILE5 42 43 singula i y exec /sha e/apps/singula i y/o ca -6.simg sam ools 44 lags a $INFILE5 > $INFILE6 45 46 m $INFILE3 47 m $INFILE4 A.0.5 S ing ie 1#!/bin/bash 2#$ -pe smp 32 3#$ -N s ing ie_coun 4#$ -cwd 5#$ -j y 6#$ -S /bin/bash 7#$ -l h=!(compu e -0-0|compu e -0-1|compu e -0-2|compu e -0-3 8# |compu e -0-4|compu e -0-5|compu e -0-6) 9#$ -e S ing ieC -s de .ou pu 10 #$ - 1-40 11 12 13 INFILE1=$(head -n $SGE_TASK_ID Con igFile1. x | ail -n1|cu - 1) 14 INFILE2=$(head -n $SGE_TASK_ID Con igFile1. x | ail -n1|cu - 2) 15 INFILE3=$(head -n $SGE_TASK_ID Con igFile1. x | ail -n1|cu - 3) 16 INFILE4=$(head -n $SGE_TASK_ID Con igFile1. x | ail -n1|cu - 4) 17 INFILE5=$(head -n $SGE_TASK_ID Con igFile1. x | ail -n1|cu - 5) 18 INFILE6=$(head -n $SGE_TASK_ID Con igFile1. x | ail -n1|cu - 6) 19 INFILE7=$(head -n $SGE_TASK_ID Con igFile1. x | ail -n1|cu - 7) 20 INFILE8=$(head -n $SGE_TASK_ID Con igFile1. x | ail -n1|cu - 8) 21 INFILE9=$(head -n $SGE_TASK_ID Con igFile1. x | ail -n1|cu - 9) 22 INFILE10=$(head -n $SGE_TASK_ID Con igFile1. x | ail -n1|cu - 10) 23 INFILE11=$(head -n $SGE_TASK_ID Con igFile1. x | ail -n1|cu - 11) 24 25 26 singula i y exec /sha e/apps/singula i y/s ing ie_ 2 .1.2.si 27 s ing ie $INFILE5 -e -B -p 30 -G Ude_anno a ion_so ed.g 28 -o $INFILE8 -A $INFILE9 109 Appendix B De ails o esul s B.0.1 De ailed lis o go e ms and hei associa ed Ensembl ID, gene name, and de- sc ip ion o he compa a i e analysis o 20 ºC o he ch onic expe imen s, using g: P o ile - Table 12. B.0.2 De ailed lis o go e ms and hei associa ed Ensembl ID, gene name, and de- sc ip ion o he compa a i e analysis o 25 ºC o he ch onic expe imen s, using g: P o ile - Table 13. B.0.3 De ailed lis o go e ms and hei associa ed Ensembl ID, gene name, and de- sc ip ion o he compa a i e analysis o 30 ºC o he ch onic expe imen s, using g: P o ile - Table 14. B.0.4 De ailed lis o go e ms and hei associa ed Ensembl ID, gene name, and de- sc ip ion o he compa a i e analysis o No h s Sou h o he ch onic expe i- men s, using g: P o ile - Table 15. B.0.5 De ailed lis o go e ms and hei associa ed Ensembl ID, gene name, and de- sc ip ion o he compa a i e analysis o No h s Sou h o he acu e expe imen s, using g: P o ile - Table 16. Table 12: Lis o go e ms and hei associa e gene names and desc ip ions o he compa a i e analysis o ch onic expe imen s in he empe a u e o 20 ºC. Te m ID Ensembl ID Gene Name Gene Desc ip ion GO:0003829 ENSG00000140297 GCNT3 glucosaminyl (N-ace yl) ans e ase 3 ENSG00000187210 GCNT1 glucosaminyl (N-ace yl) ans e ase 1 CORUM:7197 ENSG00000151224 MAT1A me hionine adenosyl ans e ase 1A GO:0030686 ENSG00000100029 PES1 pescadillo ibosomal biogenesis ac o 1 ENSG00000165271 NOL6 nucleola p o ein 6 HP:0010068 ENSG00000137601 NEK1 NIMA ela ed kinase 1 ENSG00000066468 FGFR2 ib oblas g ow h ac o ecep o 2 R-HSA-2408508 ENSG00000116761 CTH cys a hionine gamma-lyase ENSG00000166741 NNMT nico inamide N-me hyl ans e ase 110 Table 13: Lis o go e ms and hei associa e gene names and desc ip ions o he compa a i e analysis o ch onic expe imen s in he empe a u e o 25 ºC. Te m ID Ensembl ID Gene Name Gene Desc ip ion GO:0016823 ENSG00000180185 FAHD1 uma ylace oace a e hyd olase domain con aining 1 ENSG00000103876 FAH uma ylace oace a e hyd olase GO:0039531 ENSG00000110330 BIRC2 baculo i al IAP epea con aining 2 ENSG00000023445 BIRC3 baculo i al IAP epea con aining 3 ENSG00000149476 TKFC iokinase and FMN cyclase ENSG00000139370 SLC15A4 solu e ca ie amily 15 membe 4 ENSG00000110171 TRIM3 ipa i e mo i con aining 3 ENSG00000174130 TLR6 oll like ecep o 6 GO:0035082 ENSG00000272514 CFAP206 cilia and lagella associa ed p o ein 206 ENSG00000157856 DRC1 dynein egula o y complex subuni 1 ENSG00000119661 DNAL1 dynein axonemal ligh chain 1 ENSG00000172426 RSPH9 adial spoke head componen 9 ENSG00000197889 MEIG1 meiosis/spe miogenesis associa ed 1 ENSG00000092850 TEKT2 ek in 2 ENSG00000187726 DNAJB13 DnaJ hea shock p o ein amily (Hsp40) membe B13 GO:0001578 ENSG00000272514 CFAP206 cilia and lagella associa ed p o ein 206 ENSG00000157856 DRC1 dynein egula o y complex subuni 1 ENSG00000119661 DNAL1 dynein axonemal ligh chain 1 ENSG00000172426 RSPH9 adial spoke head componen 9 ENSG00000197889 MEIG1 meiosis/spe miogenesis associa ed 1 ENSG00000092850 TEKT2 ek in 2 ENSG00000187726 DNAJB13 DnaJ hea shock p o ein amily (Hsp40) membe B13 GO:0002753 ENSG00000110330 BIRC2 baculo i al IAP epea con aining 2 ENSG00000023445 BIRC3 baculo i al IAP epea con aining 3 ENSG00000152223 EPG5 ec opic P-g anules 5 au ophagy e he ing ac o ENSG00000149476 TKFC iokinase and FMN cyclase ENSG00000139370 SLC15A4 solu e ca ie amily 15 membe 4 ENSG00000115267 IFIH1 in e e on induced wi h helicase C domain 1 ENSG00000110171 TRIM3 ipa i e mo i con aining 3 ENSG00000174130 TLR6 oll like ecep o 6 GO:0060294 ENSG00000163060 TEKT4 ek in 4 ENSG00000151023 CFAP206 cilia and lagella associa ed p o ein 206 ENSG00000196118 CFAP20 cilia and lagella associa ed p o ein 20 ENSG00000203666 RSPH9 adial spoke head componen 9 GO:0097228 ENSG00000163060 TEKT4 ek in 4 ENSG00000272514 CFAP206 cilia and lagella associa ed p o ein 206 ENSG00000070761 CFAP20 cilia and lagella associa ed p o ein 20 ENSG00000172426 RSPH9 adial spoke head componen 9 ENSG00000197889 MEIG1 meiosis/spe miogenesis associa ed 1 ENSG00000151023 ENKUR enku in, TRPC channel in e ac ing p o ein ENSG00000092850 TEKT2 ek in 2 GO:0005879 ENSG00000163060 TEKT4 ek in 4 ENSG00000272514 CFAP206 cilia and lagella associa ed p o ein 206 ENSG00000186973 CFAP144 cilia and lagella associa ed p o ein 144 ENSG00000070761 CFAP20 cilia and lagella associa ed p o ein 20 ENSG00000151023 ENKUR enku in, TRPC channel in e ac ing p o ein ENSG00000183690 EFHC2 EF-hand domain con aining 2 ENSG00000179902 ENKUR enku in, TRPC channel in e ac ing p o ein ENSG00000092850 CFAP276 cilia and lagella associa ed p o ein 276 ENSG00000128408 RIBC2 RIB43A domain wi h coiled-coils 2 Con inued in he nex page. Te m ID Ensembl ID Gene Name Gene Desc ip ion GO:0030286 ENSG00000157856 DRC1 dynein egula o y complex subuni 1 ENSG00000213123 DYNLT2B dynein ligh chain Tc ex- ype 2B ENSG00000100246 DNAL4 dynein axonemal ligh chain 4 ENSG00000119661 DNAL1 dynein axonemal ligh chain 1 ENSG00000152760 DYNLT5 dynein ligh chain Tc ex- ype amily membe 5 ENSG00000264364 DYNLL2 dynein ligh chain LC8- ype 2 GO:0005881 ENSG00000163060 TEKT4 ek in 4 ENSG00000272514 CFAP206 cilia and lagella associa ed p o ein 206 ENSG00000186973 CFAP144 cilia and lagella associa ed p o ein 144 ENSG00000070761 CFAP20 cilia and lagella associa ed p o ein 20 ENSG00000151023 ENKUR enku in, TRPC channel in e ac ing p o ein ENSG00000183690 EFHC2 EF-hand domain con aining 2 ENSG00000179902 CFAP276 cilia and lagella associa ed p o ein 276 ENSG00000092850 TEKT2 ek in 2 ENSG00000128408 RIBC2 RIB43A domain wi h coiled-coils 2 CORUM:5529 ENSG00000110330 BIRC2 baculo i al IAP epea con aining 2 ENSG00000127191 TRAF2 TNF ecep o associa ed ac o 2 Table 14: Lis o go e ms and hei associa e gene names and desc ip ions o he compa a i e analysis o ch onic expe imen s in he empe a u e o 30 ºC. Te m ID Ensembl ID Gene Name Gene Desc ip ion GO:0010854 ENSG00000160014 CALM3 calmodulin 3 ENSG00000196277 GRM7 glu ama e me abo opic ecep o 7 ENSG00000143933 CALM2 calmodulin 2 GO:0050135 ENSG00000196083 IL1RAP in e leukin 1 ecep o accesso y p o ein ENSG00000137462 TLR2 oll like ecep o 2 ENSG00000136869 TLR4 oll like ecep o 4 ENSG00000174125 TLR1 oll like ecep o 1 ENSG00000174123 TLR10 oll like ecep o 10 GO:0022848 ENSG00000080644 CHRNA3 choline gic ecep o nico inic alpha 3 subuni ENSG00000120903 CHRNA2 choline gic ecep o nico inic alpha 2 subuni ENSG00000147432 CHRNB3 choline gic ecep o nico inic be a 3 subuni ENSG00000147434 CHRNA6 choline gic ecep o nico inic alpha 6 subuni GO:0044769 ENSG00000033627 ATP6V0A1 ATPase H+ anspo ing V0 subuni a1 ENSG00000114573 ATP6V1A ATPase H+ anspo ing V1 subuni A ENSG00000100554 ATP6V1D ATPase H+ anspo ing V1 subuni D ENSG00000159720 ATP6V0D1 ATPase H+ anspo ing V0 subuni d1 ENSG00000128524 ATP6V1F ATPase H+ anspo ing V1 subuni F ENSG00000117410 ATP6V0B ATPase H+ anspo ing V0 subuni b ENSG00000047249 ATP6V1H ATPase H+ anspo ing V1 subuni H ENSG00000136888 ATP6V1G1 ATPase H+ anspo ing V1 subuni G1 GO:0016875 ENSG00000113643 RARS1 a ginyl- RNA syn he ase 1 ENSG00000140105 WARS1 yp ophanyl- RNA syn he ase 1 ENSG00000116120 FARSB phenylalanyl- RNA syn he ase subuni be a ENSG00000166986 MARS1 me hionyl- RNA syn he ase 1 ENSG00000139131 YARS2 y osyl- RNA syn he ase 2 ENSG00000133706 LARS1 leucyl- RNA syn he ase 1 ENSG00000031698 SARS1 se yl- RNA syn he ase 1 ENSG00000106105 GARS1 glycyl- RNA syn he ase 1 ENSG00000196305 IARS1 isoleucyl- RNA syn he ase 1 ENSG00000179115 FARSA phenylalanyl- RNA syn he ase subuni alpha ENSG00000113407 TARS1 h eonyl- RNA syn he ase 1 ENSG00000134440 NARS1 aspa aginyl- RNA syn he ase 1 ENSG00000110619 CARS1 cys einyl- RNA syn he ase 1 ENSG00000115866 DARS1 aspa yl- RNA syn he ase 1 Con inued in he nex page. Te m ID Ensembl ID Gene Name Gene Desc ip ion GO:0044183 ENSG00000166598 HSP90B1 hea shock p o ein 90 be a amily membe 1 ENSG00000170606 HSPA4 hea shock p o ein amily A (Hsp70) membe 4 ENSG00000004776 HSPB6 hea shock p o ein amily B (small) membe 6 ENSG00000187522 HSPA14 hea shock p o ein amily A (Hsp70) membe 14 ENSG00000115541 HSPE1 hea shock p o ein amily E (Hsp10) membe 1 ENSG00000144381 HSPD1 hea shock p o ein amily D (Hsp60) membe 1 ENSG00000143256 PFDN2 p e oldin subuni 2 ENSG00000179218 CALR cal e iculin ENSG00000113013 HSPA9 hea shock p o ein amily A (Hsp70) membe 9 GO:0048388 ENSG00000033627 ATP6V0A1 ATPase H+ anspo ing V0 subuni a1 ENSG00000114573 ATP6V1A ATPase H+ anspo ing V1 subuni A ENSG00000100554 ATP6V1D ATPase H+ anspo ing V1 subuni D ENSG00000071553 ATP6AP1 ATPase H+ anspo ing accesso y p o ein 1 ENSG00000128524 ATP6V1F ATPase H+ anspo ing V1 subuni F ENSG00000117410 ATP6V0B ATPase H+ anspo ing V0 subuni b ENSG00000047249 ATP6V1H ATPase H+ anspo ing V1 subuni H GO:0061795 ENSG00000114573 ATP6V1A ATPase H+ anspo ing V1 subuni A ENSG00000100554 ATP6V1D ATPase H+ anspo ing V1 subuni D ENSG00000065923 SLC9A7 solu e ca ie amily 9 membe A7 ENSG00000071553 ATP6AP1 ATPase H+ anspo ing accesso y p o ein 1 ENSG00000128524 ATP6V1F ATPase H+ anspo ing V1 subuni F ENSG00000117410 ATP6V0B ATPase H+ anspo ing V0 subuni b ENSG00000047249 ATP6V1H ATPase H+ anspo ing V1 subuni H GO:0036295 ENSG00000105974 CAV1 ca eolin 1 GO:0048388 ENSG00000033627 ATP6V0A1 ATPase H+ anspo ing V0 subuni a1 ENSG00000114573 ATP6V1A ATPase H+ anspo ing V1 subuni A ENSG00000100554 ATP6V1D ATPase H+ anspo ing V1 subuni D ENSG00000071553 ATP6AP1 ATPase H+ anspo ing accesso y p o ein 1 ENSG00000128524 ATP6V1F ATPase H+ anspo ing V1 subuni F ENSG00000117410 ATP6V0B ATPase H+ anspo ing V0 subuni b ENSG00000047249 ATP6V1H ATPase H+ anspo ing V1 subuni H GO:0043201 ENSG00000133706 LARS1 leucyl- RNA syn he ase 1 ENSG00000025039 RRAGD Ras ela ed GTP binding D ENSG00000121879 PIK3CA phospha idylinosi ol-4,5-bisphospha e 3-kinase ca aly ic subuni alpha ENSG00000141564 RPTOR egula o y associa ed p o ein o MTOR complex 1 ENSG00000108443 RPS6KB1 ibosomal p o ein S6 kinase B1 GO:0097401 ENSG00000033627 ATP6V0A1 ATPase H+ anspo ing V0 subuni a1 ENSG00000114573 ATP6V1A ATPase H+ anspo ing V1 subuni A ENSG00000100554 ATP6V1D ATPase H+ anspo ing V1 subuni D ENSG00000159720 ATP6V0D1 ATPase H+ anspo ing V0 subuni d1 ENSG00000071553 ATP6AP1 ATPase H+ anspo ing accesso y p o ein 1 ENSG00000128524 ATP6V1F ATPase H+ anspo ing V1 subuni F ENSG00000047249 ATP6V1H ATPase H+ anspo ing V1 subuni H ENSG00000136888 ATP6V1G1 ATPase H+ anspo ing V1 subuni G1 GO:0030150 ENSG00000154174 TOMM70 anslocase o ou e mi ochond ial memb ane 70 ENSG00000120675 DNAJC15 DnaJ hea shock p o ein amily (Hsp40) membe C15 ENSG00000126768 TIMM17B anslocase o inne mi ochond ial memb ane 17B ENSG00000104980 TIMM44 anslocase o inne mi ochond ial memb ane 44 ENSG00000109519 GRPEL1 G pE like 1, mi ochond ial ENSG00000130204 TOMM40 anslocase o ou e mi ochond ial memb ane 40 GO:0030150 ENSG00000154174 TOMM70 anslocase o ou e mi ochond ial memb ane 70 ENSG00000120675 DNAJC15 DnaJ hea shock p o ein amily (Hsp40) membe C15 ENSG00000126768 TIMM17B anslocase o inne mi ochond ial memb ane 17B ENSG00000104980 TIMM44 anslocase o inne mi ochond ial memb ane 44 ENSG00000109519 GRPEL1 G pE like 1, mi ochond ial ENSG00000130204 TOMM40 anslocase o ou e mi ochond ial memb ane 40 Con inued in he nex page. Te m ID Ensembl ID Gene Name Gene Desc ip ion GO:0007042 ENSG00000033627 ATP6V0A1 ATPase H+ anspo ing V0 subuni a1 ENSG00000114573 ATP6V1A ATPase H+ anspo ing V1 subuni A ENSG00000100554 ATP6V1D ATPase H+ anspo ing V1 subuni D o ou e mi ochond ial memb ane 70 ENSG00000071553 ATP6AP1 ATPase H+ anspo ing accesso y p o ein 1 ENSG00000128524 ATP6V1F ATPase H+ anspo ing V1 subuni F ENSG00000117410 ATP6V0B ATPase H+ anspo ing V0 subuni b ENSG00000047249 ATP6V1H ATPase H+ anspo ing V1 subuni H GO:0007035 ENSG00000033627 ATP6V0A1 ATPase H+ anspo ing V0 subuni a1 ENSG00000114573 ATP6V1A ATPase H+ anspo ing V1 subuni A ENSG00000100554 ATP6V1D ATPase H+ anspo ing V1 subuni D o ou e mi ochond ial memb ane 70 ENSG00000159720 ATP6V0D1 ATPase H+ anspo ing V0 subuni d1 ENSG00000128524 ATP6V1F ATPase H+ anspo ing V1 subuni F ENSG00000117410 ATP6V0B ATPase H+ anspo ing V0 subuni b ENSG00000047249 ATP6V1H ATPase H+ anspo ing V1 subuni H GO:0043038 ENSG00000113643 RARS1 a ginyl- RNA syn he ase 1 ENSG00000140105 WARS1 yp ophanyl- RNA syn he ase 1 ENSG00000116120 FARSB phenylalanyl- RNA syn he ase subuni be a ENSG00000166986 MARS1 me hionyl- RNA syn he ase 1 ENSG00000139131 YARS2 y osyl- RNA syn he ase 2 ENSG00000133706 LARS1 leucyl- RNA syn he ase 1 ENSG00000031698 SARS1 se yl- RNA syn he ase 1 ENSG00000106105 GARS1 glycyl- RNA syn he ase 1 ENSG00000196305 IARS1 isoleucyl- RNA syn he ase 1 ENSG00000179115 FARSA phenylalanyl- RNA syn he ase subuni alpha ENSG00000113407 TARS1 h eonyl- RNA syn he ase 1 ENSG00000134440 NARS1 aspa aginyl- RNA syn he ase 1 ENSG00000110619 CARS1 cys einyl- RNA syn he ase 1 ENSG00000115866 DARS1 aspa yl- RNA syn he ase 1 GO:0035354 ENSG00000137462 TLR2 oll like ecep o 2 ENSG00000174125 TLR1 oll like ecep o 1 GO:0033180 ENSG00000114573 ATP6V1A ATPase H+ anspo ing V1 subuni A ENSG00000100554 ATP6V1D ATPase H+ anspo ing V1 subuni D ENSG00000128524 ATP6V1F ATPase H+ anspo ing V1 subuni F ENSG00000047249 ATP6V1H ATPase H+ anspo ing V1 subuni H ENSG00000136888 ATP6V1G1 ATPase H+ anspo ing V1 subuni G1 GO:0017101 ENSG00000113643 RARS1 a ginyl- RNA syn he ase 1 ENSG00000166986 MARS1 me hionyl- RNA syn he ase 1 ENSG00000133706 LARS1 leucyl- RNA syn he ase 1 ENSG00000196305 IARS1 isoleucyl- RNA syn he ase 1 ENSG00000115866 DARS1 aspa yl- RNA syn he ase 1 KEGG:00970 ENSG00000113643 RARS1 a ginyl- RNA syn he ase 1 ENSG00000140105 MARS1 me hionyl- RNA syn he ase 1 ENSG00000116120 LARS1 leucyl- RNA syn he ase 1 ENSG00000166986 IARS1 isoleucyl- RNA syn he ase 1 ENSG00000139131 DARS1 aspa yl- RNA syn he ase 1 ENSG00000133706 IARS1 isoleucyl- RNA syn he ase 1 ENSG00000031698 IARS1 isoleucyl- RNA syn he ase 1 ENSG00000106105 IARS1 isoleucyl- RNA syn he ase 1 ENSG00000196305 IARS1 isoleucyl- RNA syn he ase 1 ENSG00000179115 IARS1 isoleucyl- RNA syn he ase 1 ENSG00000113407 IARS1 isoleucyl- RNA syn he ase 1 ENSG00000134440 IARS1 isoleucyl- RNA syn he ase 1 ENSG00000110619 IARS1 isoleucyl- RNA syn he ase 1 ENSG00000115866 IARS1 isoleucyl- RNA syn he ase 1 ENSG00000166986 IARS1 isoleucyl- RNA syn he ase 1 ENSG00000103707 IARS1 isoleucyl- RNA syn he ase 1 Con inued in he nex page. Te m ID Ensembl ID Gene Name Gene Desc ip ion KEGG:04966 ENSG00000033627 ATP6V0A1 ATPase H+ anspo ing V0 subuni a1 ENSG00000114573 ATP6V1A ATPase H+ anspo ing V1 subuni A ENSG00000100554 ATP6V1D ATPase H+ anspo ing V1 subuni D ENSG00000159720 ATP6V0D1 ATPase H+ anspo ing V0 subuni d1 ENSG00000128524 ATP6V1F ATPase H+ anspo ing V1 subuni F ENSG00000136888 ATP6V1G1 ATPase H+ anspo ing V1 subuni G1 KEGG:00071 ENSG00000155016 CYP2U1 cy och ome P450 amily 2 sub amily U membe 1 ENSG00000167969 ECI1 enoyl-CoA del a isome ase 1 ENSG00000122971 ACADS acyl-CoA dehyd ogenase sho chain ENSG00000115361 ACADL acyl-CoA dehyd ogenase long chain ENSG00000072778 ACADVL acyl-CoA dehyd ogenase e y long chain ENSG00000138029 HADHB hyd oxyacyl-CoA dehyd ogenase i unc ional mul ienzyme complex subuni be a ENSG00000157184 CPT2 ca ni ine palmi oyl ans e ase 2 ENSG00000167315 ACAA2 ace yl-CoA acyl ans e ase 2 ENSG00000105607 GCDH glu a yl-CoA dehyd ogenase REAC:R-HSA-629597 ENSG00000080644 CHRNA3 choline gic ecep o nico inic alpha 3 subuni ENSG00000120903 CHRNA2 choline gic ecep o nico inic alpha 2 subuni ENSG00000147432 CHRNB3 choline gic ecep o nico inic be a 3 subuni ENSG00000147434 CHRNA6 choline gic ecep o nico inic alpha 6 subuni Table 15: Lis o go e ms and hei associa e gene names and desc ip ions o he compa a i e analysis o No h s Sou h o ch onic expe imen s. Te m ID Ensembl ID Gene Name Gene Desc ip ion GO:0004062 ENSG00000197165 SULT1A2 sul o ans e ase amily 1A membe 2 ENSG00000173597 SULT1B1 sul o ans e ase amily 1B membe 1 ENSG00000196502 SULT1A1 sul o ans e ase amily 1A membe 1 ENSG00000198203 SULT1C2 sul o ans e ase amily 1C membe 2 GO:0061809 ENSG00000196083 IL1RAP in e leukin 1 ecep o accesso y p o ein ENSG00000174125 TLR1 oll like ecep o 1 ENSG00000174130 TLR6 oll like ecep o ENSG00000136869 TLR4 oll like ecep o 4 ENSG00000174125 TLR1 oll like ecep o 1 GO:0022848 ENSG00000174343 CHRNA9 choline gic ecep o nico inic alpha 9 subuni ENSG00000101204 CHRNA4 choline gic ecep o nico inic alpha 4 subuni ENSG00000120903 CHRNA2 choline gic ecep o nico inic alpha 2 subuni ENSG00000080644 CHRNA3 choline gic ecep o nico inic alpha 3 subuni ENSG00000147434 CHRNA6 choline gic ecep o nico inic alpha 6 subuni GO:0005231 ENSG00000174343 CHRNA9 choline gic ecep o nico inic alpha 9 subuni ENSG00000101204 CHRNA4 choline gic ecep o nico inic alpha 4 subuni ENSG00000120903 CHRNA2 choline gic ecep o nico inic alpha 2 subuni ENSG00000080644 CHRNA3 choline gic ecep o nico inic alpha 3 subuni ENSG00000147434 CHRNA6 choline gic ecep o nico inic alpha 6 subuni GO:0072349 ENSG00000165449 SLC16A9 solu e ca ie amily 16 membe 9 ENSG00000004864 SLC25A13 solu e ca ie amily 25 membe 13 ENSG00000152779 SLC16A12 SLC16A12 ENSG00000142494 SLC47A1 solu e ca ie amily 47 membe 1 ENSG00000268104 SLC6A14 solu e ca ie amily 6 membe 14 ENSG00000138074 SLC5A6 solu e ca ie amily 5 membe 6 ENSG00000103064 SLC7A6 solu e ca ie amily 7 membe 6 GO:0140359 ENSG00000154265 ABCA5 ATP binding casse e sub amily A membe 5 ENSG00000143921 ABCG8 ATP binding casse e sub amily G membe 8 ENSG00000119688 ABCD4 ATP binding casse e sub amily D membe 4 ENSG00000165029 ABCA1 ATP binding casse e sub amily A membe 1 ENSG00000103222 ABCC1 ATP binding casse e sub amily C membe 1 ENSG00000135776 ABCB10 ATP binding casse e sub amily B membe 10 ENSG00000160179 ABCG1 ATP binding casse e sub amily G membe 1 ENSG00000167972 ABCA3 ATP binding casse e sub amily A membe 3 Te m ID Ensembl ID Gene Name Gene Desc ip ion GO:0016242 ENSG00000181852 RNF41 ing inge p o ein 41 ENSG00000145016 RUBCN ubicon au ophagy egula o ENSG00000121879 PIK3CA phospha idylinosi ol-4,5-bisphospha e 3-kinase ca aly ic subuni alpha ENSG00000188906 LRRK2 leucine ich epea kinase 2 ENSG00000171055 FEZ2 ascicula ion and elonga ion p o ein ze a 2 ENSG00000198793 MTOR mechanis ic a ge o apamycin kinase ENSG00000141458 NPC1 NPC in acellula choles e ol anspo e 1 GO:0046164 ENSG00000175066 GK5 glyce ol kinase 5 ENSG00000115234 SNX17 so ing nexin 17 ENSG00000197165 SULT1A2 sul o ans e ase amily 1A membe 2 ENSG00000173597 SULT1B1 sul o ans e ase amily 1B membe 1 ENSG00000196502 SULT1A1 sul o ans e ase amily 1A membe 1 ENSG00000149476 TKFC iokinase and FMN cyclase ENSG00000140263 SORD o bi ol dehyd ogenase ENSG00000198074 AKR1B10 aldo-ke o educ ase amily 1 membe B10 GO:0072337 ENSG00000165449 SLC16A9 solu e ca ie amily 16 membe 9 ENSG00000081479 LRP2 LDL ecep o ela ed p o ein 2 ENSG00000004864 SLC25A13 solu e ca ie amily 25 membe 13 ENSG00000152779 SLC16A12 solu e ca ie amily 16 membe 12 ENSG00000142494 SLC47A1 solu e ca ie amily 47 membe 1 ENSG00000268104 SLC6A14 solu e ca ie amily 6 membe 14 ENSG00000138074 SLC5A6 solu e ca ie amily 5 membe 6 ENSG00000103064 SLC7A6 solu e ca ie amily 7 membe 6 GO:1901616 ENSG00000175066 GK5 glyce ol kinase 5 ENSG00000160868 CYP3A4 cy och ome P450 amily 3 sub amily A membe 4 ENSG00000166816 LDHD lac a e dehyd ogenase D ENSG00000115234 SNX17 so ing nexin 17 ENSG00000160868 CYP3A4 cy och ome P450 amily 3 sub amily A membe 4 ENSG00000197165 SULT1A2 sul o ans e ase amily 1A membe 2 ENSG00000173597 SULT1B1 sul o ans e ase amily 1B membe 1 ENSG00000196502 SULT1A1 sul o ans e ase amily 1A membe 1 ENSG00000149476 TKFC iokinase and FMN cyclase ENSG00000140263 SORD so bi ol dehyd ogenase ENSG00000198074 AKR1B10 aldo-ke o educ ase amily 1 membe B10 GO:0051899 ENSG00000135124 P2RX4 pu ine gic ecep o P2X 4 ENSG00000163681 SLMAP sa colemma associa ed p o ein ENSG00000049759 NEDD4L NEDD4 like E3 ubiqui in p o ein ligase ENSG00000188906 LRRK2 leucine ich epea kinase 2 ENSG00000001084 GCLC glu ama e-cys eine ligase ca aly ic subuni GO:0010507 ENSG00000181852 P2RX4 pu ine gic ecep o P2X 4 ENSG00000145016 SLMAP sa colemma associa ed p o ein ENSG00000132405 NEDD4L NEDD4 like E3 ubiqui in p o ein ligase ENSG00000025039 LRRK2 leucine ich epea kinase 2 ENSG00000121879 GCLC glu ama e-cys eine ligase ca aly ic subuni ENSG00000188906 LRRK2 leucine ich epea kinase 2 ENSG00000146872 LRRK2 leucine ich epea kinase 2 ENSG00000171055 LRRK2 leucine ich epea kinase 2 ENSG00000198793 LRRK2 leucine ich epea kinase 2 ENSG00000141564 LRRK2 leucine ich epea kinase 2 ENSG00000188906 LRRK2 leucine ich epea kinase 2 ENSG00000141458 LRRK2 leucine ich epea kinase 2 Te m ID Ensembl ID Gene Name Gene Desc ip ion GO:0005892 ENSG00000174343 CHRNA9 choline gic ecep o nico inic alpha 9 subuni ENSG00000101204 CHRNA4 choline gic ecep o nico inic alpha 4 subuni ENSG00000120903 CHRNA2 choline gic ecep o nico inic alpha 2 subuni ENSG00000080644 CHRNA3 choline gic ecep o nico inic alpha 3 subuni ENSG00000147434 CHRNA6 choline gic ecep o nico inic alpha 6 subuni KEGG:02010 ENSG00000154265 ABCA5 ATP binding casse e sub amily A membe 5 ENSG00000143921 ABCG8 ATP binding casse e sub amily G membe 8 ENSG00000119688 ABCD4 ATP binding casse e sub amily D membe 4 ENSG00000165029 ABCA1 ATP binding casse e sub amily A membe 1 ENSG00000107331 ABCA2 ATP binding casse e sub amily A membe 2 ENSG00000103222 ABCC1 ATP binding casse e sub amily C membe 1 ENSG00000135776 ABCB10 ATP binding casse e sub amily B membe 10 ENSG00000160179 ABCG1 ATP binding casse e sub amily G membe 1 ENSG00000167972 ABCA3 ATP binding casse e sub amily A membe 3 KEGG:00590 ENSG00000155016 CYP2U1 cy och ome P450 amily 2 sub amily U membe 1 ENSG00000186115 CYP4F2 cy och ome P450 amily 4 sub amily F membe 2 ENSG00000179593 ALOX15B a achidona e 15-lipoxygenase ype B ENSG00000179148 ALOXE3 a achidona e lipoxygenase 3 ENSG00000138109 CYP2C9 cy och ome P450 amily 2 sub amily C membe 9 ENSG00000159228 CBR1 ca bonyl educ ase 1 Table 16: Lis o go e ms and hei associa e gene names and desc ip ions o he compa a i e analysis o acu e expe imen s. Te m ID Ensembl ID Gene Name Gene Desc ip ion GO:0003756 ENSG00000143870 PDIA6 p o ein disul ide isome ase amily A membe 6 ENSG00000167004 PDIA3 p o ein disul ide isome ase amily A membe 3 ENSG00000155660 PDIA4 p o ein disul ide isome ase amily A membe 4 ENSG00000184164 CRELD2 cys eine ich wi h EGF like domains 2 GO:0016864 ENSG00000143870 PDIA6 p o ein disul ide isome ase amily A membe 6 ENSG00000167004 PDIA3 p o ein disul ide isome ase amily A membe 3 ENSG00000155660 PDIA4 p o ein disul ide isome ase amily A membe 4 ENSG00000184164 CRELD2 cys eine ich wi h EGF like domains 2 GO:0016701 ENSG00000129596 CDO1 cys eine dioxygenase ype 1 ENSG00000179477 ALOX12B a achidona e 12-lipoxygenase, 12R ype ENSG00000012779 ALOX5 a achidona e 5-lipoxygenase ENSG00000182551 ADI1 aci educ one dioxygenase 1 GO:0000098 ENSG00000129596 CDO1 cys eine dioxygenase ype 1 ENSG00000139631 CSAD cys eine sul inic acid deca boxylase ENSG00000151224 MAT1A me hionine adenosyl ans e ase 1A ENSG00000108578 BLMH bleomycin hyd olase GO:0034975 ENSG00000166598 HSP90B1 hea shock p o ein 90 be a amily membe 1 ENSG00000167004 PDIA3 p o ein disul ide isome ase amily A membe 3 ENSG00000044574 HSPA5 hea shock p o ein amily A (Hsp70) membe 5 ENSG00000179218 CALR cal e iculin ENSG00000102580 DNAJC3 DnaJ hea shock p o ein amily (Hsp40) membe C3 GO:0000096 ENSG00000129596 CDO1 cys eine dioxygenase ype 1 ENSG00000139631 CSAD cys eine sul inic acid deca boxylase ENSG00000151224 MAT1A me hionine adenosyl ans e ase 1A ENSG00000108578 BLMH bleomycin hyd olase ENSG00000182551 ADI1 aci educ one dioxygenase 1 Con inued in he nex page.