RSAT variation-tools: An accessible and flexible framework to predict the impact of regulatory variants on transcription factor binding

RSAT a ia ion- ools: An accessible and lexible amewo k o p edic he impac o egula o y a ian s on ansc ip ion ac o binding Wal e San ana-Ga cia a,b , Ma ia Rocha-Ace edo b , Lucia Rami ez-Na a o b , Y on Mbouamboua c, , Denis Thie y a , Mo gane Thomas-Chollie a , B uno Con e as-Mo ei a d,e , Jacques an Helden ,g, ⇑ , Alejand a Medina-Ri e a b,* a Ins i u de Biologie de l’ENS (IBENS), Dépa emen de biologie, École no male supé ieu e, CNRS, INSERM, Uni e si é PSL, 75005 Pa is, F ance b Labo a o io In e nacional de In es igación sob e el Genoma Humano, Uni e sidad Nacional Au ónoma de México, Campus Ju iquilla, Bl d Ju iquilla 3001, San iago de Que é a o 76230, Mexico c Fonda ion Congolaise pou la Reche che Médicale, B azza ille, People’s Republic o Congo d Es ación Expe imen al de Aula Dei-CSIC, Za agoza, Spain e Fundación ARAID, Za agoza, Spain Aix-Ma seille Uni , INSERM UMR S 1090, Theo y and App oaches o Genome Complexi y (TAGC), F-13288 Ma seille, F ance g CNRS, Ins i u F ançais de Bioin o ma ique, IFB-co e, UMS 3601, E y, F ance a icle in o A icle his o y: Recei ed 27 Ap il 2019 Recei ed in e ised o m 22 Sep embe 2019 Accep ed 25 Sep embe 2019 A ailable online 7 No embe 2019 Keywo ds: Regula o y a ian s T ansc ip ion ac o s Posi ion speci ic sco ing ma ix SNPs Binding mo i s abs ac Gene egula o y egions con ain sho and degene a ed DNA binding si es ecognized by ansc ip ion ac o s (TFBS). When TFBS ha bo SNPs, he DNA binding si e may be a ec ed, he eby al e ing he an- sc ip ional egula ion o he a ge genes. Such egula o y SNPs ha e been implica ed as causal a ian s in Genome-Wide Associa ion S udy (GWAS) s udies. In his s udy, we desc ibe imp o ed e sions o he p og ams Va ia ion- ools designed o p edic egula o y a ian s, and p esen ou case s udies o illus- a e hei usage and applica ions. In b ie , Va ia ion- ools acili a e i) ob aining a ia ion in o ma ion, ii) in e con e sion o a ia ion ile o ma s, iii) e ie al o sequences su ounding a ian s, and i ) calcu- la ing he change on p edic ed ansc ip ion ac o a ini y sco es be ween alleles, using mo i scanning app oaches. No ably, he ools suppo he analysis o haplo ypes. The ools a e included wi hin he well-main ained sui e Regula o y Sequence Analysis Tools (RSAT, h p:// sa .eu), and accessible h ough a web in e ace ha cu en ly enables analysis o i e me azoa and en plan genomes. Va ia ion- ools can also be used in command-line wi h any locally-ins alled Ensembl genome. Use s can inpu pe sonal collec ions o a ian s and mo i s, p o iding lexibili y in he analysis. Ó2019 The Au ho s. Published by Else ie B.V. on behal o Resea ch Ne wo k o Compu a ional and S uc u al Bio echnology. This is an open access a icle unde he CC BY-NC-ND license (h p://c ea i e- commons.o g/licenses/by-nc-nd/4.0/). 1. In oduc ion Genomic DNA sequence ha bo s he gene egula o y in o ma- ion necessa y spa ial and empo al gene exp ession pa e ns [38,31]. Gene egula o y egions encompass sho , highly edun- dan DNA mo i s ecognized by ansc ip ion ac o s (TF) [36]. These egula o y egions may con ain gene ic a ian s, Single Nucleo ide Polymo phisms (SNPs) o indels, ha al e he DNA TF binding si e (TFBS), and he eby he binding o TF [20]. Mo e- o e , i has been epo ed ha 93.7% o a ian s ha ha e been associa ed wi h human ai s o diseases ha e been ound o be loca ed in non-coding egions [43,40], and pa icula ly en iched in open ch oma in egions [57], indica ing ha hese a ian s h ps://doi.o g/10.1016/j.csbj.2019.09.009 2001-0370/Ó2019 The Au ho s. Published by Else ie B.V. on behal o Resea ch Ne wo k o Compu a ional and S uc u al Bio echnology. This is an open access a icle unde he CC BY-NC-ND license (h p://c ea i ecommons.o g/licenses/by-nc-nd/4.0/). Abb e ia ions: RSAT, Regula o y Sequence Analysis Tools; SNP, Single Nucleo- ide Polymo phism; TF, T ansc ip ion Fac o ; TFBS, T ansc ip ion Fac o Binding Si e; PSSM, Posi ion Speci ic Sco ing Ma ix; MPRA, Massi ely Pa allel Repo e Assays: MPRA; LD, Linkage Disequilib ium; sID, Re e ence SNP Iden i ie ; SOIs, SNPs o In e es ; GWAS, Genome Wide Associa ion S udies; CRM, Cis-Regula o y Module; eQTL, Exp ession Quan i a i e T ai Loci; ROC, Recei e Ope a ing Cha - ac e is ic; CEU, No he n Eu opeans om U ah. ⇑ Co esponding au ho s a : Labo a o io In e nacional de In es igación sob e el Genoma Humano, Uni e sidad Nacional Au ónoma de México, Campus Ju iquilla, Bl d Ju iquilla 3001, San iago de Que é a o 76230, México (Medina-Ri e a). Aix- Ma seille Uni , INSERM UMR S 1090, Theo y and App oaches o Genome Complexi y (TAGC), F-13288 Ma seille, F ance (J. an Helden ). E-mail add esses: [email p o ec ed] (J. an Helden), amedina@ liigh.unam.mx (A. Medina-Ri e a). Compu a ional and S uc u al Bio echnology Jou nal 17 (2019) 1415–1428 jou nal homepage: www.else ie .com/loca e/csbj may a ec ansc ip ional egula o y mechanisms, and he eby explain he obse ed pheno ypes. The Regula o y Sequence Analysis Tools (RSAT, h p:// sa .eu) [47,26] has es ablished i sel in he las 20 yea s as a majo so - wa e sui e dedica ed o he analysis o egula o y egions, wi h i e public se e s suppo ing mo e han 500 euka yo e and 9,000 p oka yo e genomes. Wi h a majo ocus on usabili y and accessi- bili y o use s wi h o wi hou o mal bioin o ma ics aining, RSAT p o ides ools o e ie e sequences, pe o m mo i s analysis, e al- ua e TF mo i quali y, compa e and clus e mo i s, con e ile o - ma s, e c. He e we desc ibe Va ia ion- ools, a subse o ools included in RSAT ha enable use s o analyse egula o y a ian s and assess hei pu a i e impac on TF binding si es. 1.1. Cu en app oaches o de ec ing po en ial egula o y a ian s The ac ha many a ian s a e loca ed in non-coding egions igge ed he de elopmen o bioin o ma ic ools o iden i y he egula o y po en ial o hese gene ic a ian s. S a ing om a lis o SNPs, compu a ional analyses can help o mula ing hypo heses on which TF may be impac ed by a gene ic a ian . Howe e , he e a e nume ous challenges o in silico analysis o un a el he impac o gene ic a ia ions in gene egula o y egions. Se e al ools and esou ces ha e been published, p o iding al e na i e me hods o ackle his p oblem (Table 1). Mos o hem a e ei he based on pa e n-ma ching app oaches o e alua e he impac o alleles on TF binding, o on machine lea ning models buil using unc ional anno a ions o he egula o y egions, e.g. epigenomics and an- sc ip omics da a. S ill, hese esou ces and ools ha e limi a ions hampe ing hei usage in se e al o ganisms [68,28,35], on new anno a ed a ian s [5,63,54], and/o on analyses wi h pe sonal col- lec ions o TF mo i s [68,28,41]. All ools in he Pa e n Ma ching ca ego y, (labeled PM in Table1) use Posi ion-Speci ic Sco ing Ma ices (PSSMs) o e alua e he a ini y o a TF o a gi en sequence wi h an allele. Majo di e - ences be ween hese ools can be ound in (i) hei a ailabili y: web pages [5], command line [12] o bo h [69]; (ii) lexibili y o he use o inpu hei own da a [61]; (iii) usabili y: he possibili y o use se e al a ian o ma s [28]; (i ) esul s ep esen a ion: ig- u es and/o ables [63]; ( ) a ailable o ganisms: only human [62], o o he o ganisms [61]; and ( i) he possibili y o calcula e esul s on- he- ly [41] o access p e-calcula ed ones [5]. Ano he se o ools (labeled ML in Table1) aim o he iden i i- ca ion o po en ial egula o y a ian s by in eg a ing se e al ypes o da a, beyond aking in o accoun po en ial dis up ion o TF bind- ing. Pa icula ly, Lee, e al. [37] in eg a ed DNaseI-seq da a wi h SVM app oaches o iden i y a ian s ha could po en ially dis up TF binding. DeepSea [68] in eg a es unc ional genomic da a om ChIP-seq, DNaseI-seq, RNA-seq and o he unc ional genomic high- h oughpu da a o assess he po en ial damage o a ian s ac oss he human genome. P ecalcula ed esul s o anno a ed a ian s can be accessed on hei websi e. Bo h ools can be ained on o he o ganisms, p o ided ha unc ional genomic da a a e a ailable. The main limi a ion o hese esou ces is he equi ed expe ise in bioin o ma ics and/o com- pu a ional esou ces o use s o analyse hei own da a se s. O he ools iden i y po en ial egula o y e ec s o a a ian by compa ing he measu ed a ini y o a TF o he di e en possible alleles. Ou ool, named a ia ion-scan, alls wi hin his ca ego y. 1.2. Va ia ion- ools In his con ex , we ha e de eloped Va ia ion- ools o add ess he main limi a ions iden i ied in exis ing p og ams (Table 1). Va ia ion- ools a e composed o ou p og ams ha enable (i) e ie al o in o ma ion o Ensembl anno a ed a ian s when a ail- able o a gi en genome in RSAT ( a ia ion-in o), (ii) con e sions be ween a ian ile o ma s (con e - a ia ions), (iii) e ie al o he sequences su ounding a ian s ( e ie e- a ia ion-seq), and (i ) scanning o di e en alleles o a a ian wi h one o se e al mo i s, compa ing he sco es and p- alues in o de o iden i y a ec ed TFBS ( a ia ion-scan)(Fig. 1). Ea lie e sions o hese p o- g ams we e epo ed in 2015 as pa o a RSAT upda e a icle [45], hese i s e sions we e de eloped in pe l and we e e ac o ed and imp o ed o he 2018 upda e [47]. In his a icle we p esen he la es e sions o he ools, wi h op imized memo y usage, and no el suppo o he inclusion o haplo ype in o ma ion. In summa y, RSAT Va ia ion- ools p o ide an accessible esou ce o expe ienced and non-expe use s o analyze egula o y a i- an s in a web in e ace o i een o ganisms ( i e me azoa (h p://me azoa. sa .eu) and en plan s (h p://plan s. sa .eu), wi h lexibili y o upload pe sonal a ian and PSSM collec ions. We desc ibe he e Va ia ion- ools me hodology, along wi h ou case s udies demons a ing he lexibili y o he ools, enabling he anal- ysis o da a se s om di e en o igin (Ensembl a ian s, Genome- Wide Associa ion S udy (GWAS) da a, ChIP-seq egions, e c.), com- plexi y, and o ganisms. 2. Me hods 2.1. Va ia ion- ools: om a ian s o iden i ica ion o egula o y e ec s Va ia ion- ools consis in a subse o ou ools wi hin RSAT de o ed o he iden i ica ion o gene ic a ian s pu a i ely a ec - ing TF binding 1) a ia ion-in o: his ool elies on he Ensembl gene ic a ia- ion in o ma ion [29] anno a ed and ins alled on he co e- sponding se e o each pa icula genome (i.e. human a ian s a e ins alled in he Me azoa se e ). I can ake wo di e en inpu s: 1) a ian sID o 2) genomic loci in bed o ma . This ool will e ie e he in o ma ion o he a ian s ma ching he IDs o he in o ma ion o he a ian s loca ed in he genomic loci. Va ian s ins alled in RSAT se - e s ha e been p ocessed o emo e a ian s wi h incom- ple e anno a ions (no alleles) o ambiguous coo dina es (non ma ching alleles coo dina es). When use s ha e hei own a ian s collec ions, hey can skip his ool and use di ec ly con e - a ia ions. 2) con e - a ia ions: enables he in e con e sion o a ian ile o ma s such as VCF, GVF and a Bed. a Bed is an in e nal o ma o RSAT ha acili a es he e ie al o he sequence su ounding he a ian (Supplemen a y Fig. 1A). 3) e ie e- a ia ion-seq: e ie es he sequence su ounding he a ian , and p oduces one sequence o each allele (Sup- plemen a y Fig. 1B). The ool can ake as inpu a a Bed ile (see con e - a ia ions). Fo o ganisms wi h Ensembl anno- a ed a ian s, i can ake a lis o IDs o a bed ile lis ing genomic loci. The ou pu is p o ided in a o ma named a - Seq, wi h each ow gi ing one allele wi h i s su ounding sequence. Each a ian has a speci ic in e nal ID o accom- moda e se e al a ian s wi h a ious alleles in he same ile. 4) a ia ion-scan: pe o ms he scanning o alleles wi h a PSSM and compa es he sco es and p- alues be ween alleles o assess he pu a i e e ec on TF binding (see de ails below) (Supplemen a y Fig. 2). I equi es as inpu a a Seq ile (see e ie e- a ia ion-seq), a mo i o collec ion o mo i s (o e wen y suppo ed ile o ma s), and a backg ound model ( o me hodological de ails on backg ound model, e e o [59] Box n°3). Di e en backg ound models a e ead- 1416 W. San ana-Ga cia e al./Compu a ional and S uc u al Bio echnology Jou nal 17 (2019) 1415–1428 Table 1 Tools simila o a ia ion-scan wi h a ailable implemen a ion. PM s ands o Pa e n Ma ching, ML s ands o Machine Lea ning. Name PMID Sou ce App oach O ganism Inpu Ou pu Ma ix lexibili y Type Las upda e del aSVM 26075791 h p://www. bee lab.o g/ del as m/ Gapped k-me SVM classi ie . Any o ganism DNaseI-seq da a; pu a i e egula o y egions as posi i e aining se and andomized sequences as nega i e aining se . del aSVM, p edic ed impac o a a ian in ch oma in accessibili y which is measu ed by adding up he con ibu ion o all 10-me s in which he SNP is p esen o ch oma in accessibili y. I can only be ained o one TF a a ime. ML, non- s a ic. Las upda e Sep 2015. DeepSea 26301843 h p://deepsea. p ince on.edu/ job/analysis/ c ea e/ Deep con olu ional ne wo k. Human SNPs in VCF o ma . Ch oma in ea u e p obabili ies o e e ence and al e na i e alleles, ch oma in ea u e p obabili y log old changes o each a ian , ch oma in ea u e p obabili y di e ences o each a ian s, e- alues o ch oma in ea u e e ec s, unc ional signi icance sco e o each a ian . The e a e 919 ch oma in ea u es e alua ed. I con ains 690 TF binding p o iles o 160 di e en TFs, bu does no suppo he addi ion o new ma ices. ML, non- s a ic. Las upda e May 2017. a SNP 26092860 h ps:// gi hub.com/ keleslab/a SNP Impo ance sampling algo i hm o p- alue calcula ion, i s - o de Ma ko Model o gene a e andom backg ound sequences. Any o ganism whose genome is included in he Bioconduc o BSGenome package. SNP lis , mo i ile. p- alue o binding a ini y wi h al e na i e and e e ence allele, p- alue o binding a ini y change based on log-likelihood a io and log- ank a io. I also p o ides composi e logo plo s o di ec ly isualizing he SNP e ec s on mo i ma ches. I accep s se e al ma ices, and se e al di e en o ma s. I includes a mo i lib a y o 2,065 PSSMs om ENCODE and JASPAR, bu also allows use -de ined mo i lib a ies. PM, non- s a ic. Las upda e No 2018. BayesPI-BAR 26202972 h p:// olk.uio.no/ junbaiw/BayesPI- BAR/ Biophysical modeling o p o ein-DNA in e ac ion, es ima ion o TF chemical po en ial ( h ough a bayesian nonlinea eg ession model) and di e en ial binding a ini y. Any o ganism ChIP-seq expe imen o TFs o be es ed, DNA sequences o selec ed SNPs,PSSMs o selec ed TFs. Gi en a SNP and a PSSM lis , i p oduces wo lis s so ed by signi icance: one composed o binding mo i s dis up ed by he SNP, and one by si es wi h an inc eased a ini y o he TF caused by he SNP. Can use se e al PSSMs simul aneously. PM, biophysical modeling. Non-s a ic. No upda es lis ed, so wa e c ea ed July 2015. GWAS4D 29771388 h p://mulinlab. mu.edu.cn/ gwas4d/gwas4d/ gwas4d/gwas4d_ se e Va ian p io i iza ion me hod, ollowed by an in eg a i e analysis o genome-wide associa ion. Human Accep s VCF-like, coo dina e only, dbSNP ID and PLINK-like o ma s. Regula o y a ian p io i iza ion able: includes he mos likely a ec ed mo i by al e na i e a ian e ec . The model includes mo i s o 1,480 ansc ip ional egula o s om 13 di e en esou ces. I is no possible o upload use - speci ied ma ices. PM, s a ic Las upda e Sep 2018. sTRAP 20127973 h p:// ap.molgen. mpg.de/cgi-bin/ home.cgi P edic ion o local binding a ini y ollowed by a no maliza ion o binding a ini ies o de e mine di e ence be ween e e ence allele and SNP. O ganisms a ailable in TRANSFAC. Accep s only wo sequences in FASTA o ma . Lis o TFs anked acco ding o changes induced by he SNP. The e is no op ion o use -speci ied ma ices, ma ices om TRANSFAC e sions can be selec ed. PM, non- s a ic No upda es lis ed, so wa e c ea ed in 2011. (con inued on nex page) W. San ana-Ga cia e al./Compu a ional and S uc u al Bio echnology Jou nal 17 (2019) 1415–1428 1417 Table 1 (con inued) Name PMID Sou ce App oach O ganism Inpu Ou pu Ma ix lexibili y Type Las upda e SNP2TFBS 27899579 h ps://ccg.ep l. ch//snp2 bs/ Es ima ion based on PSSM model. Human. When wo king wi h he code, he inpu equi ed is he e e ence genome, a SNP ca alogue and a PSSM collec ion. The web in e ace accep s SNP IDs and VCF o ma , as well as a speci ica ion o a genomic egion h ough a bed ile o by speci ying he s a and end posi ions. Lis o a ec ed TFBSs, so ed by he magni ude o he e ec s. On he web in e ace, only ma ices om JASPAR can be used. None heless, i is possible o download he code used o gene a e he da abase and use a di e en inpu . PM, s a ic. Las upda e July 2017. a SNP Sea ch 30534948 h p://a snp. bios a .wisc.edu/ Used a SNP algo i hm wi h dbSNP build 144 o human genome assembly 38 agains JASPAR and Encode mo i s o c ea e a eposi o y wi h all he SNP-mo i combina ions esul ing om he p e ious esou ces. Human. I can ecei e a se o sIDs, a sID and a window size a ound he SOI, genomic coo dina es, a gene symbol and a window size a ound he gene o in e es , o a TF name. Table including p- alues o mo i ma ches o bo h e e ence and al e na e alleles, as well as he change in he mo i ma ching and he di ec ion o said change. Ou pu includes logo plo s, displaying he sequence logos aligned o bes mo i ma ches wi h e e ence and SNP alleles. Only JASPAR o ENCODE ma ices can be selec ed, and i is possible o selec only one ansc ip ion ac o a a ime. PM, s a ic. Las upda e Jan 2018. HaploReg 22064851, 26657631 h ps://pubs. b oadins i u e. o g/mammals/ haplo eg/haplo eg. php I con ains da a om mul iple genome anno a ion esou ces. PSSMs a e sco ed agains e e ence and al e na i e alleles, and change in log-odds is calcula ed. Human Use s can p o ide a lis o sIDs o ch omosome egions. Use s can also selec GWAS s udies om he NHGRI ca alog. P o ides da a on allelic equencies, conse a ion, ch oma in s a es, and nea genes. Fo each o he egula o y mo i s al e ed by he SNP, i p o ides he change in log-odds and a logo. HaploReg con ains a lib a y c ea ed om li e a u e sou ces, TRANSFAC, JASPAR and PBM expe imen s. The e is no op ion o use - speci ied ma ices. PM, s a ic. Las upda e No embe 2015. RegulomeDB 22955989 h p://www. egulomedb.o g/ RegulomeDB uses in o ma ion om se e al da ase s, as well as manual cu a ion and a heu is ic me hod o dis inguish be ween unc ional and non- unc ional a ian s. Human. Use s can p o ide a lis o dbSNP IDs, hg19 coo dina es in BED, VCF o GFF3 o ma , o hg19 ch omosomal egions in he same o ma s. Table so ed by likely unc ionali y, con aining a ian coo dina es, sco e assigned by he algo i hm, and e idence o unc ion including p o ein binding, mo i s, ch oma in s uc u e, eQTLs and his one modi ica ions. RegulomeDB includes all PSSMs om TRANSFAC, JASPAR CORE, and UniP obe. The e is no op ion o use -speci ied ma ices. PM, s a ic. No upda es, lis ed, so wa e c ea ed in Sep 2012. mo i b eakR 26272984 h ps:// gi hub.com/ Simon-Coe zee/ Mo i B eakR I has h ee op ions o algo i hms: he s anda d sum o log p obabili ies, weigh ed sum, and an in o ma ion con en me hod. O ganisms included in BSgenome. SNPs can be impo ed om an R package o p o ided o he algo i hm in BED o VCF o ma . PSSMs can be selec ed om he Mo i Db package o be use - speci ied. Table con aining s a is ics desc ibing he pe cen o maximum sco e o a ma ix and ma ix alues o bo h alleles, as well as he s and. I also epo s whe he he TFBS is dis up ed s ongly o weakly. PSSMs can be impo ed om he Mo i Db package o be use - speci ied. Mo e han one ma ix can be used a a ime. PM, non- s a ic. Las upda e Jul 2018. a ia ion- scan h p:// sa .eu Es ima ion based on PSSM model. web in e ace: ins alled Ensembl o ganisms. command- line: any locally ins alled o ganism. A collec ion o PSSMs and a se o a ian s in a Seq o ma . This o ma can be ob ained using e ie e- a ia ion-seq. A able wi h one line pe pai o alleles pe mo i (i he e a e mo e han wo, he e will be one line pe possible pai ) epo ing he posi ion, weigh and p- alue o each allele, weigh di e ence and p- alue a io. Use s can selec o he collec ions a ailable in RSAT (JASPAR, HOCOMOCO, CisBP), bu hey can also use pe sonal collec ions. PM-non s a ic. Ap il 2019. 1418 W. San ana-Ga cia e al./Compu a ional and S uc u al Bio echnology Jou nal 17 (2019) 1415–1428 ily a ailable h ough he web in e ace. Howe e , depending on he biological ques ion and ela ed po en ial biases, we ecommend he c ea ion o a dedica ed backg ound model, which can be done using he RSAT ool c ea e-backg ound, also a ailable ia he RSAT web in e ace. 2.2. Haplo ype p ocessing Gene ic a ian s can be de ec ed using high- h oughpu ech- niques. This has enabled he iden i ica ion o millions o a ian s in he HapMap [30] and 1000 genomes p ojec s [1]. Howe e , he in o ma ion on he a ian s alone is less use ul han knowing which g oups o alleles a e co-loca ed on he same ch omosome (haplo ype). The p ocess o iden i ying he a ian s ha belong o each ch omosome is known as phasing. Including haplo ype phasing in o ma ion acili a es he iden i ica ion o ela ions be ween a ian s [6]. VCF iles can include haplo ype phasing in o ma ion. The ool con e - a ia ions iden i ies and e ie es he phasing in o ma ion o he a ian s, while he ool e ie e- a ia ion-seq buil s he co - esponding haplo ype wi h all he SNPs ha lay wi hin a de ined window (de aul : 30 bp). 2.3. Compu ing binding speci ici y o a ansc ip ion ac o o a DNA sequence a ia ion-scan uses PSSMs o assess he binding speci ici y o a TF o a DNA sequence wi h di e en alleles in a gi en posi ion. The i s s ep o a ia ion-scan (i.e., scanning o he sequences wi h a gi en PSSM) is delega ed o he RSAT ool ma ix-scan. The sco - ing scheme and p- alue calcula ion a e desc ibed in de ail in [59], Box n°1 and Box n°2, espec i ely. In b ie : PSSM a e used o assess he binding speci ici y o a TF. This a ini y is calcula ed as a weigh sco e (Ws). The Ws o a si e in a ia ion-scan is calcula ed using [27]: Ws ¼lnðPðSjMÞ PðSjBÞ  whe e S is a sequence segmen o he same leng h o M, M is he PSSM, and B is he backg ound model. Hence, P(S|M) is he p obabil- i y o he sequence gi en he PSSM and P(S|B) is he p obabili y o he sequence gi en he backg ound model. Ws has been ela ed o he a ini y o he TF o he sequence, as i assesses simila i y o a sequence o a known se o binding si es, p o iding in o ma ion abou he p obabili y o a sequence o be a new ins ance o a bind- ing si e [56]. Mo eo e , i is possible o calcula e he p- alue o a gi en sco e as: P alue ¼PðWwjBÞ whe e he P- alue is calcula ed as he p obabili y o obse ing a sco e o a leas Wgi en a backg ound model w|B. When a sequence is longe han he PSSM, he PSSM is shi ed base by base un il he ull sequence has been sco ed. This scanning s ep is pe o med on he sequences o all epo ed alleles, so ha each allele is compa ed wi h all he posi ions o a gi en mo i . Backg ound models ep esen he nucleo ide composi ion o a se o sequences (whole genome, all p omo e sequences, e c.). These models a e used o es ima e he expec ancy o a nucleo ide being ound. Backg ound models can ep esen dependency be ween nucleo ides in sequences (e.g. aking in o accoun he e- Fig. 1. Schema ic ep esen a ion o Va ia ion- ools: This se o ools, included in he Regula o y Sequence Analysis Tools (RSAT), ocuses on assessing he impac o di e en allelic a ian s on T ansc ip ion ac o binding si es. A) con e - a ia ions allows use s o inpu hei own a ian s and con e hem o o he o ma s (VCF, GVF and a Bed, he la e is he o ma used in he nex s ep), while a ia ion-in o e ie es he anno a ed in o ma ion o Ensembl a ian s ins alled in RSAT se e s. B) The ool e ie e- a ia ion-seq e ie es he su ounding sequence o a ian s (including possible haplo ypes) and gene a es a ex ile wi h one line pe allele and pe a ian o haplo ype ( a Seq o ma ). C) Use s can inpu hei a ian s in a Seq o ma and a collec ion o mo i s (di ec inpu by he use o selec ed om RSAT a ailable collec ions) o a ia ion- scan; he ool hen scans he co esponding sequences wi h all mo i s and pe o m pai wise compa isons be ween he binding sco es o each ansc ip ion ac o on o all alleles o a a ian o haplo ype. W. San ana-Ga cia e al./Compu a ional and S uc u al Bio echnology Jou nal 17 (2019) 1415–1428 1419 quencies o dinucleo ides o build a Ma ko model o o de 1 [59] Box n°3). As backg ound models a e used o calcula e weigh sco es o a binding si e (P(S|B)), i is impo an o selec an app o- p ia e model o each analysis. Examples o selec ed backg ound models a e p esen ed in he di e en s udy cases ma ching each pa icula biological ques ion. 2.4. Assessmen o allele e ec on ansc ip ion ac o binding In he second s ep, i.e., e alua ing he impac o SNPs, a ia ion- scan compa es he ob ained Ws (Ws di e ence = Ws_Allele1 – Ws_Alelle2) and he P- alue (P- alue a io = P- alue_Allele1/P- al ue_Allele2) o each o he alleles, posi ion by posi ion h oughou he scanning window. To e alua e indels, a ia ion-scan compa es he highes Ws and i s co esponding P- alue o each sequence o he epo ed alleles. When mo e han wo alleles o a a ian a e epo ed, all alleles a e compa ed o all alleles in a pai wise manne . 2.5. a ia ion-scan pe o mance es 2.5.1. Compu ing e iciency The ools a ia ion-in o and con e - a ia ion a e coded in Pe l, while e ie e- a ia ion-seq and a ia ion-scan a e coded in C, o enable he analysis o la ge numbe s o a ian s om euka yo ic genomes in a easonable ime. To u he imp o e pe o mance, we educed he da a ans e om he ha d d i e o memo y. a ia ion-scan pe o mance was assessed by andomly selec ing a a ian om he 1000 genomes p ojec [1] and a mo i om he RSAT non- edundan mo i s collec ion [8]. The andomly selec ed a ian was used o c ea e se s wi h di e en numbe s o epli- ca es, anging om one housand o nine millions, o es ima e he ela ion be ween unning ime and he amoun o e alua ed a ian s. The p ocesses we e un on a Dell Powe Edge C6145 se e wi h 2 AMD Op e on( m) P ocesso 6386 SE, 16 co es each, P oces- so speed o 2.8–3.5 Ghz, RAM 256 Gb and wi h an ope a ing sys- em Cen OS 7 (7.6.1810). 2.5.2. Da ase : expe imen ally-de e mined egula o y a ian s in ed blood cells The egula o y ac i i y o 2,756 ed blood cell a ian s has been sys ema ically measu ed using Massi ely Pa allel Repo e Assays (MPRA) [60]. MPRA is a high- h oughpu assay in which a lib a y o pu a i e egula o y elemen s, each ollowed by a unique ba - code, is inse ed in o a plasmid, hen ans ec ed in o a cell, and ansc ip s a e hen quan i ied h ough he abundance o ba codes. These a ian s a e known o be in s ong linkage disequilib ium (LD) wi h 75 a ian s associa ed wi h common ai s o his cell ype. Th ee sliding windows pe a ian (le , igh , and cen e ) we e syn hesized, ba coded and used o s udy he e ec o sligh changes in hei genomic con ex . Following me hods desc ibed by Uli sch, e al.[60], o each sequence mRNA/DNA a io was com- pu ed o ob ain a quan i a i e e alua ion o he egula o y e ec o a sequence a ian . 2.5.3. E alua ion o a ia ion-scan The a ian da ase was used as inpu o a ia ion-scan; he a ian s assessed in he ed blood cell assay we e anno a ed wi h he Ensembl GRCh37 human genome elease, and gi en as inpu o con e - a ia ions ollowed by e ie e- a ia ion-seq. Since h ee sliding windows we e used o each a ian in he MPRA, he co - esponding windows we e me ged be o e compu ing a backg ound model using he c ea e-backg ound-model ool. Acco ding o he o iginal s udy [60], binding si es o he ol- lowing TF we e en iched in he sequences o in e es : GATA1, KLF1, DHS, TAL1, ETS, FLI1 and AP-1. The e o e, a o al o 48 PSSMs anno a ed as ela ed o hese TF we e e ie ed om he non- edundan RSAT mo i collec ion [8], and gi en as inpu o a ia ion-scan. A nega i e con ol se o mo i s was c ea ed using he RSAT ool pe mu e-ma ix [47]; i e pemu ed mo i s we e c ea ed o each o he 48 mo i s, gene a ing a collec ion o 240 con ol mo i s. Fo a a ian o be epo ed in a ia ion-scan as posi i e,we eques ed ha a leas one o he allele sequences was e alua ed as a binding si es wi h a p- alue o a mos 10 4 (using he pa am- e e -u h p al 1e-4 in he command line), and ha he p- alue a io was g ea e o equal o en (a change o one o de o magni ude be ween he bes and he wo s allele p- alues) (-l h p al_ a io 10). We compa ed a ia ion-scan o wo o he ools p e iously used o assess he same se o a ian s by Uli sch, e al. [60]: DeepSea [50] and [37] del aSVM. In o de o a oid pe sonal biases when cal- ib a ing ool pa ame e s, we decided o ely on he published ones [60]. Fo his analysis a ia ion-scan was un wi hou h esholds o iden i y he impac o he pa ame e s, pa icula ly he h eshold on p- alue a io. 2.6. Case s udies 2.6.1. Case s udy 1: Iden i ica ion o egula o y a ian s in he ‘‘Pla inum”genomes haplo ypes The se o high-con idence a ian s om he wo CEU (No he n Eu opeans om U ah) human Pla inum Genomes NA12877 and NA12878 [23] we e downloaded h ough he Amazon Web Se ice (AWS) Command Line In e ace om he Illumina Pla inum Gen- omes AWS S3 bucke (h ps://gi hub.com/Illumina/Pla - inumGenomes). The downloaded VCF iles con ained phasing in o ma ion o each CEU indi idual haplo ype con igu a ion. The genome e sion used was GRCh37. We selec ed SNPs in e sec ing wi h he anno a ed DNAseI-seq clus e ed peaks V3 om he ENCODE p ojec [4]. The VCF ile wi h he selec ed SNPs was p ocessed using con e - a ia ions wi h he op ion phased and hen he haplo ype sequences we e econ- s uc ed wi h e ie e- a ia ion-seq. Fo a haplo ype SNP se o single posi ion a ian s o be epo ed in a ia ion-scan, we eques ed ha a leas one o he sequences was e alua ed as a binding si e wi h a p- alue o a mos 10 4 (-u h p al 1e-4) and ha he p- alue a io be ween he wo alleles was g ea e o equal o 100 (a change o wo o de s o mag- ni ude be ween he bes and he wo s alleles p- alues) (-l h p al_ a io 100). In addi ion, we equi e a change o sign be ween he bes and wo s sco e as an addi ional il e . We anno a ed he p edic ed dis up ed TFBS wi h he TF ChIP- seq non- edundan peak collec ion and wi h he Cis-Regula o y Modules (CRM) egions om ReMap [10] using bed ools in e sec e sion 2.27 [49]. We also calcula ed he en ichmen o anno a- ions in he p o enance sequence segmen s o he p edic ed haplo- ypes si es. 2.6.2. Case s udy 2: p edic ion o egula o y a ian s associa ed wi h suscep ibili y o Mycobac e ium ube culosis in ec ion We collec ed SNPs associa ed wi h he pheno ypic ai ‘‘suscep- ibili y o Mycobac e ium ube culosis in ec ion measu emen ” (dis- ease ID EFO_0008407) om he 1.0.2 e sion o he GWAS ca alog [40] (h ps://www.ebi.ac.uk/gwas/). This que y e u ned one s udy [58] wi h 67 dis inc a ian s, o which 48 had a alid e e ence SNP iden i ie ( sID) and could be u he used (deno ed he ea e as disease-associa ed SNPs, o DA-SNPs). To p edic he TF binding si es pu a i ely a ec ed by hese selec ed SNPs, we designed an app oach combining Va ia ion- ools wi h di e en ex e nal esou ces. We u he collec ed om Ensembl REST in e - ace (h p:// es .ensembl.o g/) 564 SNPs in linkage disequilib ium 1420 W. San ana-Ga cia e al./Compu a ional and S uc u al Bio echnology Jou nal 17 (2019) 1415–1428 (LD-SNPs) in he Eu opean popula ion [62], wi h a h eshold on he eg ession coe icien ( 2 0.8) and a maximal dis ance o 200 bp. Anno a ions (ch omosomal loca ion, ype o genomic egion) o he esul ing 612 SNPs (48 DA + 564 LD) we e collec ed om Ensembl BioMa [22,21]. We hen es ic ed he selec ion o SNPs in non-coding egions, esul ing in a se o 572 SNPs o in e es (SOIs) o he de ec ion o egula o y a ian s. Using SNPs in LD, we de e mined LD-Block egions. These we e hen anno a ed based on o e laps wi h ChIP-seq peaks collec ed om he ReMap da a- base [10]. We also calcula ed en ichmen o disease anno a ions using he R XGR package [24]. Finally, we used e ie e- a ia ion-seq o e ie e he sequence a ian s a ound each SOI, and p edic ed he impac o he a ia ion on TF binding o each mo i o he JASPAR non- edundan RSAT mo i collec ion [8] using a ia ion-scan, wi h he h esholds o 1e-4 on he p- alue and 100 on he p- alue a io. 2.6.3. Case s udy 3: Assessmen o he egula o y e ec o GWAS epo ed a ian s in p omo e s wi h enhance unc ion The STARR-seq assay [2] is in i s p inciple simila o he MPRA, and helps iden i y sel - ansc ibing ac i e egula o y egions ha ha e enhance po en ial. Using his app oach Dao e al. [17], anal- ysed he enhance po en ial o anno a ed Re Seq p omo e s [48].In he wo cell lines K562 and HELA, hey iden i ied 632 and 493 p o- mo e s wi h enhance po en ial (eP omo e s), espec i ely. Mo e- o e , he au ho s iden i ied en ichmen o eQTL a ian s epo ed by GTEx [25]. To iden i y eP omo e s a ian s ha could be a ec ing TF bind- ing, we e ie ed he GWAS ca alog e sion 1.0 (downloaded on 7/01/19) [40]. Using bed ools o e lap e sion 2.26.0 [49], we com- pu ed he o e lap be ween SNPs and he eP omo e coo dina es epo ed in [17]. PSSMs ep esen ing TF en iched in eP omo e s we e also ob ained om [17], co esponding o SMRC1, JUN, FOS, ATF:MAF:NEF2, YY1, ETS amily, C eb and USF1/2. Using he selec ed GWAS a ian s ha all wi hin eP omo e s and he TF mo i s en iched in hese egions, we applied a ia ion- scan o assess he po en ial egula o y e ec o hese a ian s. a ia ion-scan was un wi h he pa ame e s – l h w_di 1 – l h p al_ a io 10, wi h a backg ound model buil using c ea e- backg ound wi h all Re Seq p omo e sequences. In o de o il a e a ian s wi h he highes pu a i e egula o y dis up ion, we u - he selec ed a ian s ha showed a change o sign in he weigh sco e be ween alleles. 2.6.4. Case s udy 4: iden i ica ion o egula o y a ian s a ec ing VRN1 binding in ba ley The la es e sion o Ho deum ulga e (ba ley) e e ence gen- ome [42] and a panel o mapped gene ic a ian s we e impo ed om Ensembl Genomes elease 42 [34] and ins alled in he RSAT Plan s se e (h p://plan s. sa .eu). We ob ained expe imen ally de e mined binding si es (ChIP-seq) o VRN1 om [19]. Since hese peaks we e o iginally posi ioned wi hin con igs o he 2012 genome assembly [14], hey had o be ma ched o he co espond- ing egions o he cu en assembly wi h BLAST + 2.9.0 (blas n) local alignmen s agains he epea -masked genome sequence (pe ec ma ches) [7]. Using bed ools o e lap e sion 2.26.0 [49], we selec ed a ian s alling wi hin he VRN1 epo ed binding peaks. The selec ed a ian s in VCF o ma we e hen p ocessed using con e - a ia ions and e ie e- a ia ion-seq o ob ain he sequences wi h he al e na i e alleles. The VRN1 DNA mo i used o scan he a ian s was ob ained om he oo p in DB plan collec ion [16] e sion: 2018-06 (h p:// lo es a.eead.csic.es/ oo p in db/index.php?mo i = AY750993:VRN1:EEADanno ). a ia ion-scan was used wi h a p e- compu ed backg ound Ma ko model (o de 1) o ba ley o assess he e ec o a ian s in TF binding, wi h he ollowing pa ame e s: – l h sco e 1 – l h w_di 1 – l h p al_ a io 10 – u h p al 1e-3. 2.7. A ailabili y Va ia ion- ools a e a ailable on he web (Me azoa: h p://me a- zoa. sa .eu/, Plan s: h p://plan s. sa .eu/, Teaching: h p:// each- ing. sa .eu/). The ools can be also ins alled o command-line usage wi h he RSAT sui e (h p://download. sa .eu/). The code and ma e ial o ep oduce he esul s p esen ed in he a icle can be accessed h ough Gi Hub (h ps://gi hub.com/RSAT- doc/supp-ma e ial-publica ions.gi ). 3. Resul s The Va ia ion- ools p o ide complemen a y p og ams enabling he e ie al o a ian s ( a ia ion-in o) and o hei su ounding sequences ( e ie e- a ia ion-seq), as well as in e con e sion be ween ile o ma s (con e - a ia ion). The main p edic i e p o- g am is a ia ion-scan, which can be used wi h any se o a ian s p o ided by he use (in VCF o GVF o ma s) o anno a ed in Ensembl ( om a lis o sIDs o a bed ile o iden i y o e lapping a ian s in genome coo dina es), wi h any se o mo i s selec ed om he collec ions a ailable in RSAT, o p o ided by he use . 3.1. a ia ion-scan accu a ely assesses he e ec o expe imen ally alida ed egula o y a ian s The o iginal e sion o a ia ion-scan [45] equi ed app oxi- ma ely i e hou s o assess he allele e ec o nine millions a i- an s. The no el e sion [47] signi ican ly educes he p ocessing ime o abou one hou (Supplemen a y Fig. 3). To e alua e he pe o mance o a ia ion-scan, we used an expe imen ally alida ed egula o y a ian se ob ained om a MPRA expe imen [60]. Fo all o he assessed allele pai s, we com- pa ed he weigh sco e di e ences compu ed wi h a ia ion-scan wi h he mRNA/DNA a io o he MPRA (see me hods). As shown in Supplemen a y Fig. 4A, we a e able o eco e only 9.37% o he expe imen ally alida ed a ian s wi h a ia ion-scan, as we eques ed a leas one o he alleles o ha e a binding si e o high con idence (p- alue 10 4 ). Focusing on he a ian s epo ed as posi i e in he MPRA da a se , we obse ed a weak co ela ion be ween he weigh di e ence and he MPRA mRNA/DNA a io in posi i e a ian s. Howe e , his co ela ion is no signi ican , as MPRA alues do no scale wi h he a ia ion-scan weigh di e - ences. Ne e heless, all a ian s show a p- alue a io indica i e o allele binding e ec s, showing ha a ia ion-scan gi es accu a e measu emen s o he impac o egula o y a ian s (Fig. 2A). Wi h he p oposed h esholds, we can con iden ly ejec 96.35% o MPRA nega i e sequences, which could be imp o ed using mo e es ic i e pa ame e , wi h a concomi an educ ion in ue posi- i es. No ewo hy, as any high- h oughpu assay, MPRA has i s limi a ions [51] and sequencing biases could inc ease he numbe o alse nega i es. We pe o med a nega i e con ol, consis ing o 240 pe mu ed ma ices ( i e pe mu ed e sions o he 48 mo i s). Wi h his col- lec ion, i was s ill possible o eco e a g oup o a ian s, bu i only ep esen ed 31.2% o he MPRA posi i e a ian s (Supplemen- a y Fig. 4B). We compa ed he pe o mance o a ia ion-scan o wo o he ools ha had been p e iously used by Uli sch, e al [60] o assess he same se o MPRA a ian s: DeepSea [68] and del aSVM [37]. We decided o use he same pa ame e s in o de o a oid pe sonal biases when calib a ing he ools. The e o e, aining weigh s o DNAse I hype sensi i i y si es we e used in he del aSVM analysis. W. San ana-Ga cia e al./Compu a ional and S uc u al Bio echnology Jou nal 17 (2019) 1415–1428 1421 As o DeepSea, he web implemen a ion o he ool was used, wi h he me ic Func ional Signi icance Sco e. Tools we e compa ed based on ROC cu es (Fig. 2B), we addi- ionally an a ia ion-scan using a se o pe mu ed ma ices as neg- a i e con ol (Fig. 2B, ed line). The h ee ools show e y simila sensi i i y s speci ici y a he beginning o he cu es, bu only a ia ion-scan and DeepSea u he emain sepa a ed om he neg- a i e con ol. As expec ed DeepSea pe o ms sligh ly be e han a ia ion-scan a he beginning o he cu e, ne e heless his ool equi es aining using epigene ic da a, while a ia ion-scan equi es only a mo i and a se o a ian s. 3.2. Va ia ion- ools case s udies To illus a e he di e se applica ions o Va ia ion- ools o ackle a ious biological ques ions, we designed ou di e en case s udies: 1. Impac o egula o y a ian s in he same haplo ype on TF bind- ing si es. 2. Iden i ica ion o he egula o y po en ial o a ian s epo ed in GWAS. 3. Assessmen o he egula o y po en ial o GWAS a ian s wi hin expe imen ally de e mined egula o y egions. 4. De e mina ion o egula o y a ian s wi hin TF binding egions iden i ied using ChIP-seq [19]. 3.2.1. Genome-wide haplo ype a ian in o ma ion can be used o iden i y se s o egula o y a ian s a ec ing he same TFBS The lowe ing cos s in sequencing ha e made i possible o ob ain whole genome sequences o mo e indi iduals, opening he possibili y o knowing, no only he a ian s o a genome, bu also he haplo ypes, and de e mining which a ian s a e passed linked wi hin he same ch omosome. This enables he assessmen o he egula o y e ec s o se s o a ian s wi hin he same haplo ype in a gi en TFBS. Using he high-con idence SNPs om wo ‘‘Pla inum” Genomes [23], we de e mined haplo ype a ian s ha a e likely o a ec one TFBS. We selec ed a ian s 30bps apa , loca ed in open ch oma in, o be analysed wi h a ia ion-scan using he non- edundan mo i collec ion a RSAT [8]. We de ec ed 7,406 haplo ype si es wi h a leas wo he e ozygous a ian s and a p obable e ec in binding o 361 TFs. O e all he numbe o he e ozygous a ian s wi hin a haplo ype inc eases he measu ed weigh di e ence. This is expec ed as mo e changes in he binding si es a e mo e likely o change TF a ini y (Fig. 3A). To assess he biological ele ance o all he pu a i e dis up ed TFBS p edic ions, we anno a ed 7,485 p edic ed haplo ypes si es con aining wo o mo e a ian s wi h a leas one he e ozygous a ian and 15,396 p edic ed si es con aining a SNP (single ons) wi h he TF ChIP-seq peaks and he Cis-Regula o y Modules (CRM) egions om ReMap [10]. We ound ha almos all he p e- dic ed dis up ed TFBS (~85%) con ain a CRM o peak anno a ion o bo h (Fig. 3B). In e es ingly, we ound en ichmen o CRM and peak anno a ions in he p o enance sequence segmen s o he 7,485 p edic ed haplo ypes si es compa ed o he p o enance sequence segmen s o he single a ian s (Fishe exac es , p- alue < 2.2e- 16). One o hese anno a ed haplo ypes is composed o he mino alleles o wo SNPs ( s2732317 and s2732318), whe e we obse ed a po en ial egula o y e ec likely a ec ing h ee binding mo i s, o EHF/ELF2, ETV4/ELK1/ETS1/FLI1/ELK4/ETS2/FEV/GABP1, and ELK3/ELF1/ERG/GABPA (Fig. 3C). 3.2.2. Gene ic a ian s associa ed wi h Mycobac e ium ube culosis in ec ion show po en ial egula o y e ec s The second case s udy illus a es a knowledge- ee use o Va ia ion- ools o iden i y egula o y a ian s om GWAS s udies o a use -speci ied disease, wi hou p io indica ion abou he po en ially in ol ed ansc ip ion ac o s o binding mo i s. The app oach is based on he p edic ion o egula o y a ian s wi h RSAT Va ia ion- ools, na owed down by selec ing he egula o y SNPs ha o e lap ChIP-seq peaks in ReMap [10], in o de o iden- i y con e gen indica ions o a po en ial impac o he a ian s on he binding o a TF. A) B) 0.00 0.25 0.50 0.75 1.00 0.000.250.500.751.00 speci ici y sensi i i y name pe mu ed del aSVM a ia ion-sca n DeepSea P- alue a io 100 P- alue a io 1000 P- alue a io 10 R=0.12,p=0.5 0 200 400 −9 −6 −3 0 MPRA p− alue o di e en ial ac i i y (log10) Va ia ion−scan p− alue a io Fig. 2. Iden i ica ion o expe imen ally alida ed egula o y a ian s using a ia ion-scan. A) Co ela ion o he Massi ely Pa allel Repo e Assays (MPRA) p- alue o he mRNA/DNA a io o posi i e a ian s and he a ia ion-scan weigh di e ence o he MPRA a ian s wi h signi ican change. B) Recei e Ope a ing Cha ac e is ic (ROC) cu e compa ing he pe o mance when aiming o classi y MPRA expe imen ally analyzed a ian s using a ia ion-scan ( u quoise), DeepSea (pu ple), del aSVM (g een), and a nega i e con ol which consis s o pe mu ed mo i s sco ed wi h a ia ion-scan ( ed). 1422 W. San ana-Ga cia e al./Compu a ional and S uc u al Bio echnology Jou nal 17 (2019) 1415–1428 Fig. 3. Haplo ype analysis in high-quali y human genomes. A) The numbe o he e ozygous a ian s (X-axis) wi hin he same pu a i e binding si e end o ha e a g ea e impac on he TF binding p obabili y. This is expec ed as he inc ease o weigh di e ence obse ed on he iolin plo co esponds o he expec ed cumula ed impac o a ia ions a ec ing di e en posi ions o he same binding si e. B) Numbe o p edic ed dis up ed T ansc ip ion Fac o Binding Si es (TFBSs) wi h Cis-Regula o y Modules (CRMs) and TF ChIP-seq peak anno a ion (blue), wi h only peak anno a ion (yellow), and non-anno a ed p edic ions (g ey). C) Uni e si y o Cali o nia San a C uz (UCSC) b owse [48] sc een sho , showing a locus encompassing wo SNPs ha compose an he e ozygous haplo ype in one o he No he n Eu opeans om U ah (CEU) indi iduals. The igu e shows he e e ence genome haplo ype. The a ian s a e loca ed in he FUT10 p omo e ( op). a ia ion-scan p edic s an e ec in h ee mo i s ha ep esen binding si es o GABPA, ETS1 and ELF2, ac o s ha ha e been p o en o ha e binding si es in his egion by he ENCODE p ojec . The a ian s2732317 has been associa ed wi h e ec s in gene exp ession by he GTEx p ojec . W. San ana-Ga cia e al./Compu a ional and S uc u al Bio echnology Jou nal 17 (2019) 1415–1428 1423