Decreased Transcription Factor Binding Levels Nearby PrimatePseudogenes Suggest Regulatory Degeneration

Gavin M Douglas1 Michael D Wilson23 and Alan M Moses14

1Department of Ecology and Evolutionary Biology University of Toronto Toronto ON Canada2Genetics and Genome Biology Program SickKids Research Institute Toronto ON Canada3Department of Molecular Genetics University of Toronto Toronto ON Canada4Department of Cell and Systems Biology University of Toronto Toronto ON Canada

Corresponding author E-mail alanmosesutorontoca

Associate editor Ilya Ruvinsky

Abstract

Characteristics of pseudogene degeneration at the coding level are well-known such as a shift toward neutral rates ofnonsynonymous substitutions and gain of frameshift mutations In contrast degeneration of pseudogene transcriptionalregulation is not well understood Here we test two predictions of regulatory degeneration along a pseudogenizedlineage 1) Decreased transcription factor (TF) binding and 2) accelerated evolution in putative cis-regulatory regionsWe find evidence for decreased TF binding levels nearby two primate pseudogenes compared with functional liver genesHowever the majority of TF-bound sequences nearby pseudogenes do not show evidence for lineage-specific acceleratedrates of evolution We conclude that decreases in TF binding level could be a marker for regulatory degeneration whilesequence degeneration in primate cis-regulatory modules may be obscured by background rates of TF binding site turnover

Key words pseudoenhancer regulatory evolution ChIP-seq neutral evolution histone modifications

Regulatory evolution is thought to be a key mechanismunderlying the diversity of closely related species (Brittenand Davidson 1969 King and Wilson 1975) For exampledeletions of conserved regulatory elements have been sug-gested to underlie human-specific traits (McLean et al2011) Despite the importance of regulatory degenerationfor human evolution little is known in general about howregulation evolves at the molecular level once selective con-straint has been lifted In addition recent studies have foundrelatively little conservation of TF binding in vertebrates(Schmidt et al 2010 Ballester et al 2014) suggesting thatmost changes in TF binding might be neutral with respect toselection By understanding how transcriptional regulationdegenerates we can help resolve which aspects of transcrip-tional regulation natural selection is preserving Herewe study TF binding and cis-regulatory modules (CRMswhich we take to refer to promoters enhancers silencersetc interchangeably) evolution near human pseudogenesto characterize the process of regulatory degenerationwhich we refer to as ldquopseudoenhancerizationrdquo (in the caseof enhancers) in analogy with pseudogenization the processwhereby natural selection fails to preserve genes We focuson regulatory degeneration nearby two unitary pseudo-genes because these represent true losses of functionfrom a species rather than degeneration of a redundantcopy (Zhang et al 2010) This study contrasts withapproaches that have looked at a large number of potentialpseudogenes in a single species (Pei et al 2012) in that weconsider the evolutionary evidence for regulatory degener-ation at a small number of known pseudogenes with clear11 orthologs across mammals

Two classic examples of unitary pseudogenes in human areurate oxidase Uox and L-gulonolactone oxidase Gulo whichare functional in the livers of most mammals Uox removesexcess nitrogen from the body by metabolizing uric acid(Gustafsson and Unwin 2013) and was pseudogenized inde-pendently in both human and gibbon (Zhang et al 2010)Gulo is responsible for encoding the protein required for thefinal step in the vitamin C (ascorbic acid) synthesis pathwayand was lost in the ancestor of human and macaque (Drouinet al 2011)

There are a number of characteristics of pseudogenizationthat are used to identify pseudogenes and are all present inUox and Gulo (Zhang et al 2010) First the former codingsequence of pseudogenes evolves faster than the orthologouscoding regions in species where the loci are still functionalSimilarly pseudogenes exhibit a KaKs (ratio of nonsynony-mous to synonymous substitution rates) that approaches 1 asevolutionary distance increases Both of these characteristicsare due to relaxed purifying selection acting at the sequencelevel

In contrast it is unknown whether regulatory sequencesshow similar signatures of relaxed selection Regulatory ele-ments that regulated the functional ancestors of pseudogenesare expected to degrade following the pseudogenizationevent In fact it is possible that the first steps of pseudogeni-zation actually occur at the regulatory level (Wu et al 1992Oda et al 2002) However to our knowledge CRM degener-ation outside promoters or ldquopseudoenhancerizationrdquo hasonly been identified once before (Leivonen et al 1999)Decreased transcription factor (TF) binding levels could bea signal of degeneration which could be caused by long-range

Letter

The Author(s) 2016 Published by Oxford University Press on behalf of the Society for Molecular Biology and EvolutionThis is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License(httpcreativecommonsorglicensesby-nc40) which permits non-commercial re-use distribution and reproduction in anymedium provided the original work is properly cited For commercial re-use please contact journalspermissionsoupcom Open AccessMol Biol Evol doi101093molbevmsw030 Advance Access publication February 16 2016 1

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chromatin modifications or evolutionary changes at the se-quence level Also accelerated rate of evolution (relative tofunctional CRMs) could be a signal of relaxed selection onCRMs Furthermore in analogy to the pattern of KaKs inpseudogenes there could be an excess of substitutions thatdecrease transcription factor binding site (TFBS) strength nearpseudogenes compared with functional genes Here we testthese predictions by investigating relaxed constraint in CRMsnearby the recently lost primate pseudogenes Gulo and UoxWe find evidence for decreased TF binding and H3K4me3enrichment levels nearby both pseudogenes and lineage-spe-cific relaxation of constraint in two CRMs near Uox

We first investigated how the regulation of gene expressiondegenerates following pseudogenization of a coding region byfocusing on the TF binding events of the liver-specific TFsCEBPA FOXA1 HNF4A and ONECUT1 (Ballester et al 2014)nearby the two primate pseudogenes Uox and Gulo In addi-tion to these four TFs we also investigated whether enrich-ment levels of two histone modifications H3K4me3 andH3K27Ac have changed nearby these pseudogenes (Villaret al 2015) H3K4me3 is considered a marker for active pro-moters (Santos-Rosa et al 2002) while H3K27Ac is a markerfor enhancers (Creyghton et al 2010)

Although Uox was pseudogenized in the human-gibbonclade (Wu et al 1992 Oda et al 2002) TFs still bind nearbythis locus (fig 1A) However a clear difference is the loss ofbinding at the human promoter compared with the otherfour mammals (fig 1B) In contrast there is no reduction inthe number of ChIP-seq control (input) reads in this region(shown as gray histograms fig 1) indicating that the absenceof ChIP-seq signal is not due to lack of read mappabilitySimilar trends of lost binding can be seen in human andmacaque at the Gulo locus as well (supplementary fig S1Supplementary Material online) Although these results sup-port our prediction that regulatory degeneration would be ac-companied by loss of TF binding evolutionary changes inmammalian TF binding have been observed at the ge-nome-wide scale (Schmidt et al 2010 Ballester et al 2014)We therefore sought to compare the patterns observed forpseudogenes with functional liver genes

We first confirmed that the loss of expression at pseudo-gene loci (as measured by RNA-seq) stands out relative togene expression changes in liver genes Using a Brownianmotion (BM) model (see Materials and Methods) we inferredgene expression in the rodent ancestor (because changessince the rodent ancestor can be estimated more reliablythan changes since the primate ancestor) and then calculatedthe change in gene expression from this ancestor for these 2pseudogenes and 1373 liver genes This large set of liver geneswas used because the inference of ancestral traits based upononly five extant species is noisy so we wanted to use a largesample size to estimate the null distribution The distributionsof changes in gene expression along each lineage were con-verted into standard scores based upon the mean and stan-dard deviation (SD) of the inferred changes in 1373 livergenes (mean changes of 0 from the rodent ancestor toboth human and macaque) The expression level decreasesfrom the rodent ancestor to human for both pseudogenes

relative to the 1373 liver genes (changes of326 and409for Gulo and Uox respectively Bonferroni corrected [BF corr]combined P lt 106 supplementary fig S2A SupplementaryMaterial online) In contrast although Gulo expression hassignificantly decreased in macaque (change342 BF corr Plt 104) Uox expression has not decreased more than ex-pected by chance (change 153 BF corr P frac14 016 supplementary fig S2B Supplementary Material online) This is ex-pected because Uox is still functional and is only expressedmoderately lower in macaque compared with other mam-mals (Oda et al 2002)

We used a similar strategy to test whether the apparentdecreased number of binding events in primate pseudogenes(fig 1) is statistically significant We implemented a quantita-tive measure of overall binding level that takes into accountbinding intensity distance from a locusrsquo transcription startsite (TSS) and the number of binding events (Wong et al2015 see Materials and Methods) Although TFs can regulategenes at a distance here we are assuming that binding eventscloser to a genersquos TSS are more likely to be regulating thatgene This measure of binding level can be considered a quan-titative trait for which we have observations in five species Ifrelaxation of selection has led to a loss of binding after pseu-dogenization we predict that this quantitative trait will de-crease in the human lineage To test this we computed thedifference in human binding level for pseudogenes relative tothe rodent ancestor as above We find a significant decreasein binding level along the human lineage for both pseudo-genes relative to the 1373 liver genes (113 and 222 forGulo and Uox respectively compared with a mean of0147for liver genes BF corr combined lt 0001 fig 2A) The de-crease in binding level in macaque is not significant for eitherGulo or Uox (individual locus and combined Pgt 005 supplementary fig S3A Supplementary Material online)

Additionally based on the same approach as above wepredicted that the enrichment levels for the histone modifi-cation markers H3K4me3 and H3K27Ac would also decreaseThere is evidence for a decrease in the H3K4me3 enrichmentlevel along the human lineage (088 and080 for Gulo andUox respectively compared with a mean of 001 for livergenes BF corr combined P lt 005 fig 2B) However similarto the above analyses on TF binding levels there is no evi-dence for decreased H3K4me3 enrichment along the ma-caque lineage (individual locus and combined P gt 005supplementary fig S3B Supplementary Material online)Decreased H3K4me3 enrichment is consistent with loss ofpromoter activity which is expected at these pseudogenesInterestingly there was no evidence for decreased enrichmentof H3K27Ac nearby the pseudogenes along either primatebranch (supplementary fig S4 Supplementary Material on-line individual locus and combined P gt 005) which is con-sistent with no loss in enhancer activity nearby thepseudogenes

We next sought to test for regulatory degeneration at thesequence level for Uox Note that sequence-level analyseswere not conducted for Gulo because this locus is a pseudo-gene in macaque and so there is no prediction of acceleratedrate of evolution for this locus between the two primate

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A

B

FIG 1 Multi-species alignment around the Uox locus (A) An alignment corresponding to 6 100 kb around the human Uox TSS (chr1 84763514ndash84963514 negative strand) Thick black lines correspond to DNA for each species while the thinner line indicates gaps Different colored circlesillustrate the binding of the four TFs around this locus (as described in the legend above) indicates the Uox promoter in humans where there ismarked loss in binding compared with the other species (B) 610 kb around the Uox TSS (indicated by box in panel A) The gray and bluehistograms show the distributions of the input control and CEBPA reads per billion over the region in each species The vertical black line at theleftmost side of each species name indicates log(100) reads per billion (RPB) Called CEBPA peaks in each species are indicated by blue circles TheUox locus is colored blue at the bottom of the alignment and nearby genes are shown in red

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lineages noncoding DNA from more distantly related mam-mals was not sufficiently alignable to confidently conductsequence-based analysis Specifically we tested for lineage-specific accelerated evolution in CRMs nearby Uox whichwe expected in analogy to coding region degeneration wherethe nonsynonymous substitution rate (Ka) along pseudogen-ized lineages accelerates relative to the synonymous (near-neutral) substitution rate (Ks) (Torrents et al 2003) We firstconfirmed that the pseudogene lineage-specific estimate ofKaKs for Uox was an outlier among the liver genes (fig 3A)Along the pseudogenized lineage Uox has KaKsfrac14 132 whilethe KaKs frac14 0649 in macaque where Uox is still functionalThe distribution of the differences in KaKs between the twoprimate sets for each gene clearly shows that this differencefor Uox is an extreme outlier (fig 3A 312 SDs) This is con-sistent with relaxed constraint on the Uox amino acidsequence

Analogous tests for human-gibbon accelerated substitu-tion rates were used on putative regulatory sequences(CRMs) within 100 kb of the Uox TSS Here regions boundby TFs were taken to be the sequences putatively under se-lection while unbound noncoding flanking sequences weretaken to be the neutral reference We defined the ratio ofsubstitutions in these regions to be KbKu (b frac14 bound u frac14unbound) in analogy to the KaKs ratio above (Hahn 2007)Peak sequences nearby liver genes evolve more slowly than

unbound flanking regions both along the humanndashgibbonlineage (supplementary fig S5A Supplementary Material on-line median of 0008 and 0007 substitution per site in humanflank and peak sequences Wilcoxon test P lt 106) and inoutgroup primates (supplementary fig S5B SupplementaryMaterial online median of 0035 and 0030 in macaque flankand peak sequences respectively Wilcoxon test BF corr P frac14002) This slower rate of evolution in peak sequences com-pared with flanks is consistent with purifying selection actingupon peak sequences and suggests that relaxed purifying se-lection should be detectable

We inferred the number of substitutions per site along thehumanndashgibbon lineage and macaque branch in peaks nearbythe liver genes and plotted the difference in substitution ratesinferred for each gene for all macaque peaks (fig 3B) Thedifference in rates for Uox falls within these distributions (001SD) Therefore there is no evidence for relaxed purifying se-lection on peak sequences nearby Uox compared with thosenearby functional liver genes We also investigated whetherthere is a difference in the pattern of changes in bindingstrength in TFBSs (Moses 2009) nearby these two gene setsbut there was insufficient power at the single-gene level (supplementary fig S6 Supplementary Material online)

To investigate whether any particular CRMs show evi-dence for degeneration nearby Uox (putative ldquopseudoen-hancersrdquo) we applied a likelihood ratio test (LRT) for

A B

FIG 2 Both human TF binding levels and H3K4me3 enrichment have decreased nearby primate pseudogenes (A) The difference in TF bindinglevel between the rodent ancestor and human (B) The analogous difference in H3K4me3 enrichment (a marker for active promoters) between therodent ancestor and human The species trees show the inferred values of the quantitative traits The white circles indicate the ancestral rodentand the red lines indicate the lineages being compared Gray histograms correspond to the distribution of changes for 1373 genes that are liverexpressed in mouse rat and dog with one-to-one orthologs across the five mammals (in standardized units) Gulo and Uox are indicated in termsof their standard scores by the blue and red arrows respectively In human where both Gulo and Uox are pseudogenized there is a significantdecrease in both TF binding and H3K4me3 enrichment levels for the pseudogenes (combined P lt 001)

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A

0649

157

175

167

-

372-

0641

136

Human

Chimp

Gorilla

Orangutan

Gibbon

Macaque

Uoxpseudogenized

Uox

B

Uoxpseudogenized

Uox

C

085

107

064

052

068

184066

083

161

Human

Chimp

Gorilla

Orangutan

Gibbon

Macaque

Uoxpseudogenized

Uox

(unbound sequence)Null hypothesis

(same scale factor α) (Different scale factors α1 and α2)α1

α2

α1

α1

α1

α1

α1

α1

α1

α

αα

α

αα

α

α

α

Human

Chimp

Gorilla

Orangutan

Gibbon

Macaque

Human

Chimp

Gorilla

Orangutan

Gibbon

Macaque

Human

Chimp

Gorilla

Orangutan

Gibbon

Macaque

05

01

00

15

02

00

25

0

(HumanGibbon lineage KbKu) - (Macaque KbKu)(HumanGibbon lineage KaKs) - (Macaque KaKs)

Num

ber

of g

enes

-2

01

02

03

04

05

06

07

0

-1 0 1 2 -2 -1 0 1 2

Num

ber

of g

enes

(HumanGibbon lineage scale factor) (Macaque scale factor)

0

01

02

03

04

0 1 2 3 4 5

Liver gene deeply shared CRMs

Uox deeply shared CRMs

Significant LRTs79 (P=0005)63 (P=0012)

Uox Uox

FIG 3 Tests for sequence degeneration Red branches and internodes on phylogenies indicate pseudogenized lineages while the dotted linesindicate that Uox is functional in macaque (A) Comparisons of the nonsynonymous substitution rate (Ka) normalized by the synonymous (near-neutral) substitution rate (Ks) along the humanndashgibbon lineage compared with macaque The KaKs is indicated along each considered primatelineage (- indicates insufficient data) The gray histogram shows the background distribution for the difference in KaKs between the two sets of

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accelerated evolution along the humanndashgibbon lineage Thistests whether a scale factor (relative to a neutral reference) forthe rate of evolution within the two primate sets is signifi-cantly higher along the humanndashgibbon lineage than over therest of the primate phylogeny (fig 3C Cooper et al 2005Siepel et al 2006) We identified candidate highly conservedCRMs nearby Uox by requiring macaque binding events to beshared with at least two other nonhuman mammals Within100 kb of the Uox TSS there are eight independent candidatesfor CRM degeneration based upon these criteria Althoughthese candidate CRMs were short (201 bp) simulations indi-cated that we had sufficient power to detect acceleratedevolution along these lineages using the LRTs given reason-able rate increases (supplementary fig S7 and supplementarytext Supplementary Material online) We applied the LRT totest for accelerated evolution along the humanndashgibbon line-age We found that 28 of these candidate degenerative CRMsare evolving significantly faster along the humanndashgibbon lin-eage (fig 3C raw P lt 005) These include multiple deeplyshared binding events in the Uox promoter and a deeplyshared ONECUT1 binding event in an intergenic regiondownstream of a neighboring gene (the coordinates andLRTs are provided in table 1 alignments are shown in supplementary figs S8 and S9 Supplementary Material online) Thisresult is consistent with relaxed selection specifically along thehumanndashgibbon lineage in the Uox promoter and a putativeenhancer nearby the Uox TSS These significant scale factorratios (fig 3C) are within the range of values observed whenthe same tests were performed on peaks nearby the set of1373 liver genes

We also tried to localize peaks that lost binding alongpseudogenized lineages using the binding data aloneHowever we were unable to do so because peaks with lostbinding along pseudogenized lineages can be identified nearfunctionally conserved liver genes Thus the multi-speciesChIP-seq data are too variable to be used alone to identify

candidate pseudoenhancers On the other hand the quanti-tative decrease in TF binding (fig 2A) suggests that at leastsome portion of TF binding events are preserved by purifyingselection and that decreased binding levels reflect an in-creased proportion of TF binding events near pseudogenesbeing nonfunctional We attempted to demonstrate the gen-erality of our results on unitary pseudogenes by analyzingthree other primate unitary pseudogenes (Zhang et al2010) but this resulted in mixed results likely because func-tional orthologs of these pseudogenes are not highly ex-pressed in the livers of all the other mammals considered(supplementary table S1 Supplementary Material online)Future work focusing on a larger set of pseudogenes couldreveal whether decreased binding level is a general signatureof regulatory degeneration Although we did identify a can-didate pseudoenhancer using sequence-based analyses(fig 3C) the overall decrease in binding level is likely relatedto decreases in H3K4me3 enrichment levels (fig 2B) and notchanges in H3K27Ac enrichment levels (supplementary figS4 Supplementary Material online) This finding is consistentwith degeneration at the pseudogene promoter while thepatterns in distal CRMs are more difficult to identifySimilar evidence for low levels of TF binding and histonemodification levels has previously been shown nearby pseu-dogenes in human (Pei et al 2012) but our work indicatesthat these observations are due to decreases in binding levelsalong the human lineage Importantly it is unclear how thedecreases in TF binding expression and histone modificationlevels are linked

Our evidence for accelerated evolution along the humanndashgibbon lineage in two regulatory elements (near the primatepseudogene Uox) is consistent with degeneration of regula-tory elements in analogy to coding pseudogenizationHowever we do not consider this strong evidence for pseu-doenhancerization at the sequence level because only oneputative enhancer and the Uox promoter (as reported in Oda

Table 1 The Eight Macaque-Bound CRMs Are Listed along with the Scale Factor Ratios (human-gibbon scale factormacaque scale factor) andLRTs

Macaque Coordinates TF Scale Factor Ratio LRT Raw P Value

chr187191849ndash87192049 FOXA1 2205 7935 0005chr187180804ndash87181004 ONECUT1 2002 6348 0012chr187187397ndash87187597 FOXA1 1207 0358 0549chr187199929ndash87200129 FOXA1 0847 031 0578chr187219961ndash87220161 FOXA1 1131 0155 0694chr187204120ndash87204320 HNF4A 1135 0134 0714chr187189207ndash87189407 FOXA1 0944 0037 0847chr187271247ndash87271447 FOXA1 0994 0 0985

FIG 3 Continuedprimates based upon the 1373 liver genes Uox is a clear outlier of this distribution (red arrow) (B) Comparisons of the bound sequencesubstitution rate (Kb) normalized by the unbound sequence substitution rate (Ku) along the humanndashgibbon lineage compared with macaqueThe primate phylogeny indicates the KbKu along each considered primate lineage The histogram is analogous to panel A except that itcorresponds to KbKu rather than KaKs Uox is not an outlier on this distribution of background differences (C) LRT of accelerated evolutionin CRMs specifically along the humanndashgibbon lineage This is a test of whether the scale factor for the rate of evolution in a CRM is the same ordifferent between the humanndashgibbon lineage and macaque Scale factors are relative to the branch lengths of a neutral reference phylogeny basedupon unbound flanking DNA The three phylogenies represent this neutral reference phylogeny the null (same scaling factors) model and thealternative (different scaling factor factor) models

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et al 2002) were identified In addition there was no signal ofrelaxed selection along the humanndashgibbon lineage when allbound sequences nearby Uox were combined (fig 3B) Thisresult could suggest that a large proportion of bound se-quences nearby gene sets are nonfunctional (Cuvanovichet al 2014) or under very weak selection However it is alsopossible that CRM degeneration is masked by the back-ground turnover in TFBSs (Stergachis et al 2014 Vierstraet al 2014) We believe that TFBS turnover could result indecreased power to detect accelerated evolution due to therapid gain and loss of functional TFBSs although we have notruled out the possibility that there are too few sites consid-ered to detect degeneration of enhancers Additionally thestructure of CRMs particularly enhancers is more complexthan has been assumed in the above analyses (Arnosti andKulkarni 2005) It is not obvious that an accelerated rate ofevolution necessarily occurs within degenerating enhancers ingeneral Alternatively many regions of animal genomes havebeen identifiably bound by many different TFs simultaneouslyeven though the known TFBSs of these TFs are not found(Moorman et al 2006 ENCODE Project Consortium 2012) soit is not clear that regulatory degeneration could be identifiedat the sequence level in these cases Taken together our anal-ysis suggests that although pseudoenhancers may be identi-fiable in a small number of cases decreased TF binding levelover an entire locus could be a more reliable signature ofregulatory degeneration

Materials and MethodsMethods are described in detail in the SupplementaryMaterial online below is a brief summary

We used publicly available ChIP-seq data produced fromthe livers of human macaque mouse rat and dog for fourliver-enriched TFs CEBPA FOXA1 HNF4A ONECUT1(Schmidt et al 2010 Funnell et al 2013 Stefflova et al2013 Ballester et al 2014) and the histone modificationmarkers H3K4me3 and H3K27Ac (Villar et al 2015) Readswere mapped to each reference genome with Bowtie2(Langmead and Salzberg 2012) with default parametersNumbers of mapped reads and quality metrics are shownin supplementary table S2 Supplementary Material onlinefor the liver-enriched TFs Peak calling was performed withSWEMBL (v331 httpswwwebiacukswilderSWEMBL) with the parameter ldquo-R 0005rdquo TF peaks werecalled as reproducible in both replicates if they overlappedby 75 reciprocally (supplementary table S3Supplementary Material online)

Primate unitary pseudogenes were acquired from Zhanget al (2010) and were screened by eye for whether they haveliver expression in mouse rat and dog (based upon previouslypublished RNA-seq data see Supplementary Material online)as well as whether they have clear 11 orthologs based onEnsembl annotations andor based on sequence similarityThe set of 1373 liver expressed genes that are one-to-oneorthologs across the 5 mammals was constructed based on acut-off of 5 read fragments per kilobase of exon per millionreads within the livers of mouse rat and dog

The binding level for orthologs across species was basedupon a previous approach (Wong et al 2015) Before runningthese analyses for each TF and species read alignment fileswere downsampled to the number of reads mapped in thereplicate with the fewest number of reads This approachcombines the number of binding events their binding inten-sity and their distance from the TSS into a single measureSpecifically binding level (ais) where i is an orthologous genein species s is given by

ais frac14 logX

j

Xk

gijks

dijks thorn 01

where k is a peak within 100 kb of the TSS of gene i gijks isthe intensity of peak k for TF j in species s and dijks is thedistance (in bp) from the TSS to the summit of peak kThe region size used is 100 kb and is discussed furtherelsewhere (Wong et al 2015) A pseudocount of 01 isadded to the denominator to ensure this value is neverzero The mean and variance in binding level was calcu-lated for all TFs and species was determined for all liverexpressed genes Because the signal-to-noise ratio differsgreatly across ChIP-seq experiments binding levels wereconverted into standard scores (for each species and TF)so that they could be better compared across speciesThe standard scores of binding levels for each TF werethen summed to obtain a single measure of binding levelper gene Maximum-likelihood ancestral binding levelswere reconstructed under a BM model in R using theldquoacerdquo function of the ape package (Paradis et al 2004)Enrichment levels for the histone modification markerswere calculated using the same steps as for binding level

All sequence analyses reported were performed on peakand flank coordinates sliced from the 38 eutherian EPO align-ment (Release 74 Cunningham et al 2015) Peak sequenceswere taken as 6100 bp from peak summits while flankingregions were taken as 62 kb from peak ends that did notintersect other peaks or exons These alignments wererealigned with MAFFT (L-INS-i method v6882b Katoh andToh 2008) Shared peaks across species were called basedupon overlapping summits (taken as the peak center) within150 bp of each other within the alignment Primate sequenceswithin the humanndashtarsier lineage were parsed from thesealignments Ancestral sequences at each node in the primatephylogeny were reconstructed using the ldquoprequelrdquo programof PHAST (v13 Hubisz et al 2011) which were used to callsubstitutions LRTs were performed with the ldquophyloPrdquo pro-gram of PHAST to test for accelerated evolution within thehumanndashgibbon lineage relative to the macaque branchAlignments are available for download at httpwwwmoseslabcsbutorontocagavinalignments

Supplementary MaterialSupplementary tables S1ndashS3 figures S1ndashS9 and text are avail-able at Molecular Biology and Evolution online (httpwwwmbeoxfordjournalsorg)

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AcknowledgmentsThis work was supported by the Natural Sciences andEngineering Research Council of Canada (NSERC) throughgrants to AMM and a fellowship to GMD MDW wasfunded by NSERC (436194-2013) and a Canada ResearchChair We thank Christopher Brown and an anonymous re-viewer for suggesting the analysis of chromatin modificationdata

ReferencesArnosti DN Kulkarni MM 2005 Transcriptional enhancers intelligent

enhanceosomes or flexible billboards J Cell Biochem 94890ndash898Ballester B Medina-Rivera A Schmidt D Gonzalez-Porta M Carlucci M

Chen X Chessman K Faure AJ Funnell AP Goncalves A et al 2014Multi-species multi-transcription factor binding highlights con-served control of tissue-specific biological pathways ELife 3e02626

Britten RJ Davidson EH 1969 Gene regulation for higher cells a theoryScience 165349ndash357

Cooper GM Stone EA Asimenos G Green ED Batzoglou S Sidow A2005 Distribution and intensity of constraint in mammalian geno-mic sequence Genome Res 15901ndash913

Creyghton MP Cheng AW Welstead GG Kooistra T Carey BW SteineEJ Hanna J Lodato MA Frampton GM Sharp PA et al 2010Histone H3K27ac separates active from poised enhancers and pre-dicts developmental state Proc Natl Acad Sci U S A 10721931ndash21936

Cunningham F Amode MR Barrell D Beal K Billis K Brent S Carvalho-Silva D Clapham P Coates G Fitzgerald S et al 2015 Ensembl 2015Nucleic Acids Res 43D662ndashD669

Cusanovich DA Pavlovic B Pritchard JK Gilad Y 2014 The functionalconsequences of variation in transcription factor binding PLoSGenet 10e1004226

Drouin G Godin JR Page B 2011 The genetics of vitamin C loss invertebrates Curr Genomics 12371ndash378

ENCODE Project Consortium 2012 An integrated encyclopedia of DNAelements in the human genome Nature 48957ndash74

Funnell APW Wilson MD Ballester B Mak KS Burdach J Magan NPearson RCM Lemaigre FP Stowell KM Odom DT et al 2013 ACpG mutational hotspot in a ONECUT binding site accounts for theprevalent variant of hemophilia B Leyden Am J Hum Genet92460ndash467

Gustafsson D Unwin R 2013 The pathophysiology of hyperuricaemiaand its possible relationship to cardiovascular disease morbidity andmortality BMC Nephrol 14164

Hahn MW 2007 Detecting natural selection on cis-regulatory DNAGenetica 1297ndash18

Hubisz MJ Pollard KS Siepel A 2011 Phast and Rphast phylogeneticanalysis with spacetime models Brief Bioinform 1241ndash51

Katoh K Toh H 2008 Recent developments in the MAFFT multiplesequence alignment program Brief Bioinform 9286ndash298

King M Wilson AC 1975 Evolution at two levels in humans and chim-panzees Science 188107ndash116

Langmead B Salzberg SL 2012 Fast gapped-read alignment with Bowtie2 Nat Methods 9357ndash359

Leivonen S Piao YS Peltoketo H Numchaisrika P Vihko R Vihko P 1999Identification of essential subelements in the hHSD17B1 en-

hancer difference in function of the enhancer and that of thehHSD17BP1 analog is due to -480C and -486G Endocrinology 1403478ndash3487

McLean CY Reno PL Pollen AA Basssan AI Capellini TD Guenther CIndjeian VB Lim X Menke DB Schaar BT et al 2011 Human-specificloss of regulatory DNA and the evolution of human-specific traitsNature 471216ndash219

Moorman C Sun LV Wang J de Wit E Talhout W Ward LD Greil F LuXJ White KP Bussemaker HJ et al 2006 Hotspots of transcriptionfactor colocalization in the genome of Drosophila melanogaster ProcNatl Acad Sci USA 10312027ndash12032

Moses AM 2009 Statistical tests for natural selection on regulatoryregions based on the strength of transcription factor binding sitesBMC Evol Biol 9286

Oda M Satta Y Takenaka O Takahata N 2002 Loss of urate oxidaseactivity in hominoids and its evolutionary implications Mol Biol Evol19640ndash653

Paradis E Claude J Strimmer K 2004 APE analyses of phylogenetics andevolution in R language Bioinformatics 20289ndash290

Pei B Sisu C Frankish A Howald C Habegger L Mu XJ Harte RBalasubramanian S Tanzer A Diekhans M et al 2012 TheGENCODE pseudogene resource Genome Biol 13R51

Santos-Rosa H Schneider R Bannister AJ Sherriff J Bernstein BE EmreNC Schreiber SL Mellor J Kouzarides T 2002 Active genes are tri-methylated at K4 of histone H3 Nature 419407ndash411

Schmidt D Wilson MD Ballester B Schwalie PC Brown GD Marshall AKutter C Watt S Martinez-jimenez CP Mackay S et al 2010 Five-vertebrate ChIP-seq reveals transcription factor binding Science3281036ndash1040

Siepel A Pollard KS Haussler D 2006 New methods for detectinglineage-specific selection Res Comput Mol Biol 3909190ndash205

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Torrents D Suyama M Zdobnov E Bork P 2003 A genome-wide surveyof human pseudogenes Genome Res 72559ndash2567

Vierstra J Rynes E Sandstrom R Zhang M Canfield T Hansen RSStehling-Sun S Sabo PJ Byron R Humbert R et al 2014 Mouseregulatory DNA landscapes reveal global principles of cis-regulatoryevolution Science 3461007ndash1012

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