Available online at www.sciencedirect.com
ScienceDirect
Exploring the genesis and functions of Human
Accelerated Regions sheds light on their role in
human evolution
1 2
Melissa J Hubisz and Katherine S Pollard
Human accelerated regions (HARs) are DNA sequences that divergent molecular or organism traits [7,8 ,9 ]. These
changed very little throughout mammalian evolution, but then comparative genomic studies differ in their methodologi-
experienced a burst of changes in humans since divergence cal details and the data sets employed, but they have a
from chimpanzees. This unexpected evolutionary signature is common goal: to identify Human Accelerated Regions
suggestive of deeply conserved function that was lost or (HARs), DNA sequences with dramatically increased
changed on the human lineage. Since their discovery, the substitution rates in the human lineage. This lineage
actual roles of HARs in human evolution have remained has generally been taken as the 6 million years since
somewhat elusive, due to their being almost exclusively non- humans diverged from our closest living relatives, the
coding sequences with no annotation. Ongoing research is chimpanzees and bonobos, although tests for accelerated
beginning to crack this problem by leveraging new genome evolution have also been used to study older events [4 ]
sequences, functional genomics data, computational and events in other lineages [10], as well as HARs that
approaches, and genetic assays to reveal that many HARs are arose after divergence from archaic hominids [11,12,13 ].
developmental gene regulatory elements and RNA genes, most In this paper, we review the discovery of HARs, discuss
of which evolved their uniquely human mutations through the evolutionary forces that may have shaped these fast-
positive selection before divergence of archaic hominins and evolving sequences, and summarize what is known about
diversification of modern humans. their functions. Addresses
1
Department of Biological Statistics and Computational Biology, Cornell
University, 102D Weill Hall, Ithaca, NY 14853, USA Scanning multiple sequence alignments for
2
Gladstone Institutes, Division of Biostatistics & Institute for Human
accelerated regions
Genetics, University of California, 1650 Owens Street, San Francisco,
Detecting acceleration on a particular lineage involves a
CA 94158, USA
statistical test comparing the DNA substitution rate
Corresponding author: Pollard, Katherine S observed on that lineage with the rate expected given
([email protected]) the rest of the tree (Box 1). This test is explicitly different
from tests for positive selection, which compare observed
substitution rates to those expected under a neutral model
Current Opinion in Genetics & Development 2014, 29:15–21
[14–16]. Rather, it is looking for a lineage-specific increase
This review comes from a themed issue on Genetics of human origin
in the substitution rate compared to a sister lineage or the
Edited by Aida M Andre´ s and Katja Nowick rest of the tree and will therefore produce a high score
whether the lineage experiences a shift to positive selec-
tion or a relaxation of negative selection (Figure 1). In the
case of the human lineage, where functional elements may
http://dx.doi.org/10.1016/j.gde.2014.07.005
have zero expected substitutions, acceleration tests can
#
0959-437X/ 2014 The Authors. Published by Elsevier Ltd. This is an reach genome-wide significance even when there are
open access article under the CC BY license (http://creativecom-
only a few human-specific substitutions (i.e. not many
mons.org/licenses/by/3.0/).
more than expected under a neutral model). Hence, tests
for acceleration can be more powerful than those for
selection. Nonetheless, many accelerated regions do
Introduction show signatures of positive selection (see below).
Humans are in many ways typical primates, but our
species does differ from its evolutionary cousins in several Typically, one is interested in detecting accelerated
ways, ranging from unique behaviors and social structures evolution in functional elements, such as promoters,
to morphological changes associated with upright walk- enhancers, exons, or splice sites. However, since much
ing, metabolic differences necessitated by a diet high in of the non-coding genome remains to be fully annotated,
starch, lactose, and meat, and a distinctive disease profile the usual approach has been to use evolutionary conser-
[1–3]. The sequencing of mammalian genomes revolu- vation as a proxy for function and perform the test on
tionized such comparisons by enabling searches for the conserved elements. One source for these is the phast-
genetic differences between species [4 ,5,6], as well as Cons program [17], which uses a phylogenetic hidden
studies aimed at linking these sequence changes to Markov model. The open-source software package
www.sciencedirect.com Current Opinion in Genetics & Development 2014, 29:15–21
16 Genetics of human origin
Box 1 Statistical tests for accelerated regions
PHAST [18 ] implements phastCons, plus several
different tests for accelerated evolution via the phyloP
The goal of a test for accelerated evolution is to determine if the rate
of DNA substitutions is faster than expected in a lineage of interest. function.
This lineage can be a single branch (e.g. human since divergence
from chimp), a clade (e.g. great apes), or an extinct species (e.g.
Discovering the fastest-evolving regions of
ancestor of all primates). A variety of tests have been proposed,
including ones that estimate substitutions via models of molecular the human genome
evolution [23,54] and ones that compare parsimony-inferred counts Beginning in 2006, a number of studies applied genome-
of substitutions [21,22]. Some tests make use of the phylogenetic
wide tests for human acceleration to various sets of
relationships between species to derive expected numbers of
mammal-conserved elements [4 ,19,20], many of which
substitutions in the lineage of interest, while others directly compare
excluded protein-coding exons [21–23]. Capra and col-
sister species. Regardless of these distinctions, the idea is to
determine whether the data in a multiple sequence alignment is more leagues [9 ] recently compared these studies and found
consistent with lineage-specific acceleration versus the expected that HAR data sets produced without coding filters were
rate of substitutions. This cross-species approach is related to, but
nonetheless comprised of mostly non-coding sites
distinct from, methods that employ polymorphism data to identify
(96.6%). They also produced a combined list of non-
selection within a species [55].
coding HARs (ncHARs), which we analyze further here
The data used to identify accelerated regions are aligned DNA
after dropping any that show little support in the most
sequences from multiple species with a phylogenetic tree, which is
recent alignments (UCSC hg19 conservation track).
either known a priori or computed from the sequence data. There are
also specialized comparative genomics methods for identifying slow These 2701 ncHARs are short (mean length = 266 base
and fast evolving proteins [16,56] or RNA genes [57], which use pairs (bp)), although they are often flanked by other
alignments of codons, amino acids, or structured RNA, as well as
conserved elements that are not accelerated, suggesting
methods based on loss and gain of regulatory motifs (Siepel and
that the HAR is part of a larger functional element. As
Arbiza, in this issue) [58]. These are powerful approaches for
studying specific small subsets of the genome, but DNA-based expected, ncHARs have many more substitutions in
methods are needed for unbiased, genome-wide scans. human (mean = 1.7 per 100 bp) compared to other mam-
mals, which are highly conserved (chimp mean = 0.2 per
Whole genomes can in principle be analyzed for lineage-specific
acceleration one base pair (bp) at a time, although this approach has 100 bp). Even though a typical ncHAR has only a few
very low power compared to testing windows 100 bp or larger [54]. human-specific substitutions, this rate is significantly
To focus on functional windows of the genome, analyses have
faster than other conserved elements [17,24] (phastCons;
typically used evolutionarily conserved elements. Because accel-
http://genome.ucsc.edu; bootstrap P < 0.01, based on 100
eration on the lineage of interest may prevent a region from being
classified as conserved, this lineage should be removed from the mammalian phastCons elements per HAR matched for
alignment before generating the conserved elements [4 ]. Accelera- length and chromosome) and the background (bootstrap
tion tests can also be applied to neutral regions to detect gain-of-
P < 0.01, based on 100 flanking regions per HAR
function events, provided the regions are long enough to have
matched for length). It is also about three times the
sufficient power.
neutral rate, enabling inferences about positive selection
versus loss of constraint in individual HARs (see below).
Figure 1
(a) (b) (c) Human Human Human Chimp Chimp Chimp
Macaque Macaque Macaque (d) (e) (f) W-to-S W-to-S Human Human Human Chimp Chimp Chimp
Macaque Macaque Macaque
Current Opinion in Genetics & Development
Many evolutionary forces can generate human accelerated regions. (a) A neutral phylogeny. Branch lengths represent expected numbers of
substitutions. (b)–(f) Examples of human-specific accelerated substitutions. (b) Positive selection versus a neutral background. (c) Positive selection
versus a background of constraint. (d) Loss of constraint. (e) GC-biased gene conversion (gBGC) versus a neutral background. (f) gBGC versus a
background of constraint. Black = neutral substitution rate, red = slower than neutral, green = faster than neutral, W-to-S = weak (A/T) to strong (G/C)
biased substitution pattern.
Current Opinion in Genetics & Development 2014, 29:15–21 www.sciencedirect.com
Genesis and functions of Human Accelerated Regions Hubisz and Pollard 17
Figure 2
It is important to note that structural variations, rather
than substitutions, comprise the majority of bases that
differ between human and chimp [5]. Unfortunately, (a)
15
misaligned or misassembled paralogous regions produce
many false positives in scans for HARs [20], and therefore
most studies filtered out duplicated regions, despite
their importance. However, complementary approaches
have revealed human-specific duplications [25,26] and
Frequency
deletions [27] of genes and conserved non-coding
elements, as well as an enrichment of HARs in duplicated
loci [22,28]. Recent alignment methods that handle
0510
duplications [29,30] may alleviate the need for paralog 0.30 0.32 0.34 0.36 0.38
filtering. Fraction african–specific
Recently evolved and evolving HARs (b)
Genomes from archaic hominins and diverse modern
humans provide information about when along the
human lineage HAR mutations arose. We analyzed
ncHARs for mutations shared with a Neanderthal [11]
and a Denisovan [12] using other primates (100-way
Frequency
alignments; http://genome.ucsc.edu) to polarize differ-
ences. We estimate that 7.1% of human–chimp differ-
ences in ncHARs occurred after divergence from archaic 02468101214
hominins and 2.7% are shared. The post-archaic fraction 0.08 0.09 0.10 0.11 0.12
is similar to that observed in targeted sequencing of Fraction European–specific
HARs captured from an Iberian Neanderthal fossil (c)
[31 ]. Compared to chimp–human differences in flanking
regions and phastCons elements, those in ncHARs are
significantly more likely to be pre-archaic (90% show
derived allele only in Neanderthal and Denisovan; both
P < 0.01). Thus, the archaic hominins provide some
Frequency
evidence for a depletion of accelerated evolution in the
past 1 million years of human evolution compared to
earlier in our lineage. 024681012
0.055 0.060 0.065 0.070 0.075 0.085
Next, we analyzed the autosomal ncHAR sequences of 54
Fraction Asian–specific
unrelated modern humans (Supplemental Table 1) from a
Current Opinion in Genetics & Development
diverse set of populations (http://www.completegen-
omics.com/public-data/69-Genomes/) [32]. As expected,
Human population-specific polymorphisms are depleted in HARs. (a)
most human–chimp differences in HARs appear to be
African population-specific polymorphisms in HARs (arrow) compared to
fixed. Nonetheless, many ncHARs are polymorphic, with
distributions of flanking regions (red) and phastCons elements (blue). (b)
polymorphism rates similar to flanking regions but
European population-specific polymorphisms. (c) Asian population-
higher than phastCons elements (P < 0.01). ncHAR poly- specific polymorphisms.
morphisms also tend to be older (11% pre-archaic;
both P < 0.01), with higher derived allele frequency
(mean = 22%; both P < 0.01), and less frequently private
to any major population group (unadmixed European, work is needed to disentangle these possibilities. To
Asian, or African) (Figure 2). This signature could poten- facilitate further analyses, we provide a table of summary
tially result from derived alleles in the reference genome statistics for individual ncHARs (Supplemental Table 2).
contributing to the original identification of HARs,
although only 10% of human–chimp differences are Evolutionary forces driving human
polymorphic, which is only a slight enrichment compared accelerated evolution
to flanking regions (P = 0.12) and similar to phastCons The primary motivation for identifying HARs was to find
elements (P = 0.16). Alternatively, positive selection, functional elements that experienced positive selection
biased gene conversion (see below), or relaxation of on the human lineage. Indeed, most HARs have substi-
constraint in HAR regions may have driven the enrich- tution rates significantly higher than genome-wide or
ment for older, higher frequency alleles in HARs. Future local neutral rates [20,33 ]. Different studies reported
www.sciencedirect.com Current Opinion in Genetics & Development 2014, 29:15–21
18 Genetics of human origin
Figure 3
variable amounts of population genetic evidence for
recent selection in HAR loci [20,22,34], likely due to
using different sets of HARs and polymorphism data.
ncHARs
These results, coupled with our observation that human– conserved elements
chimp differences are enriched before divergence from genome average
archaic hominins, suggest that many HARs were created
by positive selection and that the adaptive events are not
preferentially linked to the emergence and dispersal of 0.2 0.4 0.6 Fraction of bases Fraction modern humans.
0.0
However, it has been suggested that HARs might result
Promoter UTR ncRNA Intron Intergenic
from GC-biased gene conversion (gBGC) rather than
Current Opinion in Genetics & Development
positive selection, because they harbor excess weak (A/
T) to strong (G/C) substitutions, especially in the fastest
Genomic distribution of non-coding HARs. Proportion of ncHARs in each
evolving HARs [20,34–36]. This trend (also seen in fast-
non-coding annotation category compared to conserved elements and
evolving exons [37]) drove development of novel the whole human genome.
methods for detecting gBGC and distinguishing it from
other evolutionary forces via comparisons to neutral sub-
stitution rates [33 ,38,39]. This produced estimates that predicted that at least one third of ncHARs function as
the majority of HARs were shaped by positive selection, gene regulatory enhancers active in many different
with gBGC and loss of constraint each explaining 20% embryonic tissues [9 ]. Indeed, this study and several
[33 ]. HAR2/HACNS1 is an example of a predicted smaller ones have used transient transgenic reporter
gBGC event, which may have produced human-specific assays to test 45 ncHARs for activity at a few typically
enhancer activity through loss of repressor function studied developmental time points. They found 39
[40,41]. HARs created by loss of constraint are other good ncHARs that can drive gene expression in zebrafish
candidates for loss-of-function studies. While functional and/or mouse embryos [7,8 ,43,47]. An additional 23
experiments are needed to confirm putative adaptive and out of 47 tested ncHARs show positive developmental
non-adaptive effects of HAR substitutions, sequence enhancer activity in the VISTA Enhancer Browser (http://
based analyses have established that a combination of enhancer.lbl.gov). Cotney et al. [48 ] further showed that
positive selection and other evolutionary forces likely 16 ncHARs, including HAR2, gained an epigenetic mark
contributed to the creation of HARs. of active enhancers in the human lineage. These results
strongly support the hypothesis that many ncHARs func-
Genomic distribution of HARs tion as enhancers, although the set of tested candidates is
The genomic distribution of ncHARs is not random. still too small and non-randomly selected for a precise
They tend to cluster in particular loci and are significantly estimate of the true number of ncHAR enhancers.
enriched nearby developmental genes, transcription fac-
tors, and genes expressed in the central nervous system Transgenic enhancer assays also enable the activity of a
[9 ,20,42,43,44 ]. Most are not in the promoters or tran- human ncHAR sequence to be compared to its ortholog
scripts of these genes, but instead are found in intergenic from chimpanzee or other mammals. Of 26 ncHAR
regions (59.1% of bp; based on Gencode annotations [45]) enhancers that have been tested using both human and
(Figure 3), significantly farther from the nearest transcrip- non-human primate sequences, seven drive human-
tion start site than other conserved elements [9 ]. We specific expression patterns in mouse embryos at day
also analyzed the HARs from studies that did not filter 11.5. The tissues with differential expression are limb
out coding sequences and found that these are 3.4% (HAR2, 2xHAR114), eye (HAR25), forebrain
coding, more than the genome (1.1%) but much less than (2xHAR142, 2xHAR238), and the midbrain–hindbrain
random subsets of similar numbers of phastCons elements boundary (2xHAR164, 2xHAR170). The functional
(14.2–24.3%). Thus, a typical HAR is located together with implications of these expression differences remain to
several other HARs in a gene desert flanked by one or more be discovered, but it is tempting to speculate that changes
developmental transcription factors. in the development of these tissues could influence
human anatomy and traits such as fine motor skills,
Experimental exploration of HAR functions spoken language, and cognition.
While the genomic distribution of ncHARs is suggestive
of distal regulatory elements, very few ncHARs have Future directions for HAR research
annotated functions. A small fraction encodes non-coding The past few years have seen a shift in HAR research
RNAs (5.1% of bp), including the validated long non- from sequence based studies to functional validations,
coding RNA HAR1 [19,46]. On the basis of sequence including the discovery of several human-specific enhan-
features and functional genomics data, a recent study cers, suggesting that developmental gene regulatory
Current Opinion in Genetics & Development 2014, 29:15–21 www.sciencedirect.com
Genesis and functions of Human Accelerated Regions Hubisz and Pollard 19
changes played a significant role in human evolution. References and recommended reading
Papers of particular interest, published within the period of review,
However, there are still many hurdles to linking genetic
have been highlighted as:
changes to divergent traits. One caveat of using transgenic
mice or fish to assay HAR activity is that the trans of special interest
environment is not identical to either human or chim- of outstanding interest
panzee. Indeed, trans regulatory factors have played a
significant role in human evolution (Nowick, in this
1. Varki NM, Strobert E, Dick EJ Jr, Benirschke K, Varki A:
issue). However, a study that tested orthologous human Biomedical differences between human and nonhuman
hominids: potential roles for uniquely human aspects of sialic
and zebrafish enhancers in both zebrafish and mouse
acid biology. Annu Rev Pathol 2011, 6:365-393.
found almost no trans effects [49]. Another problem is
2. Varki A, Geschwind DH, Eichler EE: Explaining human
that only a small number of candidate enhancers can be
uniqueness: genome interactions with environment,
screened with these relatively costly and time-intensive behaviour and culture. Nat Rev Genet 2008, 9:749-763.
techniques. New genomic technologies, such as mas- 3. Calcagno JM, Fuentes A: What makes us human? Answers from
evolutionary anthropology 21
sively parallel reporter assays [50,51] and genome editing . Evolut Anthropol 2012, :182-194.
[52], are opening the door to high-throughput screens of 4. Lindblad-Toh K, Garber M, Zuk O, Lin MF, Parker BJ, Washietl S,
Kheradpour P, Ernst J, Jordan G, Mauceli E et al.: A high-
many HARs in model systems as well as human and non-
resolution map of human evolutionary constraint using 29
human primate cells. These approaches will enable the mammals. Nature 2011, 478:476-482.
This paper includes the most recent computational genome-wide scan
validation and comparative analysis of HARs in more cell
for HARs. It also includes similar analyses aimed at identifying primate
types and a larger range of developmental stages, which is
accelerated regions. Both sets of accelerated regions are analyzed for
critical for discovery of HARs with divergent enhancer their genomic distributions and potential gene targets.
activity. They may also lead to ways to easily test non- 5. Initial sequence of the chimpanzee genome and comparison
with the human genome. Nature 2005, 437:69-87.
enhancer functions, such as insulators and repressors for
which there are currently no straightforward assays. 6. Varki A, Altheide TK: Comparing the human and chimpanzee
genomes: searching for needles in a haystack. Genome Res
2005, 15:1746-1758.
Without a doubt, we are likely to learn the molecular
7. Prabhakar S, Visel A, Akiyama JA, Shoukry M, Lewis KD, Holt A,
functions of many more HARs in the coming decade. But
Plajzer-Frick I, Morrison H, Fitzpatrick DR, Afzal V et al.: Human-
the critical downstream functional studies needed to link specific gain of function in a developmental enhancer. Science
2008, 321:1346-1350.
molecular changes to traits remain low-throughput and
challenging for the foreseeable future. Perhaps as more 8. Oksenberg N, Stevison L, Wall JD, Ahituv N: Function and
regulation of AUTS2, a gene implicated in autism and human
humans are sequenced we will be able to study the traits
evolution. PLoS Genet 2013, 9:e1003221.
of individuals with ancestral or mutant versions of HARs This manuscript experimentally characterizes predicted developmental
enhancers nearby the gene AUTS2, which is associated with autism and
to discover functional effects at the population level. It
also shows signatures of recent positive selection in humans. The authors
will be particularly interesting to discover disease associ- show that a HAR in the AUTS2 locus functions as a neurodevelopmental
enhancer.
ations in HARs and to eventually unravel the roles HARs
played in the evolution of human disease. 9. Capra JA, Erwin GD, McKinsey G, Rubenstein JL, Pollard KS:
Many human accelerated regions are developmental
enhancers. Philos Trans R Soc Lond B Biol Sci 2013,
In conclusion, it is important to remember that accelerated 368:20130025.
This is the largest functional study of HARs published to date. The authors
regions are not a human-specific trait. Overall, we are not a
present sequence and functional genomics evidence that HARs are
particularly fast-evolving species. There have been more human-specific developmental enhancers. They validate test 29 of the
top HAR enhancer predictions and show that 24 have enhancer activity,
sequence changes [5] and potentially more selective
five of which have differences in activity between human and chimpanzee
events [53,54] in the chimp lineage than in ours. In fact, sequences.
the statistical techniques for identifying accelerated
10. Holloway AK, Begun DJ, Siepel A, Pollard KS: Accelerated
regions have already been applied to other lineages sequence divergence of conserved genomic elements in
Drosophila melanogaster. Genome Res 2008, 18:1592-1601.
[4 ,10]. The data and methods are already available to
explore patterns of accelerated region evolution across 11. Prufer K, Racimo F, Patterson N, Jay F, Sankararaman S,
Sawyer S, Heinze A, Renaud G, Sudmant PH, de Filippo C et al.:
the mammalian phylogeny. These studies will shed light
The complete genome sequence of a Neanderthal from the
on what, if anything, is uniquely human about the genes Altai Mountains. Nature 2014, 505:43-49.
and pathways targeted by accelerated evolution in our
12. Meyer M, Kircher M, Gansauge MT, Li H, Racimo F, Mallick S,
species. Schraiber JG, Jay F, Prufer K, de Filippo C et al.: A high-coverage
genome sequence from an archaic Denisovan individual.
Science 2012, 338:222-226.
Acknowledgements
13. Maricic T, Gunther V, Georgiev O, Gehre S, Curlin M, Schreiweis C,
This work was supported by the San Simeon Fund and institutional funds Naumann R, Burbano HA, Meyer M, Lalueza-Fox C et al.: A recent
from the Gladstone Institutes. evolutionary change affects a regulatory element in the human
FOXP2 gene. Mol Biol Evolut 2013, 30:844-852.
This manuscript investigates a positively selected region in an exon of
FOXP2, a gene required for normal development of speech and language.
Appendix A. Supplementary data
The authors show that a mutation in a POU3F2 binding site located in this
Supplementary material related to this article can be found, in the online region arose after divergence from Neanderthals and binds POU3F2 less
version, at http://dx.doi.org/10.1016/j.gde.2014.07.005. effciently than the ancestral allele.
www.sciencedirect.com Current Opinion in Genetics & Development 2014, 29:15–21
20 Genetics of human origin
14. Akey JM: Constructing genomic maps of positive selection in This manuscript details an experimental effort to sequence archaic
humans: where do we go from here? Genome Res 2009, hominin HAR sequences via custom array capture and high-throughput
19:711-722. sequencing. The authors estimate that 8% of HAR mutations occurred
after divergence from Neanderthals and Denisovans.
15. Nielsen R, Bustamante C, Clark AG, Glanowski S, Sackton TB,
Hubisz MJ, Fledel-Alon A, Tanenbaum DM, Civello D, White TJ 32. Drmanac R, Sparks AB, Callow MJ, Halpern AL, Burns NL,
et al.: A scan for positively selected genes in the genomes of Kermani BG, Carnevali P, Nazarenko I, Nilsen GB, Yeung G et al.:
humans and chimpanzees. PLoS Biol 2005, 3:e170. Human genome sequencing using unchained base reads on
self-assembling DNA nanoarrays. Science 2010, 327:78-81.
16. Kosiol C, Vinar T, da Fonseca RR, Hubisz MJ, Bustamante CD,
Nielsen R, Siepel A: Patterns of positive selection in six 33. Kostka D, Hubisz MJ, Siepel A, Pollard KS: The role of GC-biased
Mammalian genomes. PLoS Genet 2008, 4:e1000144. gene conversion in shaping the fastest evolving regions of the
human genome. Mol Biol Evolut 2012, 29:1047-1057.
17. Siepel A, Bejerano G, Pedersen JS, Hinrichs AS, Hou M,
The authors present evolutionary models for the joint effects of selection
Rosenbloom K, Clawson H, Spieth J, Hillier LW, Richards S
and biased gene conversion, as well as statistical tests for distinguishing
et al.: Evolutionarily conserved elements in vertebrate,
positive selection, biased gene conversion, and loss of contraint. They
insect, worm, and yeast genomes. Genome Res 2005,
15:1034-1050. show that the majority of HARs are most consistent with the positive
selection model.
18. Hubisz MJ, Pollard KS, Siepel A: PHAST and RPHAST:
34. Katzman S, Kern AD, Pollard KS, Salama SR, Haussler D: GC-
phylogenetic analysis with space/time models. Brief Bioinform
biased evolution near human accelerated regions. PLoS Genet
2011, 12:41-51.
2010, 6:e1000960.
This paper presents the PHAST software package, which provides
statistics and bioinformatics tools that can be used to identify HARs. It
35. Galtier N, Duret L: Adaptation or biased gene conversion?
includes a detailed vignette about how to compute conserved elements
Extending the null hypothesis of molecular evolution. Trend
and test them for accelerated substitutions in a lineage of interest.
Genet 2007, 23:273-277.
19. Pollard KS, Salama SR, Lambert N, Lambot MA, Coppens S,
36. Ratnakumar A, Mousset S, Glemin S, Berglund J, Galtier N,
Pedersen JS, Katzman S, King B, Onodera C, Siepel A et al.: An
Duret L, Webster MT: Detecting positive selection within
RNA gene expressed during cortical development evolved
genomes: the problem of biased gene conversion. Philos Trans
rapidly in humans. Nature 2006, 443:167-172.
R Soc Lond B Biol Sci 2010, 365:2571-2580.
20. Pollard KS, Salama SR, King B, Kern AD, Dreszer T, Katzman S,
37. Berglund J, Pollard KS, Webster MT: Hotspots of biased
Siepel A, Pedersen JS, Bejerano G, Baertsch R et al.: Forces
nucleotide substitutions in human genes. PLoS Biol 2009,
shaping the fastest evolving regions in the human genome.
7:e26.
PLoS Genet 2006, 2:e168.
21. Prabhakar S, Noonan JP, Paabo S, Rubin EM: Accelerated 38. Capra JA, Hubisz MJ, Kostka D, Pollard KS, Siepel A: A model-
evolution of conserved noncoding sequences in humans. based analysis of GC-biased gene conversion in the human
Science 2006, 314:786. and chimpanzee genomes. PLoS Genet 2013, 9:e1003684.
22. Bird CP, Stranger BE, Liu M, Thomas DJ, Ingle CE, Beazley C, 39. Katzman S, Capra JA, Haussler D, Pollard KS: Ongoing GC-
Miller W, Hurles ME, Dermitzakis ET: Fast-evolving noncoding biased evolution is widespread in the human genome and
sequences in the human genome. Genome Biol 2007, 8:R118. enriched near recombination hot spots. Genome Biol Evolut
2011, 3:614-626.
23. Bush EC, Lahn BT: A genome-wide screen for noncoding
elements important in primate evolution. BMC Evolut Biol 2008, 40. Sumiyama K, Saitou N: Loss-of-function mutation in a
8:17. repressor module of human-specifically activated enhancer
HACNS1. Mol Biol Evolut 2011, 28:3005-3007.
24. Siepel A, Diekhans M, Brejova B, Langton L, Stevens M,
Comstock CL, Davis C, Ewing B, Oommen S, Lau C et al.: 41. Duret L, Galtier N: Comment on ‘‘Human-specific gain of
Targeted discovery of novel human exons by comparative function in a developmental enhancer’’. Science 2009, 323:714
genomics. Genome Res 2007, 17:1763-1773. 714; author reply.
25. Dennis MY, Nuttle X, Sudmant PH, Antonacci F, Graves TA, 42. Babbitt CC, Warner LR, Fedrigo O, Wall CE, Wray GA: Genomic
Nefedov M, Rosenfeld JA, Sajjadian S, Malig M, Kotkiewicz H signatures of diet-related shifts during human origins. Proc
et al.: Evolution of human-specific neural SRGAP2 genes by Biol Sci R Soc 2011, 278:961-969.
incomplete segmental duplication. Cell 2012, 149:912-922.
43. Kamm GB, Lopez-Leal R, Lorenzo JR, Franchini LF: A fast-
26. Charrier C, Joshi K, Coutinho-Budd J, Kim JE, Lambert N, de evolving human NPAS3 enhancer gained reporter expression
Marchena J, Jin WL, Vanderhaeghen P, Ghosh A, Sassa T et al.: in the developing forebrain of transgenic mice. Philos Trans R
Inhibition of SRGAP2 function by its human-specific paralogs
Soc Lond B Biol Sci 2013, 368:20130019.
induces neoteny during spine maturation. Cell 2012, 149:923-
935. 44. Kamm GB, Pisciottano F, Kliger R, Franchini LF: The
developmental brain gene NPAS3 contains the largest number
27. McLean CY, Reno PL, Pollen AA, Bassan AI, Capellini TD,
of accelerated regulatory sequences in the human genome.
Guenther C, Indjeian VB, Lim X, Menke DB, Schaar BT et al.:
Mol Biol Evolut 2013, 30:1088-1102.
Human-specific loss of regulatory DNA and the evolution of
This manuscript functionally characterizes enhancers in the NPAS3 locus,
human-specific traits. Nature 2011, 471:216-219.
one of the largest clusters of HARs in the human genome. The authors
demonstrate that one HAR drives human-specific expression in the
28. Kostka D, Hahn MW, Pollard KS: Noncoding sequences near
developing embryo.
duplicated genes evolve rapidly. Genome Biol Evolut 2010,
2:518-533.
45. Harrow J, Frankish A, Gonzalez JM, Tapanari E, Diekhans M,
Kokocinski F, Aken BL, Barrell D, Zadissa A, Searle S et al.:
29. Paten B, Earl D, Nguyen N, Diekhans M, Zerbino D, Haussler D:
GENCODE: the reference human genome annotation for The
Cactus: algorithms for genome multiple sequence alignment.
ENCODE Project. Genome Res 2012, 22:1760-1774.
Genome Res 2011, 21:1512-1528.
30. Dubchak I, Poliakov A, Kislyuk A, Brudno M: Multiple whole- 46. Washietl S, Kellis M, Garber M: Evolutionary dynamics and
genome alignments without a reference organism. Genome tissue specificity of human long noncoding RNAs in six
Res 2009, 19:682-689. mammals. Genome Res 2014, 24:616-628.
31. Burbano HA, Green RE, Maricic T, Lalueza-Fox C, de la Rasilla M, 47. Erwin GD, Oksenberg N, Truty RM, Kostka D, Murphy KK,
Rosas A, Kelso J, Pollard KS, Lachmann M, Paabo S: Analysis of Pollard KS, Ahituv N, Capra JA: Integrating diverse datasets
human accelerated DNA regions using archaic hominin improves developmental enhancer prediction. PLoS Comput
genomes. PLoS ONE 2012, 7:e32877. Biol 2014.
Current Opinion in Genetics & Development 2014, 29:15–21 www.sciencedirect.com
Genesis and functions of Human Accelerated Regions Hubisz and Pollard 21
48. Cotney J, Leng J, Yin J, Reilly SK, DeMare LE, Emera D, Ayoub AE, 53. Bakewell MA, Shi P, Zhang J: More genes underwent positive
Rakic P, Noonan JP: The evolution of lineage-specific selection in chimpanzee evolution than in human evolution.
regulatory activities in the human embryonic limb. Cell 2013, Proc Natl Acad Sci U S A 2007, 104:7489-7494.
154:185-196.
The authors report epigenetic evidence that several HARs function as 54. Pollard KS, Hubisz MJ, Rosenbloom KR, Siepel A: Detection of
developmental enhancers. They also report human-specific gains of nonneutral substitution rates on mammalian phylogenies.
enhancer marks in embryonic tissues. Genome Res 2010, 20:110-121.
49. Ritter DI, Li Q, Kostka D, Pollard KS, Guo S, Chuang JH: The 55. Nielsen R, Hellmann I, Hubisz M, Bustamante C, Clark AG: Recent
importance of being cis: evolution of orthologous fish and and ongoing selection in the human genome. Nat Rev Genet
mammalian enhancer activity. Mol Biol Evolut 2010, 27:2322- 2007, 8:857-868.
2332.
56. Yang Z: PAML 4 phylogenetic analysis by maximum likelihood.
50. Melnikov A, Murugan A, Zhang X, Tesileanu T, Wang L, Rogov P, Mol Biol Evolut 2007, 24:1586-1591.
Feizi S, Gnirke A, Callan CG Jr, Kinney JB et al.: Systematic
dissection and optimization of inducible enhancers in human 57. Pedersen JS, Bejerano G, Siepel A, Rosenbloom K, Lindblad-
cells using a massively parallel reporter assay. Nat Biotechnol Toh K, Lander ES, Kent J, Miller W, Haussler D: Identification and
2012, 30:271-277. classification of conserved RNA secondary structures in the
human genome. PLoS Comput Biol 2006, 2:e33.
51. Patwardhan RP, Hiatt JB, Witten DM, Kim MJ, Smith RP, May D,
Lee C, Andrie JM, Lee SI, Cooper GM et al.: Massively parallel 58. Kostka D, Friedrich T, Holloway AK, Pollard KS: motifDiverge: A
functional dissection of mammalian enhancers in vivo. Model for Assessing the Statistical Significance of Gene
Nat Biotechnol 2012, 30:265-270. Regulatory Motif Divergence Between two DNA Sequences.
2014.
52. Larson MH, Gilbert LA, Wang X, Lim WA, Weissman JS, Qi LS:
CRISPR interference (CRISPRi) for sequence-specific control
of gene expression. Nat Protoc 2013, 8:2180-2196.
www.sciencedirect.com Current Opinion in Genetics & Development 2014, 29:15–21