Category Archives: human genetics

More details on the Neanderthal legacy in modern humans

Is straight hair Neanderthal?

A quick note on two recent studies on the relevance of Neanderthal introgression on modern Humankind, notably the “out of Africa” branch.

Sriran Sankararaman et al., The genomic landscape of Neanderthal ancestry in present-day humans. Nature 2014. Pay per viewLINK [doi:doi:10.1038/nature12961]


Genomic studies have shown that Neanderthals interbred with modern humans, and that non-Africans today are the products of this mixture1, 2. The antiquity of Neanderthal gene flow into modern humans means that genomic regions that derive from Neanderthals in any one human today are usually less than a hundred kilobases in size. However, Neanderthal haplotypes are also distinctive enough that several studies have been able to detect Neanderthal ancestry at specific loci1, 3, 4, 5, 6, 7, 8. We systematically infer Neanderthal haplotypes in the genomes of 1,004 present-day humans9. Regions that harbour a high frequency of Neanderthal alleles are enriched for genes affecting keratin filaments, suggesting that Neanderthal alleles may have helped modern humans to adapt to non-African environments. We identify multiple Neanderthal-derived alleles that confer risk for disease, suggesting that Neanderthal alleles continue to shape human biology. An unexpected finding is that regions with reduced Neanderthal ancestry are enriched in genes, implying selection to remove genetic material derived from Neanderthals. Genes that are more highly expressed in testes than in any other tissue are especially reduced in Neanderthal ancestry, and there is an approximately fivefold reduction of Neanderthal ancestry on the X chromosome, which is known from studies of diverse species to be especially dense in male hybrid sterility genes10, 11, 12. These results suggest that part of the explanation for genomic regions of reduced Neanderthal ancestry is Neanderthal alleles that caused decreased fertility in males when moved to a modern human genetic background.

B. Bernot & J.M. Akey, Resurrecting Surviving Neandertal Lineages from Modern Human Genomes. Science 2014. Pay per viewLINK [doi:10.1126/science.1245938]


Anatomically modern humans overlapped and mated with Neandertals such that non-African humans inherit ~1-3% of their genomes from Neandertal ancestors. We identified Neandertal lineages that persist in the DNA of modern humans, in whole-genome sequences from 379 European and 286 East Asian individuals, recovering over 15 Gb of introgressed sequence that spans ~20% of the Neandertal genome (FDR = 5%). Analyses of surviving archaic lineages suggests that there were fitness costs to hybridization, admixture occurred both before and subsequent to divergence of non-African modern humans, and Neandertals were a source of adaptive variation for loci involved in skin phenotypes. Our results provide a new avenue for paleogenomics studies, allowing substantial amounts of population-level DNA sequence information to be obtained from extinct groups even in the absence of fossilized remains.

I don’t have access to the papers (update: I do have the second one now) but, honestly, I don’t have time either, so, even with full access, I would have to be rather shallow, given the complexity of the matter.
Nevertheless I would highlight the following:
Fitness costs
Areas of dense gene presence tend to be more depleted of Neanderthal inheritance, meaning that, at least in many cases Neanderthal genes were deleterious (harmful) in the context of the H. sapiens genome. It’s probable that they worked better in their “native” context of the Neanderthal genome but we must not understimate the risks of low genetic diversity, a problem that affected Neanderthals as well as H. heidelbergensis (species probably including Denisovans or at least their non-Neanderthal ancestry).
Partial hybrid infertility
The areas of very low Neanderthal genetic influence include those of reproductive relevance, including genes affecting the testes and the chromosome X. This is typical of the hybrid infertility phenomenon, which is part of species divergence, making more difficult or even impossible that hybrids can reproduce. This particular item emphasizes that the differential speciation of Neanderthals and H. sapiens was in a quite advance stage already some 100 Ka ago, what does not seem too consistent with the lowest estimates for the divergence of both human species (H. sapiens have been diverging for some 200 Ka and are still perfectly inter-fertile). 
Adaptive Neanderthal hair introgression
On the other hand the Neanderthal genetic legacy has been best preserved in genes that appear to affect keratin (affecting skin, nails and hair). This bit I consider of particular interest because, based on the modern distribution of hair texture phenotypes, I have often speculated that straight hair may be a Neanderthal heritage and this finding seems supportive of my speculation.
It’s possible that straight hair conferred some sort of advantage in some of the new areas colonized by H. sapiens, maybe providing better insulation against rain or cold (the ancestral Sapiens thinly curly hair phenotype is probably an adaption to tropical climate, allowing for a ventilated insulation of the head).
Some 20% of the Neanderthal genome still lives in us
Collectively, that is. The actual expressed genes are probably a quite less important proportion anyhow and the actual individual Neanderthal legacy (expressing genes and junk together) seldom is greater than 3% in any case.

Is the ability to digest milk in Europeans caused by ancient social inequality?

I’ve got involved these days in a discussion at Dienekes’ Anthropology Blog on the causes of lactase persistance (LP), i.e. the ability to digest milk as adults, in Europe. 
The discussion orbits around a recent pay-per-view study by O.O. Sverrisdóttir, which claims, with some soundness for what I can discern, that LP in Europeans must have gone through positive selection. 
Actually the study, as most of its kind, deals only with one LP marker, the well known SNP rs4988235, whose T variant allows adults (in dominant fashion) to digest milk, an ability often lost after weaning. 
As I discussed back in 2010, there must be other such SNPs because actual LP phenotype only partly corresponds with the known LP alleles. But for whatever is worth, this is the (2010) “known allele” LP map:
In Europe at least, it essentially corresponds with the T variant of rs49235, which concentrates in Scandinavia, Atlantic Islands and the Basque/SW French area. 
At first I boarded the discussion with perplexity, because, even if the positive selection argument seems sound, it seems hard to find a reason for it: milk is not such a “great” source of food, excepting the issue of calcium and a high content of protein and fat, and the occasional claims that it is related to vitamin D deficiency seem extremely feeble because this vitamin is present at extremely low frequencies in natural milk, being rickets (where milk’s extra calcium could play some role) only a “less important” side effect of vitamin D deficiency, because its main harmful effect is to impair early brain development, a most serious problem for which calcium seems quite meaningless. So why would the ability to digest milk would have become such a matter of life or death to be actively selected for generation after generation until near-fixation?
A key piece of information is that not a single sequenced Neolithic farmer has ever been found to carry the relevant LP allele (being all CC) and only since Chalcolithic we begin to find some TT and CT individuals. These are found in Sweden and in the southern areas of the Basque Country (see here for a lengthier discussion):
  • In Götland (Pitted Ware culture) only 1/20 alleles was T (i.e. 1/10
    persons had the CT combo, all the rest being CC and therefore likely
    lactose intolerants). 
  • In Longar (Navarre, dated to c. 4500 BP)
    1/7 individuals was TT, while the other six were CC (intolerant). There
    were no CT cases.
  • In San Juan Ante Porta Latinam (SJAPL, Araba, dated to c. 5000 BP), 4/19 were TT, 2/19 were CT, while the remaining 13 were CC.
In the Basque cases we can appreciate that there must have already been two different populations regarding this SNP, because the CT cases are rare, implying that the two groups were only beginning to mix. It is worth mentioning that the Basque sites are odd in several aspects: on one side they seem to be military cemeteries (mostly males, arrow injuries and arrow points) and, on the other, they are rather exceptional in the Basque historical sequence of mtDNA pools (a lot more K and some other lineages than usual, less H and U).
But a key finding in this study is that a Neolithic sequence from Atapuerca (near Burgos city, historical Basque SW border) was again CC for the relevant SNP (and therefore likely lactose intolerant). So it is very possible that proto-Basques did not have the T allele in notable frequencies either (although I keep some reservations for lack of larger samples).
Whatever the case, if the T allele was selected positively as it seems, there must be a powerful reason for it. Was it cows, as some have claimed a bit too vehemently? I doubt it. 
Why? Because for all we know from the Middle Ages, a period very similar in many aspects to the Metal Ages, it were goats and not cows the main providers of milk. This makes total sense because the hardy goats are rather inexpensive to rear, while cows are more costly and were often reserved for traction jobs. In most cases, cow produce, be it milk or meat, was an expensive luxury apt only for the upper echelons of a society that was becoming more and more hierarchical and unequal since precisely the Chalcolithic period. 
Some oral accounts I have heard tell that not so long ago “acorn bread and goat milk” were often staple for the poor. In other areas maybe it was not acorn bread but, say, oat meal (or whatever else), but almost certainly the milk came almost invariably from goat udders, which very efficiently transform leaves and almost any vegetable, even thorny ones, into milk (and meat) for our consumption.
It is crucial to understand that only if milk was a key survival staple, LP would have become fixated. Otherwise people would have preferred alternative foods and survived in similar shape, so positive selection would never have happened at this locus (non-LP individuals would have survived easily, selection would never have happened or would have been mild enough to retain much greater diversity). 
It is also crucial to understand that, for all we know, this positive selection only happened since the Chalcolithic, i.e. when social stratification, inequality and private aristocratic property became common. Obviously the upper classes (or castes) had no problems accessing high quality foods, including meat, but the masses probably had growing problems in this aspect as the land and cattle became more and more concentrated in few hands. 
Even where a wide class of free peasants existed, as was probably the case in much of Atlantic Europe, these were surely often not well-off enough to afford dairy cows. Instead goats would have been available for almost everybody, even the poorest of farmers. And very likely they were the only steady supply of proteins and fat, mostly via milk.
Plausibly this need of extra nutrients of animal origin was more intense in the Atlantic areas of Europe because cereals do not perform so well in the prevalent humid conditions. Also before the medieval development of the heavy plough, the deep Atlantic soils were not at all as productive as they are now (and that’s why NW Europe only got its economic prominence in the last millennium, being before a peripheral area to the much more productive Mediterranean climate). 
But climatic and agricultural issues aside, I strongly suspect that the main driver of LP positive selection, were goats, because these and their dairy produce were almost certainly available for almost everyone and, in the Metal Ages, the vast majority of people were farmers, often rather poor peasants who had to rely on their goats for survival, very especially in the bad times.
I really do not see any other explanation that fits the data.

PS- This social inequality & goats argument makes sense assuming that the positive selection theory is correct. However before I fully embrace it, I would need a half-decent sample of aDNA sequences from the Atlantic areas of Europe, notably Britain & Ireland, the Basque Country & SW France and mainland Scandinavia, where the T allele peaks. I say because what we find in some Chalcolithic sites, notably in the Basque Country, rather strongly suggests that there was already a TT population somewhere and we have not yet found it. So maybe some of the premises of the positive selection theory are not as sound as I said above – but we do not know yet.


Exercise causes epigenetic changes in fat cells

It seems more and more obvious than rather just burning fat, what exercise does against overweight is to alter the way the body works in more subtle pathways.
Tina Röhn et al., A Six Months Exercise Intervention Influences the Genome-wide DNA Methylation Pattern in Human Adipose Tissue. PLoS Genetics 2013. Open access → LINK [doi:10.1371/journal.pgen.1003572]


Epigenetic mechanisms are implicated in gene regulation and the
development of different diseases. The epigenome differs between cell
types and has until now only been characterized for a few human tissues.
Environmental factors potentially alter the epigenome. Here we describe
the genome-wide pattern of DNA methylation in human adipose tissue from
23 healthy men, with a previous low level of physical activity, before
and after a six months exercise intervention. We also investigate the
differences in adipose tissue DNA methylation between 31 individuals
with or without a family history of type 2 diabetes. DNA methylation was
analyzed using Infinium HumanMethylation450 BeadChip, an array
containing 485,577 probes covering 99% RefSeq genes. Global DNA
methylation changed and 17,975 individual CpG sites in 7,663 unique
genes showed altered levels of DNA methylation after the exercise
intervention (q<0.05). Differential mRNA expression was present in 1/3 of gene regions with altered DNA methylation, including RALBP1, HDAC4 and NCOR2 (q<0.05). Using a luciferase assay, we could show that increased DNA methylation in vitro of the RALBP1 promoter suppressed the transcriptional activity (p
= 0.03). Moreover, 18 obesity and 21 type 2 diabetes candidate genes
had CpG sites with differences in adipose tissue DNA methylation in
response to exercise (q<0.05), including TCF7L2 (6 CpG sites) and KCNQ1
(10 CpG sites). A simultaneous change in mRNA expression was seen for 6
of those genes. To understand if genes that exhibit differential DNA
methylation and mRNA expression in human adipose tissue in vivo affect adipocyte metabolism, we silenced Hdac4 and Ncor2
respectively in 3T3-L1 adipocytes, which resulted in increased
lipogenesis both in the basal and insulin stimulated state. In
conclusion, exercise induces genome-wide changes in DNA methylation in
human adipose tissue, potentially affecting adipocyte metabolism.

Figure 2. Analysis flowchart.
Table 3. Changes in adipose tissue DNA methylation in response to a 6 months exercise intervention. Significant CpG sites (q<0.05) with the biggest change in DNA methylation (>8%).

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Posted by on July 7, 2013 in epigenetics, health, human genetics


HERC2 haplotypes worldwide study at Kurdish DNA

I must congratulate again Palisto of Kurdish DNA blog for his excellent work on the description of HERC2 haplotypes and their frequency across world populations. It is not a peer-reviewed academic paper but it could well be, and within the high quality sector.
Palisto, The color of the eyes: at least 17 HERC2 variants in Human gene pool. Kurdish DNA 2013. Freely accessible blog articleLINK
After initially detecting seven haplotypes in the Kurdish genetic pool (which were named ht1-7) and then studying these in the Eurasian gene pool, he decided to study the African haplotypes, largely in the “other” category, as well as comparing them all with the known Neanderthal and Denisovan sequences, at the very least to infer a root. The main result is this tree:
So the ancestral haplotype is ht13, found not just among Neanderthals and Denisovans, but also among scattered populations of H. sapiens both in Africa as in Eurasia-plus. 
From it hang ht8 (Homo sapiens, found in and outside Africa) and ht18 (Neanderthal-exclusive).
This main branch has two major sub-haplogroups, which I will label D and E for convenience (A would be ht13, B ht8, and C Neanderthal-only ht18). Haplogroup D (hts 11, 16 and 17) seems to have remained in Africa (only ht 11 was detected at low frequencies in Lebanon), while haplogroup E (all the rest) massively participated in the migration out of Africa (OoA).
However it must have done already in highly diversified form, as most named haplotypes are found at significant frequencies both outside and inside Africa. There are four exceptions only:
  1. Ht9 is only found in Africa (with a minor Arabian exception), so this haplotype did not took part in the OoA.
  2. Ht15 has not been found in Africa instead, so it is possible that it evolved already in Eurasia.
  3. Ht2 and its descendant ht1 (both of which cause blue eyes, albeit in recessive manner) don’t seem to exist in Africa either (with the exception of the HGDP San sample, which seems notably admixed with Europeans, at levels of almost 20%, not your typical Bushmen really), so again they probably arose already in Eurasia. 
These are the wider regional frequencies:

However at the original article there is a much more detailed list, which is probably more interesting to use when pondering each haplotype. For example the overall data for America is pretty much irrelevant, as it groups native peoples with mixed creole ones.
For example we can see that “blue eyes” ancestral haplotype ht2 looks like originated in West Asia, and it may also be the case of its descendant ht1. 
Ht 15 in turn may well have coalesced in Altai, from where it spread to mostly Native American peoples (represented by Mestizo Colombians). A similar pattern can be seen in ht14, however this must be original from Africa (the Biaka have it, as do Mozabites) and therefore it is found also in some other scattered populations like Cambodians, Sindhi, etc.
Something I wonder about is the low diversity displayed by East Asians in this haplotype. Or inversely, why did West Eurasians evolve so all non-African novel variants? While there is still some left to analyze in the ND box, it is very small in East Asia. I wonder if it has some relation with skin pigmentation pathways indirectly influencing this change somehow.

Reconstructing human demographic history from IBS segments

Figure 1. An eight base-pair tract of identity by state (IBS).
Identity-by-state (IBS) segments are those located between any two SNPs (polymorphisms, letters that vary among individuals). According to this new paper, they seem to be evolutionarily neutral and therefore their length, modified by recombination events each new generation, is a good trail to reconstruct human demographic history.
Kelley Harris & Rasmus Nielsen, Inferring Demographic History from a Spectrum of Shared Haplotype Lengths. PLoS Genetics 2013. Open accessLINK [doi:10.1371/journal.pgen.1003521]


There has been much recent excitement about the use of genetics to elucidate ancestral history and demography. Whole genome data from humans and other species are revealing complex stories of divergence and admixture that were left undiscovered by previous smaller data sets. A central challenge is to estimate the timing of past admixture and divergence events, for example the time at which Neanderthals exchanged genetic material with humans and the time at which modern humans left Africa. Here, we present a method for using sequence data to jointly estimate the timing and magnitude of past admixture events, along with population divergence times and changes in effective population size. We infer demography from a collection of pairwise sequence alignments by summarizing their length distribution of tracts of identity by state (IBS) and maximizing an analytic composite likelihood derived from a Markovian coalescent approximation. Recent gene flow between populations leaves behind long tracts of identity by descent (IBD), and these tracts give our method power by influencing the distribution of shared IBS tracts. In simulated data, we accurately infer the timing and strength of admixture events, population size changes, and divergence times over a variety of ancient and recent time scales. Using the same technique, we analyze deeply sequenced trio parents from the 1000 Genomes project. The data show evidence of extensive gene flow between Africa and Europe after the time of divergence as well as substructure and gene flow among ancestral hominids. In particular, we infer that recent African-European gene flow and ancient ghost admixture into Europe are both necessary to explain the spectrum of IBS sharing in the trios, rejecting simpler models that contain less population structure.

The most interesting graph, synthesizing the result for standard HapMap European and African proxy samples is figure 7. However I have major issues with the age estimates, which seem to be half what is needed to be realistic according to archaeological and other genetic data (unlineal haplogroup history, for example). Therefore I have annotated it with a revised timeline, so it fits better with the objective data:

Figure 7. A history inferred from IBS sharing in Europeans and Yorubans.
This is the simplest history we found to satisfactorily explain IBS tract sharing in the 1000 Genomes trio data. It includes ancient ancestral population size changes, an out-of-African bottleneck in Europeans, ghost admixture into Europe from an ancestral hominid, and a long period of gene flow between the diverging populations.
(Right margin annotations by Maju).

Indeed the simplest revision of the time-scale was to double it. I guess it can be refined a bit more than that, maybe pushing it a bit further into the past, but the alternative time-scale I propose fits closely enough with known archaeological data like the time of the OoA to Arabia and Palestine or the spread of Acheulean (and therefore H. ergaster, common ancestor of Neanderthals and H. sapiens) out of Africa c. 1 Ma ago to illustrate that the reconstruction seems pretty much correct overall but fails when estimating the dates (because of scholastic-autistic academic biases that are too common in the field of human population genetics).

Update: even Dienekes agrees, on his own well documented reasoning, with a x2 mutation rate being necessary for the above graph.


Not more than 2% of educational attainment can be attributed to genes

Correction: a reader indicates that ~2% is the amount of influence from the addition of many SNPs (often with a tiny estimated impact each), while ~0.2% is the amount of influence estimated for each of the three most influential SNPs, not together. I stand corrected (but still a very small influence). 

While the authors express themselves hopeful that this proportion will increase in the future, so far only three SNPs have been found with a clear correlation to educational attainment, representing 0.2% of all genetic influence. When they consider a linear polygenic score from all measured SNPs, they can’t still measure more than an elusive 2% of putative genetic causes for these differences.

Cornelius A. Rietveld et al., GWAS of 126,559 Individuals Identifies Genetic Variants Associated with Educational Attainment. Science 2013. Pay per viewLINK [doi:10.1126/science.1235488]


A genome-wide association study of educational attainment was conducted in a discovery sample of 101,069 individuals and a replication sample of 25,490. Three independent SNPs are genome-wide significant (rs9320913, rs11584700, rs4851266), and all three replicate. Estimated effects sizes are small (R2 ≈ 0.02%), approximately 1 month of schooling per allele. A linear polygenic score from all measured SNPs accounts for ≈ 2% of the variance in both educational attainment and cognitive function. Genes in the region of the loci have previously been associated with health, cognitive, and central nervous system phenotypes, and bioinformatics analyses suggest the involvement of the anterior caudate nucleus. These findings provide promising candidate SNPs for follow-up work, and our effect size estimates can anchor power analyses in social-science genetics.

Seriously, if they could find no more than an elusive ~2% in more than 100,000 individuals… how do they expect to ever find any more?
Let’s be honest: there is only very limited genetic influence on intelligence and cognitive or educational attainment, because, after all what genes do with the brain is to lay out the hardware, so to say, with all the software (but surely a basic emotional-instinctual ROM) being the product of environmental interaction. It’s possible that there is minor variance in the hardware (genetics) and maybe even more in its initial configuration (basic epigenetics) but, the same that most desktop computers can do the same things, with less important variability, human brains can too (unless somehow damaged).

Posted by on June 2, 2013 in human genetics, intelligence, mind, psychology


‘Neanderthal’ allele that is probably not Neanderthal in modern humans

This is a generally well finished study on an allele shared by (some) modern humans, Neanderthals and “Denisovans” but which the authors properly gouge to be probably not Neanderthal in origin among us.
Omer Gockumen et al., Balancing Selection on a Regulatory Region Exhibiting Ancient Variation That Predates Human–Neandertal Divergence. PLoS Genetics 2013. Open accessLINK [doi:10.1371/journal.pgen.1003404]

Ancient population structure shaping contemporary genetic variation has been recently appreciated and has important implications regarding our understanding of the structure of modern human genomes. We identified a ~36-kb DNA segment in the human genome that displays an ancient substructure. The variation at this locus exists primarily as two highly divergent haplogroups. One of these haplogroups (the NE1 haplogroup) aligns with the Neandertal haplotype and contains a 4.6-kb deletion polymorphism in perfect linkage disequilibrium with 12 single nucleotide polymorphisms (SNPs) across diverse populations. The other haplogroup, which does not contain the 4.6-kb deletion, aligns with the chimpanzee haplotype and is likely ancestral. Africans have higher overall pairwise differences with the Neandertal haplotype than Eurasians do for this NE1 locus (p<10−15). Moreover, the nucleotide diversity at this locus is higher in Eurasians than in Africans. These results mimic signatures of recent Neandertal admixture contributing to this locus. However, an in-depth assessment of the variation in this region across multiple populations reveals that African NE1 haplotypes, albeit rare, harbor more sequence variation than NE1 haplotypes found in Europeans, indicating an ancient African origin of this haplogroup and refuting recent Neandertal admixture. Population genetic analyses of the SNPs within each of these haplogroups, along with genome-wide comparisons revealed significant FST (p = 0.00003) and positive Tajima’s D (p = 0.00285) statistics, pointing to non-neutral evolution of this locus. The NE1 locus harbors no protein-coding genes, but contains transcribed sequences as well as sequences with putative regulatory function based on bioinformatic predictions and in vitro experiments. We postulate that the variation observed at this locus predates Human–Neandertal divergence and is evolving under balancing selection, especially among European populations.
The paper discusses an allele (NE1) of APOBEC3G, a gene arguably related to anti-viral immunity, which is found primarily in its derived variant among non-Africans (especially South Asians, Europeans and Native Americans). In similar cases other similar studies have claimed that it should be a Neanderthal introgression, ignoring the presence of the relevant allele at low frequencies in Africa. The authors of this study do not commit this error but finding it at low frequencies not just among the Maasai and the Luhya but also among Pygmies, they consider that there is a high likelihood of the allele found among Eurasians and Native Americans to have originated among Homo sapiens in Africa and then maybe favored by natural selection or other mechanisms outside the ancestral continent. 
Figure 3. Ancient African origins of the NE1 haplogroup.
(A) Models of scenarios that could lead to NE1 haplotypes observed in humans and Neandertals. The frequency of the NE1 haplogroup is depicted in red and the frequency of the nonNE1 haplogroup in yellow. The red corresponds to higher frequencies, whereas yellow corresponds to lower frequencies of the NE1 haplotypes in the population. The arrows represent the direction of possible admixture events. The left panel represents a model, under which the NE1 haplotypes admixed into Eurasian populations (Asn and Eur) after Human-Neandertal divergence. The second model, which is depicted in the central panel, is similar to the first model, except with the addition of more recent back migration of Eurasian NE1 haplotypes into Africa (Afr). The right panel shows the third model, under which the NE1 haplotypes among humans are explained by persistence of ancient African substructure. All these scenarios were based on the assumption that the NE1 haplotype occurs at high frequency or is fixed in the Neandertal population given that the available Neandertal sequences align well to the NE1 haplotype. (B) Geographical distribution of the NE1 haplogroup. We estimated the proportion of chromosomes that carry the CNVR8163.1 deletion from various sources described in Materials and Methods. The dark red portion of each circle represents the frequency of the homozygous nonNE1 genotypes, the white represents the homozygous NE1 genotypes and the light red represents the frequency of heterozygote genotypes. Note the existence of the NE1 haplotypes (i.e., as heterozygotes, light red) among sub-Saharan African populations (e.g., LWK and ASW) as well as the high frequency of heterozygotes (light red) in the European populations. (C) The pairwise distances between the African (Afr) NE1 haplotypes, the Asian (Asn) NE1 haplotypes, and the European (Eur) NE1 haplotypes, calculated using phase 1 data from the 1000 Genomes Project. p-values were calculated by the Mann-Whitney test.

Figure 4. Selection acting on the NE1 locus.
(A) Maximum likelihood tree based on select NE1 (red) and nonNE1 (blue)
haplotypes, with the chimpanzee haplotype as an outgroup. The gray-box
indicates the estimated interval for the Human-Neandertal divergence
between 400,000–800,000 years ago [51].
Note that the coalescence at this locus is extremely long and very
unlikely to have evolved under neutral conditions as modeled here. (B)
Comparison of FST and Tajima’s D values of
10 kb intervals across the human genome. The red to dark blue gradient
indicates decreased density of observed events at a given location in
the graph. The NE1 locus, and other loci with similar profiles, are
highlighted in white.
While the Neanderthal-Sapiens divergence estimate they use (fig. 4A) is clearly more recent than I would gladly accept (I’m more into 1.3-0.9 Ma BP, based on archaeological and paleoanthropological data), it does not seem to matter for the conclusions, as they estimate that the two main haplotypes in chromosome 22 related to this allele diverged much earlier, at the beginnings of the history of the genus Homo. 
Chimpanzees by the way have the non-NE1 allele, which is therefore considered ancestral.


Bisphenol A severely disrupts fetal epigenetics

Water bottle containing bisphenol A
The most controversial chemical compound bisphenol A is found in many plastics, including sometimes those used as food or water containers. This study adds to the long list of known harms of this chemical, which nevertheless remains widely allowed.
Martha Susiarjo et al., Bisphenol A Exposure Disrupts Genomic Imprinting in the Mouse. PLoS Genetics 2013. Open accessLINK [doi:10.1371/journal.pgen.1003401]

Exposure to endocrine disruptors is associated with developmental defects. One compound of concern, to which humans are widely exposed, is bisphenol A (BPA). In model organisms, BPA exposure is linked to metabolic disorders, infertility, cancer, and behavior anomalies. Recently, BPA exposure has been linked to DNA methylation changes, indicating that epigenetic mechanisms may be relevant. We investigated effects of exposure on genomic imprinting in the mouse as imprinted genes are regulated by differential DNA methylation and aberrant imprinting disrupts fetal, placental, and postnatal development. Through allele-specific and quantitative real-time PCR analysis, we demonstrated that maternal BPA exposure during late stages of oocyte development and early stages of embryonic development significantly disrupted imprinted gene expression in embryonic day (E) 9.5 and 12.5 embryos and placentas. The affected genes included Snrpn, Ube3a, Igf2, Kcnq1ot1, Cdkn1c, and Ascl2; mutations and aberrant regulation of these genes are associated with imprinting disorders in humans. Furthermore, the majority of affected genes were expressed abnormally in the placenta. DNA methylation studies showed that BPA exposure significantly altered the methylation levels of differentially methylated regions (DMRs) including the Snrpn imprinting control region (ICR) and Igf2 DMR1. Moreover, exposure significantly reduced genome-wide methylation levels in the placenta, but not the embryo. Histological and immunohistochemical examinations revealed that these epigenetic defects were associated with abnormal placental development. In contrast to this early exposure paradigm, exposure outside of the epigenetic reprogramming window did not cause significant imprinting perturbations. Our data suggest that early exposure to common environmental compounds has the potential to disrupt fetal and postnatal health through epigenetic changes in the embryo and abnormal development of the placenta.

Eye and skin pigmentation genetics: Cape Verdeans as informative population

Cape Verde from space
Still getting updated with the backlog. Here there is an interesting study on human pigmentation using the heavily admixed Cape Verdean (essentially West African + West Iberian) population as reference.
Sandra Beleza et al., Genetic Architecture of Skin and Eye Color in an African-European Admixed Population. PLoS Genetics 2013. Open accessLINK [doi:10.1371/journal.pgen.1003372]


Variation in human skin and eye color is substantial and especially apparent in admixed populations, yet the underlying genetic architecture is poorly understood because most genome-wide studies are based on individuals of European ancestry. We study pigmentary variation in 699 individuals from Cape Verde, where extensive West African/European admixture has given rise to a broad range in trait values and genomic ancestry proportions. We develop and apply a new approach for measuring eye color, and identify two major loci (HERC2[OCA2] P = 2.3×10−62, SLC24A5 P = 9.6×10−9) that account for both blue versus brown eye color and varying intensities of brown eye color. We identify four major loci (SLC24A5 P = 5.4×10−27, TYR P = 1.1×10−9, APBA2[OCA2] P = 1.5×10−8, SLC45A2 P = 6×10−9) for skin color that together account for 35% of the total variance, but the genetic component with the largest effect (~44%) is average genomic ancestry. Our results suggest that adjacent cis-acting regulatory loci for OCA2 explain the relationship between skin and eye color, and point to an underlying genetic architecture in which several genes of moderate effect act together with many genes of small effect to explain ~70% of the estimated heritability.

Children of Praia
(CC by Otimarte)
Most interestingly maybe the authors conclude that KITLG, a gene which displays large differences in allele frequency between Africa and Eurasia and has been therefore suggested to be a cause of pigmentation differences, does not actually play any obvious role in this matter.
HERC2 (OCA2) is confirmed to be very important in eye color (semi-recessive inheritance for blue color), the only other gene known to affect eye color is SLC24A5, which is mostly involved in skin pigmentation however.  
SLC24A5 and SLC45A2 are confirmed as important pigmentation genes. However two otherwise unsuspecting genes, APBA2 (near OCA2) and GRM5TYR, are found to have also important impact in skin pigmentation.
Still most (~3/5) of the inherited pigmentation traits remain unexplained and are probably caused by some sort of complex interactions. Eye and skin pigmentation have no strong genetic correlation apparently.
Some interesting images from the paper:

Figure 1. Relationship of geography and ancestry to skin and eye color.
Individual ancestry proportions for Cape Verdeans displayed on all four panels were obtained from a supervised analysis in frappe
with K = 2 and HapMap’s CEU and YRI fixed as European and African
parental populations. (a) Bar plots of individual ancestry proportions
for Cape Verdeans across the islands. The width of the plots is
proportional to sample size (Santiago, n = 172; Fogo, n = 129; NW
cluster, n = 192; Boa Vista, n = 27). The proportion of African vs.
European ancestry of the individuals is indicated by the proportion of
blue vs. red color in each plot. (b) Individual African ancestry
distribution in the total cohort of 685 Cape Verdeans (histogram) and in
802 African Americans (kernel density curve) from the Family Blood
Pressure Program (FBPP) [21].
(c) Scatter-plot of skin color vs. Individual African ancestry
proportions. Skin color is measured by the MM index described in
Material and Methods. (d) Scatter-plot of eye color vs. Individual
African ancestry proportions. Eye color is measured by the T-index,
described in Figure 2 and Material and Methods. Points in scatter-plots are color coded according to the island of origin of the individuals.
Figure 3. GWAS results for skin and eye color in the total Cape Verdean cohort.
Results are shown as −log10(P
value) for the genotyped SNPs. Plots are ordered by chromosomal
position. (a,c) Genotype and admixture association scan results for skin
color. (b,d) Genotype and admixture association scan results for eye
color. (a,b) show the P values obtained in the initial scans and (c,d) the P values of the following scans adjusting for the strongest associated SNP (in SLC24A5 for skin color and in HERC2 for eye color). Dashed red lines correspond to the genome-wide significance threshold (P<5×10−8 in the genotype scan; P<7×10−6
in the ancestry scan [see Material and Methods]). The location and
identity of candidate genes are colored to correspond with chromosomal
location; individual SNPs are given in Table 1.
Figure 7. Genetic architecture of skin color variation.
Effect sizes of the loci associated with skin color. Effect values
represent the beta values obtained from a regression model containing
the four associated loci plus ancestry. (b) The pie chart represents the
proportion of phenotypic variation accounted for by the different
components, including non-heritable factors (~20%), the four major loci
(~35%, color-coded as in [a]), and average genomic ancestry (44%). The
heritable contributions were estimated by regression and variance
decomposition as described in Material and Methods, and are also
represented below the pie chart separately as grey (genomic ancestry) or
open (four major loci) areas. However, because of admixture
stratification, the heritable contributions overlap as described in the


Non-additive genetic models and the problem of stasis (relative stability of the genomes) and missing heritability

A simple and classical approach to genetic understanding of phenotype variability is to assume that allele influence is additive. However this may be just a mirage of imperfect methodology.
In any case the additive model approach has reached a point when it is quite obvious not enough to explain the genetic background of phenotype heritability.
Gibran Hemani et al., An Evolutionary Perspective on Epistasis and the Missing Heritability. PLoS Genetics 2013. Open access → LINK [doi:10.1371/journal.pgen.1003295]

The relative importance between additive and non-additive genetic variance has been widely argued in quantitative genetics. By approaching this question from an evolutionary perspective we show that, while additive variance can be maintained under selection at a low level for some patterns of epistasis, the majority of the genetic variance that will persist is actually non-additive. We propose that one reason that the problem of the “missing heritability” arises is because the additive genetic variation that is estimated to be contributing to the variance of a trait will most likely be an artefact of the non-additive variance that can be maintained over evolutionary time. In addition, it can be shown that even a small reduction in linkage disequilibrium between causal variants and observed SNPs rapidly erodes estimates of epistatic variance, leading to an inflation in the perceived importance of additive effects. We demonstrate that the perception of independent additive effects comprising the majority of the genetic architecture of complex traits is biased upwards and that the search for causal variants in complex traits under selection is potentially underpowered by parameterising for additive effects alone. Given dense SNP panels the detection of causal variants through genome-wide association studies may be improved by searching for epistatic effects explicitly.
It is difficult for me to explain (or even understand well in some aspects) the issues under debate here but some excerpts from the text do ring very true in my mind:
There exists a paradox in evolutionary biology. Despite a near-ubiquitous abundance of genetic variation [1]
traits under selection often evolve more slowly than expected and,
contrary to expectation, genetic variation is maintained under
selection. This problem is known as ‘stasis’ [2], [3], and it is particularly evident in fitness-related traits where the genetic variation tends to be highest [4] yet there is commonly no observed response to selection at all [5][7].
After hundreds of genome-wide association (GWA) studies [11]
a picture is emerging where the total genetic variation explained by
variants that have been individually mapped to complex traits is vastly
lower than the amount of genetic variation expected to exist as
estimated from pedigree-based studies, a phenomenon that has come to be
known as the problem of the ‘missing heritability’ [12].
Again, there are probably numerous contributing factors, and ostensibly
the most parsimonious explanation is that complex traits comprise many
small effects that GWA studies are underpowered to detect [13], [14], but whether this is the complete story deserves exploration.

Beyond the realm of complex trait genetics it appears that epistasis
does appear to be common. For example in molecular studies it is routine
to observe ‘phenotypic rescue’ where the phenotypic effect of a gene
knockout can be masked by a second knockout (e.g. [31]). Another commonly encountered form of epistasis is ‘canalisation’ [32], where phenotypes exhibit robustness to the knockout of one gene, requiring a second knockout to elicit a response (e.g. [33]).
At the macroevolutionary scale, epistasis is also of central
importance, for example it has recently been shown that an advantageous
substitution in one species is often found to be deleterious in others,
thus the substition’s effect on fitness is dependent upon the genetic
background in which it is found [34]
The results suggest that we should expect significant levels of
non-additive variation to be maintained in fitness-related traits.
One of the criticisms seems to suggest that studying homogeneous populations in GWAS is inefficient because linkage disequilibrium (LD) masks the non-additive effect of the alleles, making them appear, erroneously, as additive. 
… it was observed that even with modest reductions in LD between causal
variants and observed SNPs all testing strategies tended to decline in
performance rapidly.
The example of the single locus case, overdominance, is central to processes of heterosis and inbreeding depression [52], [53], and has been identified in molecular studies also [54], [55].
Indeed, heterozygote advantage plays an important role in evolutionary
theory, as it confers segregational load on a population, and this type
of load cannot be purged due to balancing selection, potentially
rendering populations susceptible to accumulating a critical mass of
such polymorphisms [56].

It is important to note that the processes underlying stasis and missing
heritability are unlikely to be caused by any single factor. For
example, a compelling argument is that though most traits exhibit
genetic variation, selection acts upon multidimensional trait space in
which there is no genetic variation [59], and this will hold under an additive model of genetic variation.
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Posted by on March 2, 2013 in Genetics, human genetics