The contribution of Neanderthal introgression to modern human traits.

Neanderthals, our closest extinct relatives, lived in western Eurasia from 400,000 years ago until they went extinct around 40,000 years ago. DNA retrieved from ancient specimens revealed that Neanderthals mated with modern human contemporaries. As a consequence, introgressed Neanderthal DNA survives scattered across the human genome such that 1-4% of the genome of present-day people outside Africa are inherited from Neanderthal ancestors. Patterns of Neanderthal introgressed genomic sequences suggest that Neanderthal alleles had distinct fates in the modern human genetic background. Some Neanderthal alleles facilitated human adaptation to new environments such as novel climate conditions, UV exposure levels and pathogens, while others had deleterious consequences. Here, we review the body of work on Neanderthal introgression over the past decade. We describe how evolutionary forces shaped the genomic landscape of Neanderthal introgression and highlight the impact of introgressed alleles on human biology and phenotypic variation.

Evolution of Human-Specific Alleles Protecting Cognitive Function of Grandmothers.

The myelomonocytic receptor CD33 (Siglec-3) inhibits innate immune reactivity by extracellular V-set domain recognition of sialic acid (Sia)-containing "self-associated molecular patterns" (SAMPs). We earlier showed that V-set domain-deficient CD33-variant allele, protective against late-onset Alzheimer's Disease (LOAD), is derived and specific to the hominin lineage. We now report multiple hominin-specific CD33 V-set domain mutations. Due to hominin-specific, fixed loss-of-function mutation in the CMAH gene, humans lack N-glycolylneuraminic acid (Neu5Gc), the preferred Sia-ligand of ancestral CD33. Mutational analysis and molecular dynamics (MD)-simulations indicate that fixed change in amino acid 21 of hominin V-set domain and conformational changes related to His45 corrected for Neu5Gc-loss by switching to N-acetylneuraminic acid (Neu5Ac)-recognition. We show that human-specific pathogens Neisseria gonorrhoeae and Group B Streptococcus selectively bind human CD33 (huCD33) as part of immune-evasive molecular mimicry of host SAMPs and that this binding is significantly impacted by amino acid 21 modification. In addition to LOAD-protective CD33 alleles, humans harbor derived, population-universal, cognition-protective variants at several other loci. Interestingly, 11 of 13 SNPs in these human genes (including CD33) are not shared by genomes of archaic hominins: Neanderthals and Denisovans. We present a plausible evolutionary scenario to compile, correlate, and comprehend existing knowledge about huCD33-evolution and suggest that grandmothering emerged in humans.

An open science study of ageing in companion dogs.

The Dog Aging Project is a long-term longitudinal study of ageing in tens of thousands of companion dogs. The domestic dog is among the most variable mammal species in terms of morphology, behaviour, risk of age-related disease and life expectancy. Given that dogs share the human environment and have a sophisticated healthcare system but are much shorter-lived than people, they offer a unique opportunity to identify the genetic, environmental and lifestyle factors associated with healthy lifespan. To take advantage of this opportunity, the Dog Aging Project will collect extensive survey data, environmental information, electronic veterinary medical records, genome-wide sequence information, clinicopathology and molecular phenotypes derived from blood cells, plasma and faecal samples. Here, we describe the specific goals and design of the Dog Aging Project and discuss the potential for this open-data, community science study to greatly enhance understanding of ageing in a genetically variable, socially relevant species living in a complex environment.

Deep sequencing of 1320 genes reveals the landscape of protein-truncating variants and their contribution to psoriasis in 19,973 Chinese individuals.

Protein-truncating variants (PTVs) have important impacts on phenotype diversity and disease. However, their population genetics characteristics in more globally diverse populations are not well defined. Here, we describe patterns of PTVs in 1320 genes sequenced in 10,539 healthy controls and 9434 patients with psoriasis, all of Han Chinese ancestry. We identify 8720 PTVs, of which 77% are novel, and estimate 88% of all PTVs are deleterious and subject to purifying selection. Furthermore, we show that individuals with psoriasis have a significantly higher burden of PTVs compared to controls (P = 0.02). Finally, we identified 18 PTVs in 14 genes with unusually high levels of population differentiation, consistent with the action of local adaptation. Our study provides insights into patterns and consequences of PTVs.

Implications of localized charge for human influenza A H1N1 hemagglutinin evolution: Insights from deep mutational scans.

Seasonal influenza A viruses of humans evolve rapidly due to strong selection pressures from host immune responses, principally on the hemagglutinin (HA) viral surface protein. Based on mouse transmission experiments, a proposed mechanism for immune evasion consists of increased avidity to host cellular receptors, mediated by electrostatic charge interactions with negatively charged cell surfaces. In support of this, the HA charge of the globally circulating H3N2 has increased over time since its pandemic. However, the same trend was not seen in H1N1 HA sequences. This is counter-intuitive, since immune escape due to increased avidity (due itself to an increase in charge) was determined experimentally. Here, we explore whether patterns of local charge of H1N1 HA can explain this discrepancy and thus further associate electrostatic charge with immune escape and viral evolutionary dynamics. Measures of site-wise functional selection and expected charge computed from deep mutational scan data on an early H1N1 HA yield a striking division of residues into three groups, separated by charge. We then explored evolutionary dynamics of these groups from 1918 to 2008. In particular, one group increases in net charge over time and consists of sites that are evolving the fastest, that are closest to the receptor binding site (RBS), and that are exposed to solvent (i.e., on the surface). By contrast, another group decreases in net charge and consists of sites that are further away from the RBS and evolving slower, but also exposed to solvent. The last group consists of those sites in the HA core, with no change in net charge and that evolve very slowly. Thus, there is a group of residues that follows the same trend as seen for the entire H3N2 HA. It is possible that the H1N1 HA is under other biophysical constraints that result in compensatory decreases in charge elsewhere on the protein. Our results implicate localized charge in HA interactions with host cells, and highlight how deep mutational scan data can inform evolutionary hypotheses.

Identifying and Interpreting Apparent Neanderthal Ancestry in African Individuals.

Admixture has played a prominent role in shaping patterns of human genomic variation, including gene flow with now-extinct hominins like Neanderthals and Denisovans. Here, we describe a novel probabilistic method called IBDmix to identify introgressed hominin sequences, which, unlike existing approaches, does not use a modern reference population. We applied IBDmix to 2,504 individuals from geographically diverse populations to identify and analyze Neanderthal sequences segregating in modern humans. Strikingly, we find that African individuals carry a stronger signal of Neanderthal ancestry than previously thought. We show that this can be explained by genuine Neanderthal ancestry due to migrations back to Africa, predominately from ancestral Europeans, and gene flow into Neanderthals from an early dispersing group of humans out of Africa. Our results refine our understanding of Neanderthal ancestry in African and non-African populations and demonstrate that remnants of Neanderthal genomes survive in every modern human population studied to date.

Evolutionary history and adaptation of a human pygmy population of Flores Island, Indonesia.

Flores Island, Indonesia, was inhabited by the small-bodied hominin species Homo floresiensis, which has an unknown evolutionary relationship to modern humans. This island is also home to an extant human pygmy population. Here we describe genome-scale single-nucleotide polymorphism data and whole-genome sequences from a contemporary human pygmy population living on Flores near the cave where H. floresiensis was found. The genomes of Flores pygmies reveal a complex history of admixture with Denisovans and Neanderthals but no evidence for gene flow with other archaic hominins. Modern individuals bear the signatures of recent positive selection encompassing the FADS (fatty acid desaturase) gene cluster, likely related to diet, and polygenic selection acting on standing variation that contributed to their short-stature phenotype. Thus, multiple independent instances of hominin insular dwarfism occurred on Flores.

Massive variation of short tandem repeats with functional consequences across strains of Arabidopsis thaliana.

Short tandem repeat (STR) mutations may comprise more than half of the mutations in eukaryotic coding DNA, yet STR variation is rarely examined as a contributor to complex traits. We assessed this contribution across a collection of 96 strains of Arabidopsis thaliana, genotyping 2046 STR loci each, using highly parallel STR sequencing with molecular inversion probes. We found that 95% of examined STRs are polymorphic, with a median of six alleles per STR across these strains. STR expansions (large copy number increases) are found in most strains, several of which have evident functional effects. These include three of six intronic STR expansions we found to be associated with intron retention. Coding STRs were depleted of variation relative to noncoding STRs, and we detected a total of 56 coding STRs (11%) showing low variation consistent with the action of purifying selection. In contrast, some STRs show hypervariable patterns consistent with diversifying selection. Finally, we detected 133 novel STR-phenotype associations under stringent criteria, most of which could not be detected with SNPs alone, and validated some with follow-up experiments. Our results support the conclusion that STRs constitute a large, unascertained reservoir of functionally relevant genomic variation.

Outstanding questions in the study of archaic hominin admixture.

The complete sequencing of archaic and modern human genomes has revolutionized the study of human history and evolution. The application of paleogenomics has answered questions that were beyond the scope of archaeology alone-definitively proving admixture between archaic and modern humans. Despite the remarkable progress made in the study of archaic-modern human admixture, many outstanding questions remain. Here, we review some of these questions, which include how frequent archaic-modern human admixture was in history, to what degree drift and selection are responsible for the loss and retention of introgressed sequences in modern human genomes, and how surviving archaic sequences affect human phenotypes.

Evolution of DNAase I Hypersensitive Sites in MHC Regulatory Regions of Primates.

It has been challenging to determine the disease-causing variant(s) for most major histocompatibility complex (MHC)-associated diseases. However, it is becoming increasingly clear that regulatory variation is pervasive and a fundamentally important mechanism governing phenotypic diversity and disease susceptibility. We gathered DNase I data from 136 human cells to characterize the regulatory landscape of the MHC region, including 4867 DNase I hypersensitive sites (DHSs). We identified thousands of regulatory elements that have been gained or lost in the human or chimpanzee genomes since their evolutionary divergence. We compared alignments of the DHS across six primates and found 149 DHSs with convincing evidence of positive and/or purifying selection. Of these DHSs, compared to neutral sequences, 24 evolved rapidly in the human lineage. We identified 15 instances of transcription-factor-binding motif gains, such as USF, MYC, MAX, MAFK, STAT1, PBX3, etc, and observed 16 GWAS (genome-wide association study) SNPs associated with diseases within these 24 DHSs using FIMO (Find Individual Motif Occurrences) and UCSC (University of California, Santa Cruz) ChIP-seq data. Combining eQTL and Hi-C data, our results indicated that there were five SNPs located in human gains motifs affecting the corresponding gene's expression, two of which closely matched DHS target genes. In addition, a significant SNP, rs7756521, at genome-wide significant level likely affects DDR expression and represents a causal genetic variant for HIV-1 control. These results indicated that species-specific motif gains or losses of rapidly evolving DHSs in the primate genomes might play a role during adaptation evolution and provided some new evidence for a potentially causal role for these GWAS SNPs.

Analysis of Human Sequence Data Reveals Two Pulses of Archaic Denisovan Admixture.

Anatomically modern humans interbred with Neanderthals and with a related archaic population known as Denisovans. Genomes of several Neanderthals and one Denisovan have been sequenced, and these reference genomes have been used to detect introgressed genetic material in present-day human genomes. Segments of introgression also can be detected without use of reference genomes, and doing so can be advantageous for finding introgressed segments that are less closely related to the sequenced archaic genomes. We apply a new reference-free method for detecting archaic introgression to 5,639 whole-genome sequences from Eurasia and Oceania. We find Denisovan ancestry in populations from East and South Asia and Papuans. Denisovan ancestry comprises two components with differing similarity to the sequenced Altai Denisovan individual. This indicates that at least two distinct instances of Denisovan admixture into modern humans occurred, involving Denisovan populations that had different levels of relatedness to the sequenced Altai Denisovan. VIDEO ABSTRACT.

Selection plays the hand it was dealt: evidence that human adaptation commonly targets standing genetic variation.

Using a powerful machine learning approach, a recent study of human genomes has revealed widespread footprints of recent positive selection on standing genetic variation.

Impacts of Neanderthal-Introgressed Sequences on the Landscape of Human Gene Expression.

Regulatory variation influencing gene expression is a key contributor to phenotypic diversity, both within and between species. Unfortunately, RNA degrades too rapidly to be recovered from fossil remains, limiting functional genomic insights about our extinct hominin relatives. Many Neanderthal sequences survive in modern humans due to ancient hybridization, providing an opportunity to assess their contributions to transcriptional variation and to test hypotheses about regulatory evolution. We developed a flexible Bayesian statistical approach to quantify allele-specific expression (ASE) in complex RNA-seq datasets. We identified widespread expression differences between Neanderthal and modern human alleles, indicating pervasive cis-regulatory impacts of introgression. Brain regions and testes exhibited significant downregulation of Neanderthal alleles relative to other tissues, consistent with natural selection influencing the tissue-specific regulatory landscape. Our study demonstrates that Neanderthal-inherited sequences are not silent remnants of ancient interbreeding but have measurable impacts on gene expression that contribute to variation in modern human phenotypes.

Tracing the peopling of the world through genomics.

Advances in the sequencing and the analysis of the genomes of both modern and ancient peoples have facilitated a number of breakthroughs in our understanding of human evolutionary history. These include the discovery of interbreeding between anatomically modern humans and extinct hominins; the development of an increasingly detailed description of the complex dispersal of modern humans out of Africa and their population expansion worldwide; and the characterization of many of the genetic adaptions of humans to local environmental conditions. Our interpretation of the evolutionary history and adaptation of humans is being transformed by analyses of these new genomic data.

Human RECQ Helicase Pathogenic Variants, Population Variation and "Missing" Diseases.

Heritable loss of function mutations in the human RECQ helicase genes BLM, WRN, and RECQL4 cause Bloom, Werner, and Rothmund-Thomson syndromes, cancer predispositions with additional developmental or progeroid features. In order to better understand RECQ pathogenic and population variation, we systematically analyzed genetic variation in all five human RECQ helicase genes. A total of 3,741 unique base pair-level variants were identified, across 17,605 potential mutation sites. Direct counting of BLM, RECQL4, and WRN pathogenic variants was used to determine aggregate and disease-specific carrier frequencies. The use of biochemical and model organism data, together with computational prediction, identified over 300 potentially pathogenic population variants in RECQL and RECQL5, the two RECQ helicases that are not yet linked to a heritable deficiency syndrome. Despite the presence of these predicted pathogenic variants in the human population, we identified no individuals homozygous for any biochemically verified or predicted pathogenic RECQL or RECQL5 variant. Nor did we find any individual heterozygous for known pathogenic variants in two or more of the disease-associated RECQ helicase genes BLM, RECQL4, or WRN. Several postulated RECQ helicase deficiency syndromes-RECQL or RECQL5 loss of function, or compound haploinsufficiency for the disease-associated RECQ helicases-may remain missing, as they likely incompatible with life.

Archaic Hominin Admixture Facilitated Adaptation to Out-of-Africa Environments.

As modern humans dispersed from Africa throughout the world, they encountered and interbred with archaic hominins, including Neanderthals and Denisovans [1, 2]. Although genome-scale maps of introgressed sequences have been constructed [3-6], considerable gaps in knowledge remain about the functional, phenotypic, and evolutionary significance of archaic hominin DNA that persists in present-day individuals. Here, we describe a comprehensive set of analyses that identified 126 high-frequency archaic haplotypes as putative targets of adaptive introgression in geographically diverse populations. These loci are enriched for immune-related genes (such as OAS1/2/3, TLR1/6/10, and TNFAIP3) and also encompass genes (including OCA2 and BNC2) that influence skin pigmentation phenotypes. Furthermore, we leveraged existing and novel large-scale gene expression datasets to show many positively selected archaic haplotypes act as expression quantitative trait loci (eQTLs), suggesting that modulation of transcript abundance was a common mechanism facilitating adaptive introgression. Our results demonstrate that hybridization between modern and archaic hominins provided an important reservoir of advantageous alleles that enabled adaptation to out-of-Africa environments.

Detecting Sources of Transcriptional Heterogeneity in Large-Scale RNA-Seq Data Sets.

Gene expression levels are dynamic molecular phenotypes that respond to biological, environmental, and technical perturbations. Here we use a novel replicate-classifier approach for discovering transcriptional signatures and apply it to the Genotype-Tissue Expression data set. We identified many factors contributing to expression heterogeneity, such as collection center and ischemia time, and our approach of scoring replicate classifiers allows us to statistically stratify these factors by effect strength. Strikingly, from transcriptional expression in blood alone we detect markers that help predict heart disease and stroke in some patients. Our results illustrate the challenges and opportunities of interpreting patterns of transcriptional variation in large-scale data sets.