FADS1 and the Timing of Human Adaptation to Agriculture

Recurrent evolution and selection shape structural diversity at the amylase locus

The adoption of agriculture triggered a rapid shift towards starch-rich diets in human populations1. Amylase genes facilitate starch digestion, and increased amylase copy number has been observed in some modern human populations with high-starch intake2, although evidence of recent selection is lacking3,4. Here, using 94 long-read haplotype-resolved assemblies and short-read data from approximately 5,600 contemporary and ancient humans, we resolve the diversity and evolutionary history of structural variation at the amylase locus. We find that amylase genes have higher copy numbers in agricultural populations than in fishing, hunting and pastoral populations. We identify 28 distinct amylase structural architectures and demonstrate that nearly identical structures have arisen recurrently on different haplotype backgrounds throughout recent human history. AMY1 and AMY2A genes each underwent multiple duplication/deletion events with mutation rates up to more than 10,000-fold the single-nucleotide polymorphism mutation rate, whereas AMY2B gene duplications share a single origin. Using a pangenome-based approach, we infer structural haplotypes across thousands of humans identifying extensively duplicated haplotypes at higher frequency in modern agricultural populations. Leveraging 533 ancient human genomes, we find that duplication-containing haplotypes (with more gene copies than the ancestral haplotype) have rapidly increased in frequency over the past 12,000 years in West Eurasians, suggestive of positive selection. Together, our study highlights the potential effects of the agricultural revolution on human genomes and the importance of structural variation in human adaptation.

Deep estimation of the intensity and timing of natural selection from ancient genomes

Leveraging past allele frequencies has proven to be key for identifying the impact of natural selection across time. However, this approach suffers from imprecise estimations of the intensity (s) and timing (T) of selection, particularly when ancient samples are scarce in specific epochs. Here, we aimed to bypass the computation of allele frequencies across arbitrarily defined past epochs and refine the estimations of selection parameters by implementing convolutional neural networks (CNNs) algorithms that directly use ancient genotypes sampled across time. Using computer simulations, we first show that genotype-based CNNs consistently outperform an approximate Bayesian computation (ABC) approach based on past allele frequency trajectories, regardless of the selection model assumed and the number of available ancient genotypes. When applying this method to empirical data from modern and ancient Europeans, we replicated the reported increased number of selection events in post-Neolithic Europe, independently of the continental subregion studied. Furthermore, we substantially refined the ABC-based estimations of s and T for a set of positively and negatively selected variants, including iconic cases of positive selection and experimentally validated disease-risk variants. Our CNN predictions support a history of recent positive and negative selection targeting variants associated with host defence against pathogens, aligning with previous work that highlights the significant impact of infectious diseases, such as tuberculosis, in Europe. These findings collectively demonstrate that detecting the footprints of natural selection on ancient genomes is crucial for unravelling the history of severe human diseases.

Selection scan in Native Americans of Mexico identifies FADS2 rs174616: Evidence of gene-diet interactions affecting lipid levels and Delta-6-desaturase activity

Searching for positive selection signals across genomes has identified functional genetic variants responding to environmental change. In Native Americans of Mexico, we used the fixation index (Fst) and population branch statistic (PBS) to identify SNPs suggesting positive selection. The 103 most differentiated SNPs were tested for associations with metabolic traits, the most significant association was FADS2/rs174616 with body mass index (BMI). This variant lies within a linkage disequilibrium (LD) block independent of previously reported FADS selection signals and has not been clearly associated with metabolic phenotypes. We tested this variant in two independent cohorts with cardiometabolic data. In the Genetics of Atherosclerotic Disease (GEA) cohort, the derived allele (T) was associated with increased BMI, lower LDL-C levels and a decreased risk of subclinical atherosclerosis in women. Significant gene-diet interactions affected lipid, apolipoprotein and adiponectin levels with differences according to sex, involving mainly total and complex dietary carbohydrate%. In the Genotype-related Effects of PUFA trial, the derived allele was associated with lower Δ-6 desaturase activity and erythrocyte membrane dihomo-gamma-linolenic acid (DGLA) levels, and with increased Δ-5 desaturase activity and eicosapentaenoic acid levels. This variant interacted with dietary carbohydrate% affecting Δ-6 desaturase activity. Notably, the relationship of DGLA and other erythrocyte membrane LC-PUFA indices with HOMA-IR differed according to rs174616 genotype, which has implications regarding how these indices should be interpreted. In conclusion, this observational study identified rs174616 as a signal suggesting selection in an independent linkage disequilibrium block, was associated with cardiometabolic and erythrocyte measurements of LC-PUFA in two independent Mexican cohorts and showed significant gene-diet interactions.

We Are What, When, And How We Eat: The Evolutionary Impact of Dietary Shifts on Physical and Cognitive Development, Health, and Disease

"We are what, when, and how we eat": the evolution of human dietary habits mirrors the evolution of humans themselves. Key developments in human history, such as the advent of stone tool technology, the shift to a meat-based diet, control of fire, advancements in cooking and fermentation techniques, and the domestication of plants and animals, have significantly influenced human anatomical, physiological, social, cognitive, and behavioral changes. Advancements in scientific methods, such as the analysis of microfossils like starch granules, plant-derived phytoliths, and coprolites, have yielded unprecedented insights into past diets. Nonetheless, the isolation of ancient food matrices remains analytically challenging. Future technological breakthroughs and a more comprehensive integration of paleogenomics, paleoproteomics, paleoglycomics, and paleometabolomics will enable a more nuanced understanding of early human ancestors' diets, which holds the potential to guide contemporary dietary recommendations and tackle modern health challenges, with far-reaching implications for human well-being, and ecological impact on the planet.

Improving data archiving practices in ancient genomics

Ancient DNA is producing a rich record of past genetic diversity in humans and other species. However, unless the primary data is appropriately archived, its long-term value will not be fully realised. I surveyed publicly archived data from 42 recent ancient genomics studies. Half of the studies archived incomplete datasets, preventing accurate replication and representing a loss of data of potential future use. No studies met all criteria that could be considered best practice. Based on these results, I make six recommendations for data producers: (1) archive all sequencing reads, not just those that aligned to a reference genome, (2) archive read alignments too, but as secondary analysis files, (3) provide correct experiment metadata on samples, libraries and sequencing runs, (4) provide informative sample metadata, (5) archive data from low-coverage and negative experiments, and (6) document archiving choices in papers, and peer review these. Given the reliance on destructive sampling of finite material, ancient genomics studies have a particularly strong responsibility to ensure the longevity and reusability of generated data.

Effect of FADS1 SNPs rs174546, rs174547 and rs174550 on blood fatty acid profiles and plasma free oxylipins

Introduction

Previous studies have indicated that activity of fatty acid desaturase 1 (FADS1), is involved in cardiometabolic risk. Recent experimental data have shown that FADS1 knockdown can promote lipid accumulation and lipid droplet formation in liver cells. In this study, we aimed to characterize whether different FADS1 genotypes affect liver fat content, essential fatty acid content and free oxylipin mediators in the blood.

Methods

We analyzed the impact of FADS1 single-nucleotide polymorphisms (SNPs) rs174546, rs174547, and rs174550 on blood fatty acids and free oxylipins in a cohort of 85 patients from an academic metabolic medicine outpatient center. Patients were grouped based on their genotype into the homozygous major (derived) allele group, the heterozygous allele group, and the homozygous minor (ancestral) allele group. Omega-3 polyunsaturated fatty acids (n-3 PUFA) and omega-6 polyunsaturated fatty acids (n-6 PUFA) in the blood cell and plasma samples were analyzed by gas chromatography. Free Oxylipins in plasma samples were analyzed using HPLC-MS/MS. Liver fat content and fibrosis were evaluated using Fibroscan technology.

Results

Patients with the homozygous ancestral (minor) FADS1 genotype exhibited significantly lower blood levels of the n-6 PUFA arachidonic acid (AA), but no significant differences in the n-3 PUFAs eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). There were no significant differences in liver fat content or arachidonic acid-derived lipid mediators, such as thromboxane B2 (TXB2), although there was a trend toward lower levels in the homozygous ancestral genotype group.

Discussion

Our findings suggest that FADS1 genotypes influence the blood levels of n-6 PUFAs, while not significantly affecting the n-3 PUFAs EPA and DHA. The lack of significant differences in liver fat content and arachidonic acid-derived lipid mediators suggests that the genotype-related variations in fatty acid levels may not directly translate to differences in liver fat or inflammatory lipid mediators in this cohort. However, the trend towards lower levels of certain lipid mediators in the homozygous ancestral genotype group warrants further investigation to elucidate the underlying mechanisms of different FADS1 genotypes and potential implications for cardiometabolic risk.

Investigating food production-associated DNA methylation changes in paleogenomes: Lack of consistent signals beyond technical noise

The Neolithic transition introduced major diet and lifestyle changes to human populations across continents. Beyond well-documented bioarcheological and genetic effects, whether these changes also had molecular-level epigenetic repercussions in past human populations has been an open question. In fact, methylation signatures can be inferred from UDG-treated ancient DNA through postmortem damage patterns, but with low signal-to-noise ratios; it is thus unclear whether published paleogenomes would provide the necessary resolution to discover systematic effects of lifestyle and diet shifts. To address this we compiled UDG-treated shotgun genomes of 13 pre-Neolithic hunter-gatherers (HGs) and 21 Neolithic farmers (NFs) individuals from West and North Eurasia, published by six different laboratories and with coverage c.1×-58× (median = 9×). We used epiPALEOMIX and a Monte Carlo normalization scheme to estimate methylation levels per genome. Our paleomethylome dataset showed expected genome-wide methylation patterns such as CpG island hypomethylation. However, analyzing the data using various approaches did not yield any systematic signals for subsistence type, genetic sex, or tissue effects. Comparing the HG-NF methylation differences in our dataset with methylation differences between hunter-gatherers versus farmers in modern-day Central Africa also did not yield consistent results. Meanwhile, paleomethylome profiles did cluster strongly by their laboratories of origin. Using larger data volumes, minimizing technical noise and/or using alternative protocols may be necessary for capturing subtle environment-related biological signals from paleomethylomes.

Global diversity, recurrent evolution, and recent selection on amylase structural haplotypes in humans

The adoption of agriculture, first documented ~12,000 years ago in the Fertile Crescent, triggered a rapid shift toward starch-rich diets in human populations. Amylase genes facilitate starch digestion and increased salivary amylase copy number has been observed in some modern human populations with high starch intake, though evidence of recent selection is lacking. Here, using 52 long-read diploid assemblies and short read data from ~5,600 contemporary and ancient humans, we resolve the diversity, evolutionary history, and selective impact of structural variation at the amylase locus. We find that amylase genes have higher copy numbers in populations with agricultural subsistence compared to fishing, hunting, and pastoral groups. We identify 28 distinct amylase structural architectures and demonstrate that nearly identical structures have arisen recurrently on different haplotype backgrounds throughout recent human history. AMY1 and AMY2A genes each exhibit multiple duplications/deletions with mutation rates >10,000-fold the SNP mutation rate, whereas AMY2B gene duplications share a single origin. Using a pangenome graph-based approach to infer structural haplotypes across thousands of humans, we identify extensively duplicated haplotypes present at higher frequencies in modern day populations with traditionally agricultural diets. Leveraging 533 ancient human genomes we find that duplication-containing haplotypes (i.e. haplotypes with more amylase gene copies than the ancestral haplotype) have increased in frequency more than seven-fold over the last 12,000 years providing evidence for recent selection in West Eurasians. Together, our study highlights the potential impacts of the agricultural revolution on human genomes and the importance of long-read sequencing in identifying signatures of selection at structurally complex loci.

High Frequency of Ancestral Haplotype A of Fatty Acid Desaturase Genes in the Yakut Population

Aims: The purpose of this study was to study the correlation of the body weight of Yakuts with the variability of polymorphisms rs174537, rs174546 and rs3834458 of the FADS1 - FADS2 region to identify the connection of certain genotypes with obesity. Materials and Methods: For genotyping, classical methods of PCR-RFLP analysis were used. A sample of 446 DNA samples from Yakut volunteers without chronic diseases (143 women and 303 men) was studied. Results: The predominance of the ancestral alleles of SNPs rs174537, rs174546 and rs3834458 was established in all of our studied groups. Analysis of the odds ratio of allele and genotype frequencies in patients with normal BMI, high BMI and obesity did not show statistically significant values. We did not find an association between rs174537, rs174546 and rs3834458 with obesity, but we did not take into account the diet of the subjects, which may have had a stronger effect on BMI. Analysis of pairwise linkage disequilibrium and assessment of haplotypes for 3 SNPs in the FADS1 and FADS2 genes showed strong linkage of all three SNPs to each other (r2 = 0.93-0.96). Conclusions: According to the result of genotyping of SNP rs174537, the frequency of haplotype A in the Yakut population was 0.76 and, in comparison with other world data, is quite high. Which in turn is associated with lower conversion of short-chain polyunsaturated fatty acid to long-chain polyunsaturated fatty acid. Accordingly, a shift in nutrition towards more plant foods can negatively impact the health of the Yakuts. At the moment, the exact dosage of polyunsaturated fatty acids (PUFAs) for humans has not yet been established, but judging by the fact that all recommendations are mainly made on the basis of European populations, in connection with the results of the study, the Yakuts have a particularly high need for PUFAs.

Paleolithic Gene Duplications Primed Adaptive Evolution of Human Amylase Locus Upon Agriculture

Starch digestion is a cornerstone of human nutrition. The amylase genes code for the starch-digesting amylase enzyme. Previous studies suggested that the salivary amylase (AMY1) gene copy number increased in response to agricultural diets. However, the lack of nucleotide resolution of the amylase locus hindered detailed evolutionary analyses. Here, we have resolved this locus at nucleotide resolution in 98 present-day humans and identified 30 distinct haplotypes, revealing that the coding sequences of all amylase gene copies are evolving under negative selection. The phylogenetic reconstruction suggested that haplotypes with three AMY1 gene copies, prevalent across all continents and constituting about 70% of observed haplotypes, originated before the out-of-Africa migrations of ancestral modern humans. Using thousands of unique 25 base pair sequences across the amylase locus, we showed that additional AMY1 gene copies existed in the genomes of four archaic hominin genomes, indicating that the initial duplication of this locus may have occurred as far back 800,000 years ago. We similarly analyzed 73 ancient human genomes dating from 300 - 45,000 years ago and found that the AMY1 copy number variation observed today existed long before the advent of agriculture (~10,000 years ago), predisposing this locus to adaptive increase in the frequency of higher amylase copy number with the spread of agriculture. Mechanistically, the common three-copy haplotypes seeded non-allelic homologous recombination events that appear to be occurring at one of the fastest rates seen for tandem repeats in the human genome. Our study provides a comprehensive population-level understanding of the genomic structure of the amylase locus, identifying the mechanisms and evolutionary history underlying its duplication and copy number variability in relation to the onset of agriculture.

Comparative transcriptome and methylome of polar bears, giant and red pandas reveal diet-driven adaptive evolution

Epigenetic regulation plays an important role in the evolution of species adaptations, yet little information is available on the epigenetic mechanisms underlying the adaptive evolution of bamboo-eating in both giant pandas (Ailuropoda melanoleuca) and red pandas (Ailurus fulgens). To investigate the potential contribution of epigenetic to the adaptive evolution of bamboo-eating in giant and red pandas, we performed hepatic comparative transcriptome and methylome analyses between bamboo-eating pandas and carnivorous polar bears (Ursus maritimus). We found that genes involved in carbohydrate, lipid, amino acid, and protein metabolism showed significant differences in methylation and expression levels between the two panda species and polar bears. Clustering analysis of gene expression revealed that giant pandas did not form a sister group with the more closely related polar bears, suggesting that the expression pattern of genes in livers of giant pandas and red pandas have evolved convergently driven by their similar diets. Compared to polar bears, some key genes involved in carbohydrate metabolism and biological oxidation and cholesterol synthesis showed hypomethylation and higher expression in giant and red pandas, while genes involved in fat digestion and absorption, fatty acid metabolism, lysine degradation, resistance to lipid peroxidation and detoxification showed hypermethylation and low expression. Our study elucidates the special nutrient utilization mechanism of giant pandas and red pandas and provides some insights into the molecular mechanism of their adaptive evolution of bamboo feeding. This has important implications for the breeding and conservation of giant pandas and red pandas.

Predicting Functional Consequences of Recent Natural Selection in Britain

Ancient DNA can directly reveal the contribution of natural selection to human genomic variation. However, while the analysis of ancient DNA has been successful at identifying genomic signals of selection, inferring the phenotypic consequences of that selection has been more difficult. Most trait-associated variants are noncoding, so we expect that a large proportion of the phenotypic effects of selection will also act through noncoding variation. Since we cannot measure gene expression directly in ancient individuals, we used an approach (Joint-Tissue Imputation [JTI]) developed to predict gene expression from genotype data. We tested for changes in the predicted expression of 17,384 protein coding genes over a time transect of 4,500 years using 91 present-day and 616 ancient individuals from Britain. We identified 28 genes at seven genomic loci with significant (false discovery rate [FDR] < 0.05) changes in predicted expression levels in this time period. We compared the results from our transcriptome-wide scan to a genome-wide scan based on estimating per-single nucleotide polymorphism (SNP) selection coefficients from time series data. At five previously identified loci, our approach allowed us to highlight small numbers of genes with evidence for significant shifts in expression from peaks that in some cases span tens of genes. At two novel loci (SLC44A5 and NUP85), we identify selection on gene expression not captured by scans based on genomic signatures of selection. Finally, we show how classical selection statistics (iHS and SDS) can be combined with JTI models to incorporate functional information into scans that use present-day data alone. These results demonstrate the potential of this type of information to explore both the causes and consequences of natural selection.

Human adaptations to diet: Biological and cultural coevolution

Modern humans evolved in Africa some 200,000 years ago, and since then, human populations have expanded and diversified to occupy a broad range of habitats and use different subsistence modes. This has resulted in different adaptations, such as differential responses to diseases and different abilities to digest or tolerate certain foods. The shift from a subsistence strategy based on hunting and gathering during the Palaeolithic to a lifestyle based on the consumption of domesticated animals and plants in the Neolithic can be considered one of the most important dietary transitions of Homo sapiens. In this text, we review four examples of gene-culture coevolution: (i) the persistence of the enzyme lactase after weaning, which allows the digestion of milk in adulthood, related to the emergence of dairy farming during the Neolithic; (ii) the population differences in alcohol susceptibility, in particular the ethanol intolerance of Asian populations due to the increased accumulation of the toxic acetaldehyde, related to the spread of rice domestication; (iii) the maintenance of gluten intolerance (celiac disease) with the subsequent reduced fitness of its sufferers, related to the emergence of agriculture and (iv) the considerable variation in the biosynthetic pathway of long-chain polyunsaturated fatty acids in native populations with extreme diets.

Genetic history of Cambridgeshire before and after the Black Death

The extent of the devastation of the Black Death pandemic (1346-1353) on European populations is known from documentary sources and its bacterial source illuminated by studies of ancient pathogen DNA. What has remained less understood is the effect of the pandemic on human mobility and genetic diversity at the local scale. Here, we report 275 ancient genomes, including 109 with coverage >0.1×, from later medieval and postmedieval Cambridgeshire of individuals buried before and after the Black Death. Consistent with the function of the institutions, we found a lack of close relatives among the friars and the inmates of the hospital in contrast to their abundance in general urban and rural parish communities. While we detect long-term shifts in local genetic ancestry in Cambridgeshire, we find no evidence of major changes in genetic ancestry nor higher differentiation of immune loci between cohorts living before and after the Black Death.

Unveiling recent and ongoing adaptive selection in human populations

Genome-wide scans for signals of selection have become a routine part of the analysis of population genomic variation datasets and have resulted in compelling evidence of selection during recent human evolution. This Essay spotlights methodological innovations that have enabled the detection of selection over very recent timescales, even in contemporary human populations. By harnessing large-scale genomic and phenotypic datasets, these new methods use different strategies to uncover connections between genotype, phenotype, and fitness. This Essay outlines the rationale and key findings of each strategy, discusses challenges in interpretation, and describes opportunities to improve detection and understanding of ongoing selection in human populations.

The selection landscape and genetic legacy of ancient Eurasians

The Holocene (beginning around 12,000 years ago) encompassed some of the most significant changes in human evolution, with far-reaching consequences for the dietary, physical and mental health of present-day populations. Using a dataset of more than 1,600 imputed ancient genomes1, we modelled the selection landscape during the transition from hunting and gathering, to farming and pastoralism across West Eurasia. We identify key selection signals related to metabolism, including that selection at the FADS cluster began earlier than previously reported and that selection near the LCT locus predates the emergence of the lactase persistence allele by thousands of years. We also find strong selection in the HLA region, possibly due to increased exposure to pathogens during the Bronze Age. Using ancient individuals to infer local ancestry tracts in over 400,000 samples from the UK Biobank, we identify widespread differences in the distribution of Mesolithic, Neolithic and Bronze Age ancestries across Eurasia. By calculating ancestry-specific polygenic risk scores, we show that height differences between Northern and Southern Europe are associated with differential Steppe ancestry, rather than selection, and that risk alleles for mood-related phenotypes are enriched for Neolithic farmer ancestry, whereas risk alleles for diabetes and Alzheimer's disease are enriched for Western hunter-gatherer ancestry. Our results indicate that ancient selection and migration were large contributors to the distribution of phenotypic diversity in present-day Europeans.

Exploring the genetic diversity of the Japanese population: Insights from a large-scale whole genome sequencing analysis

The Japanese archipelago is a terminal location for human migration, and the contemporary Japanese people represent a unique population whose genomic diversity has been shaped by multiple migrations from Eurasia. We analyzed the genomic characteristics that define the genetic makeup of the modern Japanese population from a population genetics perspective from the genomic data of 9,287 samples obtained by high-coverage whole-genome sequencing (WGS) by the National Center Biobank Network. The dataset comprised populations from the Ryukyu Islands and other parts of the Japanese archipelago (Hondo). The Hondo population underwent two episodes of population decline during the Jomon period, corresponding to the Late Neolithic, and the Edo period, corresponding to the Early Modern era, while the Ryukyu population experienced a population decline during the shell midden period of the Late Neolithic in this region. Haplotype analysis suggested increased allele frequencies for genes related to alcohol and fatty acid metabolism, which were reported as loci that had experienced positive natural selection. Two genes related to alcohol metabolism were found to be 12,500 years out of phase with the time when they began to increase in the allele frequency; this finding indicates that the genomic diversity of Japanese people has been shaped by events closely related to agriculture and food production.

Domain-adaptive neural networks improve supervised machine learning based on simulated population genetic data

Investigators have recently introduced powerful methods for population genetic inference that rely on supervised machine learning from simulated data. Despite their performance advantages, these methods can fail when the simulated training data does not adequately resemble data from the real world. Here, we show that this "simulation mis-specification" problem can be framed as a "domain adaptation" problem, where a model learned from one data distribution is applied to a dataset drawn from a different distribution. By applying an established domain-adaptation technique based on a gradient reversal layer (GRL), originally introduced for image classification, we show that the effects of simulation mis-specification can be substantially mitigated. We focus our analysis on two state-of-the-art deep-learning population genetic methods-SIA, which infers positive selection from features of the ancestral recombination graph (ARG), and ReLERNN, which infers recombination rates from genotype matrices. In the case of SIA, the domain adaptive framework also compensates for ARG inference error. Using the domain-adaptive SIA (dadaSIA) model, we estimate improved selection coefficients at selected loci in the 1000 Genomes CEU population. We anticipate that domain adaptation will prove to be widely applicable in the growing use of supervised machine learning in population genetics.

Investigating Associations of Omega-3 Fatty Acids, Lung Function Decline, and Airway Obstruction

Rationale: Inflammation contributes to lung function decline and the development of chronic obstructive pulmonary disease. Omega-3 fatty acids have antiinflammatory properties and may benefit lung health. Objectives: To investigate associations of omega-3 fatty acids with lung function decline and incident airway obstruction in a diverse sample of adults from general-population cohorts. Methods: Complementary study designs: 1) longitudinal study of plasma phospholipid omega-3 fatty acids and repeated FEV1 and FVC measures in the NHLBI Pooled Cohorts Study and 2) two-sample Mendelian randomization (MR) study of genetically predicted omega-3 fatty acids and lung function parameters. Measurements and Main Results: The longitudinal study found that higher omega-3 fatty acid levels were associated with attenuated lung function decline in 15,063 participants, with the largest effect sizes for the most metabolically downstream omega-3 fatty acid, docosahexaenoic acid (DHA). An increase in DHA of 1% of total fatty acids was associated with attenuations of 1.4 ml/yr for FEV1 (95% confidence interval [CI], 1.1-1.8) and 2.0 ml/yr for FVC (95% CI, 1.6-2.4) and a 7% lower incidence of spirometry-defined airway obstruction (95% CI, 0.89-0.97). DHA associations persisted across sexes and smoking histories and in Black, White, and Hispanic participants, with associations of the largest magnitude in former smokers and Hispanic participants. The MR study showed similar trends toward positive associations of genetically predicted downstream omega-3 fatty acids with FEV1 and FVC. Conclusions: The longitudinal and MR studies provide evidence supporting beneficial effects of higher levels of downstream omega-3 fatty acids, especially DHA, on lung health.

Natural Selection Signatures in the Hondo and Ryukyu Japanese Subpopulations

Natural selection signatures across Japanese subpopulations are under-explored. Here we conducted genome-wide selection scans with 622,926 single nucleotide polymorphisms for 20,366 Japanese individuals, who were recruited from the main-islands of Japanese Archipelago (Hondo) and the Ryukyu Archipelago (Ryukyu), representing two major Japanese subpopulations. The integrated haplotype score (iHS) analysis identified several signals in one or both subpopulations. We found a novel candidate locus at IKZF2, especially in Ryukyu. Significant signals were observed in the major histocompatibility complex region in both subpopulations. The lead variants differed and demonstrated substantial allele frequency differences between Hondo and Ryukyu. The lead variant in Hondo tags HLA-A*33:03-C*14:03-B*44:03-DRB1*13:02-DQB1*06:04-DPB1*04:01, a haplotype specific to Japanese and Korean. While in Ryukyu, the lead variant tags DRB1*15:01-DQB1*06:02, which had been recognized as a genetic risk factor for narcolepsy. In contrast, it is reported to confer protective effects against type 1 diabetes and human T lymphotropic virus type 1-associated myelopathy/tropical spastic paraparesis. The FastSMC analysis identified 8 loci potentially affected by selection within the past 20-150 generations, including 2 novel candidate loci. The analysis also showed differences in selection patterns of ALDH2 between Hondo and Ryukyu, a gene recognized to be specifically targeted by selection in East Asian. In summary, our study provided insights into the selection signatures within the Japanese and nominated potential sources of selection pressure.

High-coverage genome of the Tyrolean Iceman reveals unusually high Anatolian farmer ancestry

The Tyrolean Iceman is known as one of the oldest human glacier mummies, directly dated to 3350-3120 calibrated BCE. A previously published low-coverage genome provided novel insights into European prehistory, despite high present-day DNA contamination. Here, we generate a high-coverage genome with low contamination (15.3×) to gain further insights into the genetic history and phenotype of this individual. Contrary to previous studies, we found no detectable Steppe-related ancestry in the Iceman. Instead, he retained the highest Anatolian-farmer-related ancestry among contemporaneous European populations, indicating a rather isolated Alpine population with limited gene flow from hunter-gatherer-ancestry-related populations. Phenotypic analysis revealed that the Iceman likely had darker skin than present-day Europeans and carried risk alleles associated with male-pattern baldness, type 2 diabetes, and obesity-related metabolic syndrome. These results corroborate phenotypic observations of the preserved mummified body, such as high pigmentation of his skin and the absence of hair on his head.

Domain-adaptive neural networks improve supervised machine learning based on simulated population genetic data

Investigators have recently introduced powerful methods for population genetic inference that rely on supervised machine learning from simulated data. Despite their performance advantages, these methods can fail when the simulated training data does not adequately resemble data from the real world. Here, we show that this "simulation mis-specification" problem can be framed as a "domain adaptation" problem, where a model learned from one data distribution is applied to a dataset drawn from a different distribution. By applying an established domain-adaptation technique based on a gradient reversal layer (GRL), originally introduced for image classification, we show that the effects of simulation mis-specification can be substantially mitigated. We focus our analysis on two state-of-the-art deep-learning population genetic methods-SIA, which infers positive selection from features of the ancestral recombination graph (ARG), and ReLERNN, which infers recombination rates from genotype matrices. In the case of SIA, the domain adaptive framework also compensates for ARG inference error. Using the domain-adaptive SIA (dadaSIA) model, we estimate improved selection coefficients at selected loci in the 1000 Genomes CEU population. We anticipate that domain adaptation will prove to be widely applicable in the growing use of supervised machine learning in population genetics.

Comparative study of the digestion and metabolism related genes' expression changes during the postnatal food change in different dietary mammals

The changes in the expression of genes related to digestion and metabolism may be various in different dietary mammals from juvenile to adult, especially, the giant panda (Ailuropoda melanoleuca) and red panda (Ailurus fulgens), which were once carnivores but have shifted to being specialized bamboo eaters, are unique features of their changes are more unclear. To elucidate the changing patterns of gene expression related to digestion and metabolism from juvenile to adult in different dietary mammals, we performed transcriptome analysis of the liver or pancreas in giant and red pandas, herbivorous rabbits (Oryctolagus cuniculus) and macaques (Macaca mulatta), carnivorous ferrets (Mustela putorius furo), and omnivorous mice (Mus musculus) from juvenile to adult. During the transition from juvenile to adulthood, giant and red pandas, as well as rabbits and macaques, show significant upregulation of key genes for carbohydrate metabolism, such as starch hydrolysis and sucrose metabolism, and unsaturated fatty acid metabolism, such as linoleic acid, while there is no significant difference in the expression of key genes for fatty acid β-oxidation. A large number of amino acid metabolism related genes were upregulated in adult rabbits and macaques compared to juveniles. While adult giant and red pandas mainly showed upregulation of key genes for arginine synthesis and downregulation of key genes for arginine and lysine degradation. In adult stages, mouse had significantly higher expression patterns in key genes for starch hydrolysis and sucrose metabolism, as well as lipid and protein metabolism. In contrast to general expectations, genes related to lipid, amino acid and protein metabolism were significantly higher expressed in adult group of ferrets, which may be related to their high metabolic levels. Our study elucidates the pattern of changes in the expression of genes related to digestion and metabolism from juvenile to adult in different dietary mammals, with giant and red pandas showing adaptations associated with specific nutritional limitations of bamboo.

GWAS-identified bipolar disorder risk allele in the FADS1/2 gene region links mood episodes and unsaturated fatty acid metabolism in mutant mice

Large-scale genome-wide association studies (GWASs) on bipolar disorder (BD) have implicated the involvement of the fatty acid desaturase (FADS) locus. These enzymes (FADS1 and FADS2) are involved in the metabolism of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), which are thought to potentially benefit patients with mood disorders. To model reductions in the activity of FADS1/2 affected by the susceptibility alleles, we generated mutant mice heterozygously lacking both Fads1/2 genes. We measured wheel-running activity over six months and observed bipolar swings in activity, including hyperactivity and hypoactivity. The hyperactivity episodes, in which activity was far above the norm, usually lasted half a day; mice manifested significantly shorter immobility times on the behavioral despair test performed during these episodes. The hypoactivity episodes, which lasted for several weeks, were accompanied by abnormal circadian rhythms and a marked decrease in wheel running, a spontaneous behavior associated with motivation and reward systems. We comprehensively examined lipid composition in the brain and found that levels of certain lipids were significantly altered between wild-type and the heterozygous mutant mice, but no changes were consistent with both sexes and either DHA or EPA was not altered. However, supplementation with DHA or a mixture of DHA and EPA prevented these episodic behavioral changes. Here we propose that heterozygous Fads1/2 knockout mice are a model of BD with robust constitutive, face, and predictive validity, as administration of the mood stabilizer lithium was also effective. This GWAS-based model helps to clarify how lipids and their metabolisms are involved in the pathogenesis and treatment of BD.

The role of Beringia in human adaptation to Arctic conditions based on results of genomic studies of modern and ancient populations

The results of studies in Quaternary geology, archeology, paleoanthropology and human genetics demonstrate that the ancestors of Native Americans arrived in mid-latitude North America mainly along the Pacific Northwest Coast, but had previously inhabited the Arctic and during the last glacial maximum were in a refugium in Beringia, a land bridge connecting Eurasia and North America. The gene pool of Native Americans is represented by unique haplogroups of mitochondrial DNA and the Y chromosome, the evolutionary age of which ranges from 13 to 22 thousand years. The results of a paleogenomic analysis also show that during the last glacial maximum Beringia was populated by human groups that had arisen as a result of interaction between the most ancient Upper Paleolithic populations of Northern Eurasia and newcomer groups from East Asia. Approximately 20 thousand years ago the Beringian populations began to form, and the duration of their existence in relative isolation is estimated at about 5 thousand years. Thus, the adaptation of the Beringians to the Arctic conditions could have taken several millennia. The adaptation of Amerindian ancestors to high latitudes and cold climates is supported by genomic data showing that adaptive genetic variants in Native Americans are associated with various metabolic pathways: melanin production processes in the skin, hair and eyes, the functioning of the cardiovascular system, energy metabolism and immune response characteristics. Meanwhile, the analysis of the existing hypotheses about the selection of some genetic variants in the Beringian ancestors of the Amerindians in connection with adaptation to the Arctic conditions (for example, in the FADS, ACTN3, EDAR genes) shows the ambiguity of the testing results, which may be due to the loss of some traces of the "Beringian" adaptation in the gene pools of modern Native Americans. The most optimal strategy for further research seems to be the search for adaptive variant.

Food System Transformation and Gut Microbiota Transition: Evidence on Advancing Obesity, Cardiovascular Diseases, and Cancers-A Narrative Review

Food, a vital component of our daily life, is fundamental to our health and well-being, and the knowledge and practices relating to food have been passed down from countless generations of ancestors. Systems may be used to describe this extremely extensive and varied body of agricultural and gastronomic knowledge that has been gathered via evolutionary processes. The gut microbiota also underwent changes as the food system did, and these alterations had a variety of effects on human health. In recent decades, the gut microbiome has gained attention due to its health benefits as well as its pathological effects on human health. Many studies have shown that a person's gut microbiota partially determines the nutritional value of food and that diet, in turn, shapes both the microbiota and the microbiome. The current narrative review aims to explain how changes in the food system over time affect the makeup and evolution of the gut microbiota, advancing obesity, cardiovascular disease (CVD), and cancer. After a brief discussion of the food system's variety and the gut microbiota's functions, we concentrate on the relationship between the evolution of food system transformation and gut microbiota system transition linked to the increase of non-communicable diseases (NCDs). Finally, we also describe sustainable food system transformation strategies to ensure healthy microbiota composition recovery and maintain the host gut barrier and immune functions to reverse advancing NCDs.

A gene-level test for directional selection on gene expression

Most variants identified in human genome-wide association studies and scans for selection are noncoding. Interpretation of their effects and the way in which they contribute to phenotypic variation and adaptation in human populations is therefore limited by our understanding of gene regulation and the difficulty of confidently linking noncoding variants to genes. To overcome this, we developed a gene-wise test for population-specific selection based on combinations of regulatory variants. Specifically, we use the QX statistic to test for polygenic selection on cis-regulatory variants based on whether the variance across populations in the predicted expression of a particular gene is higher than expected under neutrality. We then applied this approach to human data, testing for selection on 17,388 protein-coding genes in 26 populations from the Thousand Genomes Project. We identified 45 genes with significant evidence (FDR<0.1) for selection, including FADS1, KHK, SULT1A2, ITGAM, and several genes in the HLA region. We further confirm that these signals correspond to plausible population-level differences in predicted expression. While the small number of significant genes (0.2%) is consistent with most cis-regulatory variation evolving under genetic drift or stabilizing selection, it remains possible that there are effects not captured in this study. Our gene-level QX score is independent of standard genomic tests for selection, and may therefore be useful in combination with traditional selection scans to specifically identify selection on regulatory variation. Overall, our results demonstrate the utility of combining population-level genomic data with functional data to understand the evolution of gene expression.

Genome-wide analysis identifies genetic effects on reproductive success and ongoing natural selection at the FADS locus

Identifying genetic determinants of reproductive success may highlight mechanisms underlying fertility and identify alleles under present-day selection. Using data in 785,604 individuals of European ancestry, we identified 43 genomic loci associated with either number of children ever born (NEB) or childlessness. These loci span diverse aspects of reproductive biology, including puberty timing, age at first birth, sex hormone regulation, endometriosis and age at menopause. Missense variants in ARHGAP27 were associated with higher NEB but shorter reproductive lifespan, suggesting a trade-off at this locus between reproductive ageing and intensity. Other genes implicated by coding variants include PIK3IP1, ZFP82 and LRP4, and our results suggest a new role for the melanocortin 1 receptor (MC1R) in reproductive biology. As NEB is one component of evolutionary fitness, our identified associations indicate loci under present-day natural selection. Integration with data from historical selection scans highlighted an allele in the FADS1/2 gene locus that has been under selection for thousands of years and remains so today. Collectively, our findings demonstrate that a broad range of biological mechanisms contribute to reproductive success.

Understanding natural selection in Holocene Europe using multi-locus genotype identity scans

Ancient DNA (aDNA) has been a revolutionary technology in understanding human history but has not been used extensively to study natural selection as large sample sizes to study allele frequency changes over time have thus far not been available. Here, we examined a time transect of 708 published samples over the past 7,000 years of European history using multi-locus genotype-based selection scans. As aDNA data is affected by high missingness, ascertainment bias, DNA damage, random allele calling, and is unphased, we first validated our selection scan, G 12 a n c i e n t , on simulated data resembling aDNA under a demographic model that captures broad features of the allele frequency spectrum of European genomes as well as positive controls that have been previously identified and functionally validated in modern European datasets on data from ancient individuals from time periods very close to the present time. We then applied our statistic to the aDNA time transect to detect and resolve the timing of natural selection occurring genome wide and found several candidates of selection across the different time periods that had not been picked up by selection scans using single SNP allele frequency approaches. In addition, enrichment analysis discovered multiple categories of complex traits that might be under adaptation across these periods. Our results demonstrate the utility of applying different types of selection scans to aDNA to uncover putative selection signals at loci in the ancient past that might have been masked in modern samples.

Expression profiles of east-west highly differentiated genes in Uyghur genomes

It remains unknown and debatable how European-Asian-differentiated alleles affect individual phenotypes. Here, we made the first effort to analyze the expression profiles of highly differentiated genes with eastern and western origins in 90 Uyghurs using whole-genome (30× to 60×) and transcriptome data. We screened 921 872 east-west highly differentiated genetic variants, of which ∼4.32% were expression quantitative trait loci (eQTLs), ∼0.12% were alternative splicing quantitative trait loci (sQTLs), and ∼0.12% showed allele-specific expression (ASE). The 8305 highly differentiated eQTLs of strong effects appear to have undergone natural selection, associated with immunity and metabolism. European-origin alleles tend to be more biasedly expressed; highly differentiated ASEs were enriched in diabetes-associated genes, likely affecting the diabetes susceptibility in the Uyghurs. We proposed an admixture-induced expression model to dissect the highly differentiated expression profiles. We provide new insights into the genetic basis of phenotypic differentiation between Western and Eastern populations, advancing our understanding of the impact of genetic admixture.

Extraordinary selection on the human X chromosome associated with archaic admixture

The X chromosome in non-African humans shows less diversity and less Neanderthal introgression than expected from neutral evolution. Analyzing 162 human male X chromosomes worldwide, we identified fourteen chromosomal regions where nearly identical haplotypes spanning several hundred kilobases are found at high frequencies in non-Africans. Genetic drift alone cannot explain the existence of these haplotypes, which must have been associated with strong positive selection in partial selective sweeps. Moreover, the swept haplotypes are entirely devoid of archaic ancestry as opposed to the non-swept haplotypes in the same genomic regions. The ancient Ust'-Ishim male dated at 45,000 before the present (BP) also carries the swept haplotypes, implying that selection on the haplotypes must have occurred between 45,000 and 55,000 years ago. Finally, we find that the chromosomal positions of sweeps overlap previously reported hotspots of selective sweeps in great ape evolution, suggesting a mechanism of selection unique to X chromosomes.

Fluctuating selection and the determinants of genetic variation

Recent studies of cosmopolitan Drosophila populations have found hundreds to thousands of genetic loci with seasonally fluctuating allele frequencies, bringing temporally fluctuating selection to the forefront of the historical debate surrounding the maintenance of genetic variation in natural populations. Numerous mechanisms have been explored in this longstanding area of research, but these exciting empirical findings have prompted several recent theoretical and experimental studies that seek to better understand the drivers, dynamics, and genome-wide influence of fluctuating selection. In this review, we evaluate the latest evidence for multilocus fluctuating selection in Drosophila and other taxa, highlighting the role of potential genetic and ecological mechanisms in maintaining these loci and their impacts on neutral genetic variation.

Long-term trends in human body size track regional variation in subsistence transitions and growth acceleration linked to dairying

Evidence for a reduction in stature between Mesolithic foragers and Neolithic farmers has been interpreted as reflective of declines in health, however, our current understanding of this trend fails to account for the complexity of cultural and dietary transitions or the possible causes of phenotypic change. The agricultural transition was extended in primary centers of domestication and abrupt in regions characterized by demic diffusion. In regions such as Northern Europe where foreign domesticates were difficult to establish, there is strong evidence for natural selection for lactase persistence in relation to dairying. We employ broad-scale analyses of diachronic variation in stature and body mass in the Levant, Europe, the Nile Valley, South Asia, and China, to test three hypotheses about the timing of subsistence shifts and human body size, that: 1) the adoption of agriculture led to a decrease in stature, 2) there were different trajectories in regions of in situ domestication or cultural diffusion of agriculture; and 3) increases in stature and body mass are observed in regions with evidence for selection for lactase persistence. Our results demonstrate that 1) decreases in stature preceded the origins of agriculture in some regions; 2) the Levant and China, regions of in situ domestication of species and an extended period of mixed foraging and agricultural subsistence, had stable stature and body mass over time; and 3) stature and body mass increases in Central and Northern Europe coincide with the timing of selective sweeps for lactase persistence, providing support for the "Lactase Growth Hypothesis."

Investigating associations of omega-3 fatty acids, lung function decline, and airway obstruction

Rationale

Inflammation contributes to lung function decline and the development of chronic obstructive pulmonary disease. Omega-3 fatty acids have anti-inflammatory properties and may benefit lung health.

Objectives

Investigate associations of omega-3 fatty acids with lung function decline and incident airway obstruction in adults of diverse races/ethnicities from general population cohorts.

Methods

Complementary study designs: (1) longitudinal study of plasma phospholipid omega-3 fatty acids and repeated FEV 1 and FVC measures in the National Heart, Lung, and Blood Institute Pooled Cohorts Study, and (2) two-sample Mendelian Randomization (MR) study of genetically predicted omega-3 fatty acids and lung function parameters.

Measurements and Main Results

The longitudinal study found that higher omega-3 fatty acid concentrations were associated with attenuated lung function decline in 15,063 participants, with the largest effect sizes for docosahexaenoic acid (DHA). One standard deviation higher DHA was associated with an attenuation of 1.8 mL/year for FEV 1 (95% confidence interval [CI] 1.3-2.2) and 2.4 mL/year for FVC (95% CI 1.9-3.0). One standard deviation higher DHA was also associated with a 9% lower incidence of spirometry-defined airway obstruction (95% CI 0.86-0.97). DHA associations persisted across sexes, smoking histories, and Black, white and Hispanic participants, with the largest magnitude associations in former smokers and Hispanics. The MR study showed positive associations of genetically predicted omega-3 fatty acids with FEV 1 and FVC, with statistically significant findings across multiple MR methods.

Conclusions

The longitudinal and MR studies provide evidence supporting beneficial effects of higher circulating omega-3 fatty acids, especially DHA, on lung health.

Balancing selection on genomic deletion polymorphisms in humans

A key question in biology is why genomic variation persists in a population for extended periods. Recent studies have identified examples of genomic deletions that have remained polymorphic in the human lineage for hundreds of millennia, ostensibly owing to balancing selection. Nevertheless, genome-wide investigation of ancient and possibly adaptive deletions remains an imperative exercise. Here, we demonstrate an excess of polymorphisms in present-day humans that predate the modern human-Neanderthal split (ancient polymorphisms), which cannot be explained solely by selectively neutral scenarios. We analyze the adaptive mechanisms that underlie this excess in deletion polymorphisms. Using a previously published measure of balancing selection, we show that this excess of ancient deletions is largely owing to balancing selection. Based on the absence of signatures of overdominance, we conclude that it is a rare mode of balancing selection among ancient deletions. Instead, more complex scenarios involving spatially and temporally variable selective pressures are likely more common mechanisms. Our results suggest that balancing selection resulted in ancient deletions harboring disproportionately more exonic variants with GWAS (genome-wide association studies) associations. We further found that ancient deletions are significantly enriched for traits related to metabolism and immunity. As a by-product of our analysis, we show that deletions are, on average, more deleterious than single nucleotide variants. We can now argue that not only is a vast majority of common variants shared among human populations, but a considerable portion of biologically relevant variants has been segregating among our ancestors for hundreds of thousands, if not millions, of years.

Modeling the spatiotemporal spread of beneficial alleles using ancient genomes

Ancient genome sequencing technologies now provide the opportunity to study natural selection in unprecedented detail. Rather than making inferences from indirect footprints left by selection in present-day genomes, we can directly observe whether a given allele was present or absent in a particular region of the world at almost any period of human history within the last 10,000 years. Methods for studying selection using ancient genomes often rely on partitioning individuals into discrete time periods or regions of the world. However, a complete understanding of natural selection requires more nuanced statistical methods which can explicitly model allele frequency changes in a continuum across space and time. Here we introduce a method for inferring the spread of a beneficial allele across a landscape using two-dimensional partial differential equations. Unlike previous approaches, our framework can handle time-stamped ancient samples, as well as genotype likelihoods and pseudohaploid sequences from low-coverage genomes. We apply the method to a panel of published ancient West Eurasian genomes to produce dynamic maps showcasing the inferred spread of candidate beneficial alleles over time and space. We also provide estimates for the strength of selection and diffusion rate for each of these alleles. Finally, we highlight possible avenues of improvement for accurately tracing the spread of beneficial alleles in more complex scenarios.

CONGA: Copy number variation genotyping in ancient genomes and low-coverage sequencing data

To date, ancient genome analyses have been largely confined to the study of single nucleotide polymorphisms (SNPs). Copy number variants (CNVs) are a major contributor of disease and of evolutionary adaptation, but identifying CNVs in ancient shotgun-sequenced genomes is hampered by typical low genome coverage (<1×) and short fragments (<80 bps), precluding standard CNV detection software to be effectively applied to ancient genomes. Here we present CONGA, tailored for genotyping CNVs at low coverage. Simulations and down-sampling experiments suggest that CONGA can genotype deletions >1 kbps with F-scores >0.75 at ≥1×, and distinguish between heterozygous and homozygous states. We used CONGA to genotype 10,002 outgroup-ascertained deletions across a heterogenous set of 71 ancient human genomes spanning the last 50,000 years, produced using variable experimental protocols. A fraction of these (21/71) display divergent deletion profiles unrelated to their population origin, but attributable to technical factors such as coverage and read length. The majority of the sample (50/71), despite originating from nine different laboratories and having coverages ranging from 0.44×-26× (median 4×) and average read lengths 52-121 bps (median 69), exhibit coherent deletion frequencies. Across these 50 genomes, inter-individual genetic diversity measured using SNPs and CONGA-genotyped deletions are highly correlated. CONGA-genotyped deletions also display purifying selection signatures, as expected. CONGA thus paves the way for systematic CNV analyses in ancient genomes, despite the technical challenges posed by low and variable genome coverage.

Admixture has obscured signals of historical hard sweeps in humans

The role of natural selection in shaping biological diversity is an area of intense interest in modern biology. To date, studies of positive selection have primarily relied on genomic datasets from contemporary populations, which are susceptible to confounding factors associated with complex and often unknown aspects of population history. In particular, admixture between diverged populations can distort or hide prior selection events in modern genomes, though this process is not explicitly accounted for in most selection studies despite its apparent ubiquity in humans and other species. Through analyses of ancient and modern human genomes, we show that previously reported Holocene-era admixture has masked more than 50 historic hard sweeps in modern European genomes. Our results imply that this canonical mode of selection has probably been underappreciated in the evolutionary history of humans and suggest that our current understanding of the tempo and mode of selection in natural populations may be inaccurate.

Unraveling Signatures of Local Adaptation among Indigenous Groups from Mexico

Few studies have addressed how selective pressures have shaped the genetic structure of the current Native American populations, and they have mostly limited their inferences to admixed Latin American populations. Here, we searched for local adaptation signals, based on integrated haplotype scores and population branch statistics, in 325 Mexican Indigenous individuals with at least 99% Native American ancestry from five previously defined geographical regions. Although each region exhibited its own local adaptation profile, only PPARG and AJAP1, both negative regulators of the Wnt/β catenin signaling pathway, showed significant adaptation signals in all the tested regions. Several signals were found, mainly in the genes related to the metabolic processes and immune response. A pathway enrichment analysis revealed the overrepresentation of selected genes related to several biological phenotypes/conditions, such as the immune response and metabolic pathways, in agreement with previous studies, suggesting that immunological and metabolic pressures are major drivers of human adaptation. Genes related to the gut microbiome measurements were overrepresented in all the regions, highlighting the importance of studying how humans have coevolved with the microbial communities that colonize them. Our results provide a further explanation of the human evolutionary history in response to environmental pressures in this region.

Tracing Bai-Yue Ancestry in Aboriginal Li People on Hainan Island

As the most prevalent aboriginal group on Hainan Island located between South China and the mainland of Southeast Asia, the Li people are believed to preserve some unique genetic information due to their isolated circumstances, although this has been largely uninvestigated. We performed the first whole-genome sequencing of 55 Hainan Li (HNL) individuals with high coverage (∼30-50×) to gain insight into their genetic history and potential adaptations. We identified the ancestry enriched in HNL (∼85%) is well preserved in present-day Tai-Kadai speakers residing in South China and North Vietnam, that is, Bai-Yue populations. A lack of admixture signature due to the geographical restriction exacerbated the bottleneck in the present-day HNL. The genetic divergence among Bai-Yue populations began ∼4,000-3,000 years ago when the proto-HNL underwent migration and the settling of Hainan Island. Finally, we identified signatures of positive selection in the HNL, some outstanding examples included FADS1 and FADS2 related to a diet rich in polyunsaturated fatty acids. In addition, we observed that malaria-driven selection had occurred in the HNL, with population-specific variants of malaria-related genes (e.g., CR1) present. Interestingly, HNL harbors a high prevalence of malaria leveraged gene variants related to hematopoietic function (e.g., CD3G) that may explain the high incidence of blood disorders such as B-cell lymphomas in the present-day HNL. The results have advanced our understanding of the genetic history of the Bai-Yue populations and have provided new insights into the adaptive scenarios of the Li people.

1,000 ancient genomes uncover 10,000 years of natural selection in Europe

Ancient DNA has revolutionized our understanding of human population history. However, its potential to examine how rapid cultural evolution to new lifestyles may have driven biological adaptation has not been met, largely due to limited sample sizes. We assembled genome-wide data from 1,291 individuals from Europe over 10,000 years, providing a dataset that is large enough to resolve the timing of selection into the Neolithic, Bronze Age, and Historical periods. We identified 25 genetic loci with rapid changes in frequency during these periods, a majority of which were previously undetected. Signals specific to the Neolithic transition are associated with body weight, diet, and lipid metabolism-related phenotypes. They also include immune phenotypes, most notably a locus that confers immunity to Salmonella infection at a time when ancient Salmonella genomes have been shown to adapt to human hosts, thus providing a possible example of human-pathogen co-evolution. In the Bronze Age, selection signals are enriched near genes involved in pigmentation and immune-related traits, including at a key human protein interactor of SARS-CoV-2. Only in the Historical period do the selection candidates we detect largely mirror previously-reported signals, highlighting how the statistical power of previous studies was limited to the last few millennia. The Historical period also has multiple signals associated with vitamin D binding, providing evidence that lactase persistence may have been part of an oligogenic adaptation for efficient calcium uptake and challenging the theory that its adaptive value lies only in facilitating caloric supplementation during times of scarcity. Finally, we detect selection on complex traits in all three periods, including selection favoring variants that reduce body weight in the Neolithic. In the Historical period, we detect selection favoring variants that increase risk for cardiovascular disease plausibly reflecting selection for a more active inflammatory response that would have been adaptive in the face of increased infectious disease exposure. Our results provide an evolutionary rationale for the high prevalence of these deadly diseases in modern societies today and highlight the unique power of ancient DNA in elucidating biological change that accompanied the profound cultural transformations of recent human history.

Evolutionary adaptation highlights the interconnection of fatty acids, sunlight, inflammation and epithelial adhesion

Gene variants that influence human biology today reflect thousands of years of evolution. Genetic effects on infant health are a major point of selective pressure, given that childhood survival is essential to evolutionary success. Knowledge of this evolutionary history can have implications for paediatric research. CONCLUSION: An episode of human adaptation to the extremely low ultraviolet radiation environment of the Arctic 20,000 years ago implicates the Ectodysplasin A Receptor (EDAR) and the Fatty Acid Desaturases (FADS) in human lactation and epithelial inflammation.

Eco-Evolutionary Dynamics of the Human-Gut Microbiota Symbiosis in a Changing Nutritional Environment

The operational harmony between living beings and their circumstances, their ever-changing environment, is a constitutive condition of their existence. Nutrition and symbiosis are two essential aspects of this harmony. Disruption of the symbiosis between host and gut microbiota, the so-called dysbiosis, as well as the inadequate diet from which it results, contribute to the etiology of immunometabolic disorders. Research into the development of these diseases is highly influenced by our understanding of the evolutionary roots of metabolic functioning, thereby considering that chronic non-communicable diseases arise from an evolutionary mismatch. However, the lens has been mostly directed toward energy availability and metabolism, but away from our closest environmental factor, the gut microbiota. Thus, this paper proposes a narrative thread that places symbiosis in an evolutionary perspective, expanding the traditional framework of humans’ adaptation to their food environment.

Evolutionary Trajectories of Complex Traits in European Populations of Modern Humans

Humans have a great diversity in phenotypes, influenced by genetic, environmental, nutritional, cultural, and social factors. Understanding the historical trends of physiological traits can shed light on human physiology, as well as elucidate the factors that influence human diseases. Here we built genome-wide polygenic scores for heritable traits, including height, body mass index, lipoprotein concentrations, cardiovascular disease, and intelligence, using summary statistics of genome-wide association studies in Europeans. Subsequently, we applied these scores to the genomes of ancient European populations. Our results revealed that after the Neolithic, European populations experienced an increase in height and intelligence scores, decreased their skin pigmentation, while the risk for coronary artery disease increased through a genetic trajectory favoring low HDL concentrations. These results are a reflection of the continuous evolutionary processes in humans and highlight the impact that the Neolithic revolution had on our lifestyle and health.

Similarity-Based Analysis of Allele Frequency Distribution among Multiple Populations Identifies Adaptive Genomic Structural Variants

Structural variants have a considerable impact on human genomic diversity. However, their evolutionary history remains mostly unexplored. Here, we developed a new method to identify potentially adaptive structural variants based on a similarity-based analysis that incorporates genotype frequency data from 26 populations simultaneously. Using this method, we analyzed 57,629 structural variants and identified 576 structural variants that show unusual population differentiation. Of these putatively adaptive structural variants, we further showed that 24 variants are multiallelic and overlap with coding sequences, and 20 variants are significantly associated with GWAS traits. Closer inspection of the haplotypic variation associated with these putatively adaptive and functional structural variants reveals deviations from neutral expectations due to: 1) population differentiation of rapidly evolving multiallelic variants, 2) incomplete sweeps, and 3) recent population-specific negative selection. Overall, our study provides new methodological insights, documents hundreds of putatively adaptive variants, and introduces evolutionary models that may better explain the complex evolution of structural variants.

A Deep-Learning Approach for Inference of Selective Sweeps from the Ancestral Recombination Graph

Detecting signals of selection from genomic data is a central problem in population genetics. Coupling the rich information in the ancestral recombination graph (ARG) with a powerful and scalable deep-learning framework, we developed a novel method to detect and quantify positive selection: Selection Inference using the Ancestral recombination graph (SIA). Built on a Long Short-Term Memory (LSTM) architecture, a particular type of a Recurrent Neural Network (RNN), SIA can be trained to explicitly infer a full range of selection coefficients, as well as the allele frequency trajectory and time of selection onset. We benchmarked SIA extensively on simulations under a European human demographic model, and found that it performs as well or better as some of the best available methods, including state-of-the-art machine-learning and ARG-based methods. In addition, we used SIA to estimate selection coefficients at several loci associated with human phenotypes of interest. SIA detected novel signals of selection particular to the European (CEU) population at the MC1R and ABCC11 loci. In addition, it recapitulated signals of selection at the LCT locus and several pigmentation-related genes. Finally, we reanalyzed polymorphism data of a collection of recently radiated southern capuchino seedeater taxa in the genus Sporophila to quantify the strength of selection and improved the power of our previous methods to detect partial soft sweeps. Overall, SIA uses deep learning to leverage the ARG and thereby provides new insight into how selective sweeps shape genomic diversity.

Direct detection of natural selection in Bronze Age Britain

We developed a novel method for efficiently estimating time-varying selection coefficients from genome-wide ancient DNA data. In simulations, our method accurately recovers selective trajectories and is robust to misspecification of population size. We applied it to a large data set of ancient and present-day human genomes from Britain and identified seven loci with genome-wide significant evidence of selection in the past 4500 yr. Almost all of them can be related to increased vitamin D or calcium levels, suggesting strong selective pressure on these or related phenotypes. However, the strength of selection on individual loci varied substantially over time, suggesting that cultural or environmental factors moderated the genetic response. Of 28 complex anthropometric and metabolic traits, skin pigmentation was the only one with significant evidence of polygenic selection, further underscoring the importance of phenotypes related to vitamin D. Our approach illustrates the power of ancient DNA to characterize selection in human populations and illuminates the recent evolutionary history of Britain.