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 from high-coverage whole-genome sequences of diverse African hunter-gatherers.

To reconstruct modern human evolutionary history and identify loci that have shaped hunter-gatherer adaptation, we sequenced the whole genomes of five individuals in each of three different hunter-gatherer populations at > 60× coverage: Pygmies from Cameroon and Khoesan-speaking Hadza and Sandawe from Tanzania. We identify 13.4 million variants, substantially increasing the set of known human variation. We found evidence of archaic introgression in all three populations, and the distribution of time to most recent common ancestors from these regions is similar to that observed for introgressed regions in Europeans. Additionally, we identify numerous loci that harbor signatures of local adaptation, including genes involved in immunity, metabolism, olfactory and taste perception, reproduction, and wound healing. Within the Pygmy population, we identify multiple highly differentiated loci that play a role in growth and anterior pituitary function and are associated with height.

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.

Spatially Resolved Metabolomics Based on Air-Flow-Assisted Desorption Electrospray Ionization-Mass Spectrometry Imaging Reveals Region-Specific Metabolic Alterations in Diabetic Encephalopathy.

Spatially resolved metabolic profiling of brain is vital for elucidating tissue-specific molecular histology and pathology underlying diabetic encephalopathy (DE). In this study, a spatially resolved metabolomic method based on air-flow-assisted desorption electrospray ionization-mass spectrometry imaging (AFADESI-MSI) was developed for investigating the region-specific metabolic disturbances in the brain of DE model rats induced by a high-fat diet in combination with streptozotocin administration. A total of 19 discriminating metabolites associated with glycolysis and the pentose phosphate pathway (PPP); the glutamate/gamma aminobutyric acid-glutamine cycle and tricarboxylic acid cycle; nucleotide metabolism; lipid metabolism; carnitine homeostasis; and taurine, ascorbic acid, histidine, and choline metabolism were identified and located in the brains of the diabetic rats simultaneously for the first time. The results indicated that increased glycolytic and PPP activity; dysfunction of mitochondrial metabolism; dysregulation of adenosinergic, glutamatergic, dopaminergic, cholinergic, and histaminergic systems; disorder of osmotic regulation and antioxidant system; and disorder of lipid metabolism occur in a region-specific fashion in the brains of DE rats. Thus, this study provides valuable information regarding the molecular pathological signature of DE. These findings also underline the high potential of AFADESI-MSI for applications in various central nervous system diseases.

Robust Inference of Identity by Descent from Exome-Sequencing Data.

Identifying and characterizing genomic regions that are shared identical by descent (IBD) among individuals can yield insight into population history, facilitate the identification of adaptively evolving loci, and be an important tool in disease gene mapping. Although increasingly large collections of exome sequences have been generated, it is challenging to detect IBD segments in exomes, precluding many potentially informative downstream analyses. Here, we describe an approach, ExIBD, to robustly detect IBD segments in exome-sequencing data, rigorously evaluate its performance, and apply this method to high-coverage exomes from 6,515 European and African Americans. Furthermore, we show how IBD networks, constructed from patterns of pairwise IBD between individuals, and principles from graph theory provide insight into recent population history and reveal cryptic population structure in European Americans. Our results enable IBD analyses to be performed on exome data, which will expand the scope of inferences that can be made from existing massively large exome-sequencing datasets.

Analysis of 6,515 exomes reveals the recent origin of most human protein-coding variants.

Establishing the age of each mutation segregating in contemporary human populations is important to fully understand our evolutionary history and will help to facilitate the development of new approaches for disease-gene discovery. Large-scale surveys of human genetic variation have reported signatures of recent explosive population growth, notable for an excess of rare genetic variants, suggesting that many mutations arose recently. To more quantitatively assess the distribution of mutation ages, we resequenced 15,336 genes in 6,515 individuals of European American and African American ancestry and inferred the age of 1,146,401 autosomal single nucleotide variants (SNVs). We estimate that approximately 73% of all protein-coding SNVs and approximately 86% of SNVs predicted to be deleterious arose in the past 5,000-10,000 years. The average age of deleterious SNVs varied significantly across molecular pathways, and disease genes contained a significantly higher proportion of recently arisen deleterious SNVs than other genes. Furthermore, European Americans had an excess of deleterious variants in essential and Mendelian disease genes compared to African Americans, consistent with weaker purifying selection due to the Out-of-Africa dispersal. Our results better delimit the historical details of human protein-coding variation, show the profound effect of recent human history on the burden of deleterious SNVs segregating in contemporary populations, and provide important practical information that can be used to prioritize variants in disease-gene discovery.

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.

Correlation between frequency of non-allelic homologous recombination and homology properties: evidence from homology-mediated CNV mutations in the human genome.

Non-allelic homologous recombination (NAHR) is one of the key mechanisms of DNA rearrangement. NAHR occurring between direct homologous repeats can generate genomic copy number variation (CNV) and make significant contributions to both genome evolution and human diseases such as cancer. Intriguingly, previous observations on the rare CNVs at certain genomic disorder loci suggested that NAHR frequency could be dependent on homology properties. However, such a correlation remains unclear at the other NAHR-mediated CNV loci, especially the common CNVs in human populations. Different from the rare CNVs associated with genomic disorders, it is challenging to identify de novo NAHR events at common CNV loci. Therefore, our previously proposed statistic M was employed in estimating relative mutation rate for the NAHR-mediated CNVs in human populations. By utilizing generalized regression neural network and principal component analysis in studying 4330 CNVs ascertained in 3 HapMap populations, we identified the CNVs mediated by NAHR between paired segmental duplications (SDs) and further revealed the correlations between SD properties and NAHR probability. SD length and inter-SD distance were shown to make major contributions to the occurrence of NAHR, whereas chromosomal position and sequence similarity of paired SDs are also involved in NAHR. An integrated effect of SD properties on NAHR frequency was revealed for the common CNVs in human populations. These observations can be well explained by ectopic synapsis in NAHR together with our proposed model of chromosomal compression/extension/looping (CCEL) for homology mis-pairing. Our findings showed the important roles of SDs in NAHR and human genomic evolution.

Characteristics of neutral and deleterious protein-coding variation among individuals and populations.

Whole-genome and exome data sets continue to be produced at a frenetic pace, resulting in massively large catalogs of human genomic variation. However, a clear picture of the characteristics and patterns of neutral and deleterious variation within and between populations has yet to emerge, given that recent large-scale sequencing studies have often emphasized different aspects of the data and sometimes appear to have conflicting conclusions. Here, we comprehensively studied characteristics of protein-coding variation in high-coverage exome sequence data from 6,515 European American (EA) and African American (AA) individuals. We developed an unbiased approach to identify putatively deleterious variants and investigated patterns of neutral and deleterious single-nucleotide variants and alleles between individuals and populations. We show that there are substantial differences in the composition of genotypes between EA and AA populations and that small but statistically significant differences exist in the average number of deleterious alleles carried by EA and AA individuals. Furthermore, we performed extensive simulations to delineate the temporal dynamics of deleterious alleles for a broad range of demographic models and use these data to inform the interpretation of empirical patterns of deleterious variation. Finally, we illustrate that the effects of demographic perturbations, such as bottlenecks and expansions, often manifest in opposing patterns of neutral and deleterious variation depending on whether the focus is on populations or individuals. Our results clarify seemingly disparate empirical characteristics of protein-coding variation and provide substantial insights into how natural selection and demographic history have patterned neutral and deleterious variation within and between populations.

Rare variation facilitates inferences of fine-scale population structure in humans.

Understanding the genetic structure of human populations has important implications for the design and interpretation of disease mapping studies and reconstructing human evolutionary history. To date, inferences of human population structure have primarily been made with common variants. However, recent large-scale resequencing studies have shown an abundance of rare variation in humans, which may be particularly useful for making inferences of fine-scale population structure. To this end, we used an information theory framework and extensive coalescent simulations to rigorously quantify the informativeness of rare and common variation to detect signatures of fine-scale population structure. We show that rare variation affords unique insights into patterns of recent population structure. Furthermore, to empirically assess our theoretical findings, we analyzed high-coverage exome sequences in 6,515 European and African American individuals. As predicted, rare variants are more informative than common polymorphisms in revealing a distinct cluster of European-American individuals, and subsequent analyses demonstrate that these individuals are likely of Ashkenazi Jewish ancestry. Our results provide new insights into the population structure using rare variation, which will be an important factor to account for in rare variant association studies.

Global and disease-associated genetic variation in the human Fanconi anemia gene family.

Fanconi anemia (FA) is a human recessive genetic disease resulting from inactivating mutations in any of 16 FANC (Fanconi) genes. Individuals with FA are at high risk of developmental abnormalities, early bone marrow failure and leukemia. These are followed in the second and subsequent decades by a very high risk of carcinomas of the head and neck and anogenital region, and a small continuing risk of leukemia. In order to characterize base pair-level disease-associated (DA) and population genetic variation in FANC genes and the segregation of this variation in the human population, we identified 2948 unique FANC gene variants including 493 FA DA variants across 57,240 potential base pair variation sites in the 16 FANC genes. We then analyzed the segregation of this variation in the 7578 subjects included in the Exome Sequencing Project (ESP) and the 1000 Genomes Project (1KGP). There was a remarkably high frequency of FA DA variants in ESP/1KGP subjects: at least 1 FA DA variant was identified in 78.5% (5950 of 7578) individuals included in these two studies. Six widely used functional prediction algorithms correctly identified only a third of the known, DA FANC missense variants. We also identified FA DA variants that may be good candidates for different types of mutation-specific therapies. Our results demonstrate the power of direct DNA sequencing to detect, estimate the frequency of and follow the segregation of deleterious genetic variation in human populations.

Selection and adaptation in the human genome.

An enduring goal of evolutionary biology is to understand how natural selection has shaped patterns of polymorphism and divergence within and between species and to map the genetic basis of adaptations. The rapid maturation of next-generation sequencing technology has generated a deluge of genomics data from nonhuman primates, extinct hominins, and diverse human populations. These emerging genome data sets have simultaneously broadened our understanding of human evolution and sharply defined existing gaps in knowledge about the mechanistic basis of evolutionary change. In this review, we summarize recent insights into how natural selection has influenced the human genome across different timescales. Although the path to a more comprehensive understanding of selection and adaptation in humans remains arduous, some general insights are beginning to emerge, such as the importance of adaptive regulatory evolution, the absence of pervasive classic selective sweeps, and the potential roles that selection from standing variation and polygenic adaptation have likely played in recent human evolutionary history.

Identification of Key Genes of Fruit Shape Variation in Jujube with Integrating Elliptic Fourier Descriptors and Transcriptome.

Jujube (Ziziphus jujuba) exhibits a rich diversity in fruit shape, with natural occurrences of gourd-like, flattened, and other special shapes. Despite the ongoing research into fruit shape, studies integrating elliptical Fourier descriptors (EFDs) with both Short Time-series Expression Miner (STEM) and weighted gene co-expression network analysis (WGCNA) for gene discovery remain scarce. In this study, six cultivars of jujube fruits with distinct shapes were selected, and samples were collected from the fruit set period to the white mature stage across five time points for shape analysis and transcriptome studies. By combining EFDs with WGCNA and STEM, the study aimed to identify the critical periods and key genes involved in the formation of jujube fruit shape. The findings indicated that the D25 (25 days after flowering) is crucial for the development of jujube fruit shape. Moreover, ZjAGL80, ZjABI3, and eight other genes have been implicated to regulate the shape development of jujubes at different periods of fruit development, through seed development and fruit development pathway. In this research, EFDs were employed to precisely delineate the shape of jujube fruits. This approach, in conjunction with transcriptome, enhanced the precision of gene identification, and offered an innovative methodology for fruit shape analysis. This integration facilitates the advancement of research into the morphological characteristics of plant fruits, underpinning the development of a refined framework for the genetic underpinnings of fruit shape variation.

Identification of copy number variation hotspots in human populations.

Copy number variants (CNVs) in the human genome contribute to both Mendelian and complex traits as well as to genomic plasticity in evolution. The investigation of mutational rates of CNVs is critical to understanding genomic instability and the etiology of the copy number variation (CNV)-related traits. However, the evaluation of the CNV mutation rate at the genome level poses an insurmountable practical challenge that requires large samples and accurate typing. In this study, we show that an approximate estimation of the CNV mutation rate could be achieved by using the phylogeny information of flanking SNPs. This allows a genome-wide comparison of mutation rates between CNVs with the use of vast, readily available data of SNP genotyping. A total of 4187 CNV regions (CNVRs) previously identified in HapMap populations were investigated in this study. We showed that the mutation rates for the majority of these CNVRs are at the order of 10⁻5 per generation, consistent with experimental observations at individual loci. Notably, the mutation rates of 104 (2.5%) CNVRs were estimated at the order of 10⁻³ per generation; therefore, they were identified as potential hotspots. Additional analyses revealed that genome architecture at CNV loci has a potential role in inciting mutational hotspots in the human genome. Interestingly, 49 (47%) CNV hotspots include human genes, some of which are known to be functional CNV loci (e.g., CNVs of C4 and ß-defensin causing autoimmune diseases and CNVs of HYDIN with implication in control of cerebral cortex size), implicating the important role of CNV in human health and evolution, especially in common and complex diseases.

Genomic dissection of population substructure of Han Chinese and its implication in association studies.

To date, most genome-wide association studies (GWAS) and studies of fine-scale population structure have been conducted primarily on Europeans. Han Chinese, the largest ethnic group in the world, composing 20% of the entire global human population, is largely underrepresented in such studies. A well-recognized challenge is the fact that population structure can cause spurious associations in GWAS. In this study, we examined population substructures in a diverse set of over 1700 Han Chinese samples collected from 26 regions across China, each genotyped at approximately 160K single-nucleotide polymorphisms (SNPs). Our results showed that the Han Chinese population is intricately substructured, with the main observed clusters corresponding roughly to northern Han, central Han, and southern Han. However, simulated case-control studies showed that genetic differentiation among these clusters, although very small (F(ST) = 0.0002 approximately 0.0009), is sufficient to lead to an inflated rate of false-positive results even when the sample size is moderate. The top two SNPs with the greatest frequency differences between the northern Han and southern Han clusters (F(ST) > 0.06) were found in the FADS2 gene, which associates with the fatty acid composition in phospholipids, and in the HLA complex P5 gene (HCP5), which associates with HIV infection, psoriasis, and psoriatic arthritis. Ingenuity Pathway Analysis (IPA) showed that most differentiated genes among clusters are involved in cardiac arteriopathy (p < 10(-101)). These signals indicating significant differences among Han Chinese subpopulations should be carefully explained in case they are also detected in association studies, especially when sample sources are diverse.

Present Y chromosomes reveal the ancestry of Emperor CAO Cao of 1800 years ago.

Emperor CAO Cao (155AD-220AD) is one of the most famous persons in Chinese history that had changed the history of East Asia. He claimed to be a descendant of Marquis CAO Can and therefore was of aristocratic ancestry. However, this claim has been suspected for around 1800 years. Here, we collected some present clans with full records of 70-100 generations claimed to be descendants of CAO Cao or CAO Can, and validated them by comparing their Y chromosomes. Haplotype O2-M268 is the only one that is enriched significantly in the Emperor's claimed descendant clans (P=9.323 × 10(-5), odds ratio=12.72) and, therefore, is most likely to be that of the Emperor. Moreover, our analysis showed that the Y chromosome haplotype of the Emperor is different from that of the Marquis (Haplotype O3-002611). Therefore, Emperor CAO Cao's claim was not supported by genetic evidence. This study offers a successful showcase of the utility of genetics in studying the ancient history.

Association of polymorphisms in the solute carrier organic anion transporter family member 1B1 gene with essential hypertension in the Uyghur population.

Solute carrier organic anion transporter family member 1B1 (SLCO1B1) is an important hepatic uptake transporter that can transport a wide variety of endogenous compounds, including thyroid hormones and prostaglandin E2. Dysregulation of thyroid hormones and prostaglandin E2 plays a role in the development of hypertension, suggesting that SLCO1B1 might contribute to the aetiology of essential hypertension (EH). In this study, we selected five single nucleotide polymorphisms (SNPs) at the SLCO1B1 gene promoter or coding regions and performed a case-control association study involving 731 unrelated Uyghur subjects, including 374 hypertensive and 357 normotensive individuals, to investigate the potential genetic contribution of SLCO1B1 to the aetiology of EH. Of the five polymorphisms, only one (i.e., rs4149014) showed correlation with EH. The minor allele of SNP rs4149014 at the SLCO1B1 promoter showed association with increased risk for EH (adjusted OR 1.88; 95% CI 1.36-2.60; P= 1.22 × 10(-4)). This study provides preliminary genetic evidence for the role of variant of SLCO1B1 in the susceptibility to human EH in Uyghurs.

Kinetic cellular phenotypic profiling: prediction, identification, and analysis of bioactive natural products.

Natural products have always been a major source of therapeutic agents; however, the development of traditional herbal products has been currently hampered by the lack of analytic methods suitable for both high-throughput screening and evaluating the mechanism of action. Cellular processes such as proliferation, apoptosis, and toxicity are well-orchestrated in real time. Monitoring these events and their perturbation by natural products can provide high-rich information about cell physiological relevancies being involved. Here, we report a novel cell-based phenotypic profiling strategy that uses electronic impedance readouts for real-time monitoring of cellular responses to traditional Chinese medicines (TCMs). The utility of this approach was used to screen natural herbs that have been historically documented to cure human diseases and that have been classified into seven clusters based on their mechanisms of action. The results suggest that herbal medicines with similar cellular mechanisms produce similar time/dose-dependent cell response profiles (TCRPs). By comparing the TCRPs produced by the Chinese medicinal Cordyceps sinensis with similar TCRPs of chemical compounds, we explored the potential use of herbal TCRPs for predicting cellular mechanisms of action, herbal authentications, and bioactive identification. Additionally, we further compared this novel TCRP technology with high-performance liquid chromatography (HPLC)-based methods for herbal origin-tracing authentication and identification of bioactive ingredients. Together, our findings suggest that using TCRP as an alternative to existing spectroscopic techniques can allow us to analyze natural products in a more convenient and physiologically relevant manner.

Association of a BLVRA common polymorphism with essential hypertension and blood pressure in Kazaks.

Biliverdin reductase A (BLVRA) is a powerful intracellular antioxidant enzyme and an antagonist to insulin-mediated glucose uptake by the cells. Increased oxidative stress and insulin-resistance (IR) are associated with increased risk for hypertension. Therefore, we hypothesized that BLVRA might be attributable to the variation of susceptibility to essential hypertension, and investigated single nucleotide polymorphism (SNP) rs699512 (Thr3Ala), the only common non-synonymous SNP within BLVRA, in population-based samples of 999 Kazak herdsmen from the villages in Xinjiang, China. The minor allele of SNP rs699512 reduced the risk of essential hypertension (age- and gender-adjusted odds ratio 0.76; 95% confidence interval 0.61-0.94; p = 0.010). Single nucleotide polymorphism rs699512 showed association with both systolic and diastolic blood pressures: the minor allele homozygous carriers had lowest systolic and diastolic blood pressures (139.6 mmHg, 89.6mmHg), followed by heterozygous carriers (145.3 mmHg, 92.3 mmHg), and then major allele homozygous carriers (150.3 mmHg, 95.1 mmHg) (p = 0.005 and 0.009, respectively). These findings provide the first genetic evidence for the role of BLVRA on the susceptibility to human essential hypertension and blood pressure.

Spatial-resolved metabolomics reveals tissue-specific metabolic reprogramming in diabetic nephropathy by using mass spectrometry imaging.

Detailed knowledge on tissue-specific metabolic reprogramming in diabetic nephropathy (DN) is vital for more accurate understanding the molecular pathological signature and developing novel therapeutic strategies. In the present study, a spatial-resolved metabolomics approach based on air flow-assisted desorption electrospray ionization (AFADESI) and matrix-assisted laser desorption ionization (MALDI) integrated mass spectrometry imaging (MSI) was proposed to investigate tissue-specific metabolic alterations in the kidneys of high-fat diet-fed and streptozotocin (STZ)-treated DN rats and the therapeutic effect of astragaloside IV, a potential anti-diabetic drug, against DN. As a result, a wide range of functional metabolites including sugars, amino acids, nucleotides and their derivatives, fatty acids, phospholipids, sphingolipids, glycerides, carnitine and its derivatives, vitamins, peptides, and metal ions associated with DN were identified and their unique distribution patterns in the rat kidney were visualized with high chemical specificity and high spatial resolution. These region-specific metabolic disturbances were ameliorated by repeated oral administration of astragaloside IV (100 mg/kg) for 12 weeks. This study provided more comprehensive and detailed information about the tissue-specific metabolic reprogramming and molecular pathological signature in the kidney of diabetic rats. These findings highlighted the promising potential of AFADESI and MALDI integrated MSI based metabolomics approach for application in metabolic kidney diseases.