Human Genome Evolution Research Articles

The whole genome sequences and experimentally phased haplotypes of over 100 personal genomes.

BackgroundSince the completion of the Human Genome Project in 2003, it is estimated that more than 200,000 individual whole human genomes have been sequenced. A stunning accomplishment in such a short period of time. However, most of these were sequenced without experimental haplotype data and are therefore missing an important aspect of genome biology. In addition, much of the genomic data is not available to the public and lacks phenotypic information.FindingsAs part of the Personal Genome Project, blood samples from 184 participants were collected and processed using Complete Genomics’ Long Fragment Read technology. Here, we present the experimental whole genome haplotyping and sequencing of these samples to an average read coverage depth of 100X. This is approximately three-fold higher than the read coverage applied to most whole human genome assemblies and ensures the highest quality results. Currently, 114 genomes from this dataset are freely available in the GigaDB repository and are associated with rich phenotypic data; the remaining 70 should be added in the near future as they are approved through the PGP data release process. For reproducibility analyses, 20 genomes were sequenced at least twice using independent LFR barcoded libraries. Seven genomes were also sequenced using Complete Genomics’ standard non-barcoded library process. In addition, we report 2.6 million high-quality, rare variants not previously identified in the Single Nucleotide Polymorphisms database or the 1000 Genomes Project Phase 3 data.ConclusionsThese genomes represent a unique source of haplotype and phenotype data for the scientific community and should help to expand our understanding of human genome evolution and function.Electronic supplementary materialThe online version of this article (doi:10.1186/s13742-016-0148-z) contains supplementary material, which is available to authorized users.

Identification of Multiple Forms of RNA Transcripts Associated with Human-Specific Retrotransposed Gene Copies.

The human genome contains thousands of retrocopies, mostly as processed pseudogenes, which were recently shown to be prevalently transcribed. In particular, those specifically acquired in the human lineage are able to modulate gene expression in a manner that contributed to the evolution of human-specific traits. Therefore, knowledge of the human-specific retrocopies that are transcribed or their full-length transcript structure contributes to better understand human genome evolution. In this study, we identified 16 human-specific retrocopies that harbor 5′ CpG islands by in silico analysis and showed that 12 were transcribed in normal tissues and cancer cell lines with a variety of expression patterns, including cancer-specific expression. Determination of the structure of the transcripts associated with the retrocopies revealed that none were transcribed from their 5′ CpG islands, but rather, from inside the 3′ UTR and the nearby 5′ flanking region of the retrocopies as well as the promoter of neighboring genes. The multiple forms of the transcripts, such as chimeric and individual transcripts in both the sense and antisense orientation, might have introduced novel post-transcriptional regulation into the genome during human evolution. These results shed light on the potential role of human-specific retrocopies in the evolution of gene regulation and genomic disorders.

The Columbian Exchange as a source of adaptive introgression in human populations.

BackgroundThe term “Columbian Exchange” refers to the massive transfer of life between the Afro-Eurasian and American hemispheres that was precipitated by Columbus’ voyage to the New World. The Columbian Exchange is widely appreciated by historians, social scientists and economists as a major turning point that had profound and lasting effects on the trajectory of human history and development.Presentation of the hypothesisI propose that the Columbian Exchange should also be appreciated by biologists for its role in the creation of novel human genomes that have been shaped by rapid adaptive evolution. Specifically, I hypothesize that the process of human genome evolution stimulated by the Columbian Exchange was based in part on selective sweeps of introgressed haplotypes from ancestral populations, many of which possessed pre-evolved adaptive utility based on regional-specific fitness and health effects.Testing the hypothesisTesting of this hypothesis will require comparative analysis of genome sequences from putative ancestral source populations, with genomes from modern admixed populations, in order to identify ancestry-specific introgressed haplotypes that exist at higher frequencies in admixed populations than can be expected by chance alone. Investigation of such ancestry-enriched genomic regions can be used to provide clues as to the functional roles of the genes therein and the selective forces that have acted to increase their frequency in the population.Implications of the hypothesisCritical interrogation of this hypothesis could serve to underscore the important role of introgression as a source of adaptive alleles and as a driver of evolutionary change, and it would highlight the role of admixture in facilitating rapid human evolution.ReviewersThis article was reviewed by Frank Eisenhaber, Lakshminarayan Iyer and Igor B. Rogozin

Islands of linkage in an ocean of pervasive recombination reveals two-speed evolution of human cytomegalovirus genomes.

Human cytomegalovirus (HCMV) infects most of the population worldwide, persisting throughout the host's life in a latent state with periodic episodes of reactivation. While typically asymptomatic, HCMV can cause fatal disease among congenitally infected infants and immunocompromised patients. These clinical issues are compounded by the emergence of antiviral resistance and the absence of an effective vaccine, the development of which is likely complicated by the numerous immune evasins encoded by HCMV to counter the host's adaptive immune responses, a feature that facilitates frequent super-infections. Understanding the evolutionary dynamics of HCMV is essential for the development of effective new drugs and vaccines. By comparing viral genomes from uncultivated or low-passaged clinical samples of diverse origins, we observe evidence of frequent homologous recombination events, both recent and ancient, and no structure of HCMV genetic diversity at the whole-genome scale. Analysis of individual gene-scale loci reveals a striking dichotomy: while most of the genome is highly conserved, recombines essentially freely and has evolved under purifying selection, 21 genes display extreme diversity, structured into distinct genotypes that do not recombine with each other. Most of these hyper-variable genes encode glycoproteins involved in cell entry or escape of host immunity. Evidence that half of them have diverged through episodes of intense positive selection suggests that rapid evolution of hyper-variable loci is likely driven by interactions with host immunity. It appears that this process is enabled by recombination unlinking hyper-variable loci from strongly constrained neighboring sites. It is conceivable that viral mechanisms facilitating super-infection have evolved to promote recombination between diverged genotypes, allowing the virus to continuously diversify at key loci to escape immune detection, while maintaining a genome optimally adapted to its asymptomatic infectious lifecycle.

The Impact of Evolutionary Driving Forces on Human Complex Diseases: A Population Genetics Approach.

Investigating the molecular evolution of human genome has paved the way to understand genetic adaptation of humans to the environmental changes and corresponding complex diseases. In this review, we discussed the historical origin of genetic diversity among human populations, the evolutionary driving forces that can affect genetic diversity among populations, and the effects of human movement into new environments and gene flow on population genetic diversity. Furthermore, we presented the role of natural selection on genetic diversity and complex diseases. Then we reviewed the disadvantageous consequences of historical selection events in modern time and their relation to the development of complex diseases. In addition, we discussed the effect of consanguinity on the incidence of complex diseases in human populations. Finally, we presented the latest information about the role of ancient genes acquired from interbreeding with ancient hominids in the development of complex diseases.

Genes with stable DNA methylation levels show higher evolutionary conservation than genes with fluctuant DNA methylation levels.

Different human genes often exhibit different degrees of stability in their DNA methylation levels between tissues, samples or cell types. This may be related to the evolution of human genome. Thus, we compared the evolutionary conservation between two types of genes: genes with stable DNA methylation levels (SM genes) and genes with fluctuant DNA methylation levels (FM genes). For long-term evolutionary characteristics between species, we compared the percentage of the orthologous genes, evolutionary rate dn/ds and protein sequence identity. We found that the SM genes had greater percentages of the orthologous genes, lower dn/ds, and higher protein sequence identities in all the 21 species. These results indicated that the SM genes were more evolutionarily conserved than the FM genes. For short-term evolutionary characteristics among human populations, we compared the single nucleotide polymorphism (SNP) density, and the linkage disequilibrium (LD) degree in HapMap populations and 1000 genomes project populations. We observed that the SM genes had lower SNP densities, and higher degrees of LD in all the 11 HapMap populations and 13 1000 genomes project populations. These results mean that the SM genes had more stable chromosome genetic structures, and were more conserved than the FM genes.

Intergenic Alu exonisation facilitates the evolution of tissue-specific transcript ends.

The 3′ untranslated regions (3′ UTRs) of transcripts serve as important hubs for posttranscriptional gene expression regulation. Here, we find that the exonisation of intergenic Alu elements introduced new terminal exons and polyadenylation sites during human genome evolution. While Alu exonisation from introns has been described previously, we shed light on a novel mechanism to create alternative 3′ UTRs, thereby opening opportunities for differential posttranscriptional regulation. On the mechanistic level, we show that intergenic Alu exonisation can compete both with alternative splicing and polyadenylation in the upstream gene. Notably, the Alu-derived isoforms are often expressed in a tissue-specific manner, and the Alu-derived 3′ UTRs can alter mRNA stability. In summary, we demonstrate that intergenic elements can affect processing of preceding genes, and elucidate how intergenic Alu exonisation can contribute to tissue-specific posttranscriptional regulation by expanding the repertoire of 3′ UTRs.

Structural variation mutagenesis of the human genome: Impact on disease and evolution.

Watson-Crick base-pair changes, or single-nucleotide variants (SNV), have long been known as a source of mutations. However, the extent to which DNA structural variation, including duplication and deletion copy number variants (CNV) and copy number neutral inversions and translocations, contribute to human genome variation and disease has been appreciated only recently. Moreover, the potential complexity of structural variants (SV) was not envisioned; thus, the frequency of complex genomic rearrangements and how such events form remained a mystery. The concept of genomic disorders, diseases due to genomic rearrangements and not sequence-based changes for which genomic architecture incite genomic instability, delineated a new category of conditions distinct from chromosomal syndromes and single-gene Mendelian diseases. Nevertheless, it is the mechanistic understanding of CNV/SV formation that has promoted further understanding of human biology and disease and provided insights into human genome and gene evolution. Environ. Mol. Mutagen. 56:419-436, 2015. © 2015 Wiley Periodicals, Inc.

Characterization of 26 deletion CNVs reveals the frequent occurrence of micro-mutations within the breakpoint-flanking regions and frequent repair of double-strand breaks by templated insertions derived from remote genomic regions.

Copy number variations (CNVs) have increasingly been reported to cause, or predispose to, human disease. However, a large fraction of these CNVs have not been accurately characterized at the single-base-pair level, thereby hampering a better understanding of the mutational mechanisms underlying CNV formation. Here, employing a composite pipeline method derived from various inference-based programs, we have characterized 26 deletion CNVs [including three novel pathogenic CNVs involving an autosomal gene (EXT2) causing hereditary osteochondromas and an X-linked gene (CLCN5) causing Dent disease, as well as 23 CNVs previously identified by inference from a cohort of Canadian autism spectrum disorder families] to the single-base-pair level of accuracy from whole-genome sequencing data. We found that breakpoint-flanking micro-mutations (within 22 bp of the breakpoint) are present in a significant fraction (5/26; 19%) of the deletion CNVs. This analysis also provided evidence that a recently described error-prone form of DNA repair (i.e., repair of DNA double-strand breaks by templated nucleotide sequence insertions derived from distant regions of the genome) not only causes human genetic disease but also impacts on human genome evolution. Our findings illustrate the importance of precise CNV breakpoint delineation for understanding the underlying mutational mechanisms and have implications for primer design in relation to the detection of deletion CNVs in clinical diagnosis.

A reconsideration of the role of self-identified races in epidemiology and biomedical research

A considerable number of studies in epidemiology and biomedicine investigate the etiology of complex diseases by considering (self-identified) race as a relevant variable and focusing on the differences in risk among racial groups in the United States; they extensively draw on a genetic hypothesis—viz. the hypothesis that differences in the risk of complex diseases among racial groups are largely due to genetic differences covarying with genetic ancestry—that appears highly problematic in the light of both current biological evidence and the theory of human genome evolution. Is this reason for dismissing self-identified races? No. An alternative promising use of self-identified races exists, and ironically is suggested by those studies that investigate the etiology of complex diseases without focusing on racial differences. These studies provide a large amount of empirical evidence supporting the primacy of the contribution of non-genetic as opposed to genetic factors to the risk of complex diseases. We show that differences in race—or, better, in racial self-identification—may be critically used as proxies for differences in risk-related exposomes and epigenomes in the context of the United States. Self-identified race is what we need to capture the complexity of the effects of present and past racism on people's health and investigate risk-related external and internal exposures, gene–environment interactions, and epigenetic events. In fact patterns of racial self-identifications on one side, and patterns of risk-related exposomes and epigenomes on the other side, constantly coevolve and tend to match each other. However, there is no guarantee that using self-identified races in epidemiology and biomedical research will be beneficial all things considered: special attention must be paid at balancing positive and negative consequences.

Toolbox for mobile-element insertion detection on cancer genomes.

Mobile elements constitute greater than 45% of the human genome as a result of repeated insertion events during human genome evolution. Although most of mobile elements are fixed within the human population, some elements (including ALU, long interspersed elements (LINE) 1 (L1), and SVA) are still actively duplicating and may result in life-threatening human diseases such as cancer, motivating the need for accurate mobile-element insertion (MEI) detection tools. We developed a software package, TANGRAM, for MEI detection in next-generation sequencing data, currently serving as the primary MEI detection tool in the 1000 Genomes Project. TANGRAM takes advantage of valuable mapping information provided by our own MOSAIK mapper, and until recently required MOSAIK mappings as its input. In this study, we report a new feature that enables TANGRAM to be used on alignments generated by any mainstream short-read mapper, making it accessible for many genomic users. To demonstrate its utility for cancer genome analysis, we have applied TANGRAM to the TCGA (The Cancer Genome Atlas) mutation calling benchmark 4 dataset. TANGRAM is fast, accurate, easy to use, and open source on https://github.com/jiantao/Tangram.

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.

Tangram: a comprehensive toolbox for mobile element insertion detection.

BackgroundMobile elements (MEs) constitute greater than 50% of the human genome as a result of repeated insertion events during human genome evolution. Although most of these elements are now fixed in the population, some MEs, including ALU, L1, SVA and HERV-K elements, are still actively duplicating. Mobile element insertions (MEIs) have been associated with human genetic disorders, including Crohn’s disease, hemophilia, and various types of cancer, motivating the need for accurate MEI detection methods. To comprehensively identify and accurately characterize these variants in whole genome next-generation sequencing (NGS) data, a computationally efficient detection and genotyping method is required. Current computational tools are unable to call MEI polymorphisms with sufficiently high sensitivity and specificity, or call individual genotypes with sufficiently high accuracy.ResultsHere we report Tangram, a computationally efficient MEI detection program that integrates read-pair (RP) and split-read (SR) mapping signals to detect MEI events. By utilizing SR mapping in its primary detection module, a feature unique to this software, Tangram is able to pinpoint MEI breakpoints with single-nucleotide precision. To understand the role of MEI events in disease, it is essential to produce accurate individual genotypes in clinical samples. Tangram is able to determine sample genotypes with very high accuracy. Using simulations and experimental datasets, we demonstrate that Tangram has superior sensitivity, specificity, breakpoint resolution and genotyping accuracy, when compared to other, recently developed MEI detection methods.ConclusionsTangram serves as the primary MEI detection tool in the 1000 Genomes Project, and is implemented as a highly portable, memory-efficient, easy-to-use C++ computer program, built under an open-source development model.

Genomic landscape of human, bat, and ex vivo DNA transposon integrations.

The integration and fixation preferences of DNA transposons, one of the major classes of eukaryotic transposable elements, have never been evaluated comprehensively on a genome-wide scale. Here, we present a detailed study of the distribution of DNA transposons in the human and bat genomes. We studied three groups of DNA transposons that integrated at different evolutionary times: 1) ancient (>40 My) and currently inactive human elements, 2) younger (<40 My) bat elements, and 3) ex vivo integrations of piggyBat and Sleeping Beauty elements in HeLa cells. Although the distribution of ex vivo elements reflected integration preferences, the distribution of human and (to a lesser extent) bat elements was also affected by selection. We used regression techniques (linear, negative binomial, and logistic regression models with multiple predictors) applied to 20-kb and 1-Mb windows to investigate how the genomic landscape in the vicinity of DNA transposons contributes to their integration and fixation. Our models indicate that genomic landscape explains 16-79% of variability in DNA transposon genome-wide distribution. Importantly, we not only confirmed previously identified predictors (e.g., DNA conformation and recombination hotspots) but also identified several novel predictors (e.g., signatures of double-strand breaks and telomere hexamer). Ex vivo integrations showed a bias toward actively transcribed regions. Older DNA transposons were located in genomic regions scarce in most conserved elements-likely reflecting purifying selection. Our study highlights how DNA transposons are integral to the evolution of bat and human genomes, and has implications for the development of DNA transposon assays for gene therapy and mutagenesis applications.

PSMA6 (rs2277460, rs1048990), PSMC6 (rs2295826, rs2295827) and PSMA3 (rs2348071) genetic diversity in Latvians, Lithuanians and Taiwanese

PSMA6 (rs2277460, rs1048990), PSMC6 (rs2295826, rs2295827) and PSMA3 (rs2348071) genetic diversity was investigated in 1438 unrelated subjects from Latvia, Lithuania and Taiwan. In general, polymorphism of each individual locus showed tendencies similar to determined previously in HapMap populations. Main differences concern Taiwanese and include presence of rs2277460 rare allele A not found before in Asians and absence of rs2295827 rare alleles homozygotes TT observed in all other human populations. Observed patterns of SNPs and haplotype diversity were compatible with expectation of neutral model of evolution. Linkage disequilibrium between the rs2295826 and rs2295827 was detected to be complete in Latvians and Lithuanians (D´=1; r2=1) and slightly disrupted in Taiwanese (D´=0.978; r2=0.901).Population differentiation (FST statistics) was estimated from pairwise population comparisons of loci variability, five locus haplotypes and PSMA6 and PSMC6 two locus haplotypes. Latvians were significantly different from all Asians at each of 5 SNPs and from Lithuanians at the rs1048990 and PSMC6 loci. Lithuanian and Asian populations exhibited similarities at the PSMC6 loci and were different at the PSMA6 and PSMA3 SNPs. Considering five locus haplotypes all European populations were significantly different from Asian; Lithuanian population was different from both Latvian and CEU.Allele specific patterns of transcription factor binding sites and splicing signals were predicted in silico and addressed to eventual functionality of nucleotide substitutions and their potential to be involved in human genome evolution and geographical adaptation. Current study represents a novel step toward a systematic analysis of the proteasomal gene genetic diversity in human populations.

Diversity through duplication: Whole‐genome sequencing reveals novel gene retrocopies in the human population

Gene retrocopies are generated by reverse transcription and genomic integration of mRNA. As such, retrocopies present an important exception to the central dogma of molecular biology, and have substantially impacted the functional landscape of the metazoan genome. While an estimated 8,000–17,000 retrocopies exist in the human genome reference sequence, the extent of variation between individuals in terms of retrocopy content has remained largely unexplored. Three recent studies by Abyzov et al., Ewing et al. and Schrider et al. have exploited 1,000 Genomes Project Consortium data, as well as other sources of whole-genome sequencing data, to uncover novel gene retrocopies. Here, we compare the methods and results of these three studies, highlight the impact of retrocopies in human diversity and genome evolution, and speculate on the potential for somatic gene retrocopies to impact cancer etiology and genetic diversity among individual neurons in the mammalian brain.

Toolbox for mobile-element insertion detection on cancer genomes.

Mobile elements constitute greater than 45% of the human genome as a result of repeated insertion events during human genome evolution. Although most of mobile elements are fixed within the human population, some elements (including ALU, long interspersed elements (LINE) 1 (L1), and SVA) are still actively duplicating and may result in life-threatening human diseases such as cancer, motivating the need for accurate mobile-element insertion (MEI) detection tools. We developed a software package, TANGRAM, for MEI detection in next-generation sequencing data, currently serving as the primary MEI detection tool in the 1000 Genomes Project. TANGRAM takes advantage of valuable mapping information provided by our own MOSAIK mapper, and until recently required MOSAIK mappings as its input. In this study, we report a new feature that enables TANGRAM to be used on alignments generated by any mainstream short-read mapper, making it accessible for many genomic users. To demonstrate its utility for cancer genome analysis, we have applied TANGRAM to the TCGA (The Cancer Genome Atlas) mutation calling benchmark 4 dataset. TANGRAM is fast, accurate, easy to use, and open source on https://github.com/jiantao/Tangram.

L1 retrotransposons, cancer stem cells and oncogenesis

Retrotransposons have played a central role in human genome evolution. The accumulation of heritable L1, Alu and SVA retrotransposon insertions continues to generate structural variation within and between populations, and can result in spontaneous genetic disease. Recent works have reported somatic L1 retrotransposition in tumours, which in some cases may contribute to oncogenesis. Intriguingly, L1 mobilization appears to occur almost exclusively in cancers of epithelial cell origin. In this review, we discuss how L1 retrotransposition could potentially trigger neoplastic transformation, based on the established correlation between L1 activity and cellular plasticity, and the proven capacity of L1-mediated insertional mutagenesis to decisively alter gene expression and functional output.

A fine-scale recombination map of the human–chimpanzee ancestor reveals faster change in humans than in chimpanzees and a strong impact of GC-biased gene conversion

Recombination is a major determinant of adaptive and nonadaptive evolution. Understanding how the recombination landscape has evolved in humans is thus key to the interpretation of human genomic evolution. Comparison of fine-scale recombination maps of human and chimpanzee has revealed large changes at fine genomic scales and conservation over large scales. Here we demonstrate how a fine-scale recombination map can be derived for the ancestor of human and chimpanzee, allowing us to study the changes that have occurred in human and chimpanzee since these species diverged. The map is produced from more than one million accurately determined recombination events. We find that this new recombination map is intermediate to the maps of human and chimpanzee but that the recombination landscape has evolved more rapidly in the human lineage than in the chimpanzee lineage. We use the map to show that recombination rate, through the effect of GC-biased gene conversion, is an even stronger determinant of base composition evolution than previously reported.

The influence of genomic context on mutation patterns in the human genome inferred from rare variants.

Understanding patterns of spontaneous mutations is of fundamental interest in studies of human genome evolution and genetic disease. Here, we used extremely rare variants in humans to model the molecular spectrum of single-nucleotide mutations. Compared to common variants in humans and human–chimpanzee fixed differences (substitutions), rare variants, on average, arose more recently in the human lineage and are less affected by the potentially confounding effects of natural selection, population demographic history, and biased gene conversion. We analyzed variants obtained from a population-based sequencing study of 202 genes in >14,000 individuals. We observed considerable variability in the per-gene mutation rate, which was correlated with local GC content, but not recombination rate. Using >20,000 variants with a derived allele frequency ≤10−4, we examined the effect of local GC content and recombination rate on individual variant subtypes and performed comparisons with common variants and substitutions. The influence of local GC content on rare variants differed from that on common variants or substitutions, and the differences varied by variant subtype. Furthermore, recombination rate and recombination hotspots have little effect on rare variants of any subtype, yet both have a relatively strong impact on multiple variant subtypes in common variants and substitutions. This observation is consistent with the effect of biased gene conversion or selection-dependent processes. Our results highlight the distinct biases inherent in the initial mutation patterns and subsequent evolutionary processes that affect segregating variants.