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Germline mutation rates in humans have been estimated for a variety of mutation types, including single-nucleotide and large structural variants. Here, we directly measure the germline retrotransposition rate for the three active retrotransposon elements: L1, Alu , and SVA. We used three tools for calling mobile element insertions (MEIs) (MELT, RUFUS, and TranSurVeyor) on blood-derived whole-genome sequence (WGS) data from 599 CEPH individuals, comprising 33 three-generation pedigrees. We identified 26 de novo MEIs in 437 births. The retrotransposition rate estimates for Alu elements, one in 40 births, is roughly half the rate estimated using phylogenetic analyses, a difference in magnitude similar to that observed for single-nucleotide variants. The L1 retrotransposition rate is one in 63 births and is within range of previous estimates (1:20-1:200 births). The SVA retrotransposition rate, one in 63 births, is much higher than the previous estimate of one in 900 births. Our large, three-generation pedigrees allowed us to assess parent-of-origin effects and the timing of insertion events in either gametogenesis or early embryonic development. We find a statistically significant paternal bias in Alu retrotransposition. Our study represents the first in-depth analysis of the rate and dynamics of human retrotransposition from WGS data in three-generation human pedigrees., (© 2019 Feusier et al.; Published by Cold Spring Harbor Laboratory Press.)

Alu retrotransposons are the most numerous and active mobile elements in humans, causing genetic disease and creating genomic diversity. Mobile element scanning (ME-Scan) enables comprehensive and affordable identification of mobile element insertions (MEI) using targeted high-throughput sequencing of multiplexed MEI junction libraries. In a single experiment, ME-Scan identifies nearly all AluYb8 and AluYb9 elements, with high sensitivity for both rare and common insertions, in 169 individuals of diverse ancestry. ME-Scan detects heterozygous insertions in single individuals with 91% sensitivity. Insertion presence or absence states determined by ME-Scan are 95% concordant with those determined by locus-specific PCR assays. By sampling diverse populations from Africa, South Asia, and Europe, we are able to identify 5799 Alu insertions, including 2524 novel ones, some of which occur in exons. Sub-Saharan populations and a Pygmy group in particular carry numerous intermediate-frequency Alu insertions that are absent in non-African groups. There is a significant dearth of exon-interrupting insertions among common Alu polymorphisms, but the density of singleton Alu insertions is constant across exonic and nonexonic regions. In one case, a validated novel singleton Alu interrupts a protein-coding exon of FAM187B. This implies that exonic Alu insertions are generally deleterious and thus eliminated by natural selection, but not so quickly that they cannot be observed as extremely rare variants.

VAAST (the Variant Annotation, Analysis & Search Tool) is a probabilistic search tool for identifying damaged genes and their disease-causing variants in personal genome sequences. VAAST builds on existing amino acid substitution (AAS) and aggregative approaches to variant prioritization, combining elements of both into a single unified likelihood framework that allows users to identify damaged genes and deleterious variants with greater accuracy, and in an easy-to-use fashion. VAAST can score both coding and noncoding variants, evaluating the cumulative impact of both types of variants simultaneously. VAAST can identify rare variants causing rare genetic diseases, and it can also use both rare and common variants to identify genes responsible for common diseases. VAAST thus has a much greater scope of use than any existing methodology. Here we demonstrate its ability to identify damaged genes using small cohorts (n = 3) of unrelated individuals, wherein no two share the same deleterious variants, and for common, multigenic diseases using as few as 150 cases.

Accurate estimation of recent shared ancestry is important for genetics, evolution, medicine, conservation biology, and forensics. Established methods estimate kinship accurately for first-degree through third-degree relatives. We demonstrate that chromosomal segments shared by two individuals due to identity by descent (IBD) provide much additional information about shared ancestry. We developed a maximum-likelihood method for the estimation of recent shared ancestry (ERSA) from the number and lengths of IBD segments derived from high-density SNP or whole-genome sequence data. We used ERSA to estimate relationships from SNP genotypes in 169 individuals from three large, well-defined human pedigrees. ERSA is accurate to within one degree of relationship for 97% of first-degree through fifth-degree relatives and 80% of sixth-degree and seventh-degree relatives. We demonstrate that ERSA's statistical power approaches the maximum theoretical limit imposed by the fact that distant relatives frequently share no DNA through a common ancestor. ERSA greatly expands the range of relationships that can be estimated from genetic data and is implemented in a freely available software package.

Structural variants (SVs) are common in the human genome. Because approximately half of the human genome consists of repetitive, transposable DNA sequences, it is plausible that these elements play an important role in generating SVs in humans. Sequencing of the diploid genome of one individual human (HuRef) affords us the opportunity to assess, for the first time, the impact of mobile elements on SVs in an individual in a thorough and unbiased fashion. In this study, we systematically evaluated more than 8000 SVs to identify mobile element-associated SVs as small as 100 bp and specific to the HuRef genome. Combining computational and experimental analyses, we identified and validated 706 mobile element insertion events (including Alu, L1, SVA elements, and nonclassical insertions), which added more than 305 kb of new DNA sequence to the HuRef genome compared with the Human Genome Project (HGP) reference sequence (hg18). We also identified 140 mobile element-associated deletions, which removed approximately 126 kb of sequence from the HuRef genome. Overall, approximately 10% of the HuRef-specific indels larger than 100 bp are caused by mobile element-associated events. More than one-third of the insertion/deletion events occurred in genic regions, and new Alu insertions occurred in exons of three human genes. Based on the number of insertions and the estimated time to the most recent common ancestor of HuRef and the HGP reference genome, we estimated the Alu, L1, and SVA retrotransposition rates to be one in 21 births, 212 births, and 916 births, respectively. This study presents the first comprehensive analysis of mobile element-related structural variants in the complete DNA sequence of an individual and demonstrates that mobile elements play an important role in generating inter-individual structural variation.

We report an analysis of more than 240,000 loci genotyped using the Affymetrix SNP microarray in 554 individuals from 27 worldwide populations in Africa, Asia, and Europe. To provide a more extensive and complete sampling of human genetic variation, we have included caste and tribal samples from two states in South India, Daghestanis from eastern Europe, and the Iban from Malaysia. Consistent with observations made by Charles Darwin, our results highlight shared variation among human populations and demonstrate that much genetic variation is geographically continuous. At the same time, principal components analyses reveal discernible genetic differentiation among almost all identified populations in our sample, and in most cases, individuals can be clearly assigned to defined populations on the basis of SNP genotypes. All individuals are accurately classified into continental groups using a model-based clustering algorithm, but between closely related populations, genetic and self-classifications conflict for some individuals. The 250K data permitted high-level resolution of genetic variation among Indian caste and tribal populations and between highland and lowland Daghestani populations. In particular, upper-caste individuals from Tamil Nadu and Andhra Pradesh form one defined group, lower-caste individuals from these two states form another, and the tribal Irula samples form a third. Our results emphasize the correlation of genetic and geographic distances and highlight other elements, including social factors that have contributed to population structure.

We examine the distribution and structure of human genetic diversity for 710 individuals representing 31 populations from Africa, East Asia, Europe, and India using 100 Alu insertion polymorphisms from all 22 autosomes. Alu diversity is highest in Africans (0.349) and lowest in Europeans (0.297). Alu insertion frequency is lowest in Africans (0.463) and higher in Indians (0.544), E. Asians (0.557), and Europeans (0.559). Large genetic distances are observed among African populations and between African and non-African populations. The root of a neighbor-joining network is located closest to the African populations. These findings are consistent with an African origin of modern humans and with a bottleneck effect in the human populations that left Africa to colonize the rest of the world. Genetic distances among all pairs of populations show a significant product-moment correlation with geographic distances (r = 0.69, P < 0.00001). F(ST), the proportion of genetic diversity attributable to population subdivision is 0.141 for Africans/E. Asians/Europeans, 0.047 for E. Asians/Indians/Europeans, and 0.090 for all 31 populations. Resampling analyses show that approximately 50 Alu polymorphisms are sufficient to obtain accurate and reliable genetic distance estimates. These analyses also demonstrate that markers with higher F(ST) values have greater resolving power and produce more consistent genetic distance estimates.

The origins and affinities of the approximately 1 billion people living on the subcontinent of India have long been contested. This is owing, in part, to the many different waves of immigrants that have influenced the genetic structure of India. In the most recent of these waves, Indo-European-speaking people from West Eurasia entered India from the Northwest and diffused throughout the subcontinent. They purportedly admixed with or displaced indigenous Dravidic-speaking populations. Subsequently they may have established the Hindu caste system and placed themselves primarily in castes of higher rank. To explore the impact of West Eurasians on contemporary Indian caste populations, we compared mtDNA (400 bp of hypervariable region 1 and 14 restriction site polymorphisms) and Y-chromosome (20 biallelic polymorphisms and 5 short tandem repeats) variation in approximately 265 males from eight castes of different rank to approximately 750 Africans, Asians, Europeans, and other Indians. For maternally inherited mtDNA, each caste is most similar to Asians. However, 20%-30% of Indian mtDNA haplotypes belong to West Eurasian haplogroups, and the frequency of these haplotypes is proportional to caste rank, the highest frequency of West Eurasian haplotypes being found in the upper castes. In contrast, for paternally inherited Y-chromosome variation each caste is more similar to Europeans than to Asians. Moreover, the affinity to Europeans is proportionate to caste rank, the upper castes being most similar to Europeans, particularly East Europeans. These findings are consistent with greater West Eurasian male admixture with castes of higher rank. Nevertheless, the mitochondrial genome and the Y chromosome each represents only a single haploid locus and is more susceptible to large stochastic variation, bottlenecks, and selective sweeps. Thus, to increase the power of our analysis, we assayed 40 independent, biparentally inherited autosomal loci (1 LINE-1 and 39 Alu elements) in all of the caste and continental populations (approximately 600 individuals). Analysis of these data demonstrated that the upper castes have a higher affinity to Europeans than to Asians, and the upper castes are significantly more similar to Europeans than are the lower castes. Collectively, all five datasets show a trend toward upper castes being more similar to Europeans, whereas lower castes are more similar to Asians. We conclude that Indian castes are most likely to be of proto-Asian origin with West Eurasian admixture resulting in rank-related and sex-specific differences in the genetic affinities of castes to Asians and Europeans.