Integrating Human Population Genetics And Genomics To Elucidate The Etiology Of Brain Disorders

Brain disorders present a significant burden on affected individuals, their families and society at large. Existing diagnostic tests suffer from a lack of genetic biomarkers, particularly for substance use disorders, such as alcohol dependence (AD). Numerous studies have demonstrated that AD has a genetic heritability of 40-60%. The existing genetics literature of AD has primarily focused on linkage analyses in small family cohorts and more recently on genome-wide association analyses (GWAS) in large case-control cohorts, fueled by rapid advances in next generation sequencing (NGS). Numerous AD-associated genomic variations are present at a common frequency in the general population, making these variants of public health significance. However, known AD-associated variants explain only a fraction of the expected heritability. In this dissertation, we demonstrate that systems biology applications that integrate evolutionary genomics, rare variants and structural variation can dissect the genetic architecture of AD and elucidate its heritability. We identified several complex human diseases, including AD and other brain disorders, as potential targets of natural selection forces in diverse world populations. Further evidence of natural selection forces affecting AD was revealed when we identified an association between eye color, a trait under strong selection, and AD. These findings provide strong support for conducting GWAS on brain disorder phenotypes. However, with the ever-increasing abundance of rare genomic variants and large cohorts of multi-ethnic samples, population stratification becomes a serious confounding factor for GWAS. To address this problem, we designed a novel approach to identify ancestry informative single nucleotide polymorphisms (SNPs) for population stratification adjustment in association analyses. Furthermore, to leverage untyped variants from genotyping arrays – particularly rare variants – for GWAS and meta-analysis through rapid imputation, we designed a tool that converts genotype definitions across various array platforms. To further elucidate the genetic heritability of brain disorders, we designed approaches aimed at identifying Copy Number Variations (CNVs) and viral insertions into the human genome. We conducted the first CNV-based whole genome meta-analysis for AD. We also designed an integrated approach to estimate the sensitivity of NGS-based methods of viral insertion detection. For the first time in the literature, we identified herpesvirus in NGS data from an Alzheimer’s disease brain sample. The work in this dissertation represents a three-faceted advance in our understanding of brain disease etiology: 1) evolutionary genomic insights, 2) novel resources and tools to leverage rare variants, and 3) the discovery of disease-associated structural genomic aberrations. Our findings have broad implications on the genetics of complex human disease and hold promise for delivering clinically useful knowledge and resources

Improved assembly and variant detection of a haploid human genome using single-molecule, high-fidelity long reads

The sequence and assembly of human genomes using long-read sequencing technologies has revolutionized our understanding of structural variation and genome organization. We compared the accuracy, continuity, and gene annotation of genome assemblies generated from either high-fidelity (HiFi) or continuous long-read (CLR) datasets from the same complete hydatidiform mole human genome. We find that the HiFi sequence data assemble an additional 10% of duplicated regions and more accurately represent the structure of tandem repeats, as validated with orthogonal analyses. As a result, an additional 5 Mbp of pericentromeric sequences are recovered in the HiFi assembly, resulting in a 2.5-fold increase in the NG50 within 1 Mbp of the centromere (HiFi 480.6 kbp, CLR 191.5 kbp). Additionally, the HiFi genome assembly was generated in significantly less time with fewer computational resources than the CLR assembly. Although the HiFi assembly has significantly improved continuity and accuracy in many complex regions of the genome, it still falls short of the assembly of centromeric DNA and the largest regions of segmental duplication using existing assemblers. Despite these shortcomings, our results suggest that HiFi may be the most effective standalone technology for de novo assembly of human genomes

An evolutionary driver of interspersed segmental duplications in primates

Background The complex interspersed pattern of segmental duplications in humans is responsible for rearrangements associated with neurodevelopmental disease, including the emergence of novel genes important in human brain evolution. We investigate the evolution of LCR16a, a putative driver of this phenomenon that encodes one of the most rapidly evolving human–ape gene families, nuclear pore interacting protein (NPIP). Results Comparative analysis shows that LCR16a has independently expanded in five primate lineages over the last 35 million years of primate evolution. The expansions are associated with independent lineage-specific segmental duplications flanking LCR16a leading to the emergence of large interspersed duplication blocks at non-orthologous chromosomal locations in each primate lineage. The intron-exon structure of the NPIP gene family has changed dramatically throughout primate evolution with different branches showing characteristic gene models yet maintaining an open reading frame. In the African ape lineage, we detect signatures of positive selection that occurred after a transition to more ubiquitous expression among great ape tissues when compared to Old World and New World monkeys. Mouse transgenic experiments from baboon and human genomic loci confirm these expression differences and suggest that the broader ape expression pattern arose due to mutational changes that emerged in cis. Conclusions LCR16a promotes serial interspersed duplications and creates hotspots of genomic instability that appear to be an ancient property of primate genomes. Dramatic changes to NPIP gene structure and altered tissue expression preceded major bouts of positive selection in the African ape lineage, suggestive of a gene undergoing strong adaptive evolution

A high-quality bonobo genome refines the analysis of hominid evolution

The divergence of chimpanzee and bonobo provides one of the few examples of recent hominid speciation1,2. Here we describe a fully annotated, high-quality bonobo genome assembly, which was constructed without guidance from reference genomes by applying a multiplatform genomics approach. We generate a bonobo genome assembly in which more than 98% of genes are completely annotated and 99% of the gaps are closed, including the resolution of about half of the segmental duplications and almost all of the full-length mobile elements. We compare the bonobo genome to those of other great apes1,3,4,5 and identify more than 5,569 fixed structural variants that specifically distinguish the bonobo and chimpanzee lineages. We focus on genes that have been lost, changed in structure or expanded in the last few million years of bonobo evolution. We produce a high-resolution map of incomplete lineage sorting and estimate that around 5.1% of the human genome is genetically closer to chimpanzee or bonobo and that more than 36.5% of the genome shows incomplete lineage sorting if we consider a deeper phylogeny including gorilla and orangutan. We also show that 26% of the segments of incomplete lineage sorting between human and chimpanzee or human and bonobo are non-randomly distributed and that genes within these clustered segments show significant excess of amino acid replacement compared to the rest of the genome

Fully phased human genome assembly without parental data using single-cell strand sequencing and long reads

Human genomes are typically assembled as consensus sequences that lack information on parental haplotypes. Here we describe a reference-free workflow for diploid de novo genome assembly that combines the chromosome-wide phasing and scaffolding capabilities of single-cell strand sequencing with continuous long-read or high-fidelity sequencing data. Employing this strategy, we produced a completely phased de novo genome assembly for each haplotype of an individual of Puerto Rican descent (HG00733) in the absence of parental data. The assemblies are accurate (quality value > 40) and highly contiguous (contig N50 > 23 Mbp) with low switch error rates (0.17%), providing fully phased single-nucleotide variants, indels and structural variants. A comparison of Oxford Nanopore Technologies and Pacific Biosciences phased assemblies identified 154 regions that are preferential sites of contig breaks, irrespective of sequencing technology or phasing algorithms

GACT: a Genome build and Allele definition Conversion Tool for SNP imputation and meta-analysis in genetic association studies GACT: a Genome build and Allele definition Conversion Tool for SNP imputation and meta-analysis in genetic association studies

Abstract Background: Genome-wide association studies (GWAS) have successfully identified genes associated with complex human diseases. Although much of the heritability remains unexplained, combining single nucleotide polymorphism (SNP) genotypes from multiple studies for meta-analysis will increase the statistical power to identify new disease-associated variants. Meta-analysis requires same allele definition (nomenclature) and genome build among individual studies. Similarly, imputation, commonly-used prior to meta-analysis, requires the same consistency. However, the genotypes from various GWAS are generated using different genotyping platforms, arrays or SNP-calling approaches, resulting in use of different genome builds and allele definitions. Incorrect assumptions of identical allele definition among combined GWAS lead to a large portion of discarded genotypes or incorrect association findings. There is no published tool that predicts and converts among all major allele definitions. Results: In this study, we have developed a tool, GACT, which stands for Genome build and Allele definition Conversion Tool, that predicts and inter-converts between any of the common SNP allele definitions and between the major genome builds. In addition, we assessed several factors that may affect imputation quality, and our results indicated that inclusion of singletons in the reference had detrimental effects while ambiguous SNPs had no measurable effect. Unexpectedly, exclusion of genotypes with missing rate > 0.001 (40% of study SNPs) showed no significant decrease of imputation quality (even significantly higher when compared to the imputation with singletons in the reference), especially for rare SNPs

Characterization of Hepatitis B Virus Integrations Identified in Hepatocellular Carcinoma Genomes

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality. Almost half of HCC cases are associated with hepatitis B virus (HBV) infections, which often lead to HBV sequence integrations in the human genome. Accurate identification of HBV integration sites at a single nucleotide resolution is critical for developing a better understanding of the cancer genome landscape and of the disease itself. Here, we performed further analyses and characterization of HBV integrations identified by our recently reported VIcaller platform in recurrent or known HCC genes (such as TERT, MLL4, and CCNE1) as well as non-recurrent cancer-related genes (such as CSMD2, NKD2, and RHOU). Our pathway enrichment analysis revealed multiple pathways involving the alcohol dehydrogenase 4 gene, such as the metabolism pathways of retinol, tyrosine, and fatty acid. Further analysis of the HBV integration sites revealed distinct patterns involving the integration upper breakpoints, integrated genome lengths, and integration allele fractions between tumor and normal tissues. Our analysis also implies that the VIcaller method has diagnostic potential through discovering novel clonal integrations in cancer-related genes. In conclusion, although VIcaller is a hypothesis free virome-wide approach, it can still be applied to accurately identify genome-wide integration events of a specific candidate virus and their integration allele fractions

Characterization of Hepatitis B Virus Integrations Identified in Hepatocellular Carcinoma Genomes

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality. Almost half of HCC cases are associated with hepatitis B virus (HBV) infections, which often lead to HBV sequence integrations in the human genome. Accurate identification of HBV integration sites at a single nucleotide resolution is critical for developing a better understanding of the cancer genome landscape and of the disease itself. Here, we performed further analyses and characterization of HBV integrations identified by our recently reported VIcaller platform in recurrent or known HCC genes (such as TERT, MLL4, and CCNE1) as well as non-recurrent cancer-related genes (such as CSMD2, NKD2, and RHOU). Our pathway enrichment analysis revealed multiple pathways involving the alcohol dehydrogenase 4 gene, such as the metabolism pathways of retinol, tyrosine, and fatty acid. Further analysis of the HBV integration sites revealed distinct patterns involving the integration upper breakpoints, integrated genome lengths, and integration allele fractions between tumor and normal tissues. Our analysis also implies that the VIcaller method has diagnostic potential through discovering novel clonal integrations in cancer-related genes. In conclusion, although VIcaller is a hypothesis free virome-wide approach, it can still be applied to accurately identify genome-wide integration events of a specific candidate virus and their integration allele fractions

Recurrent de novo mutations in neurodevelopmental disorders: properties and clinical implications

Abstract Next-generation sequencing (NGS) is now more accessible to clinicians and researchers. As a result, our understanding of the genetics of neurodevelopmental disorders (NDDs) has rapidly advanced over the past few years. NGS has led to the discovery of new NDD genes with an excess of recurrent de novo mutations (DNMs) when compared to controls. Development of large-scale databases of normal and disease variation has given rise to metrics exploring the relative tolerance of individual genes to human mutation. Genetic etiology and diagnosis rates have improved, which have led to the discovery of new pathways and tissue types relevant to NDDs. In this review, we highlight several key findings based on the discovery of recurrent DNMs ranging from copy number variants to point mutations. We explore biases and patterns of DNM enrichment and the role of mosaicism and secondary mutations in variable expressivity. We discuss the benefit of whole-genome sequencing (WGS) over whole-exome sequencing (WES) to understand more complex, multifactorial cases of NDD and explain how this improved understanding aids diagnosis and management of these disorders. Comprehensive assessment of the DNM landscape across the genome using WGS and other technologies will lead to the development of novel functional and bioinformatics approaches to interpret DNMs and drive new insights into NDD biology

Human-specific tandem repeat expansion and differential gene expression during primate evolution

Short tandem repeats (STRs) and variable number tandem repeats (VNTRs) are important sources of natural and disease-causing variation, yet they have been problematic to resolve in reference genomes and genotype with short-read technology. We created a framework tomodel the evolution and instability of STRs and VNTRs in apes. We phased and assembled 3 ape genomes (chimpanzee, gorilla, and orangutan) using long-read and 10x Genomics linked-read sequence data for 21,442 human tandem repeats discovered in 6 haplotype-resolved assemblies of Yoruban, Chinese, and Puerto Rican origin. We define a set of 1,584 STRs/VNTRs expanded specifically in humans, including large tandem repeats affecting coding and noncoding portions of genes (e.g., MUC3A, CACNA1C). We show that short interspersed nuclear element-VNTR-Alu (SVA) retrotransposition is the main mechanism for distributing GC-rich human-specific tandem repeat expansions throughout the genome but with a bias against genes. In contrast, we observe that VNTRs not originating from retrotransposons have a propensity to cluster near genes, especially in the subtelomere. Using tissue-specific expression from human and chimpanzee brains, we identify genes where transcript isoform usage differs significantly, likely caused by cryptic splicing variation within VNTRs. Using single-cell expression from cerebral organoids, we observe a strong effect for genes associated with transcription profiles analogous to intermediate progenitor cells. Finally, we compare the sequence composition of some of the largest human-specific repeat expansions and identify 52 STRs/VNTRs with at least 40 uninterrupted pure tracts as candidates for genetically unstable regions associated with disease