Identification Of Rare Variant Effect In Complex Human Traits Using Whole Genome And Whole Exome Sequencing Data
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Identification of Rare-variant Effect in Complex Human Traits Using Whole-genome and Whole- Exome Sequencing Data
For recent advancements in sequencing technologies, genetic information can be obtained from a large population at a relatively low cost. This provides an unprecedented opportunity to understand the role of genetic variability in association with complex human traits. One common strategy is to conduct genome-wide association studies to identify loci significantly associated with phenotypes of interest. However, the findings are usually limited to common variants with small effect sizes. Collectively, these identified loci can not fully explain the observed heritability, which is a problem commonly referred to as "the missing heritability." To uncover this problem, human genetic research has shifted more focus to other types of genetic variations, including rare variants, which is further capacitated and facilitated by the next-generation sequencing technique. These rare mutations are believed to harbor large effect sizes and, therefore to be one of the major contributors to complex traits.Here, we describe our effort in analyzing the effect of rare variants in two complex human traits, Alzheimer's Disease and Tourette Syndrome, followed by conducting a genome-wide association study on human blood lipids. Exploring large whole-genome sequencing datasets, we have first demonstrated that rare variants were strongly associated with Alzheimer's Disease, neurofibrillary tangles, and age-related phenotypes within the endocytic pathway using a gene-set burden analysis framework. Subsequent gene-based analyses identified one AD-associated gene, ANKRD13D, and two e-Genes, HLA-A and SLC26A7. Leveraging bulk and scRNA-Seq data, we observed significant differential expression patterns in all three implicated genes. Secondly, we have explored a specific type of rare variants, de novo mutations, within Tourette Syndrome patients using a whole-exome sequencing trio dataset and identified a recurrent mutation in one gene, FBN2, previously implicated in TS. Comparing to the expected mutation rate, we demonstrated that the protein-truncating variants were enriched in probands. In addition, gene-set analysis displayed differential expression patterns across different tissue types and brain developmental stages. Lastly, we have performed a multi-population meta-analysis on blood lipid levels using electronic health records and genotyping information from the UCLA ATLAS database. We have observed genetic effects both specific to and shared across five different populations. Compared to previous large-scale GWASes, our results demonstrated consistent effect estimates while identifying one novel locus, rs72552763.
Assessing Rare Variation in Complex Traits
This book is unique in covering a wide range of design and analysis issues in genetic studies of rare variants, taking advantage of collaboration of the editors with many experts in the field through large-scale international consortia including the UK10K Project, GO-T2D and T2D-GENES. Chapters provide details of state-of-the-art methodology for rare variant detection and calling, imputation and analysis in samples of unrelated individuals and families. The book also covers analytical issues associated with the study of rare variants, such as the impact of fine-scale population structure, and with combining information on rare variants across studies in a meta-analysis framework. Genetic association studies have in the last few years substantially enhanced our understanding of factors underlying traits of high medical importance, such as body mass index, lipid levels, blood pressure and many others. There is growing empirical evidence that low-frequency and rare variants play an important role in complex human phenotypes. This book covers multiple aspects of study design, analysis and interpretation for complex trait studies focusing on rare sequence variation. In many areas of genomic research, including complex trait association studies, technology is in danger of outstripping our capacity to analyse and interpret the vast amounts of data generated. The field of statistical genetics in the whole-genome sequencing era is still in its infancy, but powerful methods to analyse the aggregation of low-frequency and rare variants are now starting to emerge. The chapter Functional Annotation of Rare Genetic Variants is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Genome Mapping and Genomics in Human and Non-Human Primates
This book provides an introduction to the latest gene mapping techniques and their applications in biomedical research and evolutionary biology. It especially highlights the advances made in large-scale genomic sequencing. Results of studies that illustrate how the new approaches have improved our understanding of the genetic basis of complex phenotypes including multifactorial diseases (e.g., cardiovascular disease, type 2 diabetes, and obesity), anatomic characteristics (e.g., the craniofacial complex), and neurological and behavioral phenotypes (e.g., human brain structure and nonhuman primate behavior) are presented. Topics covered include linkage and association methods, gene expression, copy number variation, next-generation sequencing, comparative genomics, population structure, and a discussion of the Human Genome Project. Further included are discussions of the use of statistical genetic and genetic epidemiologic techniques to decipher the genetic architecture of normal and disease-related complex phenotypes using data from both humans and non-human primates.