| 1. |
- Chevy, Elizabeth T., et al.
(författare)
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Integrating sex-bias into studies of archaic introgression on chromosome X
- 2023
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Ingår i: PLOS Genetics. - 1553-7390 .- 1553-7404. ; 19:8
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Tidskriftsartikel (refereegranskat)abstract
- Evidence of interbreeding between archaic hominins and humans comes from methods thatinfer the locations of segments of archaic haplotypes, or ‘archaic coverage’ using thegenomes of people living today. As more estimates of archaic coverage have emerged, ithas become clear that most of this coverage is found on the autosomes— very little isretained on chromosome X. Here, we summarize published estimates of archaic coverageon autosomes and chromosome X from extant human samples. We find on average 7 timesmore archaic coverage on autosomes than chromosome X, and identify broad continentalpatterns in this ratio: greatest in European samples, and least in South Asian samples. Wealso perform extensive simulation studies to investigate how the amount of archaic cover-age, lengths of coverage, and rates of purging of archaic coverage are affected by sex-biascaused by an unequal sex ratio within the archaic introgressors. Our results generally con-firm that, with increasing male sex-bias, less archaic coverage is retained on chromosomeX. Ours is the first study to explicitly model such sex-bias and its potential role in creating thedearth of archaic coverage on chromosome X.
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| 2. |
- Lappalainen, Tuuli, et al.
(författare)
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Genetic and molecular architecture of complex traits
- 2024
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Ingår i: Cell. - : Elsevier BV. - 0092-8674 .- 1097-4172. ; 187:5, s. 1059-1075
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Forskningsöversikt (refereegranskat)abstract
- Human genetics has emerged as one of the most dynamic areas of biology, with a broadening societal impact. In this review, we discuss recent achievements, ongoing efforts, and future challenges in the field. Advances in technology, statistical methods, and the growing scale of research efforts have all provided many insights into the processes that have given rise to the current patterns of genetic variation. Vast maps of genetic associations with human traits and diseases have allowed characterization of their genetic architecture. Finally, studies of molecular and cellular effects of genetic variants have provided insights into biological processes underlying disease. Many outstanding questions remain, but the field is well poised for groundbreaking discoveries as it increases the use of genetic data to understand both the history of our species and its applications to improve human health.
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| 3. |
- Musharoff, Shaila, et al.
(författare)
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The inference of sex-biased human demography from whole-genome data
- 2019
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Ingår i: PLOS Genetics. - : Public Library of Science (PLoS). - 1553-7390 .- 1553-7404. ; 15:9
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Tidskriftsartikel (refereegranskat)abstract
- Sex-biased demographic events (“sex-bias”) involve unequal numbers of females and males. These events are typically inferred from the relative amount of X-chromosomal to autosomal genetic variation and have led to conflicting conclusions about human demographic history. Though population size changes alter the relative amount of X-chromosomal to autosomal genetic diversity even in the absence of sex-bias, this has generally not been accounted for in sex-bias estimators to date. Here, we present a novel method to identify sex-bias from genetic sequence data that models population size changes and estimates the female fraction of the effective population size during each time epoch. Compared to recent sex-bias inference methods, our approach can detect sex-bias that changes on a single population branch without requiring data from an outgroup or knowledge of divergence events. When applied to simulated data, conventional sex-bias estimators are biased by population size changes, especially recent growth or bottlenecks, while our estimator is unbiased. We next apply our method to high-coverage exome data from the 1000 Genomes Project and estimate a male bias in Yorubans (47% female) and Europeans (44%), possibly due to stronger background selection on the X chromosome than on the autosomes. Finally, we apply our method to the 1000 Genomes Project Phase 3 high-coverage Complete Genomics whole-genome data and estimate a female bias in Yorubans (63% female), Europeans (84%), Punjabis (82%), as well as Peruvians (56%), and a male bias in the Southern Han Chinese (45%). Our method additionally identifies a male-biased migration out of Africa based on data from Europeans (20% female). Our results demonstrate that modeling population size change is necessary to estimate sex-bias parameters accurately. Our approach gives insight into signatures of sex-bias in sexual species, and the demographic models it produces can serve as more accurate null models for tests of selection.
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| 4. |
- Ramachandran, Sohini, et al.
(författare)
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Detecting Shared Genetic Architecture Among Multiple Phenotypes by Hierarchical Clustering of Gene-Level Association Statistics
- 2020
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Ingår i: Genetics. - : Genetics. - 0016-6731 .- 1943-2631. ; 215:2, s. 511-529
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Tidskriftsartikel (refereegranskat)abstract
- Emerging large-scale biobanks pairing genotype data with phenotype data present new opportunities to prioritize shared genetic associations across multiple phenotypes for molecular validation. Past research, by our group and others, has shown gene-level tests of association produce biologically interpretable characterization of the genetic architecture of a given phenotype. Here, we present a new method, Ward clustering to identify Internal Node branch length outliers using Gene Scores (WINGS), for identifying shared genetic architecture among multiple phenotypes. The objective of WINGS is to identify groups of phenotypes, or “clusters,” sharing a core set of genes enriched for mutations in cases. We validate WINGS using extensive simulation studies and then combine gene-level association tests with WINGS to identify shared genetic architecture among 81 case-control and seven quantitative phenotypes in 349,468 European-ancestry individuals from the UK Biobank. We identify eight prioritized phenotype clusters and recover multiple published gene-level associations within prioritized clusters.
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| 5. |
- Ramachandran, Sohini, et al.
(författare)
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Estimation of non-null SNP effect size distributions enables the detection of enriched genes underlying complex traits
- 2020
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Ingår i: PLOS Genetics. - : Public Library of Science (PLoS). - 1553-7390 .- 1553-7404. ; 16:6
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Tidskriftsartikel (refereegranskat)abstract
- Traditional univariate genome-wide association studies generate false positives and nega-tives due to difficulties distinguishing associated variants from variants with spurious non-zero effects that do not directly influence the trait. Recent efforts have been directed atidentifying genes or signaling pathways enriched for mutations in quantitative traits or case-control studies, but these can be computationally costly and hampered by strict modelassumptions. Here, we present gene-ε, a new approach for identifying statistical associa-tions between sets of variants and quantitative traits. Our key insight is that enrichment stud-ies on the gene-level are improved when we reformulate the genome-wide SNP-level nullhypothesis to identify spurious small-to-intermediate SNP effects and classify them as non-causal. gene-ε efficiently identifies enriched genes under a variety of simulated geneticarchitectures, achieving greater than a 90% true positive rate at 1% false positive rate forpolygenic traits. Lastly, we apply gene-ε to summary statistics derived from six quantitativetraits using European-ancestry individuals in the UK Biobank, and identify enriched genesthat are in biologically relevant pathways.
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