scholarly journals Systematic Analyses of Autosomal Recombination Rates from the 1000 Genomes Project Uncovers the Global Recombination Landscape in Humans

2018 ◽  
Author(s):  
Shivakumara Manu ◽  
Kshitish K Acharya ◽  
Saravanamuthu Thiyagarajan
Keyword(s):  
Meiotic Recombination ◽  
Genetic Maps ◽  
Human Populations ◽  
1000 Genomes Project ◽  
Recombination Rates ◽  
1000 Genomes ◽  
Genome Wide ◽  
Shared Ancestry ◽  
Genomic Locations ◽  
First Time

ABSTRACTBackgroundMeiotic recombination plays an important role in evolution by shuffling different alleles along the chromosomes, thus generating the genetic diversity across generations that is vital for adaptation. The plasticity of recombination rates and presence of hotspots of recombination along the genome has attracted much attention over two decades due to their contribution to the evolution of the genome. Yet, the variation in genome-wide recombination landscape and the differences in the location and strength of hotspots across worldwide human populations remains little explored.ResultsWe make use of the untapped linkage disequilibrium (LD) based genetic maps from the 1000 Genomes Project (1KGP) to perform in-depth analyses of finescale variation in the autosomal recombination rates across 20 human populations to uncover the global recombination landscape. We have generated a detailed map of human recombination landscape comprising of a comprehensive set of 88,841 putative hotspots and 80,129 coldspots with their respective strengths across populations, about 2/3rd of which were previously unknown. We have validated and assessed the number of historical putative hotspots derived from the patterns of LD that are currently active in the contemporary populations using a recently published high-resolution pedigree-based genetic map, constructed and refined using 3.38 million crossovers from various populations. For the first time, we provide statistics regarding the conserved, shared, and unique hotspots across all the populations studied.ConclusionsOur analysis yields clusters of continental groups, reflecting their shared ancestry and genetic similarities in the recombination rates that are linked to the migratory and evolutionary histories of the populations. We provide the genomic locations and strengths of hotspots and coldspots across all the populations studied which are a valuable set of resources arising out our analyses of 1KGP data. The findings are of great importance for further research on human hotspots as we approach the dusk of retiring HapMap-based resources.

scholarly journals A method for genome-wide genealogy estimation for thousands of samples

2019 ◽  
Author(s):  
Leo Speidel ◽  
Marie Forest ◽  
Sinan Shi ◽  
Simon R. Myers
Keyword(s):  
Blood Pressure ◽  
Human Populations ◽  
1000 Genomes Project ◽  
Hair Colour ◽  
Strong Positive Selection ◽  
Data Errors ◽  
1000 Genomes ◽  
Genome Wide ◽  
Branch Lengths ◽  
Population Sizes

AbstractKnowledge of genome-wide genealogies for thousands of individuals would simplify most evolutionary analyses for humans and other species, but has remained computationally infeasible. We developed a method, Relate, scaling to > 10,000 sequences while simultaneously estimating branch lengths, mutational ages, and variable historical population sizes, as well as allowing for data errors. Application to 1000 Genomes Project haplotypes produces joint genealogical histories for 26 human populations. Highly diverged lineages are present in all groups, but most frequent in Africa. Outside Africa, these mainly reflect ancient introgression from groups related to Neanderthals and Denisovans, while African signals instead reflect unknown events, unique to that continent. Our approach allows more powerful inferences of natural selection than previously possible. We identify multiple novel regions under strong positive selection, and multi-allelic traits including hair colour, BMI, and blood pressure, showing strong evidence of directional selection, varying among human groups.

scholarly journals Genome-Wide Analysis of Wild-Type Epstein–Barr Virus Genomes Derived from Healthy Individuals of the 1000 Genomes Project

2014 ◽  
Vol 6 (4) ◽  
pp. 846-860 ◽  
Author(s):  
Gabriel Santpere ◽  
Fleur Darre ◽  
Soledad Blanco ◽  
Antonio Alcami ◽  
Pablo Villoslada ◽  
...  
Keyword(s):  
Epstein Barr Virus ◽  
Healthy Individuals ◽  
Wild Type ◽  
1000 Genomes Project ◽  
Genome Wide Analysis ◽  
Barr Virus ◽  
1000 Genomes ◽  
Genome Wide ◽  
Epstein Barr ◽  
Virus Genomes

scholarly journals Legacy Data Confound Genomics Studies

2019 ◽  
Vol 37 (1) ◽  
pp. 2-10 ◽  
Author(s):  
Luke Anderson-Trocmé ◽  
Rick Farouni ◽  
Mathieu Bourgey ◽  
Yoichiro Kamatani ◽  
Koichiro Higasa ◽  
...  
Keyword(s):  
Population Stratification ◽  
Quality Data ◽  
Human Populations ◽  
Batch Effects ◽  
Sequencing Data ◽  
1000 Genomes Project ◽  
Mutational Spectra ◽  
1000 Genomes ◽  
Legacy Data ◽  
Early Phases

Abstract Recent reports have identified differences in the mutational spectra across human populations. Although some of these reports have been replicated in other cohorts, most have been reported only in the 1000 Genomes Project (1kGP) data. While investigating an intriguing putative population stratification within the Japanese population, we identified a previously unreported batch effect leading to spurious mutation calls in the 1kGP data and to the apparent population stratification. Because the 1kGP data are used extensively, we find that the batch effects also lead to incorrect imputation by leading imputation servers and a small number of suspicious GWAS associations. Lower quality data from the early phases of the 1kGP thus continue to contaminate modern studies in hidden ways. It may be time to retire or upgrade such legacy sequencing data.

scholarly journals Variation in recombination rate and its genetic determinism in sheep (Ovis Aries) populations from combining multiple genome-wide datasets

2017 ◽  
Author(s):  
Morgane Petit ◽  
Jean-Michel Astruc ◽  
Julien Sarry ◽  
Laurence Drouilhet ◽  
Stéphane Fabre ◽  
...  
Keyword(s):  
Meiotic Recombination ◽  
Individual Variation ◽  
Recombination Rate ◽  
Snp Array ◽  
Genetic Determinism ◽  
Ovis Aries ◽  
Domestic Sheep ◽  
Recombination Rates ◽  
Male Recombination ◽  
Genome Wide

AbstractRecombination is a complex biological process that results from a cascade of multiple events during meiosis. Understanding the genetic determinism of recombination can help to understand if and how these events are interacting. To tackle this question, we studied the patterns of recombination in sheep, using multiple approaches and datasets. We constructed male recombination maps in a dairy breed from the south of France (the Lacaune breed) at a fine scale by combining meiotic recombination rates from a large pedigree genotyped with a 50K SNP array and historical recombination rates from a sample of unrelated individuals genotyped with a 600K SNP array. This analysis revealed recombination patterns in sheep similar to other mammals but also genome regions that have likely been affected by directional and diversifying selection. We estimated the average recombination rate of Lacaune sheep at 1.5 cM/Mb, identified about 50,000 crossover hotspots on the genome and found a high correlation between historical and meiotic recombination rate estimates. A genome-wide association study revealed two major loci affecting inter-individual variation in recombination rate in Lacaune, including the RNF212 and HEI10 genes and possibly 2 other loci of smaller effects including the KCNJ15 and FSHR genes. Finally, we compared our results to those obtained previously in a distantly related population of domestic sheep, the Soay. This comparison revealed that Soay and Lacaune males have a very similar distribution of recombination along the genome and that the two datasets can be combined to create more precise male meiotic recombination maps in sheep. Despite their similar recombination maps, we show that Soay and Lacaune males exhibit different heritabilities and QTL effects for inter-individual variation in genome-wide recombination rates.

scholarly journals Legacy Data Confounds Genomics Studies

2019 ◽  
Author(s):  
Luke Anderson-Trocmé ◽  
Rick Farouni ◽  
Mathieu Bourgey ◽  
Yoichiro Kamatani ◽  
Koichiro Higasa ◽  
...  
Keyword(s):  
Population Stratification ◽  
Quality Data ◽  
Human Populations ◽  
Batch Effects ◽  
Sequencing Data ◽  
1000 Genomes Project ◽  
Mutational Spectra ◽  
1000 Genomes ◽  
Legacy Data ◽  
Early Phases

AbstractRecent reports have identified differences in the mutational spectra across human populations. While some of these reports have been replicated in other cohorts, most have been reported only in the 1000 Genomes Project (1kGP) data. While investigating an intriguing putative population stratification within the Japanese population, we identified a previously unreported batch effect leading to spurious mutation calls in the 1kGP data and to the apparent population stratification. Because the 1kGP data is used extensively, we find that the batch effects also lead to incorrect imputation by leading imputation servers and a small number of suspicious GWAS associations. Lower-quality data from the early phases of the 1kGP thus continues to contaminate modern studies in hidden ways. It may be time to retire or upgrade such legacy sequencing data.

scholarly journals Genome-wide recombination map construction from single individuals using linked-read sequencing

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Andreea Dréau ◽  
Vrinda Venu ◽  
Elena Avdievich ◽  
Ludmila Gaspar ◽  
Felicity C. Jones
Keyword(s):  
Meiotic Recombination ◽  
Molecular Basis ◽  
Low Cost ◽  
Single Individual ◽  
Recombination Rates ◽  
Recombination Hotspots ◽  
Map Construction ◽  
Genome Wide ◽  
Genomic Location ◽  
Exciting Opportunity

Abstract Meiotic recombination rates vary across the genome, often involving localized crossover hotspots and coldspots. Studying the molecular basis and mechanisms underlying this variation has been challenging due to the high cost and effort required to construct individualized genome-wide maps of recombination crossovers. Here we introduce a new method, called ReMIX, to detect crossovers from gamete DNA of a single individual using Illumina sequencing of 10X Genomics linked-read libraries. ReMIX reconstructs haplotypes and identifies the valuable rare molecules spanning crossover breakpoints, allowing quantification of the genomic location and intensity of meiotic recombination. Using a single mouse and stickleback fish, we demonstrate how ReMIX faithfully recovers recombination hotspots and landscapes that have previously been built using hundreds of offspring. ReMIX provides a high-resolution, high-throughput, and low-cost approach to quantify recombination variation across the genome, providing an exciting opportunity to study recombination among multiple individuals in diverse organisms.

scholarly journals A High-Resolution Genetic Map for the Laboratory Rat

2018 ◽  
Author(s):  
John Littrell ◽  
Shirng-Wern Tsaih ◽  
Amelie Baud ◽  
Pasi Rastas ◽  
Leah Solberg-Woods ◽  
...  
Keyword(s):  
High Resolution ◽  
Genetic Markers ◽  
Genetic Map ◽  
Complex Traits ◽  
Substantial Improvement ◽  
Genetic Maps ◽  
Female Rats ◽  
Recombination Rates ◽  
Male And Female Rats ◽  
First Time

ABSTRACTAn accurate and high-resolution genetic map is critical for mapping complex traits, yet the resolution of the current rat genetic map is far lower than human and mouse, and has not been updated since the original ensen-Seaman map in 2004. For the first time, we have refined the rat genetic map to sub-centimorgan (cM) r solution (<0.02 cM) by using 95,769 genetic markers and 870 informative meioses from a cohort of 528 heterogeneous stock (HS) rats. Global recombination rates in the revised sex-averaged map (0.66 cM/Mb) did not difeer compared to the historical map (0.65 cM/Mb); however, substantial refinement was made to the localization of highly recombinant regions within the revised map. Also for the first time, sex-specific rat genetic maps were generated, which revealed both genomewide and fine-scale variation in recombination rates between male and female rats. Reanalysis of multiple quantitative trait loci (QTL) using the historical and refined rat genetic maps demonstrated marked changes to QTL localization, shape, and effect size. As a resource to the rat research community, we have provided revised centimorgan positions for all physical positions within the rat genome and commonly used genetic markers for trait mapping, including 44,828 SSLP markers and the RATDIV genotyping array. Collectively, this study provides a substantial improvement to the rat genetic map and an unprecedented resource for analysis of complex traits and recombination in the rat.

scholarly journals Genetically regulated expression underlies cellular sensitivity to chemotherapy in diverse populations

2021 ◽  
Author(s):  
Ashley J Mulford ◽  
Claudia Wing ◽  
M Eileen Dolan ◽  
Heather E Wheeler
Keyword(s):  
Genetic Factors ◽  
Association Studies ◽  
Cancer Cell Line ◽  
Chemotherapeutic Agents ◽  
Lung Cancer Cell Line ◽  
1000 Genomes Project ◽  
Functional Studies ◽  
Chemotherapy Drugs ◽  
1000 Genomes ◽  
Genome Wide

Abstract Most cancer chemotherapeutic agents are ineffective in a subset of patients, thus it is important to consider the role of genetic variation in drug response. Lymphoblastoid cell lines (LCLs) in 1000 Genomes Project populations of diverse ancestries are a useful model for determining how genetic factors impact variation in cytotoxicity. In our study, LCLs from three 1000 Genomes Project populations of diverse ancestries were previously treated with increasing concentrations of eight chemotherapeutic drugs and cell growth inhibition was measured at each dose with half-maximal inhibitory concentration (IC50) or area under the dose–response curve (AUC) as our phenotype for each drug. We conducted both genome-wide (GWAS) and transcriptome-wide association studies (TWAS) within and across ancestral populations. We identified four unique loci in GWAS and three genes in TWAS significantly associated with chemotherapy-induced cytotoxicity within and across ancestral populations. For etoposide, increased STARD5 predicted expression associated with decreased etoposide IC50 (p = 8.5 x 10−8). Functional studies in A549, a lung cancer cell line, revealed that knockdown of STARD5 expression resulted in decreased sensitivity to etoposide following exposure for 72 (p = 0.033) and 96 hours (p = 0.0001). By identifying loci and genes associated with cytotoxicity across ancestral populations, we strive to understand the genetic factors impacting the effectiveness of chemotherapy drugs and to contribute to the development of future cancer treatment.

scholarly journals The Simons Genome Diversity Project: A Global Analysis of Mobile Element Diversity

2020 ◽  
Vol 12 (6) ◽  
pp. 779-794 ◽  
Author(s):  
W Scott Watkins ◽  
Julie E Feusier ◽  
Jainy Thomas ◽  
Clement Goubert ◽  
Swapon Mallick ◽  
...  
Keyword(s):  
Native American ◽  
Global Analysis ◽  
General Pattern ◽  
Mobile Element ◽  
Human Populations ◽  
Single Individual ◽  
Genome Diversity ◽  
1000 Genomes Project ◽  
Alu Elements ◽  
1000 Genomes

Abstract Ongoing retrotransposition of Alu, LINE-1, and SINE–VNTR–Alu elements generates diversity and variation among human populations. Previous analyses investigating the population genetics of mobile element insertions (MEIs) have been limited by population ascertainment bias or by relatively small numbers of populations and low sequencing coverage. Here, we use 296 individuals representing 142 global populations from the Simons Genome Diversity Project (SGDP) to discover and characterize MEI diversity from deeply sequenced whole-genome data. We report 5,742 MEIs not originally reported by the 1000 Genomes Project and show that high sampling diversity leads to a 4- to 7-fold increase in MEI discovery rates over the original 1000 Genomes Project data. As a result of negative selection, nonreference polymorphic MEIs are underrepresented within genes, and MEIs within genes are often found in the transcriptional orientation opposite that of the gene. Globally, 80% of Alu subfamilies predate the expansion of modern humans from Africa. Polymorphic MEIs show heterozygosity gradients that decrease from Africa to Eurasia to the Americas, and the number of MEIs found uniquely in a single individual are also distributed in this general pattern. The maximum fraction of MEI diversity partitioned among the seven major SGDP population groups (FST) is 7.4%, similar to, but slightly lower than, previous estimates and likely attributable to the diverse sampling strategy of the SGDP. Finally, we utilize these MEIs to extrapolate the primary Native American shared ancestry component to back to Asia and provide new evidence from genome-wide identical-by-descent genetic markers that add additional support for a southeastern Siberian origin for most Native Americans.

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