Demographic history and patterns of molecular evolution from whole genome sequencing in the radiation of Galapagos giant tortoises

2021 ◽  
Author(s):  
Evelyn L. Jensen ◽  
Stephen J. Gaughran ◽  
Ryan C. Garrick ◽  
Michael A. Russello ◽  
Adalgisa Caccone
Keyword(s):  
Molecular Evolution ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Demographic History ◽  
Whole Genome

scholarly journals Insights into platypus population structure and history from whole-genome sequencing

2017 ◽  
Author(s):  
Hilary C. Martin ◽  
Elizabeth M. Batty ◽  
Julie Hussin ◽  
Portia Westall ◽  
Tasman Daish ◽  
...  
Keyword(s):  
Population Structure ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
De Novo ◽  
Demographic History ◽  
Population Decline ◽  
Egg Laying ◽  
Whole Genome ◽  
Data Set ◽  
Important Species

AbstractThe platypus is an egg-laying mammal which, alongside the echidna, occupies a unique place in the mammalian phylogenetic tree. Despite widespread interest in its unusual biology, little is known about its population structure or recent evolutionary history. To provide new insights into the dispersal and demographic history of this iconic species, we sequenced the genomes of 57 platypuses from across the whole species range in eastern mainland Australia and Tasmania. Using a highly-improved reference genome, we called over 6.7M SNPs, providing an informative genetic data set for population analyses. Our results show very strong population structure in the platypus, with our sampling locations corresponding to discrete groupings between which there is no evidence for recent gene flow. Genome-wide data allowed us to establish that 28 of the 57 sampled individuals had at least a third-degree relative amongst other samples from the same river, often taken at different times. Taking advantage of a sampled family quartet, we estimated the de novo mutation rate in the platypus at 7.0×10−9/bp/generation (95% CI 4.1×10−9 − 1.2×10−8/bp/generation). We estimated effective population sizes of ancestral populations and haplotype sharing between current groupings, and found evidence for bottlenecks and long-term population decline in multiple regions, and early divergence between populations in different regions. This study demonstrates the power of whole-genome sequencing for studying natural populations of an evolutionarily important species.

scholarly journals Comparison of Genotype Imputation for SNP Array and Low-Coverage Whole-Genome Sequencing Data

2022 ◽  
Vol 12 ◽  
Author(s):  
Tianyu Deng ◽  
Pengfei Zhang ◽  
Dorian Garrick ◽  
Huijiang Gao ◽  
Lixian Wang ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Demographic History ◽  
Imputation Accuracy ◽  
Reference Population ◽  
Genotype Imputation ◽  
Whole Genome ◽  
Snp Chip ◽  
A Genome ◽  
Low Coverage

Genotype imputation is the term used to describe the process of inferring unobserved genotypes in a sample of individuals. It is a key step prior to a genome-wide association study (GWAS) or genomic prediction. The imputation accuracy will directly influence the results from subsequent analyses. In this simulation-based study, we investigate the accuracy of genotype imputation in relation to some factors characterizing SNP chip or low-coverage whole-genome sequencing (LCWGS) data. The factors included the imputation reference population size, the proportion of target markers /SNP density, the genetic relationship (distance) between the target population and the reference population, and the imputation method. Simulations of genotypes were based on coalescence theory accounting for the demographic history of pigs. A population of simulated founders diverged to produce four separate but related populations of descendants. The genomic data of 20,000 individuals were simulated for a 10-Mb chromosome fragment. Our results showed that the proportion of target markers or SNP density was the most critical factor affecting imputation accuracy under all imputation situations. Compared with Minimac4, Beagle5.1 reproduced higher-accuracy imputed data in most cases, more notably when imputing from the LCWGS data. Compared with SNP chip data, LCWGS provided more accurate genotype imputation. Our findings provided a relatively comprehensive insight into the accuracy of genotype imputation in a realistic population of domestic animals.

scholarly journals Demographic history and biologically relevant genetic variation of Native Mexicans inferred from whole-genome sequencing

2017 ◽  
Vol 8 (1) ◽  
Author(s):  
Sandra Romero-Hidalgo ◽  
Adrián Ochoa-Leyva ◽  
Alejandro Garcíarrubio ◽  
Victor Acuña-Alonzo ◽  
Erika Antúnez-Argüelles ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Demographic History ◽  
Whole Genome ◽  
Biologically Relevant

Whole-genome sequencing of giant pandas provides insights into demographic history and local adaptation

2012 ◽  
Vol 45 (1) ◽  
pp. 67-71 ◽  
Author(s):  
Shancen Zhao ◽  
Pingping Zheng ◽  
Shanshan Dong ◽  
Xiangjiang Zhan ◽  
Qi Wu ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Local Adaptation ◽  
Genome Sequencing ◽  
Demographic History ◽  
Whole Genome ◽  
Giant Pandas

scholarly journals Population structure, genomic diversity and demographic history of Komodo dragons inferred from whole‐genome sequencing

2021 ◽  
Author(s):  
Alessio Iannucci ◽  
Andrea Benazzo ◽  
Chiara Natali ◽  
Evy Ayu Arida ◽  
Moch Samsul Arifin Zein ◽  
...  
Keyword(s):  
Population Structure ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Demographic History ◽  
Genomic Diversity ◽  
Whole Genome ◽  
History Of

Utility of Whole Genome Sequencing in diagnosing complex disorders: lesson from renal tubular disorders

2018 ◽  
Author(s):  
Mark Stevenson ◽  
Alistair T Pagnamenta ◽  
Heather G Mack ◽  
Judith A Savige ◽  
Kate E Lines ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Whole Genome ◽  
Complex Disorders ◽  
Tubular Disorders ◽  
Renal Tubular Disorders ◽  
Renal Tubular

0306 Exploring the feasibility of using copy number variants as genetic markers through large-scale whole genome sequencing experiments

2016 ◽  
Vol 94 (suppl_5) ◽  
pp. 146-146
Author(s):  
D. M. Bickhart ◽  
L. Xu ◽  
J. L. Hutchison ◽  
J. B. Cole ◽  
D. J. Null ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genetic Markers ◽  
Genome Sequencing ◽  
Copy Number ◽  
Large Scale ◽  
Copy Number Variants ◽  
Whole Genome
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