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A cost-effective, high-throughput, highly accurate genotyping method for outbred populations.

Chen Denghui, D Chitre, Apurva S AS et al.

39670731 PubMed ID
20 Authors
2025-02-05 Published
127 Views
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Chapter I

Publication Details

Comprehensive information about this research publication

Authors

CD
Chen Denghui
DC
D Chitre
AS
Apurva S AS
NK
Nguyen Khai-Minh H
KC
KH Cohen
KA
Katerina A KA
PB
Peng Beverly F
BZ
BF Ziegler
KS
Kendra S KS
OF
Okamoto Faith
FL
F Lin
BB
Bonnie B
JB
Johnson Benjamin B
BS
BB Sanches
TM
Thiago M TM
CR
Cheng Riyan
RP
R Polesskaya
OO
Oksana O
PA
Palmer Abraham A
A
AA
Chapter II

Abstract

Summary of the research findings

Affordable sequencing and genotyping methods are essential for large-scale genome-wide association studies. While genotyping microarrays and reference panels for imputation are available for human subjects, nonhuman model systems often lack such options. Our lab previously demonstrated an efficient and cost-effective method to genotype heterogeneous stock rats using double-digest genotyping by sequencing. However, low-coverage whole-genome sequencing offers an alternative method that has several advantages. Here, we describe a cost-effective, high-throughput, high-accuracy genotyping method for N/NIH heterogeneous stock rats that can use a combination of sequencing data previously generated by double-digest genotyping by sequencing and more recently generated by low-coverage whole-genome sequencing data. Using double-digest genotyping-by-sequencing data from 5,745 heterogeneous stock rats (mean 0.21× coverage) and low-coverage whole-genome sequencing data from 8,760 heterogeneous stock rats (mean 0.27× coverage), we can impute 7.32 million biallelic single-nucleotide polymorphisms with a concordance rate > 99.76% compared to high-coverage (mean 33.26× coverage) whole-genome sequencing data for a subset of the same individuals. Our results demonstrate the feasibility of using sequencing data from double-digest genotyping by sequencing or low-coverage whole-genome sequencing for accurate genotyping and demonstrate techniques that may also be useful for other genetic studies in nonhuman subjects.

Chapter III

AI-Generated Summary

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