A customized and versatile high-density genotyping array for the mouse

Yang, Hyuna; Ding, Yueming; Hutchins, Lucie N.; Szatkiewicz, Jin P.; Bell, Timothy A.; Paigen, Beverly; Graber, Joel H.; Villena, Fernando Pardo Manuel de; Churchill, Gary A.

doi:10.1038/nmeth.1359

Cited by 244 publications

(279 citation statements)

References 17 publications

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“…Genotypes for all 100 female and 113 male strains were obtained from the Jackson Laboratory using the Mouse Diversity Array (29). SNPs that had poor quality or had a minor allele frequency of more than 5% and a missing genotype rate of less than 10% were removed.…”

Section: Association Analysismentioning

confidence: 99%

Genetic and hormonal control of hepatic steatosis in female and male mice

Norheim

Hui

Kulahcioglu

et al. 2017

Journal of Lipid Research

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Section: Association Analysismentioning

confidence: 99%

Genetic and hormonal control of hepatic steatosis in female and male mice

Norheim

Hui

Kulahcioglu

et al. 2017

Journal of Lipid Research

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“…This study is based on local phylogenetic trees for 100 classical laboratory strains ( Figure S1) based on genotypes from MDA. MDA is an Affymetrix-based 6.5M probe platform with .600,000 SNP markers uniformly spaced across the nonrepetitive regions of the mouse genome (Yang et al 2009). We used the subset of 549,683 high-quality markers that were genotyped in Yang et al (2011).…”

Section: Mda Genotype Datamentioning

confidence: 99%

“…A complementary resource is the recent release of Mouse Diversity Array (MDA) genotypes from 162 mouse strains (Yang et al 2011). MDA is a high-density DNA microarray designed to assay diversity among commonly used laboratory mice (Yang et al 2009). The density of SNP genotypes available on the MDA exceeds the density of recombination events accumulated over the development of the classical inbred strains and as such the MDA SNPs can provide a framework for imputation of the underlying whole-genome sequence.…”

mentioning

confidence: 99%

Imputation of Single-Nucleotide Polymorphisms in Inbred Mice Using Local Phylogeny

Wang¹,

Villena

Lawson

et al. 2012

Genetics

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We present full-genome genotype imputations for 100 classical laboratory mouse strains, using a novel method. Using genotypes at 549,683 SNP loci obtained with the Mouse Diversity Array, we partitioned the genome of 100 mouse strains into 40,647 intervals that exhibit no evidence of historical recombination. For each of these intervals we inferred a local phylogenetic tree. We combined these data with 12 million loci with sequence variations recently discovered by whole-genome sequencing in a common subset of 12 classical laboratory strains. For each phylogenetic tree we identified strains sharing a leaf node with one or more of the sequenced strains. We then imputed high-and medium-confidence genotypes for each of 88 nonsequenced genomes. Among inbred strains, we imputed 92% of SNPs genome-wide, with 71% in high-confidence regions. Our method produced 977 million new genotypes with an estimated per-SNP error rate of 0.083% in high-confidence regions and 0.37% genome-wide. Our analysis identified which of the 88 nonsequenced strains would be the most informative for improving full-genome imputation, as well as which additional strain sequences will reveal more new genetic variants. Imputed sequences and quality scores can be downloaded and visualized online.

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“…Oligonucleotide microarrays, composed of millions of probes based on genome sequences, can capture large numbers of sequence variations between different samples by comparative genomic hybridization, which can be used for high-throughput marker discovery and genotyping (1)(2)(3). However, restrictions in microarray design and the number of probes on the microarrays limit the applications of this technology.…”

mentioning

confidence: 99%

Parent-independent genotyping for constructing an ultrahigh-density linkage map based on population sequencing

Xie

Feng²,

Yu³

et al. 2010

Proc. Natl. Acad. Sci. U.S.A.

293

258

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Bar-coded multiplexed sequencing approaches based on newgeneration sequencing technologies provide capacity to sequence a mapping population in a single sequencing run. However, such approaches usually generate low-coverage and error-prone sequences for each line in a population. Thus, it is a significant challenge to genotype individual lines in a population for linkage map construction based on low-coverage sequences without the availability of high-quality genotype data of the parental lines. In this paper, we report a method for constructing ultrahigh-density linkage maps composed of high-quality single-nucleotide polymorphisms (SNPs) based on low-coverage sequences of recombinant inbred lines. First, all potential SNPs were identified to obtain drafts of parental genotypes using a maximum parsimonious inference of recombination, making maximum use of SNP information found in the entire population. Second, high-quality SNPs were identified by filtering out low-quality ones by permutations involving resampling of windows of SNPs followed by Bayesian inference. Third, lines in the mapping population were genotyped using the high-quality SNPs assisted by a hidden Markov model. With 0.05× genome sequence per line, an ultrahigh-density linkage map composed of bins of high-quality SNPs using 238 recombinant inbred lines derived from a cross between two rice varieties was constructed. Using this map, a quantitative trait locus for grain width (GW5) was localized to its presumed genomic region in a bin of 200 kb, confirming the accuracy and quality of the map. This method is generally applicable in genetic map construction with low-coverage sequence data.genomics | maximum parsimony of recombination | Bayesian inference | hidden Markov model | rice G enetic maps provide the bases for a wide range of genetic and genomic studies and are pivotal for mapping and identifying genes associated with phenotypic performance, referred to as traits. The resolution of a genetic linkage map depends on the number of recombination events in the mapping population and the density of molecular markers. The number of recombination events depends on how the population is created, whereas the density of the markers can be improved continually with advances in molecular techniques. Traditional molecular markers that have been widely used in genotyping assays of populations, although laborious and time-consuming, have limitations in throughput and can provide information only for low-density maps, and thus are of low efficiency.Oligonucleotide microarrays, composed of millions of probes based on genome sequences, can capture large numbers of sequence variations between different samples by comparative genomic hybridization, which can be used for high-throughput marker discovery and genotyping (1-3). However, restrictions in microarray design and the number of probes on the microarrays limit the applications of this technology. In addition, it is cost-prohibitive for genotyping especially if the mapping population is large.New sequencing t...

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A customized and versatile high-density genotyping array for the mouse

Cited by 244 publications

References 17 publications

Genetic and hormonal control of hepatic steatosis in female and male mice

Genetic and hormonal control of hepatic steatosis in female and male mice

Imputation of Single-Nucleotide Polymorphisms in Inbred Mice Using Local Phylogeny

Parent-independent genotyping for constructing an ultrahigh-density linkage map based on population sequencing

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