2011
DOI: 10.1186/1471-2164-12-559
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Whole genome resequencing of black Angus and Holstein cattle for SNP and CNV discovery

Abstract: BackgroundOne of the goals of livestock genomics research is to identify the genetic differences responsible for variation in phenotypic traits, particularly those of economic importance. Characterizing the genetic variation in livestock species is an important step towards linking genes or genomic regions with phenotypes. The completion of the bovine genome sequence and recent advances in DNA sequencing technology allow for in-depth characterization of the genetic variations present in cattle. Here we describ… Show more

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Cited by 153 publications
(152 citation statements)
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“…The SNP on these arrays, primarily selected using spacing along the genome and allele frequency (Matukumalli et al, 2009;Ramos et al, 2009), are ef- Table 6. Genetic correlations between genomic EBV trained by GPE Cycle VII shear force measurements, using whole-genome and sets selected by functional annotation and association with phenotype, and 14-d slice shear force measured on steers from Cycle VIII and continuous GPE 1 (Cánovas et al, 2010;Stothard et al, 2011;Larkin et al, 2012). Categorizing these variants according to expected effect on annotated protein coding genes may reveal the variants most infl uential to gene function (McLaren et al, 2010;Cingolani et al, 2012).…”
Section: Future Effortsmentioning
confidence: 99%
“…The SNP on these arrays, primarily selected using spacing along the genome and allele frequency (Matukumalli et al, 2009;Ramos et al, 2009), are ef- Table 6. Genetic correlations between genomic EBV trained by GPE Cycle VII shear force measurements, using whole-genome and sets selected by functional annotation and association with phenotype, and 14-d slice shear force measured on steers from Cycle VIII and continuous GPE 1 (Cánovas et al, 2010;Stothard et al, 2011;Larkin et al, 2012). Categorizing these variants according to expected effect on annotated protein coding genes may reveal the variants most infl uential to gene function (McLaren et al, 2010;Cingolani et al, 2012).…”
Section: Future Effortsmentioning
confidence: 99%
“…However, it could also be related to differences between C. angulata and C. gigas genomes, that may reflect the finding that C. angulata is evolutionarily more distant from the reference genome (C. gigas) than is usually thought [37e39]. On the other hand, the average mapping depth presents lower values than those observed in the wild C. gigas oyster (50-fold) [3] and Korean cattle (45.6-fold) [40] but higher than those previously reported in whole-genome re-sequenced carried out in cattle of the Black Angus and Holstein breed (9.8-fold and 10.8-fold, respectively) [41] or Japanese native cattle (15.8-fold) [42]. So, in spite of the large number of scaffolds existing in the reference genome, ranging between 100 bp and 1.9 millions bp in size (Supplementary file 1), both the coverage of reads and the mapping depth obtained (83.36% and 29.34-fold respectively) are in the range of optimal values required for the analysis of the genome of C. angulata by a whole-genome re-sequencing approach.…”
Section: Sequencing Mapping and Snp/indel Detectionmentioning
confidence: 55%
“…The libraries were prepared using the reagents and protocols provided by Applied Biosystems, and as reported in previous studies. 29 Sequence reads were mapped to the Btau4.0 bovine genome assembly using the Bioscope 1.0 software suite (Life Technologies Corporation). A list of putative SNPs was generated for each animal from the mapped reads, using the diBayes SNP Detection module (with the "med-coverage" stringency setting) included with Bioscope.…”
Section: Supplemental Materialsmentioning
confidence: 99%
“…Transcript sequences from liver, hypothalamus, muscle, adipose, duodenum, kidney, lung blood, cortex and Peyer's patch were evaluated to identify SNPs in each of the 89 candidate genes mapped to the 57 regions of the bovine genome thought to be related to BSE susceptibility. Whole-genome sequences from a Holstein bull and a Black Angus bull 29 were also used to identify structural variation within candidate genes. Non-synonymous mutations were selected when available as were SNPs predicted to introduce a stop codon or splice variation.…”
Section: Introductionmentioning
confidence: 99%