Variance components for bovine tuberculosis infection and multi-breed genome-wide association analysis using imputed whole genome sequence data

Abstract Background White spotting of the coat is a characteristic trait of various domestic species including cattle and other mammals. It is a hallmark of Holstein–Friesian cattle, and several previous studies have detected genetic loci with major effects for white spotting in animals with Holstein–Friesian ancestry. Here, our aim was to better understand the underlying genetic and molecular mechanisms of white spotting, by conducting the largest mapping study for this trait in cattle, to date. Results Using imputed whole-genome sequence data, we conducted a genome-wide association analysis in 2973 mixed-breed cows and bulls. Highly significant quantitative trait loci (QTL) were found on chromosomes 6 and 22, highlighting the well-established coat color genes KIT and MITF as likely responsible for these effects. These results are in broad agreement with previous studies, although we also report a third significant QTL on chromosome 2 that appears to be novel. This signal maps immediately adjacent to the PAX3 gene, which encodes a known transcription factor that controls MITF expression and is the causal locus for white spotting in horses. More detailed examination of these loci revealed a candidate causal mutation in PAX3 (p.Thr424Met), and another candidate mutation (rs209784468) within a conserved element in intron 2 of MITF transcripts expressed in the skin. These analyses also revealed a mechanistic ambiguity at the chromosome 6 locus, where highly dispersed association signals suggested multiple or multiallelic QTL involving KIT and/or other genes in this region. Conclusions Our findings extend those of previous studies that reported KIT as a likely causal gene for white spotting, and report novel associations between candidate causal mutations in both the MITF and PAX3 genes. The sizes of the effects of these QTL are substantial, and could be used to select animals with darker, or conversely whiter, coats depending on the desired characteristics.

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A multi-trait meta-analysis with imputed sequence variants reveals twelve QTL for mammary gland morphology in Fleckvieh cattle

10.1101/030981 ◽

2015 ◽

Author(s):

Hubert Pausch ◽

Reiner Emmerling ◽

Hermann Schwarzenbacher ◽

Ruedi Fries

Keyword(s):

Mammary Gland ◽

Association Analysis ◽

Genome Sequence ◽

Sequence Data ◽

Association Studies ◽

Whole Genome Sequence ◽

Sequence Variants ◽

Whole Genome ◽

Genome Sequence Data ◽

Mammary Gland Morphology

Background: The availability of whole-genome sequence data from key ancestors provides an exhaustive catalogue of polymorphic sites segregating within and across cattle breeds. Sequence variants from key ancestors can be imputed in animals that have been genotyped using medium- and high-density genotyping arrays. Association analysis with imputed sequences, particularly if applied to multiple traits simultaneously, is a very powerful approach to revealing candidate causal variants underlying complex phenotypes. Results: We used whole-genome sequence data from 157 key ancestors of the German Fleckvieh population to impute 20 561 798 sequence variants in 10 363 animals that had (partly imputed) array-derived genotypes at 634 109 SNP. The imputed sequence data were enriched for rare variants. Association studies with imputed sequence variants were performed using seven correlated udder conformation traits as response variables. The calculation of an approximate multi-trait test statistic enabled us to detect twelve major QTL (P<2.97 x 10-9) controlling different aspects of mammary gland morphology. Imputed sequence variants were the most significantly associated at eleven QTL, whereas the top association signal at a QTL on BTA14 resulted from an array-derived variant. Seven QTL were associated with multiple phenotypes. Most QTL were located in non-coding regions of the genome in close neighborhood, however, to plausible candidate genes for mammary gland morphology (SP5, GC, NPFFR2, CRIM1, RXFP2, TBX5, RBM19, ADAM12). Conclusions: Association analysis with imputed sequence variants allows QTL characterization at maximum resolution. Multi-trait approaches can reveal QTL that are not detected in single-trait association studies. Most QTL for udder conformation traits were located in non-coding elements of the genome suggesting regulatory mutations to be the major determinants of variation in mammary gland morphology in cattle.

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Linkage disequilibrium maps for European and African populations constructed from whole genome sequence data

Scientific Data ◽

10.1038/s41597-019-0227-y ◽

2019 ◽

Vol 6 (1) ◽

Cited By ~ 1

Author(s):

Alejandra Vergara-Lope ◽

M. Reza Jabalameli ◽

Clare Horscroft ◽

Sarah Ennis ◽

Andrew Collins ◽

...

Keyword(s):

Linkage Disequilibrium ◽

Genome Sequence ◽

Sequence Data ◽

Association Studies ◽

Large Population ◽

Whole Genome Sequence ◽

European Ancestry ◽

Genome Wide Association Studies ◽

Whole Genome ◽

Genome Wide

Abstract Quantification of linkage disequilibrium (LD) patterns in the human genome is essential for genome-wide association studies, selection signature mapping and studies of recombination. Whole genome sequence (WGS) data provides optimal source data for this quantification as it is free from biases introduced by the design of array genotyping platforms. The Malécot-Morton model of LD allows the creation of a cumulative map for each choromosome, analogous to an LD form of a linkage map. Here we report LD maps generated from WGS data for a large population of European ancestry, as well as populations of Baganda, Ethiopian and Zulu ancestry. We achieve high average genetic marker densities of 2.3–4.6/kb. These maps show good agreement with prior, low resolution maps and are consistent between populations. Files are provided in BED format to allow researchers to readily utilise this resource.

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