Mutations in the bovineABCG2 and the ovineMSTN gene added to the few quantitative trait nucleotides identified in farm animals: a mini-review

Braunschweig, M

doi:10.1007/bf03208858

Cited by 8 publications

(6 citation statements)

References 57 publications

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“…On the other hand, ABCG2 , DGAT1 and GHR consistently found under selection signatures and investigated in further details. The ABCG2 has been found involved in milk yield and composition [ 129 – 132 ] and a differential expression found it as lactation regulator [ 133 ]. Similarly, for dairy production, the DGAT1 [ 134 , 135 ] and GHR [ 80 , 106 , 136 ] are also strong candidate genes with major effect on milk yield and composition and the regional QTLs and strong selection signatures have been found coincided in multiple cattle breeds [ 30 , 31 ].…”

Section: Discussionmentioning

confidence: 99%

A Meta-Assembly of Selection Signatures in Cattle

Randhawa¹,

Khatkar²,

Thomson³

et al. 2016

PLoS ONE

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Since domestication, significant genetic improvement has been achieved for many traits of commercial importance in cattle, including adaptation, appearance and production. In response to such intense selection pressures, the bovine genome has undergone changes at the underlying regions of functional genetic variants, which are termed “selection signatures”. This article reviews 64 recent (2009–2015) investigations testing genomic diversity for departure from neutrality in worldwide cattle populations. In particular, we constructed a meta-assembly of 16,158 selection signatures for individual breeds and their archetype groups (European, African, Zebu and composite) from 56 genome-wide scans representing 70,743 animals of 90 pure and crossbred cattle breeds. Meta-selection-scores (MSS) were computed by combining published results at every given locus, within a sliding window span. MSS were adjusted for common samples across studies and were weighted for significance thresholds across and within studies. Published selection signatures show extensive coverage across the bovine genome, however, the meta-assembly provides a consensus profile of 263 genomic regions of which 141 were unique (113 were breed-specific) and 122 were shared across cattle archetypes. The most prominent peaks of MSS represent regions under selection across multiple populations and harboured genes of known major effects (coat color, polledness and muscle hypertrophy) and genes known to influence polygenic traits (stature, adaptation, feed efficiency, immunity, behaviour, reproduction, beef and dairy production). As the first meta-assembly of selection signatures, it offers novel insights about the hotspots of selective sweeps in the bovine genome, and this method could equally be applied to other species.

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Section: Discussionmentioning

confidence: 99%

A Meta-Assembly of Selection Signatures in Cattle

Randhawa¹,

Khatkar²,

Thomson³

et al. 2016

PLoS ONE

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“…Therefore, in order to infer information across breeds, it is important to use variants that are in high LD with the causative mutations. Although the true causative mutations are unknown, with a few exceptions [21], a large number of quantitative trait loci (QTL) regions have been detected in dairy cattle [22–27], and this information could be used to select sequence variants for genomic prediction. However, variants that are linked to a QTL in one breed but not in another breed can introduce noise, and reduce accuracy of genomic prediction for the other breed.…”

Section: Introductionmentioning

confidence: 99%

Sequence variants selected from a multi-breed GWAS can improve the reliability of genomic predictions in dairy cattle

2016

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BackgroundSequence data can potentially increase the reliability of genomic predictions, because such data include causative mutations instead of relying on linkage disequilibrium (LD) between causative mutations and prediction variants. However, the location of the causative mutations is not known, and the presence of many variants that are in low LD with the causative mutations may reduce prediction reliability. Our objective was to investigate whether the use of variants at quantitative trait loci (QTL) that are identified in a multi-breed genome-wide association study (GWAS) for milk, fat and protein yield would increase the reliability of within- and multi-breed genomic predictions in Holstein, Jersey and Danish Red cattle. A wide range of scenarios that test different strategies to select prediction markers, for both within-breed and multi-breed prediction, were compared.ResultsFor all breeds and traits, the use of variants selected from a multi-breed GWAS resulted in substantial increases in prediction reliabilities compared to within-breed prediction using a 50 K SNP array. Reliabilities depended highly on the choice of the prediction markers, and the scenario that led to the highest reliability varied between breeds and traits. While genomic correlations across breeds were low for genome-wide sequence variants, the effects of the QTL variants that yielded the highest reliabilities were highly correlated across breeds.ConclusionsOur results show that the use of sequence variants, which are located near peaks of QTL that are detected in a multi-breed GWAS, can increase reliability of genomic predictions.Electronic supplementary materialThe online version of this article (doi:10.1186/s12711-016-0259-0) contains supplementary material, which is available to authorized users.

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“…However, the mutations that underlie such QTL have been identified only in a few cases [1]. Even reasonably fine-mapped QTL regions of around 2 Mb can still contain multiple genes with a large number of potential causative mutations.…”

Section: Introductionmentioning

confidence: 99%

Concordance analysis for QTL detection in dairy cattle: a case study of leg morphology

Berg

Fritz

Rodriguez

et al. 2014

Genetics Selection Evolution

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BackgroundThe present availability of sequence data gives new opportunities to narrow down from QTL (quantitative trait locus) regions to causative mutations. Our objective was to decrease the number of candidate causative mutations in a QTL region. For this, a concordance analysis was applied for a leg conformation trait in dairy cattle. Several QTL were detected for which the QTL status (homozygous or heterozygous for the QTL) was inferred for each individual. Subsequently, the inferred QTL status was used in a concordance analysis to reduce the number of candidate mutations.MethodsTwenty QTL for rear leg set side view were mapped using Bayes C. Marker effects estimated during QTL mapping were used to infer the QTL status for each individual. Subsequently, polymorphisms present in the QTL regions were extracted from the whole-genome sequences of 71 Holstein bulls. Only polymorphisms for which the status was concordant with the QTL status were kept as candidate causative mutations.ResultsQTL status could be inferred for 15 of the 20 QTL. The number of concordant polymorphisms differed between QTL and depended on the number of QTL statuses that could be inferred and the linkage disequilibrium in the QTL region. For some QTL, the concordance analysis was efficient and narrowed down to a limited number of candidate mutations located in one or two genes, while for other QTL a large number of genes contained concordant polymorphisms.ConclusionsFor regions for which the concordance analysis could be performed, we were able to reduce the number of candidate mutations. For part of the QTL, the concordant analyses narrowed QTL regions down to a limited number of genes, of which some are known for their role in limb or skeletal development in humans and mice. Mutations in these genes are good candidates for QTN (quantitative trait nucleotides) influencing rear leg set side view.

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Mutations in the bovineABCG2 and the ovineMSTN gene added to the few quantitative trait nucleotides identified in farm animals: a mini-review

Cited by 8 publications

References 57 publications

A Meta-Assembly of Selection Signatures in Cattle

A Meta-Assembly of Selection Signatures in Cattle

Sequence variants selected from a multi-breed GWAS can improve the reliability of genomic predictions in dairy cattle

Concordance analysis for QTL detection in dairy cattle: a case study of leg morphology

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