Quantitative trait loci associated with pre-weaning growth in South African Angora goats

Visser, Carina; Marle-Köster, E. van; Snyman, M.A.; Bovenhuis, H.; Crooijmans, R.P.M.A.

doi:10.1016/j.smallrumres.2012.11.035

Cited by 9 publications

(10 citation statements)

References 49 publications

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“…In a separate QTL identification study focusing on pre-weaning growth traits, four chromosomal regions of interest with an influence on birth weight (BW) were identified on CHI 4, 8, 18 and 27 (Visser et al, 2013). Analyses indicated two candidate regions for weaning weight (WW)…”

Section: Selectionmentioning

confidence: 99%

Strategies for the genetic improvement of South African Angora goats

Visser

Marle-Köster

2014

Small Ruminant Research

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Selection of Angora goats over the past decades has focused on traits related to fitness, body weight and fiber production. Research for genetic improvement of the Angora has been based on quantitative selection and more recently molecular technology has been applied. Although considerable progress has been made at increasing fine mohair production, the inability of Angora goats to survive sub-optimum conditions has become a concern. Selection emphasis on fibre production resulted in unthrifty animals and the South African (SA) Angora industry is still hampered by the loss of young goats. DNA marker information assists conventional selection by increasing selection accuracy, improving the rate of genetic improvement and leading to a better understanding of the physiological background of traits. The genetic diversity of the SA Angora goat breed was estimated and an improved linkage map was recently developed. The extensive production systems in South Africa pose a challenge for pedigree integrity, and a microsatellite panel was constructed for parentage verification. Selection for quantitative trait loci (QTL) will lead to increased genetic progress and offers the opportunity to improve understanding of and exploit phenotypic variation.Putative QTL associated with fleece and growth traits have been identified in the South African Angora goat population. The current goat SNP chip does not include any fibre-producing goat breed, and this chip is currently being verified in the SA Angora goat population, in conjunction with the sequencing of certain keratin genes.

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Section: Selectionmentioning

confidence: 99%

Strategies for the genetic improvement of South African Angora goats

Visser

Marle-Köster

2014

Small Ruminant Research

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“…Quantitative trait loci for traits such as birth and weaning weight (Mohammad Abadi et al, 2009;Visser et al, 2013), hair fiber characteristics (Cano et al, 2007;Visser et al, 2011), growth (Mohammad Abadi et al, 2009), body conformation (Marrube et al, 2007), parasite resistance (Bolormaa et al, 2010;De La Chevrotière et al, 2012), milk traits (Roldán et al, 2008), and α S1 -casein (Sacchi et al, 2005;Hayes et al, 2006;Dagnachew et al, 2011) have been identified in goats using microsatellite markers. With the availability of the Illumina Caprine 50K BeadChip (Illumina Inc., San Diego, CA;Tosser-Klopp et al, 2012, 2014, it is now possible to perform genome-wide scans in goats Genome-wide association study of conformation and milk yield in mixed-breed dairy goats with much greater resolution.…”

Section: Introductionmentioning

confidence: 99%

Genome-wide association study of conformation and milk yield in mixed-breed dairy goats

Mucha

Mrode

Coffey

et al. 2018

Journal of Dairy Science

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Identification of genetic markers that affect economically important traits is of high value from a biological point of view, enabling the targeting of candidate genes and providing practical benefits for the industry such as wide-scale genomic selection. This study is one of the first to investigate the genetic background of economically important traits in dairy goats using the caprine 50K single nucleotide polymorphism (SNP) chip. The aim of the project was to perform a genome-wide association study for milk yield and conformation of udder, teat, and feet and legs. A total of 137,235 milk yield records on 4,563 goats each scored for 10 conformation traits were available. Out of these, 2,381 goats were genotyped with the Illumina Caprine 50K BeadChip (Illumina Inc., San Diego, CA). A range of pseudo-phenotypes were used including deregressed breeding values and pseudo-estimated breeding values. Genome-wide association studies were performed using the multi-locus mixed model (MLMM) algorithm implemented in SNP & Variation Suite v7.7.8 (Golden Helix Inc., Bozeman, MT). A genome-wise significant [-log(P-value) > 5.95] SNP for milk yield was identified on chromosome 19, with additional chromosome-wise significant (-log(P-value) > 4.46] SNP on chromosomes 4, 8, 14, and 29. Three genome-wise significant SNP for conformation of udder attachment, udder depth, and front legs were identified on chromosome 19, and chromosome-wise SNP were found on chromosomes 4, 5, 6, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 23, and 27. The proportion of variance explained by the significant SNP was between 0.4 and 7.0% for milk yield and between 0.1 and 13.8% for conformation traits. This study is the first attempt to identify SNP associated with milk yield and conformation in dairy goats. Two genome-wise significant SNP for milk yield and 3 SNP for conformation of udder attachment, udder depth, and front legs were found. Our results suggest that conformation traits have a polygenic background because, for most of them, we did not identify any quantitative trait loci with major effect.

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“…) and CHI 4 and 18 in Angora goats (Visser et al . ), were associated with birth weight in other independent studies in goat, whereas QTL associated with birth weight in sheep were detected on CHI 14 (OAR 14; corresponding to CHI 18) in Scottish Blackface sheep (Hadjipavlou & Bishop ) and on OAR 3 (corresponding to CHI 5 and 1) in Merino sheep (Roldan et al . ).…”

Section: Discussionmentioning

confidence: 92%

“…In addition, QTL affecting birth weight on CHI 4 (68 cM), CHI 8 (0 cM), CHI 18 (17 cM) and CHI 27 (6 cM) and QTL for weaning weight on CH16 (68 cM) and CHI 19 (46 cM) have been recently reported by Visser et al . () in South African Angora goats but still need to be validated in other goat breeds. Thus, one of the objectives of this study was to map QTL affecting birth weight in Rayini cashmere goats.…”

Section: Introductionmentioning

confidence: 99%

Genome‐scan analysis for genetic mapping of quantitative trait loci underlying birth weight and onset of puberty in doe kids (Capra hircus)

Esmailizadeh

2014

Animal Genetics

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The objective of this study was to locate quantitative trait loci (QTL) causing variation in birth weight and age of puberty of doe kids in a population of Rayini cashmere goats. Four hundred and thirty kids from five half-sib families were genotyped for 116 microsatellite markers located on the caprine autosomes. The traits recorded were birth weight of the male and female kids, body weight at puberty, average daily gain from birth to age of puberty and age at puberty of the doe kids. QTL analysis was conducted using the least squares interval mapping approach. Linkage analysis indicated significant QTL for birth weight on Capra hircus chromosomes (CHI) 4, 5, 6, 18 and 21. Five QTL located on CHI 5, 14 and 29 were associated with age at puberty. Across-family analysis revealed evidence for overlapping QTL affecting birth weight (78 cM), body weight at puberty (72 cM), average daily gain from birth to age of puberty (72 cM) and age at puberty (76 cM) on CHI 5 and overlapping QTL controlling body weight at puberty and age at puberty on CHI 14 at 18-19 cM. The proportion of the phenotypic variance explained by the detected QTL ranged between 7.9% and 14.4%. Confirming some of the previously reported results for birth weight and growth QTL in goats, this study identified more QTL for these traits and is the first report of QTL for onset of puberty in doe kids.

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Quantitative trait loci associated with pre-weaning growth in South African Angora goats

Cited by 9 publications

References 49 publications

Strategies for the genetic improvement of South African Angora goats

Strategies for the genetic improvement of South African Angora goats

Genome-wide association study of conformation and milk yield in mixed-breed dairy goats

Genome‐scan analysis for genetic mapping of quantitative trait loci underlying birth weight and onset of puberty in doe kids (Capra hircus)

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