Merino sheep: a further look at quantitative trait loci for wool production

2014

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.

Section: Selectionmentioning

confidence: 84%

Strategies for the genetic improvement of South African Angora goats

2014

“…The putative QTL on CHI 5 had the largest effect (0.5) on this trait and explained 10.3% of the variance for this trait, while the QTL on CHI 2 and 24 explained between 8.8% and 13.4% of the variance respectively. Several studies have located a putative QTL for fibre yield on CHI 5 of Rayini goats (Mohammed Abadi et al, 2009), Angora × Creole goats (Debenedetti et al, 2010), purebred Angora goats (Cano et al, 2009b) and on the corresponding ovine chromosome (OAR 3) of Merino sheep (Roldan et al, 2010). QTL detecting in Rayini goats affecting cashmere hair traits resulted in QTL on chromosome 2, 5 and 13 of which those on chromosomes 2 and 5 overlap with the QTLs found on chromosome 2 and 5 for angora yield (trait FW).…”

Section: Discussionmentioning

confidence: 99%

“…Although several QTL identification studies have been undertook for wool sheep (Allain et al, 2006;Bidinost et al, 2006Bidinost et al, , 2008Roldan et al, 2010), relatively few studies have been conducted to identify linkage with goat fibre traits. Chromosome segments that affect mohair were identified by Cano et al (2007) in Argentinean Angora goats and this resulted in further investigation into goat chromosome 19 (Cano et al, 2009a).…”

Section: Introductionmentioning

confidence: 99%

QTL for mohair traits in South African Angora goats

Bovenhuis

et al. 2011

a b s t r a c tThe aim of this study was to identify QTL associated with mohair production and quality traits in South African Angora goats. Limited research has been performed on QTL influencing the economically important mohair traits of Angora goats. Twelve half-sib Angora goat families with an average of 58 offspring per sire were genotyped for 88 microsatellites covering 22 autosomes. Phenotypic data was collected at second and third shearing for males and females respectively. A linkage analysis was performed under the half-sib model using the least squared regression approach of GridQTL. Three putative QTL were detected for fleece weight on CHI 2, 5 and 24, which corresponds with the locations of keratin and keratin-associated proteins. This study detected two putative QTL associated with mohair fibre diameter (on CHI 4 and 24, respectively), which is the most important pricedetermining trait. Four QTL were detected on CHI 8, 13, 18 and 20 which influence both comfort factor and spinning fineness. The variance explained by the QTL ranged between 6.9% for fibre diameter and 33.6% for standard deviation along the length of the staple. These results reveal segregation of QTL influencing mohair production and quality, and contribute to the understanding of the genetic variation of mohair traits.

“…Birth weight of Angora goat kids under different management systems have been noted to vary from 2.55kg to 3.21kg and that of weaning weight between 14.7kg and 20.5kg (Snyman, 2010 (Hadjipavlou & Bishop, 2008) and on OAR 3 in Merino sheep in a scan including OAR 1, 3, 4 and 11 (Roldan et al (2010). In a partial genome scan on Kermani sheep, Esmailizadeh (2010) however identified QTL for birth weight on three chromosomes namely, OAR 1, 3, and 6 (corresponding to CHI 1 and 3, CHI 5 and 1 and CHI 6 respectively).…”

Section: Discussionmentioning

confidence: 99%

“…Chromosomal fragments influencing various growth traits have been detected on this chromosome, i.e. birth weight and postweaning ADG in cattle (Kneeland et al, 2004) and weight at first shearing in sheep (Roldan et al, 2010 Usually more associations between genotypes and phenotypic traits are detected for traits with higher heritability estimates than for lower heritable traits. Identifying the polymorphisms linked to the genes controlling lowly heritable traits are more difficult and require substantially more data (Snelling et al, 2010).…”

Section: Discussionmentioning

confidence: 99%

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

Snyman

et al. 2013

This study aimed to identify chromosomal regions associated with genetic variation in preweaning growth traits in Angora goats. A genome-wide scan was performed by genotyping 1042 offspring from 12 half-sib families using 88 microsatellite caprine markers covering 1368cM.Phenotypes were recorded at birth (BW) and weaning (WW) and analysed using GridQTL software.A total of six putative QTL were detected on six different chromosomes, all at chromosome-wide significance level. Four QTL were identified for BW on CHI 4, 8, 17 and 27 and two QTL for WW on CHI 16 and 19. QTL effects ranged from -0.32 to 0.25 in units of residual standard deviation in different families. Some of these QTL correspond to chromosomes where QTL associated with growth have been identified in other species. These chromosomal segments hold potential to influence weight gain in young goats.