QTL affecting fleece traits in Angora goats

Cano, Eduardo; Marrube, G.; Roldan, D.L.; Bidinost, F.; Abad, Miguel Pino; Allain, Daniel; Vaiman, Daniel; Taddeo, H.; Poli, M. A.

doi:10.1016/j.smallrumres.2006.06.002

Cited by 23 publications

(23 citation statements)

References 28 publications

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“…Detecting QTL on different chromosomes than Cano et al (2009b) could be due to phenotypic traits measured at either second or third shearing in the current study, while samples were taken at 4 and 11 months of age in the study by Cano et al (2009b). It should also be noted that all but one of the QTL detected was at chromosomewide significance level, as was those reported by Cano et al (2007Cano et al ( , 2009a Further studies should focus on confirming the reported QTL at genome-wide significance levels in experimental designs with higher statistical power.…”

Section: Discussionmentioning

confidence: 46%

“…Differences between families are due to herd effects, breeders following different selection strategies and placing emphasis on varying selection criteria, with limited genetic linkages between farms. Previous reports on QTL associated with mohair traits are limited to one research group (Cano et al, , 2009a between studies. In this study several putative QTL were identified for CF, SF, FW and FD and one each for SDA, SDFD and CVFD.…”

Section: Discussionmentioning

confidence: 99%

“…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). These results, together with the QTL affecting conformation traits in Angora goats Debenedetti et al (2010) on CHI 5 in a backcross Angora × Creole population.…”

Section: Introductionmentioning

confidence: 89%

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QTL for mohair traits in South African Angora goats

Visser

Marle-Köster

Bovenhuis

et al. 2011

Small Ruminant Research

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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.

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Section: Discussionmentioning

confidence: 46%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 89%

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QTL for mohair traits in South African Angora goats

Visser

Marle-Köster

Bovenhuis

et al. 2011

Small Ruminant Research

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“…For instance, De la Chevrotière et al [2] identified 13 QTL for resistance to gastrointestinal nematode infections in Creole goats by analysing 101 microsatellites. Quantitative trait loci affecting mohair [3,4] and conformation traits [5] as well as preweaning growth [6] have also been reported in Angora goats. On the other hand, partial genome scans have been carried out by Bolormaa et al [7], who described QTL for worm egg and blood eosinophil counts in Australian Angora and Cashmere goats through the analysis of three microsatellites mapping to the caprine major histocompatibility complex on chromosome 23, and by Roldán et al [8] who genotyped 37 microsatellites mapping to four chromosomes and found several QTL influencing the variation of milk yield and quality traits across lactation.…”

Section: Introductionmentioning

confidence: 91%

The Application of Genomic Technologies to Investigate the Inheritance of Economically Important Traits in Goats

Amills

2014

Advances in Biology

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Goat genomics has evolved at a low pace because of a lack of molecular tools and sufficient investment. Whilst thousands and hundreds of quantitative trait loci (QTL) have been identified in cattle and sheep, respectively, about nine genome scans have been performed in goats dealing with traits as conformation, growth, fiber quality, resistance to nematodes, and milk yield and composition. In contrast, a great effort has been devoted to the characterization of candidate genes and their association with milk, meat, and reproduction phenotypes. In this regard, causal mutations have been identified in the S1 -casein gene that has a strong effect on milk composition and the PIS locus that is linked to intersexuality and polledness. In recent times, the development of massive parallel sequencing technologies has allowed to build a reference genome for goats as well as to monitor the expression of mRNAs and microRNAs in a broad array of tissues and experimental conditions. Besides, the recent design of a 52K SNP chip is expected to have a broad impact in the analysis of the genetic architecture of traits of economic interest as well as in the study of the population structure of goats at a worldwide scale.

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“…To date molecular studies in goats have been limited to mainly genetic diversity studies using microsatellite markers (Iamartino et al, 2005;Kumar et al, 2005;Gour et al, 2006;Qi et al, 2009;Visser & Van Marle-Koster, 2009), parentage verification (Luikart et al, 1999;Ganai & Yadav, 2005;Glowatzki-Mullis et al, 2007;Bolormaa et al, 2008;De Araujo et al, 2010;Visser et al, 2011b) and identification of QTL for fibre traits (Cano et al & 2009Mohammed Abadi et al 2009;Debenedetti et al 2010;Visser et al 2011a) in different breeds. DNA marker information will assist conventional selection by increasing selection accuracy and improving the rate of genetic improvement, as well as leading to a better understanding of the physiological background of quantitative traits (Pollak, 2005;Jeon et al, 2006;Dodds et al, 2 0 0 7 ) .…”

Section: Introductionmentioning

confidence: 99%

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

Visser

Marle-Köster

Snyman

et al. 2013

Small Ruminant Research

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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.

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QTL affecting fleece traits in Angora goats

Cited by 23 publications

References 28 publications

QTL for mohair traits in South African Angora goats

QTL for mohair traits in South African Angora goats

The Application of Genomic Technologies to Investigate the Inheritance of Economically Important Traits in Goats

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

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