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Mapping traits in farm animals
In the Literature.

Here, GNN highlights papers on mapping quantitative trait loci (QTLs) in farm animals related to the article Scientists pinpoint gene linked to fat in cow's milk.


Development of microsatellite markers and comparative mapping for bovine chromosome 19.

Previous research has mapped an ovulation rate quantitative trait locus (QTL) to bovine chromosome 19. In an effort to enhance comparative mapping information and develop additional markers for refined QTL mapping, microsatellite markers were developed in a targeted approach. A bovine bacterial artificial chromosome (BAC) library was screened for loci with either known or predicted locations on bovine chromosome 19. An average of 6.4 positive BAC were identified per screened locus. A total of 10 microsatellite markers were developed for five targeted loci with heterozygosity of 7-83% in a sample of reference family parents. The newly developed markers were typed on reference families along with four previously mapped marker loci and used to create a linkage map. Comparison of locus order between human and cattle provides support for previously observed rearrangement. One of the mapped loci myotubularin related protein 4 (MTMR4) potentially extends the proximal boundary of a conserved linkage group.

Anim Genet 2002 Feb;33(1):65-8.

Detection of quantitative trait loci for resistance/susceptibility to pseudorabies virus in swine.

This study describes genetic differences in resistance/susceptibility to pseudorabies virus (PrV) between European Large White and Chinese Meishan pigs, with a mapping of quantitative trait loci (QTL) obtained from a genome-wide scan in F(2) animals. Eighty-nine F(2) pigs were challenged intranasally at 12 weeks with 10(5) p.f.u. of the wild-type PrV strain NIA-3. For QTL analysis, 85 microsatellite markers, evenly spaced on the 18 porcine autosomes and on the pseudoautosomal region of the X chromosome, were genotyped. All pigs developed clinical signs, i.e. fever, from 3 to 7 days p.i. The pure-bred Large White pigs, the F(1) and three-quarters of the F(2) animals, but none of the Meishan pigs, developed neurological symptoms and died or were euthanized. QTLs for appearance/non-appearance of neurological symptoms were found on chromosomes 9, 5, 6 and 13. They explained 10.6-17.9% of F(2) phenotypic variance. QTL effects for rectal temperature after PrV challenge were found on chromosomes 2, 4, 8, 10, 11 and 16. Effects on chromosomes 9, 10 and 11 were significant on a genome-wide level. The results present chromosomal regions that are associated with presence/absence of neurological symptoms as well as temperature course after intranasal challenge with NIA-3. The QTLs are in proximity to important candidate genes that are assumed to play crucial roles in host defence against PrV.

J Gen Virol 2002 Jan;83(Pt 1):167-72.

Quantitative trait loci affecting clinical mastitis and somatic cell count in dairy cattle.

Norway has a field recording system for dairy cattle that includes recording of all veterinary treatments on an individual animal basis from 1978 onwards. Application of these data in a genome search for quantitative trait loci (QTL) verified genome-wise significant QTL affecting clinical mastitis on Chromosome (Chr) 6. Additional putative QTL for clinical mastitis were localized to Chrs. 3, 4, 14, and 27. The comprehensive field recording system includes information on somatic cell count as well. This trait is often used in selection against mastitis when direct information on clinical mastitis is not available. The absence of common QTL positions for the two traits in our study indicates that the use of somatic cell count data in QTL studies aimed for reducing the incidence of mastitis should be carefully evaluated.

Mamm Genome 2001 Nov;12(11):837-42.

Mapping quantitative trait loci for milk production traits on ovine chromosome 6.

Spanish Churra sheep were studied in a daughter design for the presence on chromosome 6 of quantitative trait loci (QTL) influencing milk production traits. Eight half-sib families were genotyped for 11 microsatellites and marker-QTL effects analysed using yield deviations (YD) as quantitative measurements for the following traits: milk yield, protein yield, and protein percentage. QTL analysis was performed by interval mapping based on multimarker regression principles. Significance thresholds were estimated through a permutation test followed by a correction for multiple testing. The results suggest a region on ovine chromosome 6, close to the casein cluster, with an influence on milk traits and particularly on protein percentage. These results, the first ones reported for QTL affecting milk traits in sheep, are discussed in relation to data available for cattle, a closely related species.

J Dairy Res 2001 Aug;68(3):389-97.

Detection of quantitative trait loci affecting milk production traits on 10 chromosomes in Holstein cattle.

Sons (n = 71 to 75) of each of six Holstein sires were genotyped at 69 microsatellite loci covering a total of 676 cM on chromosomes 3, 5, 9, 10, 13, 15, 17, 20, 23, and 26. Estimates of quantitative trait loci (QTL) effect and location were made using a least squares interval mapping approach based on daughter yield deviations of sons for 305 d milk, fat, and protein yield and fat and protein percentage. Thresholds for statistical significance of QTL effects were determined from interval mapping of 10,000 random permutations of the data across the bull sire families and within each sire family separately. Analyses combining data across sires indicated the presence of QTL affecting milk, fat, and protein yield on chromosomes 20 and 26 and a QTL affecting fat and protein percentage on chromosome 3. Analyses within each sire family separately indicated the presence of segregating QTL in at least one family on 7 of the 10 chromosomes. Statistically significant estimates of QTL effects on breeding value ranged from 438 to 658 kg of milk, from 17.4 to 24.9 kg of fat, 13.0 to 17.0 kg of protein, 0.04 to 0.17% fat, and 0.07 to 0.10% protein.

J Dairy Sci 2001 Jun;84(6):1516-24.

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