A search for quantitative trait loci for milk production traits on chromosome 6 in Finnish Ayrshire cattle

Velmala, Riikka; Vilkki, H. J.; Elo, Kari; Koning, Dirk-Jan de; Mäki‐Tanila, Asko

doi:10.1046/j.1365-2052.1999.00435.x

Cited by 92 publications

(68 citation statements)

References 22 publications

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“…This marker has also been reported by others to affect FP (Schnabel et al, 2005), MY (Gomez-Raya et al 1998;Velmala et al, 1999) and PP (Spelman et al, 1996;Zhang et al, 1998;Velmala et al, 1999;Schnabel et al, 2005), but we only confirmed that it affects FP. Moreover, we found two extra QTL Bayesian mapping in half-sib families M Fang et al that affected PP traits.…”

Section: Discussionsupporting

confidence: 69%

“…For the first extra QTL, the position estimates were close to the marker ILSTS97, which was also reported by Moisio et al (2000) to affect the PP trait. For the second, the estimated position was close to CSN3 and CSN1, as reported by many researchers (Velmala et al, 1995;Maki-Tanila et al, 1998;Leone et al, 1998;Ikonen et al, 1999), and also close to AFR227, as reported by Velmala et al (1999), and to BP7, as reported by Ashwell et al (1998) and Schnabel et al (2005), all of which were found to affect the PP trait. The variance component model can be written as…”

Section: Discussionsupporting

confidence: 63%

“…Georges et al (1995) developed a maximum likelihood method for a single-family design and implemented it to map QTL for milk production traits in the US Holstein population. A regression method of interval mapping proposed by Knott et al (1996) has been commonly used to map QTL in half-sib families, particularly in dairy cattle (Spelman et al, 1996;Zhang et al, 1998;Heyen et al, 1999;Velmala et al, 1999;Nadesalingam et al, 2001;Plante et al, 2001;Ron et al, 2001;Freyer et al, 2002). Grignola et al (1996a, b) proposed a restricted maximum likelihood method for half-sib families, which was implemented by a number of investigators (for example, Zhang et al, 1998;Freyer et al, 2002;Liu et al, 2004).…”

Section: Introductionmentioning

confidence: 99%

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QTL mapping in outbred half-sib families using Bayesian model selection

Fang¹,

Liu²,

Sun³

et al. 2011

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In this article, we propose a model selection method, the Bayesian composite model space approach, to map quantitative trait loci (QTL) in a half-sib population for continuous and binary traits. In our method, the identity-by-descentbased variance component model is used. To demonstrate the performance of this model, the method was applied to map QTL underlying production traits on BTA6 in a Chinese half-sib dairy cattle population. A total of four QTLs were detected, whereas only one QTL was identified using the traditional least square (LS) method. We also conducted two simulation experiments to validate the efficiency of our method. The results suggest that the proposed method based on a multiple-QTL model is efficient in mapping multiple QTL for an outbred half-sib population and is more powerful than the LS method based on a single-QTL model.

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Section: Discussionsupporting

confidence: 69%

Section: Discussionsupporting

confidence: 63%

Section: Introductionmentioning

confidence: 99%

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QTL mapping in outbred half-sib families using Bayesian model selection

Fang¹,

Liu²,

Sun³

et al. 2011

Heredity

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“…The genes are organised in a cluster of approximately 250 kB [13,41] and share common transcription regulating elements [41]. The locus is considered to influence milk production traits [8,9,17,22,46] and antibacterial activities of derived peptides [29] may also affect the biological fitness of the offspring. Moreover, casein genes harbour a number of variants with suggested effects concerning traits such as the manufacturing properties of milk [1,35].…”

Section: Introductionmentioning

confidence: 99%

Geographic distribution of haplotype diversity at the bovine casein locus

et al. 2004

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-The genetic diversity of the casein locus in cattle was studied on the basis of haplotype analysis. Consideration of recently described genetic variants of the casein genes which to date have not been the subject of diversity studies, allowed the identification of new haplotypes. Genotyping of 30 cattle breeds from four continents revealed a geographically associated distribution of haplotypes, mainly defined by frequencies of alleles at CSN1S1 and CSN3. The genetic diversity within taurine breeds in Europe was found to decrease significantly from the south to the north and from the east to the west. Such geographic patterns of cattle genetic variation at the casein locus may be a result of the domestication process of modern cattle as well as geographically differentiated natural or artificial selection. The comparison of African Bos taurus and Bos indicus breeds allowed the identification of several Bos indicus specific haplotypes (CSN1S1*C-CSN2*A 2 -CSN3*A I / CSN3*H) that are not found in pure taurine breeds. The occurrence of such haplotypes in southern European breeds also suggests that an introgression of indicine genes into taurine breeds could have contributed to the distribution of the genetic variation observed.casein / haplotype / Bos taurus / Bos indicus / phylogeny

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“…The same QTLs were also discovered in other populations of Holstein cattle as well as in breeds such as Finnish Ayrshire (19) and Norwegian cattle (20). Ron et al (13) showed that the region containing the analyzed QTLs was located approximately 4 cM from the BM143 microsatellite, whereas Olsen et al (20), using physical mapping, combined linkage and LD mapping and determined the location of these QTLs.…”

Section: Discussionmentioning

confidence: 99%

Genetic polymorphisms of FAM13A1, OPN, LAP3, and HCAP-G genes in Jersey cattle

Umul

2013

Turk J Vet Anim Sci

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IntroductionStudies by numerous authors indicate that many bovine chromosomes (BTAs), including BTA3,6,9,14,20, and 23, in particular, bear clusters of quantitative trait loci (QTL) of different milk performance traits. In numerous reports the studies concentrated on BTA6 within 2 regions, in which clusters of genes associated with milk performance traits are located (1). These regions are the fragments in the middle part of BTA6, close to the BM143 marker, and the region close to the casein genes complex (2,3). Previous literature suggests that genes located near BM143 affect 5 milk performance traits, including milk yield (kg), milk protein and fat yield (kg), and milk protein and fat content (%) (1). The region encompassing these genes extends from the FAM13A (family with sequence similarity 13, member A1) to the PPARGC1A (peroxisome proliferator-activated receptor-γ coactivator-1α) genes and spans approximately 6.2 cM. In this range, there are genes whose effects on the performance traits of cattle have already been examined, such as OPN (osteopontin), and genes that may potentially influence these traits, such as FAM13A1, LAP3 (leucine aminopeptidase 3), and HCAP-G (condensin subunit 3) (4-6).Osteopontin (OPN) is a phosphorylated glycoprotein that plays a role in different processes in the organism, for example in cell adhesion, chemotaxis, cell signaling, and the regulation of growth and development of the fetus, as well as in the initiation and maintenance of pregnancy ( 7). The presence of OPN in milk and its high level of expression in mammary epithelial cells may cause proliferation and differentiation of the mammary gland (8). Despite fulfilling so many functions, OPN is treated by most authors as a positional candidate gene for milkperformance traits harboring the QTL region on BTA6 (9,10). Other studied genes do not play such an important role in the organism and, therefore, are considered first of all as positional candidate genes.It was suggested that the FAM13A1, LAP3, and HCAP-G genes may be associated with milk-performance traits such as milk yield and milk composition, mainly due to their location in the analyzed region and due to the fact that the expression levels of these genes were found to be different in the mammary gland (4,(11)(12)(13). Preliminary assessments of the association of these genes with milkperformance traits were reported (5,(11)(12)(13). For instance, the LAP3 gene may affect milk fat and protein yield, the FAM13A1 and LAP3 genes may affect the change in milk protein content, and the LAP3 gene has been associated with milk yield (5,(11)(12)(13).On the basis of the above-mentioned data, this research aimed at determining the allele and genotype frequencies of the single-nucleotide polymorphisms (SNPs) in the FAM13A1, OPN, LAP3, and HCAP-G genes in a herd of Jersey cows, as well as establishing possible associations between the genotypes and the milk-performance traits of the examined herd of cattle.

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A search for quantitative trait loci for milk production traits on chromosome 6 in Finnish Ayrshire cattle

Cited by 92 publications

References 22 publications

QTL mapping in outbred half-sib families using Bayesian model selection

QTL mapping in outbred half-sib families using Bayesian model selection

Geographic distribution of haplotype diversity at the bovine casein locus

Genetic polymorphisms of FAM13A1, OPN, LAP3, and HCAP-G genes in Jersey cattle

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