Quantitative Trait Loci Affecting Calving Traits in Danish Holstein Cattle

Thomasen, Jørn Rind; Guldbrandtsen, Bernt; Sørensen, Peter; Thomsen, Bo; Lund, Mogens Sandø

doi:10.3168/jds.2007-0602

Cited by 42 publications

(57 citation statements)

References 19 publications

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“…The first one, transmembrane protein 130 ( TMEM130 ) on BTA25 was also detected by Wu et al [38], that was associated with animal size and capacity in Chinese Holstein. Meanwhile, this gene is within a QTL region affecting calf size reported in Danish Holstein cattle[39]. In 2014, Zhao et al [40] has identified a selective signature in seven dairy and beef cattle breeds.…”

Section: Discussionmentioning

confidence: 99%

Genome-wide association studies identified multiple genetic loci for body size at four growth stages in Chinese Holstein cattle

Chu

Guo

et al. 2017

PLoS ONE

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The growth and maturity of cattle body size affect not only feed efficiency, but also productivity and longevity. Dissecting the genetic architecture of body size is critical for cattle breeding to improve both efficiency and productivity. The volume and weight of body size are indicated by several measurements. Among them, Heart Girth (HG) and Hip Height (HH) are the most important traits. They are widely used as predictors of body weight (BW). Few association studies have been conducted for HG and HH in cattle focusing on single growth stage. In this study, we extended the Genome-wide association studies to a full spectrum of four growth stages (6-, 12-, 18-, and 24-months after birth) in Chinese Holstein heifers. The whole genomic single nucleotide polymorphisms (SNPs) were obtained from the Illumina BovineSNP50 v2 BeadChip genotyped on 3,325 individuals. Estimated breeding values (EBVs) were derived for both HG and HH at the four different ages and analyzed separately for GWAS by using the Fixed and random model Circuitous Probability Unification (FarmCPU) method. In total, 27 SNPs were identified to be significantly associated with HG and HH at different growth stages. We found 66 candidate genes located nearby the associated SNPs, including nine genes that were known as highly related to development and skeletal and muscular growth. In addition, biological function analysis was performed by Ingenuity Pathway Analysis and an interaction network related to development was obtained, which contained 16 genes out of the 66 candidates. The set of putative genes provided valuable resources and can help elucidate the genomic architecture and mechanisms underlying growth traits in dairy cattle.

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Section: Discussionmentioning

confidence: 99%

Genome-wide association studies identified multiple genetic loci for body size at four growth stages in Chinese Holstein cattle

Chu

Guo

et al. 2017

PLoS ONE

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“…Another reason could be the family structure of the REF and VAL datasets. The REF population was from an earlier within-family linkage study for QTL mapping [14]. Therefore, in the REF we expect to have larger half sib families.…”

Section: Discussionmentioning

confidence: 99%

Analyzes of genome-wide association follow-up study for calving traits in dairy cattle

et al. 2012

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BackgroundThere is often a pronounced disagreement between results obtained from different genome-wide association studies in cattle. There are multiple reasons for this disagreement. Particularly the presence of false positives leads to a need to validate detected QTL before they are optimally incorporated or weighted in selection decisions or further studied for causal gene. In dairy cattle progeny testing scheme new data is routinely accumulated which can be used to validate previously discovered associations. However, the data is not an independent sample and the sample size may not be sufficient to have enough power to validate previous discoveries. Here we compared two strategies to validate previously detected QTL when new data is added from the same study population. We compare analyzing a combined dataset (COMB) including all data presently available to only analyzing a validation dataset (VAL) i.e. a new dataset not previously analyzed as an independent replication. Secondly, we confirm SNP detected in the Reference population (REF) (i.e. previously analyzed dataset consists of older bulls) in the VAL dataset.ResultsClearly the results from the combined (COMB) dataset which had nearly twice the sample size of other two subsets allowed the detection of far more significant associations than the two smaller subsets. The number of significant SNPs in REF (older bulls) was about four times higher compare to VAL (younger bulls) though both had similar sample sizes, 2,219 and 2,039 respectively. A total of 424 SNP-trait combinations on 22 chromosomes showed genome-wide significant association involving 284 unique SNPs in the COMB dataset. In the REF data set 101 associations (73 unique SNPs) and in the VAL 24 associations (18 unique SNPs) were found genome-wide significant. Sixty-eight percent of the SNPs in the REF dataset could be confirmed in the VAL dataset. Out of 469 unique SNPs showing chromosome-wide significant association with calving traits in the REF dataset 321 could be confirmed in the VAL dataset at P < 0.05.ConclusionsThe follow-up study for GWAS in cattle will depend on the aim of the study. If the aim is to discover novel QTL, analyses of the COMB dataset is recommended, while in case of identification of the causal mutation underlying a QTL, confirmation of the discovered SNPs are necessary to avoid following a false positive.

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“…This SNP is located within an intron of the TRPC1 gene, which was shown to regulate osteoblast formation in mice [114]. Cole et al [30] reported a common SNP (ss86324977) on chromosome 18 in an intronic region of the sialic acid-binding Ig-like lectin-5 (SIGLEC5) gene, associated with sire and daughter calving ease, that was also reported to affect direct calving traits in multiple studies [30,80,133,149]. In humans this gene is expressed in the placenta and has been suggested to have a role in the initiation of parturition [21].…”

Section: Genomic Regions and Genes Affecting Multiple Traits In Dairymentioning

confidence: 99%

Tissues, Metabolic Pathways and Genes of Key Importance in Lactating Dairy Cattle

Nayeri

Stothard

2016

Springer Science Reviews

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Milk and dairy products are valuable sources of food for humans. Increased milk yield and changes in milk composition in dairy cows have been achieved through a variety of means including better nutrition, management and genetic selection. This selection can be performed without consideration of the specific genes and genetic variation involved. However, association analysis using dense SNP genotyping panels provides an approach for identifying genomic regions affecting milk production. Coupling physiological and metabolic information with association analysis results can provide greater insight into the specific genetic variants and molecular mechanisms affecting production traits as well as the potential effects of these variants on fertility in dairy cattle. To this end, this review highlights key tissues, metabolic pathways and genes of importance in lactating dairy cattle, particularly early in lactation. Physiological and metabolic adaptations in three key tissues (adipose, mammary gland and liver) are discussed, followed by the important endocrine adaptations during negative energy balance. Key genes mediating metabolic and endocrine adaptations are also highlighted. Finally, genes that account for variation in production traits are presented in relation to the tissues and processes described. Knowledge of the genes and pathways involved will be important for ongoing efforts aimed at finding other genes and variants that contribute to milk production and fertility traits. Also, a better understanding of the molecular basis of these traits may lead to more accurate genomic predictions.

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Quantitative Trait Loci Affecting Calving Traits in Danish Holstein Cattle

Cited by 42 publications

References 19 publications

Genome-wide association studies identified multiple genetic loci for body size at four growth stages in Chinese Holstein cattle

Genome-wide association studies identified multiple genetic loci for body size at four growth stages in Chinese Holstein cattle

Analyzes of genome-wide association follow-up study for calving traits in dairy cattle

Tissues, Metabolic Pathways and Genes of Key Importance in Lactating Dairy Cattle

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