Genome-wide association analysis in Italian Simmental cows for lactation curve traits using a low-density (7K) SNP panel

Abstract

High-throughput cow genotyping has opened new perspectives for genome-wide association studies (GWAS). Directly recorded phenotypes and several records per animal could be used. In this study, a GWAS on lactation curve traits of 337 Italian Simmental cows genotyped with the Illumina (San Diego, CA) low-density BeadChip (7K) was carried out. Scores of the first 2 principal components extracted from test-day records (7 for each lactation) for milk yield, fat and protein percentages, and somatic cell score were used as phenotypes. The first component described the average level of the lactation curve, whereas the second summarized its shape. Data were analyzed with a mixed linear model that included fixed effects of herd, calving month, calving year, parity, SNP genotype, and random effects of animal and permanent environment. All statistically significant markers (Bonferroni corrected) were associated with the average level component (2 for milk yield, 9 for fat percentage, 6 for protein percentages, and 1 for somatic cell score). No markers were found to be associated with the lactation curve shape. Gene discovery was performed using windows of variable size, according to the linkage disequilibrium level of the specific genomic region. Several suggestive candidate genes were identified, some of which already reported to be associated with dairy traits, such as DGAT1. Others were involved in lipid metabolism, in protein synthesis, in the immune response, in cellular processes, and in early development. The large number of genes flagged in the present study suggests interesting perspectives for the use of low-density genotyped females for GWAS, also for novel phenotypes that are not currently considered as breeding goals.

Genome-wide association study of milk fatty acid composition in Italian Simmental and Italian Holstein cows using single nucleotide polymorphism arrays

“…A GWAS approach was used to identify QTL affecting milk FA composition in IS and IH cows and to assess genetic differences or similarities between those 2 breeds. In this regard, this is the first GWAS on FA composition in IS because other similar studies focused on either milk production and related quality traits (Capomaccio et al, 2015a) or the lactation curve (Macciotta et al, 2015).…”

Genome wide association study on beef production traits in Marchigiana cattle breed

“…Windows of variable amplitude in Mb were defined based on linkage disequilibrium of the specific genomic region (Macciotta et al . ). For each significant SNP, the squared coefficient ( r 2 ) statistic with all other SNPs positioned in the same chromosome was calculated (Table S1).…”

Invited review: Advances and applications of random regression models: From quantitative genetics to genomics

“…Another alternative approach for GWAS of longitudinal traits is principal component analysis, in which the scores of a reduced number of principal components based on multiple variables (e.g., longitudinal records) can be used as a "single phenotype" when performing the GWAS analysis. As indicated by Macciotta et al (2015), these model-free approaches are able to derive measures of lactation curve (or other longitudinal trait) traits without specific assumptions on data structure. For instance, Macciotta et al (2015) performed a GWAS using the scores of the first 2 principal components from test-day records for milk yield, fat and protein percentages, and SCS as the response variables for GWAS analyses.…”

“…As indicated by Macciotta et al (2015), these model-free approaches are able to derive measures of lactation curve (or other longitudinal trait) traits without specific assumptions on data structure. For instance, Macciotta et al (2015) performed a GWAS using the scores of the first 2 principal components from test-day records for milk yield, fat and protein percentages, and SCS as the response variables for GWAS analyses.…”