ArticleFrontiers in genetics2022
Genetic parameters and genome-wide association for milk production traits and somatic cell score in different lactation stages of Shanghai Holstein population.
Article in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 14 papers.
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14 citing papers in PubMed, 18 citations in OpenAlex.
- Integrated selection scans and cis-eQTL analyses reveal genes and variants associated with milk quality, immunity, and adaptation in endangered Dengchuan cattle.BMC genomics · 2026Article
- Integrative analysis of quantitative trait loci of alternative polyadenylation and GWAS highlights key regulators of milk production and immune traits in Holstein.Animal genetics · 2026Article
- Longitudinal Genome-Wide Association Study for Female Fertility Traits in German Holstein Cattle.Animal genetics · 2026Article
- Runs of homozygosity in Italian Holstein bulls: a permutation approach and time-based mapping of the genomic regions potentially under selection.BMC genomics · 2026Article
- Comprehensive assessment of lifetime performance traits and their genetic background in Holstein cows under semi-arid conditions.Tropical animal health and production · 2026Article
- Genome-wide identifications of regulatory variants influencing milk fat percentage in Chinese Holstein cow.BMC genomics · 2025Article
- Single-step genome-wide association study of milk somatic cell scores across multi-cattle breeds in Ethiopia.Animal biotechnology · 2025Article
- Estimation of Genetic Parameters and Stability for Milk Production Traits in Huaxi Cattle from the Xinjiang Region.Animals : an open access journal from MDPI · 2025Article
- Estimation of Genetic Parameters for Six Economic Traits in Beijing Holstein Cows.Veterinary medicine and science · 2025Article
- Genomic diversity of Cameroonian Gudali and Gudali-cross cattle.Scientific reports · 2025Article
- HSF1 and CPSF1 affect milk fat and protein synthesis by regulating the AKT/mTOR signaling pathway.Journal of animal science · 2025Article
- Genomic analysis uncovers novel candidate genes related to adaptation to tropical climates and milk production traits in native goats.BMC genomics · 2024Article
- Heritability estimates and genome-wide association study of methane emission traits in Nellore cattle.Journal of animal science · 2024Article
- Genome-wide association studies for milk production traits and persistency of first calving Holstein cattle in Türkiye.Frontiers in veterinary science · 2024Article
Corrections and comments
- Erratum issued
Authors and funding
11 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of this study was to investigate the genetic parameters and genetic architectures of six milk production traits in the Shanghai Holstein population. The data used to estimate the genetic parameters consisted of 1,968,589 test-day records for 305,031 primiparous cows. Among the cows with phenotypes, 3,016 cows were genotyped with Illumina Bovine SNP50K BeadChip, GeneSeek Bovine 50K BeadChip, GeneSeek Bovine LD BeadChip v4, GeneSeek Bovine 150K BeadChip, or low-depth whole-genome sequencing. A genome-wide association study was performed to identify quantitative trait loci and genes associated with milk production traits in the Shanghai Holstein population using genotypes imputed to whole-genome sequences and both fixed and random model circulating probability unification and a mixed linear model with rMVP software. Estimated heritabilities (h2) varied from 0.04 to 0.14 for somatic cell score (SCS), 0.07 to 0.22 for fat percentage (FP), 0.09 to 0.27 for milk yield (MY), 0.06 to 0.23 for fat yield (FY), 0.09 to 0.26 for protein yield (PY), and 0.07 to 0.35 for protein percentage (PP), respectively. Within lactation, genetic correlations for SCS, FP, MY, FY, PY, and PP at different stages of lactation estimated in random regression model were ranged from -0.02 to 0.99, 0.18 to 0.99, 0.04 to 0.99, 0.04 to 0.99, 0.01 to 0.99, and 0.33 to 0.99, respectively. The genetic correlations were highest between adjacent DIM but decreased as DIM got further apart. Candidate genes included those related to production traits (
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