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Identification of loci associated with conception rate in primiparous Holstein cows.

ABSTRACT: BACKGROUND:Subfertility is a major issue facing the dairy industry as the average US Holstein cow conception rate (CCR) is approximately 35%. The genetics underlying the physiological processes responsible for CCR, the proportion of cows able to conceive and maintain a pregnancy at each breeding, are not well characterized. The objectives of this study were to identify loci, positional candidate genes, and transcription factor binding sites (TFBS) associated with CCR and determine if there was a genetic correlation between CCR and milk production in primiparous Holstein cows. Cows were bred via artificial insemination (AI) at either observed estrus or timed AI and pregnancy status was determined at day 35 post-insemination. Additive, dominant, and recessive efficient mixed model association expedited (EMMAX) models were used in two genome-wide association analyses (GWAA). One GWAA focused on CCR at first service (CCR1) comparing cows that conceived and maintained pregnancy to day 35 after the first AI (n = 494) to those that were open after the first AI (n = 538). The second GWAA investigated loci associated with the number of times bred (TBRD) required for conception in cows that either conceived after the first AI (n = 494) or repeated services (n = 472). RESULTS:The CCR1 GWAA identified 123, 198, and 76 loci associated (P < 5 × 10- 08) in additive, dominant, and recessive models, respectively. The TBRD GWAA identified 66, 95, and 33 loci associated (P < 5 × 10- 08) in additive, dominant, and recessive models, respectively. Four of the top five loci were shared in CCR1 and TBRD for each GWAA model. Many of the associated loci harbored positional candidate genes and TFBS with putative functional relevance to fertility. Thirty-six of the loci were validated in previous GWAA studies across multiple breeds. None of the CCR1 or TBRD associated loci were associated with milk production, nor was their significance with phenotypic and genetic correlations to 305-day milk production. CONCLUSIONS:The identification and validation of loci, positional candidate genes, and TFBS associated with CCR1 and TBRD can be utilized to improve, and further characterize the processes involved in cattle fertility.

SUBMITTER: Kiser JN

PROVIDER: S-EPMC6852976 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundMastitis is a very common disease in the dairy industry that producers encounter daily. Transcriptomics, using RNA-Sequencing (RNA - Seq) technology, can be used to study the functional aspect of mastitis resistance to identify animals that have a better immune response to mastitis. When the cow has mastitis, not only genes but also specific mRNA isoforms generated via alternative splicing (AS) could be differentially expressed (DE), leading to the phenotypic variation observed. Therefore, the objective of this study was to use large gap read mapping to identify mRNA isoforms DE between healthy and mastitic milk somatic cell samples (N = 12). These mRNA isoforms were then categorized based on being 1) annotated mRNA isoforms for gene name and length, 2) annotated mRNA isoforms with different transcript length and 3) novel mRNA isoforms of non - annotated genes.ResultsAnalysis identified 333 DE transcripts (with at least 2 mRNA isoforms annotated, with at least one being DE) between healthy and mastitic samples corresponding to 303 unique genes. Of these 333 DE transcripts between healthy and mastitic samples, 68 mRNA isoforms are annotated in the bovine genome reference (ARS.UCD.1.2), 249 mRNA isoforms had novel transcript lengths of known genes and 16 were novel transcript lengths of non - annotated genes in the bovine genome reference (ARS.UCD.1.2). Functional analysis including gene ontology, gene network and metabolic pathway analysis was performed on the list of 288 annotated and unique DE mRNA isoforms. In total, 67 significant metabolic pathways were identified including positive regulation of cytokine secretion and immune response. Additionally, numerous DE novel mRNA isoforms showed potential involvement with the immune system or mastitis. Lastly, QTL annotation analysis was performed on coding regions of the DE mRNA isoforms, identifying overlapping QTLs associated with clinical mastitis and somatic cell score.ConclusionThis study identified novel mRNA isoforms generated via AS that could lead to differences in the immune response of Holstein dairy cows and be potentially implemented in future breeding programs.

Project description:Mitigation of greenhouse gas emissions is relevant for reducing the environmental impact of ruminant production. In this study, the rumen microbiome from Holstein cows was characterized through a combination of 16S rRNA gene and shotgun metagenomic sequencing. Methane production (CH4 ) and dry matter intake (DMI) were individually measured over 4-6 weeks to calculate the CH4 yield (CH4 y = CH4 /DMI) per cow. We implemented a combination of clustering, multivariate and mixed model analyses to identify a set of operational taxonomic unit (OTU) jointly associated with CH4 y and the structure of ruminal microbial communities. Three ruminotype clusters (R1, R2 and R3) were identified, and R2 was associated with higher CH4 y. The taxonomic composition on R2 had lower abundance of Succinivibrionaceae and Methanosphaera, and higher abundance of Ruminococcaceae, Christensenellaceae and Lachnospiraceae. Metagenomic data confirmed the lower abundance of Succinivibrionaceae and Methanosphaera in R2 and identified genera (Fibrobacter and unclassified Bacteroidales) not highlighted by metataxonomic analysis. In addition, the functional metagenomic analysis revealed that samples classified in cluster R2 were overrepresented by genes coding for KEGG modules associated with methanogenesis, including a significant relative abundance of the methyl-coenzyme M reductase enzyme. Based on the cluster assignment, we applied a sparse partial least-squares discriminant analysis at the taxonomic and functional levels. In addition, we implemented a sPLS regression model using the phenotypic variation of CH4 y. By combining these two approaches, we identified 86 discriminant bacterial OTUs, notably including families linked to CH4 emission such as Succinivibrionaceae, Ruminococcaceae, Christensenellaceae, Lachnospiraceae and Rikenellaceae. These selected OTUs explained 24% of the CH4 y phenotypic variance, whereas the host genome contribution was ~14%. In summary, we identified rumen microbial biomarkers associated with the methane production of dairy cows; these biomarkers could be used for targeted methane-reduction selection programmes in the dairy cattle industry provided they are heritable.

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Identification of loci associated with conception rate in primiparous Holstein cows.

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