Systematic characterization of the molecular states of cells in livestock tissues is essential for understanding the cellular and genetic mechanisms underlying economically and ecologically important physiological traits. Here, as part of the Farm Animal Genotype-Tissue Expression (FarmGTEx) project, we describe a comprehensive reference map including 1,793,854 cells from 59 bovine tissues in calves and adult cattle, spanning both sexes, which reveals intra-tissue and inter-tissue cellular heterogeneity in gene expression, transcription factor regulation and intercellular communication. Integrative analysis with genetic variants that underpin bovine monogenic and complex traits uncovers cell types of relevance, such as spermatocytes, responsible for sperm motility and excitatory neurons for milk fat yield. Comparative analysis reveals similarities in gene expression between cattle and humans, allowing for the detection of relevant cell types to study human complex phenotypes. This Cattle Cell Atlas will serve as a key resource for cattle genetics and genomics, selective breeding and comparative biology.

Our initial RNA sequencing work identified that lipin 1 (LPIN1) was differentially expressed during dry period, early lactation, and peak of lactation in dairy cows, and it was enriched into the fat metabolic Gene Ontology (GO) terms and pathways, thus we considered LPIN1 as the candidate gene for milk production traits. In this study, we detected the polymorphisms of LPIN1 and verified their genetic effects on milk yield and composition in a Chinese Holstein cow population. We found seven SNPs by re-sequencing the entire coding region and partial flanking region of LPIN1, including one in 5′ flanking region, four in exons, and two in 3′ flanking region. Of these, four SNPs, c.637T > C, c.708A > G, c.1521C > T, and c.1555A > C, in the exons were predicted to result in the amino acid replacements. With the Haploview 4.2, we found that seven SNPs in LPIN1 formed two haplotype blocks (D′ = 0.98–1.00). Single-SNP association analyses showed that SNPs were significantly associated with milk yield, fat yield, fat percentage, or protein yield in the first or second lactation (p = < 0.0001–0.0457), and only g.86049389C > T was strongly associated with protein percentage in both lactations (p = 0.0144 and 0.0237). The haplotype-based association analyses showed that the two haplotype blocks were significantly associated with milk yield, fat yield, protein yield, or protein percentage (p = < 0.0001–0.0383). By quantitative real-time PCR (qRT-PCR), we found that LPIN1 had relatively high expression in mammary gland and liver tissues. Furthermore, we predicted three SNPs, c.637T > C, c.708A > G, and c.1521C > T, using SOPMA software, changing the LPIN1 protein structure that might be potential functional mutations. In summary, we demonstrated the significant genetic effects of LPIN1 on milk production traits, and the identified SNPs could serve as genetic markers for dairy breeding.

We previously conducted a genome-wide association study (GWAS) strategy for milk fatty acids in Chinese Holstein, and identified 83 genome-wide significant single nucleotide polymorphisms (SNPs) and 314 suggestive significant SNPs. Among them, two SNPs, BTB-01077939 and BTA-11275-no-rs associated with C10:0, C12:0, and C14 index (P = 0.000014 ~ 0.000024), were within and close to (0.85 Mb) protein kinase, cGMP-dependent, type І (PRKG1) gene on BTA26, respectively. PRKG1 gene plays a key role in lipolysis to release fatty acids and glycerol through the hydrolysis of triacyglycerol in adipocytes. We herein considered it as a promising candidate for milk fatty acids. The purpose of this study was to investigate whether PRKG1 had effects on milk fatty acids. By direct sequencing the PCR products of pooled DNA, we identified a total of six SNPs, including one in 5′ flanking region, four in 3′ untranslated region (UTR), and one in 3′ flanking region. The single-locus association analysis was carried out, and showed that the six SNPs mainly had significant associations with C6:0, C8:0 and C17:1 (P < 0.0001 ~ 0.0035). In addition, we observed a haplotype block formed by g.6903810G > A and g.6904047G > T with Haploview 4.1, and it was strongly associated with C8:0, C10:0, C16:1, C17:1, C20:0 and C16 index (P = < 0.0001 ~ 0.0123). The SNP, g.8344262A > T, was predicted to alter the binding site (BS) of transcription factor (TF) GAGA box with Genomatix software, and the subsequent luciferase assay verified that it really changed the transcriptional activity of PRKG1 gene (P = 0.0009). In conclusion, to our best of knowledge, we are the first who identified the significant effects of PRKG1 on milk fatty acids in dairy cattle.

Our previous work had confirmed that pyruvate kinase L/R (PKLR) gene was expressed differently in different lactation periods of dairy cattle, and participated in lipid metabolism through insulin, PI3K-Akt, MAPK, AMPK, mTOR, and PPAR signaling pathways, suggesting that PKLR is a candidate gene to affect milk production traits in dairy cattle. Here, we verified whether this gene has significant genetic association with milk yield and composition traits in a Chinese Holstein cow population. In total, we identified 21 single nucleotide polymorphisms (SNPs) by resequencing the entire coding region and partial flanking region of PKLR gene, in which, two SNPs were located in 5′ promoter region, two in 5′ untranslated region (UTR), three in introns, five in exons, six in 3′ UTR and three in 3′ flanking region. The single marker association analysis displayed that all SNPs were significantly associated with milk yield, fat and protein yields or protein percentage (p ≤ 0.0497). The haplotype block containing all the SNPs, predicted by Haploview, had a significant association with fat yield and protein percentage (p ≤ 0.0145). Further, four SNPs in 5′ regulatory region and eight SNPs in UTR and exon regions were predicted to change the transcription factor binding sites (TFBSs) and mRNA secondary structure, respectively, thus affecting the expression of PKLR, leading to changes in milk production phenotypes, suggesting that these SNPs might be the potential functional mutations for milk production traits in dairy cattle. In conclusion, we demonstrated that PKLR had significant genetic effects on milk production traits, and the SNPs with significant genetic effects could be used as candidate genetic markers for genomic selection (GS) in dairy cattle.