Associations between polymorphisms of SLC22A7, NGFR, ARNTL and PPP2R2B genes and Milk production traits in Chinese Holstein

Identification of Genetic Associations of IDH2, LDHA, and LDHB Genes with Milk Yield and Compositions in Dairy Cows

Previous study revealed that isocitrate dehydrogenase (NADP (+)) 2, mitochondrial (IDH2), lactate dehydrogenase A (LDHA), and lactate dehydrogenase B (LDHB) genes were significantly differentially expressed in liver tissues of Holstein cows among different lactation periods and associated with lipid and protein metabolism; hence, they were considered as candidates for milk production traits. Herein, the genetic effects of the three genes on milk yield, fat, and protein traits were studied by association analysis using 926 Chinese Holstein cows from 45 sire families. As a result, five single nucleotide polymorphisms (SNPs) in IDH2, one in LDHA, and three in LDHB were identified by re-sequencing, and subsequently, they were genotyped in 926 Chinese Holstein cows by genotyping by target sequencing (GBTS). With the animal model, single-locus association analysis revealed that four SNPs in IDH2 and one SNP in LDHA were significantly associated with milk, fat, and protein yields (p ≤ 0.0491), and three SNPs in LDHB were associated with milk yield, milk fat yield, and fat percentage (p ≤ 0.0285). Further, four IDH2 SNPs were found to form a haplotype block significantly associated with milk yield, fat yield, protein yield, and protein percentage (p ≤ 0.0249). In addition, functional predictions indicated that one SNP in LDHA, g.26304153G>A, may affect transcription factor binding and two SNPs, g.88544541A>G and g.88556310T>C could alter LDHB mRNA secondary structure. In summary, this study profiled the significant genetic effects of IDH2, LDHA, and LDHB on milk yield and composition traits and provided referable genetic markers for genomic selection programs in dairy cattle.

A Comparative Analysis of the Gene Expression Profiles in the Mammary Glands of Lactating and Nonlactating Mares at the Second Month of Gestation

To investigate molecular regulation involved in lactation during pregnancy, this study focused on the transcriptomic profiles of mammary tissue from lactating and non-lactating Mongolian mares at the second month of gestation. A total of 4197 differentially expressed genes were identified by comparing mammary tissues from pregnant mares at two different states, including 1974 differentially expressed genes such as the milk protein-related genes a-s1-casein (CSN1S1), k-casein (CSN3), lactalbumin (LALBA), and lactoferrin (LTF), which were highly expressed in the lactating mares group, and overall, these differentially expressed genes were mainly associated with biological processes such as endoplasmic reticulum protein processing, the Toll-like receptor signaling pathway, steroid biosynthesis, cytokine-cytokine receptor interactions, and amino sugar and nucleotide glycolysis. These findings serve as a foundation for investigating the molecular underpinnings of lactation in pregnant equids.

Genetic marker identification of SEC13 gene for milk production traits in Chinese holstein

SEC13 homolog, nuclear pore and COPII coat complex component (SEC13) is the core component of the cytoplasmic COPII complex, which mediates material transport from the endoplasmic reticulum to the Golgi complex. Our preliminary work found that SEC13 gene was differentially expressed in dairy cows during different stages of lactation, and involved in metabolic pathways of milk synthesis such as citric acid cycle, fatty acid, starch and sucrose metabolisms, so we considered that the SEC13 might be a candidate gene affecting milk production traits. In this study, we detected the polymorphisms of SEC13 gene and verified their genetic effects on milk yield and composition traits in a Chinese Holstein cow population. By sequencing the whole coding and partial flanking regions of SEC13, we found four single nucleotide polymorphisms (SNPs). Subsequent association analysis showed that these four SNPs were significantly associated with milk yield, fat yield, protein yield or protein percentage in the first and second lactations (p ≤.0351). We also found that two SNPs in SEC13 formed one haplotype block by Haploview4.2, and the block was significantly associated with milk yield, fat yield, fat percentage, protein yield or protein percentage (p ≤ .0373). In addition, we predicted the effect of SNP on 5'region on transcription factor binding sites (TFBSs), and found that the allele A of 22:g.54362761A>G could bind transcription factors (TFs) GATA5, GATA3, HOXD9, HOXA10, CDX1 and Hoxd13; and further dual-luciferase reporter assay verified that the allele A of this SNP inhibited the fluorescence activity. We speculate that the A allele of 22:g.54362761A>G might inhibit the transcriptional activity of SEC13 gene by binding the TFs, which may be a cause mutation affecting the formation of milk production traits in dairy cows. In summary, we proved that SEC13 has a significant genetic effect on milk production traits and the identified significant SNPs could be used as candidate genetic markers for GS SNP chips development; on the other hand, we verified the transcriptional regulation of 22:g.54362761A>G on SEC13 gene, providing research direction for further function validation tests.

GWAS of Reproductive Traits in Large White Pigs on Chip and Imputed Whole-Genome Sequencing Data

Total number born (TNB), number of stillborn (NSB), and gestation length (GL) are economically important traits in pig production, and disentangling the molecular mechanisms associated with traits can provide valuable insights into their genetic structure. Genotype imputation can be used as a practical tool to improve the marker density of single-nucleotide polymorphism (SNP) chips based on sequence data, thereby dramatically improving the power of genome-wide association studies (GWAS). In this study, we applied Beagle software to impute the 50 K chip data to the whole-genome sequencing (WGS) data with average imputation accuracy (R2) of 0.876. The target pigs, 2655 Large White pigs introduced from Canadian and French lines, were genotyped by a GeneSeek Porcine 50K chip. The 30 Large White reference pigs were the key ancestral individuals sequenced by whole-genome resequencing. To avoid population stratification, we identified genetic variants associated with reproductive traits by performing within-population GWAS and cross-population meta-analyses with data before and after imputation. Finally, several genes were detected and regarded as potential candidate genes for each of the traits: for the TNB trait: NOTCH2, KLF3, PLXDC2, NDUFV1, TLR10, CDC14A, EPC2, ORC4, ACVR2A, and GSC; for the NSB trait: NUB1, TGFBR3, ZDHHC14, FGF14, BAIAP2L1, EVI5, TAF1B, and BCAR3; for the GL trait: PPP2R2B, AMBP, MALRD1, HOXA11, and BICC1. In conclusion, expanding the size of the reference population and finding an optimal imputation strategy to ensure that more loci are obtained for GWAS under high imputation accuracy will contribute to the identification of causal mutations in pig breeding.

Single Nucleotide Polymorphisms of ALDH18A1 and MAT2A Genes and Their Genetic Associations with Milk Production Traits of Chinese Holstein Cows

Our preliminary work had suggested two genes, aldehyde dehydrogenase 18 family member A1 (ALDH18A1) and methionine adenosyltransferase 2A (MAT2A), related to amino acid synthesis and metabolism as candidates affecting milk traits by analyzing the liver transcriptome and proteome of dairy cows at different lactation stages. In this study, the single nucleotide polymorphisms (SNPs) of ALDH18A1 and MAT2A genes were identified and their genetic effects and underlying causative mechanisms on milk production traits in dairy cattle were analyzed, with the aim of providing effective genetic information for the molecular breeding of dairy cows. By resequencing the entire coding and partial flanking regions of ALDH18A1 and MAT2A, we found eight SNPs located in ALDH18A1 and two in MAT2A. Single-SNP association analysis showed that most of the 10 SNPs of these two genes were significantly associated with the milk yield traits, 305-day milk yield, fat yield, and protein yield in the first and second lactations (corrected p ≤ 0.0488). Using Haploview 4.2, we found that the seven SNPs of ALDH18A1 formed two haplotype blocks; subsequently, the haplotype-based association analysis showed that both haplotypes were significantly associated with 305-day milk yield, fat yield, and protein yield (corrected p ≤ 0.014). Furthermore, by Jaspar and Genomatix software, we found that 26:g.17130318 C>A and 11:g.49472723G>C, respectively, in the 5′ flanking region of ALDH18A1 and MAT2A genes changed the transcription factor binding sites (TFBSs), which might regulate the expression of corresponding genes to affect the phenotypes of milk production traits. Therefore, these two SNPs were considered as potential functional mutations, but they also require further verification. In summary, ALDH18A1 and MAT2A were proved to probably have genetic effects on milk production traits, and their valuable SNPs might be used as candidate genetic markers for dairy cattle’s genomic selection (GS).