Genome-wide association analysis and gene set enrichment analysis with SNP data identify genes associated with 305-day milk yield in Holstein dairy cows

Exome-wide comparative analyses revealed differentiating genomic regions for performance traits in Indian native buffaloes

In India, 20 breeds of buffalo have been identified and registered, yet limited studies have been conducted to explore the performance potential of these breeds, especially in the Indian native breeds. This study is a maiden attempt to delineate the important variants and unique genes through exome sequencing for milk yield, milk composition, fertility, and adaptation traits in Indian local breeds of buffalo. In the present study, whole exome sequencing was performed on Chhattisgarhi (n = 3), Chilika (n = 4), Gojri (n = 3), and Murrah (n = 4) buffalo breeds and after stringent quality control, 4333, 6829, 4130, and 4854 InDels were revealed, respectively. Exome-wide FST along 100-kb sliding windows detected 27, 98, 38, and 35 outlier windows in Chhattisgarhi, Chilika, Gojri, and Murrah, respectively. The comparative exome analysis of InDels and subsequent gene ontology revealed unique breed specific genes for milk yield (CAMSAP3), milk composition (CLCN1, NUDT3), fertility (PTGER3) and adaptation (KCNA3, TH) traits. Study provides insight into mechanism of how these breeds have evolved under natural selection, the impact of these events on their respective genomes, and their importance in maintaining purity of these breeds for the traits under study. Additionally, this result will underwrite to the genetic acquaintance of these breeds for breeding application, and in understanding of evolution of these Indian local breeds.

Weighted single step GWAS reveals genomic regions associated with economic traits in Murrah buffaloes

The objective of the present study was to identify genomic regions influencing economic traits in Murrah buffaloes using weighted single step Genome Wide Association Analysis (WssGWAS). Data on 2000 animals, out of which 120 were genotyped using a double digest Restriction site Associated DNA (ddRAD) sequencing approach. The phenotypic data were collected from NDRI, India, on growth traits, viz., body weight at 6M (month), 12M, 18M and 24M, production traits like 305D (day) milk yield, lactation length (LL) and dry period (DP) and reproduction traits like age at first calving (AFC), calving interval (CI) and first service period (FSP). The biallelic genotypic data consisted of 49353 markers post-quality check. The heritability estimates were moderate to high, low to moderate, low for growth, production, reproduction traits, respectively. Important genomic regions explaining more than 0.5% of the total additive genetic variance explained by 30 adjacent SNPs were selected for further analysis of candidate genes. In this study, 105 genomic regions were associated with growth, 35 genomic regions with production and 42 window regions with reproduction traits. Different candidate genes were identified in these genomic regions, of which important are OSBPL8, NAP1L1 for growth, CNTNAP2 for production and ILDR2, TADA1 and POGK for reproduction traits.

Single-step genome-wide association analyses for milk urea concentration in Walloon Holstein cows

The aims of this study were to conduct a single-step genome-wide association to identify genomic regions associated with milk urea (MU) and to estimate genetic correlations between MU and milk yield (MY), milk composition (calcium content [CC], fat percentage [FP], protein percentage [PP], and casein percentage [CNP]), and cheese-making properties (CMP; coagulation time [CT], curd firmness after 30 min from rennet addition [a30], and titratable acidity [TA]). The used data have been collected from 2015 to 2020 on 78,073 first-parity (485,218 test-day records) and 48,766 second-parity (284,942 test-day records) Holstein cows distributed in 671 herds in the Walloon Region of Belgium. Data of 565,533 SNP located on 29 BTA of 6,617 animals (1,712 males) were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method. The SNP solutions were estimated using a single-step genomic BLUP approach. The proportion of the total additive genetic variance explained by windows of 50 consecutive SNPs (with an average size of ∼216 kb) was calculated, and the top-3 genomic regions explaining the largest rate of the genetic variance were considered promising regions and used to identify potential candidate genes. Mean (SD) MU was 25.38 (8.02) mg/dL and 25.03 (8.06) mg/dL in the first and second lactation, respectively. Mean heritability estimates for daily MU were 0.21 and 0.23 for the first and second lactation, respectively. The genetic correlations estimated between MU and MY, milk composition, and CMP were quite low (ranged from -0.10 [CC] to 0.10 [TA] and -0.05 [CT] to 0.13 [TA] for the first and second lactations, respectively). The top-3 regions associated with MU were located from 80.61 to 80.74 Mb on BTA6, 103.26 to 103.41 Mb on BTA11, and 1.59 to 2.15 Mb on BTA14. Genes including KCNT1, MROH1, SHARPIN, TSSK5, CPSF1, HSF1, TONSL, DGAT1, SCX, and MAF1 were identified as positional candidate genes for MU. The findings of this study can be used for a better understanding of the genomic architecture underlying MU in Holstein cattle.

Identification of genetic variants affecting reproduction traits in Vrindavani cattle

Genome-wide association studies (GWAS) are one of the best ways to look into the connection between single-nucleotide polymorphisms (SNPs) and the phenotypic performance. This study aimed to identify the genetic variants that significantly affect the important reproduction traits in Vrindavani cattle using genome-wide SNP chip array data. In this study, 96 randomly chosen Vrindavani cows were genotyped using the Illumina Bovine50K BeadChip platform. A linear regression model of the genome-wide association study was fitted in the PLINK program between genome-wide SNP markers and reproduction traits, including age at first calving (AFC), inter-calving period (ICP), dry days (DD), and service period (SP) across the first three lactations. Information on different QTLs and genes, overlapping or adjacent to genomic coordinates of significant SNPs, was also mined from relevant databases in order to identify the biological pathways associated with reproductive traits in bovine. The Bonferroni correction resulted in total 39 SNP markers present on different chromosomes being identified that significantly affected the variation in AFC (6 SNPs), ICP (7 SNPs), DD (9 SNPs), and SP (17 SNPs). Novel potential candidate genes associated with reproductive traits that were identified using the GWAS methodology included UMPS, ITGB5, ADAM2, UPK1B, TEX55, bta-mir-708, TMPO, TDRD5, MAPRE2, PTER, AP3B1, DPP8, PLAT, TXN2, NDUFAF1, TGFA, DTNA, RSU1, KCNQ1, ADAM32, and CHST8. The significant SNPs and genes associated with the reproductive traits and the enriched genes may be exploited as candidate biomarkers in animal improvement programs, especially for improved reproduction performance in bovines.

Polymorphisms of CCSER1 Gene and Their Correlation with Milk Quality Traits in Gannan Yak (Bos grunniens)

Coiled-coil serine-rich protein 1 (CCSER 1) gene is a regulatory protein gene. This gene has been reported to be associated with various economic traits in large mammals in recent years. The aim of this study was to investigate the association between CCSER1 gene single nucleotide polymorphisms (SNPs) and Gannan yaks and to identify potential molecular marker loci for breeding milk quality in Gannan yaks. We genotyped 172 Gannan yaks using Illumina Yak cGPS 7K liquid microarrays and analyzed the correlation between the three SNPs loci of the CCSER1 gene and the milk qualities of Gannan yaks, including milk fat, protein and casein. It was found that mutations at the g.183,843A>G, g.222,717C>G and g.388,723G>T loci all affected the fat, protein, casein and lactose traits of Gannan yak milk to varying extents, and that the milk quality of individuals with mutant phenotypes was significantly improved. Among them, the milk fat content of AG heterozygous genotype population at g.183,843A>G locus was significantly higher than that of AA and GG genotype populations (p < 0.05); the casein and protein content of mutant GG and CG genotype populations at g.222,717C>G locus was significantly higher than that of wild-type CC genotype population (p < 0.05); and the g.388,723G>T locus of the casein and protein contents of the mutant TT genotype population were significantly higher (p < 0.05) than those of the wild-type GG genotype population. These results provide potential molecular marker sites for Gannan yak breeding.

Single-step genome-wide association analyses for selected infrared-predicted cheese-making traits in Walloon Holstein cows

This study aimed to perform genome-wide association study to identify genomic regions associated with milk production and cheese-making properties (CMP) in Walloon Holstein cows. The studied traits were milk yield, fat percentage, protein percentage, casein percentage (CNP), calcium content, somatic cell score (SCS), coagulation time, curd firmness after 30 min from rennet addition, and titratable acidity. The used data have been collected from 2014 to 2020 on 78,073 first-parity (485,218 test-day records), 48,766 second-parity (284,942 test-day records), and 21,948 third-parity (105,112 test-day records) Holstein cows distributed in 671 herds in the Walloon Region of Belgium. Data of 565,533 single nucleotide polymorphisms (SNP), located on 29 Bos taurus autosomes (BTA) of 6,617 animals (1,712 males), were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method. The SNP solutions were estimated using a single-step genomic BLUP approach. The proportion of the total additive genetic variance explained by windows of 50 consecutive SNPs (with an average size of ∼216 KB) was calculated, and regions accounting for at least 1.0% of the total additive genetic variance were used to search for positional candidate genes. Heritability estimates for the studied traits ranged from 0.10 (SCS) to 0.53 (CNP), 0.10 (SCS) to 0.50 (CNP), and 0.12 (SCS) to 0.49 (CNP) in the first, second, and third parity, respectively. Genome-wide association analyses identified 6 genomic regions (BTA1, BTA14 [4 regions], and BTA20) associated with the considered traits. Genes including the SLC37A1 (BTA1), SHARPIN, MROH1, DGAT1, FAM83H, TIGD5, MROH6, NAPRT, ADGRB1, GML, LYPD2, JRK (BTA14), and TRIO (BTA20) were identified as positional candidate genes for the studied CMP. The findings of this study help to unravel the genomic background of a cow's ability for cheese production and can be used for the future implementation and use of genomic evaluation to improve the cheese-making traits in Walloon Holstein cows.

Identification of Candidate Genes and Functional Pathways Associated with Body Size Traits in Chinese Holstein Cattle Based on GWAS Analysis

Body size is one of the most economically important traits of dairy cattle, as it is significantly associated with cow longevity, production, health, fertility, and environmental adaptation. The identification and application of genetic variants using a novel genetic approach, such as genome-wide association studies (GWASs), may give more insights into the genetic architecture of complex traits. The identification of genes, single nucleotide polymorphisms (SNPs), and pathways associated with the body size traits may offer a contribution to genomic selection and long-term planning for selection in dairy cows. In this study, we performed GWAS analysis to identify the genetic markers and genes associated with four body size traits (body height, body depth, chest width, and angularity) in 1000 Chinese Holstein cows. We performed SNPs genotyping in 1000 individuals, based on the GeneSeek Genomic Profiler Bovine 100 K. In total, we identified 11 significant SNPs in association with body size traits at the threshold of Bonferroni correction (5.90 × 10−7) using the fixed and random model circulating probability unification (FarmCPU) model. Several genes within 200 kb distances (upstream or downstream) of the significant SNPs were identified as candidate genes, including MYH15, KHDRBS3, AIP, DCC, SQOR, and UBAP1L. Moreover, genes within 200 kb of the identified SNPs were significantly enriched (p ≤ 0.05) in 25 Gene Ontology terms and five Kyoto Encyclopedia of Genes and Genomes pathways. We anticipate that these results provide a foundation for understanding the genetic architecture of body size traits. They will also contribute to breeding programs and genomic selection work on Chinese Holstein cattle.

Longitudinal genome-wide association studies of milk production traits in Holstein cattle using whole-genome sequence data imputed from medium-density chip data

Longitudinal traits, such as milk production traits in dairy cattle, are featured by having phenotypic values at multiple time points, which change dynamically over time. In this study, we first imputed SNP chip (50-100K) data to whole-genome sequence (WGS) data in a Chinese Holstein population consisting of 6,470 cows. The imputation accuracies were 0.88 to 0.97 on average after quality control. We then performed longitudinal GWAS in this population based on a random regression test-day model using the imputed WGS data. The longitudinal GWAS revealed 16, 39, and 75 quantitative trait locus regions associated with milk yield, fat percentage, and protein percentage, respectively. We estimated the 95% confidence intervals (CI) for these quantitative trait locus regions using the logP drop method and identified 581 genes involved in these CI. Further, we focused on the CI that covered or overlapped with only 1 gene or the CI that contained an extremely significant top SNP. Twenty-eight candidate genes were identified in these CI. Most of them have been reported in the literature to be associated with milk production traits, such as DGAT1, HSF1, MGST1, GHR, ABCG2, ADCK5, and CSN1S1. Among the unreported novel genes, some also showed good potential as candidate genes, such as CCSER1, CUX2, SNTB1, RGS7, OSR2, and STK3, and are worth being further investigated. Our study provided not only new insights into the candidate genes for milk production traits, but also a general framework for longitudinal GWAS based on random regression test-day model using WGS data.

Effects of sustained hyperprolactinemia in late gestation on the mammary parenchymal tissue transcriptome of gilts

BACKGROUND

Gilts experiencing sustained hyperprolactinemia from d 90 to 109 of gestation showed an early onset of lactogenesis coupled with premature mammary involution. To better understand the molecular mechanisms underlying the premature mammary involution observed in these gilts, a transcriptomic analysis was undertaken. Therefore, this study aimed to explore the effect of hyperprolactinemia on the global transcriptome in the mammary tissue of late gestating gilts and identify the molecular pathways involved in triggering premature mammary involution.

METHODS

On d 90 of gestation, gilts received daily injections of (1) canola oil until d 109 ± 1 of gestation (CTL, n = 18); (2) domperidone (to induce hyperprolactinemia) until d 96 ± 1 of gestation (T7, n = 17) or; (3) domperidone (until d 109 ± 1 of gestation (T20, n = 17). Mammary tissue was collected on d 110 of gestation and total RNA was isolated from six CTL and six T20 gilts for microarray analysis. The GeneChip® Porcine Gene 1.0 ST Array was used for hybridization. Functional enrichment analyses were performed to explore the biological significance of differentially expressed genes, using the DAVID bioinformatics resource.

RESULTS

The expression of 335 genes was up-regulated and that of 505 genes down-regulated in the mammary tissue of T20 vs CTL gilts. Biological process GO terms and KEGG pathways enriched in T20 vs CTL gilts reflected the concurrent premature lactogenesis and mammary involution. When looking at individual genes, it appears that mammary cells from T20 gilts can simultaneously upregulate the transcription of milk proteins such as WAP, CSN1S2 and LALBA, and genes triggering mammary involution such as STAT3, OSMR and IL6R. The down-regulation of PRLR expression and up-regulation of genes known to inactivate the JAK-STAT5 pathway (CISH, PTPN6) suggest the presence of a negative feedback loop trying to counteract the effects of hyperprolactinemia.

CONCLUSIONS

Genes and pathways identified in this study suggest that sustained hyperprolactinemia during late-pregnancy, in the absence of suckling piglets, sends conflicting pro-survival and cell death signals to mammary epithelial cells. Reception of these signals results in a mammary gland that can simultaneously synthesize milk proteins and initiate mammary involution.

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.

Genetic analysis of production traits and body size measurements and their relationships with metabolic diseases in German Holstein cattle

This study sheds light on the genetic complexity and interplay of production, body size, and metabolic health in dairy cattle. Phenotypes for body size-related traits from conformation classification (130,166 animals) and production (101,562 animals) of primiparous German Holstein cows were available. Additionally, 21,992, 16,641, and 7,096 animals were from herds with recordings of the metabolic diseases ketosis, displaced abomasum, and milk fever in first, second, and third lactation. Moreover, all animals were genotyped. Heritabilities of traits and genetic correlations between all traits were estimated and GWAS were performed. Heritability was between 0.240 and 0.333 for production and between 0.149 and 0.368 for body size traits. Metabolic diseases were lowly heritable, with estimates ranging from 0.011 to 0.029 in primiparous cows, from 0.008 to 0.031 in second lactation, and from 0.037 to 0.052 in third lactation. Production was found to have negative genetic correlations with body condition score (BCS; -0.279 to -0.343) and udder depth (-0.348 to -0.419). Positive correlations were observed for production and body depth (0.138-0.228), dairy character (DCH) (0.334-0.422), and stature (STAT) (0.084-0.158). In first parity cows, metabolic disease traits were unfavorably correlated with production, with genetic correlations varying from 0.111 to 0.224, implying that higher yielding cows have more metabolic problems. Genetic correlations of disease traits in second and third lactation with production in primiparous cows were low to moderate and in most cases unfavorable. While BCS was negatively correlated with metabolic diseases (-0.255 to -0.470), positive correlations were found between disease traits and DCH (0.269-0.469) as well as STAT (0.172-0.242). Thus, the results indicate that larger and sharper animals with low BCS are more susceptible to metabolic disorders. Genome-wide association studies revealed several significantly associated SNPs for production and conformation traits, confirming previous findings from literature. Moreover, for production and conformation traits, shared significant signals on Bos taurus autosome (BTA) 5 (88.36 Mb) and BTA 6 (86.40 to 87.27 Mb) were found, implying pleiotropy. Additionally, significant SNPs were observed for metabolic diseases on BTA 3, 10, 14, 17, and 26 in first lactation and on BTA 2, 6, 8, 17, and 23 in third lactation. Overall, this study provides important insights into the genetic basis and interrelations of relevant traits in today's Holstein cattle breeding programs, and findings may help to improve selection decisions.

Polymorphisms of the IL-17A Gene Influence Milk Production Traits and Somatic Cell Score in Chinese Holstein Cows

The cow’s milk production characteristics are a significant economic indicator in the livestock industry. Serum cytokines such as interleukin-17 (IL-17) may be potential indicators for bovine mastitis concerning the milk somatic cell count (SCC) and somatic cell score (SCS). The current study aims to find previously undiscovered single nucleotide polymorphisms in the bovine (IL-17A) gene and further investigates their associations with milk production traits in Chinese Holstein cows. Twenty Chinese Holstein cows were randomly chosen from six farms in Jiangsu Province, China. The DNA was extracted from selected samples of bloods for PCR amplification Sequence analyses were used to find SNPs in the bovine (IL-17A) gene. The discovered five SNPs are g-1578A>G, g-1835G>A, and g-398T>A in the 5′UTR; g3164T>C and g3409G>C in the exon region. The genotyping of Holstein cows (n = 992) was performed based on Sequenom Mass ARRAY and SNP data. The connection between SNPs, milk production variables, and the somatic cell score was investigated using the least-squares method. Based on the results, SNP g-398T>A had a significant linkage disequilibrium with g3164T>C. SNPs were found to have significant (p < 0.05) correlations with the test-day milk yield. In conclusion, IL-17A affects cow’s milk production traits significantly.

Fatty acid desaturase 2 affects the milk-production traits in Chinese Holsteins

As a member of the fatty acid desaturase family, fatty acid desaturase 2 (FADS2) gene is a rate-limiting enzyme in the synthesis of unsaturated fatty acids and within/near to the reported QTL regions for milk-production traits. We previously found that FADS2 is differentially expressed during different lactations of Chinese Holstein cows, and participates in lipid metabolic processes by influencing the insulin, PI3K-Akt, MAPK, AMPK, mTOR and PPAR signaling pathways. Therefore, we considered this gene as a candidate gene for milk-production traits. In this study, we identified 12 SNPs in FADS2 by re-sequencing, including two SNPs in the 5' flanking region, one in the seventh exon, five in introns, two in the 3' untranslated region and two in the 3' flanking region. The 29:g.40378819C>T is a missense mutation that causes alanine (GCG) to be replaced with valine (GTG). Through single marker association analysis, we found that all of the 12 SNPs were significantly associated with 305 day milk yield, fat yield, fat percentage, protein yield or protein percentage (p < 0.0493). The results of the subsequent haplotype association analysis also confirmed the associations between the gene and milk-production traits. In summary, this study suggests that there is a significant genetic association between FADS2 and milk-production traits, and that the SNPs with significant genetic effects can provide important molecular information for the development of a genomic selection chip in dairy cattle.

Genomewide Association Analyses of Lactation Persistency and Milk Production Traits in Holstein Cattle Based on Imputed Whole-Genome Sequence Data

Lactation persistency and milk production are among the most economically important traits in the dairy industry. In this study, we explored the association of over 6.1 million imputed whole-genome sequence variants with lactation persistency (LP), milk yield (MILK), fat yield (FAT), fat percentage (FAT%), protein yield (PROT), and protein percentage (PROT%) in North American Holstein cattle. We identified 49, 3991, 2607, 4459, 805, and 5519 SNPs significantly associated with LP, MILK, FAT, FAT%, PROT, and PROT%, respectively. Various known associations were confirmed while several novel candidate genes were also revealed, including ARHGAP35, NPAS1, TMEM160, ZC3H4, SAE1, ZMIZ1, PPIF, LDB2, ABI3, SERPINB6, and SERPINB9 for LP; NIM1K, ZNF131, GABRG1, GABRA2, DCHS1, and SPIDR for MILK; NR6A1, OLFML2A, EXT2, POLD1, GOT1, and ETV6 for FAT; DPP6, LRRC26, and the KCN gene family for FAT%; CDC14A, RTCA, HSTN, and ODAM for PROT; and HERC3, HERC5, LALBA, CCL28, and NEURL1 for PROT%. Most of these genes are involved in relevant gene ontology (GO) terms such as fatty acid homeostasis, transporter regulator activity, response to progesterone and estradiol, response to steroid hormones, and lactation. The significant genomic regions found contribute to a better understanding of the molecular mechanisms related to LP and milk production in North American Holstein cattle.

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

Background

Our preliminary work confirmed that, SLC22A7 (solute carrier family 22 member 7), NGFR (nerve growth factor receptor), ARNTL (aryl hydrocarbon receptor nuclear translocator like) and PPP2R2B (protein phosphatase 2 regulatory subunit Bβ) genes were differentially expressed in dairy cows during different stages of lactation, and involved in the lipid metabolism through insulin, PI3K-Akt, MAPK, AMPK, mTOR, and PPAR signaling pathways, so we considered these four genes as the candidates affecting milk production traits. In this study, we detected polymorphisms of the four genes and verified their genetic effects on milk yield and composition traits in a Chinese Holstein cow population.

Results

By resequencing the whole coding region and part of the flanking region of SLC22A7, NGFR, ARNTL and PPP2R2B, we totally found 20 SNPs, of which five were located in SLC22A7, eight in NGFR, three in ARNTL, and four in PPP2R2B. Using Haploview4.2, we found three haplotype blocks including five SNPs in SLC22A7, eight in NGFR and three in ARNTL. Single-SNP association analysis showed that 19 out of 20 SNPs were significantly associated with at least one of milk yield, fat yield, fat percentage, protein yield or protein percentage in the first and second lactations (P < 0.05). Haplotype-based association analysis showed that the three haplotypes were significantly associated with at least one of milk yield, fat yield, fat percentage, protein yield or protein percentage (P < 0.05). Further, we used SOPMA software to predict a SNP, 19:g.37095131C > T in NGFR, changed the structure of NGFR protein. In addition, we used Jaspar software to found that four SNPs, 19:g.37113872C > G,19:g.37113157C > T, and 19:g.37112276C > T in NGFR and 15:g.39320936A > G in ARNTL, could change the transcription factor binding sites and might affect the expression of the corresponding genes. These five SNPs might be the potential functional mutations for milk production traits in dairy cattle.

Conclusions

In summary, we proved that SLC22A7, NGFR, ARNTL and PPP2R2B have significant genetic effects on milk production traits. The valuable SNPs can be used as candidate genetic markers for genomic selection of dairy cattle, and the effects of these SNPs on other traits need to be further verified.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12863-021-01002-0.

Relationship between polymorphism within Peptidoglycan Recognition Protein 1 gene (PGLYRP1) and somatic cell counts in milk of Holstein cows

Bovine peptidoglycan recognition protein 1 (PGLYRP1) is an important receptor that binds to murein peptidoglycans (PGN) of Gram-positive and Gram-negative bacteria and is, therefore, involved in innate immunity. The SNP T>C rs68268284 located in the 1st exon of the PGLYRP1 gene was identified by the PCR-RFLP method in a population of 319 Holstein cows. Somatic cell count (SCC) was measured 7–10 times in each of three completed lactations to investigate whether the PGLYRP1 polymorphism is associated with SCC. Using the GLM model, it was found that cows with the TT genotype showed significantly lower somatic cell counts than those with the CC genotype during the first lactation (P = 0.023). Moreover, during lactations 1–2 and 1–3, cows with the TT genotype reveal significantly lower SCC than CT heterozygotes, at P = 0.025 and P = 0.006, respectively. Computer-aided analysis showed that rs68268284 polymorphism could modify the PGLYRP1 functions because the mutated residue is located in a domain that is important for the binding of other molecules.

Polymorphisms of the ACSL1 Gene Influence Milk Production Traits and Somatic Cell Score in Chinese Holstein Cows

Simple Summary

Milk production traits of cows are important economic indicators of the livestock industry. Many dairy farms strive to improve the quality of their milk. Long-chain acyl-CoA synthetase 1 (ACSL1) is a gene related to lipid metabolism. It is widely found in various organisms and can affect fat content and protein content in milk. Single nucleotide polymorphisms (SNP) refers to the polymorphism of DNA sequence caused by a single nucleotide variation at the gene level, which plays a vital function in the genetic study of milk production traits in dairy cows. Our study identified six SNPs of the ACSL1 gene in Chinese Holstein cows, which were related to milk yield, milk fat content, milk protein content and somatic cell score (SCS) to some extent. In summary, the pleiotropic effects of bovine ACSL1 for milk production traits were found in this paper, which will provide a reference for Chinese Holstein cow breeding selection and high economic benefits.

Abstract

Improving the quality of milk is a challenge for zootechnicians and dairy farms across the globe. Long-chain acyl-CoA synthetase 1 (ACSL1) is a significant member of the long-chain acyl-CoA synthetase gene family. It is widely found in various organisms and influences the lactation performance of cows, including fat percentage, milk protein percentage etc. Our study was aimed to investigate the genetic effects of single nucleotide polymorphisms (SNPs) in ACSL1 on milk production traits. Twenty Chinese Holstein cows were randomly selected to extract DNA from their blood samples for PCR amplification and sequencing to identify SNPs of the bovine ACSL1 gene, and six SNPs (5’UTR-g.20523C>G, g.35446C>T, g.35651G>A, g.35827C>T, g.35941G>A and g.51472C>T) were discovered. Then, Holstein cow genotyping (n = 992) was performed by Sequenom MassARRAY based on former SNP information. Associations between SNPs and milk production traits and somatic cell score (SCS) were analyzed by the least-squares method. The results showed that SNP g.35827C>T was in high linkage disequilibrium with g.35941G>A. Significant associations were found between SNPs and test-day milk yield (TDMY), fat content (FC), protein content (PC) and SCS (p < 0.05). Among these SNPs, SNP 5’UTR-g.20523C>G showed an extremely significant effect on PC and SCS (p < 0.01). The SNP g.35446C>T showed a statistically significant effect on FC, PC, and SCS (p < 0.01), and also TDMY (p < 0.05). The SNP g.35651G>A had a statistically significant effect on PC (p < 0.01). The SNP g.35827C>T showed a highly significant effect on TDMY, FC, and SCS (p < 0.01) and significantly influenced PC (p < 0.05). Lastly, SNP g.51472C>T was significantly associated with TDMY, FC, and SCS (p < 0.05). In summary, the pleiotropic effects of bovine ACSL1 for milk production traits were found in this paper, but further investigation will be required on the intrinsic correlation to provide a theoretical basis for the research on molecular genetics of milk quality traits of Holstein cows.