Analysis of single nucleotide polymorphisms related to heifer fertility in Hanwoo (Korean cattle)

Identification of genomic regions and genes associated with subclinical ketosis in periparturient dairy cows

Subclinical ketosis (SCK) is a prevalent metabolic disorder that occurs during the transition to lactation period. It is defined as a high blood concentration of ketone bodies (beta-hydroxybutyric acid f ≥ 1.2 mmol/L) within the first few weeks of lactation, and often presents without clinical signs. SCK is mainly caused by negative energy balance (NEB). The objective of this study is to identify single nucleotide polymorphisms (SNPs) associated with SCK using genome-wide association studies (GWAS), and to predict the biological functions of proximal genes using gene-set enrichment analysis (GSEA). Blood samples were collected from 112 Holstein cows between 5 and 18 days postpartum to determine the incidence of SCK. Genomic DNA extracted from both SCK and healthy cows was examined using the Illumina Bovine SNP50K BeadChip for genotyping. GWAS revealed 194 putative SNPs and 163 genes associated with those SNPs. Additionally, GSEA showed that the genes retrieved by Database for Annotation, Visualization, and Integrated Discovery (DAVID) belonged to calcium signaling, starch and sucrose, immune network, and metabolic pathways. Furthermore, the proximal genes were found to be related to germ cell and early embryo development. In summary, this study proposes several feasible SNPs and genes associated with SCK through GWAS and GSEA. These candidates can be utilized in selective breeding programs to reduce the genetic risk for SCK and subfertility in high-performance dairy cows.

A Genome-Wide Association Study for Resistance to Tropical Theileriosis in Two Bovine Portuguese Autochthonous Breeds

The control of Tropical Theileriosis, a tick-borne disease with a strong impact on cattle breeding, can be facilitated using marker-assisted selection in breeding programs. Genome-wide association studies (GWAS) using high-density arrays are extremely important for the ongoing process of identifying genomic variants associated with resistance to Theileria annulata infection. In this work, single-nucleotide polymorphisms (SNPs) were analyzed in the Portuguese autochthonous cattle breeds Alentejana and Mertolenga. In total, 24 SNPs suggestive of significance (p ≤ 10-4) were identified for Alentejana cattle and 20 SNPs were identified for Mertolenga cattle. The genomic regions around these SNPs were further investigated for annotated genes and quantitative trait loci (QTLs) previously described by other authors. Regarding the Alentejana breed, the MAP3K1, CMTM7, SSFA2, and ATG13 genes are located near suggestive SNPs and appear as candidate genes for resistance to Tropical Theileriosis, considering its action in the immune response and resistance to other diseases. On the other hand, in the Mertolenga breed, the UOX gene is also a candidate gene due to its apparent link to the pathogenesis of the disease. These results may represent a first step toward the possibility of including genetic markers for resistance to Tropical Theileriosis in current breed selection programs.

Identification of quantitative trait loci and associated candidate genes for pregnancy success in Angus-Brahman crossbred heifers

BACKGROUND

In beef cattle, more than 50% of the energy input to produce a unit of beef is consumed by the female that produced the calf. Development of genomic tools to identify females with high genetic merit for reproductive function could increase the profitability and sustainability of beef production.

RESULTS

Genome-wide association studies (GWAS) were performed using a single-step genomic best linear unbiased prediction approach on pregnancy outcome traits from a population of Angus-Brahman crossbred heifers. Furthermore, a validation GWAS was performed using data from another farm. Heifers were genotyped with the Bovine GGP F250 array that contains 221,077 SNPs. In the discovery population, heifers were bred in winter breeding seasons involving a single round of timed artificial insemination (AI) followed by natural mating for 3 months. Two phenotypes were analyzed: pregnancy outcome to first-service AI (PAI; n = 1,481) and pregnancy status at the end of the breeding season (PEBS; n = 1,725). The heritability was estimated as 0.149 and 0.122 for PAI and PEBS, respectively. In the PAI model, one quantitative trait locus (QTL), located between 52.3 and 52.5 Mb on BTA7, explained about 3% of the genetic variation, in a region containing a cluster of γ-protocadherin genes and SLC25A2. Other QTLs explaining between 0.5% and 1% of the genetic variation were found on BTA12 and 25. In the PEBS model, a large QTL on BTA7 was synonymous with the QTL for PAI, with minor QTLs located on BTA5, 9, 10, 11, 19, and 20. The validation population for pregnancy status at the end of the breeding season were Angus-Brahman crossbred heifers bred by natural mating. In concordance with the discovery population, the large QTL on BTA7 and QTLs on BTA10 and 12 were identified.

CONCLUSIONS

In summary, QTLs and candidate SNPs identified were associated with pregnancy outcomes in beef heifers, including a large QTL associated with a group of protocadherin genes. Confirmation of these associations with larger populations could lead to the development of genomic predictions of reproductive function in beef cattle. Moreover, additional research is warranted to study the function of candidate genes associated with QTLs.

Effect of LHCGR and FSHR gene polymorphisms on fertility traits and milk yield of cross-bred dairy cows in Sri Lanka

Single nucleotide polymorphism (SNP) analysis of fertility genes will be useful in improving the genetic potential of dairy cows. A population of 142 cross-bred dairy cows was screened for SNPs in bovine luteinizing hormone choriogonadotropin receptor (LHCGR) and bovine follicle stimulating hormone receptor (FSHR) genes. The effect of reported SNPs on selected fertility traits (average calving interval, average number of services per conception and age at first calving) and milk yield was determined. Altogether six SNPs were detected in animals screened under the present study. Among them, four SNPs (rs41256848, rs41256850, rs465790244, and rs45463781) were located in the exon 11 region of the LHCGR gene and two SNPs (rs43676359 and G-278-A (GU253337) were located in the five upstream region of the FSHR gene. Minor alleles identified for SNPs in the FSHR gene in the studied small population of cows differed from those reported in other research. In this study, only rs45463781 SNP at exon 11 of the LHCGR gene significantly affected the average milk yield in cross-bred cows. The nucleotide change from "G" to "A" negatively affected the average milk yield. Further investigations are needed to confirm the reported association with a larger sample size.

Intelligent Big Information Retrieval of Smart Library Based on Graph Neural Network (GNN) Algorithm

In order to provide users with more humanized and intelligent big data knowledge services, a research method of intelligent big information retrieval of Smart Library Based on graph neural network (GNN) algorithm is proposed. Through the key technical problems and solutions of information recommendation represented by graph neural network (GNN) algorithm, this method explores how the library can realize the management and value mining of big data knowledge services. The research shows that the intelligent information retrieval of Smart Library Based on graph neural network (GNN) algorithm is 80% higher than the previous general methods. Graph neural network is a more advantageous algorithm for node classification, link prediction, node clustering, or network visualization, which is of great help to improve the efficiency of information retrieval.