Weighted Gene Correlation Network Meta-Analysis Reveals Functional Candidate Genes Associated with High- and Sub-Fertile Reproductive Performance in Beef Cattle

Investigating the expression of fertility-regulating LncRNAs in multiparous and uniparous Shal ewe's ovaries

Sheep is the primary source of animal protein in Iran. Birth type is one of the significant features that determine total meat output. Little is known about how long non-coding RNAs (LncRNAs) affect litter size. The purpose of this research is to investigate the DE-LncRNAs in ovarian tissue between multiparous and uniparous Shal ewes. Through bioinformatics analyses, LncRNAs with variable expression levels between ewes were discovered. Target genes were annotated using the DAVID database, and STRING and Cytoscape software were used to evaluate their interactions. The expression levels of 148 LncRNAs were different in the multiparous and uniparous ewe groups (false discovery rate (FDR) < 0.05). Eight biological process terms, nine cellular component terms, 10 molecular function terms, and 38 KEGG pathways were significant (FDR < 0.05) in the GO analysis. One of the most significant processes impacting fertility is mitogen-activated protein kinase (MAPK) signaling pathway, followed by oocyte meiosis, gonadotropin-releasing hormone signaling pathway, progesterone-mediated oocyte maturation, oxytocin signaling pathway, and cAMP signaling pathway. ENSOARG00000025710, ENSOARG00000025667, ENSOARG00000026034, and ENSOARG00000026632 are LncRNAs that may affect litter size and fertility. The most crucial hub genes include MAPK1, BRD2, GAK, RAP1B, FGF2, RAP1B, and RAP1B. We hope that this study will encourage researchers to further investigate the effect of LncRNAs on fertility.

Transcriptome profiling revealed that key rumen epithelium functions change in relation to short-chain fatty acids and rumen epithelium-attached microbiota during the weaning transition

This study aims to characterize the functional changes of the rumen epithelium associated with ruminal short-chain fatty acid (SCFA) concentration and epithelium-attached microbes during the weaning transition in dairy calves. Ruminal SCFA concentrations were determined, and transcriptome and microbiota profiling in biopsied rumen papillae were obtained from Holstein calves before and after weaning using RNA- and amplicon sequencing. Metabolic pathway analysis showed that pathways related to SCFA metabolism and cell apoptosis were up- and down-regulated postweaning, respectively. Functional analysis showed that genes related to SCFA absorption, metabolism, and protective roles against oxidative stress were positively correlated with ruminal SCFA concentrations. The relative abundance of epithelium-attached Rikenellaceae RC9 gut group and Campylobacter was positively correlated with genes involved in SCFA absorption and metabolism, suggesting that these microbes can cooperatively affect host functions. Future research should examine the contribution of attenuated apoptosis on rumen epithelial functional shifts during the weaning transition.

Reduction in mucosa thickness is associated with changes in immune function in the colon mucosa during the weaning transition in Holstein bull dairy calves

This study aims to characterize changes in the structure and the molecules related to immune function in the colon mucosa in dairy calves during the weaning transition (weaned at week 6 of age). Colon mucosa thickness, measured at week 5 to 8 and 12 of age, decreased for 2 weeks after weaning, but then recovered. Colon mucosa's transcriptome profiling at week 5, 7, and 12 of age was obtained using RNA-sequencing. Functional analysis showed that pathways related to immune function were up-regulated postweaning. A weighted gene co-expression network analysis identified 17 immune function related genes, expressed higher postweaning, which were negatively correlated with colon mucosa thickness, suggesting that these genes may be involved in colon mucosa inflammation and recovery from mucosa thickness decrement during the weaning transition. As such, it is important to determine the function of immune cells in the colon mucosa during the weaning transition in dairy calves.

Genome-wide scan for runs of homozygosity in South American Camelids

BACKGROUND

Alpaca (Vicugna pacos), llama (Lama glama), vicugna (Vicugna vicugna) and guanaco (Lama guanicoe), are the camelid species distributed over the Andean high-altitude grasslands, the Altiplano, and the Patagonian arid steppes. Despite the wide interest on these animals, most of the loci under selection are still unknown. Using whole-genome sequencing (WGS) data we investigated the occurrence and the distribution of Runs Of Homozygosity (ROHs) across the South American Camelids (SACs) genome to identify the genetic relationship between the four species and the potential signatures of selection.

RESULTS

A total of 37 WGS samples covering the four species was included in the final analysis. The multi-dimensional scaling approach showed a clear separation between the four species; however, admixture analysis suggested a strong genetic introgression from vicugna and llama to alpaca. Conversely, very low genetic admixture of the guanaco with the other SACs was found. The four species did not show significant differences in the number, length of ROHs (100-500 kb) and genomic inbreeding values. Longer ROHs (> 500 kb) were found almost exclusively in alpaca. Seven overlapping ROHs were shared by alpacas, encompassing nine loci (FGF5, LOC107034918, PRDM8, ANTXR2, LOC102534792, BSN, LOC116284892, DAG1 and RIC8B) while nine overlapping ROHs were found in llama with twenty-five loci annotated (ERC2, FZD9, BAZ1B, BCL7B, LOC116284208, TBL2, MLXIPL, PHF20, TRNAD-AUC, LOC116284365, RBM39, ARFGEF2, DCAF5, EXD2, HSPB11, LRRC42, LDLRAD1, TMEM59, LOC107033213, TCEANC2, LOC102545169, LOC116278408, SMIM15, NDUFAF2 and RCOR1). Four overlapping ROHs, with three annotated loci (DLG1, KAT6B and PDE4D) and three overlapping ROHs, with seven annotated genes (ATP6V1E1, BCL2L13, LOC116276952, BID, KAT6B, LOC116282667 and LOC107034552), were detected for vicugna and guanaco, respectively.

CONCLUSIONS

The signatures of selection revealed genomic areas potentially selected for production traits as well as for natural adaptation to harsh environment. Alpaca and llama hint a selection driven by environment as well as by farming purpose while vicugna and guanaco showed selection signals for adaptation to harsh environment. Interesting, signatures of selection on KAT6B gene were identified for both vicugna and guanaco, suggesting a positive effect on wild populations fitness. Such information may be of interest to further ecological and animal production studies.

Runs of homozygosity and signatures of selection for number of oocytes and embryos in the Gir Indicine cattle

Runs of homozygosity (ROH) and signatures of selection are the results of selection processes in livestock species that have been shown to affect several traits in cattle. The aim of the current work was to verify the profile of ROH and inbreeding depression in the number of total (TO) and viable oocytes (VO) and the number of embryos (EMBR) in Gir Indicine cattle. In addition, we aim to identify signatures of selection, genes, and enriched regions between Gir subpopulations sorted by breeding value for these traits. The genotype file contained 2093 animals and 420,718 SNP markers. Breeding values used to sort Gir animals were previously obtained. ROH and signature of selection analyses were performed using PLINK software, followed by ROH-based (F_ROH) and pedigree-based inbreeding (F_ped) and a search for genes and their functions. An average of 50 ± 8.59 ROHs were found per animal. ROHs were separated into classes according to size, ranging from 1 to 2 Mb (ROH_1-2Mb: 58.17%), representing ancient inbreeding, ROH_2-4Mb (22.74%), ROH_4-8Mb (11.34%), ROH_8-16Mb (5.51%), and ROH_>16Mb (2.24%). Combining our results, we conclude that the increase in general F_ROH and F_ped significantly decreases TO and VO; however, in different chromosomes traits can increase or decrease with F_ROH. In the analysis for signatures of selection, we identified 15 genes from 47 significant genomic regions, indicating differences in populations with high and low breeding value for the three traits.

Machine Learning-Based Co-Expression Network Analysis Unravels Potential Fertility-Related Genes in Beef Cows

Simple Summary

Female reproductive failure is still a challenge for the beef industry. Several biological processes that underlie fertility-related traits, such as the establishment of pregnancy and embryo survival, are still unclear. Increased availability of transcriptomic data has allowed a deep investigation of the potential mechanisms involved in fertility. This study investigated candidate gene biomarkers predictive of pregnancy status and underlying fertility-related networks. To this end, we integrated gene expression profiles through supervised machine learning and gene network modeling. We identified nine biologically relevant endometrial gene biomarkers that could discriminate against pregnancy status in cows. These biomarkers were co-expressed with genes critical for uterine receptivity, including endometrial tissue remodeling, focal adhesion, and embryo development. This study outlined key pathways involved with pregnancy success and provided predictive candidate biomarkers for pregnancy outcome in cows.

Abstract

Reproductive failure is still a challenge for beef producers and a significant cause of economic loss. The increased availability of transcriptomic data has shed light on the mechanisms modulating pregnancy success. Furthermore, new analytical tools, such as machine learning (ML), provide opportunities for data mining and uncovering new biological events that explain or predict reproductive outcomes. Herein, we identified potential biomarkers underlying pregnancy status and fertility-related networks by integrating gene expression profiles through ML and gene network modeling. We used public transcriptomic data from uterine luminal epithelial cells of cows retrospectively classified as pregnant (P, n = 25) and non-pregnant (NP, n = 18). First, we used a feature selection function from BioDiscML and identified SERPINE3, PDCD1, FNDC1, MRTFA, ARHGEF7, MEF2B, NAA16, ENSBTAG00000019474, and ENSBTAG00000054585 as candidate biomarker predictors of pregnancy status. Then, based on co-expression networks, we identified seven genes significantly rewired (gaining or losing connections) between the P and NP networks. These biomarkers were co-expressed with genes critical for uterine receptivity, including endometrial tissue remodeling, focal adhesion, and embryo development. We provided insights into the regulatory networks of fertility-related processes and demonstrated the potential of combining different analytical tools to prioritize candidate genes.

Recent developments and future directions in meta-analysis of differential gene expression in livestock RNA-Seq

Decreases in the costs of high-throughput sequencing technologies have led to continually increasing numbers of livestock RNA-Seq studies in the last decade. Although the number of studies has increased dramatically, most livestock RNA-Seq experiments are limited by cost to a small number of biological replicates. Meta-analysis procedures can be used to integrate and jointly analyze data from multiple independent studies. Meta-analyses increase the sample size, which in turn increase both statistical power and robustness of the results. In this work, we discuss cutting edge approaches to combining results from multiple independent RNA-Seq studies to improve livestock transcriptomics research. We review currently published RNA-Seq meta-analyses in livestock, describe many of the key issues specific to RNA-Seq meta-analysis in livestock species, and discuss future perspectives.

Unrevealing functional candidate genes for bovine fertility through RNA sequencing meta-analysis and regulatory elements networks of co-expressed genes and lncRNAs

The high genetic heterogeneity and environmental effects of subfertility in livestock species make the elucidation of the genetic mechanisms associated with reproductive efficiency a difficult task. Network and co-expression network meta-analyses were applied alongside genetic variant calling and long non-coding RNA (lncRNA) characterization to identify functionally relevant target genes and regulatory subnetworks associated with fertility in dairy cattle. In total, 505 lncRNAs (441 previously annotated in the bovine reference genome ARS-UCD 1.2 and 64 novel lncRNAs) were identified. Seven differentially expressed genes between high-fertile (HF) and sub-fertile (SF) Holstein cows were identified in the network meta-analysis (CA5A, ENSBTAG00000051149, ENSBTAG00000003272, DEFB7, DIO2, TRPV3, and COL4A4). Additionally, seven functional candidate differentially co-expressed (DcoExp) modules with a differential regulatory pattern (|z-score|>2) were identified between HF and SF cows. The functional candidate genes and DcoExp modules identified were associated with fertility relevant processes such as the regulation of embryonic implantation and proliferation, interaction and molecule transfer between the fetus and the cow, and the immune system. These results help to better understand the genetic mechanisms associated with reproductive efficiency in dairy cattle through the identification of potential biomarkers and genetic variants associated with differentially expressed regulatory gene and lncRNAs regulatory element networks.

Genome-Wide Selection Signatures and Human-Mediated Introgression Events in Bos taurus indicus-influenced Composite Beef Cattle

Genetic introgression from interbreeding hybridization of European Bos taurus taurus (EBT) and Indian Bos taurus indicus (IBI) cattle breeds have been widely used to combine the climatic resilience of the IBI cattle and the higher productivity of EBT when forming new composite beef cattle (CB) populations. The subsequent breeding strategies have shifted their initial genomic compositions. To uncover population structure, signatures of selection, and potential introgression events in CB populations, high-density genotypes [containing 492,954 single nucleotide polymorphisms (SNPs) after the quality control] of 486 individuals from 15 cattle breeds, including EBT, IBI, and CB populations, along with two Bos grunniens genotypes as outgroup were used in this study. Then, in-depth population genetics analyses were performed for three CB breeds of Beefmaster, Brangus, and Santa Gertrudis. Neighbor-joining, principal components, and admixture analyses confirmed the historical introgression of EBT and IBI haplotypes into CB breeds. The f_dM statistics revealed that only 12.9% of CB populations' genetic components are of IBI origin. The results of signatures of selection analysis indicated different patterns of selection signals in the three CB breeds with primary pressure on pathways involved in protein processing and stress response in Beefmaster, cell proliferation regulation and immune response in Brangus, and amino acids and glucose metabolisms in Santa Gertrudis. An average of >90% of genomic regions underlying selection signatures were of EBT origin in the studied CB populations. Investigating the CB breeds' genome allows the estimation of EBT and IBI ancestral proportions and the locations within the genome where either taurine or indicine origin alleles are under selective pressure. Such findings highlight various opportunities to control the selection process more efficiently and explore complementarity at the genomic level in CB populations.

Genome-wide association study using haplotype libraries and repeated measures model to identify candidate genomic regions for stillbirth in Holstein cattle

Reduced fertility is one of the main causes of economic losses on dairy farms, resulting in economic losses estimated at $938 per stillbirth case in Holstein herds. The identification of genomic regions associated with stillbirth could help to develop better management and breeding strategies aimed to reduce the frequency of undesirable gestation outcomes. Here, 10,570 cows and 50,541 birth records were used to perform a haplotype-based GWAS. A total of 41 significantly associated pseudo-SNPs (haplotypes within haplotype blocks converted to a binary classification) were identified after Bonferroni adjustment for multiple tests. A total of 117 positional candidate genes were annotated within or close (in a 200-kb interval) to significant pseudo-SNPs (haplotype blocks). The guilt-by-association functional prioritization identified 31 potential functional candidate genes for reproductive performance out of the 117 positional candidate genes annotated. These genes play crucial roles in biological processes associated with pregnancy persistence, fetus development, immune response, among others. These results helped us to better understand the genetic basis of stillbirth in dairy cattle and may be useful for the prediction of stillbirth in Holstein cattle, helping to reduce the related economic losses caused by this phenotype.

Heat stress and immune response phenotype affect DNA methylation in blood mononuclear cells from Holstein dairy cows

Heat stress negatively affects health and production in cows. Examining the cellular response to heat stress could reveal underlying protective molecular mechanisms associated with superior resilience and ultimately enable selection for more resilient cattle. This type of investigation is increasingly important as future predictions for the patterns of heat waves point to increases in frequency, severity, and duration. Cows identified as high immune responders based on High Immune Response technology (HIR) have lower disease occurrence compared to their average and low immune responder herd-mates. In this study, our goal was to identify epigenetic differences between high and low immune responder cows in response to heat stress. We examined genome-wide DNA methylation of blood mononuclear cells (BMCs) isolated from high and low cows, before and after in vitro heat stress. We identified differential methylation of promoter regions associated with a variety of biological processes including immune function, stress response, apoptosis, and cell signalling. The specific differentially methylated promoter regions differed between samples from high and low cows, and results revealed pathways associated with cellular protection during heat stress.

Genome-wide association study to identify genomic regions and positional candidate genes associated with male fertility in beef cattle

Fertility plays a key role in the success of calf production, but there is evidence that reproductive efficiency in beef cattle has decreased during the past half-century worldwide. Therefore, identifying animals with superior fertility could significantly impact cow-calf production efficiency. The objective of this research was to identify candidate regions affecting bull fertility in beef cattle and positional candidate genes annotated within these regions. A GWAS using a weighted single-step genomic BLUP approach was performed on 265 crossbred beef bulls to identify markers associated with scrotal circumference (SC) and sperm motility (SM). Eight windows containing 32 positional candidate genes and five windows containing 28 positional candidate genes explained more than 1% of the genetic variance for SC and SM, respectively. These windows were selected to perform gene annotation, QTL enrichment, and functional analyses. Functional candidate gene prioritization analysis revealed 14 prioritized candidate genes for SC of which MAP3K1 and VIP were previously found to play roles in male fertility. A different set of 14 prioritized genes were identified for SM and five were previously identified as regulators of male fertility (SOD2, TCP1, PACRG, SPEF2, PRLR). Significant enrichment results were identified for fertility and body conformation QTLs within the candidate windows. Gene ontology enrichment analysis including biological processes, molecular functions, and cellular components revealed significant GO terms associated with male fertility. The identification of these regions contributes to a better understanding of fertility associated traits and facilitates the discovery of positional candidate genes for future investigation of causal mutations and their implications.

Integrating RNA-Seq with GWAS reveals novel insights into the molecular mechanism underpinning ketosis in cattle

Background

Ketosis is a common metabolic disease during the transition period in dairy cattle, resulting in long-term economic loss to the dairy industry worldwide. While genetic selection of resistance to ketosis has been adopted by many countries, the genetic and biological basis underlying ketosis is poorly understood.

Results

We collected a total of 24 blood samples from 12 Holstein cows, including 4 healthy and 8 ketosis-diagnosed ones, before (2 weeks) and after (5 days) calving, respectively. We then generated RNA-Sequencing (RNA-Seq) data and seven blood biochemical indicators (bio-indicators) from leukocytes and plasma in each of these samples, respectively. By employing a weighted gene co-expression network analysis (WGCNA), we detected that 4 out of 16 gene-modules, which were significantly engaged in lipid metabolism and immune responses, were transcriptionally (FDR < 0.05) correlated with postpartum ketosis and several bio-indicators (e.g., high-density lipoprotein and low-density lipoprotein). By conducting genome-wide association signal (GWAS) enrichment analysis among six common health traits (ketosis, mastitis, displaced abomasum, metritis, hypocalcemia and livability), we found that 4 out of 16 modules were genetically (FDR < 0.05) associated with ketosis, among which three were correlated with postpartum ketosis based on WGCNA. We further identified five candidate genes for ketosis, including GRINA, MAF1, MAFA, C14H8orf82 and RECQL4. Our phenome-wide association analysis (Phe-WAS) demonstrated that human orthologues of these candidate genes were also significantly associated with many metabolic, endocrine, and immune traits in humans. For instance, MAFA, which is involved in insulin secretion, glucose response, and transcriptional regulation, showed a significantly higher association with metabolic and endocrine traits compared to other types of traits in humans.

Conclusions

In summary, our study provides novel insights into the molecular mechanism underlying ketosis in cattle, and highlights that an integrative analysis of omics data and cross-species mapping are promising for illustrating the genetic architecture underpinning complex traits.