Transcriptomics-genomics data integration and expression quantitative trait loci analyses in oocyte donors and embryo recipients for improving invitro production of dairy cattle embryos

Whole-genome resequencing deciphers patterns of genetic diversity, phylogeny, and evolutionary dynamics in Kashmir cattle

Kashmir cattle, which were kept by local pastoralists for centuries, are exceptionally resilient and adaptive to harsh environments. Despite its significance, the genomic characteristics of this cattle breed remain elusive. This study utilized whole genome sequences of Kashmir cattle (n = 20; newly sequenced) alongside published whole genomes of 32 distinct breeds and seven core cattle populations (n = 135). The analysis identified ~25.87 million biallelic single nucleotide polymorphisms in Kashmir cattle, predominantly in intergenic and intron regions. Population structure analyses revealed distinct clustering patterns of Kashmir cattle with proximity to the South Asian, African and Chinese indicine cattle populations. Genetic diversity analysis of Kashmir cattle demonstrated lower inbreeding and greater nucleotide diversity than analyzed global breeds. Homozygosity runs indicated less consanguineous mating in Kashmir cattle compared with European taurine breeds. Furthermore, six selection sweep detection methods were used within Kashmir cattle and other cattle populations to identify genes associated with vital traits, including immunity (BOLA-DQA5, BOLA-DQB, TNFAIP8L, FCRL4, AOAH, HIF1AN, FBXL3, MPEG1, CDC40, etc.), reproduction (GOLGA4, BRWD1, OSBP2, LEO1 ADCY5, etc.), growth (ADPRHL1, NRG2, TCF12, TMOD4, GBP4, IGF2, RSPO3, SCD, etc.), milk composition (MRPS30 and CSF1) and high-altitude adaptation (EDNRA, ITPR2, AGBL4 and SCG3). These findings provide essential genetic insights into the characteristics and establish the foundation for the scientific conservation and utilization of Kashmir cattle breed.

Inheritance of genomic regions and genes associated with number of oocytes and embryos in Gir cattle through daughter design

Over the past decades, daughter designs, including genotyped sires and their genotyped daughters, have been used as an approach to identify QTL related to economic traits. The aim of this study was to identify genomic regions inherited by Gir sire families and genes associated with number of viable oocytes (VO), total number of oocytes (TO), and number of embryos (EMBR) based on a daughter design approach. In total, 15 Gir sire families were selected. The number of daughters per family ranged from 26 to 395, which were genotyped with different SNP panels and imputed to the Illumina BovineHD BeadChip (777K) and had phenotypes for oocyte and embryo production. Daughters had phenotypic data for VO, TO, and EMBR. The search for QTL was performed through GWAS based on GBLUP. The QTL were found for each trait among and within families based on the top 10 genomic windows with the greatest genetic variance. For EMBR, genomic windows identified among families were located on BTA4, BTA5, BTA6, BTA7, BTA8, BTA13, BTA16, and BTA17, and they were most frequent on BTA7 within families. For VO, genomic windows were located on BTA2, BTA4, BTA5, BTA7, BTA17, BTA21, BTA22, BTA23, and BTA27 among families, being most frequent on BTA8 within families. For TO, the top 10 genomic windows were identified on BTA2, BTA4, BTA5, BTA7, BTA17, BTA21, BTA22, BTA26, and BTA27, being most frequent on BTA7 and BTA8 within families. Considering all results, the greatest number of genomic windows was found on BTA7, where the VCAN, XRCC4, TRNAC-ACA, HAPLN1, and EDIL3 genes were identified in the common regions. In conclusion, 15 Gir sire families with 26 to 395 daughters per family with phenotypes for oocyte and embryo production helped to identify the inheritance of several genomic regions, especially on BTA7, where the EDIL3, HAPLN1, and VCAN candidate genes were associated with number of oocytes and embryos in Gir cattle families.

Mapping Expression Quantitative Trait Loci Targeting Candidate Genes for Pregnancy in Beef Cows

Despite collective efforts to understand the complex regulation of reproductive traits, no causative genes and/or mutations have been reported yet. By integrating genomics and transcriptomics data, potential regulatory mechanisms may be unveiled, providing opportunities to dissect the genetic factors governing fertility. Herein, we identified regulatory variants from RNA-Seq data associated with gene expression regulation in the uterine luminal epithelial cells of beef cows. We identified 4676 cis and 7682 trans eQTLs (expression quantitative trait loci) affecting the expression of 1120 and 2503 genes, respectively (FDR < 0.05). These variants affected the expression of transcription factor coding genes (71 cis and 193 trans eQTLs) and genes previously reported as differentially expressed between pregnant and nonpregnant cows. Functional over-representation analysis highlighted pathways related to metabolism, immune response, and hormone signaling (estrogen and GnRH) affected by eQTL-regulated genes (p-value ≤ 0.01). Furthermore, eQTLs were enriched in QTL regions for 13 reproduction-related traits from the CattleQTLdb (FDR ≤ 0.05). Our study provides novel insights into the genetic basis of reproductive processes in cattle. The underlying causal mechanisms modulating the expression of uterine genes warrant further investigation.

Harnessing Genomics and Transcriptomics Approaches to Improve Female Fertility in Beef Cattle-A Review

Female fertility is the foundation of the cow-calf industry, impacting both efficiency and profitability. Reproductive failure is the primary reason why beef cows are sold in the U.S. and the cause of an estimated annual gross loss of USD 2.8 billion. In this review, we discuss the status of the genomics, transcriptomics, and systems genomics approaches currently applied to female fertility and the tools available to cow-calf producers to maximize genetic progress. We highlight the opportunities and limitations associated with using genomic and transcriptomic approaches to discover genes and regulatory mechanisms related to beef fertility. Considering the complex nature of fertility, significant advances in precision breeding will rely on holistic, multidisciplinary approaches to further advance our ability to understand, predict, and improve reproductive performance. While these technologies have advanced our knowledge, the next step is to translate research findings from bench to on-farm applications.

Outstanding Gir oocyte donors: How does individual factor affect in vitro embryo production efficiency?

The oocyte donor plays a pivotal role in bovine in vitro embryo production (IVP) success. The individual factor affects blastocyst/oocyte ratio and determine the existence of outstanding performing animals. The aim of this study was to assess the extent of individual factor effect to IVP efficiency, in a population of Gir oocyte donors. Extreme (high or low IVP efficiency based on blastocyst/oocyte ratio) animals were selected out of a population of 250 oocyte donors (1,734 observations) to form high (>0.48, n = 40), average (0.17-0.48, n = 168), and low (<0.17, n = 42) efficiency donor groups. Cumulus-oocyte complex indicators (total number, IVF-grade number, and IVF-grade/total ratio) were lower (p < 0.05) in high efficiency donors. The number of blastocysts per OPU was analyzed for highest performing bull, and an increase (p < 0.05) in high efficiency donors and a decrease (p < 0.05) in low efficiency donors were noticed, compared to average efficiency donors. The number of pregnancies obtained per OPU was affected (p = 0.017) by donor's efficiency (low:0.60 ± 0.09 $$ 0.60\pm 0.09 $$ , average:1.17 ± 0.07 $$ 1.17\pm 0.07 $$ , high:2.57 ± 0.26 $$ 2.57\pm 0.26 $$ ), being 4.3-fold higher in high than in low efficiency donors. We conclude that producing embryos from high efficiency blastocyst/oocyte ratio donors increases blastocyst and pregnancy numbers by OPU, being an important indicator for donor selection in IVP programs.

Restraint stress of female mice during oocyte development facilitates oocyte postovulatory aging

Studies suggest that psychological stress on women can impair their reproduction and that postovulatory oocyte aging (POA) might increase the risk of early pregnancy loss and affect offspring's reproductive fitness and longevity. However, whether psychological stress during oocyte development would facilitate POA is unknown but worth exploring to understand the mechanisms by which psychological stress and POA damage oocytes. This study observed effects of female restraint stress during oocyte development (FRSOD) on oocyte resistance to POA. Female mice were restrained for 48 h before superovulation, and they were sacrificed at different intervals after ovulation to recover aging oocytes for analyzing their early and late aged characteristics. The effects of FRSOD on aging oocytes included: (1) increasing their susceptibility to activation stimulus with elevated cytoplasmic calcium; (2) impairing their developmental potential with downregulated expression of development-beneficial genes; (3) facilitating degeneration, cytoplasmic fragmentation and apoptosis; (4) worsening the disorganization of cortical granules and spindle/chromosomes; and (5) impairing redox potential with increased oxidative stress. In conclusion, FRSOD impairs oocyte resistance to POA, so that stressed oocytes become aged significantly quicker than unstressed controls. Thus, couples wishing to achieve pregnancy should take steps to avoid not only fertilization of aged oocytes but also pregestational stressful life events.

Machine learning approach to integrated endometrial transcriptomic datasets reveals biomarkers predicting uterine receptivity in cattle at seven days after estrous

The main goal was to apply machine learning (ML) methods on integrated multi-transcriptomic data, to identify endometrial genes capable of predicting uterine receptivity according to their expression patterns in the cow. Public data from five studies were re-analyzed. In all of them, endometrial samples were obtained at day 6–7 of the estrous cycle, from cows or heifers of four different European breeds, classified as pregnant (n = 26) or not (n = 26). First, gene selection was performed through supervised and unsupervised ML algorithms. Then, the predictive ability of potential key genes was evaluated through support vector machine as classifier, using the expression levels of the samples from all the breeds but one, to train the model, and the samples from that one breed, to test it. Finally, the biological meaning of the key genes was explored. Fifty genes were identified, and they could predict uterine receptivity with an overall 96.1% accuracy, despite the animal’s breed and category. Genes with higher expression in the pregnant cows were related to circadian rhythm, Wnt receptor signaling pathway, and embryonic development. This novel and robust combination of computational tools allowed the identification of a group of biologically relevant endometrial genes that could support pregnancy in the cattle.