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Summary: Progesterone signaling and uterine function are crucial in terms of pregnancy establishment. To investigate how the uterine tissue and its secretion changes in relation to puberty, we sampled tissue and uterine fluid from six pre‐ and six post‐pubertal Brahman heifers. Post‐pubertal heifers were sampled in the luteal phase. Gene expression of the uterine tissue was investigated with RNA‐sequencing, whereas the uterine fluid was used for protein profiling with mass spectrometry. A total of 4034 genes were differentially expressed (DE) at a nominal P‐value of 0.05, and 26 genes were significantly DE after Bonferroni correction (P < 3.1 × 10−6). We also identified 79 proteins (out of 230 proteins) that were DE (P < 1 × 10−5) in the uterine fluid. When we compared proteomics and transcriptome results, four DE proteins were identified as being encoded by DE genes: OVGP1, GRP, CAP1 and HBA. Except for CAP1, the other three had lower expression post‐puberty. The function of these four genes hypothetically related to preparation of the uterus for a potential pregnancy is discussed in the context of puberty. All DE genes and proteins were also used in pathway and ontology enrichment analyses to investigate overall function. The DE genes were enriched for terms related to ribosomal activity. Transcription factors that were deemed key regulators of DE genes are also reported. Transcription factors ZNF567,ZNF775,RELA,PIAS2,LHX4,SOX2,MEF2C,ZNF354C,HMG20A,TCF7L2,ZNF420,HIC1,GTF3A and two novel genes had the highest regulatory impact factor scores. These data can help to understand how puberty influences uterine function. [ABSTRACT FROM AUTHOR]

To understand genes, pathways, and networks related to puberty, we characterized the transcriptome of two tissues: the pituitary gland and ovaries. Samples were harvested from pre- and postpubertal Brahman heifers (same age group). Brahman heifers (Bos indicus) are older at puberty compared with Bos taurus, a productivity issue. With RNA sequencing, we identified differentially expressed (DEx) genes and important transcription factors (TF) and predicted coexpression networks. The number of DEx genes detected in the pituitary gland was 284 (P < 0.05), and VWC2L was the most DEx gene (fold change = 4.12, P = 0.01). The gene VWC2L promotes bone mineralization through transforming growth factor-β (TGFβ) signaling. Further studies of the link between bone mineralization and puberty could target VWC2L. In ovaries, 3,871 genes were DEx (P < 0.05). Four highly DEx genes were noteworthy for their function: SLC6A13 (a γ-aminobutyric acid [GABA] transporter), OXT (oxytocin), and NPY (neuropeptide Y) and its receptor NPY2R. These genes had higher ovarian expression in postpubertal heifers. The GABA and its receptors and transporters were expressed in the ovaries of many mammals, suggesting a role for this pathway beyond the brain. The OXT pathway has been known to influence the timing of puberty in rats, via modulation of GnRH. The effects of NPY at the hypothalamus, pituitary gland, and ovaries have been documented. Neuropeptide Y and its receptors are known factors in the release of GnRH, similar to OXT and GABA, although their roles in ovarian tissue are less clear. Pathways previously related to puberty such as TGFβ signaling (P = 6.71 × 10-5), Wnt signaling (P = 4.1 × 10-2), and peroxisome proliferator-activated receptor (PPAR) signaling (P = 4.84 × 10-2) were enriched in our data set. Seven genes were identified as key TF in both tissues: HIC2, ZIC4, ZNF219, ZSCAN26, LHX1, OLIG1, and a novel gene. An ovarian subnetwork created with TF and significant ovarian DEx genes revealed five zinc fingers as regulators: ZNF507, ZNF12, ZNF512, ZNF184, and ZNF432. Recent work of hypothalamic gene expression also pointed to zinc fingers as TF for bovine puberty. Although some zinc fingers may be ubiquitously expressed, the identification of DEx genes in common across tissues points to key regulators of puberty. The hypothalamus and pituitary gland had eight DEx genes in common. The hypothalamus and ovaries had 89 DEx genes in common. The pituitary gland and ovaries had 48 DEx genes in common. Our study confirmed the complexity of puberty and suggested further investigation on genes that code zinc fingers. [ABSTRACT FROM AUTHOR]

Puberty onset is a developmental process influenced by genetic determinants, environment, and nutrition. Mutations and regulatory gene networks constitute the molecular basis for the genetic determinants of puberty onset. The emerging knowledge of these genetic determinants presents opportunities for innovation in the breeding of early pubertal cattle. This paper presents new data on hypothalamic gene expression related to puberty in Bos indicus (Brahman) in age- and weight-matched heifers. Six postpubertal heifers were compared with 6 prepubertal heifers using whole-genome RNA sequencing methodology for quantification of global gene expression in the hypothalamus. Five transcription factors (TF) with potential regulatory roles in the hypothalamus were identified in this experiment: E2F8, NFAT5, SIX5, ZBTB38, and ZNF605. These TF genes were significantly differentially expressed in the hypothalamus of postpubertal versus prepubertal heifers and were also identified as significant according to the applied regulatory impact factor metric (P < 0.05). Two of these 5 TF, ZBTB38 and ZNF605, were zinc fingers, belonging to a gene family previously reported to have a central regulatory role in mammalian puberty. The SIX5 gene belongs to the family of homologues of Drosophila sine oculis (SIX) genes implicated in transcriptional regulation of gonadotrope gene expression. Tumor-related genes such as E2F8 and NFAT5 are known to affect basic cellular processes that are relevant in both cancer and developmental processes. Mutations in NFAT5 were associated with puberty in humans. Mutations in these TF, together with other genetic determinants previously discovered, could be used in genomic selection to predict the genetic merit of cattle (i.e., the likelihood of the offspring presenting earlier than average puberty for Brahman). Knowledge of key mutations involved in genetic traits is an advantage for genomic prediction because it can increase its accuracy. [ABSTRACT FROM AUTHOR]

Background: Asian buffaloes (Bubalus bubalis) have an important socio-economic role. The majority of the population is situated in developing countries. Due to the scarce resources in these countries, very few species-specific biotechnology tools exist and a lot of cattle-derived technologies are applied to buffaloes. However, the application of cattle genomic tools to buffaloes is not straightforward and, as results suggested, despite genome sequences similarity the genetic polymorphisms are different. Results: The first SNP chip genotyping platform designed specifically for buffaloes has recently become available. Herein, a genome-wide association study (GWAS) and gene network analysis carried out in buffaloes is presented. Target phenotypes were six milk production and four reproductive traits. GWAS identified SNP with significant associations and suggested candidate genes that were specific to each trait and also genes with pleiotropic effect, associated to multiple traits. Conclusions: Network predictions of interactions between these candidate genes may guide further molecular analyses in search of disruptive mutations, help select genes for functional experiments and evidence metabolism differences in comparison to cattle. The cattle SNP chip does not offer an optimal coverage of buffalo genome, thereafter the development of new buffalo-specific genetic technologies is warranted. An annotated reference genome would greatly facilitate genetic research, with potential impact to buffalo-based dairy production. [ABSTRACT FROM AUTHOR]

Deposition of intramuscular fat, or "marbling," in beef cattle contributes significantly to meat quality variables, including juiciness, flavor, and tenderness. The accumulation of intramuscular fat is largely influenced by the genetic background of cattle, as well as their age and nutrition. To identify genes that can be used as early biomarkers for the prediction of marbling capacity, we studied the muscle transcriptome of 2 cattle crossbreeds with contrasting intramuscular fat content. The transcriptomes of marbling LM tissue of heifers from Wagyu × Hereford (W × H; n = 6) and Piedmontese × Hereford (P × H; n = 7) crosses were profiled by using a combination of complementary DNA microarray and quantitative reverse transcription-PCR. Five biopsies of LM were taken from each animal at approximately 3, 7, 12, 20, and 25 mo from birth. Tissue was also collected from the LM of each animal at slaughter (approximately 30 mo). Microarray experiments, conducted on the first 3 biopsies of 2 animals from each crossbreed, identified 97 differentially expressed genes. The gene expression results indicated that the LM transcriptome of animals with high marbling potential (W × H) could be reliably distinguished from less marbled animals (P × H) when the animals were as young as 7 mo of age. At this early age, one cannot reliably determine meaningful differences in intramuscular fat deposition. We observed greater expression of a set of adipogenesis- and lipogenesis-related genes in the LM of young W × H animals compared with their P × H contemporaries. In contrast, genes highly expressed in P × H animals were associated with mitochondrial oxidative activity. Further quantitative reverse transcription-PCR experiments revealed that the messenger RNA of 6 of the lipogenesis-related genes also peaked at the age of 20 to 25 mo in W × H animals. The messenger RNA expression of ADIPOQ, SCD, and THRSP was highly correlated with intramuscular fat content of an individual in W × H animals. Our study provides clear evidence of early molecular changes associated with marbling and also identifies specific time frames when intramuscular fat development in cattle muscle can be detected by using gene expression. This information could be used by animal scientists to design optimal nutrition for high marbling potential. In addition, the genes found to be highly expressed during development of marbling could be used to develop genetic markers or biomarkers to assist with beef production strategies. [ABSTRACT FROM AUTHOR]

Gene expression profiles of LM from beef cattle that underwent significant postweaning undernutrition were studied using complementary DNA (cDNA) microarrays. After 114 d of undernutrition, the RNA from LM showed 2- to 6-fold less expression of many genes from the classes of muscle structural proteins, muscle metabolic enzymes, and extracellular matrix compared with animals on a rapid growth diet. The expression levels of these genes had mostly returned to pretreatment levels after 84 d of realimentation. The gene expression changes associated with undernutrition and BW loss showed an emphasis on downregulation of gene expression specific to fast-twitch fibers, typical of starving mammals, with a preferential atrophy of glycolytic fast-twitch fibers. We also identified a small group of genes that showed 2- to 5-fold elevated expression in LM after 114 d of undernutrition. Putative roles for these genes in atrophying skeletal muscle are regulation of myogenic differentiation (CSRP3), maintenance of mesenchymal stem cells (CYR61), modulation of membrane function (TM4SF2), prevention of oxidative damage (SESN1), and regulation of muscle protein degradation (SQSTM1). A significant increase in stearoyl-CoA desaturase (SCD) gene expression was observed in atrophying muscle, suggesting either that increased fatty acid synthesis is part of the tissue response to caloric restriction, or that SCD plays another role in energy metabolism in the mixed cellular environment of bovine skeletal muscle. [ABSTRACT FROM AUTHOR]

In functional genomic laboratories, it is common to use the same microarray slide across studies, each investigating a unique biological question, and each analyzed separately due to computational limitations and/or because there is no hybridization of samples from different studies on one slide. However, the question of analyzing data from multiple studies is a major current issue in microarray data analysis because there are gains to be made in the accuracy of estimated effects by exploiting a covariance structure between gene expression data across studies. We propose an approach for combining multiple studies using multivariate mixed models, with the assumption of a nonzero correlation among genes across experiments, while imposing a null residual covariance. We applied this method to jointly analyze three experiments in genetics of cattle with a total of 54 arrays, each with 19,200 spots and 7,638 elements. The resulting seven-variate model contains 752,476 equations and 56 covariances. To identify differentially expressed genes, we applied model-based clustering to a linear combination of the random gene × variety interaction effect. We enhanced the biological interpretation of the results by applying an iterative algorithm to identify the gene ontology classes that significantly changed in each experiment. We found 118 elements with coordinate expression that clustered into distinct biological functions such as adipogenesis and protein turnover. These results contribute to our understanding of the mechanistic processes involved in adipogenesis and nutrient partitioning. [ABSTRACT FROM AUTHOR]

We proposed a novel statistical approach for the analysis of cDNA experiments based on mixed-model methodology combined with mixtures of distributions. Our objective was to detect genes that may be involved in conferring heritable differences in susceptibility to common infections in intensive pig production. We employed a microarray expression profiling strategy and a mixed-model approach to the analysis of the expression data. A cDNA microarray of pig with 6,420 probes from immune tissues and cells was used to compare gene expression in peripheral blood leukocytes of two pigs showing extreme performance in their response to infection with Actinobacillus pleuropneurnoniae. Principal components analyses were used to identify the two most extreme-performing pigs after infection (i.e., pigs whose measured responses to infection fell at the extremes). Blood samples and expression profiles from 0 to 24 h after infection were compared using a bivariate, mixed-model approach, in which the effect gene × immunological status interaction was treated as a random effect. Bayesian model-based clustering via mixtures of normal distributions of the resulting BLUP of the random interaction was approached and resulted in a list of 307 differentially expressed genes, of which 179 were down-regulated in the susceptible pig. The majority of the differentially expressed genes were derived from a cDNA library of leukocytes of A. pleuropneumoniae-challenged pigs that were subtracted against leukocytes before the challenge. These results provide evidence that the proposed statistical approach was useful in enhancing the knowledge of the mechanisms involved in the genetics of the immune response. [ABSTRACT FROM AUTHOR]