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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 (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: , , , , and . 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 ( < 0.05). Two of these 5 TF, and , were zinc fingers, belonging to a gene family previously reported to have a central regulatory role in mammalian puberty. The gene belongs to the family of homologues of Drosophila sine oculis () genes implicated in transcriptional regulation of gonadotrope gene expression. Tumor-related genes such as and are known to affect basic cellular processes that are relevant in both cancer and developmental processes. Mutations in 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.

The objective of this study was to examine five different sources of RNA, namely mammary gland tissue (MGT), milk somatic cells (SC), laser microdissected mammary epithelial cells (LCMEC), milk fat globules (MFG) and antibody-captured milk mammary epithelial cells (mMEC) to analyze the bovine mammary gland transcriptome using RNA-Sequencing. Our results provide a comparison between different sampling methods (invasive and non-invasive) to define the transcriptome of mammary gland tissue and milk cells. This information will be of value to investigators in choosing the most appropriate sampling method for different research applications to study specific physiological states during lactation. One of the simplest procedures to study the transcriptome associated with milk appears to be the isolation of total RNA directly from SC or MFG released into milk during lactation. Our results indicate that the SC and MFG transcriptome are representative of MGT and LCMEC and can be used as effective and alternative samples to study mammary gland expression without the need to perform a tissue biopsy.

Inorganic arsenic oxides have been identified as carcinogens in several human tissues, including epidermis. Due to the chemical similarity between trivalent inorganic arsenic (arsenite) and antimony (antimonite), we hypothesized that common intracellular targets lead to similarities in cellular responses. Indeed, transcriptional and proteomic profiling revealed remarkable similarities in differentially expressed genes and proteins resulting from exposure of cultured human epidermal keratinocytes to arsenite and antimonite in contrast to comparisons of arsenite with other metal compounds. These data were analyzed to predict upstream regulators and affected signaling pathways following arsenite and antimonite treatments. A majority of the top findings in each category were identical after treatment with either compound. Inspection of the predicted upstream regulators led to previously unsuspected roles for oncostatin M, corticosteroids and ephrins in mediating cellular response. The influence of these predicted mediators was then experimentally verified. Together with predictions of transcription factor effects more generally, the analysis has led to model signaling networks largely accounting for arsenite and antimonite action. The striking parallels between responses to arsenite and antimonite indicate the skin carcinogenic risk of exposure to antimonite merits close scrutiny.

Reactive Nitrogen Species (RNS) are a group of bactericidal molecules produced by macrophages in response to pathogens in a process called oxidative burst. Nitric oxide (NO-) is a member of RNS produced from arginine by inducible Nitric Oxide Synthase (iNOS) enzyme. The activity of iNOS and production of NO- by macrophages following stimulation is one of the indicators of macrophage polarization towards M1/proinflammatory. Production of NO- by bovine monocyte-derived macrophage (MDM) and mouse peritoneal macrophages has been shown to be strongly associated with host genetic with the heritability of 0.776 in bovine MDM and 0.8 in mouse peritoneal macrophages. However, the mechanism of genetic regulation of macrophage response has remained less explored. In the current study, the transcriptome of bovine MDMs was compared between two extreme phenotypes that had been classified as high and low responder based on NO- production. The results showed that 179 and 392 genes were differentially expressed (DE) between high and low responder groups at 3 and 18 hours after exposure to Escherichia coli, respectively. A set of 11 Transcription Factors (TFs) (STAT1, IRF7, SPI1, STAT4, IRF1, HIF1A, FOXO3, REL, NFAT5, HIC1, and IRF4) at 3 hours and a set of 13 TFs (STAT1, IRF1, HIF1A, STAT4, ATF4, TP63, EGR1, CDKN2A, RBL1, E2F1, PRDM1, GATA3, and IRF4) at 18 hours after exposure to E. coli were identified to be differentially regulated between the high and low responder phenotypes. These TFs were found to be divided into two clusters of inflammatory- and hypoxia-related TFs. Functional analysis revealed that some key canonical pathways such as phagocytosis, chemotaxis, antigen presentation, and cell-to-cell signalling are enriched among the over-expressed genes by high responder phenotype. Based on the results of this study, it was inferred that the functional characteristics of bovine MDMs are associated with NO-based classification. Since NO- production is strongly associated with host genetics, this study for the first time shows the distinct proinflammatory profiles of macrophages are controlled by the natural genetic polymorphism in an outbred population. In addition, the results suggest that genetics can be considered as a new dimension in the current model of macrophage polarization which is currently described by the combination of stimulants, only.

BackgroundMouse chromosome 2 is linked to growth and body fat phenotypes in many mouse crosses. With the goal to identify the underlying genes regulating growth and body fat on mouse chromosome 2, we developed five overlapping subcongenic strains that contained CAST/EiJ donor regions in a C57BL/6J (hg/hg) background (hg is a spontaneous deletion of 500 Kb on mouse chromosome 10). To fine map QTL on distal mouse chromosome 2 a total of 1,712 F2 mice from the five subcongenic strains, plus 278 F2 mice from the HG2D founder congenic strain were phenotyped and analyzed. Interval mapping (IM) and composite IM (CIM) were performed on body weight and body fat traits on a combination of SNP and microsatellite markers, which generated a high-density genotyping panel.ResultsPhenotypic analysis and interval mapping of total fat mass identified two QTL on distal mouse chromosome 2. One QTL between 150 and 161 Mb, Fatq2a, and the second between 173.3 and 175.6 Mb, Fatq2b. The two QTL reside in different congenic strains with significant total fat differences between homozygous cast/cast and b6/b6 littermates. Both of these QTL were previously identified only as a single QTL affecting body fat, Fatq2. Furthermore, through a novel approach referred here as replicated CIM, Fatq2b was mapped to the Gnas imprinted locus.ConclusionsThe integration of subcongenic strains, high-density genotyping, and CIM succesfully partitioned two previously linked QTL 20 Mb apart, and the strongest QTL, Fatq2b, was fine mapped to a ~2.3 Mb region interval encompassing the Gnas imprinted locus.

The liver plays a central role in metabolism and produces important hormones. Hepatic estrogen receptors and the release of insulin-like growth factor 1 (IGF1) are critical links between liver function and the reproductive system. However, the role of liver in pubertal development is not fully understood. To explore this question, we applied transcriptomic analyses to liver samples of pre- and post-pubertal Brahman heifers and identified differentially expressed (DE) genes and genes encoding transcription factors (TFs). Differential expression of genes suggests potential biological mechanisms and pathways linking liver function to puberty. The analyses identified 452 DE genes and 82 TF with significant contribution to differential gene expression by using a regulatory impact factor metric. Brain-derived neurotrophic factor was observed as the most down-regulated gene (P = 0.003) in post-pubertal heifers and we propose this gene influences pubertal development in Brahman heifers. Additionally, co-expression network analysis provided evidence for three TF as key regulators of liver function during pubertal development: the signal transducer and activator of transcription 6, PBX homeobox 2, and polybromo 1. Pathway enrichment analysis identified transforming growth factor-beta and Wnt signaling pathways as significant annotation terms for the list of DE genes and TF in the co-expression network. Molecular information regarding genes and pathways described in this work are important to further our understanding of puberty onset in Brahman heifers. [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 is a complex physiological event by which animals mature into an adult capable of sexual reproduction. In order to enhance our understanding of the genes and regulatory pathways and networks involved in puberty, we characterized the transcriptome of five reproductive tissues (i.e. hypothalamus, pituitary gland, ovary, uterus, and endometrium) as well as tissues known to be relevant to growth and metabolism needed to achieve puberty (i.e., longissimus dorsi muscle, adipose, and liver). These tissues were collected from pre- and post-pubertal Brangus heifers (3/8 Brahman; Bos indicus x 5/8 Angus; Bos taurus) derived from a population of cattle used to identify quantitative trait loci associated with fertility traits (i.e., age of first observed corpus luteum (ACL), first service conception (FSC), and heifer pregnancy (HPG)). In order to exploit the power of complementary omics analyses, pre- and post-puberty co-expression gene networks were constructed by combining the results from genome-wide association studies (GWAS), RNA-Seq, and bovine transcription factors. Eight tissues among pre-pubertal and post-pubertal Brangus heifers revealed 1,515 differentially expressed and 943 tissue-specific genes within the 17,832 genes confirmed by RNA-Seq analysis. The hypothalamus experienced the most notable up-regulation of genes via puberty (i.e., 204 out of 275 genes). Combining the results of GWAS and RNA-Seq, we identified 25 loci containing a single nucleotide polymorphism (SNP) associated with ACL, FSC, and (or) HPG. Seventeen of these SNP were within a gene and 13 of the genes were expressed in uterus or endometrium. Multi-tissue omics analyses revealed 2,450 co-expressed genes relative to puberty. The pre-pubertal network had 372,861 connections whereas the post-pubertal network had 328,357 connections. A sub-network from this process revealed key transcriptional regulators (i.e., PITX2, FOXA1, DACH2, PROP1, SIX6, etc.). Results from these multi-tissue omics analyses improve understanding of the number of genes and their complex interactions for puberty in cattle. [ABSTRACT FROM AUTHOR]

Measures of heifer fertility are economi-cally relevant traits for beef production systems and knowledge of candidate genes could be incorporated into future genomic selection strategies. Ten traits related to growth and fertility were measured in 890 Brangus heif-ers (3/8 Brahman x 5/8 Angus, from 67 sires). These traits were: BW and hip height adjusted to 205 and 365 d of age, postweaning ADG, yearling assessment of carcass traits (i.e., back fat thickness, intramuscular fat, and LM area), as well as heifer pregnancy and first service con-ception (FSC). These fertility traits were collected from controlled breeding seasons initiated with estrous syn-chronization and Al targeting heifers to calve by 24 mo of age. The BovineSNP50 BeadChip was used to ascertain 53,692 SNP genotypes for -802 heifers. Associations of genotypes and phenotypes were performed and SNP effects were estimated for each trait. Minimally associ-ated SNP (P < 0.05) and their effects across the 10 traits formed the basis for an association weight matrix and its derived gene network related to FSC (57.3% success and heritability = 0.06 ± 0.05). These analyses yielded 1,555 important SNP, which inferred genes linked by 113,873 correlations within a network. Specifically, 1,386 SNP were nodes and the 5,132 strongest correlations (|r| > 0.90) were edges. The network was filtered with genes queried from a transcriptome resource created from deep sequencing of RNA (i.e., RNA-Seq) from the hypothala-mus of a prepubertal and a postpubertal Brangus heifer. The remaining hypothalamic-influenced network con-tained 978 genes connected by 2,560 edges or predicted gene interactions. This hypothalamic gene network was enriched with genes involved in axon guidance, which is a pathway known to influence pulsatile release of LHRH. There were 5 transcription factors with 21 or more connections: ZMAT3, STAT6, RFX4, PLAGL1, and NR6A1 for FSC. The SNP that identified these genes were intragenic and were on chromosomes 1, 5, 9, and 11. Chromosome 5 harbored both STAT6 and RFX4. The large number of interactions and genes observed with network analyses of multiple sources of genomic data (i.e., GWAS and RNA-Seq) support the concept of FSC being a polygenic trait. [ABSTRACT FROM AUTHOR]