An Always Correlated gene expression landscape for ovine skeletal muscle, lessons learnt from comparison with an "equivalent" bovine landscape

Within- and between-Breed Selection Signatures in the Original and Improved Valachian Sheep

This study explored the genomic diversity and selection signatures in two Slovakian national breeds, the Original Valachian and the Improved Valachian sheep. As they are an important animal genetic resource within the country, but with decreasing population size, our aim is to identify potentially valuable genomic regions. A total of 97 sheep (18 male and 79 female) from the Original Valachian, and 69 sheep (25 male and 44 female) from the Improved Valachian populations were genotyped using the GeneSeek GGP Ovine 50 K chip. The inbreeding levels were assessed with runs of homozygosity (ROH). The selection signatures within breeds were identified based on the top 1% of most homozygous regions within the breed, the so-called ROH islands. The selection signatures between breeds were assessed based on variance in linkage disequilibrium. Overall, we have identified selection signatures with quantitative trait loci (QTL) and genes pointing towards all three production purposes of the Valachian sheep, milk, meat, and wool, including their quality characteristics. Another group with apparent large importance was the various traits related to health and resistance to parasites, which is well in line with the sturdy nature of this breed.

Gene co-expression networks contributing to the expression of compensatory growth in metabolically active tissues in cattle

Compensatory growth (CG) is an accelerated growth phenomenon which occurs in animals upon re-alimentation following a period of dietary restriction. The objective of this study was to perform gene co-expression analysis on metabolic tissues of animals undergoing CG, in order to elucidate the molecular control governing this phenomenon. Thirty Holstein Friesian bulls were fed a restricted diet for 125 days, after which they received feed ad libitum. Following 55 days of ad libitum feeding all animals were slaughtered. RNAseq and gene co-expression analyses were performed on tissue samples collected at slaughter including liver, rumen papillae and jejunum epithelium tissues. A period of CG resulted in 15 networks of co-expressed genes. One network of genes, involved in proteasome core complex, signal transduction and protein synthesis was found to be similar across liver and jejunum tissue datasets (r = 0.68, P = 0.04). Results from this study also showed that a large portion of co-expressed genes had not previously been implicated in the expression of CG, thus this study identifies novel genes involved in controlling CG across tissues, with hub genes holding potential for use as biomarkers for the selection of animals with a greater propensity to display CG.

Multi-tissue omics analyses reveal molecular regulatory networks for puberty in composite beef cattle

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.

A marker-derived gene network reveals the regulatory role of PPARGC1A, HNF4G, and FOXP3 in intramuscular fat deposition of beef cattle

High intramuscular fat (IMF) awards price premiums to beef producers and is associated with meat quality and flavor. Studying gene interactions and pathways that affect IMF might unveil causative physiological mechanisms and inform genomic selection, leading to increased accuracy of predictions of breeding value. To study gene interactions and pathways, a gene network was derived from genetic markers associated with direct measures of IMF, other fat phenotypes, feedlot performance, and a number of meat quality traits relating to body conformation, development, and metabolism that might be plausibly expected to interact with IMF biology. Marker associations were inferred from genomewide association studies (GWAS) based on high density genotypes and 29 traits measured on 10,181 beef cattle animals from 3 breed types. For the network inference, SNP pairs were assessed according to the strength of the correlation between their additive association effects across the 29 traits. The co-association inferred network was formed by 2,434 genes connected by 28,283 edges. Topological network parameters suggested a highly cohesive network, in which the genes are strongly functionally interconnected. Pathway and network analyses pointed towards a trio of transcription factors (TF) as key regulators of carcass IMF: PPARGC1A, HNF4G, and FOXP3. Importantly, none of these genes would have been deemed as significantly associated with IMF from the GWAS. Instead, a total of 313 network genes show significant co-association with the 3 TF. These genes belong to a wide variety of biological functions, canonical pathways, and genetic networks linked to IMF-related phenotypes. In summary, our GWAS and network predictions are supported by the current literature and suggest a cooperative role for the 3 TF and other interacting genes including CAPN6, STC2, MAP2K4, EYA1, COPS5, XKR4, NR2E1, TOX, ATF1, ASPH, TGS1, and TTPA as modulators of carcass and meat quality traits in beef cattle.