An across breed, diet and tissue analysis reveals the transcription factor NR1H3 as a key mediator of residual feed intake in beef cattle.

BACKGROUND: Provision of feed is a major determinant of overall profitability in beef production systems, accounting for up to 75% of the variable costs. Thus, improving cattle feed efficiency, by way of determining the underlying genomic control and subsequently selecting for feed efficient cattle, provides a method through which feed input costs may be reduced. The objective of this study was to undertake gene co-expression network analysis using RNA-Sequence data generated from Longissimus dorsi and liver tissue samples collected from steers of two contrasting breeds (Charolais and Holstein-Friesian) divergent for residual feed intake (RFI), across two consecutive distinct dietary phases (zero-grazed grass and high-concentrate). Categories including differentially expressed genes (DEGs) based on the contrasts of RFI phenotype, breed and dietary source, as well as key transcription factors and proteins secreted in plasma were utilised as nodes of the gene co-expression network. RESULTS: Of the 2,929 DEGs within the network analysis, 1,604 were reported to have statistically significant correlations (≥ 0.80), resulting in a total of 43,876 significant connections between genes. Pathway analysis of clusters of co-expressed genes revealed enrichment of processes related to lipid metabolism (fatty acid biosynthesis, fatty acid ß-oxidation, cholesterol biosynthesis), immune function, (complement cascade, coagulation system, acute phase response signalling), and energy production (oxidative phosphorylation, mitochondrial L-carnitine shuttle pathway) based on genes related to RFI, breed and dietary source contrasts. CONCLUSIONS: Although similar biological processes were evident across the three factors examined, no one gene node was evident across RFI, breed and diet contrasts in both liver and muscle tissues. However within the liver tissue, the IRX4, NR1H3, HOXA13 and ZNF648 gene nodes, which all encode transcription factors displayed significant connections across the RFI, diet and breed comparisons, indicating a role for these transcription factors towards the RFI phenotype irrespective of diet and breed. Moreover, the NR1H3 gene encodes a protein secreted into plasma from the hepatocytes of the liver, highlighting the potential for this gene to be explored as a robust biomarker for the RFI trait in beef cattle.

Low-density SNP panel for efficient imputation and genomic selection of milk production and technological traits in dairy sheep.

The present study aimed to ascertain how different strategies for leveraging genomic information enhance the accuracy of estimated breeding values for milk and cheese-making traits and to evaluate the implementation of a low-density (LowD) SNP chip designed explicitly for that aim. Thus, milk samples from a total of 2,020 dairy ewes from 2 breeds (1,039 Spanish Assaf and 981 Churra) were collected and analyzed to determine 3 milk production and composition traits and 2 traits related to milk coagulation properties and cheese yield. The 2 studied populations were genotyped with a customized 50K Affymetrix SNP chip (Affymetrix Inc.) containing 55,627 SNP markers. The prediction accuracies were obtained using different multitrait methodologies, such as the BLUP model based on pedigree information, the genomic BLUP (GBLUP), and the BLUP at the SNP level (SNP-BLUP), which are based on genotypic data, and the single-step GBLUP (ssGBLUP), which combines both sources of information. All of these methods were analyzed by cross-validation, comparing predictions of the whole population with the test population sets. Additionally, we describe the design of a LowD SNP chip (3K) and its prediction accuracies through the different methods mentioned previously. Furthermore, the results obtained using the LowD SNP chip were compared with those based on the 50K SNP chip data sets. Finally, we conclude that implementing genomic selection through the ssGBLUP model in the current breeding programs would increase the accuracy of the estimated breeding values compared with the BLUP methodology in the Assaf (from 0.19 to 0.39) and Churra (from 0.27 to 0.44) dairy sheep populations. The LowD SNP chip is cost-effective and has proven to be an accurate tool for estimating genomic breeding values for milk and cheese-making traits, microsatellite imputation, and parentage verification. The results presented here suggest that the routine use of this LowD SNP chip could potentially increase the genetic gains of the breeding selection programs of the 2 Spanish dairy sheep breeds considered here.

Islands of runs of homozygosity indicate selection signatures in Ovis aries 6 (OAR6) of French dairy sheep.

Runs of homozygosity (ROH) are contiguous homozygous segments of the genome where the haplotypes inherited from each parent are identical. The occurrence of ROH is not randomly distributed across the genome, and ROH islands across many animals may be the result of selective pressure. The objective of this study was to demonstrate that the presence of ROH islands may be indicative of selection signatures in French dairy sheep breeds and subpopulations. The data set available included animals (artificial insemination males) from various breeds and subpopulations: Basco-Béarnaise breed (321 individuals), Manech Tête Noire breed (329 individuals), Manech Tête Rousse breed (1,906 individuals), Lacaune Confederation subpopulation (3,030 individuals), and Lacaune Ovitest subpopulation (3,114 individuals). Animals were genotyped with the Illumina OvineSNP50 BeadChip. After applying filtering criteria, the genomic data included 38,287 autosomal SNP distributed across 26 chromosomes and 8,700 individuals. One island of ROH was detected on OAR6 in the same genomic position across animals (between 30 and 40 Mb). Global Wright's differentiation coefficients for 2 SNP within this ROH island were high (0.67-0.68). The linkage disequilibrium between both SNP was also elevated (0.98). The divergence in allele frequencies in those SNP grouped Basco-Béarnaise, Manech Tête Noire, and Manech Tête Rousse breeds in one cluster and Lacaune Confederation and Lacaune Ovitest subpopulations in another cluster. The closest candidate genes are NCAPG and LCORL, which have been reported to be under positive selection and suggested to control weight and height in sheep. The preliminary identification of ROH suggests the presence of selection. However, for the identification of potential candidate genes, ROH detection should be combined with other approaches to improve mapping accuracy.

Behavior of the Linear Regression method to estimate bias and accuracies with correct and incorrect genetic evaluation models.

Bias in genetic evaluations has been a constant concern in animal genetics. The interest in this topic has increased in the last years, since many studies have detected overestimation (bias) in estimated breeding values (EBV). Detecting the existence of bias, and the realized accuracy of predictions, is therefore of importance, yet this is difficult when studying small data sets or breeds. In this study, we tested by simulation the recently presented method Linear Regression (LR) for estimation of bias, slope, and accuracy of pedigree EBV. The LR method computes statistics by comparing EBV from a data set containing old, partial information with EBV from a data set containing all information (old and new, a whole data set) for the same individuals. The method proposes an estimator for bias (Δpˆ), an estimator of slope (bpˆ), and 3 estimators related to accuracies: the ratio between accuracies [Formula: see text] the reliability of the partial data set (accp2ˆ), and the ratio of reliabilities (ρp,w2ˆ). We simulated a dairy scheme for low (0.10) and moderate (0.30) heritabilities. In both cases, we checked the behavior of the estimators for 3 scenarios: (1) when the evaluation model is the same as the model used to simulate the data; (2) when the evaluation model uses an incorrect heritability; and (3) when the data includes an environmental trend. For scenarios in which the evaluation model was correct, the LR method was capable of correctly estimating bias, slope, and accuracies, with better performance for higher heritability [i.e., corr(bp,bpˆ) was 0.45 for h2 = 0.10 and 0.59 for h2 = 0.30]. In cases of the use of incorrect heritabilities in the evaluation model, the bias was correctly estimated in direction but not in magnitude. In the same way, the magnitudes of bias and of slope were underestimated in scenarios with environmental trends in data, except for cases in which contemporary groups were random and greatly shrunken. In general, accuracies were well estimated in all scenarios. The LR method is capable of checking bias and accuracy in all cases, if the evaluation model is reasonably correct or robust, and its estimations are more precise with more information (e.g., high heritability). If the model uses an incorrect heritability or a hidden trend exists in the data, it is still possible to estimate the direction and existence of bias and slope but not always their magnitudes.

Pre- and post-puberty expression of genes and proteins in the uterus of Bos indicus heifers: the luteal phase effect post-puberty.

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.

Genomic inbreeding depression for climatic adaptation of tropical beef cattle.

Inbreeding has the potential to negatively impact animal performance. Strategies to monitor and mitigate inbreeding depression require that it can be accurately estimated. Here, we used genomewide SNP data to explore 3 alternative measures of genomic inbreeding: the diagonal elements of the genomic relationship matrix (FGRM), the proportion of homozygous SNP (FHOM), and the proportion of the genome covered by runs of homozygosity (FROH). We used 2,111 Brahman (BR) and 2,550 Tropical Composite (TC) cattle with phenotypes recorded for 10 traits of relevance to tropical adaptation. We further explored 3 marker densities ranging from a high-density chip (729,068 SNP), a medium-density chip (71,726 SNP) specifically designed for cattle, and a low-density chip (18,860 SNP) associated with the measures of inbreeding. Measures of FGRM were highly correlated across the 3 SNP densities and negatively correlated with FHOM and FROH in the BR population. In both populations, there was a strong positive correlation for each measure of inbreeding across the 3 SNP panels. We found significant ( < 0.01) inbreeding depression for various traits, particularly when using the highest-density SNP chip in the BR population, where inbreeding was negatively associated with coat color and coat type such that inbred animals presented shorter, slicker, and lighter coats. Based on FGRM using the medium-density chip, we found that a 1% increase in inbreeding in the BR and TC populations was associated with a decrease of 0.514 and 0.579 kg BW, respectively, in yearlings. In the TC population, a 1% increase in FHOM was associated with a decrease in BCS of -0.636% ( < 0.001). The low-density chip, comprising SNP associated with inbreeding, captured genes, and regions with pleiotropic effects ( < 0.001). However, it did not improve our ability to identify inbreeding depression, relative to the use of higher-density panels. We conclude that where heterogeneous populations are present, such as in tropical environments where composite animals abound, measures of inbreeding that do not depend on allele frequencies, such as FHOM and FROH, are preferable for estimating genomic inbreeding. Finally, the sustainable intensification of livestock systems in tropical regions will rely on genetic safeguards to ensure that productivity is improved while also adapting animals to cope with climate change. The results of this study are a step toward achieving that goal.

Data compression can discriminate broilers by selection line, detect haplotypes, and estimate genetic potential for complex phenotypes.

Accurately establishing the relationships among individuals lays the foundation for genetic analyses such as genome-wide association studies and identification of selection signatures. Of particular interest to the poultry industry are estimates of genetic merit based on molecular data. These estimates can be commercially exploited in marker-assisted breeding programs to accelerate genetic improvement. Here, we test the utility of a new method we have recently developed to estimate animal relatedness and applied it to genetic parameter estimation in commercial broilers. Our approach is based on the concept of data compression from information theory. Using the real-world compressor gzip to estimate normalized compression distance (NCD) we have built compression-based relationship matrices (CRM) for 988 chickens from 4 commercial broiler lines-2 male and 2 female lines. For all pairs of individuals, we found a strong negative relationship between the commonly used genomic relationship matrix (GRM) and NCD. This reflects the fact that "similarity" is the inverse of "distance." The CRM explained more genetic variation than the corresponding GRM in 2 of 3 phenotypes, with corresponding improvements in accuracy of genomic-enabled predictions of breeding value. A sliding-window version of the analysis highlighted haplotype regions of the genome apparently under selection in a line-specific manner. In the male lines, we retrieved high population-specific scores for IGF-1 and a cognate receptor, INSR. For the female lines, we detected an extreme score for a region containing a reproductive hormone receptor (GNRHR). We conclude that our compression-based method is a valid approach to established relationships and identify regions under selective pressure in commercial lines of broiler chickens.

Global differential gene expression in the pituitary gland and the ovaries of pre- and postpubertal Brahman heifers.

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 () are older at puberty compared with , 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 ( < 0.05), and was the most DEx gene (fold change = 4.12, = 0.01). The gene promotes bone mineralization through transforming growth factor-ß (TGFß) signaling. Further studies of the link between bone mineralization and puberty could target . In ovaries, 3,871 genes were DEx ( < 0.05). Four highly DEx genes were noteworthy for their function: (a γ-aminobutyric acid [GABA] transporter), (), and () and its receptor . 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 pathway has been known to influence the timing of puberty in rats, via modulation of GnRH. The effects of at the hypothalamus, pituitary gland, and ovaries have been documented. and its receptors are known factors in the release of GnRH, similar to and GABA, although their roles in ovarian tissue are less clear. Pathways previously related to puberty such as TGFß signaling ( = 6.71 × 10), Wnt signaling ( = 4.1 × 10), and peroxisome proliferator-activated receptor (PPAR) signaling ( = 4.84 × 10) were enriched in our data set. Seven genes were identified as key TF in both tissues: , , , , , , and a novel gene. An ovarian subnetwork created with TF and significant ovarian DEx genes revealed five zinc fingers as regulators: , , , , and . 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.

Evaluation of non-additive genetic variation in feed-related traits of broiler chickens.

Genome-wide association mapping and genomic predictions of phenotype of individuals in livestock are predominately based on the detection and estimation of additive genetic effects. Non-additive genetic effects are largely ignored. Studies in animals, plants, and humans to assess the impact of non-additive genetic effects in genetic analyses have led to differing conclusions. In this paper, we examined the consequences of including non-additive genetic effects in genome-wide association mapping and genomic prediction of total genetic values in a commercial population of 5,658 broiler chickens genotyped for 45,176 single nucleotide polymorphism (SNP) markers. We employed mixed-model equations and restricted maximum likelihood to analyze 7 feed related traits (TRT1 - TRT7). Dominance variance accounted for a significant proportion of the total genetic variance in all 7 traits, ranging from 29.5% for TRT1 to 58.4% for TRT7. Using a 5-fold cross-validation schema, we found that in spite of the large dominance component, including the estimated dominance effects in the prediction of total genetic values did not improve the accuracy of the predictions for any of the phenotypes. We offer some possible explanations for this counter-intuitive result including the possible confounding of dominance deviations with common environmental effects such as hatch, different directional effects of SNP additive and dominance variations, and the gene-gene interactions' failure to contribute to the level of variance.

The 'heritability' of domestication and its functional partitioning in the pig.

We propose to estimate the proportion of variance explained by regression on genome-wide markers (or genomic heritability) when wild/domestic status is considered the phenotype of interest. This approach differs from the standard Fst in that it can accommodate genetic similarity between individuals in a general form. We apply this strategy to complete genome data from 47 wild and domestic pigs from Asia and Europe. When we partitioned the total genomic variance into components associated to subsets of single nucleotide polymorphisms (SNPs) defined in terms of their annotation, we found that potentially deleterious non-synonymous mutations (9566 SNPs) explained as much genetic variance as the whole set of 25 million SNPs. This suggests that domestication may have affected protein sequence to a larger extent than regulatory or other kinds of mutations. A pathway-guided analysis revealed ovarian steroidogenesis and leptin signaling as highly relevant in domestication. The genomic regression approach proposed in this study revealed molecular processes not apparent through typical differentiation statistics. We propose that at least some of these processes are likely new discoveries because domestication is a dynamic process of genetic selection, which may not be completely characterized by a static metric like Fst. Nevertheless, and despite some particularly influential mutation types or pathways, our analyses tend to rule out a simplistic genetic basis for the domestication process: neither a single pathway nor a unique set of SNPs can explain the process as a whole.

Genomic analyses of tropical beef cattle fertility based on genotyping pools of Brahman cows with unknown pedigree.

We introduce an innovative approach to lowering the overall cost of obtaining genomic EBV (GEBV) and encourage their use in commercial extensive herds of Brahman beef cattle. In our approach, the DNA genotyping of cow herds from 2 independent properties was performed using a high-density bovine SNP chip on DNA from pooled blood samples, grouped according to the result of a pregnancy test following their first and second joining opportunities. For the DNA pooling strategy, 15 to 28 blood samples from the same phenotype and contemporary group were allocated to pools. Across the 2 properties, a total of 183 pools were created representing 4,164 cows. In addition, blood samples from 309 bulls from the same properties were also taken. After genotyping and quality control, 74,584 remaining SNP were used for analyses. Pools and individual DNA samples were related by means of a "hybrid" genomic relationship matrix. The pooled genotyping analysis of 2 large and independent commercial populations of tropical beef cattle was able to recover significant and plausible associations between SNP and pregnancy test outcome. We discuss 24 SNP with significant association ( < 1.0 × 10) and mapped within 40 kb of an annotated gene. We have established a method to estimate the GEBV in young herd bulls for a trait that is currently unable to be predicted at all. In summary, our novel approach allowed us to conduct genomic analyses of fertility in 2 large commercial Brahman herds managed under extensive pastoral conditions.

Transcriptome analyses identify five transcription factors differentially expressed in the hypothalamus of post- versus prepubertal Brahman heifers.

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.

A regulatory gene network related to the porcine umami taste receptor (TAS1R1/TAS1R3).

Taste perception plays an important role in the mediation of food choices in mammals. The first porcine taste receptor genes identified, sequenced and characterized, TAS1R1 and TAS1R3, were related to the dimeric receptor for umami taste. However, little is known about their regulatory network. The objective of this study was to unfold the genetic network involved in porcine umami taste perception. We performed a meta-analysis of 20 gene expression studies spanning 480 porcine microarray chips and screened 328 taste-related genes by selective mining steps among the available 12,320 genes. A porcine umami taste-specific regulatory network was constructed based on the normalized coexpression data of the 328 genes across 27 tissues. From the network, we revealed the 'taste module' and identified a coexpression cluster for the umami taste according to the first connector with the TAS1R1/TAS1R3 genes. Our findings identify several taste-related regulatory genes and extend previous genetic background of porcine umami taste.

Genome-wide association for the outcome of fixed-time artificial insemination of Brahman heifers in northern Australia.

Fixed-time AI (FTAI) is a powerful tool for genetic improvement of extensively managed beef cattle. A genomewide association study (GWAS) was conducted to investigate genes and genetic markers associated with the outcome (pregnant or not pregnant) of FTAI in 614 commercial Brahman heifers genotyped for 18,895 SNP and imputed to 51,588 SNP. The likelihood of Brahman heifers becoming pregnant after hormonal treatment to synchronize ovulation followed by FTAI was influenced by the content of their genomes, as determined by a principal component analysis. The principal component analysis involved comparisons between the studied heifers and populations of known and ancestry. The heritability of FTAI outcome was = 0.18, which is higher than for most other reproductive outcome traits. The number of SNP associated with FTAI outcome was 101 ( < 0.001, false discovery rate = 0.53). Compared with all SNP tested, associated SNP had a tendency for highly divergent allelic frequencies between and . Associated SNP were located in nearly all chromosomes, a result that shows a complex genetic architecture that is typical of highly complex traits with low heritability. Considering this and previous GWAS that examined Brahman heifer puberty and postpartum anestrus interval, 3 genomic regions emerge as important for overall Brahman heifer fertility, which mapped to chromosomes 1, 7, and 9. Further analyses, including improved genome annotation, are required to elucidate the link between these regions and heifer fertility. Additional studies are needed to confirm SNP and gene associations reported herein and further elucidate the genetics of FTAI outcome. Future GWAS should target other Braham populations and additional cattle breeds with FTAI records, including breeds with higher ancestry.

Prospecting major genes in dairy buffaloes.

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.

Longitudinal muscle gene expression patterns associated with differential intramuscular fat in cattle.

Intramuscular fat (IMF) can improve meat product quality through its impact on flavour and juiciness. High marbling cuts can command premium prices in some countries and grading systems, but there is substantial cost involved in choosing to grain feed animals in an effort to deposit more IMF. There would be value in developing methods to predict predisposition to 'marble' well. Unfortunately, the biological mechanisms underpinning marbling remain a mystery: the key adipocyte cell populations have not been defined, there are no reliable DNA markers, no known (if any) causal mutations and gene expression analyses in the main have tended to characterise increases in expression of end-point fat metabolism proteins such as the fatty acid-binding proteins. To shed light on expression-based markers of marbling potential, we contrasted LD gene expression in high IMF Wagyu cross animals with a low IMF Piedmontese cross at various time points. The expected divergence in the fat metabolism genes FABP4, THRSP, CIDEC and ACACA between the breeds occurs surprisingly late in postnatal development at about 20 months. On the other hand, divergent expression of WISP2, RAI14 and CYP4F2 was discovered in animals at or before 12 months of age, suggesting these genes may have potential as earlier predictors of marbling potential. In line with other researchers, we found intriguing links between IMF development and connective tissue remodelling. WISP2 - a novel adipokine highly expressed and secreted by adipose precursor cells and an inhibitor of the pro-fibrotic connective tissue growth factor - emerges as a particularly attractive candidate. It is relatively upregulated in high marbling Wagyu before admission to feedlotting, somewhere between 7 and 12 months. This difference is subsequently maintained until 25 months, but not thereafter. RAI14, thought to play a role in porcine adipocyte differentiation and with links to retinoic acid metabolism, has an unusual expression profile. Its expression level increases monotonically with postnatal development, and is always higher in Wagyu than Piedmontese. Strong, sustained upregulation of the anti-inflammatory CYP4F2 in Piedmontese is consistent with Wagyu adiposity being a pro-inflammatory state. Application of regulatory impact factor analysis, a network method for identifying causal effector molecules, suggests marbling roles for transcription factors previously implicated in (1) the formation of liposarcoma (unconstrained fatty masses) (YEATS4, MDM2), (2) adipogenesis (CREBL2, SP1, STAT1) and (3) inflammation (ISGF3G, HOXB13, PML).

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.

Numerical analysis of intensity signals resulting from genotyping pooled DNA samples in beef cattle and broiler chicken.

Pooled genomic DNA has been proposed as a cost-effective approach in genomewide association studies (GWAS). However, algorithms for genotype calling of biallelic SNP are not adequate with pooled DNA samples because they assume the presence of 2 fluorescent signals, 1 for each allele, and operate under the expectation that at most 2 copies of the variant allele can be found for any given SNP and DNA sample. We adapt analytical methodology from 2-channel gene expression microarray technology to SNP genotyping of pooled DNA samples. Using 5 datasets from beef cattle and broiler chicken of varying degrees of complexity in terms of design and phenotype, continuous and dichotomous, we show that both differential hybridization (M = green minus red intensity signal) and abundance (A = average of red and green intensities) provide useful information in the prediction of SNP allele frequencies. This is predominantly true when making inference about extreme SNP that are either nearly fixed or highly polymorphic. We propose the use of model-based clustering via mixtures of bivariate normal distributions as an optimal framework to capture the relationship between hybridization intensity and allele frequency from pooled DNA samples. The range of M and A values observed here are in agreement with those reported within the context of gene expression microarray and also with those from SNP array data within the context of analytical methodology for the identification of copy number variants. In particular, we confirm that highly polymorphic SNP yield a strong signal from both channels (red and green) while lowly or nonpolymorphic SNP yield a strong signal from 1 channel only. We further confirm that when the SNP allele frequencies are known, either because the individuals in the pools or from a closely related population are themselves genotyped, a multiple regression model with linear and quadratic components can be developed with high prediction accuracy. We conclude that when these approaches are applied to the estimation of allele frequencies, the resulting estimates allow for the development of cost-effective and reliable GWAS.

Evidence for pleiotropism and recent selection in the PLAG1 region in Australian Beef cattle.

A putative functional mutation (rs109231213) near PLAG1 (BTA14) associated with stature was studied in beef cattle. Data from 8199 Bos taurus, Bos indicus and Tropical Composite cattle were used to test the associations between rs109231213 and various phenotypes. Further, 23 496 SNPs located on BTA14 were tested for association with these phenotypes, both independently and fitted together with rs109231213. The C allele of rs109231213 significantly increased hip height, weight, net food intake, age at puberty in males and females and decreased IGF-I concentration in blood and fat depth. When rs109231213 was fitted as a fixed effect in the model, there was an overall reduction in associations between other SNPs and these traits but some SNPs remained associated (P < 10(-4) ). Frequency of the mutant C allele of rs109231213 differed among B. indicus (0.52), B. taurus (0.96) and Tropical Composite (0.68). Most chromosomes carrying the C allele had the same surrounding 10 SNP haplotype, probably because the C allele was introgressed into Brahman from B. taurus cattle. A region of reduced heterozygosity surrounds the C allele; this is small in B. taurus but 20 Mb long in Brahmans, indicating recent and strong selection for the mutant allele. Thus, the C allele appears to mark a mutation that has been selected almost to fixation in the B. taurus breeds studied here and introduced into Brahman cattle during grading up and selected to a frequency of 0.52 despite its negative effects on fertility.

Genome-wide association study for inhibin, luteinizing hormone, insulin-like growth factor 1, testicular size and semen traits in bovine species.

The fertility of young bulls impacts on reproduction rates, farm profit and the rate of genetic progress in beef herds. Cattle researchers and industry therefore routinely collect data on the reproductive performance of bulls. Genome-wide association studies were carried out to identify genomic regions and genes associated with reproductive traits measured during the pubertal development of Tropical Composite bulls, from 4 to 24 months of age. Data from 1 085 bulls were collected for seven traits: blood hormone levels of inhibin at 4 months (IN), luteinizing hormone following a gonadotropin releasing hormone challenge at 4 months (LH), insulin-like growth factor 1 at 6 months (IGF1), scrotal circumference at 12 months (SC), sperm motility at 18 months (MOT), percentage of normal spermatozoa at 24 months (PNS) and age at a scrotal circumference of 26 cm (AGE26, or pubertal age). Data from 729 068 single-nucleotide polymorphisms were used in the association analysis. Significant polymorphism associations were discovered for IN, IGF1, SC, AGE26 and PNS. Based on these associations, INHBE, INHBC and HELB are proposed as candidate genes for IN regulation. Polymorphisms associated with IGF1 mapped to the PLAG1 gene region, validating a reported quantitative trait locus on chromosome 14 for IGF1. The X chromosome contained most of the significant associations found for SC, AGE26 and PNS. These findings will contribute to the identification of diagnostic genetic markers and informed genomic selection strategies to assist breeding of cattle with improved fertility. Furthermore, this work provides evidence contributing to gene function annotation in the context of male fertility.