A single nucleotide polymorphism-derived regulatory gene network underlying puberty in 2 tropical breeds of beef cattle

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.

Nutrigenomics and its role in male puberty of cattle: a mini review

Nutrigenomics a novel era in genomics research is based on puzzling issue on how nutrition and genes re-interacts. Perusal of literature reveals that very few information are available in this field and especially when it is associated with puberty in cattle which is a multigenic trait of great economic importance. Thus it opens a new area of research interest. Various markers like-gonadotropin releasing hormone/GNRH (responsible for sexual differentiation and reproduction), interstitial growth regulating factor/IGF1 (having signal controlling reproduction function linked to somatic growth); circulating metabolic hormones viz., leptin apart from GnRH and IGF1 (having impact on testicular development in peripubertal bull) are proved to be associated with male puberty in cattle. Various minerals (copper, selenium, manganese, zinc, chromium, iron and molybdenum) and vitamins (Vit. A, D, E and C) are directly or indirectly linked to male puberty. But no research till today initiated how the nutrients effect on the transcriptome/proteome/metabolome level of marker genes associated with male puberty in cattle. Application of nanotechnology to make food safer for promotion of good health has created much excitement and nanoparticles has been developed against infectious diseases (e.g., Campylobacteriosis) affecting puberty along with certain nanocarriers that can facilitate the uptake of essential nutrients associated with puberty. Much of nutrigenomics research is however in infancy and hence the present mini-review will allow building the concept among researchers and scientists to initiate research in this interesting area.

Adaptive admixture in the West African bovine hybrid zone: insight from the Borgou population

Understanding the adaptive response to environmental fluctuations represents a central issue in evolutionary biology. Population admixture between divergent ancestries has often been considered as an efficient short-term adaptation strategy. Cattle populations from the West African Bos taurus × Bos indicus hybrid zone represent a valuable resource to characterize the effect of such adaptive admixture at the genome level. We here provide a detailed assessment of the global and local genome ancestries of the Borgou breed, one of the most representative cattle of this hybrid zone. We analysed a large data set consisting of 38,100 SNPs genotyped on 203 Borgou and 591 individuals representative of all the different cattle ancestries. At the global genomic level, we show that Borgou is a stabilized admixed breed whose origin (c. 130 years ago) traces back to the great African rinderpest pandemic, several centuries after the last admixture events, the West African zebus originate from (c. 500 years ago). To identify footprints of adaptive admixture, we combined the identification of signatures of selection and the functional annotation of the underlying genes using systems biology tools. The detection of the SILV coat coloration gene likely under artificial selection may be viewed as a validation of our approach. Overall, our results suggest that the long-term presence of pathogens and the intermediate environmental conditions are the main acting selective pressures. Our analytical framework can be extended to other model or nonmodel species to understand the process that shapes the patterns of genetic variability in hybrid zones.

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.

Variation in genes involved in epigenetic processes offers insights into tropically adapted cattle diversity

We evaluated the relevance of the BovineHD Illumina SNP chip with respect to genes involved in epigenetic processes. Genotypes for 729,068 SNP on two tropical cattle breeds of Australia were used: Brahman (n = 2112) and Tropical Composite (n = 2550). We used data mining approaches to compile a list of bovine protein-coding genes involved in epigenetic processes. These genes represent 9 functional categories that contain between one (histone demethylases) and 99 (chromatin remodeling factors) genes. A total of 3091 SNP mapped to positions within 3000 bp of the 193 coding regions of those genes, including 113 SNP in transcribed regions, 2738 in intronic regions and 240 in up- or down-stream regions. For all these SNP categories, we observed differences in the allelic frequencies between Brahman and Tropical Composite cattle. These differences were larger than those observed for the entire set of 729,068 SNP (P = 1.79 x 10⁻⁵). A multidimensional scaling analysis using only the 113 SNP in transcribed regions allowed for the separation of the two populations and this separation was comparable to the one obtained with a random set of 113 SNP (Principal Component 1 r² > 0.84). To further characterize the differences between the breeds we defined a gene-differentiation metric based on the average genotypic frequencies of SNP connected to each gene and compared both cattle populations. The 10% most differentiated genes were distributed across 10 chromosomes, with significant (P < 0.05) enrichment on BTA 3 and 10. The 10% most conserved genes were located in 12 chromosomes. We conclude that there is variation between cattle populations in genes connected to epigenetic processes, and this variation can be used to differentiate cattle breeds. More research is needed to fully characterize the use of these SNP and its potential as means to further our understanding of biological variation and epigenetic processes.

From SNP co-association to RNA co-expression: novel insights into gene networks for intramuscular fatty acid composition in porcine

Background

Fatty acids (FA) play a critical role in energy homeostasis and metabolic diseases; in the context of livestock species, their profile also impacts on meat quality for healthy human consumption. Molecular pathways controlling lipid metabolism are highly interconnected and are not fully understood. Elucidating these molecular processes will aid technological development towards improvement of pork meat quality and increased knowledge of FA metabolism, underpinning metabolic diseases in humans.

Results

The results from genome-wide association studies (GWAS) across 15 phenotypes were subjected to an Association Weight Matrix (AWM) approach to predict a network of 1,096 genes related to intramuscular FA composition in pigs. To identify the key regulators of FA metabolism, we focused on the minimal set of transcription factors (TF) that the explored the majority of the network topology. Pathway and network analyses pointed towards a trio of TF as key regulators of FA metabolism: NCOA2, FHL2 and EP300. Promoter sequence analyses confirmed that these TF have binding sites for some well-know regulators of lipid and carbohydrate metabolism. For the first time in a non-model species, some of the co-associations observed at the genetic level were validated through co-expression at the transcriptomic level based on real-time PCR of 40 genes in adipose tissue, and a further 55 genes in liver. In particular, liver expression of NCOA2 and EP300 differed between pig breeds (Iberian and Landrace) extreme in terms of fat deposition. Highly clustered co-expression networks in both liver and adipose tissues were observed. EP300 and NCOA2 showed centrality parameters above average in the both networks. Over all genes, co-expression analyses confirmed 28.9% of the AWM predicted gene-gene interactions in liver and 33.0% in adipose tissue. The magnitude of this validation varied across genes, with up to 60.8% of the connections of NCOA2 in adipose tissue being validated via co-expression.

Conclusions

Our results recapitulate the known transcriptional regulation of FA metabolism, predict gene interactions that can be experimentally validated, and suggest that genetic variants mapped to EP300, FHL2, and NCOA2 modulate lipid metabolism and control energy homeostasis in pigs.

Influence networks based on coexpression improve drug target discovery for the development of novel cancer therapeutics

Background

The demand for novel molecularly targeted drugs will continue to rise as we move forward toward the goal of personalizing cancer treatment to the molecular signature of individual tumors. However, the identification of targets and combinations of targets that can be safely and effectively modulated is one of the greatest challenges facing the drug discovery process. A promising approach is to use biological networks to prioritize targets based on their relative positions to one another, a property that affects their ability to maintain network integrity and propagate information-flow. Here, we introduce influence networks and demonstrate how they can be used to generate influence scores as a network-based metric to rank genes as potential drug targets.

Results

We use this approach to prioritize genes as drug target candidates in a set of ER ⁺ breast tumor samples collected during the course of neoadjuvant treatment with the aromatase inhibitor letrozole. We show that influential genes, those with high influence scores, tend to be essential and include a higher proportion of essential genes than those prioritized based on their position (i.e. hubs or bottlenecks) within the same network. Additionally, we show that influential genes represent novel biologically relevant drug targets for the treatment of ER ⁺ breast cancers. Moreover, we demonstrate that gene influence differs between untreated tumors and residual tumors that have adapted to drug treatment. In this way, influence scores capture the context-dependent functions of genes and present the opportunity to design combination treatment strategies that take advantage of the tumor adaptation process.

Conclusions

Influence networks efficiently find essential genes as promising drug targets and combinations of targets to inform the development of molecularly targeted drugs and their use.

A systems biology approach using metabolomic data reveals genes and pathways interacting to modulate divergent growth in cattle

BACKGROUND

Systems biology enables the identification of gene networks that modulate complex traits. Comprehensive metabolomic analyses provide innovative phenotypes that are intermediate between the initiator of genetic variability, the genome, and raw phenotypes that are influenced by a large number of environmental effects. The present study combines two concepts, systems biology and metabolic analyses, in an approach without prior functional hypothesis in order to dissect genes and molecular pathways that modulate differential growth at the onset of puberty in male cattle. Furthermore, this integrative strategy was applied to specifically explore distinctive gene interactions of non-SMC condensin I complex, subunit G (NCAPG) and myostatin (GDF8), known modulators of pre- and postnatal growth that are only partially understood for their molecular pathways affecting differential body weight.

RESULTS

Our study successfully established gene networks and interacting partners affecting growth at the onset of puberty in cattle. We demonstrated the biological relevance of the created networks by comparison to randomly created networks. Our data showed that GnRH (Gonadotropin-releasing hormone) signaling is associated with divergent growth at the onset of puberty and revealed two highly connected hubs, BTC and DGKH, within the network. Both genes are known to directly interact with the GnRH signaling pathway. Furthermore, a gene interaction network for NCAPG containing 14 densely connected genes revealed novel information concerning the functional role of NCAPG in divergent growth.

CONCLUSIONS

Merging both concepts, systems biology and metabolomic analyses, successfully yielded new insights into gene networks and interacting partners affecting growth at the onset of puberty in cattle. Genetic modulation in GnRH signaling was identified as key modifier of differential cattle growth at the onset of puberty. In addition, the benefit of our innovative concept without prior functional hypothesis was demonstrated by data suggesting that NCAPG might contribute to vascular smooth muscle contraction by indirect effects on the NO pathway via modulation of arginine metabolism. Our study shows for the first time in cattle that integration of genetic, physiological and metabolomics data in a systems biology approach will enable (or contribute to) an improved understanding of metabolic and gene networks and genotype-phenotype relationships.

Association between JY-1 gene polymorphisms and reproductive traits in beef cattle

Reproductive traits have a high economic value and it is interesting to include them in the selection objectives of an animal breeding program. These traits generally show low heritability and molecular markers may therefore be used in genetic evaluations to improve the accuracy of predictions. The JY-1 gene is expressed in the oocyte and it is associated with folliculogenesis and early embryo development. It has been suggested to affect reproductive traits. In this study, exons 1 and 2 of the JY-1 gene were studied in 385 Nellore females by PCR-sequencing. Seventeen polymorphisms were identified. After analysis of linkage disequilibrium, association tests were performed between eight SNPs and the occurrence of early pregnancy, age at first calving, days to calving, and reconception of primiparous heifers. Seven SNPs were significant for three traits. The most significant was chr29:12,999 T/A (p=0.003) which was associated with the occurrence of early pregnancy. This SNP might be involved in protein translation inhibition since it affects the initial methionine codon. The JY-1, an oocyte specific gene, influences reproductive traits; further studies investigating other regions of the gene or other genes expressed in tissues of the female reproductive system would be interesting to be performed.

Genome-wide association study identifies major loci for carcass weight on BTA14 in Hanwoo (Korean cattle)

This genome-wide association study (GWAS) was conducted to identify major loci that are significantly associated with carcass weight, and their effects, in order to provide increased understanding of the genetic architecture of carcass weight in Hanwoo. This genome-wide association study identified one major chromosome region ranging from 23 Mb to 25 Mb on chromosome 14 as being associated with carcass weight in Hanwoo. Significant Bonferroni-corrected genome-wide associations (P<1.52×10⁻⁶) were detected for 6 Single Nucleotide Polymorphic (SNP) loci for carcass weight on chromosome 14. The most significant SNP was BTB-01280026 (P = 4.02×10⁻¹¹), located in the 25 Mb region on Bos taurus autosome 14 (BTA14). The other 5 significant SNPs were Hapmap27934-BTC-065223 (P = 4.04×10⁻¹¹) in 25.2 Mb, BTB-01143580 (P = 6.35×10⁻¹¹) in 24.3 Mb, Hapmap30932-BTC-011225 (P = 5.92×10⁻¹⁰) in 24.8 Mb, Hapmap27112-BTC-063342 (P = 5.18×10⁻⁹) in 25.4 Mb, and Hapmap24414-BTC-073009 (P = 7.38×10⁻⁸) in 25.4 Mb, all on BTA 14. One SNP (BTB-01143580; P = 6.35×10⁻¹¹) lies independently from the other 5 SNPs. The 5 SNPs that lie together showed a large Linkage disequilibrium (LD) block (block size of 553 kb) with LD coefficients ranging from 0.53 to 0.89 within the block. The most significant SNPs accounted for 6.73% to 10.55% of additive genetic variance, which is quite a large proportion of the total additive genetic variance. The most significant SNP (BTB-01280026; P = 4.02×10⁻¹¹) had 16.96 kg of allele substitution effect, and the second most significant SNP (Hapmap27934-BTC-065223; P = 4.04×10⁻¹¹) had 18.06 kg of effect on carcass weight, which correspond to 44% and 47%, respectively, of the phenotypic standard deviation for carcass weight in Hanwoo cattle. Our results demonstrated that carcass weight was affected by a major Quantitative Trait Locus (QTL) with a large effect and by many SNPs with small effects that are normally distributed.

SIRT1 gene polymorphisms are associated with growth traits in Nanyang cattle

Growth is under complex genetic control and uncovering the molecular mechanisms how the genes and polymorphisms affect economic growth traits, are important for successful marker-assisted selection and more efficient management strategies in commercial cattle populations. SIRT1 is a NAD(+)-dependent deacetylase that belongs to the class III histone deacetylases. It plays an important role in numerous fundamental cellular processes including gene silencing, DNA repair, and metabolic regulation. In addition, SIRT1 acts as an inhibitor of adipogenesis and has been associated with body weight regulation. The objective of the present study was to identify single nucleotide polymorphisms (SNPs) of bovine SIRT1 using 1255 animals representing the five main Chinese breeds and to determine if these SNPs are associated with economically important traits in Nanyang cattle. The approach consisted of resequencing SIRT1 using a panel of DNA from unrelated animals of five different breeds and the process revealed five novel SNPs. SNPs g.17324T>C and g.17491G>A exhibited a high degree of linkage disequilibrium in all tested breeds. Seven major haplotypes accounting for 91.2% of the alleles were observed and the haplotype 'GCCGA' was the most common haplotype in NY, QC, LX and JX breeds. An association analysis was performed between the five SNPs and six performance traits. SNP g.-274C>G was demonstrated to have a strong effect on 24-months-old body weight and g.17379A>G polymorphism was related to 6 and 12-months-old body weight in NY population, although these effects did not remained significant after the Bonferroni correction. Our results provide evidence that polymorphisms in SIRT1 are associated with growth efficiency traits, and may be used for marker-assisted selection and management in feedlot cattle.

Key genes for modulating information flow play a temporal role as breast tumor coexpression networks are dynamically rewired by letrozole

Background

Genes do not act in isolation but instead as part of complex regulatory networks. To understand how breast tumors adapt to the presence of the drug letrozole, at the molecular level, it is necessary to consider how the expression levels of genes in these networks change relative to one another.

Methods

Using transcriptomic data generated from sequential tumor biopsy samples, taken at diagnosis, following 10-14 days and following 90 days of letrozole treatment, and a pairwise partial correlation statistic, we build temporal gene coexpression networks. We characterize the structure of each network and identify genes that hold prominent positions for maintaining network integrity and controlling information-flow.

Results

Letrozole treatment leads to extensive rewiring of the breast tumor coexpression network. Approximately 20% of gene-gene relationships are conserved over time in the presence of letrozole while 80% of relationships are condition dependent. The positions of influence within the networks are transiently held with few genes stably maintaining high centrality scores across the three time points.

Conclusions

Genes integral for maintaining network integrity and controlling information flow are dynamically changing as the breast tumor coexpression network adapts to perturbation by the drug letrozole.

Association weight matrix: a network-based approach towards functional genome-wide association studies

In this chapter we describe the Association Weight Matrix (AWM), a novel procedure to exploit the results from genome-wide association studies (GWAS) and, in combination with network inference algorithms, generate gene networks with regulatory and functional significance. In simple terms, the AWM is a matrix with rows represented by genes and columns represented by phenotypes. Individual {i, j}th elements in the AWM correspond to the association of the SNP in the ith gene to the jth phenotype. While our main objective is to provide a recipe-like tutorial on how to build and use AWM, we also take the opportunity to briefly reason the logic behind each step in the process. To conclude, we discuss the impact on AWM of issues like the number of phenotypes under scrutiny, the density of the SNP chip and the choice of contrast upon which to infer the cause-effect regulatory interactions.

Heritability and Bayesian genome-wide association study of first service conception and pregnancy in Brangus heifers

Brangus [3/8 Brahman (Bos indicus) × 5/8 Angus (Bos taurus); n ≈ 800] heifers from 67 sires were used to estimate heritability and conduct a genome-wide association study (GWAS) for 2 binary fertility traits: first service conception (FSC) and heifer pregnancy (HPG). Genotypes were from 53,692 loci on the BovineSNP50 (Infinium Bead Chips, Illumina, San Diego, CA). Yearling heifers were estrous synchronized, bred by AI, and then exposed to natural service breeding. Reproductive ultrasound and DNA-based parentage testing were used to determine if the heifer conceived by AI or natural service, and code for FSC and HPG traits. Success rates for FSC and HPG were 53.3% and 78.0% ± 0.01%, and corresponding heritability estimates were 0.18 ± 0.07 and 0.10 ± 0.06, respectively. The models used in obtaining these heritability estimates and GWAS included fixed effects of year (i.e., 2005 to 2007), birth location, calving season, age of dam, and contemporary group. In GWAS, simultaneous associations of 1 Mb SNP windows with phenotype were undertaken with Bayes C analyses using GenSel software. The 1 Mb windows contained 21.3 ± 1.1 SNP. Analyses fitted a mixture model that treated SNP effects as random, with an assumed fraction pi = 0.9995 having no effect on phenotype. The windows that accounted for 1.0% of genetic variance were considered as QTL associated with FSC or HPG. Eighteen QTL existed on 15 chromosomes for the 2 traits. On average, each QTL accounted for 2.43% ± 0.2% of the genetic variance. Chromosome 8 harbored 2 QTL for FSC and 1 for HPG; however, these regions did not overlap. Chromosomes 3, 15, 16, 19, 24, 26, 27, 29, and X included QTL only for FSC, whereas chromosomes 2, 4, 10, 13, and 20 contained QTL only for HPG. The multitude of QTL detected for FSC and HPG in this GWAS involving Brangus heifers exemplifies the complex regulation of variation in heifer fertility traits of low heritability.

Breeding and Genetics Symposium: building single nucleotide polymorphism-derived gene regulatory networks: Towards functional genomewide association studies

The advent of economically viable high-throughput genetic and genomic techniques has equipped animal geneticists with an unprecedented ability to generate massive amounts of molecular data. As a result, large lists of genes differentially expressed in many experimental conditions of interests have been reported and, likewise, the association of an ever growing number of DNA variants with phenotypes of importance is now a routine endeavor. Although these studies have greatly improved our understanding of the genetic basis of complex phenotypes, they have also revealed the difficulty in explaining more than a fraction of the genetic variance. Inspired by this data-rich and knowledge-poor dichotomy, systems biology aims at the formal integration of seemingly disparate datasets allowing for a holistic view where key properties of the systems emerge as an intuitive feature and enable the generation of testable hypotheses. Herein, we present 2 examples of integrating molecular data anchored in the power of gene network inference. The first example is concerned with the onset of puberty in Bos indicus-influenced cows bred in Australia. Using the results from genomewide association studies across a range of phenotypes, we developed what we termed an association weight matrix to generate a gene network underlying phenotypes of puberty in cattle. The network was mined for the minimal set of transcription factor genes whose predicted target spanned the majority of the topology of the entire network. The second example deals with piebald, a pigmentation phenotype in Merino sheep. Two networks were developed: a regulatory network and an epistatic network. The former is inferred based on promoter sequence analysis of differentially expressed genes. The epistatic network is built from 2-locus models among all pairwise associated polymorphisms. At the intersection between these 2 networks, we revealed a set of genes and gene-gene interactions of validated and de novo predicted relevance to the piebald phenotype. We argue that these new approaches are holistic and therefore more appropriate than traditional approaches for investigating genetic mechanisms underlying complex phenotypes of importance in livestock species.

First polymorphisms in JY-1 gene in cattle (Bos taurus indicus) and their association with sexual precocity and growth traits

Protein JY-1 is a bovine oocyte-specific protein that regulates granulosa cell function and is involved in early embryonic development, influencing the chance of pregnancy. This study investigated molecular markers for the JY-1 gene. Seven SNPs were identified in exon 3 of the gene. The positions of the SNPs in the exon and the respective substitutions are: 163 (T/C), 281 (T/C), 321 (T/C), 532 (T/C), 652 (A/G), 679 (T/C), and 722 (G/C) (GenBank: JN592587 and JF262042.2). SNP 163 is located in a coding region and causes a proline-to-leucine substitution. The other SNPs are located in the 3'UTR region. SNPs 163, 281, 321, and 679 were genotyped in 297 Nellore heifers and the haplotypes were constructed. The haplotypes of JY-1 were not correlated with the traits studied at 5 %.

Gene network analyses of first service conception in Brangus heifers: use of genome and trait associations, hypothalamic-transcriptome information, and transcription factors

Measures of heifer fertility are economically 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 heifers (3/8 Brahman × 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 conception (FSC). These fertility traits were collected from controlled breeding seasons initiated with estrous synchronization and AI 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 associated 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 hypothalamus of a prepubertal and a postpubertal Brangus heifer. The remaining hypothalamic-influenced network contained 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.

Identification of Candidate Genes Associated with Beef Marbling Using QTL and Pathway Analysis in Hanwoo (Korean Cattle)

Marbling from intramuscular fat is an important trait of meat quality and has an economic benefit for the beef industry. Quantitative trait loci (QTL) fine mapping was performed to identify the marbling trait in 266 Hanwoo steers using a 10K single nucleotide polymorphism panel with the combined linkage and linkage disequilibrium method. As a result, we found nine putative QTL regions for marbling: three on BTA6, two on BTA17, two on BTA22, and two on BTA29. We detected candidate genes for marbling within 1 cM of either side of the putative QTL regions. Additionally, to understand the functions of these candidate genes at the molecular level, we conducted a functional categorization using gene ontology and pathway analyses for those genes involved in lipid metabolism or fat deposition. In these putative QTL regions, we found 95 candidate genes for marbling. Using these candidate genes, we found five genes that had a direct interaction with the candidate genes. We also found SCARB1 as a putative candidate gene for marbling that involves fat deposition related to cholesterol transport.

Association between GNRHR, LHR and IGF1 polymorphisms and timing of puberty in male Angus cattle

Background

In bovines, there are significant differences within and among beef breeds in the time when bulls reach puberty. Although the timing of puberty is likely to be a multigenic trait, previous studies indicate that there may also be single genes that exert major effects on the timing of puberty within the general population. Despite its economic importance, there are not many SNPs or genetic markers associated with the age of puberty in male cattle. In the present work, we selected three candidate genes, GNRHR, LHR and IGF1, and associated their polymorphisms with the age of puberty in Angus male cattle.

Results

After weaning, 276 Angus males were measured every month for weight (W), scrotal circumference (SC), sperm concentration (C) and percentage of motility (M). A total of 4 SNPs, two within GNRHR, one in LHR and one in IGF1 were genotyped using the pyrosequencing technique. IGF1-SnaBI SNP was significant associated (P < 0.01) with age at SC 28 cm, but it were not associated with age at M 10% and C 50 million. Genotype CC exhibited an average age at SC 28 cm of 7 and 11 days higher than CT (p = 0.037) and TT (p = 0.012), respectively. This SNP explained 1.5% of the genetic variance of age of puberty at SC28. LHR-I499L, GNRHR-SNP5 and GNRHR-SNP6 were not associated with any of the measurements. However, GNRHR haplotypes showed a suggestive association with age at SC 28 cm.

Conclusions

The findings presented here could support the hypothesis that IGF1 is a regulator of the arrival to puberty in male calves and is involved in the events that precede and initiate puberty in bull calves. Given that most studies in cattle, as well as in other mammals, were done in female, the present results are the first evidence of markers associated with age at puberty in male cattle.

Genome-wide association studies of female reproduction in tropically adapted beef cattle

The genetics of reproduction is poorly understood because the heritabilities of traits currently recorded are low. To elucidate the genetics underlying reproduction in beef cattle, we performed a genome-wide association study using the bovine SNP50 chip in 2 tropically adapted beef cattle breeds, Brahman and Tropical Composite. Here we present the results for 3 female reproduction traits: 1) age at puberty, defined as age in days at first observed corpus luteum (CL) after frequent ovarian ultrasound scans (AGECL); 2) the postpartum anestrous interval, measured as the number of days from calving to first ovulation postpartum (first rebreeding interval, PPAI); and 3) the occurrence of the first postpartum ovulation before weaning in the first rebreeding period (PW), defined from PPAI. In addition, correlated traits such as BW, height, serum IGF1 concentration, condition score, and fatness were also examined. In the Brahman and Tropical Composite cattle, 169 [false positive rate (FPR) = 0.262] and 84 (FPR = 0.581) SNP, respectively, were significant (P < 0.001) for AGECL. In Brahman, 41% of these significant markers mapped to a single chromosomal region on BTA14. In Tropical Composites, 16% of these significant markers were located on BTA5. For PPAI, 66 (FPR = 0.67) and 113 (FPR = 0.432) SNP were significant (P < 0.001) in Brahman and Tropical Composite, respectively, whereas for PW, 68 (FPR = 0.64) and 113 (FPR = 0.432) SNP were significant (P < 0.01). In Tropical Composites, the largest concentration of PPAI markers were located on BTA5 [19% (PPAI) and 23% (PW)], and BTA16 [17% (PPAI) and 18% (PW)]. In Brahman cattle, the largest concentration of markers for postpartum anestrus was located on BTA3 (14% for PPAI and PW) and BTA14 (17% PPAI). Very few of the significant markers for female reproduction traits for the Brahman and Tropical Composite breeds were located in the same chromosomal regions. However, fatness and BW traits as well as serum IGF1 concentration were found to be associated with similar genome regions within and between breeds. Clusters of SNP associated with multiple traits were located on BTA14 in Brahman and BTA5 in Tropical Composites.

Physiology and Endocrinology Symposium: How single nucleotide polymorphism chips will advance our knowledge of factors controlling puberty and aid in selecting replacement beef females

The promise of genomic selection is accurate prediction of the genetic potential of animals from their genotypes. Simple DNA tests might replace low-accuracy predictions for expensive or lowly heritable measures of puberty and fertility based on performance and pedigree. Knowing with some certainty which DNA variants (e.g., SNP) affect puberty and fertility is the best way to fulfill the promise. Several SNP from the BovineSNP50 assay have tentatively been associated with reproductive traits including age at puberty, antral follicle count, and pregnancy observed on different sets of heifers. However, sample sizes are too small and SNP density is too sparse to definitively determine genomic regions harboring causal variants affecting reproductive success. Additionally, associations between individual SNP and similar phenotypes are inconsistent across data sets, and genomic predictions do not appear to be globally applicable to cattle of different breeds. Discrepancies may be a result of different QTL segregating in the sampled populations, differences in linkage disequilibrium (LD) patterns such that the same SNP are not correlated with the same QTL, and spurious correlations with phenotype. Several approaches can be used independently or in combination to improve detection of genomic factors affecting heifer puberty and fertility. Larger samples and denser SNP will increase power to detect real associations with SNP having more consistent LD with underlying QTL. Meta-analysis combining results from different studies can also be used to effectively increase sample size. High-density genotyping with heifers pooled by pregnancy status or early and late puberty can be a cost-effective means to sample large numbers. Networks of genes, implicated by associations with multiple traits correlated with puberty and fertility, could provide insight into the complex nature of these traits, especially if corroborated by functional annotation, established gene interaction pathways, and transcript expression. Example analyses are provided to demonstrate how integrating information about gene function and regulation with statistical associations from whole-genome SNP genotyping assays might enhance knowledge of genomic mechanisms affecting puberty and fertility, enabling reliable DNA tests to guide heifer selection decisions.