Characterization of genes for beef marbling based on applying gene coexpression network

Identification of several lncRNA-mRNA pairs associated with marbling trait between Nanyang and Angus cattle

BACKGROUND

The marbling trait of cattle muscles, being a key indicator, played an important role in evaluating beef quality. Two breeds of cattle, namely a high-marbling (Angus) and a low-marbling (Nanyang) one, with their cattle muscles selected as our samples for transcriptome sequencing, were aimed to identify differentially expressed long non-coding RNAs (lncRNAs) and their targets associated with the marbling trait.

RESULTS

Transcriptome sequencing identified 487 and 283 differentially expressed mRNAs and lncRNAs respectively between the high-marbling (Angus) and low-marbling (Nanyang) cattle muscles. Twenty-seven pairs of differentially expressed lncRNAs-mRNAs, including eighteen lncRNAs and eleven target genes, were found to be involved in fat deposition and lipid metabolism. We established a positive correlation between fourteen up-regulated (NONBTAT000849.2, MSTRG.9591.1, NONBTAT031089.1, MSTRG.3720.1, NONBTAT029718.1, NONBTAT004228.2, NONBTAT007494.2, NONBTAT011094.2, NONBTAT015080.2, NONBTAT030943.1, NONBTAT021005.2, NONBTAT021004.2, NONBTAT025985.2, and NONBTAT023845.2) and four down-regulated (NONBTAT000850.2, MSTRG.22188.3, MSTRG.22188.4, and MSTRG.22188.5) lncRNAs and eleven genes related to adiponectin family protein (ADIPOQ), cytochrome P450 family (CYP4V2), 3-hydroxyacyl-CoA dehydratase family (HACD4), kinesin family (KIF5C), lipin family (LPIN2), perilipin family (PLIN1), prostaglandin family (PTGIS), solute carrier family (SLC16A7, SLC2213, and SLCO4C1), and containing a transmembrane domain protein family (VSTM1).

CONCLUSIONS

These candidate genes and lncRNAs can be regarded as being responsible for regulating the marbling trait of cattle. lncRNAs along with the variations in intramuscular fat marbling established a foundation for elucidating the genetic basis of high marbling in cattle.

Genomic predictions and GWAS for heat tolerance in pigs based on reaction norm models with performance records and data from public weather stations considering alternative temperature thresholds

Genetic improvement of livestock productivity has resulted in greater production of metabolic heat and potentially greater susceptibility to heat stress. Various studies have demonstrated that there is genetic variability for heat tolerance and genetic selection for more heat tolerant individuals is possible. The rate of genetic progress tends to be greater when genomic information is incorporated into the analyses as more accurate breeding values can be obtained for young individuals. Therefore, this study aimed (1) to evaluate the predictive ability of genomic breeding values for heat tolerance based on routinely recorded traits, and (2) to investigate the genetic background of heat tolerance based on single-step genome-wide association studies for economically important traits related to body composition, growth and reproduction in Large White pigs. Pedigree information was available for 265,943 animals and genotypes for 8686 animals. The studied traits included ultrasound backfat thickness (BFT), ultrasound muscle depth (MDP), piglet weaning weight (WW), off-test weight (OTW), interval between farrowing (IBF), total number of piglets born (TNB), number of piglets born alive (NBA), number of piglets born dead (NBD), number of piglets weaned (WN) and weaning-to-estrus interval (IWE). The number of phenotypic records ranged from 6059 (WN) to 172,984 (TNB). Single-step genomic reaction norm predictions were used to calculate the genomic estimated breeding values for each individual. Predictions of breeding values for the validation population individuals were compared between datasets containing phenotypic records measured in the whole range of temperatures (WR) and datasets containing only phenotypic records measured when the weather station temperature was above 10°C (10C) or 15°C (15C), to evaluate the usefulness of these datasets that may better reflect the within-barn temperature. The use of homogeneous or heterogeneous residual variance was found to be trait-dependent, where homogeneous variance presented the best fit for MDP, BFT, OTW, TNB, NBA, WN and IBF, while the other traits (WW and IWE) had better fit with heterogeneous variance. The average prediction accuracy, dispersion and bias values considering all traits for WR were 0.36 ± 0.05, -0.07 ± 0.13 and 0.76 ± 0.10, respectively; for 10C were 0.39 ± 0.02, -0.05 ± 0.07 and 0.81 ± 0.05, respectively; and for 15C were 0.32 ± 0.05, -0.05 ± 0.11 and 0.84 ± 0.10, respectively. Based on the studied traits, using phenotypic records collected when the outside temperature (from public weather stations) was above 10°C provided better predictions for most of the traits. Forty-three and 62 candidate genomic regions were associated with the intercept (overall performance level) and slope term (specific biological mechanisms related to environmental sensitivity), respectively. Our results contribute to improve genomic predictions using existing datasets and better understand the genetic background of heat tolerance in pigs. Furthermore, the genomic regions and candidate genes identified will contribute to future genomic studies and breeding applications.

Development of nutrigenomic based precision management model for Hanwoo steers

Focusing high marble deposition, Hanwoo feedlot system uses high-energy diet over the prolonged fattening period. However, due to the individual genetic variation, around 40% of them are graded into inferior quality grades (QG), despite they utilized the same resources. Therefore, focusing on development of a nutrigenomic based precision management model, this study was to evaluated the response to the divergent selection on genetic merit for marbling score (MS), under different dietary total digestible nutrient (TDN) levels. Total of 111 calves were genotyped and initially grouped according to estimated breeding value (high and low) for marbling score (MS-EBV). Subsequently, managed under two levels of feed TDN%, over the calf period, early, middle, and final fattening periods following 2 × 2 factorial arrangement. Carcasses were evaluated for MS, Back fat thickness (BFT) and Korean beef quality grading standard. As the direct response to the selection was significant, the results confirmed the importance of initial genetic grouping of Hanwoo steers for MS-EBV. However, dietary TDN level did not show an effect (p > 0.05) on the MS. Furthermore, no genetic-by-nutrition interaction for MS (p > 0.05) was also observed. The present results showed no correlation response on BFT (p > 0.05), which indicates that the selection based on MS-EBV can be used to enhance the MS without undesirable effect on BFT. Ultimate turnover of the Hanwoo feedlot operation is primarily determined by the QGs. The present model shows that the initial grouping for MS-EBV increased the proportion of carcasses graded for higher QGs (QG1⁺⁺ and QG1⁺) by approximately 20%. Moreover, there appear to be a potential to increase the proportion of QG 1⁺⁺ animals among the high-genetic group by further increasing the dietary energy content. Overall, this precision management strategy suggests the importance of adopting an MS based initial genetic grouping system for Hanwoo steers with a subsequent divergent management based on dietary energy level.

Genome-wide association study reveals genetic loci and candidate genes for meat quality traits in a four-way crossbred pig population

Meat quality traits (MQTs) have gained more attention from breeders due to their increasing economic value in the commercial pig industry. In this genome-wide association study (GWAS), 223 four-way intercross pigs were genotyped using the specific-locus amplified fragment sequencing (SLAF-seq) and phenotyped for PH at 45 min post mortem (PH45), meat color score (MC), marbling score (MA), water loss rate (WL), drip loss (DL) in the longissimus muscle, and cooking loss (CL) in the psoas major muscle. A total of 227, 921 filtered single nucleotide polymorphisms (SNPs) evenly distributed across the entire genome were detected to perform GWAS. A total of 64 SNPs were identified for six meat quality traits using the mixed linear model (MLM), of which 24 SNPs were located in previously reported QTL regions. The phenotypic variation explained (PVE) by the significant SNPs was from 2.43% to 16.32%. The genomic heritability estimates based on SNP for six meat-quality traits were low to moderate (0.07-0.47) being the lowest for CL and the highest for DL. A total of 30 genes located within 10 kb upstream or downstream of these significant SNPs were found. Furthermore, several candidate genes for MQTs were detected, including pH45 (GRM8), MC (ANKRD6), MA (MACROD2 and ABCG1), WL (TMEM50A), CL (PIP4K2A) and DL (CDYL2, CHL1, ABCA4, ZAG and SLC1A2). This study provided substantial new evidence for several candidate genes to participate in different pork quality traits. The identification of these SNPs and candidate genes provided a basis for molecular marker-assisted breeding and improvement of pork quality traits.

The new oncogene transmembrane protein 60 is a potential therapeutic target in glioma

Glioma is a malignant tumor with a high fatality rate, originating in the central nervous system. Even after standard treatment, the prognosis remains unsatisfactory, probably due to the lack of effective therapeutic targets. The family of transmembrane proteins (TMEM) is a large family of genes that encode proteins closely related to the malicious behavior of tumors. Thus, it is necessary to explore the molecular and clinical characteristics of newly identified oncogenes, such as transmembrane protein 60 (TMEM60), to develop effective treating options for glioma. We used bioinformatic methods and basic experiments to verify the expression of transmembrane protein 60 in gliomas and its relationship with 1p and 19q (1p19q) status, isocitrate dehydrogenase (IDH) status, patient prognosis, and immune cell infiltration using public databases and clinical samples. In addition, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to detect co-expressed genes. Thus, we inhibited the expression of transmembrane protein 60 to observe the proliferation and activity of glioma LN229 cells. We found transmembrane protein 60 was significantly upregulated in glioma compared with that in normal brain tissue at the mRNA. In the subgroups of World Health Organization high grade, isocitrate dehydrogenase wildtype, 1p and 19q non-codeletion, or isocitrate dehydrogenase wild combined with 1p and 19q non-codeletion, the expression of transmembrane protein 60 increased, and the prognosis of glioma patients worsened. In the transmembrane protein 60 high expression group, infiltration of immune cells and stromal cells in the tumor microenvironment increased, tumor purity decreased, and immune cells and pathways were activated. The immune cells mainly included regulatory T-cell, gamma delta T-cell, macrophages M0, neutrophils, and CD8⁺ T-cells. Overexpression of co-inhibitory receptors (CTLA4, PDL1 and CD96) may promote the increase of depletion of T-cell, thus losing the anti-tumor function in the transmembrane protein 60 high expression group. Finally, we found that transmembrane protein 60 silencing weakened the viability, proliferation, and colony formation of glioma LN229 cells. This is the 0 report on the abnormally high expression of transmembrane protein 60 in glioma and its related clinical features, such as tumor microenvironment, immune response, tumor heterogeneity, and patient prognosis. We also found that transmembrane protein 60 silencing weakened the proliferation and colony formation of glioma LN229 cells. Thus, the new oncogene transmembrane protein 60 might be an effective therapeutic target for the clinical treatment of glioma.

Genome-Wide Association Study of Meat Quality Traits in a Three-Way Crossbred Commercial Pig Population

Meat quality is an important trait for pig-breeding programs aiming to meet consumers' demands. Geneticists must improve meat quality based on their understanding of the underlying genetic mechanisms. Previous studies showed that most meat-quality indicators were low-to-moderate heritability traits; therefore, improving meat quality using conventional techniques remains a challenge. Here, we performed a genome-wide association study of meat-quality traits using the GeneSeek Porcine SNP50K BeadChip in 582 crossbred Duroc × (Landrace × Yorkshire) commercial pigs (249 males and 333 females). Meat conductivity, marbling score, moisture, meat color, pH, and intramuscular fat (IMF) content were investigated. The genome-wide association study was performed using both fixed and random model Circulating Probability Unification (FarmCPU) and a mixed linear model (MLM) with the rMVP software. The genomic heritability of the studied traits ranged from 0.13 ± 0.07 to 0.55 ± 0.08 for conductivity and meat color, respectively. Thirty-two single-nucleotide polymorphisms (SNPs) were identified for meat quality in the crossbred pigs using both FarmCPU and MLM. Among the detected SNPs, five, nine, seven, four, six, and five were significantly associated with conductivity, IMF, marbling score, meat color, moisture, and pH, respectively. Several candidate genes for meat quality were identified in the detected genomic regions. These findings will contribute to the ongoing improvement of meat quality, meeting consumer demands and improving the economic outlook for the swine industry.

Discovery of Genomic Characteristics and Selection Signatures in Southern Chinese Local Cattle

Chinese local cattle with a high level of genetic diversity mainly originate from two subspecies; the cattle in northern China are primarily Bos Taurus, and the cattle in southern China are primarily Bos indicus. Cattle from southern China are characterized by a specific phenotype and adapted to the local environment. This study explored the genetic diversity, degree of admixture, and selection signature in eight local cattle breeds in southern China. The lowest level of heterozygosity was found in Hainan and Nandan cattle from Hainan and Guangxi province, respectively, whereas the highest level of heterozygosity was detected in Zhaotong cattle from Yunnan province. A neighbor-joining phylogenetic tree analysis clearly separated Lufeng cattle from other breeds, whereas Leiqiong and Hainan cattle have some crossover. Based on linkage disequilibrium-filtered single nucleotide polymorphisms (SNPs), the admixture analysis revealed two clusters corresponding to the taurine and indicine cattle lineages, and the local cattle breeds from southern China showed a certain degree of admixture. When K = 4 and 9, we found a slight separation among Leiqiong, Lufeng, and Hainan cattle. Meanwhile, we performed a selection signature analysis in Hainan, Leiqiong, and Lufeng cattle distributed in the extreme south of China, using the integrated haplotype score (iHS), Rsb statistic, and BayeScan software. Using the iHS approach, we identified 251, 270, and 256 candidate regions in Lufeng, Leiqiong, and Hainan cattle, respectively. Moreover, we identified 184, 174, and 146 candidate regions in pairwise comparisons of Leiqiong vs. Lufeng, Leiqiong vs. Hainan, and Hainan vs. Lufeng cattle using the Rsb approach. In addition, we identified 76 loci with a total of 48 genes under selection, based on the F_ST approach. Several candidate genes under selection were found to be related to meat quality, immunity, and adaptation to the local environment in southern China. Our results provide significant information about the genetic differences among the cattle breeds from southern China and the possible cause of difference in breed-specific characteristics. Selection signature analysis identified a few candidate SNPs and genes related to certain important traits of these cattle. In general, our results provide valuable insights into the genetic basis of specific traits under selection in certain local cattle breeds.

Use of gene expression and whole-genome sequence information to improve the accuracy of genomic prediction for carcass traits in Hanwoo cattle

Background

In this study, we assessed the accuracy of genomic prediction for carcass weight (CWT), marbling score (MS), eye muscle area (EMA) and back fat thickness (BFT) in Hanwoo cattle when using genomic best linear unbiased prediction (GBLUP), weighted GBLUP (wGBLUP), and a BayesR model. For these models, we investigated the potential gain from using pre-selected single nucleotide polymorphisms (SNPs) from a genome-wide association study (GWAS) on imputed sequence data and from gene expression information. We used data on 13,717 animals with carcass phenotypes and imputed sequence genotypes that were split in an independent GWAS discovery set of varying size and a remaining set for validation of prediction. Expression data were used from a Hanwoo gene expression experiment based on 45 animals.

Results

Using a larger number of animals in the reference set increased the accuracy of genomic prediction whereas a larger independent GWAS discovery dataset improved identification of predictive SNPs. Using pre-selected SNPs from GWAS in GBLUP improved accuracy of prediction by 0.02 for EMA and up to 0.05 for BFT, CWT, and MS, compared to a 50 k standard SNP array that gave accuracies of 0.50, 0.47, 0.58, and 0.47, respectively. Accuracy of prediction of BFT and CWT increased when BayesR was applied with the 50 k SNP array (0.02 and 0.03, respectively) and was further improved by combining the 50 k array with the top-SNPs (0.06 and 0.04, respectively). By contrast, using BayesR resulted in limited improvement for EMA and MS. wGBLUP did not improve accuracy but increased prediction bias. Based on the RNA-seq experiment, we identified informative expression quantitative trait loci, which, when used in GBLUP, improved the accuracy of prediction slightly, i.e. between 0.01 and 0.02. SNPs that were located in genes, the expression of which was associated with differences in trait phenotype, did not contribute to a higher prediction accuracy.

Conclusions

Our results show that, in Hanwoo beef cattle, when SNPs are pre-selected from GWAS on imputed sequence data, the accuracy of prediction improves only slightly whereas the contribution of SNPs that are selected based on gene expression is not significant. The benefit of statistical models to prioritize selected SNPs for estimating genomic breeding values is trait-specific and depends on the genetic architecture of each trait.

Single-Locus and Multi-Locus Genome-Wide Association Studies for Intramuscular Fat in Duroc Pigs

Intramuscular fat (IMF) is an important quantitative trait of meat, which affects the associated sensory properties and nutritional value of pork. To gain a better understanding of the genetic determinants of IMF, we used a composite strategy, including single-locus and multi-locus association analyses to perform genome-wide association studies (GWAS) for IMF in 1,490 Duroc boars. We estimated the genomic heritability of IMF to be 0.23 ± 0.04. A total of 30 single nucleotide polymorphisms (SNPs) were found to be significantly associated with IMF. The single-locus mixed linear model (MLM) and multiple-locus methods multi-locus random-SNP-effect mixed linear model (mrMLM), fast multi-locus random-SNP-effect efficient mixed model association (FASTmrEMMA), and integrative sure independence screening expectation maximization Bayesian least absolute shrinkage and selection operator model (ISIS EM-BLASSO) analyses identified 5, 9, 8, and 21 significant SNPs, respectively. Interestingly, a novel quantitative trait locus (QTL) on SSC 7 was found to affect IMF. In addition, 10 candidate genes (BDKRB2, GTF2IRD1, UTRN, TMEM138, DPYD, CASQ2, ZNF518B, S1PR1, GPC6, and GLI1) were found to be associated with IMF based on their potential functional roles in IMF. GO analysis showed that most of the genes were involved in muscle and organ development. A significantly enriched KEGG pathway, the sphingolipid signaling pathway, was reported to be associated with fat deposition and obesity. Identification of novel variants and functional genes will advance our understanding of the genetic mechanisms of IMF and provide specific opportunities for marker-assisted or genomic selection in pigs. In general, such a composite single-locus and multi-locus strategy for GWAS may be useful for understanding the genetic architecture of economic traits in livestock.

Transcriptome Analysis Reveals the Effect of Long Intergenic Noncoding RNAs on Pig Muscle Growth and Fat Deposition

Muscle growth and fat deposition are the two important biological processes in the development of pigs which are closely related to the pig production performance. Long intergenic noncoding RNAs (lincRNAs), with lack of coding potential and the length of at least 200nt, have been extensively studied to play important roles in many biological processes. However, the importance and molecular regulation mechanism of lincRNAs in the process of muscle growth and fat deposition in pigs are still to be further studied comprehensively. In our study, we used the data, including liver, abdominal fat, and longissimus dorsi muscle of 240 days' age of two F2 full-sib female individuals from the white Duroc and Erhualian crossbreed, to identify 581 putative lincRNAs associated with pig muscle growth and fat deposition. The 581 putative lincRNAs shared many common features with other mammalian lincRNAs, such as fewer exons, lower expression levels, and shorter transcript lengths. Cross-tissue comparisons showed that many transcripts were tissue-specific and were involved in the important biological processes in their corresponding tissues. Gene ontology and pathway analysis revealed that many potential target genes (PTGs) of putative lincRNAs were involved in pig muscle growth and fat deposition-related processes, including muscle cell proliferation, lipid metabolism, and fatty acid degradation. In Quantitative Trait Locus (QTLs) analysis, some PTGs were screened from putative lincRNAs, MRPL12 is associated with muscle growth, GCGR and SLC25A10 were associated with fat deposition, and PPP3CA, DPYD, and FGGY were related not only to muscle growth but also to fat deposition. Therefore, it implied that these lincRNAs might participate in the biological processes related to muscle growth or fat deposition through homeostatic regulation of PTGs, but the detailed molecular regulatory mechanisms still needed to be further explored. This study lays the molecular foundation for the in-depth study of the role of lincRNAs in the pig muscle growth and fat deposition and further provides the new molecular markers for understanding the complex biological mechanisms of pig muscle growth and fat deposition.

Gene Coexpression Network Comparison via Persistent Homology

Persistent homology, a topological data analysis (TDA) method, is applied to microarray data sets. Although there are a few papers referring to TDA methods in microarray analysis, the usage of persistent homology in the comparison of several weighted gene coexpression networks (WGCN) was not employed before to the very best of our knowledge. We calculate the persistent homology of weighted networks constructed from 38 Arabidopsis microarray data sets to test the relevance and the success of this approach in distinguishing the stress factors. We quantify multiscale topological features of each network using persistent homology and apply a hierarchical clustering algorithm to the distance matrix whose entries are pairwise bottleneck distance between the networks. The immunoresponses to different stress factors are distinguishable by our method. The networks of similar immunoresponses are found to be close with respect to bottleneck distance indicating the similar topological features of WGCNs. This computationally efficient technique analyzing networks provides a quick test for advanced studies.

TRIENNIAL GROWTH AND DEVELOPMENT SYMPOSIUM: Intramuscular fat deposition in ruminants and pigs: A transcriptomics perspective

The genomics era has led to an explosion in the study of gene expression in production animals. Intramuscular fat (IMF) content (both high and low) and composition are major quality attributes of meat, and more than 90 transcriptomic studies of IMF deposition have been undertaken in the ruminants and pigs since 2001, with the majority since 2008. The studies have implicated many genes involved in the control of adipogenesis, lipogenesis, and deposition of IMF, but there is relatively little consistency between the different studies. However, the genes encoding the synthesis enzymes acetyl-CoA carboxylase α, fatty acid synthase, and stearoyl-CoA desaturase; the fatty acid binding protein 4; the potential signaling protein thyroid hormone responsive; and the regulators C/EBPα, PPARγ, and sterol regulatory element binding transcription factor 1 are supported by 5 or more of the 90 studies. By combining the results of all the studies, complete pathways for long-chain fatty acid (LCFA) and triacylglyceride (TAG) synthesis are identified, as are a number of genes encoding proteins probably associated with the storage of TAG and genes encoding a number of known and potential adipokines. In contrast, support for the association of lipolytic pathways with IMF percentage is less strong. Differences in experimental design-in particular, the age of the animals, the rate of IMF deposition at sampling, the past nutritional history of the animals used, and the complexities of using a tissue with mixed cell types-have contributed to the differences in results and interpretation. Biomarkers predictive of future IMF percentage, facilitating reaching optimal IMF content at slaughter, may have industry utility, but to be useful in animal biopsy and postslaughter samples, where multiple cell types are present, genes must be carefully chosen to ensure that they are informative about the expected processes. Despite these problems, candidate biomarkers for estimation of de novo intramuscular adipocyte LCFA synthesis, LCFA uptake rate by intramuscular adipocytes, and IMF deposition rate have been identified and examples of their utility have been published. However, further work is required to demonstrate how best to apply the assays for the benefit of the relevant livestock production industries.

Large-scale gene co-expression network as a source of functional annotation for cattle genes

Background

Genome sequencing and subsequent gene annotation of genomes has led to the elucidation of many genes, but in vertebrates the actual number of protein coding genes are very consistent across species (~20,000). Seven years after sequencing the cattle genome, there are still genes that have limited annotation and the function of many genes are still not understood, or partly understood at best. Based on the assumption that genes with similar patterns of expression across a vast array of tissues and experimental conditions are likely to encode proteins with related functions or participate within a given pathway, we constructed a genome-wide Cattle Gene Co-expression Network (CGCN) using 72 microarray datasets that contained a total of 1470 Affymetrix Genechip Bovine Genome Arrays that were retrieved from either NCBI GEO or EBI ArrayExpress.

Results

The total of 16,607 probe sets, which represented 11,397 genes, with unique Entrez ID were consolidated into 32 co-expression modules that contained between 29 and 2569 probe sets. All of the identified modules showed strong functional enrichment for gene ontology (GO) terms and Reactome pathways. For example, modules with important biological functions such as response to virus, response to bacteria, energy metabolism, cell signaling and cell cycle have been identified. Moreover, gene co-expression networks using “guilt-by-association” principle have been used to predict the potential function of 132 genes with no functional annotation. Four unknown Hub genes were identified in modules highly enriched for GO terms related to leukocyte activation (LOC509513), RNA processing (LOC100848208), nucleic acid metabolic process (LOC100850151) and organic-acid metabolic process (MGC137211). Such highly connected genes should be investigated more closely as they likely to have key regulatory roles.

Conclusions

We have demonstrated that the CGCN and its corresponding regulons provides rich information for experimental biologists to design experiments, interpret experimental results, and develop novel hypothesis on gene function in this poorly annotated genome. The network is publicly accessible at http://www.animalgenome.org/cgi-bin/host/reecylab/d.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3176-2) contains supplementary material, which is available to authorized users.