Genes associated with body weight gain and feed intake identified by meta-analysis of the mesenteric fat from crossbred beef steers

Combined Use of Univariate and Multivariate Approaches to Detect Selection Signatures Associated with Milk or Meat Production in Cattle

OBJECTIVES

The aim of this study was to investigate the genomic structure of the cattle breeds selected for meat and milk production and to identify selection signatures between them.

METHODS

A total of 391 animals genotyped at 41,258 SNPs and belonging to nine breeds were considered: Angus (N = 62), Charolais (46), Hereford (31), Limousin (44), and Piedmontese (24), clustered in the Meat group, and Brown Swiss (42), Holstein (63), Jersey (49), and Montbéliarde (30), clustered in the Milk group. The population stratification was analyzed by principal component analysis (PCA), whereas selection signatures were identified by univariate (Wright fixation index, FST) and multivariate (canonical discriminant analysis, CDA) approaches. Markers with FST values larger than three standard deviations from the chromosomal mean were considered interesting. Attention was focused on markers selected by both techniques.

RESULTS

A total of 10 SNPs located on seven different chromosomes (7, 10, 14, 16, 17, 18, and 24) were identified. Close to these SNPs (±250 kb), 165 QTL and 51 genes were found. The QTL were grouped in 45 different terms, of which three were significant (Bonferroni correction < 0.05): milk fat content, tenderness score, and length of productive life. Moreover, genes mainly associated with milk production, immunity and environmental adaptation, and reproduction were mapped close to the common SNPs.

CONCLUSIONS

The results of the present study suggest that the combined use of univariate and multivariate approaches can help to better identify selection signatures due to directional selection.

Genes involved in the cholecystokinin receptor signaling map were differentially expressed in the jejunum of steers with variation in residual feed intake

The jejunum is a critical site for nutrient digestion and absorption, and variation in its ability to take up nutrients within the jejunum is likely to affect feed efficiency. The purpose of this study was to determine differences in gene expression in the jejunum of beef steers divergent for residual feed intake (RFI) in one cohort of steers (Year 1), and to validate those genes in animals from a second study (Year 2). Steers from Year 1 (n = 16) were selected for high and low RFI. Jejunum mucosal tissue was obtained for RNA-seq. Thirty-two genes were differentially expressed (PFDR≤0.15), and five were over-represented in pathways including inflammatory mediator, cholecystokinin receptor (CCKR) signaling, and p38 MAPK pathways. Several differentially expressed genes (ALOX12, ALPI, FABP6, FABP7, FLT1, GSTA2, MEF2B, PDK4, SPP1, and TTF2) have been previously associated with RFI in other studies. Real-time qPCR was used to validate nine differentially expressed genes in the Year 1 steers used for RNA-seq, and in the Year 2 validation cohort. Six genes were validated as differentially expressed (P < 0.1) using RT-qPCR in the Year 1 population. In the Year 2 population, five genes displayed the same direction of expression as the Year 1 population and 3 were differentially expressed (P < 0.1). The CCKR pathway is involved in digestion, appetite control, and regulation of body weight making it a compelling candidate for feed efficiency in cattle, and the validation of these genes in a second population of cattle is suggestive of a role in feed efficiency.

Evaluation of genetic differentiation and search for candidate genes for reproductive traits in pigs

OBJECTIVE

The use of molecular genetic methods in pig breeding can significantly increase the efficiency of breeding and breeding work. We applied the Fst (fixsacion index) method, the main focus of the work was on the search for common options related to the number of born piglets and the weight of born piglets, since today the urgent task is to prevent a decrease in the weight of piglets at birth while maintaining high fertility of sows.

METHODS

One approach is to scan the genome, followed by an assessment of Fst and identification of selectively selected regions. We chose Large White sows (n = 237) with the same conditions of keeping and feeding. The data were collected from the sows across three farrowing. For genotyping, we used GeneSeek GGP Porcine HD Genomic Profiler v1, which included 68,516 single nucleotide polymorphisms evenly distributed with an average spacing of 25 kb (Illumina Inc, San Diego, CA, USA).

RESULTS

Based on the results of the Fst analysis, 724 variants representing selection signals for the signs BALWT, BALWT1, NBA, and TNB (weight of piglets born alive, average weight of the 1st piglets born alive, total number born alive, total number born). At the same time, 18 common variants have been identified that are potential markers for both the number of piglets at birth and the weight of piglets at birth, which is extremely important for breeding work to improve reproductive characteristics in sows.

CONCLUSION

Оur work resulted in identification of variants associated with the reproductive characteristics of pigs. Moreover, we identified, variants which are potential markers for both the number of piglets at birth and the weight of piglets at birth, which is extremely important for breeding work to improve reproductive performance in sows.

Multi-tissue transcriptome analysis to identify candidate genes associated with weight regulation in Hanwoo cattle

While genetic markers related to meat production traits have been identified in many other cattle breeds, research on weight in Hanwoo cattle (Korean native cattle) is still insufficient. In this study, we performed expression quantitative trait loci (eQTL) analysis and differential gene expression analysis to detect candidate genes influencing the weight characteristics of 32 castrated Hanwoo cattle across 22 tissues and, we identified variants that affect gene expression levels. In total, we identified a total of 3,298 differentially expressed genes, among which we discovered key genes such as UBD, RGS2, FASN, and SCD that have functions related to adipogenesis, body weight, obesity, and lipid metabolism. Gene-set enrichment analysis revealed that candidate genes in adipose tissue are involved in metabolic pathways linked to obesity-related traits, adipose metabolism, and lipid metabolism. Additionally, we found that decreased expression of TRIM31 contributes to weight gain which can be explained by the associated candidate cis-eQTL genotypes for TRIM31 and their effect on differential gene expression between the lower and higher weight groups. Our findings revealed candidate genes associated with the weight of Hanwoo cattle and perhaps can provide comprehensive insights into the association of weight with various tissues beyond adipose tissue and muscle, indicating the potential for expanding the focus of livestock trait research.

Genomic and transcriptomic analyses enable the identification of important genes associated with subcutaneous fat deposition in Holstein cows

Subcutaneous fat deposition has many important roles in dairy cattle, including immunological defense and mechanical protection. The main objectives of this study are to identify key candidate genes regulating subcutaneous fat deposition in high-producing dairy cows by integrating genomic and transcriptomic datasets. A total of 1654 genotyped Holstein cows are used to perform a genome-wide association study (GWAS) aiming to identify genes associated with subcutaneous fat deposition. Subsequently, weighted gene co-expression network analyses (WGCNA) are conducted based on RNA-sequencing data of 34 cows and cow yield deviations of subcutaneous fat deposition. Lastly, differentially expressed (DE) mRNA, lncRNA, and differentially alternative splicing genes are obtained for 12 Holstein cows with extreme and divergent phenotypes for subcutaneous fat deposition. Forty-six protein-coding genes are identified as candidate genes regulating subcutaneous fat deposition in Holstein cattle based on GWAS. Eleven overlapping genes are identified based on the analyses of DE genes and WGCNA. Furthermore, the candidate genes identified based on GWAS, WGCNA, and analyses of DE genes are significantly enriched for pathways involved in metabolism, oxidative phosphorylation, thermogenesis, fatty acid degradation, and glycolysis/gluconeogenesis pathways. Integrating all findings, the NID2, STARD3, UFC1, DEDD, PPP1R1B, and USP21 genes are considered to be the most important candidate genes influencing subcutaneous fat deposition traits in Holstein cows. This study provides novel insights into the regulation mechanism underlying fat deposition in high-producing dairy cows, which will be useful when designing management and breeding strategies.

Gene expression networks and functionally enriched pathways involved in the response of domestic chicken to acute heat stress

Heat stress in poultry houses, especially in warm areas, is one of the main environmental factors that restrict the growth of broilers or laying performance of layers, suppresses the immune system, and deteriorates egg quality and feed conversion ratio. The molecular mechanisms underlying the response of chicken to acute heat stress (AHS) have not been comprehensively elucidated. Therefore, the main object of the current work was to investigate the liver gene expression profile of chickens under AHS in comparison with their corresponding control groups, using four RNA-seq datasets. The meta-analysis, GO and KEGG pathway enrichment, WGCNA, machine-learning, and eGWAS analyses were performed. The results revealed 77 meta-genes that were mainly related to protein biosynthesis, protein folding, and protein transport between cellular organelles. In other words, under AHS, the expression of genes involving in the structure of rough reticulum membrane and in the process of protein folding was adversely influenced. In addition, genes related to biological processes such as "response to unfolded proteins," "response to reticulum stress" and "ERAD pathway" were differentially regulated. We introduce here a couple of genes such as HSPA5, SSR1, SDF2L1, and SEC23B, as the most significantly differentiated under AHS, which could be used as bio-signatures of AHS. Besides the mentioned genes, the main findings of the current work may shed light to the identification of the effects of AHS on gene expression profiling of domestic chicken as well as the adaptive response of chicken to environmental stresses.

Recent developments and future directions in meta-analysis of differential gene expression in livestock RNA-Seq

Decreases in the costs of high-throughput sequencing technologies have led to continually increasing numbers of livestock RNA-Seq studies in the last decade. Although the number of studies has increased dramatically, most livestock RNA-Seq experiments are limited by cost to a small number of biological replicates. Meta-analysis procedures can be used to integrate and jointly analyze data from multiple independent studies. Meta-analyses increase the sample size, which in turn increase both statistical power and robustness of the results. In this work, we discuss cutting edge approaches to combining results from multiple independent RNA-Seq studies to improve livestock transcriptomics research. We review currently published RNA-Seq meta-analyses in livestock, describe many of the key issues specific to RNA-Seq meta-analysis in livestock species, and discuss future perspectives.

Genes Involved in Feed Efficiency Identified in a Meta-Analysis of Rumen Tissue from Two Populations of Beef Steers

In cattle, the rumen is an important site for the absorption of feed by-products released by bacterial fermentation, and variation in ruminal function plays a role in cattle feed efficiency. Studies evaluating gene expression in the rumen tissue have been performed prior to this. However, validating the expression of genes identified in additional cattle populations has been challenging. The purpose of this study was to perform a meta-analysis of the ruminal transcriptome of two unrelated populations of animals to identify genes that are involved in feed efficiency across populations. RNA-seq data from animals with high and low residual feed intake (RFI) from a United States population of cattle (eight high and eight low RFI) and a Canadian population of cattle (nine high and nine low RFI) were analyzed for differences in gene expression. A total of 83 differentially expressed genes were identified. Some of these genes have been previously identified in other feed efficiency studies. These genes included ATP6AP1, BAG6, RHOG, and YPEL3. Differentially expressed genes involved in the Notch signaling pathway and in protein turnover were also identified. This study, combining two unrelated populations of cattle in a meta-analysis, produced several candidate genes for feed efficiency that may be more robust indicators of feed efficiency than those identified from single populations of animals.

Genomic Selection and Genome-wide Association Study for Feed-Efficiency Traits in a Farmed Nile Tilapia (Oreochromis niloticus) Population

Nile tilapia is a key aquaculture species with one of the highest production volumes globally. Genetic improvement of feed efficiency via selective breeding is an important goal, and genomic selection may expedite this process. The aims of this study were to 1) dissect the genetic architecture of feed-efficiency traits in a Nile tilapia breeding population, 2) map the genomic regions associated with these traits and identify candidate genes, 3) evaluate the accuracy of breeding value prediction using genomic data, and 4) assess the impact of the genetic marker density on genomic prediction accuracies. Using an experimental video recording trial, feed conversion ratio (FCR), body weight gain (BWG), residual feed intake (RFI) and feed intake (FI) traits were recorded in 40 full-sibling families from the GIFT (Genetically Improved Farmed Tilapia) Nile tilapia breeding population. Fish were genotyped with a ThermoFisher Axiom 65 K Nile tilapia SNP array. Significant heritabilities, ranging from 0.12 to 0.22, were estimated for all the assessed traits using the genomic relationship matrix. A negative but favourable genetic correlation was found between BWG and the feed-efficiency related traits; -0.60 and -0.63 for FCR and RFI, respectively. While the genome-wide association analyses suggested a polygenic genetic architecture for all the measured traits, there were significant QTL identified for BWG and FI on chromosomes seven and five respectively. Candidate genes previously found to be associated with feed-efficiency traits were located in these QTL regions, including ntrk3a, ghrh and eif4e3. The accuracy of breeding value prediction using the genomic data was up to 34% higher than using pedigree records. A SNP density of approximately 5,000 SNPs was sufficient to achieve similar prediction accuracy as the full genotype data set. Our results highlight the potential of genomic selection to improve feed efficiency traits in Nile tilapia breeding programmes.

Analysis of merged whole blood transcriptomic datasets to identify circulating molecular biomarkers of feed efficiency in growing pigs

Background

Improving feed efficiency (FE) is an important goal due to its economic and environmental significance for farm animal production. The FE phenotype is complex and based on the measurements of the individual feed consumption and average daily gain during a test period, which is costly and time-consuming. The identification of reliable predictors of FE is a strategy to reduce phenotyping efforts.

Results

Gene expression data of the whole blood from three independent experiments were combined and analyzed by machine learning algorithms to propose molecular biomarkers of FE traits in growing pigs. These datasets included Large White pigs from two lines divergently selected for residual feed intake (RFI), a measure of net FE, and in which individual feed conversion ratio (FCR) and blood microarray data were available. Merging the three datasets allowed considering FCR values (Mean = 2.85; Min = 1.92; Max = 5.00) for a total of n = 148 pigs, with a large range of body weight (15 to 115 kg) and different test period duration (2 to 9 weeks). Random forest (RF) and gradient tree boosting (GTB) were applied on the whole blood transcripts (26,687 annotated molecular probes) to identify the most important variables for binary classification on RFI groups and a quantitative prediction of FCR, respectively. The dataset was split into learning (n = 74) and validation sets (n = 74). With iterative steps for variable selection, about three hundred’s (328 to 391) molecular probes participating in various biological pathways, were identified as important predictors of RFI or FCR. With the GTB algorithm, simpler models were proposed combining 34 expressed unique genes to classify pigs into RFI groups (100% of success), and 25 expressed unique genes to predict FCR values (R² = 0.80, RMSE = 8%). The accuracy performance of RF models was slightly lower in classification and markedly lower in regression.

Conclusion

From small subsets of genes expressed in the whole blood, it is possible to predict the binary class and the individual value of feed efficiency. These predictive models offer good perspectives to identify animals with higher feed efficiency in precision farming applications.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07843-4.

Genome-wide detection of CNVs and their association with performance traits in broilers

Background

Copy number variations (CNVs) are a major type of structural genomic variants that underlie genetic architecture and phenotypic variation of complex traits, not only in humans, but also in livestock animals. We identified CNVs along the chicken genome and analyzed their association with performance traits. Genome-wide CNVs were inferred from Affymetrix® high density SNP-chip data for a broiler population. CNVs were concatenated into segments and association analyses were performed with linear mixed models considering a genomic relationship matrix, for birth weight, body weight at 21, 35, 41 and 42 days, feed intake from 35 to 41 days, feed conversion ratio from 35 to 41 days and, body weight gain from 35 to 41 days of age.

Results

We identified 23,214 autosomal CNVs, merged into 5042 distinct CNV regions (CNVRs), covering 12.84% of the chicken autosomal genome. One significant CNV segment was associated with BWG on GGA3 (q-value = 0.00443); one significant CNV segment was associated with BW35 (q-value = 0.00571), BW41 (q-value = 0.00180) and BW42 (q-value = 0.00130) on GGA3, and one significant CNV segment was associated with BW on GGA5 (q-value = 0.00432). All significant CNV segments were verified by qPCR, and a validation rate of 92.59% was observed. These CNV segments are located nearby genes, such as KCNJ11, MyoD1 and SOX6, known to underlie growth and development. Moreover, gene-set analyses revealed terms linked with muscle physiology, cellular processes regulation and potassium channels.

Conclusions

Overall, this CNV-based GWAS study unravels potential candidate genes that may regulate performance traits in chickens. Our findings provide a foundation for future functional studies on the role of specific genes in regulating performance in chickens.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07676-1.