Molecular characterization, expression patterns and subcellular localization of Myotrophin (MTPN) gene in porcine skeletal muscle

Transcriptome analyses reveal differentially expressed genes associated with development of the palatal organ in bighead carp (Hypophthalmichthys nobilis)

The palatal organ is a filter-feeding related organ and occupies a considerable proportion of the head of bighead carp (Hypophthalmichthys nobilis), a large cyprinid fish intensive aquaculture in Asia. In this study, we performed RNA-seq of the palatal organ during growth periods of two (M2), six (M6) and 15 (M15) months of age after hatching. The numbers of differentially expressed genes (DEGs) were 1384, 481 and 1837 for M2 VS M6, M6 VS M15 and M2 VS M15 respectively. The following signaling pathways of energy metabolism and cytoskeleton function were enriched, including ECM-receptor interaction, Cardiac muscle contraction, Steroid biosynthesis and PPAR signaling pathway. Several members of collagen family (col1a1, col2a1, col6a2, col6a3, col9a2), Laminin gamma 1 (lamc1), integrin alpha 1 (itga1), Fatty acid binding protein 2 (fads2) and lipoprotein lipase (lpl), and Protein tyrosine kinase 7 (Ptk7) are candidate genes for growth and development of basic tissues of the palatal organ. Furthermore, taste-related genes such as fgfrl1, fgf8a, fsta and notch1a were also identified, which may be involved in the development of taste buds of the palatal organ. The transcriptome data obtained in this study provide insights into the understanding functions and development mechanisms of palatal organ, and potential candidate genes that may be related to the genetic modulation of head size of bighead carp.

Whole-Genome Sequencing and Characterization of Buffalo Genetic Resources: Recent Advances and Future Challenges

The buffalo was domesticated around 3000-6000 years ago and has substantial economic significance as a meat, dairy, and draught animal. The buffalo has remained underutilized in terms of the development of a well-annotated and assembled reference genome de novo. It is mandatory to explore the genetic architecture of a species to understand the biology that helps to manage its genetic variability, which is ultimately used for selective breeding and genomic selection. Morphological and molecular data have revealed that the swamp buffalo population has strong geographical genomic diversity with low gene flow but strong phenotypic consistency, while the river buffalo population has higher phenotypic diversity with a weak phylogeographic structure. The availability of recent high-quality reference genome and genotyping marker panels has invigorated many genome-based studies on evolutionary history, genetic diversity, functional elements, and performance traits. The increasing molecular knowledge syndicate with selective breeding should pave the way for genetic improvement in the climatic resilience, disease resistance, and production performance of water buffalo populations globally.

Key Genes Regulating Skeletal Muscle Development and Growth in Farm Animals

Simple Summary

Skeletal muscle mass is an important economic trait, and muscle development and growth is a crucial factor to supply enough meat for human consumption. Thus, understanding (candidate) genes regulating skeletal muscle development is crucial for understanding molecular genetic regulation of muscle growth and can be benefit the meat industry toward the goal of increasing meat yields. During the past years, significant progress has been made for understanding these mechanisms, and thus, we decided to write a comprehensive review covering regulators and (candidate) genes crucial for muscle development and growth in farm animals. Detection of these genes and factors increases our understanding of muscle growth and development and is a great help for breeders to satisfy demands for meat production on a global scale.

Abstract

Farm-animal species play crucial roles in satisfying demands for meat on a global scale, and they are genetically being developed to enhance the efficiency of meat production. In particular, one of the important breeders’ aims is to increase skeletal muscle growth in farm animals. The enhancement of muscle development and growth is crucial to meet consumers’ demands regarding meat quality. Fetal skeletal muscle development involves myogenesis (with myoblast proliferation, differentiation, and fusion), fibrogenesis, and adipogenesis. Typically, myogenesis is regulated by a convoluted network of intrinsic and extrinsic factors monitored by myogenic regulatory factor genes in two or three phases, as well as genes that code for kinases. Marker-assisted selection relies on candidate genes related positively or negatively to muscle development and can be a strong supplement to classical selection strategies in farm animals. This comprehensive review covers important (candidate) genes that regulate muscle development and growth in farm animals (cattle, sheep, chicken, and pig). The identification of these genes is an important step toward the goal of increasing meat yields and improves meat quality.

A genome-wide association study revealed five SNPs affecting 8-month weight in sheep

Lamb weight at 8 months of age is an important trait in the sheep industry in terms of the onset of puberty around this age; however, knowledge of its effective genetic factors is limited. Therefore, a GWAS using the 50K SNP-Chip was performed on 96 Baluchi sheep to identify the genomic regions associated with 8-month weight. The results of the present study revealed five SNPs on chromosomes 4, 14 and 16 at 5% chromosome-wide significance level, jointly accounting for 0.95% of total genetic variance. Four genes - MTPN, HYDIN, LRGUK and ZFP90 - were found in 50 kb intervals around the significant SNPs, of which MTPN is involved in regulation of skeletal muscle growth. Our results may provide a new vision to identify the genomic regions affecting growth traits in sheep.

Identification and validation of a novel candidate gene regulating net meat weight in Simmental beef cattle based on imputed next-generation sequencing

Objectives

Genome‐wide association studies (GWAS) represent a powerful approach to detecting candidate genes for economically important traits in livestock. Our aim was to identify promising candidate muscle development genes that affect net meat weight (NMW) and validate these candidate genes in cattle.

Materials and methods

Using a next‐generation sequencing (NGS) dataset, we applied ~ 12 million imputed single nucleotide polymorphisms (SNPs) from 1,252 Simmental cattle to detect genes influencing net meat yield by way of a linear mixed model method. Haplotype and linkage disequilibrium (LD) blocks were employed to augment support for identified genes. To investigate the role of MTPN in bovine muscle development, we isolated myoblasts from the longissimus dorsi of a bovine foetus and treated the cells during proliferation, differentiation and hypertrophy.

Results

We identified one SNP (rs100670823) that exceeded our stringent significance threshold (P = 8.58 × 10⁻⁸) for a putative NMW‐related quantitative trait locus (QTL). We identified a promising candidate gene, myotrophin (MTPN), in the region around this SNP Myotrophin had a stimulatory effect on six muscle‐related markers that regulate differentiation and myoblast fusion. During hypertrophy, myotrophin promoted myotube hypertrophy and increased myotube diameters. Cell viability assay and flow cytometry showed that myotrophin inhibited myoblast proliferation.

Conclusions

The present experiments showed that myotrophin increases differentiation and hypertrophy of skeletal muscle cells, while inhibiting their proliferation. Our examination of GWAS results with in vitro biological studies provides new information regarding the potential application of myotrophin to increase meat yields in cattle and helpful information for further studies.

Novel insights into the genetic basis of buffalo reproductive performance

Background

Fertility is a complex trait that has a major impact on the development of the buffalo industry. Genome-wide association study (GWAS) has increased the ability to detect genes influencing complex traits, and many important genes related to reproductive traits have been identified in ruminants. However, reproductive traits are influenced by many factors. The development of the follicle is one of the most important internal processes affecting fertility. Genes found by GWAS to be associated with follicular development may directly affect fertility. The present study combined GWAS and RNA-seq of follicular granulosa cells to identify important genes which may affect fertility in the buffalo.

Results

The 90 K Affymetrix Axiom Buffalo SNP Array was used to identify the SNPs, genomic regions, and genes that were associated with reproductive traits. A total of 40 suggestive loci (related to 28 genes) were identified to be associated with six reproductive traits (first, second and third calving age, calving interval, the number of services per conception and open days). Interestingly, the mRNA expressions of 25 of these genes were also observed in buffalo follicular granulosa cells. The IGFBP7 gene showed high level of expression during whole antral follicle growth. The knockdown of IGFBP7 in buffalo granulosa cells promoted cell apoptosis and hindered cell proliferation, and increased the production of progesterone and estradiol. Furthermore, a notable signal was detected at 2.3–2.7 Mb on the equivalent of bovine chromosome 5 associated with age at second calving, calving interval, and open days.

Conclusions

The genes associated with buffalo reproductive traits in this study may have effect on fertility by regulating of follicular growth. These results may have important implications for improving buffalo breeding programs through application of genomic information.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5208-6) contains supplementary material, which is available to authorized users.

Messenger RNA sequencing and pathway analysis provide novel insights into the biological basis of chickens' feed efficiency

Background

Advanced selection technologies have been developed and continually optimized to improve traits of agricultural importance; however, these methods have been primarily applied without knowledge of underlying biological changes that may be induced by selection. This study aims to characterize the biological basis of differences between chickens with low and high feed efficiency (FE) with a long-term goal of improving the ability to select for FE.

Results

High-throughput RNA sequencing was performed on 23 breast muscle samples from commercial broiler chickens with extremely high (n = 10) and low (n = 13) FE. An average of 34 million paired-end reads (75 bp) were produced for each sample, 80% of which were properly mapped to the chicken reference genome (Ensembl Galgal4). Differential expression analysis identified 1,059 genes (FDR < 0.05) that significantly divergently expressed in breast muscle between the high- and low-FE chickens. Gene function analysis revealed that genes involved in muscle remodeling, inflammatory response and free radical scavenging were mostly up-regulated in the high-FE birds. Additionally, growth hormone and IGFs/PI3K/Akt signaling pathways were enriched in differentially expressed genes, which might contribute to the high breast muscle yield in high-FE birds and partly explain the FE advantage of high-FE chickens.

Conclusions

This study provides novel insights into transcriptional differences in breast muscle between high- and low-FE broiler chickens. Our results show that feed efficiency is associated with breast muscle growth in these birds; furthermore, some physiological changes, e.g., inflammatory response and oxidative stress, may occur in the breast muscle of the high-FE chickens, which may be of concern for continued selection for both of these traits together in modern broiler chickens.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1364-0) contains supplementary material, which is available to authorized users.

Genome wide association studies for body conformation traits in the Chinese Holstein cattle population

BACKGROUND

Genome-wide association study (GWAS) is a powerful tool for revealing the genetic basis of quantitative traits. However, studies using GWAS for conformation traits of cattle is comparatively less. This study aims to use GWAS to find the candidates genes for body conformation traits.

RESULTS

The Illumina BovineSNP50 BeadChip was used to identify single nucleotide polymorphisms (SNPs) that are associated with body conformation traits. A least absolute shrinkage and selection operator (LASSO) was applied to detect multiple SNPs simultaneously for 29 body conformation traits with 1,314 Chinese Holstein cattle and 52,166 SNPs. Totally, 59 genome-wide significant SNPs associated with 26 conformation traits were detected by genome-wide association analysis; five SNPs were within previously reported QTL regions (Animal Quantitative Trait Loci (QTL) database) and 11 were very close to the reported SNPs. Twenty-two SNPs were located within annotated gene regions, while the remainder were 0.6-826 kb away from known genes. Some of the genes had clear biological functions related to conformation traits. By combining information about the previously reported QTL regions and the biological functions of the genes, we identified DARC, GAS1, MTPN, HTR2A, ZNF521, PDIA6, and TMEM130 as the most promising candidate genes for capacity and body depth, chest width, foot angle, angularity, rear leg side view, teat length, and animal size traits, respectively. We also found four SNPs that affected four pairs of traits, and the genetic correlation between each pair of traits ranged from 0.35 to 0.86, suggesting that these SNPs may have a pleiotropic effect on each pair of traits.

CONCLUSIONS

A total of 59 significant SNPs associated with 26 conformation traits were identified in the Chinese Holstein population. Six promising candidate genes were suggested, and four SNPs showed genetic correlation for four pairs of traits.