Transcriptome profiling of longissimus lumborum in Holstein bulls and steers with different beef qualities

Li, Yan; Wang, Meimei; Li, Qiufeng; Gao, Yanxia; Li, Qian; Li, Jianguo; Cao, Yong

doi:10.1371/journal.pone.0235218

Cited by 22 publications

(19 citation statements)

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Gene DNAJB9 was associated with inflammatory, immune and stress response in lambs (Sabino et al, 2018). Li et al (2020) observed that gene EEPD1 was associated with meat quality and reproduction traits in Holstein bulls. Saatchi et al (2014) find out that gene SEPT7 was a candidate gene for QTL affected body weights in Maine-Anjou cattle.…”

Section: Resultsmentioning

confidence: 92%

Detection of Selection Signals in Cattle Populations by Pca

Olšanská

Kasarda

Lehocká

et al. 2020

AGR

View full text Add to dashboard Cite

The presented study provides a genome-wide scan of selection signals in cattle by principal component analysis (PCA). The aim was to identify SNP affected by intensive selection based on package PCAdapt implemented under software R. This analysis provided insight into the association between the SNP frequencies related to population differentiation. The four cattle populations were involved in the analysis (Slovak Spotted cattle, Ayrshire, Swiss Simmental and Holstein) with overall 272 of genotyped individuals. After applying quality control, the final dataset consisted of 35 675 SNPs, with an overall length of 2496.14 Mb and average space between adjacent SNP 70.03 ± 76.1 kb. After performing PCA analysis, the uniqueness of the breeds was revealed. On the other hand, a close genetic relationship and eleven SNPs affected by selection were found, with a position close to 162 genes involved in the various biological processes. The majority of genes were involved in the positive regulation of adenylate cyclase activity, embryo development and somatic diversification of immune receptors via somatic mutation. Several candidate genes for genetic control of the immune system (DNAJB9), muscle development (SEPT7, TRIM32, ROCK1, NRAP, PZDZ8, HSPA12A and FGFR2), milk production (SOCS5, CD46), reproduction (LHCGR, EEPD1, FSHR) and coat colour (KIT) were identified. Our results provide insights into the regions of the genome affected by the intensive selection of analysed cattle populations.

show abstract

Section: Resultsmentioning

confidence: 92%

Detection of Selection Signals in Cattle Populations by Pca

Olšanská

Kasarda

Lehocká

et al. 2020

AGR

View full text Add to dashboard Cite

show abstract

“…NFKB1 [31], CYP2R1 [32], HSF2 [33], TMEM135 [34], PDCD4 [35], HERPUD2 [36], and NMRAL1 [37]) and seven (SPNS1 [31], MYOD1 [38], PDXK [39], TMUB1 [34],…”

Section: Hub Gene Searches For Modules Of Interestmentioning

confidence: 99%

Use of a graph neural network to the weighted gene co-expression network analysis of Korean native cattle

Lee

Chung

Chung³

et al. 2021

Preprint

View full text Add to dashboard Cite

In the general framework of the weighted gene co-expression network analysis (WGCNA), a hierarchical clustering algorithm is commonly used to module definition. However, hierarchical clustering depends strongly on the topological overlap measure. In other words, this algorithm may assign two genes with low topological overlap to different modules even though their expression patterns are similar. Here, a novel gene module clustering algorithm for WGCNA is proposed. We develop a gene module clustering network (gmcNet), which simultaneously addresses single-level expression and topological overlap measure. The proposed gmcNet includes a "co-expression pattern recognizer" (CEPR) and "module classifier". The CEPR incorporates expression features of single genes into the topological features of co-expressed ones. Given this CEPR-embedded feature, the module classifier computes module assignment probabilities. We validated gmcNet performance using 4,976 genes from 20 native Korean cattle. We observed that the CEPR generates more robust features than single-level expression or topological overlap measure. Given the CEPR-embedded feature, gmcNet achieved the best performance in terms of modularity (0.261) and the differentially expressed signal (27.739) compared with other clustering methods tested. Furthermore, gmcNet detected some interesting biological functionalities for carcass weight, backfat thickness, intramuscular fat, and beef tenderness of Korean native cattle. Therefore, gmcNet is a useful framework for WGCNA module clustering.

show abstract

“…Therefore, we performed a transcriptome analysis to attempt to elucidate this molecular mechanism. Recent improvements in the comprehensive analysis of large-scale RNA sequencing (RNAseq) data have been generated, and several research institutes attempted to study mRNA expression profiles in cattle [11][12][13][14]. However, RNA-seq analysis has not been performed to report the transcriptome associated with pure Japanese Black cattle.…”

Section: Introductionmentioning

confidence: 99%

Gene Expression Analysis Provides New Insights into the Mechanism of Intramuscular Fat Formation in Japanese Black Cattle

Ueda

Hosoda

Yoshino

et al. 2021

Genes

View full text Add to dashboard Cite

Japanese Black cattle (Japanese Wagyu) have a unique phenotype in which ectopic intramuscular fat accumulates in skeletal muscle, producing finely marbled beef. However, the mechanism of intramuscular fat formation in Japanese Black cattle remains unclear. To investigate the key genes involved in intramuscular fat accumulation, we comprehensively analyzed mRNA levels in subcutaneous and intramuscular fat tissues using RNA sequence (RNA-seq) analysis, which detected 27,606 genes. We identified eight key genes, namely carboxypeptidase E, tenascin C, transgelin, collagen type IV alpha 5 (COL4A5), cysteine and glycine-rich protein 2, PDZ, and LIM domain 3, phosphatase 1 regulatory inhibitor subunit 14A, and regulator of calcineurin 2. These genes were highly and specifically expressed in intramuscular fat tissue. Immunohistochemical analysis revealed a collagen network, including COL4A5, in the basement membrane around the intramuscular fat tissue. Moreover, pathway analysis revealed that, in intramuscular fat tissue, differentially expressed genes are related to cell adhesion, proliferation, and cancer pathways. Furthermore, pathway analysis showed that the transforming growth factor-β (TGF-β) and small GTPases regulators RASGRP3, ARHGEF26, ARHGAP10, ARHGAP24, and DLC were upregulated in intramuscular fat. Our study suggests that these genes are involved in intramuscular fat formation in Japanese Black cattle.

show abstract

Transcriptome profiling of longissimus lumborum in Holstein bulls and steers with different beef qualities

Cited by 22 publications

References 52 publications

Detection of Selection Signals in Cattle Populations by Pca

Detection of Selection Signals in Cattle Populations by Pca

Use of a graph neural network to the weighted gene co-expression network analysis of Korean native cattle

Gene Expression Analysis Provides New Insights into the Mechanism of Intramuscular Fat Formation in Japanese Black Cattle

Contact Info

Product

Resources

About