Identification of Key Modules and Hub Genes Involved in Regulating the Color of Chicken Breast Meat Using WGCNA

Network analyses unraveled the complex interactions in the rumen microbiota associated with methane emission in dairy cattle

BACKGROUND

Methane emissions from livestock, particularly from dairy cattle, represent a significant source of greenhouse gas, contributing to the global climate crisis. Understanding the complex interactions within the rumen microbiota that influence methane emissions is crucial for developing effective mitigation strategies.

RESULTS

This study employed Weighted Gene Co-expression Network Analysis to investigate the complex interactions within the rumen microbiota that influence methane emissions. By integrating extensive rumen microbiota sequencing data with precise methane emission measurements in 750 Holstein dairy cattle, our research identified distinct microbial communities and their associations with methane production. Key findings revealed that the blue module from network analysis was significantly correlated (0.45) with methane emissions. In this module, taxa included the genera Prevotella and Methanobrevibactor, along with species such as Prevotella brevis, Prevotella ruminicola, Prevotella baroniae, Prevotella bryantii, Lachnobacterium bovis, and Methanomassiliicoccus luminyensis are the key components to drive the complex networks. However, the absence of metagenomics sequencing is difficult to reveal the deeper taxa level and functional profiles.

CONCLUSIONS

The application of Weighted Gene Co-expression Network Analysis provided a comprehensive understanding of the microbiota-methane emission relationship, serving as an innovative approach for microbiota-phenotype association studies in cattle. Our findings underscore the importance of microbiota-trait and microbiota-microbiota associations related to methane emission in dairy cattle, contributing to a systematic understanding of methane production in cattle. This research offers key information on microbial management for mitigating environmental impact on the cattle population.

Identification of Key Genes Correlated with Economic Trait Superiorities and Their SNP Screening Through Transcriptome Comparisons, WGCNA and Pearson Correlation Coefficient in the Sea Cucumber Apostichopus Japonicus

Variation in morphology-driven economic traits is a common issue hindering the development of the sea cucumber aquaculture industry. In this study, transcriptome comparisons, weighted gene correlation network analysis (WGCNA) and Pearson correlation coefficient (PCC) were first employed to identify key genes correlated with morphological variation in the sea cucumber Apostichopus japonicus, after which the relationship between identified key genes (relative expression and genotype) and economic trait phenotypes was investigated to screen potential biomarker targets for molecular-assisted breeding. The results showed that three genes (putative ficolin-2, fibrinogen c domain-containing protein 1, and angiopoietin-4) were closely associated with economic trait superiorities. Two single nucleotide polymorphisms (SNPs) were identified in the putative ficolin-2 gene as having a strong correlation with body weight and papilla number. The findings from this study will enrich breeding biomarker resources and benefit the development of molecular-assisted breeding techniques in sea cucumber aquaculture.

Transcriptomic analysis reveals differentially expressed genes associated with meat quality in Chinese Dagu chicken and AA+ broiler roosters

BACKGROUND

With the improvement of living standards, the quality of chicken has become a significant concern. Chinese Dagu Chicken (dual-purpose type) and Arbor Acres plus broiler (AA+ broiler) (meat-type) were selected as the research subjects in this study, the meat quality of the breast and leg muscles were measured. However, the molecular mechanism(s) underlying regulation of muscle development are not yet fully elucidated. Therefore, finding molecular markers or major genes that regulate muscle quality has become a crucial breakthrough in chicken breeding. Unraveling the molecular mechanism behind meat traits in chicken and other domestic fowl is facilitated by identifying the key genes associated with these developmental events. Here, a comparative transcriptomic analysis of chicken meat was conducted on breast muscles (BM) and leg muscles (LM) in AA+ broilers (AA) and Dagu chicken (DG) to explore the differences in their meat traits employing RNA-seq.

RESULTS

Twelve cDNA libraries of BM and LM from AA and DG were constructed from four experimental groups, yielding 14,464 genes. Among them, Dagu chicken breast muscles (DGB) vs AA+ broilers breast muscles (AAB) showed 415 upregulated genes and 449 downregulated genes, Dagu chicken leg muscles (DGL) vs AA+ broilers leg muscles (AAL) exhibited 237 upregulated genes and 278 downregulated genes, DGL vs DGB demonstrated 391 upregulated genes and 594 downregulated genes, and AAL vs AAB displayed 122 upregulated genes and 154 downregulated genes. 13 genes, including nine upregulated genes (COX5A, COX7C, NDUFV1, UQCRFS1, UQCR11, BRT-1, FGF14, TMOD1, MYOZ2) and four downregulated genes (MYBPC3, MYO7B, MTMR7, and TNNC1), were found to be associated with the oxidative phosphorylation signaling pathway. Further analysis revealed that the differentially expressed genes (DEGs) from muscle were enriched in various pathways, such as metabolic pathways, oxidative phosphorylation, carbon metabolism, glycolysis, extracellular matrix-receptor interaction, biosynthesis of amino acids, focal adhesion, vascular smooth muscle contraction, and cardiac muscle contraction, all of which are involved in muscle development and metabolism. This study also measured the meat quality of the breast and leg muscles from the two breeds, which demonstrated superior overall meat quality in Chinese Dagu Chicken compared to the AA+ broiler.

CONCLUSIONS

Our findings show that the meat quality of dual-purpose breeds (Chinese Dagu chicken) is higher than meat-type (AA+ broiler), which may be related to the DEGs regulating muscle development and metabolism. Our findings also provide transcriptomic insights for a comparative analysis of molecular mechanisms underlying muscle development between the two breeds, and have practical implications for the improvement of chicken breeding practices.

Weighted gene co-expression network analysis identifies important modules and hub genes involved in the regulation of breast muscle yield in broilers

OBJECTIVE

Increasing breast meat production is one of the primary goals of the broiler industry. Over the past few decades, tremendous progress has been made in genetic selection and the identification of candidate genes for improving the breast muscle mass. However, the molecular network contributing to muscle production traits in chickens still needs to be further illuminated.

METHODS

A total of 150 1-day-old male 817 broilers were reared in a floor litter system. At the market age of 50 d, eighteen healthy 817 broilers were slaughtered and the left pectoralis major muscle sample from each bird was collected for RNA-seq sequencing. The birds were then plucked and eviscerated and the whole breast muscle was removed and weighed. Breast muscle yield was calculated as the ratio of the breast muscle weight to the eviscerated weight. To identify the co-expression networks and hub genes contributing to breast muscle yield in chickens, we performed weighted gene co-expression network analysis (WGCNA) based on the 18 transcriptome datasets of pectoralis major muscle from eighteen 817 broilers.

RESULTS

The WGCNA analysis classified all co-expressed genes in the pectoral muscle of 817 broilers into 44 modules. Among these modules, the turquoise and skyblue3 modules were found to be most significantly positively (r = 0.78, p = 1e-04) and negatively (r = -0.57, p = 0.01) associated with breast meat yield, respectively. Further analysis identified several hub genes (e.g., DLX3, SH3RF2, TPM1, CAV3, MYF6, and CFL2) that involved in muscle structure and muscle development were identified as potential regulators of breast meat production.

CONCLUSION

The present study has advanced our understanding of the molecular regulatory networks contributing to muscle growth and breast muscle production and will contribute to the molecular breeding of chickens in the future.

Genome-Wide Association Study Reveals the Genetic Architecture of Growth and Meat Production Traits in a Chicken F2 Resource Population

BACKGROUND/OBJECTIVES

For genomic selection to enhance the efficiency of broiler production, finding SNPs and candidate genes that define the manifestation of main selected traits is essential. We conducted a genome-wide association study (GWAS) for growth and meat productivity traits of roosters from a chicken F2 resource population (n = 152).

METHODS

The population was obtained by crossing two breeds with contrasting phenotypes for performance indicators, i.e., Russian White (slow-growing) and Cornish White (fast-growing). The birds were genotyped using the Illumina Chicken 60K SNP iSelect BeadChip. After LD filtering of the data, 54,188 SNPs were employed for the GWAS analysis that allowed us to reveal significant specific associations for phenotypic traits of interest and economic importance.

RESULTS

At the threshold value of p < 9.2 × 10-7, 83 SNPs associated with body weight at the age of 28, 42, and 63 days were identified, as well as 171 SNPs associated with meat qualities (average daily gain, slaughter yield, and dressed carcass weight and its components). Moreover, 34 SNPs were associated with a group of three or more traits, including 15 SNPs significant for a group of growth traits and 5 SNPs for a group of meat productivity indicators. Relevant to these detected SNPs, nine prioritized candidate genes associated with the studied traits were revealed, including WNT2, DEPTOR, PPA2, UNC80, DDX51, PAPPA, SSC4D, PTPRU, and TLK2.

CONCLUSIONS

The found SNPs and candidate genes can serve as genetic markers for growth and meat performance characteristics in chicken breeding in order to achieve genetic improvement in broiler production.

Exploring the Molecular Mechanism of Skeletal Muscle Development in Ningxiang Pig by Weighted Gene Co-Expression Network Analysis

With the continuous improvement in living standards, people's demand for high-quality meat is increasing. Ningxiang pig has delicious meat of high nutritional value, and is loved by consumers. However, its slow growth and low meat yield seriously restrict its efficient utilization. Gene expression is the internal driving force of life activities, so in order to fundamentally improve its growth rate, it is key to explore the molecular mechanism of skeletal muscle development in Ningxiang pigs. In this paper, Ningxiang boars were selected in four growth stages (30 days: weaning period, 90 days: nursing period, 150 days: early fattening period, and 210 days: late fattening period), and the longissimus dorsi (LD) muscle was taken from three boars in each stage. The fatty acid content, amino acid content, muscle fiber diameter density and type of LD were detected by gas chromatography, acidolysis, hematoxylin eosin (HE) staining and immunofluorescence (IF) staining. After transcription sequencing, weighted gene co-expression network analysis (WGCNA) combined with the phenotype of the LD was used to explore the key genes and signaling pathways affecting muscle development. The results showed that 10 modules were identified by WGCNA, including 5 modules related to muscle development stage, module characteristics of muscle fiber density, 5 modules characteristic of muscle fiber diameter, and a module characteristic of palmitoleic acid (C16:1) and linoleic acid (C18:2n6C). Gene ontology (GO) enrichment analysis found that 52 transcripts relating to muscle development were enriched in these modules, including 44 known genes and 8 novel genes. The Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that these genes were enriched in the auxin, estrogen and cyclic guanosine monophosphate-protein kinase G (cGMP-PKG) pathways. Twelve of these genes were transcription factors, there were interactions among 20 genes, and the interactions among 11 proteins in human, pig and mouse were stable. To sum up, through the integrated analysis of phenotype and transcriptome, this paper analyzed the key genes and possible regulatory networks of skeletal muscle development in Ningxiang pigs at various stages, to provide a reference for the in-depth study of skeletal muscle development.

Unraveling the Genetic Foundations of Broiler Meat Quality: Advancements in Research and Their Impact

As societal progress elevates living standards, the focus on meat consumption has shifted from quantity to quality. In broiler production, optimizing meat quality has become paramount, prompting efforts to refine various meat attributes. Recent advancements in sequencing technologies have revealed the genome's complexity, surpassing previous conceptions. Through experimentation, numerous genetic elements have been linked to crucial meat quality traits in broiler chickens. This review synthesizes the current understanding of genetic determinants associated with meat quality attributes in broilers. Researchers have unveiled the pivotal insights detailed herein by employing diverse genomic methodologies such as QTL-based investigations, candidate gene studies, single-nucleotide polymorphism screening, genome-wide association studies, and RNA sequencing. These studies have identified numerous genes involved in broiler meat quality traits, including meat lightness (COL1A2 and ACAA2), meat yellowness (BCMO1 and GDPD5), fiber diameter (myostatin and LncIRS1), meat pH (PRDX4), tenderness (CAPN1), and intramuscular fat content (miR-24-3p and ANXA6). Consequently, a comprehensive exploration of these genetic elements is imperative to devise novel molecular markers and potential targets, promising to revolutionize strategies for enhancing broiler meat quality.

Transcriptome and Weighted Gene Co-Expression Network Analysis for Feather Follicle Density in a Chinese Indigenous Breed

Feather follicle density plays an important role in appealing to consumers' first impressions when making purchasing decisions. However, the molecular network that contributes to this trait remains largely unknown. The aim of this study was to perform transcriptome and weighted gene co-expression network analyses to determine the candidate genes relating to feather follicle density in Wannan male chickens. In total, five hundred one-day-old Wannan male chickens were kept in a conventional cage system. Feather follicle density was recorded for each bird at 12 weeks of age. At 12 weeks, fifteen skin tissue samples were selected for weighted gene co-expression network analysis, of which six skin tissue samples (three birds in the H group and three birds in the L group) were selected for transcriptome analysis. The results showed that, in total, 95 DEGs were identified, and 56 genes were upregulated and 39 genes were downregulated in the high-feather-follicle-density group when compared with the low-feather-follicle-density group. Thirteen co-expression gene modules were identified. The red module was highly significantly negatively correlated with feather follicle density (p < 0.01), with a significant negative correlation coefficient of -0.72. In total, 103 hub genes from the red module were screened. Upon comparing the 103 hub genes with differentially expressed genes (DEGs), it was observed that 13 genes were common to both sets, including MELK, GTSE1, CDK1, HMMR, and CENPE. From the red module, FOXM1, GTSE1, MELK, CDK1, ECT2, and NEK2 were selected as the most important genes. These genes were enriched in the DNA binding pathway, the heterocyclic compound binding pathway, the cell cycle pathway, and the oocyte meiosis pathway. This study suggests that FOXM1, GTSE1, MELK, CDK1, ECT2, and NEK2 may be involved in regulating the development of feather follicle density in Wannan male chickens. The results of this study reveal the genetic structure and molecular regulatory network of feather follicle density in Wannan male chickens, and provide a basis for further elucidating the genetic regulatory mechanism and identifying molecular markers with breeding value.