Integrative analysis of transcriptomics and proteomics of longissimus thoracis of the Hu sheep compared with the Dorper sheep

Characterization and discrimination of lamb with different breeds and muscle types using precursors and volatile compounds

The unique aromas of mutton stem from the chemical reactions between the characteristic precursors during cooking. This study aimed to establish the relationship of volatile compounds and aroma precursors (protein, fat, free amino acids and fatty acids) in lamb from different breeds and muscle types. Hong lamb was characterized by greater tenderness and water holding capacity, higher polyunsaturated fatty acids and higher essential/non-essential amino acids in comparison with Hu lamb. Aldehydes, such as heptanal, hexanal, octanal and nonanal were higher in Hong-ST compared with Hu-ST. Principal component analysis (PCA) showed that aroma precursors were closely related to volatile components of cooked lamb. Discriminant analysis results showed that precursors and volatile compounds could be used to identify the breeds and muscle types of lamb. These findings revealed the contributors of lamb aroma and might help understand the regulatory mechanism of aroma in lamb from different breeds and muscle types.

Exploring the impact of irradiation on the sensory quality of pork based on a metabolomics approach

The effects of irradiation on pork quality characteristics were investigated by combining sensory experiments, pork color, TBARS, volatile components, and differential metabolites. Pork irradiated at a dose of 1 kGy received the highest sensory scores, whereas pork irradiated at doses of 3 and 5 kGy obtained lower sensory scores, particularly with regard to odor. Irradiation makes pork more ruddy and promotes fat oxidation, leading to increased a* and TBARS values. The main volatile substances in irradiated pork were hydrocarbons, aldehydes, and alcohols, and hexanal, heptanal, and valeric acid were considered as important substances responsible for the generation of radiation-induced off-flavors. 65 differential metabolites were identified. l-pyroglutamic acid, l-glutamate, l-proline, fumarate acids, betaine, and l-anserine were considered as the main substances contributing to the differences in pork quality. In addition, metabolic pathways such as arginine biosynthesis, alanine, aspartate and glutamate metabolism were found to be considerably affected by irradiation.

Multiomics analyses of Jining Grey goat and Boer goat reveal genomic regions associated with fatty acid and amino acid metabolism and muscle development

OBJECTIVE

Jining Grey goat is a local Chinese goat breed that is well known for its high fertility and excellent meat quality but shows low meat production performance. Numerous studies have focused on revealing the genetic mechanism of its high fertility, but its highlighting meat quality and muscle growth mechanism still need to be studied.

METHODS

In this research, an integrative analysis of the genomics and transcriptomics of Jining Grey goats compared with Boer goats was performed to identify candidate genes and pathways related to the mechanisms of meat quality and muscle development.

RESULTS

Our results overlap among five genes (ABHD2, FN1, PGM2L1, PRKAG3, RAVER2) and detected a set of candidate genes associated with fatty acid metabolism (PRKAG3, HADHB, FASN, ACADM), amino acid metabolism (KMT2C, PLOD3, NSD2, SETDB1, STT3B, MAN1A2, BCKDHB, NAT8L, P4HA3) and muscle development (MSTN, PPARGC1A, ANKRD2). Several pathways have also been detected, such as the FoxO signaling pathway and Apelin signaling pathway that play roles in lipid metabolism, lysine degradation, N-glycan biosynthesis, valine, leucine and isoleucine degradation that involving with amino acid metabolism.

CONCLUSION

The comparative genomic and transcriptomic analysis of Jining Grey goat and Boer goat revealed the mechanisms underlying the meat quality and meat productive performance of goats. These results provide valuable information for future breeding of goats.

Identification of potential tissue-specific biomarkers involved in pig fat deposition through integrated bioinformatics analysis and machine learning

Backfat thickness (BT) and intramuscular fat (IMF) content are closely appertained to meat production and quality in pig production. Deposition in subcutaneous adipose (SA) and IMF concerns different genes and regulatory mechanisms. And larger studies with rigorous design should be carried to explore the molecular regulation of fat deposition in different tissues. The purpose of this study is to gain a better understanding of the molecular mechanisms underlying differences in fat deposition among different tissues and identify tissue-specific genes involved in regulating fat deposition. The SA-associated datasets (GSE122349 and GSE145956) and IMF-associated datasets (GSE165613 and GSE207279) were downloaded from the Gene Expression Omnibus (GEO) as the BT and IMF group, respectively. Subsequently, the Robust Rank Aggregation (RRA) algorithm identified 27 down- and 29 up-regulated differentially expressed genes (DEGs) in the BT group. Based on bioinformatics and three machine learning algorithms, four SA deposition-related potential biomarkers, namely ACLY, FASN, ME1, and ARVCF were selected. FASN was evaluated as the most valuable biomarker for the SA mechanism. The 18 down- and 34 up-regulated DEGs in the IMF group were identified, and ACTA2 and HMGCL were screened as the IMF deposition-related candidate core genes, especially the ACTA2 may play the critical role in IMF deposition regulation. Moreover, based on the constructed ceRNA network, we postulated that the role of predicted ceRNA interaction network of XIST, NEAT1/miR-15a-5p, miR-16-5p, miR-424-5p, miR-497-5p/FASN were vital in the SA metabolism, XIST, NEAT1/miR-27a/b-3p, 181a/c-5p/ACTA2 might contribute to the regulation to IMF metabolism, which all gave suggestions in molecular mechanism for regulation of fat deposition. These findings may facilitate advancements in porcine quality at the genetic and molecular levels and assist with human obesity-associated diseases.

Whole-genome resequencing of Hu sheep identifies candidate genes associated with agronomic traits

The phenotypic diversity resulting from artificial or natural selection of sheep has made a significant contribution to human civilization. Hu sheep are a local sheep breed unique to China with high reproductive rates and rapid growth. Genomic selection signatures have been widely used to investigate the genetic mechanisms underlying phenotypic variation in livestock. Here, we conduct whole-genome sequencing of 207 Hu sheep and compare them with the wild ancestors of domestic sheep (Asiatic mouflon) to investigate the genetic characteristics and selection signatures of Hu sheep. Based on six signatures of selection approaches, we detect genomic regions containing genes related to reproduction (BMPR1B, BMP2, PGFS, CYP19, CAMK4, GGT5, and GNAQ), vision (ALDH1A2, SAG, and PDE6B), nervous system (NAV1), and immune response (GPR35, SH2B2, PIK3R3, and HRAS). Association analysis with a population of 1299 Hu sheep reveal those missense mutations in the GPR35 (GPR35 g.952651 A>G; GPR35 g.952496 C>T) and NAV1 (NAV1 g.84216190 C>T; NAV1 g.84227412 G>A) genes are significantly associated (P < 0.05) with immune and growth traits in Hu sheep, respectively. This research offers unique insights into the selection characteristics of Hu sheep and facilitates further genetic improvement and molecular investigations.

Integrated Transcriptome and Proteome Analyses of β-Conglycinin-Induced Intestinal Damage in Piglets

β-conglycinin (β-CG) induces intestinal damage in piglets; however, its regulatory mechanisms are not fully understood. This study aimed to investigate the molecular mechanisms by which β-CG regulates intestinal injury in piglets through downstream genes and proteins. Our findings revealed that β-CG significantly reduced villus height while increasing the crypt depth. In addition, we analyzed the transcriptome and proteome of jejunum tissues after the β-CG treatment. In total, 382 differentially expressed genes (DEGs) and 292 differentially expressed proteins (DEPs) were identified between the treatment and the control groups. The expression levels of DEGs and DEPs were validated by using quantitative reverse transcription polymerase chain reaction (qRT-PCR) and Western blotting, respectively. The findings revealed a consistent correlation between their expression levels and transcriptomic and proteomic data. In addition, Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of DEGs and DEPs revealed their enrichment in oxidation-related GOs, as well as in lysosome-related pathways. A protein-protein interaction (PPI) regulatory network was constructed based on the DEPs. The integration of transcriptomic and proteomic analyses identified six genes that were significantly different at both the transcript and the protein levels. This study provides valuable insights into the molecular mechanisms underlying β-CG-induced intestinal injury in piglets.

Pan-Omics in Sheep: Unveiling Genetic Landscapes

Multi-omics-integrated analysis, known as panomics, represents an advanced methodology that harnesses various high-throughput technologies encompassing genomics, epigenomics, transcriptomics, proteomics, and metabolomics. Sheep, playing a pivotal role in agricultural sectors due to their substantial economic importance, have witnessed remarkable advancements in genetic breeding through the amalgamation of multiomics analyses, particularly with the evolution of high-throughput technologies. This integrative approach has established a robust theoretical foundation, enabling a deeper understanding of sheep genetics and fostering improvements in breeding strategies. The comprehensive insights obtained through this approach shed light on diverse facets of sheep development, including growth, reproduction, disease resistance, and the quality of livestock products. This review primarily focuses on the application of principal omics analysis technologies in sheep, emphasizing correlation studies between multiomics data and specific traits such as meat quality, wool characteristics, and reproductive features. Additionally, this paper anticipates forthcoming trends and potential developments in this field.

A Role of Multi-Omics Technologies in Sheep and Goat Meats: Progress and Way Ahead

Sheep and goat meats are increasingly popular worldwide due to their superior nutritional properties and distinctive flavor profiles. In recent decades, substantial progress in meat science has facilitated in-depth examinations of ovine and caprine muscle development during the antemortem phase, as well as post-mortem changes influencing meat attributes. To elucidate the intrinsic molecular mechanisms and identify potential biomarkers associated with meat quality, the methodologies employed have evolved from traditional physicochemical parameters (such as color, tenderness, water holding capacity, flavor, and pH) to some cutting-edge omics technologies, including transcriptomics, proteomics, and metabolomics approaches. This review provides a comprehensive analysis of multi-omics techniques and their applications in unraveling sheep and goat meat quality attributes. In addition, the challenges and future perspectives associated with implementing multi-omics technologies in this area of study are discussed. Multi-omics tools can contribute to deciphering the molecular mechanism responsible for the altered the meat quality of sheep and goats across transcriptomic, proteomic, and metabolomic dimensions. The application of multi-omics technologies holds great potential in exploring and identifying biomarkers for meat quality and quality control, thereby promoting the optimization of production processes in the sheep and goat meat industry.

Transcriptomics and metabolomics reveal improved performance of Hu sheep on hybridization with Southdown sheep

Consumers are increasingly demanding high-quality mutton. Cross breeding can improve meat quality and is widely used in sheep breeding. However, little is known about the molecular mechanism of cross breeding sheep meat quality. In this study, male Southdown and female Hu sheep were hybridized. The slaughter performance and longissimus dorsi quality of the 6-month-old hybrid offspring were measured, and the longissimus dorsi of the hybrid offspring was analyzed by transcriptomics and metabolomics to explore the effect of cross breeding on meat quality. The results showed that the production performance of Southdown × Hu F1 sheep was significantly improved, the carcass fat content was significantly decreased, and the eating quality of Southdown × Hu F1 sheep were better. Compared with the HS group (Hu × Hu), the NH group (Southdown × Hu) had 538 differentially expressed genes and 166 differentially expressed metabolites (P < 0.05), which were significantly enriched in amino acid metabolism and other related pathways. Up-regulated genes METTL21C, PPARGC1A and down-regulated gene WFIKKN2 are related to muscle growth and development. Among them, the METTL21C gene, which is related to muscle development, was highly correlated with carnosine, a metabolite related to meat quality (correlation > 0.6 and P < 0.05). Our results provide further understanding of the molecular mechanism of cross breeding for sheep muscle growth and meat quality optimization.

Multi-Omics Approaches to Improve Meat Quality and Taste Characteristics

With rapid advances in meat science in recent decades, changes in meat quality during the pre-slaughter phase of muscle growth and the post-slaughter process from muscle to meat have been investigated. Commonly used techniques have evolved from early physicochemical indicators such as meat color, tenderness, water holding capacity, flavor, and pH to various omic tools such as genomics, transcriptomics, proteomics, and metabolomics to explore fundamental molecular mechanisms and screen biomarkers related to meat quality and taste characteristics. This review highlights the application of omics and integrated multi-omics in meat quality and taste characteristics studies. It also discusses challenges and future perspectives of multi-omics technology to improve meat quality and taste. Consequently, multi-omics techniques can elucidate the molecular mechanisms responsible for changes of meat quality at transcriptome, proteome, and metabolome levels. In addition, the application of multi-omics technology has great potential for exploring and identifying biomarkers for meat quality and quality control that can make it easier to optimize production processes in the meat industry.

First insights into the dynamic protein changes in goat Semitendinosus muscle during the post-mortem period using high-throughput proteomics

Proteomics plays a key and insightful role in meat research in the post-genomic era. This study aimed to unveil using a shotgun proteomics approach the temporal dynamic changes in early post-mortem proteome of goat Semitendinosus muscle. Therefore, the evolution and comparison of the muscle proteome over three post-mortem times (1, 8, and 24 h) was assessed. The temporal proteomics profiling quantified 748 proteins, from which 174 were differentially abundant (DAPs): n = 55 between 1 h versus 8 h, n = 52 between 8 h versus 24 h, and n = 154 between 1 h versus 24 h. The DAPs belong to myriad interconnected pathways. Binding, transport and calcium homeostasis, as well as muscle contraction and structure, exhibited an equivalent contribution during post-mortem, demonstrating their central role. Catalytic, metabolism and ATP metabolic process, and proteolysis were active pathways from the first hours of animal bleeding. Conversely, oxidative stress, response to hypoxia and cell redox homeostasis along chaperones and heat shock proteins accounted for the large proportion of the biochemical processes, more importantly after 8 h post-mortem. Overall, the conversion of muscle into meat is largely orchestrated by energy production as well as mitochondrial metabolism and homeostasis through calcium and permeability transition regulation. The study further evidenced the role of ribosomal proteins in goat post-mortem muscle, signifying that several proteins experiencing changes during storage, also undergo splicing modifications, which is for instance a mechanism known for mitochondrial proteins. Overall, temporal proteomics profiling of early post-mortem muscle proteome offers an unparalleled view of the sophisticated post-mortem biochemical and proteolytic events associated with goat meat quality determination.

Integrative Proteomics and Transcriptomics Profiles of the Oviduct Reveal the Prolificacy-Related Candidate Biomarkers of Goats (Capra hircus) in Estrous Periods

The oviduct is a dynamic reproductive organ for mammalian reproduction and is required for gamete storage, maturation, fertilization, and early embryonic development, and it directly affects fecundity. However, the molecular regulation of prolificacy occurring in estrous periods remain poorly understood. This study aims to gain a better understanding of the genes involved in regulating goat fecundity in the proteome and transcriptome levels of the oviducts. Twenty female Yunshang black goats (between 2 and 3 years old, weight 52.22 ± 0.43 kg) were divided into high- and low-fecundity groups in the follicular (FH and FL, five individuals per group) and luteal (LH and LL, five individuals per group) phases, respectively. The DIA-based high-resolution mass spectrometry (MS) method was used to quantify proteins in twenty oviducts. A total of 5409 proteins were quantified, and Weighted gene co-expression network analysis (WGCNA) determined that the tan module was highly associated with the high-fecundity trait in the luteal phase, and identified NUP107, ANXA11, COX2, AKP13, and ITF140 as hub proteins. Subsequently, 98 and 167 differentially abundant proteins (DAPs) were identified in the FH vs. FL and LH vs. LL comparison groups, respectively. Parallel reaction monitoring (PRM) was used to validate the results of the proteomics data, and the hub proteins were analyzed with Western blot (WB). In addition, biological adhesion and transporter activity processes were associated with oviductal function, and several proteins that play roles in oviductal communication with gametes or embryos were identified, including CAMSAP3, ITGAM, SYVN1, EMG1, ND5, RING1, CBS, PES1, ELP3, SEC24C, SPP1, and HSPA8. Correlation analysis of proteomics and transcriptomic revealed that the DAPs and differentially expressed genes (DEGs) are commonly involved in the metabolic processes at the follicular phase; they may prepare the oviductal microenvironment for gamete reception; and the MAP kinase activity, estrogen receptor binding, and angiotensin receptor binding terms were enriched in the luteal phase, which may be actively involved in reproductive processes. By generating the proteome data of the oviduct at two critical phases and integrating transcriptome analysis, we uncovered novel aspects of oviductal gene regulation of fecundity and provided a reference for other mammals.