Insights into the hierarchical structure and physicochemical properties of starch isolated from fermented dough.

Understanding the hierarchical structure and physicochemical properties of starch isolated from fermented dough with different times (0-120 min) is valuable for improving the quality of fermented dough-based products. The results indicate that fermentation disrupted the starch granule surface and decreased the average particle size from 19.72 µm to 18.45 µm. Short-term fermentation (< 60 min) disrupted the crystalline, lamellar, short-range ordered molecular and helical structures of starch, while long-term fermentation (60-120 min) elevated the ordered degree of these structures. For example, relative crystallinity and double helix contents increased from 23.7 % to 26.8 % and 34.4 % to 37.2 %, respectively. During short-term fermentation, the structural amorphization facilitated interactions between starch molecular chains and water molecules, which increased the peak viscosity from 275.4 to 320.6 mPa·s and the swelling power from 7.99 to 8.52 g/g. In contrast, starches extracted from long-term fermented dough displayed the opposite results. Interestingly, the hardness and springiness of starch gels gradually decreased as fermentation time increased. These findings extend our understanding of the starch structure-property relationship during varied fermentation stages, potentially benefiting the production of better-fermented foods.

Weighted gene co-expression network analysis identified hub genes critical to fatty acid composition in Gushi chicken breast muscle.

BACKGROUND: The composition and content of fatty acids in the breast muscle are important factors influencing meat quality. In this study, we investigated the fatty acid composition and content in the breast muscle of Gushi chickens at different developmental stages (14 weeks, 22 weeks, and 30 weeks). Additionally, we utilized transcriptomic data from the same tissue and employed WGCNA and module identification methods to identify key genes associated with the fatty acid composition in Gushi chicken breast muscle and elucidate their regulatory networks. RESULTS: Among them, six modules (blue, brown, green, light yellow, purple, and red modules) showed significant correlations with fatty acid content and metabolic characteristics. Enrichment analysis revealed that these modules were involved in multiple signaling pathways related to fatty acid metabolism, including fatty acid metabolism, PPAR signaling pathway, and fatty acid biosynthesis. Through analysis of key genes, we identified 136 genes significantly associated with fatty acid phenotypic traits. Protein-protein interaction network analysis revealed that nine of these genes were closely related to fatty acid metabolism. Additionally, through correlation analysis of transcriptome data, we identified 51 key ceRNA regulatory networks, including six central genes, 7 miRNAs, and 28 lncRNAs. CONCLUSION: This study successfully identified key genes closely associated with the fatty acid composition in Gushi chicken breast muscle, as well as their post-transcriptional regulatory networks. These findings provide new insights into the molecular regulatory mechanisms underlying the flavor characteristics of chicken meat and the composition of fatty acids in the breast muscle.

Genetic architecture and key regulatory genes of fatty acid composition in Gushi chicken breast muscle determined by GWAS and WGCNA.

BACKGROUND: Fatty acids composition in poultry muscle is directly related to its tenderness, flavour, and juiciness, whereas its genetic mechanisms have not been elucidated. In this study, the genetic structure and key regulatory genes of the breast muscle fatty acid composition of local Chinese chicken, Gushi-Anka F2 resource population by integrating genome-wide association study (GWAS) and weighted gene co-expression network analysis (WGCNA) strategies. GWAS was performed based on 323,306 single nucleotide polymorphisms (SNPs) obtained by genotyping by sequencing (GBS) method and 721 chickens from the Gushi-Anka F2 resource population with highly variable fatty acid composition traits in the breast muscle. And then, according to the transcriptome data of the candidate genes that were obtained and phenotypic data of fatty acid composition traits in breast muscle of Gushi chickens at 14, 22, and 30 weeks of age, we conducted a WGCNA. RESULTS: A total of 128 suggestive significantly associated SNPs for 11 fatty acid composition traits were identified and mapped on chromosomes (Chr) 2, 3, 4, 5, 13, 17, 21, and 27. Of these, the two most significant SNPs were Chr13:5,100,140 (P = 4.56423e-10) and Chr13:5,100,173 (P = 4.56423e-10), which explained 5.6% of the phenotypic variation in polyunsaturated fatty acids (PUFA). In addition, six fatty acid composition traits, including C20:1, C22:6, saturated fatty acid (SFA), unsaturated fatty acids (UFA), PUFA, and average chain length (ACL), were located in the same QTL intervals on Chr13. We obtained 505 genes by scanning the linkage disequilibrium (LD) regions of all significant SNPs and performed a WGCNA based on the transcriptome data of the above 505 genes. Combining two strategies, 9 hub genes (ENO1, ADH1, ASAH1, ADH1C, PIK3CD, WISP1, AKT1, PANK3, and C1QTNF2) were finally identified, which could be the potential candidate genes regulating fatty acid composition traits in chicken breast muscle. CONCLUSION: The results of this study deepen our understanding of the genetic mechanisms underlying the regulation of fatty acid composition traits, which is helpful in the design of breeding strategies for the subsequent improvement of fatty acid composition in poultry muscle.

Transcriptome analysis reveals FABP5 as a key player in the development of chicken abdominal fat, regulated by miR-122-5p targeting.

BACKGROUND: The development of abdominal fat and meat quality are closely related and can impact economic efficiency. In this study, we conducted transcriptome sequencing of the abdominal fat tissue of Gushi chickens at 6, 14, 22, and 30 weeks, and selected key miRNA-mRNA regulatory networks related to abdominal fat development through correlation analysis. RESULTS: A total of 1893 differentially expressed genes were identified. Time series analysis indicated that at around 6 weeks, the development of chicken abdominal fat was extensively regulated by the TGF-ß signaling pathway, Wnt signaling pathway, and PPAR signaling pathway. However, at 30 weeks of age, the apoptosis signaling pathway was the most significant, and correlation analysis revealed several genes highly correlated with abdominal fat development, including Fatty Acid Binding Protein 5 (FABP5). Based on miRNA transcriptome data, it was discovered that miR-122-5p is a potential target miRNA for FABP5. Cell experiments showed that miR-122-5p can directly target FABP5 to promote the differentiation of preadipocytes. CONCLUSION: The present study confirms that the key gene FABP5 and its target gene miR-122-5p are critical regulatory factors in the development of chicken abdominal fat. These results provide new insights into the molecular regulatory mechanisms associated with the development of abdomen-al fat in chickens.

CircRNAs Related to Breast Muscle Development and Their Interaction Regulatory Network in Gushi Chicken.

Circular RNAs (circRNAs) play a significant regulatory role during skeletal muscle development. To identify circRNAs during postnatal skeletal muscle development in chickens, we constructed 12 cDNA libraries from breast muscle tissues of Chinese Gushi chickens at 6, 14, 22, and 30 weeks and performed RNA sequencing. In total, 2112 circRNAs were identified, and among them 79.92% were derived from exons. CircRNAs are distributed on all chromosomes of chickens, especially chromosomes 1-9 and Z. Bioinformatics analysis showed that each circRNA had an average of 38 miRNA binding sites, 61.32% of which have internal ribosomal entry site (IRES) elements. Furthermore, in total 543 differentially expressed circRNAs (DE-circRNAs) were identified. Functional enrichment analysis revealed that DE-circRNAs source genes are engaged in biological processes and muscle development-related pathways; for example, cell differentiation, sarcomere, and myofibril formation, mTOR signaling pathway, and TGF-ß signaling pathway, etc. We also established a competitive endogenous RNA (ceRNA) regulatory network associated with skeletal muscle development. The results in this report indicate that circRNAs can mediate the development of chicken skeletal muscle by means of a complex ceRNA network among circRNAs, miRNAs, genes, and pathways. The findings of this study might help increase the number of known circRNAs in skeletal muscle tissue and offer a worthwhile resource to further investigate the function of circRNAs in chicken skeletal muscle development.

Differentially Expressed lncRNAs Related to the Development of Abdominal Fat in Gushi Chickens and Their Interaction Regulatory Network.

Chickens are one of the most important sources of meat worldwide, and the growth status of abdominal fat is closely related to production efficiency. Long noncoding RNAs (lncRNAs) play an important role in lipid metabolism and deposition regulation. However, research on the expression profile of lncRNAs related to the development of abdominal fat in chickens after hatching and their interaction regulatory networks is still lacking. To characterize the lncRNA expression profile during the development of chicken abdominal fat, abdominal adipose tissues from 6-, 14-, 22-, and 30-week-old Chinese Gushi chickens were herein used to construct 12 cDNA libraries, and a total of 3,827 new lncRNAs and 5,466 previously annotated lncRNAs were revealed. At the same time, based on the comparative analysis of five combinations, 276 differentially expressed lncRNAs (DE-lncRNAs) were screened. Functional enrichment analysis showed that the predicted target genes of these DE-lncRNAs were significantly enriched in pathways related to the posttranscriptional regulation of gene expression, negative regulation of cell proliferation, cell adhesion and other biological processes, glycosphingolipid biosynthesis, PPAR signaling, fatty acid degradation, fatty acid synthesis and others. In addition, association analysis of the lncRNA transcriptome profile was performed, and DE-lncRNA-related lncRNA-mRNA, lncRNA-miRNA and lncRNA-miRNA-mRNA interaction regulatory networks were constructed. The results showed that DE-lncRNA formed a complex network with PPAR pathway components, including PPARD, ACOX1, ADIPOQ, CPT1A, FABP5, ASBG2, LPL, PLIN2 and related miRNAs, including mir-200b-3p, mir-130b-3p, mir-215-5p, mir-122-5p, mir-223 and mir-125b-5p, and played an important regulatory role in biological processes such as lipid metabolism, adipocyte proliferation and differentiation. This study described the dynamic expression profile of lncRNAs in the abdominal fat of Gushi chickens for the first time and constructed the DE-lncRNA interaction regulatory network. The results expand the number of known lncRNAs in chicken abdominal fat and provide valuable resources for further elucidating the posttranscriptional regulatory mechanism of chicken abdominal fat development or deposition.

Edge-guided second-order total generalized variation for Gaussian noise removal from depth map.

Total generalized variation models have recently demonstrated high-quality denoising capacity for single image. In this paper, we present an accurate denoising method for depth map. Our method uses a weighted second-order total generalized variational model for Gaussian noise removal. By fusing an edge indicator function into the regularization term of the second-order total generalized variational model to guide the diffusion of gradients, our method aims to use the first or second derivative to enhance the intensity of the diffusion tensor. We use the first-order primal-dual algorithm to minimize the proposed energy function and achieve high-quality denoising and edge preserving result for depth maps with high -intensity noise. Extensive quantitative and qualitative evaluations in comparison to bench-mark datasets show that the proposed method provides significant higher accuracy and visual improvements than many state-of-the-art denoising algorithms.