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348 results on '"Sun, Congjiao"'

3. An atlas of regulatory elements in chicken: A resource for chicken genetics and genomics

Author

Pan, Zhangyuan, Wang, Ying, Wang, Mingshan, Wang, Yuzhe, Zhu, Xiaoning, Gu, Shenwen, Zhong, Conghao, An, Liqi, Shan, Mingzhu, Damas, Joana, Halstead, Michelle M, Guan, Dailu, Trakooljul, Nares, Wimmers, Klaus, Bi, Ye, Wu, Shang, Delany, Mary E, Bai, Xuechen, Cheng, Hans H, Sun, Congjiao, Yang, Ning, Hu, Xiaoxiang, Lewin, Harris A, Fang, Lingzhao, and Zhou, Huaijun

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, Human Genome, Cancer, Biotechnology, Cancer Genomics, Generic health relevance, Animals, Chickens, Regulatory Sequences, Nucleic Acid, Genomics, Chromatin, Genome, Enhancer Elements, Genetic
Abstract

A comprehensive characterization of regulatory elements in the chicken genome across tissues will have substantial impacts on both fundamental and applied research. Here, we systematically identified and characterized regulatory elements in the chicken genome by integrating 377 genome-wide sequencing datasets from 23 adult tissues. In total, we annotated 1.57 million regulatory elements, representing 15 distinct chromatin states, and predicted about 1.2 million enhancer-gene pairs and 7662 super-enhancers. This functional annotation of the chicken genome should have wide utility on identifying regulatory elements accounting for gene regulation underlying domestication, selection, and complex trait regulation, which we explored. In short, this comprehensive atlas of regulatory elements provides the scientific community with a valuable resource for chicken genetics and genomics.

Published
2023

25. Comparative Analysis of Myofiber Characteristics, Shear Force, and Amino Acid Contents in Slow- and Fast-Growing Broilers.

Author

Gu, Shuang, Gao, Jia, Li, Zehao, Zhang, Shenbo, Wen, Chaoliang, Sun, Congjiao, Yan, Wei, Hou, Zhuocheng, Yang, Ning, and Li, Junying

Subjects
CHICKEN as food, MEAT quality, SKELETAL muscle, LIVESTOCK development, BROILER chickens, PECTORALIS muscle
Abstract

Skeletal muscle fiber characteristics are pivotal in assessing meat quality. However, there is currently a lack of research precisely quantifying the total number of myofibers (TNM) of skeletal muscles. This study used Arbor Acres (AA) broilers and Wenchang (WC) chickens to determine the TNM of several skeletal muscles and the meat quality of the pectoralis major muscle (PM). The results showed that the TNMs of the PM in AA males and females were 935,363.64 ± 92,529.28 and 873,983.72 ± 84,511.28, respectively, significantly higher than those in WC (511,468.97 ± 73,460.81 and 475,371.93 ± 70,187.83) at 7 days of age (p < 0.01). In terms of gastrocnemius medialis in AA males and females, we recorded values of 207,551.43 ± 31,639.97 and 177,203.23 ± 28,764.01, showing a significant difference compared to the values observed in WC (146,313.03 ± 29,633.21 and 124,238.9 ± 20,136.95) (p < 0.01). Similarly, the levels of gastrocnemius lateralis exhibited a significant difference between AA and WC (p < 0.01). Furthermore, the essential, umami, and sweet amino acids were found to be significantly higher in WC compared to AA (p < 0.01). These findings offer valuable data and insights for accurately quantifying the TNM in livestock and for the development of further genetic breeding strategies for meat quality. [ABSTRACT FROM AUTHOR]

Published
2024
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35. Host genetics and gut microbiota synergistically regulate feed utilization in egg-type chickens.

Author

Zhang, Wenxin, Lan, Fangren, Zhou, Qianqian, Gu, Shuang, Li, Xiaochang, Wen, Chaoliang, Yang, Ning, and Sun, Congjiao

Subjects
GENETIC testing, GENETIC variation, HENS, POULTRY industry, GENETICS, GUT microbiome
Abstract

Background: Feed efficiency is a crucial economic trait in poultry industry. Both host genetics and gut microbiota influence feed efficiency. However, the associations between gut microbiota and host genetics, as well as their combined contributions to feed efficiency in laying hens during the late laying period, remain largely unclear. Methods: In total, 686 laying hens were used for whole-genome resequencing and liver transcriptome sequencing. 16S rRNA gene sequencing was conducted on gut chyme (duodenum, jejunum, ileum, and cecum) and fecal samples from 705 individuals. Bioinformatic analysis was performed by integrating the genome, transcriptome, and microbiome to screen for key genetic variations, genes, and gut microbiota associated with feed efficiency. Results: The heritability of feed conversion ratio (FCR) and residual feed intake (RFI) was determined to be 0.28 and 0.48, respectively. The ileal and fecal microbiota accounted for 15% and 10% of the FCR variance, while the jejunal, cecal, and fecal microbiota accounted for 20%, 11%, and 10% of the RFI variance. Through SMR analysis based on summary data from liver eQTL mapping and GWAS, we further identified four protein-coding genes, SUCLA2, TNFSF13B, SERTM1, and MARVELD3, that influence feed efficiency in laying hens. The SUCLA2 and TNFSF13B genes were significantly associated with SNP 1:25664581 and SNP rs312433097, respectively. SERTM1 showed significant associations with rs730958360 and 1:33542680 and is a potential causal gene associated with the abundance of Corynebacteriaceae in feces. MARVELD3 was significantly associated with the 1:135348198 and was significantly correlated with the abundance of Enterococcus in ileum. Specifically, a lower abundance of Enterococcus in ileum and a higher abundance of Corynebacteriaceae in feces were associated with better feed efficiency. Conclusions: This study confirms that both host genetics and gut microbiota can drive variations in feed efficiency. A small portion of the gut microbiota often interacts with host genes, collectively enhancing feed efficiency. Therefore, targeting both the gut microbiota and host genetic variation by supporting more efficient taxa and selective breeding could improve feed efficiency in laying hens during the late laying period. [ABSTRACT FROM AUTHOR]

Published
2024
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48. Mechanisms of hepatic steatosis in chickens: integrated analysis of the host genome, molecular phenomics and gut microbiome

Author

Sun, Congjiao, primary, Lan, Fangren, additional, Zhou, Qianqian, additional, Guo, Xiaoli, additional, Jin, Jiaming, additional, Wen, Chaoliang, additional, Guo, Yanxin, additional, Hou, Zhuocheng, additional, Zheng, Jiangxia, additional, Wu, Guiqin, additional, Li, Guangqi, additional, Yan, Yiyuan, additional, Li, Junying, additional, Ma, Qiugang, additional, and Yang, Ning, additional

Published
2024
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