1
|
Yao H, Dou Z, Zhao Z, Liang X, Yue H, Ma W, Su Z, Wang Y, Hao Z, Yan H, Wu Z, Wang L, Chen G, Yang J. Transcriptome analysis of the Bactrian camel (Camelus bactrianus) reveals candidate genes affecting milk production traits. BMC Genomics 2023; 24:660. [PMID: 37919661 PMCID: PMC10621195 DOI: 10.1186/s12864-023-09703-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2023] [Accepted: 09/27/2023] [Indexed: 11/04/2023] Open
Abstract
BACKGROUND Milk production traits are complex traits with vital economic importance in the camel industry. However, the genetic mechanisms regulating milk production traits in camels remain poorly understood. Therefore, we aimed to identify candidate genes and metabolic pathways that affect milk production traits in Bactrian camels. METHODS We classified camels (fourth parity) as low- or high-yield, examined pregnant camels using B-mode ultrasonography, observed the microscopic changes in the mammary gland using hematoxylin and eosin (HE) staining, and used RNA sequencing to identify differentially expressed genes (DEGs) and pathways. RESULTS The average standard milk yield over the 300 days during parity was recorded as 470.18 ± 9.75 and 978.34 ± 3.80 kg in low- and high-performance camels, respectively. Nine female Junggar Bactrian camels were subjected to transcriptome sequencing, and 609 and 393 DEGs were identified in the low-yield vs. high-yield (WDL vs. WGH) and pregnancy versus colostrum period (RSQ vs. CRQ) comparison groups, respectively. The DEGs were compared with genes associated with milk production traits in the Animal Quantitative Trait Loci database and in Alashan Bactrian camels, and 65 and 46 overlapping candidate genes were obtained, respectively. Functional enrichment and protein-protein interaction network analyses of the DEGs and candidate genes were conducted. After comparing our results with those of other livestock studies, we identified 16 signaling pathways and 27 core candidate genes associated with maternal parturition, estrogen regulation, initiation of lactation, and milk production traits. The pathways suggest that emerged milk production involves the regulation of multiple complex metabolic and cellular developmental processes in camels. Finally, the RNA sequencing results were validated using quantitative real-time PCR; the 15 selected genes exhibited consistent expression changes. CONCLUSIONS This study identified DEGs and metabolic pathways affecting maternal parturition and milk production traits. The results provides a theoretical foundation for further research on the molecular mechanism of genes related to milk production traits in camels. Furthermore, these findings will help improve breeding strategies to achieve the desired milk yield in camels.
Collapse
Affiliation(s)
- Huaibing Yao
- Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science and Technology, Xinjiang University, 777 Huarui Street, Urumqi, 830017, Xinjiang, PR China
- Xinjiang Camel Industry Engineering Technology Research Center, Urumqi, 830017, China
| | - Zhihua Dou
- Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science and Technology, Xinjiang University, 777 Huarui Street, Urumqi, 830017, Xinjiang, PR China
- Xinjiang Camel Industry Engineering Technology Research Center, Urumqi, 830017, China
| | - Zhongkai Zhao
- Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science and Technology, Xinjiang University, 777 Huarui Street, Urumqi, 830017, Xinjiang, PR China
- Xinjiang Camel Industry Engineering Technology Research Center, Urumqi, 830017, China
| | - Xiaorui Liang
- Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science and Technology, Xinjiang University, 777 Huarui Street, Urumqi, 830017, Xinjiang, PR China
- Xinjiang Camel Industry Engineering Technology Research Center, Urumqi, 830017, China
| | - Haitao Yue
- Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science and Technology, Xinjiang University, 777 Huarui Street, Urumqi, 830017, Xinjiang, PR China
- Xinjiang Camel Industry Engineering Technology Research Center, Urumqi, 830017, China
| | - Wanpeng Ma
- College of Veterinary Medicine, Xinjiang Agricultural University, Urumqi, 830052, China
| | - Zhanqiang Su
- College of Veterinary Medicine, Xinjiang Agricultural University, Urumqi, 830052, China
| | - Yuzhuo Wang
- Xinjiang Altai Regional Animal Husbandry Veterinary Station, Altay, 836500, Xinjiang, China
| | - Zelin Hao
- Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science and Technology, Xinjiang University, 777 Huarui Street, Urumqi, 830017, Xinjiang, PR China
- Xinjiang Camel Industry Engineering Technology Research Center, Urumqi, 830017, China
| | - Hui Yan
- Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science and Technology, Xinjiang University, 777 Huarui Street, Urumqi, 830017, Xinjiang, PR China
- Xinjiang Camel Industry Engineering Technology Research Center, Urumqi, 830017, China
| | - Zhuangyuan Wu
- Xinjiang Altai Regional Animal Husbandry Veterinary Station, Altay, 836500, Xinjiang, China
| | - Liang Wang
- Xinjiang Camel Industry Engineering Technology Research Center, Urumqi, 830017, China
- Bactrian Camel Academy of Xinjiang, Xinjiang Wangyuan Camel Milk Limited Company, Altay, 836500, Xinjiang, China
| | - Gangliang Chen
- Xinjiang Camel Industry Engineering Technology Research Center, Urumqi, 830017, China
- Bactrian Camel Academy of Xinjiang, Xinjiang Wangyuan Camel Milk Limited Company, Altay, 836500, Xinjiang, China
| | - Jie Yang
- Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science and Technology, Xinjiang University, 777 Huarui Street, Urumqi, 830017, Xinjiang, PR China.
- Xinjiang Camel Industry Engineering Technology Research Center, Urumqi, 830017, China.
| |
Collapse
|
2
|
Gutiérrez-Reinoso MA, Aponte PM, García-Herreros M. Genomic and Phenotypic Udder Evaluation for Dairy Cattle Selection: A Review. Animals (Basel) 2023; 13:ani13101588. [PMID: 37238017 DOI: 10.3390/ani13101588] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 05/05/2023] [Accepted: 05/08/2023] [Indexed: 05/28/2023] Open
Abstract
The traditional point of view regarding dairy cattle selection has been challenged by recent genomic studies indicating that livestock productivity prediction can be redefined based on the evaluation of genomic and phenotypic data. Several studies that included different genomic-derived traits only indicated that interactions among them or even with conventional phenotypic evaluation criteria require further elucidation. Unfortunately, certain genomic and phenotypic-derived traits have been shown to be secondary factors influencing dairy production. Thus, these factors, as well as evaluation criteria, need to be defined. Owing to the variety of genomic and phenotypic udder-derived traits which may affect the modern dairy cow functionality and conformation, a definition of currently important traits in the broad sense is indicated. This is essential for cattle productivity and dairy sustainability. The main objective of the present review is to elucidate the possible relationships among genomic and phenotypic udder evaluation characteristics to define the most relevant traits related to selection for function and conformation in dairy cattle. This review aims to examine the potential impact of various udder-related evaluation criteria on dairy cattle productivity and explore how to mitigate the adverse effects of compromised udder conformation and functionality. Specifically, we will consider the implications for udder health, welfare, longevity, and production-derived traits. Subsequently, we will address several concerns covering the application of genomic and phenotypic evaluation criteria with emphasis on udder-related traits in dairy cattle selection as well as its evolution from origins to the present and future prospects.
Collapse
Affiliation(s)
- Miguel A Gutiérrez-Reinoso
- Carrera de Medicina Veterinaria, Facultad de Ciencias Agropecuarias y Recursos Naturales, Universidad Técnica de Cotopaxi (UTC), Latacunga 0501491, Ecuador
- Laboratorio de Biotecnología Animal, Departamento de Ciencia Animal, Facultad de Ciencias Veterinarias, Universidad de Concepción (UdeC), Chillán 3780000, Chile
| | - Pedro M Aponte
- Colegio de Ciencias Biológicas y Ambientales (COCIBA), Universidad San Francisco de Quito USFQ, Quito 170157, Ecuador
- Colegio de Ciencias de la Salud, Escuela de Medicina Veterinaria, Universidad San Francisco de Quito USFQ, Quito 170157, Ecuador
- Campus Cumbayá, Instituto de Investigaciones en Biomedicina "One-Health", Universidad San Francisco de Quito USFQ, Quito 170157, Ecuador
| | - Manuel García-Herreros
- Instituto Nacional de Investigação Agrária e Veterinária (INIAV), 2005-048 Santarém, Portugal
| |
Collapse
|
3
|
Mu T, Hu H, Ma Y, Yang C, Feng X, Wang Y, Liu J, Yu B, Zhang J, Gu Y. Identification of critical lncRNAs for milk fat metabolism in dairy cows using WGCNA and the construction of a ceRNAs network. Anim Genet 2022; 53:740-760. [PMID: 36193627 DOI: 10.1111/age.13249] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 07/26/2022] [Accepted: 08/02/2022] [Indexed: 11/27/2022]
Abstract
As key regulators, long non-coding RNAs (lncRNAs) play a crucial role in the ruminant mammary gland. However, the function of lncRNAs in milk fat synthesis from dairy cows is largely unknown. In this study, we used the weighted gene co-expression network analysis (WGCNA) to comprehensive analyze the expression profile data of lncRNAs from the group's previous Illumina PE150 sequencing results based on bovine mammary epithelial cells from high- and low-milk-fat-percentage (MFP) cows, and identify core_lncRNAs significantly associated with MFP by module membership (MM) and gene significance (GS). Functional enrichment analysis (Gene Ontology, Kyoto Encyclopedia of Genes and Genomes) of core_lncRNA target genes (co-localization and co-expression) was performed to screen potential lncRNAs regulating milk fat metabolism and further construct an interactive regulatory network of lipid metabolism-related competing endogenous RNAs (ceRNAs). A total of 4876 lncRNAs were used to construct the WGCNA. The MEdarkturquoise module among the 19 modules obtained was significantly associated with MFP (r = 0.78, p-value <0.05) and contained 64 core_lncRNAs (MM > 0.8, GS > 0.4). Twenty-four lipid metabolism-related lncRNAs were identified by core_lncRNA target gene enrichment analysis. TCONS_00054233, TCONS_00152292, TCONS_00048619, TCONS_00033839, TCONS_00153791 and TCONS_00074642 were key candidate lncRNAs for regulating milk fat synthesis. The 22 ceRNAs most likely to be involved in milk fat metabolism were constructed by interaction network analysis, and TCONS_00133813 and bta-miR-2454-5p were located at the network's core. TCONS_00133813_bta-miR-2454-5p_TNFAIP3, TCONS_00133813_bta-miR-2454-5p_ARRB1 and TCONS_00133813_bta-miR-2454-5p_PIK3R1 are key candidate ceRNAs associated with milk fat metabolism. This study provides a framework for the co-expression module of MFP-related lncRNAs in ruminants, identifies several major lncRNAs and ceRNAs that influence milk fat synthesis, and provides a new understanding of the complex biology of milk fat synthesis in dairy cows.
Collapse
Affiliation(s)
- Tong Mu
- School of Agriculture, Ningxia University, Yinchuan, China
| | - Honghong Hu
- School of Agriculture, Ningxia University, Yinchuan, China
| | - Yanfen Ma
- School of Agriculture, Ningxia University, Yinchuan, China.,Key Laboratory of Ruminant Molecular and Cellular Breeding, Ningxia University, Yinchuan, China
| | - Chaoyun Yang
- School of Agriculture, Ningxia University, Yinchuan, China
| | - Xiaofang Feng
- School of Agriculture, Ningxia University, Yinchuan, China
| | - Ying Wang
- School of Agriculture, Ningxia University, Yinchuan, China
| | - Jiamin Liu
- School of Agriculture, Ningxia University, Yinchuan, China
| | - Baojun Yu
- School of Agriculture, Ningxia University, Yinchuan, China
| | - Juan Zhang
- School of Agriculture, Ningxia University, Yinchuan, China
| | - Yaling Gu
- School of Agriculture, Ningxia University, Yinchuan, China
| |
Collapse
|