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Diao X, Yao L, Duan T, Qin J, He L, Zhang W. Melatonin promotes the development of the secondary hair follicles by regulating circMPP5. J Anim Sci Biotechnol 2023; 14:51. [PMID: 37024982 PMCID: PMC10080870 DOI: 10.1186/s40104-023-00849-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Accepted: 02/05/2023] [Indexed: 04/08/2023] Open
Abstract
BACKGROUND The quality and yield of cashmere fibre are closely related to the differentiation and development of secondary hair follicles in the skin of cashmere goats. The higher the density of secondary hair follicles, the higher the quality and yield of cashmere from the fleece. Development of secondary hair follicles commences in the embryonic stage of life and is completed 6 months after birth. Preliminary experimental results from our laboratory showed that melatonin (MT) treatment of goat kids after their birth could increase the density of secondary hair follicles and, thus, improve the subsequent yield and quality of cashmere. These changes in the secondary hair follicles resulted from increases in levels of antioxidant and expression of anti-apoptotic protein, and from a reduction in apoptosis. The present study was conducted to explore the molecular mechanism of MT-induced secondary hair follicle differentiation and development by using whole-genome analysis. RESULTS MT had no adverse effect on the growth performance of cashmere kids but significantly improved the character of the secondary hair follicles and the quality of cashmere, and this dominant effect continued to the second year. Melatonin promotes the proliferation of secondary hair follicle cells at an early age. The formation of secondary hair follicles in the MT group was earlier than that in the control group in the second year. The genome-wide data results involved KEGG analysis of 1044 DEmRNAs, 91 DElncRNAs, 1054 DEcircRNAs, and 61 DEmiRNAs which revealed that the mitogen-activated protein kinase (MAPK) signaling pathway is involved in the development of secondary hair follicles, with key genes (FGF2, FGF21, FGFR3, MAPK3 (ERK1)) being up-regulated and expressed. We also found that the circMPP5 could sponged miR-211 and regulate the expression of MAPK3. CONCLUSIONS We conclude that MT achieves its effects by regulating the MAPK pathway through the circMPP5 sponged the miR-211, regulating the expression of MAPK3, to induce the differentiation and proliferation of secondary hair follicle cells. In addition there is up-regulation of expression of the anti-apoptotic protein causing reduced apoptosis of hair follicle cells. Collectively, these events increase the numbers of secondary hair follicles, thus improving the production of cashmere from these goats.
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Affiliation(s)
- Xiaogao Diao
- Department of Animal Nutrition and Feed Science, State Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Lingyun Yao
- Department of Animal Nutrition and Feed Science, State Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Tao Duan
- Department of Animal Nutrition and Feed Science, State Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Jiaxin Qin
- Department of Animal Nutrition and Feed Science, State Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Liwen He
- Department of Animal Nutrition and Feed Science, State Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Wei Zhang
- Department of Animal Nutrition and Feed Science, State Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
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Trujano-Chavez MZ, Ruíz-Flores A, López-Ordaz R, Pérez-Rodríguez P. Genetic diversity in reproductive traits of Braunvieh cattle determined with SNP markers. Vet Med Sci 2022; 8:1709-1720. [PMID: 35545927 PMCID: PMC9297803 DOI: 10.1002/vms3.836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Braunvieh is an important dual‐purpose breed in the Mexican tropics. The study of its genetic diversity is key to implementing genetic improvement programs. This study was conducted to determine genetic diversity of reproductive traits in a Mexican Braunvieh beef cattle population using single nucleotide polymorphisms in candidate genes. Information from 24 genes with 52 intra‐genic loci reported in literature to be associated with productive life, pregnancy rate and cow and heifer conception rate of 150 Braunvieh males and females was considered. Observed heterozygosity (Ho) revealed high genetic diversity for the studied traits, Ho = 0.42 ± 0.087, relative to that of other populations of the same breed. Cluster analyses were carried out using the Ward and K‐means algorithms. These analyses revealed high genetic diversity that was observed in the biplot of non‐metric multi‐dimensional scaling. It was found that clustering strategy allowed visualisation of distant groups by genotype but not by favourable alleles in all the loci. We found that the genes CSNK1E, DNAH11, DSC2, IBSP and OCLN affected most of the traits in our study and they were highly informative. Therefore, they represent a potential resource for selection and crossbreeding programs of the traits studied in Braunvieh. The analyses showed that the Mexican Braunvieh population has a high level of genetic diversity, arguably due to decades‐long adaptation to the Mexican tropics.
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Affiliation(s)
| | - Agustín Ruíz-Flores
- Posgrado en Producción Animal, Universidad Autónoma Chapingo, Texcoco, Estado de México, Mexico
| | - Rufino López-Ordaz
- Posgrado en Producción Animal, Universidad Autónoma Chapingo, Texcoco, Estado de México, Mexico
| | - Paulino Pérez-Rodríguez
- Socio Economía Estadística e Informática, Posgrado en Producción Animal, Texcoco, Estado de México, Mexico
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3
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Hu L, Yu J, Huang R, Yang P, Zhang Z, Chai Y, Shi Q, Chen F, Liu X, Li Z, Ru B, Wang E, Lei C, Peng W, Huang Y. Copy number variation of the CCDC39 gene is associated with growth traits in Chinese cattle. Vet Med Sci 2022; 8:917-924. [PMID: 35233959 PMCID: PMC8959325 DOI: 10.1002/vms3.712] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Background Copy number variation (CNV) has become an essential part of genetic structural variation. Coiled‐coil domain containing 39 (CCDC39) is a gene that related to the growth and development of organs and tissues. It is identified that it has a CNV region by animal genome resequencing. Objective In this study, we detected the phenotypic traits and different distributions of CCDC39 gene copy numbers in five Chinese cattle breeds (Qinchuan (QC) cattle, Yunling (YL) cattle, Xianan (XN) cattle, Pinan (PN) cattle and Jiaxian (JX) cattle). Methods Five hundred and six cattle were randomly selected for CNV distribution detection. Blood samples were taken and genomic DNA was extracted. Different tissues were obtained from adult (n = 3) XN cattle, including heart, liver, kidney, skeletal muscle and lung. The genome qPCR experiment was performed with SYBR Green in triplicate. CDNA qPCR was used to detect the expression level of CCDC39 in different tissues and varieties. Using SPSS v20.0 software, the relationship between CCDC39 CNV and the growth traits of PN, XN, QC, NY and YL cattle breeds was analyzed by one‐way analysis of variance (ANOVA). Results The results showed that the expression of CCDC39 in lung was higher than that in other tissues. The expression in liver and kidney was similar, but the expression in heart and muscle was less. It can be seen that the duplication type of QC cattle CCDC39 CNV is higher than the deletion or normal in the height at hip cross. The normal type of PN cattle in body length and hip width was better than duplication and deletion (p < 0.05). In XN cattle, the deletion type of CNV had superior growth characteristics in heart girth and cannon bone circumference compared with the duplication type and the normal type (p < 0.05). Conclusion The study revealed a significant association between CNV of CCDC39 gene and growth traits in different Chinese cattle breeds.
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Affiliation(s)
- Linyong Hu
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, Qinghai, People's Republic of China
| | - Junjian Yu
- College of Animal Science and Technology, Northwest A&F University, Yangling, Qinghai, People's Republic of China
| | - Rong Huang
- Qinghai Academy of Animal Science and Veterinary Medicine, Qinghai University, Xining, Qinghai, People's Republic of China
| | - Peng Yang
- College of Animal Science and Technology, Northwest A&F University, Yangling, Qinghai, People's Republic of China
| | - Zijing Zhang
- Institute of Animal Husbandry and Veterinary Science, Henan Academy of Agricultural Sciences, Zhengzhou, Henan, People's Republic of China
| | - Yanan Chai
- Institute of Animal Husbandry and Veterinary Science, Henan Academy of Agricultural Sciences, Zhengzhou, Henan, People's Republic of China
| | - Qiaoting Shi
- Institute of Animal Husbandry and Veterinary Science, Henan Academy of Agricultural Sciences, Zhengzhou, Henan, People's Republic of China
| | - Fuying Chen
- Institute of Animal Husbandry and Veterinary Science, Henan Academy of Agricultural Sciences, Zhengzhou, Henan, People's Republic of China
| | - Xian Liu
- Henan Provincial Animal Husbandry General Station, Zhengzhou, Henan, People's Republic of China
| | - Zhiming Li
- Henan Provincial Animal Husbandry General Station, Zhengzhou, Henan, People's Republic of China
| | - Baorui Ru
- Henan Provincial Animal Husbandry General Station, Zhengzhou, Henan, People's Republic of China
| | - Eryao Wang
- Institute of Animal Husbandry and Veterinary Science, Henan Academy of Agricultural Sciences, Zhengzhou, Henan, People's Republic of China
| | - Chuzhao Lei
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, Qinghai, People's Republic of China
| | - Wei Peng
- Qinghai Academy of Animal Science and Veterinary Medicine, Qinghai University, Xining, Qinghai, People's Republic of China
| | - Yongzhen Huang
- College of Animal Science and Technology, Northwest A&F University, Yangling, Qinghai, People's Republic of China
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Abd El Fattah EM, Behour TS, Ashour AF, Amin AMS. Association analysis of prolactin and prolactin receptor genes with selected productive and reproductive traits in Egyptian buffalo. Anim Biotechnol 2022:1-9. [PMID: 35148254 DOI: 10.1080/10495398.2022.2028160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]
Abstract
A total of 266 records of buffalo raised in two experimental herds in Egypt were assessed to detect prolactin (PRL) and prolactin receptor (PRLR) genes' polymorphism using PCR-Single Strand Conformational Polymorphism (SSCP) and PCR-Restricted Fragment Length Polymorphism (RFLP) techniques as well as to investigate their association with calf birth weight (BW), weaning weight (WW), lactation period (LP), total milk yield (TMY), stillbirth, calving ease (CE), gestation length (GL), postpartum interval to pregnancy (PPIP), calving interval (CI), and age at first calving (AFC). Predicted breeding values were estimated and used in the association with detected genotypes. A monomorphic pattern of the studied PRL 156 bp segment was recorded and absence of its polymorphism in buffalo was corroborated. We also determined polymorphism of PRLR reflected in three loci: PRLR2, PRLR4, and PRLR9. Significant differences among PRLP9 genotypes (AA, AB, and BB) were displayed for all studied traits as well as among PRLR2 genotypes, except for CE, while PRLR4 genotypes significantly differed only in BW, WW, TMY, stillbirth, GL, and AFC. In practice, strong associations among genotypes of the PRLR gene and the traits of interest candidate this gene to be selective in Egyptian buffalo breeding for improving both productive and reproductive traits.
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Affiliation(s)
- Eman Mohamed Abd El Fattah
- Animal Reproduction Research Institute (ARRI), Agricultural Research Center, Ministry of Agriculture and Land Reclamation, Giza, Egypt
| | - Tahani Salama Behour
- Animal Reproduction Research Institute (ARRI), Agricultural Research Center, Ministry of Agriculture and Land Reclamation, Giza, Egypt
| | - Ayman Fouad Ashour
- Animal Production Research Institute (APRI), Agricultural Research Center, Ministry of Agriculture and Land Reclamation, Dokki, Giza, Egypt
| | - Amin Mohamed Said Amin
- Animal Production Research Institute (APRI), Agricultural Research Center, Ministry of Agriculture and Land Reclamation, Dokki, Giza, Egypt
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Guo S, Bai Y, Zhang Q, Zhang H, Fan Y, Han H, Liu Y. Associations of CALM1 and DRD1 polymorphisms, and their expression levels, with Taihang chicken egg-production traits. Anim Biotechnol 2021:1-11. [PMID: 34890302 DOI: 10.1080/10495398.2021.2008948] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Egg production by hens is an important reproductive performance index in the poultry industry. To investigate the effects of the CALM1 and DRD1 genes on egg production in chicken, their mRNA expression and single nucleotide polymorphisms (SNP) levels were investigated, and bioinformatics and egg-production association analyses were performed. Three SNPs (g.44069941G > A and g.44069889A > G in CALM1 and g.10742639C > T in DRD1) were detected in the exons and introns of CALM1 and DRD1 in 400 Taihang chickens. Among them, g.44069941G > A was significantly associated with Taihang chicken egg production on the 500th day (p < 0.05), whereas g.10742639C > T was significantly associated with the 300th day (p < 0.05). The expression levels of CALM1 and DRD1 in ovarian tissues of a high-yielding Taihang group were greater than in a low-yielding group (p < 0.05). The bioinformatics analysis revealed that the mutations influenced the mRNA secondary structures of CALM1 and DRD1. This study provides new insights into the potential effects of CALM1 and DRD1 polymorphisms on chicken egg production. The two SNPs g.44069941G > A and g.10742639C > T are potential molecular markers for improving the reproductive traits of Taihang chicken.
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Affiliation(s)
- Siwu Guo
- College of Life Sciences and Food Engineering, Hebei University of Engineering, Handan, China
| | - Ying Bai
- College of Life Sciences and Food Engineering, Hebei University of Engineering, Handan, China
| | - Qingyang Zhang
- College of Life Sciences and Food Engineering, Hebei University of Engineering, Handan, China
| | - Hui Zhang
- College of Life Sciences and Food Engineering, Hebei University of Engineering, Handan, China
| | - Yekai Fan
- College of Life Sciences and Food Engineering, Hebei University of Engineering, Handan, China
| | - Haiyin Han
- College of Life Sciences and Food Engineering, Hebei University of Engineering, Handan, China
| | - Yufang Liu
- College of Life Sciences and Food Engineering, Hebei University of Engineering, Handan, China
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Parasar P, Bhushan B, Panigrahi M, Kumar H, Kaisa K, Dutt T. Characterization of BoLA class II DQA and DQB by PCR-RFLP, cloning, and sequencing reveals sequence diversity in crossbred cattle. Anim Biotechnol 2021:1-11. [PMID: 34813716 DOI: 10.1080/10495398.2021.2006205] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
The BoLA class II DQA and DQB genes in crossbred cattle were studied using PCR-RFLP, cloning, and sequencing techniques. Seventy-two crossbred cattle (Vrindavani) were used in the current study. HaeIII and XbaI restriction enzymes digested DQA exon 2-3, revealing seven (HaeIII-A-G) and three (XbaI A-C) motifs, respectively. The BoLA-DQB gene was analyzed using PCR-RFLP with PstI and TaqI restriction enzymes, yielding five restriction motifs for each restriction enzyme (PstI-A-E and TaqI-A-E). In crossbred cattle, addition, deletion, and substitutions were observed in distinct sequences, resulting in variations in overall gene length. Changes in nucleotides at positions 64-80, 110-200, and 207-264 were largely responsible for polymorphism in DQA exon 2. The phylogenetic analysis predicted a high degree of nucleotide and amino acid changes in DQA exon 2-3 and DQB exon 2. DQA genes had a nucleotide dissimilarity of 0.3-25.4 percent, while DQB genes had a nucleotide dissimilarity of 1.5-14.3 percent. We cloned and sequenced 20 genotypes based on PCR-RFLP of the DQA and DQB genes. The current study observed variation in the DQA and DQB genes and will serve as a foundation for future research on the BoLA DQA and DQB genes.
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Affiliation(s)
- Parveen Parasar
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Bareilly, Uttar Pradesh, India
| | - Bharat Bhushan
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Bareilly, Uttar Pradesh, India
| | - Manjit Panigrahi
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Bareilly, Uttar Pradesh, India
| | - Harshit Kumar
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Bareilly, Uttar Pradesh, India
| | - Kaiho Kaisa
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Bareilly, Uttar Pradesh, India
| | - Triveni Dutt
- Livestock Production and Management Section, ICAR-Indian Veterinary Research Institute, Bareilly, Uttar Pradesh, India
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Yi X, He S, Wang S, Zhao H, Wu M, Liu S, Pan Y, Zhang Y, Sun X. Expression of different genotypes of bovine TRDMT1 gene and its polymorphisms association with body measures in Qinchuan cattle (Bos Taurus). Anim Biotechnol 2021:1-11. [PMID: 34629027 DOI: 10.1080/10495398.2021.1984248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
DNA methyltransferase 2 (DNMT2) was renamed as tRNA aspartic acid methyltransferase 1 (TRDMT1) by catalyzing the methylation of tRNAAsp anti-codon loop C38. The development of sequencing of nucleic acids and protein detection techniques have prompted the demonstration that TRDMT1 mediated tRNA modification affects protein synthesis efficiency. This process affects the growth and development of animals. The DNA of 224 Qinchuan cattles aged 2-4 years old was collected in this experiment. The genetic variations of TRDMT1 exon and some intron regions were detected by mixed pool sequencing technology. qRT-PCR and Western Blot were used to detect the expression levels of mRNA and protein produced with the combination of different genetic variant loci. Three haplotypes were detected and the distribution ratios were different. Muscle tissue mRNA and protein testing showed that there were differences in mRNA expression levels among different genotypes (P < 0.05) and the protein expression levels between different genotypes show the same trend as mRNA. This study provides potential molecular materials for the improvement of Qinchuan cattle reproductivity and provides theoretical support for studying the effects of livestock TRDMT1 on animal growth and development.
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Affiliation(s)
- Xiaohua Yi
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Shuai He
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Shuhui Wang
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Haidong Zhao
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Mingli Wu
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Shirong Liu
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Yun Pan
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Yu Zhang
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Xiuzhu Sun
- College of Grassland Agriculture, Northwest A&F University, Yangling, Shaanxi, China
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8
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Wang Z, Zhou B, Zhang T, Yan X, Yu Y, Li J, Mei B, Wang Z, Zhang Y, Wang R, Lv Q, Liu Z, Zhao Y, Du C, Su R. Assessing Genetic Diversity and Estimating the Inbreeding Effect on Economic Traits of Inner Mongolia White Cashmere Goats Through Pedigree Analysis. Front Vet Sci 2021; 8:665872. [PMID: 34239910 PMCID: PMC8258104 DOI: 10.3389/fvets.2021.665872] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Accepted: 05/10/2021] [Indexed: 11/13/2022] Open
Abstract
Objective: The purpose of this study was to discover the population structure and genetic diversity of Inner Mongolia White Cashmere goats (IMCGs) and demonstrate the effect of inbreeding on the live body weight (LBW), cashmere yield (CY), fiber length (FL), and fiber diameter (FD) of IMCGs. Materials and Methods: All data were collected from pedigree information and production performance records of IMCGs from 1983 to 2019. The population structure and genetic diversity were analyzed by Endog 4.8 software. Inbreeding coefficients were obtained by the pedigree package in R. Then, a linear regression model was used to analyze how inbreeding influences economic traits in IMCGs. Four levels of inbreeding coefficients (Fi) were classified in this study, including Fi = 0, 0< Fi ≤ 6.25, 6.25< Fi ≤ 12.5 and Fi≥12.5. Variance analysis was performed to determine whether inbreeding levels had a significant effect on economic traits in IMCGs. Results: The proportions of rams and dams in IMCGs for breeding were relatively small, with values of 0.8 and 20.5%, respectively. The proportion of inbred animals in the entire population was high, with values up to 68.6%; however, the average inbreeding coefficient and relatedness coefficient were 4.50 and 8.48%, respectively. To date, the population has experienced 12 generations. The average generation interval obtained in the present study was 4.11 ± 0.01 years. The ram-to-son pathway was lowest (3.97 years), and the ewe-to-daughter pathway was highest (4.24 years). It was discovered that the LBW, CY, and FL increased by 3.88 kg, 208.7 g, and 1.151 cm, respectively, with every 1% increase in the inbreeding coefficient, and the FD decreased by 0.819 μm with every 1% increase in the inbreeding coefficient. Additionally, multiple comparison analysis indicated that when the inbreeding coefficient was higher than 6.25%, the LBW showed an obvious decreasing trend. The threshold value of inbreeding depression in the CY is 12.5%. However, inbreeding depression has not been observed in the FL and FD. Conclusion: Pedigree completeness needs to be further strengthened. The degree of inbreeding in this flock should be properly controlled when designing breeding programs.
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Affiliation(s)
- Zhiying Wang
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, China
| | - Bohan Zhou
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, China
| | - Tao Zhang
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, China.,Inner Mongolia Bigvet Co., Ltd., Hohhot, China
| | - Xiaochun Yan
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, China
| | - Yongsheng Yu
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, China
| | - Jinquan Li
- Key Laboratory of Mutton Sheep Genetics and Breeding, Ministry of Agriculture, Hohhot, China.,Key Laboratory of Animal Genetics, Breeding and Reproduction in Inner Mongolia Autonomous Region, Hohhot, China.,Engineering Research Center for Goat Genetics and Breeding, Inner Mongolia Agriculture University, Hohhot, China
| | - Bujun Mei
- Department of Agriculture, Hetao College, Hetao University, Bayannaoer, China
| | - Zhixin Wang
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, China
| | - Yanjun Zhang
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, China
| | - Ruijun Wang
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, China
| | - Qi Lv
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, China
| | - Zhihong Liu
- Inner Mongolia Bigvet Co., Ltd., Hohhot, China
| | | | - Chen Du
- Reproductive Medicine Center, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, China
| | - Rui Su
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, China
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Pillai HB, Thirupathy Venkatachalapathy R. Association of inhibin alpha gene polymorphism with litter size and growth in Malabari goats of India. Small Rumin Res 2020. [DOI: 10.1016/j.smallrumres.2020.106188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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10
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Moazemi I, Mohammadabadi MR, Mostafavi A, Esmailizadeh AK, Babenko OI, Bushtruk MV, Tkachenko SV, Stavetska RV, Klopenko NI. Polymorphism of DMRT3 Gene and Its Association with Body Measurements in Horse Breeds. RUSS J GENET+ 2020. [DOI: 10.1134/s1022795420100087] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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Wang K, Kang Z, Jiang E, Yan H, Zhu H, Liu J, Qu L, Lan X, Pan C. Genetic effects of DSCAML1 identified in genome-wide association study revealing strong associations with litter size and semen quality in goat (Capra hircus). Theriogenology 2020; 146:20-25. [PMID: 32036056 DOI: 10.1016/j.theriogenology.2020.01.079] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Revised: 01/30/2020] [Accepted: 01/30/2020] [Indexed: 01/31/2023]
Abstract
The down syndrome cell adhesion molecule like 1 (DSCAML1), is associated with the development of the nervous system and neurologic diseases. Previous Genome-wide association studies have shown that it is associated with sperm morphology, suggesting it has a critical role in fecundity. In this study, expression profiles of goat DSCAML1 mRNA were analyzed. The results showed that its expression in the testis differ significantly between the mitotic stage and meiotic stage. Three insertion/deletion (indel) variants of goat DSCAML1 were determined in the Shaanbei White Cashmere Goat (SWCG, n = 2162). Based on the association analysis, two indels (P2-16bp, P14-15bp) were significantly related to sperm quality (sperm motility and sperm density) in male goat and three loci were markedly related to the first-birth litter size in female goat (P = 4.0 × 10-6; P = 1.0 × 10-6; P = 4.7 × 10-2). In male goats, the different genotypes of P2-16bp and P14-15bp revealed a noticeable effect on the expression of DSCAML1. Moreover, the effects observed in the first-birth litter followed a similar trend, which may provide the basis for further research of DSCAML1 gene function and marker assisted selection (MAS) programs to improve reproductive traits.
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Affiliation(s)
- Ke Wang
- College of Animal Science and Technology, Northwest A&F University, Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, Key Laboratory of Animal Biotechnology, Ministry of Agriculture, No. 22 Xinong Road, Yangling, Shaanxi, 712100, China.
| | - Zihong Kang
- College of Animal Science and Technology, Northwest A&F University, Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, Key Laboratory of Animal Biotechnology, Ministry of Agriculture, No. 22 Xinong Road, Yangling, Shaanxi, 712100, China.
| | - Enhui Jiang
- College of Animal Science and Technology, Northwest A&F University, Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, Key Laboratory of Animal Biotechnology, Ministry of Agriculture, No. 22 Xinong Road, Yangling, Shaanxi, 712100, China.
| | - Hailong Yan
- Department of Neurology, Institute of Brain Science, Medical School, Shanxi Datong University, Datong, 037000, China
| | - Haijing Zhu
- Life Science Research Center, Yulin University, Shaanxi Provincial Engineering and Technology Research Center of Cashmere Goats, Yulin, 719000, China
| | - Jinwang Liu
- Life Science Research Center, Yulin University, Shaanxi Provincial Engineering and Technology Research Center of Cashmere Goats, Yulin, 719000, China
| | - Lei Qu
- Life Science Research Center, Yulin University, Shaanxi Provincial Engineering and Technology Research Center of Cashmere Goats, Yulin, 719000, China
| | - Xianyong Lan
- College of Animal Science and Technology, Northwest A&F University, Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, Key Laboratory of Animal Biotechnology, Ministry of Agriculture, No. 22 Xinong Road, Yangling, Shaanxi, 712100, China
| | - Chuanying Pan
- College of Animal Science and Technology, Northwest A&F University, Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, Key Laboratory of Animal Biotechnology, Ministry of Agriculture, No. 22 Xinong Road, Yangling, Shaanxi, 712100, China.
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Al-Shuhaib MBS, Al-Kafajy FR, Al-Jashami GS. A computational approach for explaining the effect of the prl gene polymorphism on prolactin structure and biological activity in Japanese quails. Anim Biotechnol 2019; 32:273-281. [PMID: 31661660 DOI: 10.1080/10495398.2019.1683568] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
Prolactin is a versatile hormone with multiple activities, including a negative control on egg production. This study was conducted to genotype all the coding portions of the prl gene using PCR-SSCP-sequencing, and to investigate the effects of amino acid substitutions of the prl gene on the structure and function of prolactin in quails using in silico approach. Though all genotyped exons exerted homogenous PCR-SSCP patterns, a total of 12 novel SNPs were detected in the investigated exons, including three SNPs in exon-1, 8 SNPs in exon-2, and one SNP in exon-4. Three adjacent missense SNPs were detected in exon-2, namely H69P, T70P, and S71F. Computational tools indicated obvious deleterious effects of T70P, with less extent to H69P and S71F on prolactin functions and activity, which may lead to limited participation of this hormone in the negative control of egg production. In conclusion, the introduction of in silico prediction has suggested an alternative solution for the breeders to evaluate the effect of each witnessed nsSNP in protein structure and function. The current study suggests three nsSNPs, T70P, T70P, and S71F as strong candidates for the negative effect on prolactin biological activity with a consequent reversal positive effect on egg productivity traits.
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Affiliation(s)
| | - Fadhil R Al-Kafajy
- Department of Animal Production, College of Agriculture, Al-Qasim Green University, Al-Qasim, Babil, Iraq
| | - Ghadeer S Al-Jashami
- Department of Animal Production, College of Agriculture, Al-Qasim Green University, Al-Qasim, Babil, Iraq
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Mostafavi A, Fozi MA, Koshkooieh AE, Mohammadabadi M, Babenko OI, Klopenko NI. Effect of LCORL gene polymorphism on body size traits in horse populations. ACTA SCIENTIARUM: ANIMAL SCIENCES 2019. [DOI: 10.4025/actascianimsci.v42i1.47483] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
The aim of this study was to determine polymorphism of LCORL gene in horse breeds and its association with body size. PCR-RFLP technique was performed using AluI for genotyping of 306 horses. Results showed that C is the rare allele in Iranian Breeds, because these horses have been used since ancient times as a courier and for war and archery, hence selection has done to benefit of spiky horses with medium body that need less food and are tireless. While, for foreign breeds; frequency of C allele was high that can be concluded these breeds used in fields, forests, and mines. A UPGMA dendrogram based on the Nei's standard genetic distance among studied breeds showed separate clusters for Iranian native and exotic breeds. Statistical association analysis of three observed genotypes with body size showed that there is an association between this polymorphism and body size criteria (p < 0.01). Overall, it can be concluded that studied mutation in LCORL gene can be used as candidate marker for improving body weight in horse.
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Bai DP, Hu YQ, Li YB, Huang ZB, Li A. Polymorphisms of the prolactin gene and their association with egg production traits in two Chinese domestic ducks. Br Poult Sci 2019; 60:125-129. [PMID: 30648884 DOI: 10.1080/00071668.2019.1567909] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
1. Prolactin (PRL) as a polypeptide hormone which plays a crucial role in egg production traits. 2. Polymorphisms of the PRL gene were analysed with DNA sequencing and polymerase chain reaction-single-strand conformation polymorphism methods in two Chinese domestic laying duck breeds (Jinding, n = 400, Youxian, n = 400, respectively). 3. The results showed that one polymorphism was detected (A-412G) in intron 1 of the PRL gene, with three genotypes: AA, AG and GG. Association analysis showed that the ducks with the GG genotype had significantly greater egg production and egg weight than those with AG and AA genotype (p < 0.05). Hence, the 412A > G polymorphism of the PRL gene in intron 1 is a potentially valuable genetic marker for laying duck breeding programmes.
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Affiliation(s)
- D-P Bai
- a College of Animal Sciences , Fujian Agricultural and Forestry University , Fuzhou , China.,b Key Laboratory of Animal Embryo Engineering and Molecular Breeding , Wuhan , China
| | - Y-Q Hu
- a College of Animal Sciences , Fujian Agricultural and Forestry University , Fuzhou , China
| | - Y-B Li
- a College of Animal Sciences , Fujian Agricultural and Forestry University , Fuzhou , China
| | - Z-B Huang
- c Fujian Key Laboratory of Traditional Chinese Veterinary Medicine and Animal Health , Fuzhou , China
| | - A Li
- a College of Animal Sciences , Fujian Agricultural and Forestry University , Fuzhou , China
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15
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Bosewell A, Naicy T, Aravindakshan T, Kurian E. Sequence characterization, structural analysis, SNP detection and expression profiling of SLC11A1 gene in Indian goats. Small Rumin Res 2018. [DOI: 10.1016/j.smallrumres.2018.04.012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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Naicy T, Venkatachalapathy T, Aravindakshan T, Bosewell A, Silpa M. Association of a SacII polymorphism in the Nerve Growth Factor (NGF) gene exon 3 with growth traits in Indian goats. Small Rumin Res 2018. [DOI: 10.1016/j.smallrumres.2017.11.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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17
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Li X, Su R, Wan W, Zhang W, Jiang H, Qiao X, Fan Y, Zhang Y, Wang R, Liu Z, Wang Z, Liu B, Ma Y, Zhang H, Zhao Q, Zhong T, Di R, Jiang Y, Chen W, Wang W, Dong Y, Li J. Identification of selection signals by large-scale whole-genome resequencing of cashmere goats. Sci Rep 2017; 7:15142. [PMID: 29123196 PMCID: PMC5680388 DOI: 10.1038/s41598-017-15516-0] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2017] [Accepted: 10/27/2017] [Indexed: 01/14/2023] Open
Abstract
Inner Mongolia and Liaoning cashmere goats are two outstanding Chinese multipurpose breeds that adapt well to the semi-arid temperate grassland. These two breeds are characterized by their soft cashmere fibers, thus making them great models to identify genomic regions that are associated with cashmere fiber traits. Whole-genome sequencing of 70 cashmere goats produced more than 5.52 million single-nucleotide polymorphisms and 710,600 short insertions and deletions. Further analysis of these genetic variants showed some population-specific molecular markers for the two cashmere goat breeds that are otherwise phenotypically similar. By analyzing FST and θπ outlier values, we identified 135 genomic regions that were associated with cashmere fiber traits within the cashmere goat populations. These selected genomic regions contained genes, which are potential involved in the production of cashmere fiber, such as FGF5, SGK3, IGFBP7, OXTR, and ROCK1. Gene ontology enrichment analysis of identified short insertions and deletions also showed enrichment in keratinocyte differentiation and epidermal cell differentiation. These findings demonstrate that this genomic resource will facilitate the breeding of cashmere goat and other Capra species in future.
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Affiliation(s)
- Xiaokai Li
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, 010018, China
| | - Rui Su
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, 010018, China.,Key Laboratory of Animal Genetics, Breeding and Reproduction - Inner Mongolia Autonomous Region, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, 010018, China.,Key Laboratory of Mutton Sheep Genetics and Breeding, Ministry of Agriculture, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, 010018, China.,Engineering Research Center for Goat Genetics and Breeding - Inner Mongolia Autonomous Region, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, 010018, China.,State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, 650223, China
| | - Wenting Wan
- Center for Ecological and Environmental Sciences, Key Laboratory for Space Bioscience & Biotechnology, Northwestern Polytechnical University, Xi'an, Shaanxi, 710072, China
| | - Wenguang Zhang
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, 010018, China
| | - Huaizhi Jiang
- College of Animal Science and Technology, Jilin Agricultural University, Changchun, Jilin, 130118, China
| | - Xian Qiao
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, 010018, China
| | - Yixing Fan
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, 010018, China
| | - Yanjun Zhang
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, 010018, China.,Key Laboratory of Animal Genetics, Breeding and Reproduction - Inner Mongolia Autonomous Region, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, 010018, China.,Key Laboratory of Mutton Sheep Genetics and Breeding, Ministry of Agriculture, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, 010018, China.,Engineering Research Center for Goat Genetics and Breeding - Inner Mongolia Autonomous Region, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, 010018, China
| | - Ruijun Wang
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, 010018, China.,Key Laboratory of Animal Genetics, Breeding and Reproduction - Inner Mongolia Autonomous Region, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, 010018, China.,Key Laboratory of Mutton Sheep Genetics and Breeding, Ministry of Agriculture, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, 010018, China.,Engineering Research Center for Goat Genetics and Breeding - Inner Mongolia Autonomous Region, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, 010018, China
| | - Zhihong Liu
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, 010018, China.,Key Laboratory of Animal Genetics, Breeding and Reproduction - Inner Mongolia Autonomous Region, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, 010018, China.,Key Laboratory of Mutton Sheep Genetics and Breeding, Ministry of Agriculture, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, 010018, China.,Engineering Research Center for Goat Genetics and Breeding - Inner Mongolia Autonomous Region, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, 010018, China
| | - Zhiying Wang
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, 010018, China.,Key Laboratory of Animal Genetics, Breeding and Reproduction - Inner Mongolia Autonomous Region, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, 010018, China.,Key Laboratory of Mutton Sheep Genetics and Breeding, Ministry of Agriculture, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, 010018, China.,Engineering Research Center for Goat Genetics and Breeding - Inner Mongolia Autonomous Region, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, 010018, China
| | - Bin Liu
- Institute of Animal Husbandry, Academy of Agriculture and Stockbreeding Sciences, Hohhot, Inner Mongolia, 010030, China
| | - Yuehui Ma
- The Key Laboratory for Farm Animal Genetic Resources and Utilization of Ministry of Agriculture of China, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Hongping Zhang
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Qianjun Zhao
- The Key Laboratory for Farm Animal Genetic Resources and Utilization of Ministry of Agriculture of China, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Tao Zhong
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Ran Di
- The Key Laboratory for Farm Animal Genetic Resources and Utilization of Ministry of Agriculture of China, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Yu Jiang
- College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Wei Chen
- College of Biological Big Data, Yunnan Agriculture University, Kunming, Yunnan, 650504, China.,Yunnan Research Institute for Local Plateau Agriculture and Industry, Kunming, Yunnan, 650201, China
| | - Wen Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, 650223, China.
| | - Yang Dong
- College of Biological Big Data, Yunnan Agriculture University, Kunming, Yunnan, 650504, China. .,BGI-Shenzhen, Shenzhen, Guangdong, 518083, China. .,Yunnan Research Institute for Local Plateau Agriculture and Industry, Kunming, Yunnan, 650201, China.
| | - Jinquan Li
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, 010018, China. .,Key Laboratory of Animal Genetics, Breeding and Reproduction - Inner Mongolia Autonomous Region, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, 010018, China. .,Key Laboratory of Mutton Sheep Genetics and Breeding, Ministry of Agriculture, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, 010018, China. .,Engineering Research Center for Goat Genetics and Breeding - Inner Mongolia Autonomous Region, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, 010018, China.
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qPCR and HRM-based diagnosis of SNPs on growth differentiation factor 9 (GDF9), a gene associated with sheep (Ovis aries) prolificacy. 3 Biotech 2017; 7:204. [PMID: 28667646 DOI: 10.1007/s13205-017-0837-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2017] [Accepted: 05/26/2017] [Indexed: 10/19/2022] Open
Abstract
Prolificacy is a desirable trait for genetic improvement of sheep flocks, since it holds the potential to improve productivity. Animals carrying single-nucleotide polymorphisms (SNPs) in genes associated with this trait can be identified and employed to increase prolificacy in flocks. In this study, we report a diagnostic method based on quantitative PCR and high-resolution melting curves to detect different SNPs in the prolificacy-associated gene growth differentiation factor 9 (GDF9). The diagnostic method was validated using artificial sequences representing known SNPs in GDF9, then applied to a real flock comprising four breeds and admixed animals (n = 306). Five different SNPs were identified in this flock, as was a low or null frequency of occurrence of SNPs positively associated with prolificacy. This indicates a need to implement a breeding strategy for recovering or reintroducing such SNPs. Our method provides a genotyping strategy for identifying individuals with SNPs of interest for prolificacy, which will help producers plan a breeding strategy for this trait. This method can be adapted and expanded for the diagnosis of other traits of interest.
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