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Liu X, Dou D, Xu Z, Wang S, Chen C, Zhou J, Shen L, Wang S, Li H, Zhang D, Zhang H. Genetic parameter estimation and genetic evaluation of important economic traits in white and yellow broilers. Br Poult Sci 2024:1-7. [PMID: 39250000 DOI: 10.1080/00071668.2024.2394961] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 07/11/2024] [Indexed: 09/10/2024]
Abstract
1. This study calculated descriptive statistics for the production traits of two broiler populations: 1) the Northeast Agricultural University broiler lines divergently selected for abdominal fat content (NEAUHLF white broilers), including fat and lean lines; and 2) the Guangxi yellow broilers. Their genetic parameters were estimated, including (co)variance components, heritability (h2) and genetic correlations (rg), using the REML method.2. Heritability estimates (h2) for NEAUHLF white broilers ranged from 0.07 to 0.61. Traits with high heritability (h2 >0.3) included body weight at 3, 5 and 7 weeks of age (BW3, BW5, BW7), carcass weight (CW), metatarsal circumference (MeC), liver weight (LW), gizzard weight (GW), spleen weight (SW) and testis weight (TeW), while in Guangxi yellow broilers, heritability estimates ranged from 0.18 to 0.76, with every trait exhibiting high heritability, except for SW (0.18).3. Positive genetic correlations for NEAUHLF were found (rg >0.3, ranging from 0.31 to 0.84) between BW7 and metatarsal length (MeL), MeC, body oblique length (BoL), chest angle (ChA), LW, GW, heart weight (HW) and SW. Genetic correlations between abdominal fat weight (AFW) and BW1, BW3, BW5, CW, MeL, keel length (KeL), BoL and LW were positive (rg >0.3, ranging from 0.31 to 0.58).4. Among the Guangxi population, BW (125 d of age) showed strong positive genetic correlations with all other traits (rg >0.3, ranging from 0.30 to 0.99), while AFW displayed strong positive genetic correlations with leg muscle weight (LeW), CW, BW and thigh diameter (TD) (rg >0.3, ranging from 0.44 to 0.51).5. It was concluded that the characteristics of the two populations were different, which means there is a need to use different strategies when performing the breeding work to improve productivity and efficiency in both broiler populations.
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Affiliation(s)
- X Liu
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin, P. R. China
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department, Harbin, Heilongjiang Province, P. R. China
| | - D Dou
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin, P. R. China
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department, Harbin, Heilongjiang Province, P. R. China
| | - Z Xu
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin, P. R. China
| | - S Wang
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin, P. R. China
| | - C Chen
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin, P. R. China
| | - J Zhou
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin, P. R. China
| | - L Shen
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin, P. R. China
| | - S Wang
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin, P. R. China
| | - H Li
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin, P. R. China
| | - D Zhang
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, P. R. China
- Guangdong Wens Nanfang Poultry Breeding Co. Ltd, Xinxing, P. R. China
| | - H Zhang
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin, P. R. China
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, P. R. China
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2
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Haqani MI, Nakano M, Nagano AJ, Nakamura Y, Tsudzuki M. Association analysis of production traits of Japanese quail (Coturnix japonica) using restriction-site associated DNA sequencing. Sci Rep 2023; 13:21307. [PMID: 38042890 PMCID: PMC10693557 DOI: 10.1038/s41598-023-48293-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 10/10/2023] [Accepted: 11/24/2023] [Indexed: 12/04/2023] Open
Abstract
This study was designed to perform an association analysis and identify SNP markers associated with production traits of Japanese quail using restriction-site-associated DNA sequencing. Weekly body weight data from 805 quail were collected from hatching to 16 weeks of age. A total number of 3990 eggs obtained from 399 female quail were used to assess egg quality traits. Egg-related traits were measured at the beginning of egg production (first stage) and at 12 weeks of age (second stage). Five eggs were analyzed at each stage. Traits, such as egg weight, egg length and short axes, eggshell strength and weight, egg equator thickness, yolk weight, diameter, and colour, albumen weight, age of first egg, total number of laid eggs, and egg production rate, were assessed. A total of 383 SNPs and 1151 associations as well as 734 SNPs and 1442 associations were identified in relation to quail production traits using general linear model (GLM) and mixed linear model (MLM) approaches, respectively. The GLM-identified SNPs were located on chromosomes 1-13, 15, 17-20, 24, 26-28, and Z, underlying phenotypic traits, except for egg and albumen weight at the first stage and yolk yellowness at the second stage. The MLM-identified SNPs were positioned on defined chromosomes associated with phenotypic traits except for the egg long axis at the second stage of egg production. Finally, 35 speculated genes were identified as candidate genes for the targeted traits based on their nearest positions. Our findings provide a deeper understanding and allow a more precise genetic improvement of production traits of Galliformes, particularly in Japanese quail.
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Affiliation(s)
- Mohammad Ibrahim Haqani
- Graduate School of Integrated Sciences for Life, Hiroshima University, Higashi-Hiroshima, Hiroshima, 739-8525, Japan.
| | - Michiharu Nakano
- Faculty of Agriculture and Marine Sciences, Kochi University, Nankoku, Kochi, 783-8502, Japan
| | - Atsushi J Nagano
- Faculty of Agriculture, Ryukoku University, Otsu, Shiga, 520-2194, Japan
- Institute for Advanced Biosciences, Keio University, Yamagata, 997-0017, Japan
| | - Yoshiaki Nakamura
- Graduate School of Integrated Sciences for Life, Hiroshima University, Higashi-Hiroshima, Hiroshima, 739-8525, Japan
- Japanese Avian Bioresource Project Research Center, Hiroshima University, Higashi-Hiroshima, Hiroshima, 739-8525, Japan
| | - Masaoki Tsudzuki
- Graduate School of Integrated Sciences for Life, Hiroshima University, Higashi-Hiroshima, Hiroshima, 739-8525, Japan.
- Japanese Avian Bioresource Project Research Center, Hiroshima University, Higashi-Hiroshima, Hiroshima, 739-8525, Japan.
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3
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Zhou G, Liu T, Wang Y, Qu H, Shu D, Jia X, Luo C. Genome-Wide Association Studies Provide Insight Into the Genetic Determination for Hyperpigmentation of the Visceral Peritoneum in Broilers. Front Genet 2022; 13:820297. [PMID: 35299951 PMCID: PMC8921551 DOI: 10.3389/fgene.2022.820297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Accepted: 02/09/2022] [Indexed: 11/29/2022] Open
Abstract
Hyperpigmentation of the visceral peritoneum (HVP) has been becoming one of the most challenging problems in yellow-feathered chicken production, which seriously affected chicken carcass quality traits. Detecting which genes dominantly impact pigmentation in the peritoneum tissues is of great benefit to the genetic improvement of HVP. To investigate the genetic mechanism of HVP in yellow-feathered broilers, genome-wide association studies (GWASs) were conducted in the F2 generation of a cross broiler population with 395 birds. A total of 115,706 single-nucleotide polymorphisms (SNPs) of 122,415 were retained to identify quantitative trait loci (QTL) associated to HVP in chicken. The GWAS results based on the logistic mixed model (LMM) revealed that a narrow genomic location on chromosomes 1 (49.2–51.3 Mb) was significantly associated (p ≤ 4.32 × 10−7) with HVP, which contained 23 SNP makers related to 14 functional genes (MFNG, POLDIP3, POLR2F, PICK1, PDXP, SGSM3, RANGAP1, MYH9, RPL3, GALP3, LGALS1, MICALL1, ATF4, and CYP2D6). Four highly associated (p < 10−5) haplotype blocks of 0.80 kb (two SNPs), 0.06 kb (two SNPs), 0.95 kb (two SNPs), and 0.03 kb (two SNPs) were identified with two, two, four, and four distinct haplotypes, respectively. As a melanoma-associated gene, CYP2D6 were also possibly involved in the development of HVP occurring in chicken with two significant variations (rs314284996 and rs317955795) in the promoter regions. Further tests revealed that the expression of CYP2D6 was obviously higher in the visceral peritoneum tissue of chicken with HVP than that in the normal group (p < 0.05). Our results provide a novel clue to understand the genetic mechanism of HVP generation in chicken, and the mapped QTL or candidate genes might serve for genomic selection to improve carcass quality in the yellow-feathered chicken industry.
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Affiliation(s)
- Guangyuan Zhou
- Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, School of Life Sciences and Engineering, Foshan University, Foshan, China
- State Key Laboratory of Livestock and Poultry Breeding, Guangdong Key Laboratory of Animal Breeding and Nutrition, Institute of Animal Science, Guangdong Academy of Agricultural Sciences, Guangzhou, China
| | - Tianfei Liu
- State Key Laboratory of Livestock and Poultry Breeding, Guangdong Key Laboratory of Animal Breeding and Nutrition, Institute of Animal Science, Guangdong Academy of Agricultural Sciences, Guangzhou, China
| | - Yan Wang
- State Key Laboratory of Livestock and Poultry Breeding, Guangdong Key Laboratory of Animal Breeding and Nutrition, Institute of Animal Science, Guangdong Academy of Agricultural Sciences, Guangzhou, China
| | - Hao Qu
- State Key Laboratory of Livestock and Poultry Breeding, Guangdong Key Laboratory of Animal Breeding and Nutrition, Institute of Animal Science, Guangdong Academy of Agricultural Sciences, Guangzhou, China
| | - Dingming Shu
- State Key Laboratory of Livestock and Poultry Breeding, Guangdong Key Laboratory of Animal Breeding and Nutrition, Institute of Animal Science, Guangdong Academy of Agricultural Sciences, Guangzhou, China
| | - Xinzheng Jia
- Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, School of Life Sciences and Engineering, Foshan University, Foshan, China
- *Correspondence: Xinzheng Jia, ; Chenglong Luo,
| | - Chenglong Luo
- State Key Laboratory of Livestock and Poultry Breeding, Guangdong Key Laboratory of Animal Breeding and Nutrition, Institute of Animal Science, Guangdong Academy of Agricultural Sciences, Guangzhou, China
- *Correspondence: Xinzheng Jia, ; Chenglong Luo,
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Habimana R, Ngeno K, Okeno TO, Hirwa CDA, Keambou Tiambo C, Yao NK. Genome-Wide Association Study of Growth Performance and Immune Response to Newcastle Disease Virus of Indigenous Chicken in Rwanda. Front Genet 2021; 12:723980. [PMID: 34745207 PMCID: PMC8570395 DOI: 10.3389/fgene.2021.723980] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Accepted: 07/15/2021] [Indexed: 11/13/2022] Open
Abstract
A chicken genome has several regions with quantitative trait loci (QTLs). However, replication and confirmation of QTL effects are required particularly in African chicken populations. This study identified single nucleotide polymorphisms (SNPs) and putative genes responsible for body weight (BW) and antibody response (AbR) to Newcastle disease (ND) in Rwanda indigenous chicken (IC) using genome-wide association studies (GWAS). Multiple testing was corrected using chromosomal false detection rates of 5 and 10% for significant and suggestive thresholds, respectively. BioMart data mining and variant effect predictor tools were used to annotate SNPs and candidate genes, respectively. A total of four significant SNPs (rs74098018, rs13792572, rs314702374, and rs14123335) significantly (p ≤ 7.6E-5) associated with BW were identified on chromosomes (CHRs) 8, 11, and 19. In the vicinity of these SNPs, four genes such as pre-B-cell leukaemia homeobox 1 (PBX1), GPATCH1, MPHOSPH6, and MRM1 were identified. Four other significant SNPs (rs314787954, rs13623466, rs13910430, and rs737507850) all located on chromosome 1 were strongly (p ≤ 7.6E-5) associated with chicken antibody response to ND. The closest genes to these four SNPs were cell division cycle 16 (CDC16), zinc finger, BED-type containing 1 (ZBED1), myxovirus (influenza virus) resistance 1 (MX1), and growth factor receptor bound protein 2 (GRB2) related adaptor protein 2 (GRAP2). Besides, other SNPs and genes suggestively (p ≤ 1.5E-5) associated with BW and antibody response to ND were reported. This work offers a useful entry point for the discovery of causative genes accountable for essential QTLs regulating BW and antibody response to ND traits. Results provide auspicious genes and SNP-based markers that can be used in the improvement of growth performance and ND resistance in IC populations based on gene-based and/or marker-assisted breeding selection.
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Affiliation(s)
- Richard Habimana
- College of Agriculture, Animal Science and Veterinary Medicine, University of Rwanda, Kigali, Rwanda.,Animal Breeding and Genomics Group, Department of Animal Science, Egerton University, Egerton, Kenya
| | - Kiplangat Ngeno
- Animal Breeding and Genomics Group, Department of Animal Science, Egerton University, Egerton, Kenya
| | - Tobias Otieno Okeno
- Animal Breeding and Genomics Group, Department of Animal Science, Egerton University, Egerton, Kenya
| | | | - Christian Keambou Tiambo
- Centre for Tropical Livestock Genetics and Health, International Livestock Research Institute, Nairobi, Kenya
| | - Nasser Kouadio Yao
- Biosciences Eastern and Central Africa - International Livestock Research Institute (BecA-ILRI) Hub, Nairobi, Kenya
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5
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Sinpru P, Bunnom R, Poompramun C, Kaewsatuan P, Sornsan S, Kubota S, Molee W, Molee A. Association of growth hormone and insulin-like growth factor I genotype with body weight, dominance of body weight, and mRNA expression in Korat slow-growing chickens. Anim Biosci 2021; 34:1886-1894. [PMID: 33705631 PMCID: PMC8563241 DOI: 10.5713/ab.20.0729] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Accepted: 02/27/2021] [Indexed: 12/02/2022] Open
Abstract
Objective Growth hormone (GH) and insulin-like growth factor I (IGF-I) play a critical role in animal growth rates. We aimed to investigate the effect of GH and IGF-I genotypes on body weight (BW), dominance, and gene expression in slow-growing chickens at different ages. Methods A total of 613 Korat chickens (KRs) were bred and divided into three groups by genotype – A1A1, A1A3, and A3A3 for GH and AA, AC, and CC for IGF-I. Chickens were weighed every two weeks, and liver and breast muscle tissues were collected at 10 weeks of age. Genetic parameters of KRs were estimated using ASReml software. The GH and IGF-I mRNA levels were measured by quantitative polymerase chain reaction. Significant differences between traits were analyzed using the generalized linear model. Results A significant effect of GH genotypes on BW was found at most ages, and the A1A1 genotype had the highest value of BW. Compared with the A3A3 genotype, the A1A1 and A1A3 genotypes showed a higher dominance effect at 0 and 2 weeks, and genotype A1A1 had the highest value of dominance at 8 weeks of age. A difference in GH mRNA levels between genotypes was detected in breast muscle at 6 weeks and in the liver tissue at 2 weeks. In the case of IGF-I gene, the AA genotype had the highest BW at the beginning of life. Significant differences in BW dominance were found at 2 weeks. However, IGF-I mRNA levels were not different among genotypes in both breast muscles and liver tissues. Conclusion Our results revealed that GH and IGF-I influence growth, but may not be involved in heterosis. GH can be used as a marker gene in selection programs for growth because the homozygous genotype (A1A1) had the highest BW at all ages. The IGF-I is not a useful marker gene for selection programs.
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Affiliation(s)
- Panpradub Sinpru
- School of Animal Technology and Innovation, Institute of Agricultural Technology, Suranaree University of Technology, Nakhon Ratchasima, 30000, Thailand
| | - Rujjira Bunnom
- School of Animal Technology and Innovation, Institute of Agricultural Technology, Suranaree University of Technology, Nakhon Ratchasima, 30000, Thailand
| | - Chotima Poompramun
- School of Animal Technology and Innovation, Institute of Agricultural Technology, Suranaree University of Technology, Nakhon Ratchasima, 30000, Thailand
| | - Pramin Kaewsatuan
- School of Animal Technology and Innovation, Institute of Agricultural Technology, Suranaree University of Technology, Nakhon Ratchasima, 30000, Thailand
| | - Sirangkun Sornsan
- School of Animal Technology and Innovation, Institute of Agricultural Technology, Suranaree University of Technology, Nakhon Ratchasima, 30000, Thailand
| | - Satoshi Kubota
- School of Animal Technology and Innovation, Institute of Agricultural Technology, Suranaree University of Technology, Nakhon Ratchasima, 30000, Thailand
| | - Wittawat Molee
- School of Animal Technology and Innovation, Institute of Agricultural Technology, Suranaree University of Technology, Nakhon Ratchasima, 30000, Thailand
| | - Amonrat Molee
- School of Animal Technology and Innovation, Institute of Agricultural Technology, Suranaree University of Technology, Nakhon Ratchasima, 30000, Thailand
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6
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Zhang G, Chen F, Wu P, Li T, He M, Yin X, Shi H, Duan Y, Zhang T, Wang J, Xie K, Dai G. MicroRNA-7 Targets the KLF4 Gene to Regulate the Proliferation and Differentiation of Chicken Primary Myoblasts. Front Genet 2020; 11:842. [PMID: 33193566 PMCID: PMC7530283 DOI: 10.3389/fgene.2020.00842] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Accepted: 07/13/2020] [Indexed: 12/17/2022] Open
Abstract
The proliferation and differentiation of chicken primary myoblasts (CPMs) play an important role in the development of skeletal muscle. In our previous research, RNA-seq analysis showed that microRNA-7 (miR-7) was relatively highly expressed in the proliferation phase of CPMs, but its expression level decreased significantly after CPMS-induced differentiation. Meanwhile, the mechanism by which the miR-7 regulates the proliferation and differentiation of CPMs is still unknown. In this study, we found that the expression levels of miR-7 and the Krüppel-like factor 4 (KLF4) gene were negatively correlated during the embryonic phase, and in vitro induced differentiation. A dual-luciferase assay and a rescue experiment show that there is a target relationship between miR-7 and the KLF4 gene. Meanwhile, the results show that overexpression of miR-7 inhibited the proliferation and differentiation of CPMs, while inhibition of miR-7 had the opposite effects. Furthermore, overexpression of the KLF4 gene was found to significantly promote the proliferation and differentiation of CPMs. Conversely, inhibition of the KLF4 gene was able to significantly decrease the proliferation and differentiation of CPMs. Our results demonstrate, for the first time, that miR-7 inhibits the proliferation and differentiation of myoblasts by targeting the KLF4 gene in chicken primary myoblasts.
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Affiliation(s)
- Genxi Zhang
- College of Animal Science and Technology, Yangzhou University, Yangzhou, China.,Joint International Research Laboratory of Agriculture and Agri-Product Safety, Yangzhou University, Yangzhou, China
| | - Fuxiang Chen
- College of Animal Science and Technology, Yangzhou University, Yangzhou, China.,Joint International Research Laboratory of Agriculture and Agri-Product Safety, Yangzhou University, Yangzhou, China
| | - Pengfei Wu
- College of Animal Science and Technology, Yangzhou University, Yangzhou, China.,Joint International Research Laboratory of Agriculture and Agri-Product Safety, Yangzhou University, Yangzhou, China
| | - TingTing Li
- College of Animal Science and Technology, Yangzhou University, Yangzhou, China.,Joint International Research Laboratory of Agriculture and Agri-Product Safety, Yangzhou University, Yangzhou, China
| | - Mingliang He
- College of Animal Science and Technology, Yangzhou University, Yangzhou, China.,Joint International Research Laboratory of Agriculture and Agri-Product Safety, Yangzhou University, Yangzhou, China
| | - Xuemei Yin
- College of Animal Science and Technology, Yangzhou University, Yangzhou, China.,Joint International Research Laboratory of Agriculture and Agri-Product Safety, Yangzhou University, Yangzhou, China
| | - Huiqiang Shi
- Jiangsu Jinghai Poultry Group Co., Ltd., Nantong, China
| | - Yanjun Duan
- College of Animal Science and Technology, Yangzhou University, Yangzhou, China.,Joint International Research Laboratory of Agriculture and Agri-Product Safety, Yangzhou University, Yangzhou, China
| | - Tao Zhang
- College of Animal Science and Technology, Yangzhou University, Yangzhou, China.,Joint International Research Laboratory of Agriculture and Agri-Product Safety, Yangzhou University, Yangzhou, China
| | - Jinyu Wang
- College of Animal Science and Technology, Yangzhou University, Yangzhou, China.,Joint International Research Laboratory of Agriculture and Agri-Product Safety, Yangzhou University, Yangzhou, China
| | - Kaizhou Xie
- College of Animal Science and Technology, Yangzhou University, Yangzhou, China.,Joint International Research Laboratory of Agriculture and Agri-Product Safety, Yangzhou University, Yangzhou, China
| | - Guojun Dai
- College of Animal Science and Technology, Yangzhou University, Yangzhou, China.,Joint International Research Laboratory of Agriculture and Agri-Product Safety, Yangzhou University, Yangzhou, China
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Chen F, Wu P, Shen M, He M, Chen L, Qiu C, Shi H, Zhang T, Wang J, Xie K, Dai G, Wang J, Zhang G. Transcriptome Analysis of Differentially Expressed Genes Related to the Growth and Development of the Jinghai Yellow Chicken. Genes (Basel) 2019; 10:genes10070539. [PMID: 31319533 PMCID: PMC6678745 DOI: 10.3390/genes10070539] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Revised: 07/09/2019] [Accepted: 07/10/2019] [Indexed: 12/18/2022] Open
Abstract
The growth traits are important traits in chickens. Compared to white feather broiler breeds, Chinese local broiler breeds have a slow growth rate. The main genes affecting the growth traits of local chickens in China are still unclear and need to be further explored. This experiment used fast-growth and slow-growth groups of the Jinghai Yellow chicken as the research objects. Three males and three females with similar body weights were selected from the two groups at four weeks old and eight weeks old, respectively, with a total of 24 individuals selected. After slaughter, their chest muscles were taken for transcriptome sequencing. In the differentially expressed genes screening, all of the genes obtained were screened by fold change ≥ 2 and false discovery rate (FDR) < 0.05. For four-week-old chickens, a total of 172 differentially expressed genes were screened in males, where there were 68 upregulated genes and 104 downregulated genes in the fast-growth group when compared with the slow-growth group. A total of 31 differentially expressed genes were screened in females, where there were 11 upregulated genes and 20 downregulated genes in the fast-growth group when compared with the slow-growth group. For eight-week-old chickens, a total of 37 differentially expressed genes were screened in males. The fast-growth group had 28 upregulated genes and 9 downregulated genes when compared with the slow-growth group. A total of 44 differentially expressed genes were screened in females. The fast-growth group had 13 upregulated genes and 31 downregulated genes when compared with the slow-growth group. Through gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, many genes were found to be related to cell proliferation and differentiation, muscle growth, and cell division such as SNCG, MCL1, ARNTL, PLPPR4, VAMP1, etc. Real-time PCR results were consistent with the RNA-Seq data and validated the findings. The results of this study will help to understand the regulation mechanism of the growth and development of Jinghai Yellow chicken and provide a theoretical basis for improving the growth rate of Chinese local chicken breeds.
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Affiliation(s)
- Fuxiang Chen
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Pengfei Wu
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Manman Shen
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Mingliang He
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Lan Chen
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Cong Qiu
- Jiangsu Jinghai Poultry Group Co., Ltd., Nantong 226100, China
| | - Huiqiang Shi
- Jiangsu Jinghai Poultry Group Co., Ltd., Nantong 226100, China
| | - Tao Zhang
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Jiahong Wang
- Upper School, Rutgers Preparatory School, NJ 08873, USA
| | - Kaizhou Xie
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Guojun Dai
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Jinyu Wang
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Genxi Zhang
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China.
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8
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Tarsani E, Kranis A, Maniatis G, Avendano S, Hager-Theodorides AL, Kominakis A. Discovery and characterization of functional modules associated with body weight in broilers. Sci Rep 2019; 9:9125. [PMID: 31235723 PMCID: PMC6591351 DOI: 10.1038/s41598-019-45520-5] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2019] [Accepted: 06/04/2019] [Indexed: 12/31/2022] Open
Abstract
Aim of the present study was to investigate whether body weight (BW) in broilers is associated with functional modular genes. To this end, first a GWAS for BW was conducted using 6,598 broilers and the high density SNP array. The next step was to search for positional candidate genes and QTLs within strong LD genomic regions around the significant SNPs. Using all positional candidate genes, a network was then constructed and community structure analysis was performed. Finally, functional enrichment analysis was applied to infer the functional relevance of modular genes. A total number of 645 positional candidate genes were identified in strong LD genomic regions around 11 genome-wide significant markers. 428 of the positional candidate genes were located within growth related QTLs. Community structure analysis detected 5 modules while functional enrichment analysis showed that 52 modular genes participated in developmental processes such as skeletal system development. An additional number of 14 modular genes (GABRG1, NGF, APOBEC2, STAT5B, STAT3, SMAD4, MED1, CACNB1, SLAIN2, LEMD2, ZC3H18, TMEM132D, FRYL and SGCB) were also identified as related to body weight. Taken together, current results suggested a total number of 66 genes as most plausible functional candidates for the trait examined.
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Affiliation(s)
- Eirini Tarsani
- Department of Animal Science and Aquaculture, Agricultural University of Athens, Iera Odos 75, 11855, Athens, Greece.
| | - Andreas Kranis
- Aviagen Ltd., Newbridge, Midlothian, EH28 8SZ, UK.,The Roslin Institute, University of Edinburgh, EH25 9RG, Midlothian, United Kingdom
| | | | | | - Ariadne L Hager-Theodorides
- Department of Animal Science and Aquaculture, Agricultural University of Athens, Iera Odos 75, 11855, Athens, Greece
| | - Antonios Kominakis
- Department of Animal Science and Aquaculture, Agricultural University of Athens, Iera Odos 75, 11855, Athens, Greece
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9
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Macciotta NPP, Biffani S, Bernabucci U, Lacetera N, Vitali A, Ajmone-Marsan P, Nardone A. Derivation and genome-wide association study of a principal component-based measure of heat tolerance in dairy cattle. J Dairy Sci 2017; 100:4683-4697. [PMID: 28365122 DOI: 10.3168/jds.2016-12249] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2016] [Accepted: 02/05/2017] [Indexed: 12/19/2022]
Abstract
Heat stress represents a key factor that negatively affects the productive and reproductive performance of farm animals. In the present work, a new measure of tolerance to heat stress for dairy cattle was developed using principal component analysis. Data were from 590,174 test-day records for milk yield, fat and protein percentages, and somatic cell score of 39,261 Italian Holstein cows. Test-day records adjusted for main systematic factors were grouped into 11 temperature-humidity index (THI) classes. Daughter trait deviations (DTD) were calculated for 1,540 bulls as means of the adjusted test-day records for each THI class. Principal component analysis was performed on the DTD for each bull. The first 2 principal components (PC) explained 42 to 51% of the total variance of the system across the 4 traits. The first PC, a measure of the level at which the curve is located, was interpreted as a measure of the level at which the DTD curve was located. The second PC, which shows the slope of increasing or decreases DTD curves, synthesized the behavior of the DTD pattern. Heritability of the 2 component scores was moderate to high for level across all traits (range = 0.23-0.82) and low to moderate for slope (range = 0.16-0.28). For each trait, phenotypic and genetic correlations between level and slope were equal to zero. A genome-wide association analysis was carried out on a subsample of 423 bulls genotyped with the Illumina 50K bovine bead chip (Illumina, San Diego, CA). Two single nucleotide polymorphisms were significantly associated with slope for milk yield, 4 with level for fat percentage, and 2 with level and slope of protein percentage, respectively. The gene discovery was carried out considering windows of 0.5 Mb surrounding the significant markers and highlighted some interesting candidate genes. Some of them have been already associated with the mechanism of heat tolerance as the heat shock transcription factor (HSF1) and the malonyl-CoA-acyl carrier protein transacylase (MCAT). The 2 PC were able to describe the overall level and the slope of response of milk production traits across increasing levels of THI index. Moreover, they exhibited genetic variability and were genetically uncorrelated. These features suggest their use as measures of thermotolerance in dairy cattle breeding schemes.
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Affiliation(s)
- N P P Macciotta
- Dipartimento di Agraria, Università di Sassari, 07100 Sassari, Italy.
| | - S Biffani
- Associazione Italiana Allevatori, 00161 Roma, Italy
| | - U Bernabucci
- Dipartimento di Scienze Agrarie e Forestali, Università degli Studi della Tuscia-Viterbo, 01100 Viterbo, Italy
| | - N Lacetera
- Dipartimento di Scienze Agrarie e Forestali, Università degli Studi della Tuscia-Viterbo, 01100 Viterbo, Italy
| | - A Vitali
- Dipartimento di Scienze Agrarie e Forestali, Università degli Studi della Tuscia-Viterbo, 01100 Viterbo, Italy
| | - P Ajmone-Marsan
- Istituto di Zootecnica, Università Cattolica del Sacro Cuore, 29122 Piacenza, Italy
| | - A Nardone
- Dipartimento di Scienze Agrarie e Forestali, Università degli Studi della Tuscia-Viterbo, 01100 Viterbo, Italy.
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Xue Q, Zhang G, Li T, Ling J, Zhang X, Wang J. Transcriptomic profile of leg muscle during early growth in chicken. PLoS One 2017; 12:e0173824. [PMID: 28291821 PMCID: PMC5349469 DOI: 10.1371/journal.pone.0173824] [Citation(s) in RCA: 55] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2016] [Accepted: 02/26/2017] [Indexed: 11/27/2022] Open
Abstract
The early growth pattern, especially the age of peak growth, of broilers affects the time to market and slaughter weight, which in turn affect the profitability of the poultry industry. However, the underlying mechanisms regulating chicken growth and development have rarely been studied. This study aimed to identify candidate genes involved in chicken growth and investigated the potential regulatory mechanisms of early growth in chicken. RNA sequencing was applied to compare the transcriptomes of chicken muscle tissues at three developmental stages during early growth. In total, 978 differentially expressed genes (DEGs) (fold change ≥ 2; false discovery rate < 0.05) were detected by pairwise comparison. Functional analysis showed that the DEGs are mainly involved in the processes of cell growth, muscle development, and cellular activities (such as junction, migration, assembly, differentiation, and proliferation). Many of the DEGs are well known to be related to chicken growth, such as MYOD1, GH, IGF2BP2, IGFBP3, SMYD1, CEBPB, FGF2, and IGFBP5. KEGG pathway analysis identified that the DEGs were significantly enriched in five pathways (P < 0.1) related to growth and development: extracellular matrix–receptor interaction, focal adhesion, tight junction, insulin signaling pathway, and regulation of the actin cytoskeleton. A total of 42 DEGs assigned to these pathways are potential candidate genes inducing the difference in growth among the three developmental stages, such as MYH10, FGF2, FGF16, FN1, CFL2, MAPK9, IRS1, PHKA1, PHKB, and PHKG1. Thus, our study identified a series of genes and several pathways that may participate in the regulation of early growth in chicken. These results should serve as an important resource revealing the molecular basis of chicken growth and development.
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Affiliation(s)
- Qian Xue
- College of Animal Science and Technology, Yangzhou University, Yangzhou, Jiangsu, China
- Key Laboratory for Animal Genetics, Breeding, Reproduction and Molecular Design of Jiangsu Province, Yangzhou, Jiangsu, China
| | - Genxi Zhang
- College of Animal Science and Technology, Yangzhou University, Yangzhou, Jiangsu, China
- Key Laboratory for Animal Genetics, Breeding, Reproduction and Molecular Design of Jiangsu Province, Yangzhou, Jiangsu, China
- * E-mail: (JW); (GZ)
| | - Tingting Li
- College of Animal Science and Technology, Yangzhou University, Yangzhou, Jiangsu, China
- Key Laboratory for Animal Genetics, Breeding, Reproduction and Molecular Design of Jiangsu Province, Yangzhou, Jiangsu, China
| | - Jiaojiao Ling
- College of Animal Science and Technology, Yangzhou University, Yangzhou, Jiangsu, China
- Key Laboratory for Animal Genetics, Breeding, Reproduction and Molecular Design of Jiangsu Province, Yangzhou, Jiangsu, China
| | - Xiangqian Zhang
- College of Animal Science and Technology, Yangzhou University, Yangzhou, Jiangsu, China
- Key Laboratory for Animal Genetics, Breeding, Reproduction and Molecular Design of Jiangsu Province, Yangzhou, Jiangsu, China
| | - Jinyu Wang
- College of Animal Science and Technology, Yangzhou University, Yangzhou, Jiangsu, China
- Key Laboratory for Animal Genetics, Breeding, Reproduction and Molecular Design of Jiangsu Province, Yangzhou, Jiangsu, China
- * E-mail: (JW); (GZ)
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