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Liu W, Liu J, Zhou Y, Cao D, Lei Q, Han H, Wang J, Li D, Gao J, Li H, Li F. Genome-Wide Association Study of Abdominal Fat in Wenshang Barred Chicken Based on the Slaf-Seq Technology. BRAZILIAN JOURNAL OF POULTRY SCIENCE 2022. [DOI: 10.1590/1806-9061-2021-1612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Affiliation(s)
- W Liu
- Shandong Academy of Agricultural Sciences, P. R. China; Poultry Breeding Engineering Technology Center of Shandong Province, China
| | - J Liu
- Shandong Academy of Agricultural Sciences, P. R. China; Poultry Breeding Engineering Technology Center of Shandong Province, China
| | - Y Zhou
- Shandong Academy of Agricultural Sciences, P. R. China; Poultry Breeding Engineering Technology Center of Shandong Province, China
| | - D Cao
- Shandong Academy of Agricultural Sciences, P. R. China; Poultry Breeding Engineering Technology Center of Shandong Province, China
| | - Q Lei
- Shandong Academy of Agricultural Sciences, P. R. China; Poultry Breeding Engineering Technology Center of Shandong Province, China
| | - H Han
- Shandong Academy of Agricultural Sciences, P. R. China; Poultry Breeding Engineering Technology Center of Shandong Province, China
| | - J Wang
- Shandong Academy of Agricultural Sciences, P. R. China; Poultry Breeding Engineering Technology Center of Shandong Province, China
| | - D Li
- Shandong Academy of Agricultural Sciences, P. R. China; Poultry Breeding Engineering Technology Center of Shandong Province, China
| | - J Gao
- Shandong Academy of Agricultural Sciences, P. R. China; Poultry Breeding Engineering Technology Center of Shandong Province, China
| | - H Li
- Shandong Academy of Agricultural Sciences, P. R. China
| | - F Li
- Shandong Academy of Agricultural Sciences, P. R. China; Poultry Breeding Engineering Technology Center of Shandong Province, China
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Affiliation(s)
- P.M. Hocking
- Roslin Institute, Roslin, Midlothian, Scotland, EH25 9PS
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Abdalla BA, Chen J, Nie Q, Zhang X. Genomic Insights Into the Multiple Factors Controlling Abdominal Fat Deposition in a Chicken Model. Front Genet 2018; 9:262. [PMID: 30073018 PMCID: PMC6060281 DOI: 10.3389/fgene.2018.00262] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2018] [Accepted: 06/28/2018] [Indexed: 12/12/2022] Open
Abstract
Genetic selection for an increased growth rate in meat-type chickens has been accompanied by excessive fat accumulation particularly in abdominal cavity. These progressed to indirect and often unhealthy effects on meat quality properties and increased feed cost. Advances in genomics technology over recent years have led to the surprising discoveries that the genome is more complex than previously thought. Studies have identified multiple-genetic factors associated with abdominal fat deposition. Meanwhile, the obesity epidemic has focused attention on adipose tissue and the development of adipocytes. The aim of this review is to summarize the current understanding of genetic/epigenetic factors associated with abdominal fat deposition, or as it relates to the proliferation and differentiation of preadipocytes in chicken. The results discussed here have been identified by different genomic approaches, such as QTL-based studies, the candidate gene approach, epistatic interaction, copy number variation, single-nucleotide polymorphism screening, selection signature analysis, genome-wide association studies, RNA sequencing, and bisulfite sequencing. The studies mentioned in this review have described multiple-genetic factors involved in an abdominal fat deposition. Therefore, it is inevitable to further study the multiple-genetic factors in-depth to develop novel molecular markers or potential targets, which will provide promising applications for reducing abdominal fat deposition in meat-type chicken.
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Affiliation(s)
- Bahareldin A. Abdalla
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou, China
- National-Local Joint Engineering Research Center for Livestock Breeding, The Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, China
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, The Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, China
| | - Jie Chen
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou, China
- National-Local Joint Engineering Research Center for Livestock Breeding, The Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, China
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, The Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, China
| | - Qinghua Nie
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou, China
- National-Local Joint Engineering Research Center for Livestock Breeding, The Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, China
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, The Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, China
| | - Xiquan Zhang
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou, China
- National-Local Joint Engineering Research Center for Livestock Breeding, The Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, China
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, The Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, China
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Characteristics of Egg-related Traits in the Onagadori (Japanese Extremely Long Tail) Breed of Chickens. J Poult Sci 2015. [DOI: 10.2141/jpsa.0140109] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
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Roux PF, Boutin M, Désert C, Djari A, Esquerré D, Klopp C, Lagarrigue S, Demeure O. Re-sequencing data for refining candidate genes and polymorphisms in QTL regions affecting adiposity in chicken. PLoS One 2014; 9:e111299. [PMID: 25333370 PMCID: PMC4205046 DOI: 10.1371/journal.pone.0111299] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2014] [Accepted: 09/22/2014] [Indexed: 12/30/2022] Open
Abstract
In this study, we propose an approach aiming at fine-mapping adiposity QTL in chicken, integrating whole genome re-sequencing data. First, two QTL regions for adiposity were identified by performing a classical linkage analysis on 1362 offspring in 11 sire families obtained by crossing two meat-type chicken lines divergently selected for abdominal fat weight. Those regions, located on chromosome 7 and 19, contained a total of 77 and 84 genes, respectively. Then, SNPs and indels in these regions were identified by re-sequencing sires. Considering issues related to polymorphism annotations for regulatory regions, we focused on the 120 and 104 polymorphisms having an impact on protein sequence, and located in coding regions of 35 and 42 genes situated in the two QTL regions. Subsequently, a filter was applied on SNPs considering their potential impact on the protein function based on conservation criteria. For the two regions, we identified 42 and 34 functional polymorphisms carried by 18 and 24 genes, and likely to deeply impact protein, including 3 coding indels and 4 nonsense SNPs. Finally, using gene functional annotation, a short list of 17 and 4 polymorphisms in 6 and 4 functional genes has been defined. Even if we cannot exclude that the causal polymorphisms may be located in regulatory regions, this strategy gives a complete overview of the candidate polymorphisms in coding regions and prioritize them on conservation- and functional-based arguments.
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Affiliation(s)
- Pierre-François Roux
- INRA, UMR1348 PEGASE, Saint-Gilles, France
- Agrocampus Ouest, UMR1348 PEGASE, Rennes, France
- Université Européenne de Bretagne, Rennes, France
| | - Morgane Boutin
- INRA, UMR1348 PEGASE, Saint-Gilles, France
- Agrocampus Ouest, UMR1348 PEGASE, Rennes, France
- Université Européenne de Bretagne, Rennes, France
| | - Colette Désert
- INRA, UMR1348 PEGASE, Saint-Gilles, France
- Agrocampus Ouest, UMR1348 PEGASE, Rennes, France
- Université Européenne de Bretagne, Rennes, France
| | | | - Diane Esquerré
- INRA, UMR1388 GenPhySE, GeT-PlaGe, Castanet-Tolosan, France
| | | | - Sandrine Lagarrigue
- INRA, UMR1348 PEGASE, Saint-Gilles, France
- Agrocampus Ouest, UMR1348 PEGASE, Rennes, France
- Université Européenne de Bretagne, Rennes, France
| | - Olivier Demeure
- INRA, UMR1348 PEGASE, Saint-Gilles, France
- Agrocampus Ouest, UMR1348 PEGASE, Rennes, France
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Uemoto Y, Sato S, Odawara S, Nokata H, Oyamada Y, Taguchi Y, Yanai S, Sasaki O, Takahashi H, Nirasawa K, Kobayashi E. Genetic mapping of quantitative trait loci affecting growth and carcass traits in F2 intercross chickens. Poult Sci 2009; 88:477-82. [PMID: 19211515 DOI: 10.3382/ps.2008-00296] [Citation(s) in RCA: 38] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
We constructed a chicken F(2) resource population to facilitate the genetic improvement of economically important traits, particularly growth and carcass traits. An F(2) population comprising 240 chickens obtained by crossing a Shamo (lean, lightweight Japanese native breed) male and White Plymouth Rock breed (fat, heavyweight broiler) females was measured for BW, carcass weight (CW), abdominal fat weight (AFW), breast muscle weight (BMW), and thigh muscle weight (TMW) and was used for genome-wide linkage and QTL analysis, using a total of 240 microsatellite markers. A total of 14 QTL were detected at a 5% chromosome-wide level, and 7 QTL were significant at a 5% experiment-wide level for the traits evaluated in the F(2) population. For growth traits, significant and suggestive QTL affecting BW (measured at 6 and 9 wk) and average daily gain were identified on similar regions of chromosomes 1 and 3. For carcass traits, the QTL effects on CW were detected on chromosomes 1 and 3, with the greatest F-ratio of 15.0 being obtained for CW on chromosome 3. Quantitative trait loci positions affecting BMW and TMW were not detected at the same loci as those detected for BMW percentage of CW and TMW percentage of CW. For AFW, QTL positions were detected at the same loci as those detected for AFW percentage of CW. The present study identified significant QTL affecting BW, CW, and AFW.
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Affiliation(s)
- Y Uemoto
- National Livestock Breeding Center, Nishigo, Fukushima 961-8511, Japan.
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Abasht B, Lamont SJ. Genome-wide association analysis reveals cryptic alleles as an important factor in heterosis for fatness in chicken F2 population. Anim Genet 2007; 38:491-8. [PMID: 17894563 DOI: 10.1111/j.1365-2052.2007.01642.x] [Citation(s) in RCA: 44] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
Genome-wide association studies have become possible in the chicken because of the recent availability of the complete genome sequence, a polymorphism map and high-density single nucleotide polymorphism (SNP) genotyping platforms. We used these tools to study the genetic basis of a very high level of heterosis that was previously observed for fatness in two F(2) populations established by crossing one outbred broiler (meat-type) sire with dams from two unrelated, highly inbred, light-bodied lines (Fayoumi and Leghorn). In each F(2) population, selective genotyping was carried out using phenotypically extreme males for abdominal fat percentage (AF) and about 3000 SNPs. Single-point association analysis of about 500 informative SNPs per cross showed significant association (P < 0.01) of 15 and 24 markers with AF in the Broiler x Fayoumi and Broiler x Leghorn crosses respectively. These SNPs were on 10 chromosomes (GGA1, 2, 3, 4, 7, 8, 10, 12, 15 and 27). Interestingly, of the 39 SNPs that were significantly associated with AF, there were about twice as many homozygous genotypes associated with higher AF that traced back to the inbred lines alleles, although the broiler line had on average higher AF. These SNPs are considered to be associated with QTL with cryptic alleles. This study reveals cryptic alleles as an important factor in heterosis for fatness observed in two chicken F(2) populations, and suggests epistasis as the common underlying mechanism for heterosis and cryptic allele expression. The results of this study also demonstrate the power of high marker-density SNP association studies in discovering QTL that were not detected by previous microsatellite-based genotyping studies.
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Affiliation(s)
- B Abasht
- Department of Animal Science, Iowa State University, Ames, IA 50011, USA
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Huang Y, Haley CS, Wu F, Hu S, Hao J, Wu C, Li N. Genetic mapping of quantitative trait loci affecting carcass and meat quality traits in Beijing ducks (Anas platyrhynchos). Anim Genet 2007; 38:114-9. [PMID: 17403008 DOI: 10.1111/j.1365-2052.2007.01571.x] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Quantitative trait loci (QTL) for carcass and meat quality traits were detected in a sample of 224 progeny from four males in line VI and 12 females in line V of Beijing ducks. These lines were selected for high body weight at 42 days of age (line VI) or high egg production at 360 days of age (line V). Traits were weights of the carcass, head, neck, shanks, wings, legs, thighs, breast, heart, liver, crop, gizzard, abdominal fat (AFW) and skin fat, as well as fat thickness in the tail, and pH value, shear force, drip loss (DL) (%) and cooking loss (CL) (%) of the breast. Using a half-sib analysis with a multiple QTL model, linkage between the carcass and meat quality traits and 95 microsatellite markers was investigated. Eight genome-wide significant QTL for weight of crop, skin fat, liver, neck, shanks, wings, DL were detected on linkage groups CAU4 and CAU6. One genome-wide suggestive QTL and one chromosome-wide significant QTL for weight of breast were found on CAU1 and CAU4 respectively. Fifteen chromosome-wide suggestive QTL influencing weight of AFW, breast, crop, heart, carcass, thighs, liver, shanks, gizzard, fat thickness in tail, DL (%) and CL (%) were mapped on CAU2, CAU4, CAU5, CAU6, CAU7, CAU10 and CAU13. In addition, two linked QTL for weight of liver and DL (%) were located on CAU2 and CAU7 respectively. The detection of QTL in ducks is a step towards identification of genes influencing these traits and their use for genetic improvement in this species.
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Affiliation(s)
- Y Huang
- State Key Laboratory for Agrobiotechnology, China Agricultural University, Beijing 100094, China
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Abasht B, Dekkers JCM, Lamont SJ. Review of Quantitative Trait Loci Identified in the Chicken. Poult Sci 2006; 85:2079-96. [PMID: 17135661 DOI: 10.1093/ps/85.12.2079] [Citation(s) in RCA: 108] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Methods for mapping QTL are actively used in the chicken to identify chromosomal regions contributing to variation in traits related to growth, disease resistance, egg production, behavior, and metabolic parameters. However, higher-resolution mapping and better knowledge of the genetic architecture underlying QTL are needed for successful application of this information into breeding programs. Therefore, this paper summarizes and integrates original, primary QTL studies in the chicken to identify basic information on the genetic architecture of quantitative traits in chickens. The results of this review show several instances of consensus of QTL locations for similar traits from independent studies. Furthermore, the consensus of QTL location for different traits and evidence for QTL with parent-of-origin effect, transgressive alleles, epistatic QTL, and QTL x sex interaction in chicken are presented and discussed. This information can be helpful in identifying genes or mutations underlying the QTL and in the application of genomic information in marker-assisted breeding programs.
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Affiliation(s)
- B Abasht
- Department of Animal Science, Iowa State University, Ames 50011, USA
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Jennen DGJ, Vereijken ALJ, Bovenhuis H, Crooijmans RPMA, Veenendaal A, van der Poel JJ, Groenen MAM. Detection and localization of quantitative trait loci affecting fatness in broilers. Poult Sci 2004; 83:295-301. [PMID: 15049477 DOI: 10.1093/ps/83.3.295] [Citation(s) in RCA: 59] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
A cross between 2 genetically different outcross broiler dam lines, originating from the White Plymouth Rock breed, was used to produce a large 3-generation broiler population. This population was used to detect and localize QTL affecting fatness in chicken. Twenty full-sib birds in generation 1 and 456 full-sib birds in generation 2 were typed for microsatellite markers, and phenotypic observations were collected for 3 groups of generation 3 birds (approximately 1,800 birds per group). Body weight, abdominal fat weight, and percentage abdominal fat was recorded at the age of 7, 9, and 10 wk. To study the presence of QTL, an across-family weighted regression interval mapping approach was used in a full-sib QTL analysis. Genotypes from 410 markers mapped on 25 chromosomes were available. For the 3 traits, 26 QTL were found for 18 regions on 12 chromosomes. Two genomewise significant QTL (P < 0.05) were detected, one for percentage abdominal fat at the age of 10 wk on chicken chromosome 1 at 241 cM (MCW0058 to MCW0101) with a test statistic of 2.75 and the other for BW at the age of 10 wk on chicken chromosome 13 at 9 cM (MCW0322 to MCW0110) with a test statistic of 2.77. Significance levels were obtained using the permutation test. Multiple suggestive QTL were found on chromosomes 1, 2, 4, 13, 15, and 18, whereas chromosomes 3, 7, 10, 11, 14, and 27 had a single suggestive QTL.
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Affiliation(s)
- D G J Jennen
- Wageningen Institute of Animal Sciences, Animal Breeding and Genetics Group, Wageningen University, Marijkeweg 40, 6709 PG Wageningen, The Netherlands.
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Kerje S, Carlborg O, Jacobsson L, Schütz K, Hartmann C, Jensen P, Andersson L. The twofold difference in adult size between the red junglefowl and White Leghorn chickens is largely explained by a limited number of QTLs. Anim Genet 2003; 34:264-74. [PMID: 12873214 DOI: 10.1046/j.1365-2052.2003.01000.x] [Citation(s) in RCA: 152] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
A large intercross between the domestic White Leghorn chicken and the wild ancestor, the red junglefowl, has been used in a Quantitative Trait Loci (QTL) study of growth and egg production. The linkage map based on 105 marker loci was in good agreement with the chicken consensus map. The growth of the 851 F2 individuals was lower than both parental lines prior to 46 days of age and intermediate to the two parental lines thereafter. The QTL analysis of growth traits revealed 13 loci that showed genome-wide significance. The four major growth QTLs explained 50 and 80% of the difference in adult body weight between the founder populations for females and males, respectively. A major QTL for growth, located on chromosome 1 appears to have pleiotropic effects on feed consumption, egg production and behaviour. There was a strong positive correlation between adult body weight and average egg weight. However, three QTLs affecting average egg weight but not body weight were identified. An interesting observation was that the estimated effects for the four major growth QTLs all indicated a codominant inheritance.
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Affiliation(s)
- S Kerje
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, BMC, Uppsala, Sweden
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