Genetic architecture and candidate genes detected for chicken internal organ weight with a 600 K single nucleotide polymorphism array
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Objective: Internal organs indirectly affect economic performance and well-being of animals. Study of internal organs during later layer period will allow full utilization of layer hens. Hence, we conducted a genome-wide association study (GWAS) to identify potential quantitative trait loci or genes that potentially contribute to internal organ weight. Methods: A total of 1,512 chickens originating from White Leghorn and Dongxiang Blue-Shelled chickens were genotyped using high-density Affymetrix 600 K single nucleotide polymorphism (SNP) array. We conducted a GWAS, linkage disequilibrium analysis, and heritability estimated based on SNP information by using GEMMA, Haploview and GCTA software. Results: Our results displayed that internal organ weights show moderate to high (0.283 to 0.640) heritability. Variance partitioned across chromosomes and chromosome lengths had a linear relationship for liver weight and gizzard weight (R2 = 0.493, 0.753). A total of 23 highly significant SNPs that associated with all internal organ weights were mainly located on Gallus gallus autosome (GGA) 1 and GGA4. Six SNPs on GGA2 affected heart weight. After the final analysis, five top SNPs were in or near genes 5-Hydroxytryptamine receptor 2A, general transcription factor IIF polypeptide 2, WD repeat and FYVE domain containing 2, non-SMC condensin I complex subunit G, and sonic hedgehog, which were considered as candidate genes having a pervasive role in internal organ weights. Conclusion: Our findings provide an understanding of the underlying genetic architecture of internal organs and are beneficial in the selection of chickens.
Abstract
Objective: Internal organs indirectly affect economic performance and well-being of animals. Study of internal organs during later layer period will allow full utilization of layer hens. Hence, we conducted a genome-wide association study (GWAS) to identify potential quantitative trait loci or genes that potentially contribute to internal organ weight. Methods: A total of 1,512 chickens originating from White Leghorn and Dongxiang Blue-Shelled chickens were genotyped using high-density Affymetrix 600 K single nucleotide polymorphism (SNP) array. We conducted a GWAS, linkage disequilibrium analysis, and heritability estimated based on SNP information by using GEMMA, Haploview and GCTA software. Results: Our results displayed that internal organ weights show moderate to high (0.283 to 0.640) heritability. Variance partitioned across chromosomes and chromosome lengths had a linear relationship for liver weight and gizzard weight (R2 = 0.493, 0.753). A total of 23 highly significant SNPs that associated with all internal organ weights were mainly located on Gallus gallus autosome (GGA) 1 and GGA4. Six SNPs on GGA2 affected heart weight. After the final analysis, five top SNPs were in or near genes 5-Hydroxytryptamine receptor 2A, general transcription factor IIF polypeptide 2, WD repeat and FYVE domain containing 2, non-SMC condensin I complex subunit G, and sonic hedgehog, which were considered as candidate genes having a pervasive role in internal organ weights. Conclusion: Our findings provide an understanding of the underlying genetic architecture of internal organs and are beneficial in the selection of chickens.
참고문헌 (45)
- He Y, "Multi-breed genome-wide association study reveals novel loci associated with the weight of internal organs", Genet Sel Evol, 47, pp.87~ (2015)
- Gruber M, "Hormonal control of vitellogenin synthesis in avian liver", Mol Cell Endocrinol, 5, pp.41~50 (1976)
- Ayala I, "Hyperlipidemic chicken as a model of non-alcoholic steatohepatitis", Exp Biol Med(Maywood), 234, pp.10~16 (2009)
- Zhang LF, "Expression pattern of HIF1alpha mRNA in brain, heart and liver tissues of Tibet chicken embryos in hypoxia revealed with quantitative real-time PCR", Animal, 1, pp.1467~1471 (2007)
- Svihus B, "The gizzard : function, influence of diet structure and effects on nutrient availability", Worlds Poult Sci J, 67, pp.207~224 (2011)
- Richards MP, "Genetic regulation of feed intake and energy balance in poultry", Poult Sci, 82, pp.907~916 (2003)
- Maiti AK, "Effect of natural tenderizers on physico-chemical properties of chicken gizzard and goat heart", Am J Food Technol, 6, pp.80~86 (2011)
- Nones K, "Mapping QTLs on chicken chromosome 1 for performance and carcass traits in a broiler x layer cross", Anim Genet, 37, pp.95~100 (2006)
- Rosário MFd, "Genotypic characterization of microsatellite markers in broiler and layer selected chicken lines and their reciprocal F1s", Sci Agric, 66, pp.150~158 (2009)
- Boschiero C, "Associations between microsatellite markers and traits related to performance, carcass and organs in chickens", Int J Poult Sci, 8, pp.615~620 (2009)
- Yuan J, "Genetic parameters of feed efficiency traits in laying period of chickens", Poult Sci, 94, pp.1470~1475 (2015)
- Shen M, "Genetic architecture and candidate genes identified for follicle number in chicken", Sci Rep, 7, pp.16412~ (2017)
- Jun G, "Random regression analyses to model the longitudinal measurements of yolk proportions in the laying chicken", Poult Sci, 96, pp.3852~3857 (2017)
- Purcell S, "PLINK : a tool set for whole-genome association and population-based linkage analyses", Am J Hum Genet, 81, pp.559~575 (2007)
- Browning BL, "A unified approach to genotype imputation and haplotype-phase inference for large data sets of trios and unrelated individuals", Am J Hum Genet, 84, pp.210~223 (2009)
- Zhou X, "Genome-wide efficient mixed-model analysis for association studies", Nat Genet, 44, pp.821~824 (2012)
- Yang J, "GCTA : a tool for genome-wide complex trait analysis", Am J Hum Genet, 88, pp.76~82 (2011)
- Deeb N, "Genetic architecture of growth and body composition in unique chicken populations", J Hered, 93, pp.107~118 (2002)
- Nunes Bdo N, "Genetic parameters for body weight, carcass chemical composition and yield in a broiler-layer cross developed for QTL mapping", Genet Mol Biol, 34, pp.429~434 (2011)
- Venturini GC, "Genetic and phenotypic parameters of carcass and organ traits of broiler chickens", Genet Mol Res, 13, pp.10294~10300 (2014)
- Nitsan Z, "Organ growth and digestive enzyme levels to fifteen days of age in lines of chickens differing in body weight", Poult Sci, 70, pp.2040~2048 (1991)
- Gao G, "Transcriptome profiling of the hypothalamus during prelaying and laying periods in Sichuan white geese(Anser cygnoides)", Anim Sci J, 86, pp.800~805 (2015)
- Yi G, "Genome-wide association study dissects genetic architecture underlying longitudinal egg weights in chickens", BMC Genomics, 16, pp.746~ (2015)
- Navarro P, "Mapping of quantitative trait loci affecting organ weights and blood variables in a broiler layer cross", Br Poult Sci, 46, pp.430~442 (2005)
- Shen M, "Genome-wide association studies for comb traits in chickens", PLoS One, 11, pp.e0159081~ (2016)
- Sun C, "Promising loci and genes for yolk and ovary weight in chickens revealed by a genome-wide association study", PloS one, 10, pp.e0137145~ (2015)
- Yuan J, "Genome-wide association studies for feed intake and efficiency in two laying periods of chickens", Genet Sel Evol, 47, pp.82~ (2015)
- Zhang H, "Detection and fine mapping of quantitative trait loci for bone traits on chicken chromosome one", J Anim Breed Genet, 127, pp.462~468 (2010)
- Liu X, "Fine-mapping quantitative trait loci for body weight and abdominal fat traits : effects of marker density and sample size", Poult Sci, 87, pp.1314~1319 (2008)
- W. H. Wang, "Genome‐wide association study of growth traits in Jinghai Yellow chicken hens using SLAF‐seq technology", Animal Genetics (2015)[DOI]
- Hodgkin J, "Seven types of pleiotropy", Int J Dev Biol, 42, pp.501~505 (1998)
- Nagatomo T, "Functions of 5-HT 2A receptor and its antagonists in the cardiovascular system", Pharmacol Ther, 104, pp.59~81 (2004)
- Nichols CD, "Serotonin 5-HT2A receptor function as a contributing factor to both neuropsychiatric and cardiovascular diseases", Cardiovasc Psychiatry Neurol, 2009, pp.475108~ (2009)
- Hartman FA, "Heart weight in birds", Condor, 57, pp.221~238 (1955)
- Sopta M, "Structure and associated DNA-helicase activity of a general transcription initiation factor that binds to RNA polymerase II", Nature, 341, pp.410~414 (1989)
- Milagro FI, "Weight gain induced by high-fat feeding involves increased liver oxidative stress", Obesity(Silver Spring), 14, pp.1118~1123 (2006)
- Hu K, "Expression patterns analysis of the RNA biosynthesis, processing, transporting or catabolism-associated genes during rat liver regeneration", Life Sci J, 5, pp.1~8 (2008)
- Kannan K, "CDKN2D-WDFY2 is a cancer-specific fusion gene recurrent in high-grade serous ovarian carcinoma", PLoS Genet, 10, pp.e1004216~ (2014)
- Fritzius T, "Akt-and Foxo1-interacting WD-repeat-FYVE protein promotes adipogenesis", EMBO J, 27, pp.1399~1410 (2008)
- Shen M, "A genome-wide study to identify genes responsible for oviduct development in chickens", PLoS One, 12, pp.e0189955~ (2017)
- Widmann P, "Systems biology analysis merging phenotype, metabolomic and genomic data identifies Non-SMC Condensin I Complex, Subunit G (NCAPG) and cellular maintenance processes as major contributors to genetic variability in bovine feed efficiency", PLoS One, 10, pp.e0124574~ (2015)
- Tetens J, "A genome-wide association study indicates LCORL", NCAPG as a candidate locus for withers height in German Warmblood horses, 2013, pp.44, 467~471
- Abasht B, "Review of quantitative trait loci identified in the chicken", Poult Sci, 85, pp.2079~2096 (2006)
- Balaskas N, "Gene regulatory logic for reading the Sonic Hedgehog signaling gradient in the vertebrate neural tube", Cell, 148, pp.273~284 (2012)
- Dyer LA, "Sonic hedgehog maintains proliferation in secondary heart field progenitors and is required for normal arterial pole formation", Dev Biol, 330, pp.305~317 (2009)