Investigation of Critical Genes and Quantitative Trait Loci Related to Economic Traits in Broiler Chicken Genome Using Protein-Protein Interaction Network

Abdalhag MA, Zhang T, Fan QC, Zhang XQ, Zhang GX, Wang JY, Wei Y, Wang YJ. 2015. Single nucleotide polymorphisms associated with growth traits in Jinghai yellow chickens. Genetics and Molecular Research, 14(4): 16169-77. DOI: 10.4238/2015.December.8.6

Aerts J, Megens HJ, Veenendaal T, Ovcharenko I, Crooijmans RP, Gordon L, Stubbs L & Groenen M. 2007. Extent of linkage disequilibrium in chicken. Cytogenetic and Genome Research, 117(1-4): 338-45. DOI: 10.1159/000103196

Assenov Y, Ramírez F, Schelhorn SE, Lengauer T & Albrecht M. 2008. Computing topological parameters of biological networks. Bioinformatics, 24(2): 282-4. DOI: 10.1093/bioinformatics/btm554

Assou S, Cerecedo D, Tondeur S, Pantesco V, Hovatta O, Klein B, Hamamah S & De Vos J. 2009. A gene expression signature shared by human mature oocytes and embryonic stem cells. BMC Genomics, 10(1): 1-5. DOI: 10.1186/1471-2164-10-10

Bader GD & Hogue CW. 2003. An automated method for finding molecular complexes in large protein interaction networks. BMC Bioinformatics, 4(1): 1-27. DOI: 10.1186/1471-2105-4-2

Bai H, Lu H, Wang L, Wang S, Zeng W & Zhang T. 2021. SNPs analysis of height traits in Ningqiang pony. Animal Biotechnology, 32(5): 566-72. DOI: 10.1080/10495398.2020.1728288

Barkova OY & Smaragdov MG. 2016. Association of a nonsynonymous substitution in the condensin NCAPG gene with traits of eggs in laying hens. Russian Journal of Genetics: Applied Research, 6: 804-8. DOI: 10.1134/S2079059716080037

Brogan MD, Behrend EN & Kemppainen RJ. 2001. Regulation of Dexras1 expression by endogenous steroids. Neuroendocrinology, 74(4): 244-50. DOI: 10.1159/000054691

Charton C, Youm DJ, Ko BJ, Seol D, Kim B, Chai HH, Lim D & Kim H. 2021. The transcriptomic blueprint of molt in rooster using various tissues from Ginkkoridak (Korean long-tailed chicken). BMC Genomics, 22: 1-24. DOI: 10.1186/s12864-021-07903-9

Chatterjee RN, Sharma RP, Mishra A, Dange M & Bhattacharya TK. 2008. Variability of microsatellites and their association with egg production traits in chicken. International Journal of Poultry Science, 7(1): 77-80. DOI: 10.3923/ijps.2008.77.80

Chin CH, Chen SH, Wu HH, Ho CW, Ko MT & Lin CY. 2014. CytoHubba: identifying hub objects and sub-networks from complex interactome. BMC Systems Biology, 8(4): 1-7. DOI: 10.1186/1752-0509-8-S4-S11

Doncheva NT, Assenov Y, Domingues FS, Albrecht M. 2012. Topological analysis and interactive visualization of biological networks and protein structures. Nature Protocols, 7(4): 670-85. DOI: 10.1038/nprot.2012.004

Dou D, Shen L, Zhou J, Cao Z, Luan P, Li Y, Xiao F, Guo H, Li H & Zhang H. 2022. Genome-wide association studies for growth traits in broilers. BMC Genomic Data, 23: 1-9. DOI: 10.1186/s12863-021-01017-7

Dou T, Shen M, Ma M, Qu L, Li Y, Hu Y, Lu J, Guo J, Wang X & Wang K. 2019. Genetic architecture and candidate genes detected for chicken internal organ weight with a 600 K single nucleotide polymorphism array. Asian-Australasian Journal of Animal Sciences, 32(3): 341. DOI: 10.5713/ajas.18.0274

Fritzius T & Moelling K. 2008. Akt‐and Foxo1‐interacting WD‐repeat‐FYVE protein promotes adipogenesis. The EMBO Journal, 27(9): 1399-410. DOI: 10.1038/emboj.2008.67

Groenen MA, Cheng HH, Bumstead N, Benkel BF, Briles WE, Burke T, Burt DW, Crittenden LB, Dodgson J, Hillel J & Lamont S. 2000. A consensus linkage map of the chicken genome. Genome Research, 10(1): 137-47. DOI: 10.1101/gr.10.1.137

Gu X, Feng C, Ma L, Song C, Wang Y, Da Y, Li H, Chen K, Ye S, Ge C & Hu X. 2011. Genome-wide association study of body weight in chicken F2 resource population. PloS One, 6(7): e21872. DOI: 10.1371/journal.pone.0021872

Guo J, Qu L, Dou TC, Shen MM, Hu YP, Ma M & Wang KH. 2020. Genome-wide association study provides insights into the genetic architecture of bone size and mass in chickens. Genome, 63(3): 133-43. DOI: 10.1139/gen-2019-002

Haley CS & Knott SA. 1992. A simple regression method for mapping quantitative trait loci in line crosses using flanking markers. Heredity, 69(4): 315-24. DOI: 10.1038/hdy.1992.131

Hamzić E, Buitenhuis B, Hérault F, Hawken R, Abrahamsen MS, Servin B, Elsen JM, Pinard-van Der Laan MH & Bed’Hom B. 2015. Genome-wide association study and biological pathway analysis of the Eimeria maxima response in broilers. Genetics Selection Evolution, 47: 1-7. DOI: 10.1186/s12711-015-0170-0

Hasegawa N, Sumitomo A, Fujita A, Aritome N, Mizuta S, Matsui K, Ishino R, Inoue K, Urahama N, Nose J & Mukohara T. 2012. Mediator subunits MED1 and MED24 cooperatively contribute to pubertal mammary gland development and growth of breast carcinoma cells. Molecular and Cellular Biology, 32(8): 1483-95. DOI: 10.1186/s12711-015-0170-0

Hu ZL, Fritz ER, Reecy JM. 2007. AnimalQTLdb: a livestock QTL database tool set for positional QTL information mining and beyond. Nucleic Acids Research, 35(suppl_1): D604-9. DOI: 10.1093/nar/gkl946

Hu ZL, Park CA, Wu XL & Reecy JM. 2013. Animal QTLdb: an improved database tool for livestock animal QTL/association data dissemination in the post-genome era. Nucleic Acids Research, 41(D1): D871-9. DOI: 10.1093/nar/gks1150

Kang L, Cui X, Zhang Y, Yang C & Jiang Y. 2013. Identification of miRNAs associated with sexual maturity in chicken ovary by Illumina small RNA deep sequencing. BMC Genomics, 14(1): 1-1. DOI: 10.1186/1471-2164-14-352

Kontou PI, Pavlopoulou A, Dimou NL, Pavlopoulos GA, Bagos PG. 2016. Network analysis of genes and their association with diseases. Gene, 590(1): 68-78. DOI: 10.1016/j.gene.2016.05.044

Lee JH, Kim SW, Han JS, Shin SP, Lee SI & Park TS. 2020. Functional analyses of miRNA-146b-5p during myogenic proliferation and differentiation in chicken myoblasts. BMC Molecular and Cell Biology, 21(1): 1-3. DOI: 10.1186/s12860-020-00284-z

Li K, Zhao B, Wei D, Wang W, Cui Y, Qian L & Liu G. 2020. miR‑146a improves hepatic lipid and glucose metabolism by targeting MED1. International Journal of Molecular Medicine, 45(2): 543-55. DOI: 10.3892/ijmm.2019.4443

Li YD, Liu X, Li ZW, Wang WJ, Li YM, Cao ZP, Luan P, Xiao F, Gao HH, Guo HS & Wang N. 2021. A combination of genome-wide association study and selection signature analysis dissects the genetic architecture underlying bone traits in chickens. Animal, 15(8): 100322. DOI: 10.1016/j.animal.2021.100322

Liu J, Zhou J, Li J & Bao H. 2021. Identification of candidate genes associated with slaughter traits in F2 chicken population using genome‐wide association study. Animal Genetics, 52(4): 532-5. DOI: 10.1111/age.13079

Liu R, Sun Y, Zhao G, Wang F, Wu D, Zheng M, Chen J, Zhang L, Hu Y & Wen J. 2013. Genome-wide association study identifies loci and candidate genes for body composition and meat quality traits in Beijing-You chickens. PLoS One, 8(4): e61172. DOI: 10.1371/journal.pone.0061172

Liu R, Sun Y, Zhao G, Wang H, Zheng M, Li P, Liu L & Wen J. 2015. Identification of loci and genes for growth related traits from a genome-wide association study in a slow-× fast-growing broiler chicken cross. Genes and Genomics, 37: 829-36. DOI: 10.1007/s13258-015-0314-1

Liu Z, Meng J, Li X, Zhu F, Liu T, Wu G & Zhang L. 2018. Identification of hub genes and key pathways associated with two subtypes of diffuse large B-cell lymphoma based on gene expression profiling via integrated bioinformatics. BioMed Research International, 2018. DOI: 10.1155/2018/3574534

Lotia S, Montojo J, Dong Y, Bader GD & Pico AR. 2013. Cytoscape app store. Bioinformatics, 29(10): 1350-1. DOI: 10.1093/bioinformatics/btt138

Lyu S, Arends D, Nassar MK & Brockmann GA. 2017. Fine mapping of a distal chromosome 4 QTL affecting growth and muscle mass in a chicken advanced intercross line. Animal Genetics, 48(3): 295-302. DOI: 10.1111/age.12532

Meslin C, Desert C, Callebaut I, Djari A, Klopp C, Pitel F, Leroux S, Martin P, Froment P, Guilbert E & Gondret F. 2015. Expanding duplication of free fatty acid receptor-2 (GPR43) genes in the chicken genome. Genome Biology and Evolution, 7(5): 1332-48. DOI: 10.1093/gbe/evv072

Metzger J, Schrimpf R, Philipp U & Distl O. 2013. Expression levels of LCORL are associated with body size in horses. PloS One, 8(2): e56497. DOI: 10.1371/journal.pone.0056497

Mohammadabadi M, Bordbar F, Jensen J, Du M, Guo W. 2021. Key Genes Regulating Skeletal Muscle Development and Growth in Farm Animals. Animals, 835. DOI: 10.3390/ani11030835

Nangsuay A, Ruangpanit Y, Meijerhof R & Attamangkune S. 2011. Yolk absorption and embryo development of small and large eggs originating from young and old breeder hens. Poultry Science, 90(11): 2648-55. DOI: 10.3382/ps.2011-01415

Piórkowska K, Żukowski K, Tyra M, Szyndler-Nędza M, Szulc K, Skrzypczak E, Ropka-Molik K. 2019. The pituitary transcriptional response related to feed conversion in pigs. Genes, 10(9): 712. DOI: 10.3390/genes10090712

Seo D, Lee DH, Choi N, Sudrajad P, Lee SH & Lee JH. 2018. Estimation of linkage disequilibrium and analysis of genetic diversity in Korean chicken lines. PLoS One, 13(2): e0192063. DOI: 10.1371/journal.pone.0192063

Setoguchi K, Furuta M, Hirano T, Nagao T, Watanabe T, Sugimoto Y & Takasuga A. 2009. Cross-breed comparisons identified a critical 591-kb region for bovine carcass weight QTL (CW-2) on chromosome 6 and the Ile-442-Met substitution in NCAPG as a positional candidate. BMC Genetics, 10(1): 1-2. DOI: 10.1186/1471-2156-10-43

Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B & Ideker T. 2003. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Research, 13(11): 2498-504. DOI: 10.1101/gr.1239303

Shen M, Qu L, Ma M, Dou T, Lu J, Guo J, Hu Y, Wang X, Li Y, Wang K & Yang N. 2017. A genome-wide study to identify genes responsible for oviduct development in chickens. PLoS One, 12(12): e0189955. DOI: 10.1371/journal. pone.0189955

Sillanpää MJ & Corander J. 2002. Model choice in gene mapping: what and why. Trends in Genetics, 18(6): 301-7. DOI: 10.1016/S0168-9525(02)02688-4

Suchocki T, Wojdak-Maksymiec K & Szyda J. 2016. Using gene networks to identify genes and pathways involved in milk production traits in Polish Holstein dairy cattle. Czech Journal of Animal Science, 61(11): 526-538. DOI: 10.5555/20163388314

Sun C, Qu L, Yi G, Yuan J, Duan Z, Shen M, Qu L, Xu G, Wang K & Yang N. 2015. Genome-wide association study revealed a promising region and candidate genes for eggshell quality in an F 2 resource population. BMC Genomics, 16: 1-4. DOI: 10.1186/s12864-015-1795-7

Szklarczyk D, Franceschini A, Wyder S, Forslund K, Heller D, Huerta-Cepas J, Simonovic M, Roth A, Santos A, Tsafou KP, Kuhn M. 2015. STRING v10: protein–protein interaction networks, integrated over the tree of life. Nucleic Acids Research, 43(D1): D447-52. DOI: 10.1093/nar/gku1003

Taheri S, Saedi N, Zerehdaran S, Javadmanesh A. 2023. Identification of selection signatures in Capra hircus and Capra aegagrus in Iran. Animal Science Journal, 94(1): e13864. DOI: 10.1111/asj.13864

Tarsani E, Kranis A, Maniatis G, Avendano S, Hager-Theodorides AL & Kominakis A. 2019. Discovery and characterization of functional modules associated with body weight in broilers. Scientific Reports, 9(1): 9125. DOI: 10.1038/s41598-019-45520-5

Tetens J, Widmann P, Kühn C & Thaller G. 2013. A genome‐wide association study indicates LCORL/NCAPG as a candidate locus for withers height in G erman W armblood horses. Animal Genetics, 44(4): 467-71. DOI: 10.1111/age.12031

Van Goor A, Bolek KJ, Ashwell CM, Persia ME, Rothschild MF, Schmidt CJ & Lamont SJ. 2015. Identification of quantitative trait loci for body temperature, body weight, breast yield, and digestibility in an advanced intercross line of chickens under heat stress. Genetics Selection Evolution, 47(1): 1-3. DOI: 10.1186/s12711-015-0176-7

Verardo LL, Lopes MS, Wijga S, Madsen O, Silva FF, Groenen MA, Knol EF, Lopes PS & Guimarães SE. 2016. After genome-wide association studies: Gene networks elucidating candidate genes divergences for number of teats across two pig populations. Journal of Animal Science, 94(4): 1446-58. DOI: 10.2527/jas.2015-9917

Wakchaure R, Ganguly S, Praveen PK, Kumar A, Sharma S, & Mahajan T. 2015. Marker assisted selection (MAS) in animal breeding: a review. Journal of Drug Metabolism and Toxicology, 6(5): e127. DOI: 10.4172/2157-7609.1000e127

Walugembe M, Bertolini F, Dematawewa CM, Reis MP, Elbeltagy AR, Schmidt CJ, Lamont SJ & Rothschild MF. 2019. Detection of selection signatures among Brazilian, Sri Lankan, and Egyptian chicken populations under different environmental conditions. Frontiers in Genetics, 9: 737. DOI: 10.3389/fgene.2018.00737

Wang S, Wang Y, Li Y, Xiao F, Guo H, Gao H, Wang N, Zhang H, Li H. 2022. Genome-wide association study and selective sweep analysis reveal the genetic architecture of body weights in a chicken F2 resource population. Frontiers in Veterinary Science, 9: 875454. DOI: 10.3389/fvets.2022.875454

Wang W, Zhang T, Wang J, Zhang G, Wang Y, Zhang Y, Zhang J, Li G, Xue Q, Han K & Zhao X. 2016. Genome-wide association study of 8 carcass traits in Jinghai Yellow chickens using specific-locus amplified fragment sequencing technology. Poultry Science, 95(3): 500-6. DOI: 10.3382/ps/pev266

Wang Y, Li J, Feng C, Zhao Y, Hu X & Li N. 2017. Transcriptome analysis of comb and testis from Rose-comb Silky chicken (R1/R1) and Beijing Fatty wild type chicken (r/r). Poultry Science, 96(6): 1866-73. DOI: 10.3382/ps/pew447

Weikard R, Altmaier E, Suhre K, Weinberger KM, Hammon HM, Albrecht E, Setoguchi K, Takasuga A & Kühn C. 2010. Metabolomic profiles indicate distinct physiological pathways affected by two loci with major divergent effect on Bos taurus growth and lipid deposition. Physiological Genomics, 42(2): 79-88. DOI: 10.1152/physiolgenomics.00120.2010

Widmann P, Reverter A, Weikard R, Suhre K, Hammon HM, Albrecht E & Kuehn C. 2015. 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(4): e0124574. DOI: 10.1371/journal.pone.0124574

Wolc A, Arango J, Jankowski T, Settar P, Fulton JE, O'Sullivan NP, Fernando R, Garrick DJ & Dekkers JC. 2013. Pedigree and genomic analyses of feed consumption and residual feed intake in laying hens. Poultry Science, 92(9): 2270-5. DOI: 10.3382/ps.2013-03085

Womack JE. 2005. Advances in livestock genomics: opening the barn door. Genome Research, 15(12): 1699-705. DOI: 10.1101/gr.3809105

Xiao C, Sun T, Yang Z, Xu W, Wang J, Zeng L, Deng J & Yang X. 2021. Transcriptome landscapes of differentially expressed genes related to fat deposits in Nandan-Yao chicken. Functional & Integrative Genomics, 21: 113-24. DOI: 10.1007/s10142-020-00764-7

Yang L, He T, Xiong F, Chen X, Fan X, Jin S & Geng Z. 2020. Identification of key genes and pathways associated with feed efficiency of native chickens based on transcriptome data via bioinformatics analysis. BMC Genomics, 21: 1-8. DOI: 10.1186/s12864-020-6713-y

Yao K, Yin YL, Chu W, Liu Z, Deng D, Li T, Huang R, Zhang J, Tan B, Wang W & Wu G. 2010. Dietary arginine supplementation increases mTOR signaling activity in skeletal muscle of neonatal pigs. The Journal of Nutrition, 138(5): 867-72. DOI: 10.5555/20103009871

Ye S, Chen Z, Zheng R, Diao S, Teng J, Yuan X, Zhang H, Chen Z, Zhang X, Li J & Zhang Z. 2019. New insights from genome-wide association analysis using imputed whole-genome sequence: The genetic mechanisms underlying residual feed intake in chickens. PREPRINT (Version 1) Available at Research Square. DOI: 10.21203/rs.2.15454/v1

Ye S, Chen ZT, Zheng R, Diao S, Teng J, Yuan X, Zhang H, Chen Z, Zhang X, Li J & Zhang Z. 2020. New insights from imputed whole-genome sequence-based genome-wide association analysis and transcriptome analysis: the genetic mechanisms underlying residual feed intake in chickens. Frontiers in Genetics, 11: 243. DOI: 10.3389/fgene.2020.00243

Yeung LW, Guruge KS, Yamanaka N, Miyazaki S & Lam PK. 2007. Differential expression of chicken hepatic genes responsive to PFOA and PFOS. Toxicology, 237(1-3): 111-25. DOI: 10.1016/j.tox.2007.05.004

Yi G, Shen M, Yuan J, Sun C, Duan Z, Qu L, Dou T, Ma M, Lu J, Guo J & Chen S. 2015. Genome-wide association study dissects genetic architecture underlying longitudinal egg weights in chickens. BMC Genomics., 16: 1-4. DOI: 10.1186/s12864-015-1945-y

Zhang H, Hu X, Wang Z, Zhang Y, Wang S, Wang N, Ma L, Leng L, Wang S, Wang Q & Wang Y. 2012. Selection signature analysis implicates the PC1/PCSK1 region for chicken abdominal fat content. PloS One, 7(7): e40736. DOI: 10.1371/journal.pone.0040736

Zhang J, Duan Z, Wang X, Li F, Chen J, Lai X, Qu L, Sun C & Xu G. 2021. Screening and validation of candidate genes involved in the regulation of egg yolk deposition in chicken. Poultry Science, 100(6): 101077. DOI: 10.1016/j.psj.2021.101077

Zhang Q, Yang Y, Lu Y & Cao Z. 2021. iTRAQ-based quantitative proteomic analyses the cycle chronic heat stress affecting liver proteome in yellow-feather chickens. Poultry Science, 100(6): 101111. DOI: 10.1016/j.psj.2021.101111

Zhi Y, Wang D, Zhang K, Wang Y, Geng W, Chen B, Li H, Li Z, Tian Y, Kang X & Liu X. 2023 Genome-Wide Genetic Structure of Henan Indigenous Chicken Breeds. Animals, 13(4): 753. DOI: /10.3390/ani13040753

Zhu H, Shyh-Chang N, Segrè AV, Shinoda G, Shah SP, Einhorn WS, Takeuchi A, Engreitz JM, Hagan JP, Kharas MG & Urbach A. 2011. The Lin28/let-7 axis regulates glucose metabolism. Cell, 147(1): 81-94. DOI: 10.1016/j.cell.2011.08.033

Zhu Z, Hayart Y, Yang J, Cao L, Lou X, Xu H. 2012. Statistical method for mapping QTLs for complex traits based on two backcross populations. Chinese Science Bulletin, 57: 2645-54. DOI: 10.1007/s11434-012-5279-8