Combined transcriptomics and proteomics forecast analysis for potential genes regulating the Columbian plumage color in chickens
Autoři:
Xinlei Wang aff001; Donghua Li aff001; Sufang Song aff002; Yanhua Zhang aff001; Yuanfang Li aff001; Xiangnan Wang aff001; Danli Liu aff001; Chenxi Zhang aff001; Yanfang Cao aff001; Yawei Fu aff001; Ruili Han aff001; Wenting Li aff001; Xiaojun Liu aff001; Guirong Sun aff001; Guoxi Li aff001; Yadong Tian aff001; Zhuanjian Li aff001; Xiangtao Kang aff001
Působiště autorů:
College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan, China
aff001; College of Animal Science and Technology, Henan University of Animal Husbandry and Economy, Zhengzhou, Henan, China
aff002
Vyšlo v časopise:
PLoS ONE 14(11)
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0210850
Souhrn
Background
Coloration is one of the most recognizable characteristics in chickens, and clarifying the coloration mechanisms will help us understand feather color formation. “Yufen I” is a commercial egg-laying chicken breed in China that was developed by a three-line cross using lines H, N and D. Columbian plumage is a typical feather character of the “Yufen I” H line. To elucidate the molecular mechanism underlying the pigmentation of Columbian plumage, this study utilizes high-throughput sequencing technology to compare the transcriptome and proteome differences in the follicular tissue of different feathers, including the dorsal neck with black and white striped feather follicles (Group A) and the ventral neck with white feather follicles (Group B) in the “Yufen I” H line.
Results
In this study, we identified a total of 21,306 genes and 5,203 proteins in chicken feather follicles. Among these, 209 genes and 382 proteins were differentially expressed in two locations, Group A and Group B, respectively. A total of 8 differentially expressed genes (DEGs) and 9 differentially expressed proteins (DEPs) were found to be involved in the melanogenesis pathway. Additionally, a specifically expressed MED23 gene and a differentially expressed GNAQ protein were involved in melanin synthesis. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis mapped 190 DEGs and 322 DEPs to 175 and 242 pathways, respectively, and there were 166 pathways correlated with both DEGs and DEPs. 49 DEPs/DEGs overlapped and were enriched for 12 pathways. Transcriptomic and proteomic analyses revealed that the following pathways were activated: melanogenesis, cardiomyocyte adrenergic, calcium and cGMP-PKG. The expression of DEGs was validated by real-time quantitative polymerase chain reaction (qRT-PCR) that produced results similar to those from RNA-seq. In addition, we found that the expression of the MED23, FZD10, WNT7B and WNT11 genes peaked at approximately 8 weeks in the “Yufen I” H line, which is consistent with the molting cycle. As both groups showed significant differences in terms of the expression of the studied genes, this work opens up avenues for research in the future to assess their exact function in determining plumage color.
Conclusion
Common DEGs and DEPs were enriched in the melanogenesis pathway. MED23 and GNAQ were also reported to play a crucial role in melanin synthesis. In addition, this study is the first to reveal gene and protein variations in in the “Yufen I” H line during Columbian feather color development and to discover principal genes and proteins that will aid in functional genomics studies in the future. The results of the present study provide a significant conceptual basis for the future breeding schemes with the “Yufen I” H line and provide a basis for research on the mechanisms of feather pigmentation.
Klíčová slova:
Feathers – Gene expression – Gene regulation – Chickens – Melanin – Proteomes – RNA sequencing – Transcriptome analysis
Zdroje
1. Keiji K, Toyoko A, Makoto M, Ai S, Akira I, Hassan YH, et al. Endothelin Receptor B2 (EDNRB2) Is Responsible for the Tyrosinase-Independent Recessive White (mow) and Mottled (mo) Plumage Phenotypes in the Chicken. Plos One. 2014; 9: e86361. doi: 10.1371/journal.pone.0086361 24466053
2. Vickrey AI, Rebecca B, Zev K, Emma M, J BR, T ME, et al. Introgression of regulatory alleles and a missense coding mutation drive plumage pattern diversity in the rock pigeon. Elife. 2018; 7: e34803–. doi: 10.7554/eLife.34803 30014848
3. Cooke TF, Fischer CR, Wu P, Jiang TX, Bustamante CD. Genetic Mapping and Biochemical Basis of Yellow Feather Pigmentation in Budgerigars. Cell. 2017; 171: 427–439. doi: 10.1016/j.cell.2017.08.016 28985565
4. Oro AE, Scott MP. Splitting hairs: dissecting roles of signaling systems in epidermal development. Cell. 1998; 95: 575–578. doi: 10.1016/s0092-8674(00)81624-4 9845357
5. Hardy MH. The secret life of the hair follicle. Trends in Genetics. 1992; 8: 55–61. doi: 10.1016/0168-9525(92)90350-d 1566372
6. Galbraith H, Galbraith H. Fundamental hair follicle biology and fine fibre production in animals. Animal. 2010; 4: 1490–1509. doi: 10.1017/S175173111000025X 22444696
7. Alexeev V, Igoucheva O, Domashenko A, Cotsarelis G, Yoon K. Localized in vivo genotypic and phenotypic correction of the albino mutationin skin by RNA-DNA oligonucleotide. Nature Biotechnology. 2000; 18: 43–47. doi: 10.1038/71901 10625389
8. Demehri S, Kopan R. Notch signaling in bulge stem cells is not required for selection of hair follicle fate. Development. 2009; 136: 891. doi: 10.1242/dev.030700 19211676
9. Englaro W, Rezzonico R, Durand-ClãMent M, Lallemand D, Ortonne JP, Ballotti R. Mitogen-activated protein kinase pathway and AP-1 are activated during cAMP-induced melanogenesis in B-16 melanoma cells. Journal of Biological Chemistry. 1995; 270: 24315–24320. doi: 10.1074/jbc.270.41.24315 7592642
10. Grichnik JM, Burch JA, Burchette J, Shea CR. The SCF/KIT pathway plays a critical role in the control of normal human melanocyte homeostasis. Journal of Dermatological Science. 1998; 16: 233–238.
11. Oka M, Nagai H, Ando H, Fukunaga M, Matsumura M, Araki K, et al. Regulation of melanogenesis through phosphatidylinositol 3-kinase-Akt pathway in human G361 melanoma cells. Journal of Investigative Dermatology. 2000; 115: 699–703. doi: 10.1046/j.1523-1747.2000.00095.x 10998146
12. Sharov AA, Fessing M, Atoyan R, Sharova TY, Haskellluevano C, Weiner L, et al. Bone morphogenetic protein (BMP) signaling controls hair pigmentation by means of cross-talk with the melanocortin receptor-1 pathway. Proceedings of the National Academy of Sciences of the United States of America. 2005; 102: 93–98. doi: 10.1073/pnas.0408455102 15618398
13. Schouwey K, Beermann F. The Notch pathway: hair graying and pigment cell homeostasis. Histology & Histopathology. 2008; 23: 609.
14. Li X, Guo L, Sun Y, Zhou J, Gu Y, Li Y. Baicalein inhibits melanogenesis through activation of the ERK signaling pathway. International Journal of Molecular Medicine. 2010; 25: 923–927. doi: 10.3892/ijmm_00000423 20428797
15. Chiang HM, Chien YC, Wu CH, Kuo YH, Wu WC, Pan YY, et al. Hydroalcoholic extract of Rhodiola rosea L. (Crassulaceae) and its hydrolysate inhibit melanogenesis in B16F0 cells by regulating the CREB/MITF/tyrosinase pathway. Food & Chemical Toxicology. 2014; 65: 129–139.
16. Yeo GSH, Farooqi IS, Challis BG, Jackson RS, O'Rahilly S. The role of melanocortin signalling in the control of body weight: evidence from human and murine genetic models. Qjm Monthly Journal of the Association of Physicians. 2000; 93: 7–14. doi: 10.1093/qjmed/93.1.7 10623776
17. Pape EL, Wakamatsu K, Ito S, Wolber R, Hearing VJ. Regulation of eumelanin / pheomelanin synthesis and visible pigmentation in melanocytes by ligands of the melanocortin 1 receptor. Pigment Cell & Melanoma Research. 2008; 21: 477–486.
18. V?Ge DI, Nieminen M, Anderson DG, R?Ed KH. Two missense mutations in melanocortin 1 receptor (MC1R) are strongly associated with dark ventral coat color in reindeer (Rangifer tarandus). Animal Genetics. 2015; 45: 750–753.
19. Liu F, Kohlmeier S, Wang CY. Wnt signaling and skeletal development. Cellular Signalling. 2008; 20: 999–1009. doi: 10.1016/j.cellsig.2007.11.011 18164181
20. Chen AE, Ginty DD, Fan CM. Protein kinase A signalling via CREB controls myogenesis induced by Wnt proteins. Nature. 2005; 433: 317–322. doi: 10.1038/nature03126 15568017
21. Wagner AJ, Fisher DE. Melanocyte signaling pathways and the etiology of melanoma. Drug Discovery Today Disease Mechanisms. 2006; 2: 179–183.
22. Russell M, Hoeffler JP. Signal transduction and the regulation of cell growth. The journal of investigative dermatology Symposium proceedings / the Society for Investigative Dermatology, Inc [and] European Society for Dermatological Research. 1996; 1: 119.
23. Hubbard JK, Uy JAC, Hauber ME, Hoekstra HE, Safran RJ. Vertebrate pigmentation: from underlying genes to adaptive function. Trends in Genetics. 2010; 26: 231–239. doi: 10.1016/j.tig.2010.02.002 20381892
24. Klungland H, Vage DI. Molecular Genetics of Pigmentation in Domestic Animals. Current Genomics. 2000; 1: -. doi: 10.2174/1389202003351535
25. Chang CM, Coville JL, Coquerelle G, Gourichon D, Oulmouden A, Tixier-Boichard M. Complete association between a retroviral insertion in the tyrosinase gene and the recessive white mutation in chickens. Bmc Genomics. 2006; 7: 19–19. doi: 10.1186/1471-2164-7-19 16457736
26. Sato S, Otake T, Suzuki C, Saburi J, Kobayashi E, Mapping of the recessive white locus and analysis of the tyrosinase gene in chickens. Poult Sci. 2007; 86: 2126–2133. doi: 10.1093/ps/86.10.2126 17878441
27. Yang L, Du X, Wei S, Gu L, Li N, Gong Y, et al. Genome-wide association analysis identifies potential regulatory genes for eumelanin pigmentation in chicken plumage. Animal Genetics. 2017; 48: 611. doi: 10.1111/age.12573 28639704
28. Slominski A, Wortsman J, Plonka PM, Schallreuter KU, Paus R, Tobin DJ. Hair Follicle Pigmentation. Journal of Investigative Dermatology. 2004; 124: 13–21.
29. Dupin E, Glavieux C, Vaigot P, Douarin NML. Endothelin 3 Induces the Reversion of Melanocytes to Glia through a Neural Crest-Derived Glial-Melanocytic Progenitor. Proceedings of the National Academy of Sciences of the United States of America. 2000; 97: 7882. doi: 10.1073/pnas.97.14.7882 10884419
30. Mills MG, Patterson LB. Not just black and white: Pigment pattern development and evolution in vertebrates. Seminars in Cell & Developmental Biology. 2009; 20: 72–81.
31. Li L, Li D, Liu L, Li S, Feng Y, Peng X, et al. Endothelin Receptor B2 (EDNRB2) Gene Is Associated with Spot Plumage Pattern in Domestic Ducks (Anas platyrhynchos). Plos One. 2015; 10: e0125883. doi: 10.1371/journal.pone.0125883 25955279
32. Gunnarsson U, Hellstrom A, Tixier-Boichard M, Minvielle F, Bed'Hom B, Ito S, et al. Mutations in SLC45A2 cause plumage color variation in chicken and Japanese quail. Genetics. 2007; 175: 867. doi: 10.1534/genetics.106.063107 17151254
33. Liu WB, Chen SR, Zheng JX, Qu LJ, Xu GY, Yang N. Developmental phenotypic-genotypic associations of tyrosinase and melanocortin 1 receptor genes with changing profiles in chicken plumage pigmentation. Poultry Science. 2010; 89: 1110. doi: 10.3382/ps.2010-00628 20460655
34. S K, P S, U G, H K, S B, R F, et al. The Dominant white, Dun and Smoky color variants in chicken are associated with insertion/deletion polymorphisms in the PMEL17 gene. Genetics. 2004; 168: 1507–1518. doi: 10.1534/genetics.104.027995 15579702
35. Yeo J, Lee Y, Hyeong KE, Ha J, Yi JK, Kim B, et al. Detection of exonic variants within the melanocortin 1 receptor (MC1R) gene in Black Silky, White Leghorn and Golden duckwing Araucana chicken. Molecular Biology Reports. 2014; 41: 4843–4846. doi: 10.1007/s11033-014-3394-0 24830563
36. Hoekstra HE. Genetics, development and evolution of adaptive pigmentation in vertebrates. Heredity. 2006; 97: 222–234. doi: 10.1038/sj.hdy.6800861 16823403
37. Z R, E B, A B, D W. From tyrosine to melanin: Signaling pathways and factors regulating melanogenesis. Postepy Hig Med Dosw. 2016; 70: 695–708.
38. Sultana H, Seo D, Choi NR, Msa B, Lee SH, Heo KN, et al. Identification of polymorphisms inMITFandDCTgenes and their associations with plumage colors in Asian duck breeds. Asian-Australas J Anim Sci. 2018; 31: 180–188. doi: 10.5713/ajas.17.0298 28823136
39. Lin SJ, Foley J, Jiang TX, Yeh CY, Wu P, Foley A, et al. Topology of feather melanocyte progenitor niche allows complex pigment patterns to emerge. Science. 2013; 340: 1442–1445. doi: 10.1126/science.1230374 23618762
40. Hoekstraweebers JEHM, Hubbard BK, Hauber ME, Uy JAC, Safran RJ. Vertebrate pigmentation: from underlying genes to adaptive function. Trends in Genetics. 2010; 26: 231–239. doi: 10.1016/j.tig.2010.02.002 20381892
41. Liu X, Zhou R, Peng Y, Zhang C, Li L, Lu C, et al. Hair follicles transcriptome profiles in Bashang long-tailed chickens with different plumage colors. Genes & Genomics. 2018:
42. Jing Y, Yanhua Q, Yuan H, Fumin L. Dynamic transcriptome profiling towards understanding the morphogenesis and development of diverse feather in domestic duck. Bmc Genomics. 2018; 19: 391. doi: 10.1186/s12864-018-4778-7 29793441
43. Chen Siang Ng, Chen C-K, Fan W-L, Wu P, Wu S-M. Transcriptomic analyses of regenerating adult feathers in chicken. BMC Genomics. 2015; 16: 756. doi: 10.1186/s12864-015-1966-6 26445093
44. Gong H, Wang H, Wang YX, Bai X, Zhang WG. Skin transcriptome reveals the dynamic changes in the Wnt pathway during integument morphogenesis of chick embryos. Plos One. 2018; 13: e0190933. doi: 10.1371/journal.pone.0190933 29351308
45. Li A, Figueroa S, Jiang T-X, Wu P, Widelitz R, Nie Q, et al. Diverse feather shape evolution enabled by coupling anisotropic signalling modules with self-organizing branching programme. Nature Communications. 2017; 8: ncomms14139. doi: 10.1038/ncomms14139 28106042
46. Zhang L, Nie Q, Su Y, Xie X, Luo W, Jia X, et al. MicroRNA profile analysis on duck feather follicle and skin with high-throughput sequencing technology. Gene. 2013; 519: 77–81. doi: 10.1016/j.gene.2013.01.043 23384715
47. Shen S, Park JW, Lu ZX, Lin L, Henry MD, Wu YN, et al. rMATS: robust and flexible detection of differential alternative splicing from replicate RNA-Seq data. Proc Natl Acad Sci U S A. 2014; 111: 5593–5601.
48. Kim D, Langmead B, Salzberg SL. HISAT: a fast spliced aligner with low memory requirements. Nature Methods. 2015; 12: 357–360. doi: 10.1038/nmeth.3317 25751142
49. S A, JM C. The significance of digital gene expression profiles. Genome Research. 1997; 7: 986–995. doi: 10.1101/gr.7.10.986 9331369
50. Wen B, Zhou R, Feng Q, Wang Q, Wang J, Liu S. IQuant: an automated pipeline for quantitative proteomics based upon isobaric tags. Proteomics. 2015; 14: 2280–2285.
51. Markus B, Lu Y, Tim H, Jyoti C. Accurate and sensitive peptide identification with Mascot Percolator. Journal of Proteome Research. 2009; 8: 3176–3181. doi: 10.1021/pr800982s 19338334
52. Savitski MM, Wilhelm M, Hahne H, Kuster B, Bantscheff M. A Scalable Approach for Protein False Discovery Rate Estimation in Large Proteomic Data Sets. Molecular & Cellular Proteomics Mcp. 2015; 14: 2394.
53. Tatusov RL, Natale DA, Garkavtsev IV, Tatusova TA, Shankavaram UT, Rao BS, et al. The COG database: new developments in phylogenetic classification of proteins from complete genomes. Nucleic Acids Research. 2001; 29: 22–28. doi: 10.1093/nar/29.1.22 11125040
54. Maier T, Güell M, Serrano L. Correlation of mRNA and protein in complex biological samples. Febs Letters. 2009; 583: 3966–3973. doi: 10.1016/j.febslet.2009.10.036 19850042
55. B F, GI L, P M, CS M, JI G. A sampling of the yeast proteome. Molecular and Cellular Biology. 1999; 19: 7357. doi: 10.1128/mcb.19.11.7357 10523624
56. Audic S, Claverie JM. The significance of digital gene expression profiles. Genome Research. 1997; 7: 986–995. doi: 10.1101/gr.7.10.986 9331369
57. Jianqin Z, Fuzhu L, Junting C, Xiaolin L. Skin transcriptome profiles associated with skin color in chickens. Plos One. 2015; 10: e0127301. doi: 10.1371/journal.pone.0127301 26030885
58. Yu S, Wang G, Liao J, Tang M, Sun W. Transcriptome Profile Analysis of Mechanisms of Black and White Plumage Determination in Black-Bone Chicken. Cellular Physiology & Biochemistry. 2018; 46: 2373–2384.
59. Li JM, Huang XS, Li LT, Zheng DM, Xue C, Zhang SL, et al. Proteome analysis of pear reveals key genes associated with fruit development and quality. Planta. 2015; 241: 1363–1379. doi: 10.1007/s00425-015-2263-y 25682102
60. Greenbaum D, Jansen R, Gerstein M. Analysis of mRNA expression and protein abundance data: an approach for the comparison of the enrichment of features in the cellular population of proteins and transcripts. Bioinformatics. 2002; 18: 585–596. doi: 10.1093/bioinformatics/18.4.585 12016056
61. Zhang W, Culley DE, Scholten JCM, Hogan M, Vitiritti L, Brockman FJ. Global transcriptomic analysis of Desulfovibrio vulgaris on different electron donors. Antonie Van Leeuwenhoek. 2006; 89: 221. doi: 10.1007/s10482-005-9024-z 16710634
62. Culley DE. Integrative analysis of transcriptomic and proteomic data: challenges, solutions and applications. Critical Reviews in Biotechnology. 2007; 27: 63. doi: 10.1080/07388550701334212 17578703
63. Crick F. Central Dogma of Molecular Biology. Nature. 1970; 227: 561–563. doi: 10.1038/227561a0 4913914
64. Gygi SP, Rochon Y, Franza BR, Aebersold R. Correlation between Protein and mRNA Abundance in Yeast. Molecular & Cellular Biology. 1999; 19: 1720–1730.
65. Wang SH, You ZY, Ye LP, Che J, Qian Q, Nanjo Y, et al. Quantitative proteomic and transcriptomic analyses of molecular mechanisms associated with low silk production in silkworm Bombyx mori. Journal of Proteome Research. 2014; 13: 735–751. doi: 10.1021/pr4008333 24428189
66. Chen Q, Guo W, Feng L, Ye X, Xie W, Huang X, et al. Data for transcriptome and proteome analysis of Eucalyptus infected with Calonectria pseudoreteaudii. Data in Brief. 2015; 3: 24–28. doi: 10.1016/j.dib.2014.12.008 26217712
67. Trevisan S, Manoli A, Ravazzolo L, Botton A, Pivato M, Masi A, et al. Nitrate sensing by the maize root apex transition zone: a merged transcriptomic and proteomic survey. Journal of Experimental Botany. 2015; 66: 3699–3715. doi: 10.1093/jxb/erv165 25911739
68. Ghazalpour A, Bennett B, Petyuk VA, Orozco L, Hagopian R, Mungrue IN, et al. Comparative Analysis of Proteome and Transcriptome Variation in Mouse. Plos Genetics. 2011; 7: e1001393. doi: 10.1371/journal.pgen.1001393 21695224
69. Wu S, Zhu Y, He F. Progress in the comparison of transcriptome and proteome. Progress in Biochemistry & Biophysics. 2005; 32: 99–105.
70. Vogel C, Marcotte EM. Insights into the regulation of protein abundance from proteomic and transcriptomic analyses. Nature Reviews Genetics. 2012; 13: 227–232. doi: 10.1038/nrg3185 22411467
71. Bouchal P, Dvořáková M, Roumeliotis T, Bortlíček Z, Ihnatová I, Procházková I, et al. Combined Proteomics and Transcriptomics Identifies Carboxypeptidase B1 and Nuclear Factor κB (NF-κB) Associated Proteins as Putative Biomarkers of Metastasis in Low Grade Breast Cancer. European Journal of Cancer. 2015; 51: S24–S25.
72. Petersen HO, Höger SK, Looso M, Lengfeld T, Kuhn A, Warnken U, et al. A Comprehensive Transcriptomic and Proteomic Analysis of Hydra Head Regeneration. Molecular Biology & Evolution. 2015; 32: 1928–1947.
73. Hou L, Panthier JJ, Arnheiter H. Signaling and transcriptional regulation in the neural crest-derived melanocyte lineage: interactions between KIT and MITF. Development. 2000; 127: 5379. 11076759
74. D’Mello SAN, Finlay GJ, Baguley BC, AskarianAmiri ME. Signaling Pathways in Melanogenesis. International Journal of Molecular Sciences. 2016; 17: 1144.
75. Zhang J, Liu F, Cao J, Liu X. Skin Transcriptome Profiles Associated with Skin Color in Chickens. Plos One. 2015; 10: e0127301. doi: 10.1371/journal.pone.0127301 26030885
76. Xia M, Chen K, Yao X, Xu Y, Yao J, Yan J, et al. Mediator MED23 Links Pigmentation and DNA Repair through the Transcription Factor MITF. Cell Reports. 2017; 20: 1794. doi: 10.1016/j.celrep.2017.07.056 28834744
77. Gessi M, Hammes J, Lauriola L, Dörner E, Kirfel J, Kristiansen G, et al. GNA11 and N-RAS mutations: alternatives for MAPK pathway activating GNAQ mutations in primary melanocytic tumours of the central nervous system. Neuropathology & Applied Neurobiology. 2013; 39: 417.
78. Jipeng X, Effects of melamine, oxidized fish oil and lipid on growth and skin colour of darkbarbel catfish. Ph.D. Thesis, Ocean university of China, 2011.
Článek vyšel v časopise
PLOS One
2019 Číslo 11
- Tisícileté topoly, mokří psi, stárnoucí kočky a ospalé octomilky – „jednohubky“ z výzkumu 2024/41
- Jaké jsou aktuální trendy v léčbě karcinomu slinivky?
- Může hubnutí souviset s vyšším rizikem nádorových onemocnění?
- Menstruační krev má značný diagnostický potenciál, mimo jiné u diabetu
- Metamizol jako analgetikum první volby: kdy, pro koho, jak a proč?
Nejčtenější v tomto čísle
- A daily diary study on maladaptive daydreaming, mind wandering, and sleep disturbances: Examining within-person and between-persons relations
- A 3’ UTR SNP rs885863, a cis-eQTL for the circadian gene VIPR2 and lincRNA 689, is associated with opioid addiction
- A substitution mutation in a conserved domain of mammalian acetate-dependent acetyl CoA synthetase 2 results in destabilized protein and impaired HIF-2 signaling
- Molecular validation of clinical Pantoea isolates identified by MALDI-TOF
Zvyšte si kvalifikaci online z pohodlí domova
Všechny kurzy