Improving yield is a major objective for cotton breeding schemes, and lint yield and its three component traits (boll number, boll weight and lint percentage) are complex traits controlled by multiple genes and various environments. Association mapping was performed to detect markers associated with these four traits using 651 simple sequence repeats (SSRs). A mixed linear model including epistasis and environmental interaction was used to screen the loci associated with these four yield traits by 323 accessions of Gossypium hirsutum L. evaluated in nine different environments. 251 significant loci were detected to be associated with lint yield and its three components, including 69 loci with individual effects and all involved in epistasis interactions. These significant loci explain ~ 62.05% of the phenotypic variance (ranging from 49.06% ~ 72.29% for these four traits). It was indicated by high contribution of environmental interaction to the phenotypic variance for lint yield and boll numbers, that genetic effects of SSR loci were susceptible to environment factors. Shared loci were also observed among these four traits, which may be used for simultaneous improvement in cotton breeding for yield traits. Furthermore, consistent and elite loci were screened with ？Log10 (P-value) >8.0 based on predicted effects of loci detected in different environments. There was one locus and 6 pairs of epistasis for lint yield, 4 loci and 10 epistasis for boll number, 15 loci and 2 epistasis for boll weight, and 2 loci and 5 epistasis for lint percentage, respectively. These results provided insights into the genetic basis of lint yield and its components and may be useful for marker-assisted breeding to improve cotton production.
References
[1]
He DH, Lin ZX, Zhang XL, Nie YC, Guo XP, et al. (2005) Mapping QTLs of traits contributing to yield and analysis of genetic effects in tetraploid cotton. Euphytica 144: 141–149. doi: 10.1007/s10681-005-5297-6
[2]
Shen XL, Zhang TZ, Guo WZ, Zhu XF, Zhang XY (2006) Mapping Fiber and Yield QTLs with Main, Epistatic, and QTL × Environment Interaction Effects in Recombinant Inbred Lines of Upland Cotton. Crop Science 46: 61. doi: 10.2135/cropsci2005.0056
[3]
Murcray CE, Lewinger JP, Gauderman WJ (2008) Gene-Environment Interaction in Genome-Wide Association Studies. American Journal of Epidemiology 169: 219–226. doi: 10.1093/aje/kwn353
[4]
Chen H, Qian N, Guo WZ, Song QP, Li BC, et al. (2010) Using three selected overlapping RILs to fine-map the yield component QTL on Chro.D8 in Upland cotton. Euphytica 176: 321–329. doi: 10.1007/s10681-010-0204-1
[5]
Liu RZ, Wang BH, Guo WZ, Qin YS, Wang LG, et al. (2011a) Quantitative trait loci mapping for yield and its components by using two immortalized populations of a heterotic hybrid in Gossypium hirsutum L. Mol Breeding. 29: 297–311.
[6]
Yadava SK, Arumugam N, Mukhopadhyay A, Sodhi YS, Gupta V, et al. (2012) QTL mapping of yield-associated traits in Brassica juncea: meta-analysis and epistatic interactions using two different crosses between east European and Indian gene pool lines. Theor Appl Genet 125: 1553–1564. doi: 10.1007/s00122-012-1934-3
[7]
Yu JW, Zhang K, Li SY, Yu SX, Zhai HH, et al. (2012) Mapping quantitative trait loci for lint yield and fiber quality across environments in a Gossypium hirsutum × Gossypium barbadense backcross inbred line population. Theor Appl Genet 126: 275–287. doi: 10.1007/s00122-012-1980-x
[8]
Lacape JM, Gawrysiak G, Cao TV, Viot C, Llewellyn D, et al. (2013) Mapping QTLs for traits related to phenology, morphology and yield components in an inter-specific Gossypium hirsutum×G. barbadense cotton RIL population. Field Crops Research 144: 256–267. doi: 10.1016/j.fcr.2013.01.001
[9]
Huang XH, Wei XH, Sang T, Zhao Q, Feng Q, et al. (2010) Genome-wide association studies of 14 agronomic traits in rice landraces. Nature Genetics 42: 961–967.
[10]
Poland JA, Bradbury PJ, Buckler ES, Nelson RJ (2011) Genome-wide nested association mapping of quantitative resistance to northern leaf blight in maize. Proc Natl Acad Sci USA 108: 6893–6898.
[11]
Kump KL, Bradbury PJ, Wisser RJ, Buckler ES, Belcher AR, et al. (2011) Genome-wide association study of quantitative resistance to southern leaf blight in the maize nested association mapping population. Nature Genetics 43: 163–168. doi: 10.1038/ng.747
[12]
Tian F, Bradbury PJ, Brown PJ, Hung H, Sun Q, et al. (2011) Genome-wide association study of leaf architecture in the maize nested association mapping population. Nature Genetics 43: 159–162. doi: 10.1038/ng.746
[13]
Li H, Peng ZY, Yang XH, Wang WD, Fu JJ, et al.. (2012) Genome-wide association study dissects the genetic architecture of oil biosynthesis in maize kernels. Nature Genetics: 1–10.
[14]
Zhang TZ, Qian N, Zhu XF, Chen H, Wang S, et al. (2013) Variations and Transmission of QTL Alleles for Yield and Fiber Qualities in Upland Cotton Cultivars Developed in China. PLoS ONE 8: e57220. doi: 10.1371/journal.pone.0057220
[15]
Ziegler A, K？nig IR, Thompson JR (2008) Biostatistical Aspects of Genome-Wide Association Studies. Biom J 50: 8–28. doi: 10.1002/bimj.200710398
[16]
Carlborg O, Haley CS (2004) Epistasis: too often neglected in complex trait studies? Nat Rev Genet 5: 618–625. doi: 10.1038/nrg1407
[17]
Phillips PC (2008) Epistasis – the essential role of gene interactions in the structure and evolution of genetic systems. Nature Publishing Group 9: 855–867. doi: 10.1038/nrg2452
[18]
van Os J, Rutten BPF (2009) Gene-environment-wide interaction studies in psychiatry. Am J Psychiatry 166: 964–966. doi: 10.1176/appi.ajp.2008.09060904
[19]
Culverhouse R, Suarez BK, Lin J, Reich T (2002) A perspective on epistasis: limits of models displaying no main effect. Am J Hum Genet 70: 461–471. doi: 10.1086/338759
[20]
Brachi B, Morris GP, Borevitz JO (2011) Genome-wide association studies in plants: the missing heritability is in the field. Genome Biol 12: 232. doi: 10.1186/gb-2011-12-10-232
[21]
Zuk O, Hechter E, Sunyaev SR, Lander ES (2012) The mystery of missing heritability: genetic interactions create phantom heritability. Proc Natl Acad Sci USA 109: 1193–1198. doi: 10.1073/pnas.1119675109
[22]
Godoy S, Palomo G (1999) Genetic analysis of earliness in upland cotton. II. Yield and fiber properties. Euphytica 105: 161–166.
[23]
Campbell BT, Jones MA (2005) Assessment of genotype × environment interactions for yield and fiber quality in cotton performance trials. Euphytica 144: 69–78. doi: 10.1007/s10681-005-4336-7
[24]
Collard BCY, Mackill DJ (2008) Marker-assisted selection: an approach for precision plant breeding in the twenty-first century. Philosophical Transactions of the Royal Society B: Biological Sciences 363: 557–572.
