Mapping additive and epistatic QTLs for forage quality and yield in soybean [Glycine max (L.) Merri.] in two environments

References

• Asekova S, Kulkarni KP, Kim M, et al. Novel quantitative trait loci for forage quality traits in a cross between PI 483463 and ‘Hutcheson’ in Soybean. Crop Sci. 2016;56(5):2600–2611.
   Web of Science ®Google Scholar
• Hymowitz T. Soybeans: The success story. In: Janick J, Simon JE, editors. Advances in new crops. Portland, OR (USA): Timber Press; 1990. p. 159–163.
   Google Scholar
• Wang XZ, Jiang GL, Green M, et al. QTL analysis of unsaturated fatty acids in a recombinant inbred population of soybean. Mol Breeding. 2014;33(2):281–296.
   Web of Science ®Google Scholar
• Koivisto JM, Devine TE, Lane GPF, et al. Forage soybeans (Glycine max (L.) Merr.) in the United Kingdom: test of new cultivars. Agronomie. 2003;23(4):287–291.
   Google Scholar
• Asekova S, Kulkarni KP, Patil G, et al. Genetic analysis of shoot fresh weight in a cross of wild (G. soja) and cultivated (G. max) soybean. Mol Breeding. 2016;36(7):103.
   Web of Science ®Google Scholar
• Kulkarni KP, Tayade R, Asekova S, et al. Harnessing the potential of forage legumes, alfalfa, soybean, and cowpea for sustainable agriculture and global food security. Front Plant Sci. 2018;9:1314.
   PubMed Web of Science ®Google Scholar
• Golzarian MR, Frick RA, Rajendran K, et al. Accurate inference of shoot biomass from high-throughput images of cereal plants. Plant Methods. 2011;7:2.
   PubMed Web of Science ®Google Scholar
• Stombaugh SK, Jung HG, Orf JH, et al. Genotypic and environmental variation in soybean seed cell wall polysaccharides. Crop Sci. 2000;40(2):408–412.
   Web of Science ®Google Scholar
• Stombaugh SK, Orf JH, Jung HG, et al. Relationships between soybean seed cell wall polysaccharides, yield, and seed traits. Crop Sci. 2003;43(2):571.
   Web of Science ®Google Scholar
• Lee EJ, Choi HJ, Shin DH, et al. Evaluation of forage yield and quality for the accessions derived from inter-specific cross between wild and cultivated soybeans. Korean J Breed Sci. 2014;46(1):66–77.
   Google Scholar
• Santos MA, Geraldi IO, Garcia AA, et al. Mapping of QTLs associated with biological nitrogen fixation traits in soybean. Hereditas. 2013;150(2-3):17–25.
   PubMed Web of Science ®Google Scholar
• Jannink JL, Moreau L, Charmet G, et al. Overview of QTL detection in plants and tests for synergistic epistatic interactions. Genetica. 2009;136(2):225–236.
   PubMed Web of Science ®Google Scholar
• Zhang D, Cheng H, Geng L, et al. Detection of quantitative trait loci for phosphorus deficiency tolerance at soybean seedling stage. Euphytica. 2009;167(3):313–322.
   Web of Science ®Google Scholar
• Holland JB. Genetic architecture of complex traits in plants. Curr Opin Plant Biol. 2007;10(2):156–161.
   PubMed Web of Science ®Google Scholar
• Wang D, Salah El-Basyoni I, Stephen Baenziger P, et al. Prediction of genetic values of quantitative traits with epistatic effects in plant breeding populations. Heredity (Edinb)). 2012;109(5):313–319.
   PubMed Web of Science ®Google Scholar
• Cao Y, Li S, Chen G, et al. Deciphering the genetic architecture of plant height in soybean using two RIL populations sharing a common M8206 parent. Plants. 2019;8(10):373.
   Web of Science ®Google Scholar
• Hina A, Cao Y, Song S, et al. High-resolution mapping in two RIL populations refines major "QTL Hotspot" regions for seed size and shape in soybean (Glycine max L.). IJMS. 2020;21(3):1040.
   Web of Science ®Google Scholar
• Wang Y, Han Y, Zhao X, et al. Mapping isoflavone QTL with main, epistatic and QTL × environment effects in recombinant inbred lines of soybean. PLoS One. 2015;10(3):e0118447.
   PubMed Web of Science ®Google Scholar
• Jiang H, Li Y, Qin H, et al. Identification of major QTLs associated with first pod height and candidate gene mining in soybean. Front Plant Sci. 2018;9:1280.
   PubMed Web of Science ®Google Scholar
• Liang H, Yu Y, Wang S, et al. QTL mapping of isoflavone, oil and protein contents in soybean (Glycine max L. Merr. Agricultural Sci China. 2010;9(8):1108–1116. https://doi.org/10.1016/S1671-2927(09)60197-8
   Google Scholar
• Pathan SM, Vuong T, Clark K, et al. Genetic mapping and confirmation of quantitative trait loci for seed protein and oil contents and seed weight in soybean. Crop Sci. 2013;53(3):765–774.
   Web of Science ®Google Scholar
• Warrington CV, Abdel-Haleem H, Hyten DL, et al. QTL for seed protein and amino acids in the Benning × Danbaekkong soybean population. Theor Appl Genet. 2015;128(5):839–850.
   PubMed Web of Science ®Google Scholar
• Qi Z, Zhang X, Qi H, et al. Identification and validation of major QTLs and epistatic interactions for seed oil content in soybeans under multiple environments based on a high-density map. Euphytica. 2017;213(8):162.
   Web of Science ®Google Scholar
• Fehr WR, Caviness CE, Burmood DT, et al. Stage of development descriptions for soybeans, Glycine max (L) Merrill. Crop Sci. 1971;11(6):929–931.
   Web of Science ®Google Scholar
• Ning H, Yuan J, Dong Q, et al. Identification of QTLs related to the vertical distribution and seed-set of pod number in soybean [Glycine max (L.) Merri]. PLoS One. 2018;13(4):e0195830.
   PubMed Web of Science ®Google Scholar
• Lander ES, Botstein D. Mapping mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics. 1989;121(1):185–199.
   PubMed Web of Science ®Google Scholar
• Li H, Ye G, Wang J. A modified algorithm for the improvement of composite interval mapping. Genetics. 2007;175(1):361–374.
   PubMed Web of Science ®Google Scholar
• Kosambi DD. The estimation of map distances from recombination values. Ann Eugen. 1943;12(1):172–175.
   Google Scholar
• Mccouch S, Cho Y, Yano M, et al. Report on QTL nomenclature. Rice Genet Newsl. 1997;14:11.
   Google Scholar
• Hammond K, James JW. Genes of large effect and the shape of the distribution of a quantitative character. Aust J Biol Sci. 1970;23(4):867–876.
   PubMedGoogle Scholar
• Zeng Y, Shi J, Ji Z, et al. Combination of twelve alleles at six quantitative trait loci determines grain weight in rice. PLoS One. 2017;12(7):e0181588.
   PubMed Web of Science ®Google Scholar
• Bloomer RH, Lloyd AM, Symonds VV. The genetic architecture of constitutive and induced trichome density in two new recombinant inbred line populations of Arabidopsis thaliana: phenotypic plasticity, epistasis, and bidirectional leaf damage response. BMC Plant Biol. 2014;14:119.
   PubMed Web of Science ®Google Scholar
• Li K, Yan J, Li J, et al. Genetic architecture of rind penetrometer resistance in two maize recombinant inbred line populations. BMC Plant Biol. 2014;14:152.
   PubMed Web of Science ®Google Scholar
• Pan Q, Xu Y, Li K, et al. The genetic basis of plant architecture in 10 maize recombinant inbred line populations. Plant Physiol. 2017;175(2):858–873.
   PubMed Web of Science ®Google Scholar
• Mao T, Jiang Z, Han Y, et al. Identification of quantitative trait loci underlying seed protein and oil contents of soybean across multi-genetic backgrounds and environments. Plant Breed. 2013;132(6):630–641.
   Web of Science ®Google Scholar
• Kamfwa K, Zhao D, Kelly JD, et al. Transcriptome analysis of two recombinant inbred lines of common bean contrasting for symbiotic nitrogen fixation. PLoS One. 2017;12(2):e0172141.
   PubMed Web of Science ®Google Scholar
• Teng W, Han Y, Du Y, et al. QTL analyses of seed weight during the development of soybean (Glycine max L. Merr.). Heredity (Edinb). 2009;102(4):372–380.
   PubMed Web of Science ®Google Scholar
• Panthee DR, Pantalone VR, West DR, et al. Quantitative trait loci for seed protein and oil concentration, and seed size in soybean. Crop Sci. 2005;45(5):2015–2022.
   Web of Science ®Google Scholar
• Rossi ME, Orf JH, Liu LJ, et al. Genetic basis of soybean adaptation to North American vs. Asian mega-environments in two independent populations from Canadian × Chinese crosses. Theor Appl Genet. 2013;126(7):1809–1823.
   PubMed Web of Science ®Google Scholar
• Wang Y, Dong Q, Fang Y, et al. Identification of quantitative trait loci for seed protein and oil contents in soybean and analysis for epistatic and QTL × environment effects in multiple environments. Intl J Agric Biol. 2020; 24:493–504.
   Web of Science ®Google Scholar
• Jansen RC, Van Ooijen JW, Stam P, et al. Genotype-by-environment interaction in genetic mapping of multiple quantitative trait loci. Theor Appl Genet. 1995;91(1):33–37.
   PubMed Web of Science ®Google Scholar
• Specht JE, Chase K, Macrander M, et al. Soybean response to water: a QTL analysis of drought tolerance. Crop Sci. 2001;41(2):493–509.
   Web of Science ®Google Scholar
• Laurie C, Wang S, Carlini-Garcia LA, et al. Mapping epistatic quantitative trait loci. BMC Genet. 2014;15:112.
   PubMed Web of Science ®Google Scholar
• Zhang WK, Wang YJ, Luo GZ, et al. QTL mapping of ten agronomic traits on the soybean (Glycine max L. Merr.) genetic map and their association with EST markers. Theor Appl Genet. 2004;108(6):1131–1139.
   PubMed Web of Science ®Google Scholar
• Soest PJV. Nutritional ecology of the ruminant. Cornell Univ P. 1994;44(11):2552–2561.
   Google Scholar
• Falkner LK, Casler MD. Preference for smooth bromegrass clones is affected by divergent selection for nutritive value. Crop Sci. 1998;38(3):690–695.
   Web of Science ®Google Scholar
• Jung HJ. Analysis of forage fiber and cell walls in ruminant nutrition. J Nutr. 1997;127(5 Suppl):810S–813S.
   PubMed Web of Science ®Google Scholar
• Xiong Y, Fei SZ, Brummer EC, et al. QTL analyses of fiber components and crude protein in an annual × perennial ryegrass interspecific hybrid population. Mol Breeding. 2006;18(4):327–340.
   Web of Science ®Google Scholar
• Soest PJV. Development of a comprehensive system of feed analyses and its application to forages. J Anim Sci. 1967;26(1):119–120.
   Web of Science ®Google Scholar
• Zhang D, Li H, Wang J, et al. High-density genetic mapping identifies new major loci for tolerance to low-phosphorus stress in soybean. Front Plant Sci. 2016;7:372.
   PubMed Web of Science ®Google Scholar