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Genetic variation of world soybean maturity date and geographic distribution of maturity groups.

ABSTRACT: The maturity date of soybean (Glycine max (L.) Merr.) is sensitive to photoperiod, which varies with latitude and growing seasons. The maturity group (MG) system, composed of 13 MGs, is a major approach in characterizing varieties' ecological properties and adaptable areas. A total of 512 world soybean varieties, including 48 MG checks, were tested at a major site (Nanjing, 32.04°N) with portions tested in supplementary sites (Heihe, 50.22°N; Mudanjiang, 44.60°N; Jining, 35.38°N and Nanning, 22.84°N) in China to explore the world-wide MG distribution. The maturity date of the world soybean varied greatly (75-201 d) in Nanjing. Along with soybeans disseminated to new areas, the MGs further expanded during the last 70 years from MG I-VII to the early MG 0-000 in the north continents and to the late MG VIII-X in the south continents with the growth period structure differentiated into two subgroups in each MG 0-VIII except V. The cluster analysis among MGs and subgroups using genome-wide markers validated the MG sequential emergence order and the subgroup differentiation in eight MGs. For future evaluation, in addition to one major site (Nanjing), one supplementary southern site (Nanning) and one supplementary northern site (Heihe) are sufficient.

SUBMITTER: Liu X

PROVIDER: S-EPMC5515309 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature

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Genetic variation of world soybean maturity date and geographic distribution of maturity groups.

Liu Xueqin X Wu Ji-An JA Ren Haixiang H Qi Yuxin Y Li Chunyan C Cao Jiqiu J Zhang Xiaoyan X Zhang Zhipeng Z Cai Zhaoyan Z Gai Junyi J

Breeding science 20170530 3

The maturity date of soybean (<i>Glycine max</i> (L.) Merr.) is sensitive to photoperiod, which varies with latitude and growing seasons. The maturity group (MG) system, composed of 13 MGs, is a major approach in characterizing varieties' ecological properties and adaptable areas. A total of 512 world soybean varieties, including 48 MG checks, were tested at a major site (Nanjing, 32.04°N) with portions tested in supplementary sites (Heihe, 50.22°N; Mudanjiang, 44.60°N; Jining, 35.38°N and Nanni ...[more]

PMID: 28744175

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Project description:BackgroundAbsence of or low sensitivity to photoperiod is necessary for short-day crops, such as rice and soybean, to adapt to high latitudes. Photoperiod insensitivity in soybeans is controlled by two genetic systems and involves three important maturity genes: E1, a repressor for two soybean orthologs of Arabidopsis FLOWERING LOCUS T (GmFT2a and GmFT5a), and E3 and E4, which are phytochrome A genes. To elucidate the diverse mechanisms underlying photoperiod insensitivity in soybean, we assessed the genotypes of four maturity genes (E1 through E4) in early-flowering photoperiod-insensitive cultivars and their association with post-flowering responses.ResultsWe found two novel dysfunctional alleles in accessions originally considered to have a dominant E3 allele according to known DNA markers. The E3 locus, together with E1 and E4, contained multiple dysfunctional alleles. We identified 15 multi-locus genotypes, which we subdivided into 6 genotypic groups by classifying their alleles by function. Of these, the e1-as/e3/E4 genotypic group required an additional novel gene (different from E1, E3, and E4) to condition photoperiod insensitivity. Despite their common pre-flowering photoperiod insensitivity, accessions with different multi-locus genotypes responded differently to the post-flowering photoperiod. Cultivars carrying E3 or E4 were sensitive to photoperiod for post-flowering characteristics, such as reproductive period and stem growth after flowering. The phytochrome A-regulated expression of the determinate growth habit gene Dt1, an ortholog of Arabidopsis TERMINAL FLOWER1, was involved in the persistence of the vegetative activity at the stem apical meristem of flower-induced plants under long-day conditions.ConclusionsDiverse genetic mechanisms underlie photoperiod insensitivity in soybean. At least three multi-locus genotypes consisting of various allelic combinations at E1, E3, and E4 conferred pre-flowering photoperiod insensitivity to soybean cultivars but led to different responses to photoperiod during post-flowering vegetative and reproductive development. The phyA genes E3 and E4 are major controllers underlying not only pre-flowering but also post-flowering photoperiod responses. The current findings improve our understanding of genetic diversity in pre-flowering photoperiod insensitivity and mechanisms of post-flowering photoperiod responses in soybean.

Project description:Soybean has a recognized narrow genetic base that often makes it difficult to visualize available genetic and phenotypic variability and identify superior genotypes during the selection process. However, the phenotypic expression of soybean plants is highly affected by photoperiod and the cultivation of a given variety is performed in the latitude range that presents ideal conditions for its development based on its relative maturity group (RMG) for the optimization of the phenotypic expression of its genotype. Based on the above, this study aimed to evaluate the efficiency of artificial neural networks (ANNs) as a tool for the correct discrimination and classification of tropical soybean genotypes according to their relative maturity group during the population selection process with the aim of optimizing the phenotypic performance of these selected genotypes. For this purpose, three biparental populations were synthesized, one with a wide genetic variability for the RMG character obtained from the hybridization between genitors of maturity groups RMG 5 (Sub-tropical 23° LS) × RMG 9.4 (Tropical 0° LS) and two populations with a narrow variability obtained between genitors RMG 7.3 (Tropical 20° LS) × RMG 9.4 and RMG 5.3 × RMG 6.7, respectively. Criteria for comparing the developed ANN architecture with Fisher’s linear and Anderson’s quadratic parametric discriminant methodologies were applied to the data for the discrimination and classification of the genotypes. ANN showed an apparent error rate of less than 8.16% as well as a low influence of environmental factors, correctly classifying the genotypes in the populations even in cases of reduced genetic variability such as in the RMG 5 × RMG 6 population. In contrast, the discriminant functions were inefficient in correctly classifying the genotypes in the populations with genealogical similarity (RMG 5 × RMG 6) and wide genetic variability, with an error rate of more than 50%. Based on the results of this study, ANN can be used for the discrimination of genotypes in the initial generations of selection in breeding programs for the development of high performance cultivars for wide and reduced photoperiod amplitudes, even with fewer selection environments, more efficiently, and with fewer time and resources applied. As a result of similarity between the parents, ANN can correctly classify genotypes from populations with a narrow genetic base, in addition to pure lines and genotypes with a high degree of inbreeding.

Dataset Information

Genetic variation of world soybean maturity date and geographic distribution of maturity groups.

Publications

Genetic variation of world soybean maturity date and geographic distribution of maturity groups.

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