Genome-wide signatures of the geographic expansion and breeding of soybean

Li, Yinghui; Qin, Chao; Wang, Li; Jiao, Chengzhi; Hong, Huilong; Tian, Yu; Li, Yanfei; Xing, Guangnan; Wang, Jun; Gu, Ying; Gao, Xingpeng; Li, Delin; Li, Hongyu; Liu, Zhangxiong; Jing, Xin; Bao, Feng; Zhao, Tao; Guan, Rongxia; Guo, Yong; Li, Jun; Yan, Zhe; Zhang, Lijuan; Ge, Tianli; Li, Xiangkong; Wang, Xiaobo; Qiu, Hongmei; Zhang, Wanhai; L, Xin; Han, Yingpeng; Han, Dejun; Chang, Ru-Zhen; Guo, Ya‐Long; Reif, Jochen C.; Jackson, Scott A.; Liu, Bin; Tian, Shilin; Qiu, Lijuan

doi:10.1007/s11427-022-2158-7

Cited by 31 publications

(42 citation statements)

References 69 publications

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“…Plants and growth conditions Li et al (2022) genotyped 2,214 soybean (Glycine max (L.) Merr.) accessions, which represent the broad genetic diversity of 23,587 cultivated soybeans from the Chinese National Soybean Gene Bank, via genome resequencing.…”

Section: Methodsmentioning

confidence: 99%

“…We phenotyped 1,303 soybean accessions (Figure 1A) both manually and with the help of a UAS at Nanchang (28°31′56″ N, 116°1′34″E) in 2020. These accessions were collected from around the world (Table S1) and consisted of 903 landraces and 400 improved cultivars, which comprised the four soybean sub-populations described in a previous study (Li et al, 2022). We employed a UAS (Figure 1B) to collect data reflecting the proportion of ground covered by the vertical projection of the plant canopy, here referred to as canopy coverage or CC (Figure 1C-E).…”

Section: Acquisition Of Time-series Soybean CCmentioning

confidence: 99%

“…The population surveyed here represents the broad genetic diversity of the 23,587 cultivated soybeans from the Chinese National Soybean Gene Bank (Li et al, 2022). The 4 million SNPs with a minimum minor allele frequency of 5% were generated from whole-genome resequencing (Li et al, 2022) of the 1.1-Gb genome (Schmutz et al, 2010). Time-series CC determination of a large population improved the accuracy and statistical power of GWASs by increasing phenotype and genotype diversity and highlights the usefulness of high-throughput UAS for genetic studies.…”

Section: Introductionmentioning

confidence: 99%

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Time series canopy phenotyping enables the identification of genetic variants controlling dynamic phenotypes in soybean

Bai

Tian

et al. 2022

JIPB

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Advances in plant phenotyping technologies are dramatically reducing the marginal costs of collecting multiple phenotypic measurements across several time points. Yet, most current approaches and best statistical practices implemented to link genetic and phenotypic variation in plants have been developed in an era of single‐time‐point data. Here, we used time‐series phenotypic data collected with an unmanned aircraft system for a large panel of soybean (Glycine max (L.) Merr.) varieties to identify previously uncharacterized loci. Specifically, we focused on the dissection of canopy coverage (CC) variation from this rich data set. We also inferred the speed of canopy closure, an additional dimension of CC, from the time‐series data, as it may represent an important trait for weed control. Genome‐wide association studies (GWASs) identified 35 loci exhibiting dynamic associations with CC across developmental stages. The time‐series data enabled the identification of 10 known flowering time and plant height quantitative trait loci (QTLs) detected in previous studies of adult plants and the identification of novel QTLs influencing CC. These novel QTLs were disproportionately likely to act earlier in development, which may explain why they were missed in previous single‐time‐point studies. Moreover, this time‐series data set contributed to the high accuracy of the GWASs, which we evaluated by permutation tests, as evidenced by the repeated identification of loci across multiple time points. Two novel loci showed evidence of adaptive selection during domestication, with different genotypes/haplotypes favored in different geographic regions. In summary, the time‐series data, with soybean CC as an example, improved the accuracy and statistical power to dissect the genetic basis of traits and offered a promising opportunity for crop breeding with quantitative growth curves.

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Section: Methodsmentioning

confidence: 99%

Section: Acquisition Of Time-series Soybean CCmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Time series canopy phenotyping enables the identification of genetic variants controlling dynamic phenotypes in soybean

Bai

Tian

et al. 2022

JIPB

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“…Then SNP variations in the coding region of candidate genes were analyzed to screen candidate genes with mutation type of nonsynonymous, stoploss, stopgain, or alternative splicing. To further screen candidate genes, fixation index (F ST ) was calculated by published genome sequences data of 2214 soybeans ( Li et al., 2022d ) using vcftools (0.1.13) with window size of 100bp, and coding regions with F ST ≥ 0.6 were regarded as potential domestication gene ( Song et al., 2013 ). Subsequently, spatial and temporal expression of candidates were analyzed using publicly available soybean transcriptome integration dataset ( Yu et al., 2022 ).…”

Section: Methodsmentioning

confidence: 99%

Genome-wide association studies for soybean epicotyl length in two environments using 3VmrMLM

Hong

Chen

et al. 2022

Front. Plant Sci.

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Germination of soybean seed is the imminent vital process after sowing. The status of plumular axis and radicle determine whether soybean seed can emerge normally. Epicotyl, an organ between cotyledons and first functional leaves, is essential for soybean seed germination, seedling growth and early morphogenesis. Epicotyl length (EL) is a quantitative trait controlled by multiple genes/QTLs. Here, the present study analyzes the phenotypic diversity and genetic basis of EL using 951 soybean improved cultivars and landraces from Asia, America, Europe and Africa. 3VmrMLM was used to analyze the associations between EL in 2016 and 2020 and 1,639,846 SNPs for the identification of QTNs and QTN-by-environment interactions (QEIs)”.A total of 180 QTNs and QEIs associated with EL were detected. Among them, 74 QTNs (ELS_Q) and 16 QEIs (ELS_QE) were identified to be associated with ELS (epicotyl length of single plant emergence), and 60 QTNs (ELT_Q) and 30 QEIs (ELT_QE) were identified to be associated with ELT (epicotyl length of three seedlings). Based on transcript abundance analysis, GO (Gene Ontology) enrichment and haplotype analysis, ten candidate genes were predicted within nine genic SNPs located in introns, upstream or downstream, which were supposed to be directly or indirectly involved in the process of seed germination and seedling development., Of 10 candidate genes, two of them (Glyma.04G122400 and Glyma.18G183600) could possibly affect epicotyl length elongation. These results indicate the genetic basis of EL and provides a valuable basis for specific functional studies of epicotyl traits.

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“…Recently, the relationship between E1 and E3/E4 was further elucidated (Lin et al, 2022). In addition, several new genes including QNE1 (Xia et al, 2022), SOC1a (Kou et al, 2022), GmSPA3c (Li et al, 2022b), GmHY2 (Zhang et al, 2022) and GmCDPK38 (Li et al, 2022a) were found to play important roles in the photoperiodic flowering pathway of soybean (Gupta et al, 2022), which may be potential targets for molecular breeding of soybean in the future.…”

Section: Introductionmentioning

confidence: 99%

Establishment of a novel experimental system for studying the photoperiodic response of short-day dicots using soybean ‘cotyledon-only plant’ as material

Zhang

Xu²,

Chen³

et al. 2023

Front. Plant Sci.

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Soybean is an important model crop for photoperiodic response studies in plants and contributes significantly to the study of plant development and physiology in the past century. Because soybean plant is much bigger in size and longer in life cycle than Arabidopsis, it needs much more space for growth and time for investigation, which significantly hamper the efficiency of research. In the current study, we tested the photoperiodic response of a distinctive artificially-made cotyledon-only plant (COP) using a photoperiod-sensitive soybean variety Zigongdongdou (ZGDD) and other varieties with diverse sensitivity to photoperiod. ZGDD COPs flowered 39.4 ± 2.5 d after emergence under short-day conditions but maintained vegetative growth under long-day and night break conditions, which is similar to the case in the intact ZGDD plants. The COPs of early-maturing and medium-maturing soybean varieties also grew and flowered normally under natural day-length conditions. At the molecular level, the key genes in the photoperiodic pathway such as E1, GmFT1a, GmFT2a, and GmFT5a in the COPs also showed the same photoperiod sensitivity as in the intact plants. In addition, a simpler material of COP with only one cotyledon and root was generated and found to be sensitive to photoperiod as well. Notably, the COPs are only one-fifth the height of intact plants and one-third the maximum diameter of the intact plants grown in chambers 30 d after emergence. Based on COPs, we established a novel experimental system characterized by an entire photoperiodic response and longer longevity of cotyledons in addition to small plant size, ensuring the consistency, reliability, and stability of plant materials. COPs have the potential to be a novel model material for studies of the developmental biology of soybean and other dicots.

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Genome-wide signatures of the geographic expansion and breeding of soybean

Cited by 31 publications

References 69 publications

Time series canopy phenotyping enables the identification of genetic variants controlling dynamic phenotypes in soybean

Time series canopy phenotyping enables the identification of genetic variants controlling dynamic phenotypes in soybean

Genome-wide association studies for soybean epicotyl length in two environments using 3VmrMLM

Establishment of a novel experimental system for studying the photoperiodic response of short-day dicots using soybean ‘cotyledon-only plant’ as material

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