Evaluation of the genetic architecture of tofu traits in soybean towards genomics‐assisted breeding

Kurasch, Alena K.; Leiser, Willmar L.; Bachteler, Kristina; Miersch, Martin; Hahn, Volker; Würschum, Tobias

doi:10.1111/pbr.12651

Cited by 6 publications

(11 citation statements)

References 51 publications

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“…In previous studies, a QTL Dm6 (Sat_312 $ satt286) for the dry soymilk output was located in the region of 16.22 $ 36.14 Mb on chromosome 6 (Hou, 2009), and the two associated SNPs ss715594028 and ss715594148 in our study were located in this QTL region. Meanwhile, a QTL (S15_4569252 $ S15_4560129) for soybean protein concentration was located in the region of 4.56 $ 4.57 Mb on chromosome 15 (Kurasch, Leiser, et al, 2018), which was close ($0.58 Mb) to the associated SNP ss715621816 in our study. And also, the QTL qODT-J (Satt414 $ Satt132) for the output of dry tofu was located in the region of 8.90 $ 9.94 Mb on chromosome 16 (Zhang et al, 2008), which was 0.90 Mb away from the associated SNP ss715625558 in our study.…”

Section: A Novel and Stable Genomic Region On Chromosome 8 For Soybea...supporting

confidence: 69%

Genetic loci and candidate genes with pleiotropic effects for tofu and soymilk weights across multiple environments in soybean (Glycine max)

Huang

Chen

et al. 2023

Plant Breeding

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Soybean provides large amounts of protein for human, and the most popular consumption pattern is tofu and soymilk. Recently, the demand of tofu and soymilk is increased, and the breeding of special variety becomes very urgent. To illustrate the genetic basis of these traits, 269 accessions were evaluated under six environments, and 32 associated SNPs were identified on nine chromosomes across multiple environments or conferring diverse traits. Of these SNPs, 16 were demonstrated by BLUP values. Seven adjacent‐SNPs were first identified to associate with tofu and soymilk weights in an 1.02‐Mb region on chromosome 8, which were verified by BLUP‐values. Meanwhile, four neighbouring SNPs in a 0.32‐Mb region on chromosome 12 were first identified to associate with these traits across multiple environments, of which three were detected in BLUP values. Furthermore, some candidate genes, that is, α‐glucan water dikinase Glyma.08G283700 and E3 SUMO‐protein ligase Glyma.12G071300, were screened out with differential expressions between the high‐ and low‐tofu/soymilk‐output accessions. Thus, these associated SNPs and candidate genes provide new insight into the genetic basis of tofu and soymilk processing quality in soybean.

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Section: A Novel and Stable Genomic Region On Chromosome 8 For Soybea...supporting

confidence: 69%

Genetic loci and candidate genes with pleiotropic effects for tofu and soymilk weights across multiple environments in soybean (Glycine max)

Huang

Chen

et al. 2023

Plant Breeding

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“…Of the various known QTLs coinciding with these regions, some are related to improvement traits including seed composition (protein, oil and isoflavone content), seed yield (yield components), pathogen resistance, and time to flowering and maturity ( Table 4 ). Interestingly, some QTLs associated with tofu quality (tofu hardiness and tofu value) reported by Kurasch et al (2018) coincide with region 8.1. Different genes known to be involved in nodulation (nodulin MtN3 , nodulin MtN21 ; Gamas et al (1996) ), regulating Zn, Mn, Ca, and Fe uptake, involved in flowering and maturity including E2 ( Glyma.10G221500 ) and E4 ( Glyma.20G090000 ; in close proximity of selective sweep region 20.1), and genes related to hormonal control of plant growth including auxin response factor, gibberellin-regulated protein, brassinosteroid signaling, jasmonic acid biosynthesis and strigolactone biosynthesis are located in these selective sweep regions ( Supplementary Table 3 ).…”

Section: Resultsmentioning

confidence: 84%

A Genome-Wide Genetic Diversity Scan Reveals Multiple Signatures of Selection in a European Soybean Collection Compared to Chinese Collections of Wild and Cultivated Soybean Accessions

et al. 2021

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Targeted and untargeted selections including domestication and breeding efforts can reduce genetic diversity in breeding germplasm and create selective sweeps in crop genomes. The genomic regions at which selective sweeps are detected can reveal important information about signatures of selection. We have analyzed the genetic diversity within a soybean germplasm collection relevant for breeding in Europe (the EUCLEG collection), and have identified selective sweeps through a genome-wide scan comparing that collection to Chinese soybean collections. This work involved genotyping of 480 EUCLEG soybean accessions, including 210 improved varieties, 216 breeding lines and 54 landraces using the 355K SoySNP microarray. SNP calling of 477 EUCLEG accessions together with 328 Chinese soybean accessions identified 224,993 high-quality SNP markers. Population structure analysis revealed a clear differentiation between the EUCLEG collection and the Chinese materials. Further, the EUCLEG collection was sub-structured into five subgroups that were differentiated by geographical origin. No clear association between subgroups and maturity group was detected. The genetic diversity was lower in the EUCLEG collection compared to the Chinese collections. Selective sweep analysis revealed 23 selective sweep regions distributed over 12 chromosomes. Co-localization of these selective sweep regions with previously reported QTLs and genes revealed that various signatures of selection in the EUCLEG collection may be related to domestication and improvement traits including seed protein and oil content, phenology, nitrogen fixation, yield components, diseases resistance and quality. No signatures of selection related to stem determinacy were detected. In addition, absence of signatures of selection for a substantial number of QTLs related to yield, protein content, oil content and phenological traits suggests the presence of substantial genetic diversity in the EUCLEG collection. Taken together, the results obtained demonstrate that the available genetic diversity in the EUCLEG collection can be further exploited for research and breeding purposes. However, incorporation of exotic material can be considered to broaden its genetic base.

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“…Soybean seeds also contain around 20% oil and most of the cultivars grown worldwide are primarily bred for high oil content (Sato et al., 2014). In Europe, soybean is not only used for livestock, but with the trend towards vegetarian or vegan lifestyles, soy‐based products like the traditional Asian food tofu have become increasingly popular (Kurasch, Hahn, et al., 2018; Kurasch, Leiser, et al., 2018). Because of the strong dependency of Europe on protein imports as well as the increasing global demand for soybean, early‐maturing cultivars adapted to higher latitudes have been bred, and soybean cultivation has been expanded in Central and Northern Europe in recent years (Hahn & Würschum, 2014; Würschum et al., 2019).…”

Section: Introductionmentioning

confidence: 99%

Training set design in genomic prediction with multiple biparental families

et al. 2021

Self Cite

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Genomic selection is a powerful tool to reduce the cycle length and enhance the genetic gain of complex traits in plant breeding. However, questions remain about the optimum design and composition of the training set. In this study, we used 944 soybean [Glycine max (L.) Merr.] recombinant inbred lines from eight families derived through a partial-diallel mating design among five parental lines. The cross-validated prediction accuracies for the six traits seed yield, 1,000-seed weight, protein yield, plant height, protein content, and oil content were high, ranging from 0.79 to 0.87. We investigated among-family predictions, making use of the special mating design with different degrees of relatedness among families. Generally, the prediction accuracy decreased from full-sibs to half-sib families to unrelated families. However, half-sib and unrelated families also showed substantial variation in their prediction accuracy for a given family, which appeared to be caused at least in part by the shared segregation of quantitative trait loci in both the training and prediction sets. Combining several half-sib families in composite training sets generally led to an increase in the prediction accuracy compared with the best family alone. The prediction accuracy increased with the size of the training set, but for comparable prediction accuracy, substantially more half-sibs were required than full-sibs. Collectively, our results highlight the potential of genomic selection for soybean breeding and, in a broader context, illustrate the importance of the targeted design of the training set. INTRODUCTIONGenomic selection was first suggested for animal breeding and has been shown to enhance the rate of genetic improvement Meuwissen et al., 2001). Genomic selection has also emerged as a valuable tool for plant breeding.

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Evaluation of the genetic architecture of tofu traits in soybean towards genomics‐assisted breeding

Cited by 6 publications

References 51 publications

Genetic loci and candidate genes with pleiotropic effects for tofu and soymilk weights across multiple environments in soybean (Glycine max)

Genetic loci and candidate genes with pleiotropic effects for tofu and soymilk weights across multiple environments in soybean (Glycine max)

A Genome-Wide Genetic Diversity Scan Reveals Multiple Signatures of Selection in a European Soybean Collection Compared to Chinese Collections of Wild and Cultivated Soybean Accessions

Training set design in genomic prediction with multiple biparental families

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