A recessive allele for delayed flowering at the soybean maturity locus E9 is a leaky allele of FT2a, a FLOWERING LOCUS T ortholog

Zhao, Chen; Takeshima, Ryoma; Zhu, Jianghui; Xu, Ming; Sato, Minoru; Watanabe, Satoshi; Kanazawa, Akira; Liu, Baohui; Kong, Fanjiang; Yamada, Tetsuya; Abe, Jun

doi:10.1186/s12870-016-0704-9

Cited by 154 publications

(150 citation statements)

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“…Of these, E1, E3, E4 , and E7 have been reported as photoperiodic loci (Cober and Voldeng, 2001). Dominant alleles at E6, E9 , and J promote early flowering, whereas dominant alleles at other loci delay flowering and maturity (Zhao et al, 2016). E1, E2, E3, E4 , and E9 loci were mapped as QTLs and underlying genes were identified as a B3 DNA binding protein, GIGANTEA, Phytochrome A3, Phytochrome A2 , and GmFT2a , respectively (Liu et al, 2008; Watanabe et al, 2009, 2011; Xia et al, 2012; Zhao et al, 2016).…”

Section: Qtlomics: Qtls To Genes In Soybeanmentioning

confidence: 99%

“…Fine mapping of the QTL region identified two candidate genes GmFT2a and GmFT2b for early flowering (Kong et al, 2014). Zhao et al (2016) resolved this QTL as leaky allele of GmFT2a . The e9 allele had an insertion of 6.22 kb Ty1/copia –like retrotransposon, SORE-1 , in the first intron which attenuated FT2a expression by its allele-specific transcriptional repression (Zhao et al, 2016).…”

Section: Qtlomics: Qtls To Genes In Soybeanmentioning

confidence: 99%

“…Zhao et al (2016) resolved this QTL as leaky allele of GmFT2a . The e9 allele had an insertion of 6.22 kb Ty1/copia –like retrotransposon, SORE-1 , in the first intron which attenuated FT2a expression by its allele-specific transcriptional repression (Zhao et al, 2016). The maturity genes B3 DNA binding protein gene ( E1 ), GIGANTEA ( E2 ), GmPhyA3 ( E3 ), and GmPhyA2 ( E4 ) down regulate expression of GmFT2a ( E9 ) and GmFT5a to delay flowering and maturation under the long day condition, suggesting that GmFT2a and GmFT5a are the major targets in the control of flowering in soybean (Kong et al, 2010; Thakare et al, 2011; Watanabe et al, 2011; Xia et al, 2012; Zhao et al, 2016).…”

Section: Qtlomics: Qtls To Genes In Soybeanmentioning

confidence: 99%

“…The e9 allele had an insertion of 6.22 kb Ty1/copia –like retrotransposon, SORE-1 , in the first intron which attenuated FT2a expression by its allele-specific transcriptional repression (Zhao et al, 2016). The maturity genes B3 DNA binding protein gene ( E1 ), GIGANTEA ( E2 ), GmPhyA3 ( E3 ), and GmPhyA2 ( E4 ) down regulate expression of GmFT2a ( E9 ) and GmFT5a to delay flowering and maturation under the long day condition, suggesting that GmFT2a and GmFT5a are the major targets in the control of flowering in soybean (Kong et al, 2010; Thakare et al, 2011; Watanabe et al, 2011; Xia et al, 2012; Zhao et al, 2016). The genes and alleles identified for flowering and maturity traits in soybean have been validated in several studies using germplasm from many countries (Tsubokura et al, 2013, 2014; Jiang et al, 2014; Langewisch et al, 2014; Zhai et al, 2014; Gupta et al, 2016).…”

Section: Qtlomics: Qtls To Genes In Soybeanmentioning

confidence: 99%

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QTLomics in Soybean: A Way Forward for Translational Genomics and Breeding

et al. 2016

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Food legumes play an important role in attaining both food and nutritional security along with sustainable agricultural production for the well-being of humans globally. The various traits of economic importance in legume crops are complex and quantitative in nature, which are governed by quantitative trait loci (QTLs). Mapping of quantitative traits is a tedious and costly process, however, a large number of QTLs has been mapped in soybean for various traits albeit their utilization in breeding programmes is poorly reported. For their effective use in breeding programme it is imperative to narrow down the confidence interval of QTLs, to identify the underlying genes, and most importantly allelic characterization of these genes for identifying superior variants. In the field of functional genomics, especially in the identification and characterization of gene responsible for quantitative traits, soybean is far ahead from other legume crops. The availability of genic information about quantitative traits is more significant because it is easy and effective to identify homologs than identifying shared syntenic regions in other crop species. In soybean, genes underlying QTLs have been identified and functionally characterized for phosphorous efficiency, flowering and maturity, pod dehiscence, hard-seededness, α-Tocopherol content, soybean cyst nematode, sudden death syndrome, and salt tolerance. Candidate genes have also been identified for many other quantitative traits for which functional validation is required. Using the sequence information of identified genes from soybean, comparative genomic analysis of homologs in other legume crops could discover novel structural variants and useful alleles for functional marker development. The functional markers may be very useful for molecular breeding in soybean and harnessing benefit of translational research from soybean to other leguminous crops. Thus, soybean crop can act as a model crop for translational genomics and breeding of quantitative traits in legume crops. In this review, we summarize current status of identification and characterization of genes underlying QTLs for various quantitative traits in soybean and their significance in translational genomics and breeding of other legume crops.

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Section: Qtlomics: Qtls To Genes In Soybeanmentioning

confidence: 99%

Section: Qtlomics: Qtls To Genes In Soybeanmentioning

confidence: 99%

Section: Qtlomics: Qtls To Genes In Soybeanmentioning

confidence: 99%

Section: Qtlomics: Qtls To Genes In Soybeanmentioning

confidence: 99%

See 2 more Smart Citations

QTLomics in Soybean: A Way Forward for Translational Genomics and Breeding

et al. 2016

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“…A frameshift mutation in a sunflower FT paralog segregating at low frequency in wild populations experienced a selective sweep during domestication, and heterologous transformation studies in Arabidopsis indicate that this variant causes a photoperiod-specific delay in flowering through dominant-negative interference with the function of another FT paralog (Blackman et al, 2010;Blackman, 2013). Recent work also has associated cis-regulatory variants in FT homologs of soybean (Zhao et al, 2016) and sorghum (Sorghum bicolor; Cuevas et al, 2016) with the evolution of day-neutral varieties. Finally, FT has been implicated in the reduced photoperiod sensitivity of one Arabidopsis accession (Strange et al, 2011).…”

Section: Variation In Magnitude Of Photoperiodic Responsementioning

confidence: 99%

Changing Responses to Changing Seasons: Natural Variation in the Plasticity of Flowering Time

Blackman

2016

Plant Physiol.

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For plants that live in seasonally changing environments, timing is everything. Matching developmental transitions with the best times of year for growth and reproduction is necessary to maintain high fitness. Consequently, plants employ many mechanisms to sense and integrate multiple predictive seasonal cues to regulate their major developmental shifts. As the annual timing with which the growing season starts and ends changes across the landscape, natural selection has led to the evolution of the mechanisms that regulate the developmental plasticity of flowering among populations or varieties of species and crop plants that inhabit broad geographic ranges. There has been significant recent progress in describing the diversity of this variation in flowering time plasticity and in identifying the specific genetic changes responsible. Such work is an essential step toward understanding the processes that have shaped current and past adaptation, managing genetic diversity and improving crops in the face of climate change, and forecasting how populations may respond plastically and evolutionarily to future environmental challenges. In this Update, I review the findings of recent studies of natural variation in the plasticity of flowering to photoperiod, vernalization, and ambient temperature, and the implications and open questions raised by this work are considered.A fundamental adaptation of plants inhabiting seasonal environments is their ability to match the annual timing of major life history transitions to the local growing season. Most species achieve this synchrony through developmental plasticity. In other words, individuals sense how environmental cues like daylength and temperature change from winter to spring to summer to fall. The information gleaned from these cycles is then integrated molecularly so that germination, flowering, and other key transitions occur during periods favorable for growth, reproduction, and seed set. However, as the climate changes over the 21st century and the relative timing of annual cycles in temperature and precipitation shifts, once adaptive responses will no longer effectively predict the best calendar dates to initiate these essential developmental events (Nicotra et al., 2010;Wilczek et al., 2010). Because natural populations and cultivated landraces of many taxa have evolved to thrive in geographically diverse habitats and climates as their ranges have expanded, they harbor natural variants that may prove instructive in breeding crops and conserving native plant diversity in the face of future environmental challenges. Thus, a critical objective in plant biology is

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Genetic control of flowering time in legumes

Weller¹,

Macknight²

2019

The Model Legume Medicago Truncatula

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The timing of flowering, and in particular the degree to which it is responsive to the environment, is a key factor in the adaptation of a given species to various ecogeographic locations and agricultural practices. Flowering time variation has been documented in many crop legumes, and selection for specific variants has permitted significant expansion and improvement in cultivation, from prehistoric times to the present day. Recent advances in legume genomics have accelerated the process of gene identification and functional analysis, and opened up new prospects for a molecular understanding of flowering time adaptation in this important crop group. Within the legumes, two species have been prominent in flowering time studies; the vernalization-responsive long-day species pea (Pisum sativum) and the warm-season short-day plant soybean (Glycine max). Analysis of flowering in these species is now being complemented by reverse genetics capabilities in the model legumes Medicago truncatula and Lotus japonicus, and the emergence of genome-scale resources in a range of other legumes. This review will outline the insights gained from detailed forward genetic analysis of flowering time in pea and soybean, highlighting the importance of light perception, the circadian clock and the FT family of flowering integrators. It discusses the current state of knowledge on genetic mechanisms for photoperiod and vernalization response, and concludes with a broader discussion of flowering time adaptation across legumes generally.

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A recessive allele for delayed flowering at the soybean maturity locus E9 is a leaky allele of FT2a, a FLOWERING LOCUS T ortholog

Cited by 154 publications

References 57 publications

QTLomics in Soybean: A Way Forward for Translational Genomics and Breeding

QTLomics in Soybean: A Way Forward for Translational Genomics and Breeding

Changing Responses to Changing Seasons: Natural Variation in the Plasticity of Flowering Time

Genetic control of flowering time in legumes

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