Diurnal Expression Pattern, Allelic Variation, and Association Analysis Reveal Functional Features of the E1 Gene in Control of Photoperiodic Flowering in Soybean

Zhai, Hong; Lü, Shixiang; Wu, Hongyan; Zhang, Yupeng; Zhang, Xingzheng; Yang, Jason; Wang, Yaying; Yang, Guang; Qiu, Hongmei; Cui, Tingting; Xia, Zhengjun

doi:10.1371/journal.pone.0135909

Cited by 23 publications

(26 citation statements)

References 35 publications

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“…E1 encodes a nuclear-localized B3 domain-containing protein, suppresses both GmFT2a and GmFT5a expression, two FT orthologs promoting early flowering in soybean (Xia et al, 2012a ). E1 expression is suppressed in short day, which is regarded as the main factor for soybean being a short day plant (Xia et al, 2012a ; Zhai et al, 2015 ; Zhang et al, 2016 ). E2 encodes a homolog of GIGANTEA , controls soybean flowering through regulation of GmFT2a expression but not GmFT5a (Watanabe et al, 2011 ).…”

Section: Introductionmentioning

confidence: 99%

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Genotyping of Soybean Cultivars With Medium-Density Array Reveals the Population Structure and QTNs Underlying Maturity and Seed Traits

Wang

et al. 2018

Front. Plant Sci.

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Soybean was domesticated about 5,000 to 6,000 years ago in China. Although genotyping technologies such as genotyping by sequencing (GBS) and high-density array are available, it is convenient and economical to genotype cultivars or populations using medium-density SNP array in genetic study as well as in molecular breeding. In this study, 235 cultivars, collected from China, Japan, USA, Canada and some other countries, were genotyped using SoySNP8k iSelect BeadChip with 7,189 single nucleotide polymorphisms (SNPs). In total, 4,471 polymorphic SNP markers were used to analyze population structure and perform genome-wide association study (GWAS). The most likely K value was 7, indicating this population can be divided into 7 subpopulations, which is well in accordance with the geographic origins of cultivars or accession studied. The LD decay rate was estimated at 184 kb, where r2 dropped to half of its maximum value (0.205). GWAS using FarmCPU detected a stable quantitative trait nucleotide (QTN) for hilum color and seed color, which is consistent with the known loci or genes. Although no universal QTNs for flowering time and maturity were identified across all environments, a total of 30 consistent QTNs were detected for flowering time (R1) or maturity (R7 and R8) on 16 chromosomes, most of them were corresponding to known E1 to E4 genes or QTL region reported in SoyBase (soybase.org). Of 16 consistent QTNs for protein and oil contents, 11 QTNs were detected having antagonistic effects on protein and oil content, while 4 QTNs soly for oil content, and one QTN soly for protein content. The information gained in this study demonstrated that the usefulness of the medium-density SNP array in genotyping for genetic study and molecular breeding.

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Section: Introductionmentioning

confidence: 99%

“…Many quantitative trait loci (QTL) or quantitative trait nucleotide (QTN) related to soybean flowering time (first flowering, R1) and maturity have also been documented at SoyBase ( http://soybase.org ). Many genes or QTL might regulate flowering time through regulation of the expression of the E1 gene (Zhai et al, 2015 ).…”

Section: Introductionmentioning

confidence: 99%

Genotyping of Soybean Cultivars With Medium-Density Array Reveals the Population Structure and QTNs Underlying Maturity and Seed Traits

Wang

et al. 2018

Front. Plant Sci.

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“…Recent study indicated that circadian clocks control several physiological events such as photosynthesis and stress response ( Dodd et al, 2005 , 2014 ; Covington et al, 2008 ; Lai et al, 2012 ). In addition, controlling circadian clocks has potential to enhance productivity of cultivated species such as broccoli, petunia and lettuce by effects on growth, floral induction and pest resistance ( Goodspeed et al, 2013 ; Fenske et al, 2015 ; Higashi et al, 2015 ; Tanigaki et al, 2015 ; Thiruvengadam et al, 2015 ; Zhai et al, 2015 ). These results show that controlling circadian clocks has potential to achieve high efficiency in plant production.…”

Section: Introductionmentioning

confidence: 99%

Circadian Oscillation of the Lettuce Transcriptome under Constant Light and Light–Dark Conditions

et al. 2016

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Although, the circadian clock is a universal biological system in plants and it orchestrates important role of plant production such as photosynthesis, floral induction and growth, there are few such studies on cultivated species. Lettuce is one major cultivated species for both open culture and plant factories and there is little information concerning its circadian clock system. In addition, most of the relevant genes have not been identified. In this study, we detected circadian oscillation in the lettuce transcriptome using time-course RNA sequencing (RNA-Seq) data. Constant light (LL) and light–dark (LD) conditions were used to detect circadian oscillation because the circadian clock has some basic properties: one is self-sustaining oscillation under constant light and another is entrainment to environmental cycles such as light and temperature. In the results, 215 contigs were detected as common oscillating contigs under both LL and LD conditions. The 215 common oscillating contigs included clock gene-like contigs CCA1 (CIRCADIAN CLOCK ASSOCIATED 1)-like, TOC1 (TIMING OF CAB EXPRESSION 1)-like and LHY (LATE ELONGATED HYPOCOTYL)-like, and their expression patterns were similar to those of Arabidopsis. Functional enrichment analysis by GO (gene ontology) Slim and GO Fat showed that the GO terms of response to light stimulus, response to stress, photosynthesis and circadian rhythms were enriched in the 215 common oscillating contigs and these terms were actually regulated by circadian clocks in plants. The 215 common oscillating contigs can be used to evaluate whether the gene expression pattern related to photosynthesis and optical response performs normally in lettuce.

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“…First, reference genes must show an expression level which is high enough to be quantified easily, or at least without difficulty, in applications, particularly RT-qPCR. To determine a practical threshold to evaluate the ease of quantification, distributions of FPKM values were investigated in 16 genes that have been practically used in RTqPCR as reference genes by researchers (Abiko et al, 2005;Benschop et al, 2007;Papdi et al, 2008;Streitner et al, 2008;Li et al, 2009;Li et al, 2010;Fontaine et al, 2012;Kudo et al, 2012;Zhang et al, 2013;Wang et al, 2014;Yin et al, 2014;Gonzalez-Cabanelas et al, 2015;Kamada-Nobusada et al, 2015;Patil et al, 2015;Zhai et al, 2015). In 15 of the 16 genes, the 25th percentile of the FPKM values was above 10; the exception was the Arabidopsis PPR gene, all of whose FPKM values were below 10 ( Supplementary Fig.…”

Section: Resultsmentioning

confidence: 99%

Identification of reference genes for quantitative expression analysis using large-scale RNA-seq data of <i>Arabidopsis thaliana</i> and model crop plants

et al. 2016

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In quantitative gene expression analysis, normalization using a reference gene as an internal control is frequently performed for appropriate interpretation of the results. Efforts have been devoted to exploring superior novel reference genes using microarray transcriptomic data and to evaluating commonly used reference genes by targeting analysis. However, because the number of specifically detectable genes is totally dependent on probe design in the microarray analysis, exploration using microarray data may miss some of the best choices for the reference genes. Recently emerging RNA sequencing (RNA-seq) provides an ideal resource for comprehensive exploration of reference genes since this method is capable of detecting all expressed genes, in principle including even unknown genes. We report the results of a comprehensive exploration of reference genes using public RNA-seq data from plants such as Arabidopsis thaliana (Arabidopsis), Glycine max (soybean), Solanum lycopersicum (tomato) and Oryza sativa (rice). To select reference genes suitable for the broadest experimental conditions possible, candidates were surveyed by the following four steps: (1) evaluation of the basal expression level of each gene in each experiment; (2) evaluation of the expression stability of each gene in each experiment; (3) evaluation of the expression stability of each gene across the experiments; and (4) selection of top-ranked genes, after ranking according to the number of experiments in which the gene was expressed stably. Employing this procedure, 13, 10, 12 and 21 top candidates for reference genes were proposed in Arabidopsis, soybean, tomato and rice, respectively. Microarray expression data confirmed that the expression of the proposed reference genes under broad experimental conditions was more stable than that of commonly used reference genes. These novel reference genes will be useful for analyzing gene expression profiles across experiments carried out under various experimental conditions.

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Diurnal Expression Pattern, Allelic Variation, and Association Analysis Reveal Functional Features of the E1 Gene in Control of Photoperiodic Flowering in Soybean

Cited by 23 publications

References 35 publications

Genotyping of Soybean Cultivars With Medium-Density Array Reveals the Population Structure and QTNs Underlying Maturity and Seed Traits

Genotyping of Soybean Cultivars With Medium-Density Array Reveals the Population Structure and QTNs Underlying Maturity and Seed Traits

Circadian Oscillation of the Lettuce Transcriptome under Constant Light and Light–Dark Conditions

Identification of reference genes for quantitative expression analysis using large-scale RNA-seq data of <i>Arabidopsis thaliana</i> and model crop plants

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