Identification and Characterization of Key Genes Responsible for Weedy and Cultivar Growth Types in Soybean
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA779255 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR16898042_1.fastq.gz | Fastqsanger.gz | |||
| SRR16898042_2.fastq.gz | Fastqsanger.gz | |||
| SRR16898043_1.fastq.gz | Fastqsanger.gz | |||
| SRR16898043_2.fastq.gz | Fastqsanger.gz | |||
| SRR16898044_1.fastq.gz | Fastqsanger.gz |
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Project description:We report total mRNA library using Illumina Nova Seq high-throughput sequencing platform platform for analysis of transcriptome between the two relatives of the soybean ie weedy and cultivar growth types in F7 generation derived from the crossing of wild and cultivated soybean.
2021-11-12 | GSE188519 | GEO
Project description:Research conducted, including the rationale: Weeds reduce yield in soybeans through incompletely defined mechanisms. The effects of weeds on the soybean transcriptome were evaluated in field conditions during four separate gR1.fastqing seasons. Methods: RNASeq data were collected from 6 biological samples of soybeans gR1.fastqing with or without weeds. Weed species and the methods to maintain weed free controls varied between years to mitigate treatment effects and to allow detection of general soybeans weed responses. Key results: Soybean plants were not visibly nutrient or water stressed. We identified 55 consistently down-regulated genes in weedy plots. Many of the down-regulated genes were heat shock genes. Fourteen genes were consistently up-regulated. Several transcription factors including a PHYTOCHROME INTERACTING FACTOR 3-like gene (PIF3) were included among the up-regulated genes. Gene set enrichment analysis indicated roles for increased oxidative stress and jasmonic acid signaling responses during weed stress. Main conclusion: The relationship of this weed-induced PIF3 gene to genes involved in shade avoidance responses in arabidopsis provide evidence that this gene may be important in the response of soybean to weeds. These results suggest the weed-induced PIF3 gene will be a target for manipulating weed tolerance in soybean. Samples were collected from two treatments ("Control" and "Weedy") with six biological replicates (2008, 2009, and twop each for 2010 and 2011) for each treatment.
2014-07-30 | E-GEOD-59875 | biostudies-arrayexpress
Project description:In cultivated plants, shoot morphology is an important factor that influences crop economic value. However, the effects of gene expression patterns on shoot morphology are not clearly understood. In this study, the molecular mechanism behind shoot morphology (including leaf, stem, and node) was analyzed using RNA sequencing to compare weedy (creeper) and cultivar (stand) growth types obtained in F7 derived from a cross of wild and cultivated soybeans. A total of 12,513 (in leaves), 14,255 (in stems), and 11,850 (in nodes) differentially expressed genes were identified among weedy and cultivar soybeans. Comparative transcriptome and expression analyses revealed 22 phytohormone-responsive genes. We found that GIBBERELLIN 2-OXIDASE 8 (GA2ox), SPINDLY (SPY), FERONIA (FER), AUXIN RESPONSE FACTOR 8 (ARF8), CYTOKININ DEHYDROGENASE-1 (CKX1), and ARABIDOPSIS HISTIDINE KINASE-3 (AHK3), which are crucial phytohormone response genes, were mainly regulated in the shoot of weedy and cultivar types. These results indicate that interactions between phytohormone signaling genes regulate shoot morphology in weedy and cultivar growth type plants. Our study provides insights that are useful for breeding and improving crops to generate high-yield soybean varieties.
| S-EPMC8907156 | biostudies-literature
Project description:Research conducted, including the rationale: Weeds reduce yield in soybeans through incompletely defined mechanisms. The effects of weeds on the soybean transcriptome were evaluated in field conditions during four separate gR1.fastqing seasons. Methods: RNASeq data were collected from 6 biological samples of soybeans gR1.fastqing with or without weeds. Weed species and the methods to maintain weed free controls varied between years to mitigate treatment effects and to allow detection of general soybeans weed responses. Key results: Soybean plants were not visibly nutrient or water stressed. We identified 55 consistently down-regulated genes in weedy plots. Many of the down-regulated genes were heat shock genes. Fourteen genes were consistently up-regulated. Several transcription factors including a PHYTOCHROME INTERACTING FACTOR 3-like gene (PIF3) were included among the up-regulated genes. Gene set enrichment analysis indicated roles for increased oxidative stress and jasmonic acid signaling responses during weed stress. Main conclusion: The relationship of this weed-induced PIF3 gene to genes involved in shade avoidance responses in arabidopsis provide evidence that this gene may be important in the response of soybean to weeds. These results suggest the weed-induced PIF3 gene will be a target for manipulating weed tolerance in soybean.
2021-03-23 | GSE59875 | GEO
Project description:Purpose: Soybean aphid (Aphis glycines Matsumura; SBA) is major pest of soybean (Glycine max) in the United States of America. One previous study on soybean, soybean-aphid interactions showed that avirulent (biotype 1) and virulent (biotype 2) biotypes can co-occur and potentially interact on resistant and susceptible soybean resulting induced susceptibility. The main objective of this research was to employ RNA sequencing technique to characterize the induced susceptibility effect in which initial feeding by virulent aphids can increase the suitability of avirulent aphids in both susceptible and resistant cultivars. Methods: The data in this submission come from the green house experiment using two genotypes of soybean: susceptible soybean cultivar was LD12-15838R and the resistant cultivar was LD12-15813Ra (with Rag1 gene) and two aphid populations: biotype 1 (avirulent) and biotype 2 (virulent biotype 2). RNA was extracted from the leave samples from resistant and susceptible cultivars treated with no aphids, biotype 2: biotype1 collected at day 1 and no aphids, biotype 2: biotype1 and no aphids: biotype1 at day 11 using PureLink RNA mini kit (Invitrogen, USA). RNA samples were treated with TURBOTM DNase (Invitrogen, USA) to remove any DNA contamination following the manufacturer’s instructions. Assessment of the isolated RNA integrity was performed by 1% agarose gel electrophoresis, and RNA concentration was measured by Nanodrop 2000 (Thermo Fisher Scientific, USA). Three replicates from these treatments in resistant and susceptible cultivars were pooled in equimolar concentration. RNAseq library construction was prepared using Illumina’s TruSeq Stranded mRNA Kit v1 (San Diego, CA). The libraries were quantified by QuBit dsDNA HS Assay (Life Technologies, Carlsbad, CA) and pooled in equimolar concentrations. The libraries were sequenced on an Illumina NextSeq 500 using a NextSeq 500/550 High Output Reagent Cartridge v2 (San Diego, CA) at 75 cycles. Results: A total of 10 RNA libraries were prepared and sequenced with the sequencing depth ranging from 24,779,816 to 29,72,4913. Total reads of 266,535,654 were subjected to FastQC analysis to determine the data quality using various quality metrics such as mean quality scores, per sequence quality scores, per sequence GC content, and sequence length distribution. The phred quality scores per base for all the samples were higher than 30. The GC content ranged from 45 to 46% and followed the normal distribution. After trimming, more than 99% of the reads were retained as the clean and good quality reads. Upon mapping these reads, we obtained high mapping rate ranging from 90.4% to 92.9%. Among the mapped reads, 85.8% to 91.9% reads were uniquely mapped. Conclusions: The objective of this study is to characterize the mechanism of induced susceptibility in soybean via transcriptional response study of soybean in presence of biotype 1 and biotype 2 soybean aphids using RNA-Seq. The data resulted from this study might provide insights into the interactions between soybean and soybean aphids and identify genes, their regulation and enriched pathways that may be associated with resistance or susceptibility to A. glycines.
2019-04-26 | GSE129626 | GEO
Project description:RNA-seq was used to characterize gene expression in soybean from a wide range of tissues. The primary focus of the project was small RNAs, and the identification of microRNAs and phased siRNA-generating loci, but RNA-seq data were generated from the same samples. This project was supported by the United Soybean Board.
2020-05-09 | GSE150157 | GEO
Project description:Soybean is a critical source of vegetable protein, yet its proteome remains under-characterized. Here, we quantify 12,855 proteins across 14 soybean organs using 4D-data-independent acquisition mass spectrometry (4D-DIA-MS), creating the most extensive soybean proteome dataset to date. Organ-specific protein expression and co-expression analyses highlight functional specificity, with significant differences in protein-transcript abundance across organs. We also map N6-methyladenosine (m6A) modifications, identifying their key role in post-transcriptional protein regulation. Integrative analysis of proteome and m6A methylome identifies novel regulator in m6A methylation. This comprehensive proteomic and m6A landscape advances our understanding of soybean biology and provides a valuable resource for crop improvement.
2025-05-18 | GSE262990 | GEO
Project description:We investigated soybean seed development because (1) soybean seeds are a major source of food and fuel, (2) soybean seeds have been an excellent system for studying the basic processes controlling seed development for over three decades, and (3) new soybean genomic resources, including the sequence of the soybean genome and the gene expression profiles for all seed compartments, tissues, and cell types, can be used to gain new insights into the regulatory processes required for seed differentiation. We sequenced messenger RNA populations of specific soybean seed compartments, which will provide new insights into gene expression that are important for “making a soybean seed.”
2014-05-07 | GSE57350 | GEO
Project description:We investigated soybean seed development because (1) soybean seeds are a major source of food and fuel, (2) soybean seeds have been an excellent system for studying the basic processes controlling seed development for over three decades, and (3) new soybean genomic resources, including the sequence of the soybean genome and the gene expression profiles for all seed compartments, tissues, and cell types, can be used to gain new insights into the regulatory processes required for seed differentiation. We sequenced messenger RNA populations of specific soybean seed compartments, which will provide new insights into gene expression that are important for “making a soybean seed.”
2014-05-07 | GSE57349 | GEO
Project description:We investigated soybean seed development because (1) soybean seeds are a major source of food and fuel, (2) soybean seeds have been an excellent system for studying the basic processes controlling seed development for over three decades, and (3) new soybean genomic resources, including the sequence of the soybean genome and the gene expression profiles for all seed compartments, tissues, and cell types, can be used to gain new insights into the regulatory processes required for seed differentiation. We sequenced messenger RNA populations of specific soybean seed compartments, which will provide new insights into gene expression that are important for “making a soybean seed.”
2014-05-14 | GSE57606 | GEO