Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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RNA-seq of seven stages of soybean cotyledon development


ABSTRACT: To understand the genetic mechanisms involved in the functional transition of cotyledons from non-photosynthetic storage tissue to metabolically active photosynthetic tissue during soybean seedling development, we constructed seven different RNA-Seq libraries using cotyledons from each developmental stage separately. Analysis of RNA-Seq data from different developmental stages revealed the differential expression of many genes including transcription factors. In this study, we focused on NAC and YABBY transcription factors which showed a conspicuous expression pattern during soybean seedling development. Their expression gradually increases from stage 1 to stage 4 of soybean germinating cotyledons. The highest level of expression was found at stage 4. Then it gradually decreased as the germinating cotyledons develop a mature seedling. We investigated the differential expression of NAC and YABBY regulated genes between stage 3 (before the functional transition) and stage 6 (after the functional transition) using our RNA-Seq data. Based on our RNA-Seq data, we found that 10 genes are up-regulated and 21 genes are down-regulated by NAC transcription factor. Similarly we found that 19 genes are up-regulated and 27 genes are down-regulated by YABBY transcription factor. High-throughput sequencing using Illumina HiSeq 2000 (RNA-Seq) was performed on seven developmental stages of soybean seedlings, with two biological replicates per stage.

ORGANISM(S): Glycine max

SUBMITTER: Lila Vodkin 

PROVIDER: E-GEOD-42550 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Direct detection of transcription factors in cotyledons during seedling development using sensitive silicon-substrate photonic crystal protein arrays.

Jones Sarah I SI   Tan Yafang Y   Shamimuzzaman Md M   George Sherine S   Cunningham Brian T BT   Vodkin Lila L  

Plant physiology 20150129 3


Transcription factors control important gene networks, altering the expression of a wide variety of genes, including those of agronomic importance, despite often being expressed at low levels. Detecting transcription factor proteins is difficult, because current high-throughput methods may not be sensitive enough. One-dimensional, silicon-substrate photonic crystal (PC) arrays provide an alternative substrate for printing multiplexed protein microarrays that have greater sensitivity through an i  ...[more]

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