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Related Experiment Video

Updated: Mar 30, 2026

Obtaining High-Quality Transcriptome Data from Cereal Seeds by a Modified Method for Gene Expression Profiling

Obtaining High-Quality Transcriptome Data from Cereal Seeds by a Modified Method for Gene Expression Profiling

Published on: May 21, 2020

Transcriptome-wide functional characterization reveals novel relationships among differentially expressed transcripts

Delasa Aghamirzaie¹, Dhruv Batra², Lenwood S Heath³

¹Genetics, Bioinformatics and Computational Biology Program, Virginia Tech, Blacksburg, VA, 24061, USA. delasa@vt.edu.

|November 18, 2015

Summary

This study introduces a computational framework to predict plant transcript functions, identifying 13% of soybean embryo transcripts as noncoding RNAs and revealing alternative splicing's role in seed maturation and desiccation tolerance.

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Area of Science:

Plant molecular biology
Computational biology
Transcriptomics

Background:

Transcriptomics reveals diverse transcripts with varying coding potential and strand orientation.
Alternative splicing (AS) generates protein variants with altered functional domains, indicating widespread transcriptional and post-transcriptional regulation.
Biological processes like seed maturation and desiccation are regulated post-transcriptionally, often via AS, producing multiple transcripts from a single locus.

Purpose of the Study:

To develop and apply an integrated computational framework for predicting isoform-specific functions of plant transcripts.
To investigate the role of alternative splicing in soybean embryo development and its impact on functional domains.
To analyze co-expression networks of transcripts involved in seed maturation and desiccation tolerance.

Main Methods:

Developed CodeWise, a plant-specific support vector machine classifier for predicting transcript coding potential (>96% accuracy).
Applied the framework to analyze 103,106 soybean transcripts, including 2,938 alternatively spliced variants.
Utilized sequence similarity, functional domain, and co-expression network analyses (ArrayMining, clustering).

Main Results:

CodeWise predicted 13% of soybean embryo transcripts as noncoding RNAs.
Alternative splicing led to global changes in functional domains and truncation of protein variants.
Identified specific sub-networks and potential interactions in signaling pathways related to seed maturation and desiccation tolerance, involving noncoding and antisense transcripts.

Conclusions:

The integrated framework enables experimentally testable predictions of transcript and protein function.
Noncoding and antisense transcripts play significant regulatory roles in soybean seed maturation and desiccation signaling.
Demonstrates a powerful approach for dissecting complex biological processes at the transcriptomic level.