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Optimizing Transcriptome Assemblies for Eleusine indica Leaf and Seedling by Combining Multiple Assemblies from Three
Shu Chen1, J Scott McElroy1, Fenny Dane2
1Dep. of Crop, Soil and Environmental Science, Auburn Univ., Auburn, AL, 36849.
The Plant Genome
|November 24, 2020
Summary
Researchers optimized transcriptomes for Eleusine indica using multiple assemblers and pipelines. The EvidentialGene pipeline yielded higher quality, less redundant transcript sets, crucial for studying herbicide resistance.
Area of Science:
- Plant genomics
- Bioinformatics
- Transcriptomics
Background:
- Advances in sequencing generate vast plant genomic and transcriptomic data, posing biocomputing challenges.
- High-quality transcriptome assembly is essential for successful transcriptomics studies.
Purpose of the Study:
- To compare de novo assemblers (Trinity, Velvet, CLC) and the EvidentialGene pipeline for optimizing transcript sets in Eleusine indica.
- To evaluate the impact of read number, k-mer size, and in silico normalization on assembly quality.
Main Methods:
- Two RNA sequencing datasets from Eleusine indica (leaf and seedling) were assembled using Trinity, Velvet, and CLC.
- Assemblies were processed through the EvidentialGene pipeline (tr2aacds) to refine transcript sets.
- Assembly outputs were compared based on contig number, N50, redundancy, and coding potential.
Main Results:
- Multiple assemblers and parameter sets were evaluated, with each contributing to the final transcript set.
- The EvidentialGene pipeline produced transcript sets with improved quality and reduced redundancy compared to Trinity.
- Specific transcripts related to target-site herbicide resistance were identified.
Conclusions:
- Optimized transcriptome references for Eleusine indica enhance the study of herbicide resistance.
- The findings are valuable for understanding evolutionary processes in Eleusine indica offspring.
