Comparative de novo transcriptome analysis identifies salinity stress responsive genes and metabolic pathways in sugarcane and its wild relative Erianthus arundinaceus [Retzius] Jeswiet

Vignesh, P; Mahadevaiah, C.; Rangan, Parimalan; Ramanathan, V.; Dharshini, S. Akila Parvathy; Singh, Nisha; Suresha, G. S.; Swathi, S; Swamy, H. K. Mahadeva; Sreenivasa, V.; Mohanraj, K.; Hemaprabha, G.; Ram, Bakshi; Appunu, C.

doi:10.1038/s41598-021-03735-5

Cited by 5 publications

(2 citation statements)

References 124 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To assess performance, the human RNA-Seq dataset (HBR and UHR) was analyzed using the bestDEG web application. The DEGs were identified based on absolute log2FC >2 for upregulated genes and log2FC <−2 for downregulated genes with FDR <0.01 ( Zheng et al, 2020 ; Teng et al, 2020 ; Methot et al, 2021 ; Vignesh et al, 2021 ). The obtained consensus result and the result obtained from each DE analysis package were used to evaluate the performance statistics.…”

Section: Methodsmentioning

confidence: 99%

bestDEG: a web-based application automatically combines various tools to precisely predict differentially expressed genes (DEGs) from RNA-Seq data

Sangket

Yodsawat

Nuanpirom

et al. 2022

PeerJ

View full text Add to dashboard Cite

Background Differential gene expression analysis using RNA sequencing technology (RNA-Seq) has become the most popular technique in transcriptome research. Although many R packages have been developed to analyze differentially expressed genes (DEGs), several evaluations have shown that no single DEG analysis method outperforms all others. The validity of DEG identification could be increased by using multiple methods and producing the consensus results. However, DEG analysis methods are complex and most of them require prior knowledge of a programming language or command-line shell. Users who do not have this knowledge need to invest time and effort to acquire it. Methods We developed a novel web application called “bestDEG” to automatically analyze DEGs with different tools and compare the results. A differential expression (DE) analysis pipeline was created combining the edgeR, DESeq2, NOISeq, and EBSeq packages; selected because they use different statistical methods to identify DEGs. bestDEG was evaluated on human datasets from the MicroArray Quality Control (MAQC) project. Results The performance of the bestDEG web application with the human datasets showed excellent results, and the consensus method outperformed the other DE analysis methods in terms of precision (94.71%) and specificity (97.01%). bestDEG is a rapid and efficient tool to analyze DEGs. With bestDEG, users can select DE analysis methods and parameters in the user-friendly web interface. bestDEG also provides a Venn diagram and a table of results. Moreover, the consensus method of this tool can maximize the precision or minimize the false discovery rate (FDR), which reduces the cost of gene expression validation by minimizing wet-lab experiments.

show abstract

Section: Methodsmentioning

confidence: 99%

bestDEG: a web-based application automatically combines various tools to precisely predict differentially expressed genes (DEGs) from RNA-Seq data

Sangket

Yodsawat

Nuanpirom

et al. 2022

PeerJ

View full text Add to dashboard Cite

show abstract

“…The comparative transcriptome analysis of SBRs generated superior data compared to the earlier transcriptome data generated among Erianthus and commercial hybrids for salinity stress 47 . The transcriptome of SBRs showed higher differential expression in IND 04-1335 compared to the commercial variety Co 86032.…”

Section: Discussionmentioning

confidence: 96%

Comparative transcriptome profiling to unravel the key molecular signalling pathways and drought adaptive plasticity in shoot borne root system of sugarcane

Ramanathan

Swamy

Appunu

et al. 2023

Sci Rep

Self Cite

View full text Add to dashboard Cite

Sugarcane root system comprises of superficial sett roots as well as deeply-penetrating shoot borne roots (SBR) with latter being the permanent root system. In sugarcane, the healthy SBR contributes to a better crop yield and it also helps to produce multiple ratoon crops after the harvest. There is a dearth of in-depth knowledge on SBR system architecture and its functional role in modern day commercial hybrids. A comprehensive phenotypic, anatomical and whole transcriptome profiling, conducted between the commercial sugarcane hybrids and a wild germplasm Erianthus, found a developmental delay in both initiation and establishment of the SBR in commercial hybrid compared to Erianthus. The SBR system in Erianthus proved to be an extensive drought-adaptive root system architecture that significantly contributes to drought tolerance. On the other hand, SBRs in the commercial hybrids showed an irreversible collapse and damage of the root cells under drought stress. The outcomes from the comparative analysis of the transcriptome data showed a significant upregulation of the genes that regulate important stress signalling pathways viz., sugar, calcium, hormone signalling and phenylpropanoid biosynthesis in the SBRs of Erianthus. It was found that through these key signalling pathways, Erianthus SBRs triggered the downstream signalling cascade to impart physiological responses like osmoprotection, modification of the cell walls, detoxification of reactive oxygen species, expression of drought responsive transcription factors, maintenance of cell stability and lateral root development. The current study forms a basis for further exploration of the Shoot Borne Root system as a valuable breeding target to develop drought tolerant sugarcane genotypes.

show abstract

Comparative genome-wide characterization of salt responsive micro RNA and their targets through integrated small RNA and de novo transcriptome profiling in sugarcane and its wild relative Erianthus arundinaceus

Vignesh,

Mahadevaiah,

Selvamuthu

et al. 2023

3 Biotech

View full text Add to dashboard Cite

Comparative de novo transcriptome analysis identifies salinity stress responsive genes and metabolic pathways in sugarcane and its wild relative Erianthus arundinaceus [Retzius] Jeswiet

Cited by 5 publications

References 124 publications

bestDEG: a web-based application automatically combines various tools to precisely predict differentially expressed genes (DEGs) from RNA-Seq data

bestDEG: a web-based application automatically combines various tools to precisely predict differentially expressed genes (DEGs) from RNA-Seq data

Comparative transcriptome profiling to unravel the key molecular signalling pathways and drought adaptive plasticity in shoot borne root system of sugarcane

Comparative genome-wide characterization of salt responsive micro RNA and their targets through integrated small RNA and de novo transcriptome profiling in sugarcane and its wild relative Erianthus arundinaceus

Contact Info

Product

Resources

About