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Comprehensive temporal reprogramming ensures dynamicity of transcriptomic profile for adaptive response in Taxus contorta

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Abstract

Plants respond to the environmental perturbations by triggering the dynamic changes within the transcriptome. The assessment of these oscillations within the transcriptome would offer insights into the ecological adaptation of the plants. We evaluated how the transcriptome of Taxus contorta swings under natural conditions to elucidate its adaptive response. Thus, our study provides new insights into the performance of T. contorta under a changing environment during different seasons. The abundance estimation using the RNAseq approach revealed 6727 differentially expressed genes. Comprehensive reprogramming was observed in Taxol biosynthesis, maintenance of redox homeostasis, and generation of effective shield to UV-B, high light intensity, and temperature. Besides differential expression, the alternative splicing (AS) and single nucleotide variations (SNVs) also confer flexibility to the transcriptome of T. contorta. 1936 differentially expressing transcripts were also found to exhibit Differential Exon Usage (DEU) as well as differential SNVs. LC–MS-based untargeted metabolic analysis revealed 7774 ion features, among which around 334 putatively identified metabolites were differentially regulated. Our results showed that the swing and the oscillations of the transcriptome and metabolome of T. contorta ensure adaptability and better survival under changing environment. In addition, varying patterns of AS and SNVs compliment the adaptation provided by differential expression.

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Data availability

The raw data can be retrieved from NCBI under the SRA accession numbers of SRX4951473, SRX4951472, SRX4951471 and SRX4951470.

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Acknowledgements

This study was financially supported by MoEF (Ministry of Environment and Forests), India under the grant NMHS/SG-2016/011. Aasim Majeed acknowledges CSIR New Delhi for financial assistance during PhD programme. The authors also acknowledge Ms. Shruti Choudhary for her valuable support during the metabolite analysis. We are grateful to the anonymous reviewer and associate editor for critically commenting on the manuscript.

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Authors and Affiliations

  1. Molecular Genetics Laboratory, Department of Botany, Central University of Punjab, City Campus, Mansa Road, Bathinda, 151001, India

    Aasim Majeed, Amandeep Singh & Pankaj Bhardwaj

  2. Biotechnology Department, CSIR - Institute of Himalayan Bioresource Technology, Pālampur, Himachal Pradesh, India

    Ram Kumar Sharma

  3. Department of Pharmaceutical Sciences and Natural Products, Central University of Punjab, Bathinda, India

    Vikas Jaitak

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  1. Aasim Majeed
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  2. Amandeep Singh
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Contributions

Pankaj Bhardwaj conceived and organized the overall study. Aasim Majeed carried out sampling, wet lab experiments, bioinformatic analysis and wrote the manuscript. Amandeep Singh participated in sampling and nucleic acid isolation. Ram Kumar Sharma and Vikas Jaitak contributed in Metabolite analysis. Pankaj Bhardwaj edited and approved the final version of the manuscript. All authors have carefully read and approved the manuscript.

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Correspondence to Pankaj Bhardwaj.

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Supplementary material 1—S1: Sequences of primers used in qRT-PCR. (DOCX 12 kb)

438_2020_1709_MOESM2_ESM.tif

Supplementary material 2—S2: Graphical representation of PCA before (left) and after (right) Batch effect correction and normalization. (TIFF 59 kb)

Supplementary material 3—S3: List of Differentially expressed transcripts. (CSV 645 kb)

Supplementary material 4—S4: Correlation graph of expression results obtained from RNAseq and qRT-PCP. (TIFF 445 kb)

Supplementary material 5—S5: List if Differentially expressed metabolites. (XLSX 30 kb)

Supplementary material 6—S6: Representation of Total Ion Chromatograms (TIC). (DOCX 61 kb)

Supplementary material 7—S7: MDS plot showing similarities or dissimilarities between samples. (DOCX 25 kb)

438_2020_1709_MOESM8_ESM.docx

Supplementary material 8—S8: Integrative pathway map based on integrative analysis of RNAseq and metabolite data. Red dots represent upregulation steps while green dots represent downregulated steps in winter as compared to summer. (DOCX 729 kb)

Supplementary material 9—S9: Transcripts corresponding to Transcription Factors. (XLSX 15 kb)

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Majeed, A., Singh, A., Sharma, R.K. et al. Comprehensive temporal reprogramming ensures dynamicity of transcriptomic profile for adaptive response in Taxus contorta. Mol Genet Genomics 295, 1401–1414 (2020). https://doi.org/10.1007/s00438-020-01709-2

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