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. 2022 Oct 28;12(1):18195.
doi: 10.1038/s41598-022-21828-7.

Transcriptome analysis of mulberry (Morus alba L.) leaves to identify differentially expressed genes associated with post-harvest shelf-life elongation

Dipayan Das  1   2 , Subires Bhattacharyya  1   2 , Monidipa Bhattacharyya  1 , Puja Sashankar #  3 , Arindam Ghosh #  4   5 , Palash Mandal  6   7
Affiliations

Transcriptome analysis of mulberry (Morus alba L.) leaves to identify differentially expressed genes associated with post-harvest shelf-life elongation

Dipayan Das et al. Sci Rep. .

Abstract

Present study deals with molecular expression patterns responsible for post-harvest shelf-life extension of mulberry leaves. Quantitative profiling showed retention of primary metabolite and accumulation of stress markers in NS7 and CO7 respectively. The leaf mRNA profiles was sequenced using the Illumina platform to identify DEGs. A total of 3413 DEGs were identified between the treatments. Annotation with Arabidopsis database has identified 1022 DEGs unigenes. STRING generated protein-protein interaction, identified 1013 DEGs nodes with p < 1.0e-16. KEGG classifier has identified genes and their participating biological processes. MCODE and BiNGO detected sub-networking and ontological enrichment, respectively at p ≤ 0.05. Genes associated with chloroplast architecture, photosynthesis, detoxifying ROS and RCS, and innate-immune response were significantly up-regulated, responsible for extending shelf-life in NS7. Loss of storage sucrose, enhanced activity of senescence-related hormones, accumulation of xenobiotics, and development of osmotic stress inside tissue system was the probable reason for tissue deterioration in CO7. qPCR validation of DEGs was in good agreement with RNA sequencing results, indicating the reliability of the sequencing platform. Present outcome provides a molecular insight regarding involvement of genes in self-life extension, which might help the sericulture industry to overcome their pre-existing problems related to landless farmers and larval feeding during monsoon.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Physical texture of mulberry leaves at the end of preservation period in comparison with fresh leaves. (A) Fresh leaf, (B) 7 day preserved leaf in distilled water and (C) 7 day preserved leaf in nanosilver solution.
Figure 2
Figure 2
Comparative evaluation of (A) total chlorophyll, (B) carotenoids, (C) total protein, (D, E) total and reducing sugar, (F) hydrogen peroxide, (G) Malondialdehyde, (H) superoxide and (I) proline content between 7 day preserved leaves in distilled water (CO7) and nanosilver solution (NS7) with respect to fresh leaves (FR0). The results were expressed as Mean ± SDEV, n = 3. Values with different letters (a, b, c, etc.) differ significantly (p ≤ 0.05) by Duncan’s Multiple Range Test (DMRT).
Figure 3
Figure 3
Flowchart describing the steps of data procession and subsequent analysis of differentially expressed genes.
Figure 4
Figure 4
Top hits organism distribution of transcriptome annotation with plantNR database.
Figure 5
Figure 5
Top hits organism distribution of transcriptome annotation with PMN database.
Figure 6
Figure 6
Length distribution of identified SSRs.
Figure 7
Figure 7
Scatter-plot displaying differentially expressed isoforms (A) and unigenes (B).
Figure 8
Figure 8
Violin plot representing the log2FoldChanges of differentially expressed up-regulated and down-regulated (A) isoforms and (B) unigenes. The value within the violin indicates average log2FoldChange.
Figure 9
Figure 9
MA plot representing differential expression genes in terms of up-regulated and down-regulated (A) isoforms and (B) unigenes. The values are represented as the function of logFC vs. logCPM at p value of < 0.05 and FDR rate of < 0.05.
Figure 10
Figure 10
Hierarchical clustering of differentially expressed top 5% up-regulated (A) isoforms and (B) unigenes in relation to NS7 vs. CO7. The higher score with different colour represents the higher level of expression.
Figure 11
Figure 11
Hierarchical clustering of differentially expressed top 5% down-regulated (A) isoforms and (B) unigenes in relation to NS7 vs CO7. The higher score with different colour represents the higher level of expression.
Figure 12
Figure 12
Category wise distribution of differentially expressed (A) up-regulated and (B) down-regulated genes on annotation with Arabidopsis database.
Figure 13
Figure 13
Topological networking of STRING (second round) generated up-regulated (A) and down-regulated (B) gene interaction data using Cytoscape platform (version 3.7.1; https://cytoscape.org/). For up-regulated genes Cytoscape connected 65 nodes with network density and homogeneity of 0.143 and 0.613 respectively, with characteristic path length of 2.480 and average number of neighbours of 9.169. For down-regulated genes Cytoscape connected 74 nodes with network density and homogeneity of 0.080 and 0.690 respectively, with characteristic path length of 2.785 and average number of neighbours of 5.835.
Figure 14
Figure 14
Functional sub-networking of highly interconnected nodes (up-regulated genes) using MCODE (version 2.0.0). Networks were built considering node density and node score cut-off value of 0.1, 0.2 respectively, with kappa-core value of 2.
Figure 15
Figure 15
Functional sub-networking of highly interconnected nodes (down-regulated genes) using MCODE (version 2.0.0). Networks were built considering note density and node score cut-off value of 0.1, 0.2 respectively, with kappa-core value of 2.
Figure 16
Figure 16
Gene ontological enrichment analysis of topologically selected up-regulated (A) and down-regulated (B) genes based on biological process using BiNGO (version 3.0.4) considering Arabidopsis as model organism. Hypergeometric test was conducted, considering p value cut off ≤ 0.05. Size of the node was proportional to the number of gene (transcripts) present under a particular nodal category. Node colour shades were according to the significance level. For up-regulated genes white represents no significant differences, yellow and green colour shade represents significance level at p = 0.05 and < 0.0000005 respectively. Similarly for down-regulated genes white represents no significant differences, green and blue colour shade represents significance level at p = 0.05 and < 0.0000005 respectively.
Figure 17
Figure 17
Kyoto Encyclopaedia of Genes and Genomes (KEGG) classification of top differentially expressed (up-regulated) genes. The genes were enlisted at the top and the colour pattern (green shades) indicates the involvement of a particular gene in a particular KEGG pathway.
Figure 18
Figure 18
Kyoto Encyclopaedia of Genes and Genomes (KEGG) classification of top differentially expressed (down-regulated) genes. The genes were enlisted at the top and the colour pattern (blue shades) indicates the involvement of a particular gene in a particular KEGG pathway.
Figure 19
Figure 19
Validation of key differentially expressed up-regulated (I) and down-regulated (II) genes using qRT-PCR analysis. The y-axis indicates relative quantification of the genes and the studied genes were indicated in the x-axis. Error bar indicates the value of standard deviation (± SD).
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References

    1. Rahmathulla VK. Management of climatic factors for successful silkworm (Bombyx mori L.) crop and higher silk production: A Review. Psyche. 2012 doi: 10.1155/2012/121234. - DOI
    1. Bukhari R, Kour H. Background, current scenario and future challenges of the indian silk industry. Int. J. Curr. Microbiol. App. Sci. 2019;8(5):2448–2463.
    1. Lakshmanan S, Balasaraswathi S, Mani A. Rural labour employment through mulberry sericulture: An analysis of cross sectional study. J. Rural Dev. 2011;30(2):155–167.
    1. Kumaresan, P., Jaishankar, Qadri, S.M.H. Impact of urbanisation on sericulture development in Karnataka. J. Rural Dev. (Hyderabad) 29(2), 113–123 (2010).
    1. Sharma P, Jha AB, Dubey RS, Pessarakli M. Reactive oxygen species, oxidative damage, and antioxidative defense mechanism in plants under stressful conditions. J. Bot. 2012 doi: 10.1155/2012/217037. - DOI

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