Sanchari Sircar received her doctorate in Bioinformatics. Her research work was supervised by Dr. Nita Parekh and thesis reviewed by Dr. Sudip Kundu (University of Calcutta), Dr. Milind Watve (IISER Pune), Prof. H A Nagarajaram (University of Hyderabad) and Dr. P K Vinod (CCNSB, IIIT Hyderabad)
Here’s a summary of Sanchari’s thesis, Rice Stress Transcriptome Analysis – A Network Biology Approach, as explained by her:
I started my journey in IIIT Hyderabad as an MS Bioinformatics student in Dr. Nita’s group. I subsequently converted into a PhD scholar. After my thesis submission in November 2019, I am currently working at Université Paris-Saclay in the Chromosome Dynamics group of Prof. Moussa Benhamed.
I thank my supervisor Dr. Nita Parekh and thesis reviewers Dr. Sudip Kundu (Univ. of Calcutta), Dr. Milind Watve (IISER Pune), Prof. H A Nagarajaram (Univ. of Hyderabad) and Dr. Vinod P.K. (CCNSB, IIIT Hyderabad) who helped me immensely in this journey.
The topic of my Ph.D is “Rice Stress Transcriptome Analysis – A Network Biology Approach”. Rice is a major staple food for half the world’s population. With the completion of rice genome sequencing projects and the availability of several high-throughput experimental platforms, a large amount of data is now available in the public domain. However, there still exists a gap between data generation and effective bioinformatic analyses of such data in the scientific community. In the era of Big Data, network-based approaches have made great strides in the field of biomedical research, personal therapeutics as well as in evo-devo studies. Taking cues from these studies, in this thesis, we use a network biology approach to get a systems-level understanding of the rice stress transcriptome, using microarray and RNA-seq data. In the first part of the study, we considered transcriptome data from a drought tolerant rice genotype and constructed a weighted condition-dependent gene co-expression network. Based on differential gene expression analysis, we identified tissue and stage-specific co-expressed modules harbouring differentially expressed genes that are induced or repressed due to stress. Network topological properties such as degree along with fold-change information are used to identify “hub” genes. Unannotated genes that are topologically important in the network and co-clustered with known stress-responsive genes are selected for functional characterization (Fig.1). Network-based concepts such as conserved network neighbourhood and guide-gene approach for the annotation of these novel drought-responsive genes together with promoter analysis led to the annotations of 26 uncharacterized genes. We also used alternate network construction methods to confirm the associations of the uncharacterized genes with their conserved neighbours.
Fig.1: Uncharacterized genes in Red module. Genes that are high degree and up-regulated across all developmental stages and tissues are depicted in ‘green’ color (having Arabidopsis orthologs) and ‘purple’ color (having no Arabidopsis orthologs). Their neighbours, identified as orthologs in the co-function network in AraNet are colored according to the average fold-change in drought samples. The edges in ‘brown’ denote conserved co-expressed links among genes in rice and Arabidopsis, while the ‘gray edges correspond to co-expressed links in Red module. The numbers in the bracket indicate the rank of the neighbours (based on edge weight) in AraNet.
In the second part of the thesis we present a meta-analytic study combining gene-expression data from seven drought-tolerant genotypes to identify various drought-adaptive processes in leaf tissue using network-based approach. Here, we propose an integrated approach that incorporates protein-protein interactions with co-expression of genes to construct networks of up and down-regulated genes and identify tightly-coupled gene clusters. Based on the processes/pathways represented by these clusters, we identified some important drought adaptive processes exhibited by these genotypes. Key transcription factors, viz., bZIPs, ABA signalling machinery and interaction of its signalling components with metabolic pathways playing a role in stress adaptive pathways was highlighted. In tandem do this, stomatal regulation and photosynthesis was observed to be important among the down-regulated processes. Based on the up and down-regulated processes, we proposed a model for the drought-tolerant processes as shown in Fig. 2.
Fig.2: A representative model for drought-responsive mechanisms in drought-tolerant genotypes. Red nodes indicate key genes and clusters up-regulated and part of uDTN. Blue nodes indicate key genes and processes down-regulated and part of dDTN. Green nodes indicate key processes affected by uDTN genes. Nodes with ‘*’ indicate uDTN seed genes.
In the final part of the thesis we present our analysis of RNAseq data to analyze stress responsive processes in rice under different abiotic stress conditions, namely, drought, cold, flood, salinity, etc. For this study, publicly available large-scale mRNA sequencing data of rice (Oryza sativa L. cv. Nipponbare) obtained under uniform experimental conditions for different abiotic stress conditions and time-points was considered. A weighted co-expression network was constructed across four stress conditions and two hormone treatments using differentially expressed genes (DEGs). Co-expressed modules enriched with DEGs with respect to different stress/treatment conditions were identified and analysed in detail Fig.3.
Fig. 3: Co-expressed modules in Shoot tissue. Up-regulated genes under drought stress mapped to MapMan bins.
Finally based on this data, we are developing an online resource “NetREx” (http://bioinf.iiit.ac.in/netrex/index.html) which will aid scientists query stress-responsive genes across different stress conditions and tissues and enable network-based analysis in rice.
References:
- Meta-analysis of Drought-tolerant Genotypes in Oryza sativa: A Network-based Approach, Sanchari Sircar and Nita Parekh, PLoS One, 14(5):e0216068. DOI: 10.1371/journal.pone.0216068
- Protocol for Co-expression Network Construction and Stress-responsive Expression Analysis in Brachypodium, Sanchari Sircar, Nita Parekh and Gaurav Sablok, “Brachypodium Genomics: Methods and Protocols”, Methods in Molecular Biology, 1667, pp203-221 (2018).
- Functional characterization of Drought-responsive Modules and Genes in Oryza sativa: A Network-based Approach, Sanchari Sircar and Nita Parekh, Frontiers in Genetics, 6, 256, (2015). DOI: 10.3389/fgene.2015.00256