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Protein-protein interactions of transcription factors from the drought QTL-hotspot linked to stress tolerance in chickpea Abirami Ramalingam, Himabindu Kudapa, Spurthi N Nayak, Lekha Pazhamala, Deepa Jaganathan, Sandeep Kale, L Krishnamurthy, Pooran M Gaur, Rajeev K Varshney* International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India *Address for correspondence: [email protected] Abstract TFs Interactor Mode of action Evidence Confidence Score DREB7 ICE1 Activation, Expression Text mining 0.983 LT178 N/A Co-expression 0.958 ABF2 Binding Text mining 0.900 WRKY34 Expression Text mining 0.812 ERF 110-like Amino acid Transporter N/A Text mining 0.921 Exonuclease N/A Text mining 0.921 Glycine rich protein N/A Text mining 0.919 LTP N/A Text mining 0.919 TFID- like TAF13 N/A Experiments and Text Mining 0.999 EER4 N/A 0.999 TBP2 Binding 0.828 TBP1 Binding 0.828 PPI predicted for the TF (STRING v.9.05) PPI predicted based on the high similarity of Arabidopsis DREB1A with chickpea DREB7, Arabidopsis AP2- domain TF with chickpea ERF 110-like and Arabidopsis TAF8 with chickpea Inclusive Market-Oriented Development (IMOD) – our approach to bringing prosperity in the drylands. ICRISAT is a member of the CGIAR Consortium. DREB7 AP2/ERF DNA binding domain. Confidence:99.9% TFID-like Bromodomain associated Confidence:99.2% Differential expression of the TFs under drought stress ERF 110-like AP2, GCC box DNA binding domain. Confidence:99.9% Predictive modelling of the TF functional domains (Phyre 2, DeepView v4.1.0) Gene enrichment and expression analysis identified 13 candidate genes including 3 TFs ‘QTL-hotspot’ identified from the biparental population (ICC 4958 × ICC 1882) for drought tolerance related traits Identification of candidate genes from the ‘QTL-hotspot’ Analysis of predicted (STRING) functional partners with high confidence score JG 11 X ICC 4958 (high performing) (tolerant ; donor) Three back crosses with JG 11 JG 11+ (BC 3 F 3 ) (tolerant, high performing) The 3 TFs DREB7, ERF-110-like and TFID - like identified from chickpea ‘QTL-hotspot’ are potential candidate genes that may have suitable application in improving tolerance in chickpea Further investigation is being carried out using Y2H to confirm their physical interactions in the yeast system Summary Drought is the most prominent abiotic stress that affects the productivity of chickpea. The signalling networks in response to drought comprise several major components that include transcription factors (TFs). Drought related QTL analysis identified a genomic region (QTL-hotspot) in the chickpea biparental population (ICC 4958 × ICC 1882) that comprise several genes. Gene enrichment and expression analyses identified 13 genes which include genes of 3 TF such as : a dehydration responsive element binding protein (DREB7), ethylene responsive factor like (ERF 110-like) and a transcription initiation factor like (TFID like). qRT-PCR data showed 2 to 6 fold differences between the contrasting drought responsive chickpea genotypes for these TFs. To further understand their roles and the ability to interact with other components in the stress signalling pathways, predictive protein-protein interaction (PPI) analysis was performed with STRING 9.1 using A. thaliana as a reference model. Using query sequences with similarity to these TFs, several potential interactors were identified and the ones with the highest confident scores were selected. DREB7 possibly interacts with Ice 1 (Inducer of CBF Expression1) and ABF2 (Abscisic acid responsive elements-binding factor 2). TFID-like showed predictive interaction with other transcription factors such as TAFs (TBP-Associated factors) and EER4 (Enhanced ethylene response) while ERF 110-like showed predictive interactions with an LTP (Lipid transfer protein) and an amino acid transporter protein. Yeast two hybrid screening has been initiated to validate protein interactions of these TFs. This study will enhance the identification of candidate genes linked to drought tolerance for chickpea crop improvement.
