Non-coding RNA’s like miRNA, lncRNA, have gained immense importance as a significant regulatory factor in different physiological and developmental processes in plants. In an effort to understand the molecular role of these regulatory agents, in the present study, 3019 lncRNAs and 227 miRNAs were identified from different seed and pod developmental stages in Pigeonpea, a major grain legume of Southeast Asia and Africa. Target analysis revealed that 3768 mRNAs, including 83 TFs were targeted by lncRNAs; whereas 3060 mRNA, including 154 TFs, were targeted by miRNAs. The targeted transcription factors majorly belong to WRKY, MYB, bHLH, etc. families; whereas the targeted genes were associated with the embryo, seed, and flower development. Total 302 lncRNAs interact with miRNAs and formed endogenous target mimics (eTMs) which leads to sequestering of the miRNAs present in the cell. Expression analysis showed that notably, Cc_lncRNA-2830 expression is up-regulated and sequestrates miR160h in pod leading to higher expression of the miR160h target gene, Auxin responsive factor-18. A similar pattern was observed for SPIKE, Auxin signaling F-box-2, Bidirectional sugar transporter, and Starch synthetase-2 eTMs. All the identified target mRNAs code for transcription factor and genes are involved in the processes like cell division, plant growth and development, starch synthesis, sugar transportation and accumulation of storage proteins which are essential for seed and pod development. On a combinatorial basis, our study provides a lncRNA and miRNA based regulatory insight into the genes governing seed and pod development in Pigeonpea.
Pigeonpea, a tropical photosensitive crop, harbors significant diversity for days to flowering, but little is known about the genes that govern these differences. Our goal in the current study was to use genome wide association strategy to discover the loci that regulate days to flowering in pigeonpea. A single trait as well as a principal component based association study was conducted on a diverse collection of 142 pigeonpea lines for days to first and fifty percent of flowering over 3 years, besides plant height and number of seeds per pod. The analysis used seven association mapping models (GLM, MLM, MLMM, CMLM, EMLM, FarmCPU and SUPER) and further comparison revealed that FarmCPU is more robust in controlling both false positives and negatives as it incorporates multiple markers as covariates to eliminate confounding between testing marker and kinship. Cumulatively, a set of 22 SNPs were found to be associated with either days to first flowering (DOF), days to fifty percent flowering (DFF) or both, of which 15 were unique to trait based, 4 to PC based GWAS while 3 were shared by both. Because PC1 represents DOF, DFF and plant height (PH), four SNPs found associated to PC1 can be inferred as pleiotropic. A window of ± 2 kb of associated SNPs was aligned with available transcriptome data generated for transition from vegetative to reproductive phase in pigeonpea. Annotation analysis of these regions revealed presence of genes which might be involved in floral induction like Cytochrome p450 like Tata box binding protein, Auxin response factors, Pin like genes, F box protein, U box domain protein, chromatin remodelling complex protein, RNA methyltransferase. In summary, it appears that auxin responsive genes could be involved in regulating DOF and DFF as majority of the associated loci contained genes which are component of auxin signaling pathways in their vicinity. Overall, our findings indicates that the use of principal component analysis in GWAS is statistically more robust in terms of identifying genes and FarmCPU is a better choice compared to the other aforementioned models in dealing with both false positive and negative associations and thus can be used for traits with complex inheritance.
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