RESUMO
Horsegram (Macrotyloma uniflorum (Lam.) Verdc.) is a drought hardy food and fodder legume of Indo-African continents with diverse germplasm sources demonstrating alternating mechanisms depicting contrasting adaptations to different climatic zones. Tissue specific expression of genes contributes substantially to location specific adaptations. Regulatory networks of such adaptive genes are elucidated for downstream translational research. MicroRNAs are small endogenous regulatory RNAs which alters the gene expression profiles at a particular time and type of tissue. Identification of such small regulatory RNAs in low moisture stress hardy crops can help in cross species transfer and validation confirming stress tolerance ability. This study outlined prediction of conserved miRNAs from transcriptome shotgun assembled sequences and EST sequences of horsegram. We could validate eight out of 15 of the identified miRNAs to demonstrate their role in deficit moisture stress tolerance mechanism of horsegram variety Paiyur1 with their target networks. The putative mumiRs were related to other food legumes indicating the presence of gene regulatory networks. Differential miRNA expression among drought specific tissues indicted the probable energy conservation mechanism. Targets were identified for functional characterization and regulatory network was constructed to find out the probable pathways of post-transcriptional regulation. The functional network revealed mechanism of biotic and abiotic stress tolerance, energy conservation and photoperiod responsiveness.
Assuntos
Adaptação Fisiológica/genética , Fabaceae/genética , Redes Reguladoras de Genes/genética , MicroRNAs/genética , Aclimatação/genética , Secas , Regulação da Expressão Gênica de Plantas/genética , Estudo de Associação Genômica Ampla/métodos , Proteínas de Plantas/genética , Processamento Pós-Transcricional do RNA/genética , Estresse Fisiológico/genética , Transcriptoma/genéticaRESUMO
Online retrieval of the homologous nucleotide sequences through existing alignment techniques is a common practice against the given database of sequences. The salient point of these techniques is their dependence on local alignment techniques and scoring matrices the reliability of which is limited by computational complexity and accuracy. Toward this direction, this work offers a novel way for numerical representation of genes which can further help in dividing the data space into smaller partitions helping formation of a search tree. In this context, this paper introduces a 36-dimensional Periodicity Count Value (PCV) which is representative of a particular nucleotide sequence and created through adaptation from the concept of stochastic model of Kolekar et al. (American Institute of Physics 1298:307-312, 2010. doi: 10.1063/1.3516320 ). The PCV construct uses information on physicochemical properties of nucleotides and their positional distribution pattern within a gene. It is observed that PCV representation of gene reduces computational cost in the calculation of distances between a pair of genes while being consistent with the existing methods. The validity of PCV-based method was further tested through their use in molecular phylogeny constructs in comparison with that using existing sequence alignment methods.
Assuntos
Biologia Computacional/métodos , Evolução Molecular , Filogenia , Algoritmos , Sequência de Bases , Alinhamento de Sequência , Análise de Sequência de DNA/métodosRESUMO
BACKGROUND: Simple Sequence Repeats or microsatellites are resourceful molecular genetic markers. There are only few reports of SSR identification and development in pineapple. Complete genome sequence of pineapple available in the public domain can be used to develop numerous novel SSRs. Therefore, an attempt was made to identify SSRs from genomic, chloroplast, mitochondrial and EST sequences of pineapple which will help in deciphering genetic makeup of its germplasm resources. RESULTS: A total of 359511 SSRs were identified in pineapple (356385 from genome sequence, 45 from chloroplast sequence, 249 in mitochondrial sequence and 2832 from EST sequences). The list of EST-SSR markers and their details are available in the database. CONCLUSIONS: PineElm_SSRdb is an open source database available for non-commercial academic purpose at http://app.bioelm.com/ with a mapping tool which can develop circular maps of selected marker set. This database will be of immense use to breeders, researchers and graduates working on Ananas spp. and to others working on cross-species transferability of markers, investigating diversity, mapping and DNA fingerprinting.
