Prioritizing candidate eQTL causal genes in Arabidopsis using RANDOM FORESTS.

Expression quantitative trait locus mapping has been widely used to study the genetic regulation of gene expression in Arabidopsis thaliana. As a result, a large amount of expression quantitative trait locus data has been generated for this model plant; however, only a few causal expression quantitative trait locus genes have been identified, and experimental validation is costly and laborious. A prioritization method could help speed up the identification of causal expression quantitative trait locus genes. This study extends the machine-learning-based QTG-Finder2 method for prioritizing candidate causal genes in phenotype quantitative trait loci to be used for expression quantitative trait loci by adding gene structure, protein interaction, and gene expression. Independent validation shows that the new algorithm can prioritize 16 out of 25 potential expression quantitative trait locus causal genes within the top 20% rank. Several new features are important in prioritizing causal expression quantitative trait locus genes, including the number of protein-protein interactions, unique domains, and introns. Overall, this study provides a foundation for developing computational methods to prioritize candidate expression quantitative trait locus causal genes. The prediction of all genes is available in the AraQTL workbench (https://www.bioinformatics.nl/AraQTL/) to support the identification of gene expression regulators in Arabidopsis.

Caffeoyl-CoA 3-O-methyltransferase gene family in jute: Genome-wide identification, evolutionary progression and transcript profiling under different quandaries.

Jute (Corchorus sp.), is a versatile, naturally occurring, biodegradable material that holds the promising possibility of diminishing the extensive use of plastic bags. One of the major components of the cell wall, lignin plays both positive and negative roles in fiber fineness and quality. Although it gives mechanical strength to plants, an excess amount of it is responsible for the diminution of fiber quality. Among various gene families involved in the lignin biosynthesis, Caffeoyl-CoA 3-O-methyltransferase (CCoAOMT) is the most significant and has remained mostly unexplored. In this study, an extensive in-silico characterization of the CCoAOMT gene family was carried out in two jute species (C. capsularis L. and C. olitoroius L.) by analyzing their structural, functional, molecular and evolutionary characteristics. A total of 6 CCoAOMT gene members were identified in each of the two species using published reference genomes. These two jute species showed high syntenic conservation and the identified CCoAOMT genes formed four clusters in the phylogenetic tree. Histochemical assay of lignin in both jute species could shed light on the deposition pattern in stems and how it changes in response to abiotic stresses. Furthermore, expression profiling using qPCR showed considerable alteration of CCoAOMT transcripts under various abiotic stresses and hormonal treatment. This study will lay a base for further analysis and exploration of target candidates for overexpression of gene silencing using modern biotechnological techniques to enhance the quality of this economically important fiber crop.

Identification and expression profiling of proline metabolizing genes in Arabidopsis thaliana and Oryza sativa to reveal their stress-specific transcript alteration.

The amino acid, proline, is utilized by different organisms to offset cellular imbalances caused by environmental stresses. The wide use of proline as a stress adaptor molecule indicates that proline has a fundamental biological role in stress response. A comprehensive analysis of the transcript abundance of proline metabolizing genes is fundamental for the assessment of function and regulation of each gene. Using available microarray data and quantitative real-time RT-PCR, the expression profiles of gene encoding key proline biosynthesis and degradation enzymes i.e., OAT, P5CS, P5CR and PDH were examined. Interestingly, validation of candidate genes in rice using in-silico data provided strong evidence for their involvement in stress response. Note that, OsOAT, OsP5CS1, OsP5CS2, OsP5CR showed similar expression pattern in quantitative real-time RT-PCR results as compared to microarray data. However, OsPDH showed a different expression pattern which may be due to the genotypic variation. Furthermore, a biochemical assay measuring proline content gave us a proper indication of the accumulation of proline under stressed conditions. Identification of key proline metabolizing genes from rice and Arabidopsis provides insights on the molecular regulation of proline homeostasis, to initiate metabolic engineering to develop stress-resilient plants. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12298-021-01023-0.

Comprehensive in silico Characterization of Universal Stress Proteins in Rice (Oryza sativa L.) With Insight Into Their Stress-Specific Transcriptional Modulation.

In a world where climate change is real and its consequences are unprecedented, understanding of the plant adaptive capacity and native stress-responsive machinery is crucial. In recent years, universal stress proteins (USPs) have received much attention in the field of plant science due to their stress-specific transcriptional regulation. This study focuses on the extensive characterization of the USP gene family members in the monocot crop rice (Oryza sativa L. var. japonica). Here, we report a total of 44 USP genes in the rice genome. In silico characterization of these genes showed that domain architecture played a major role in the functional diversification of the USP gene family which holds for all plant USPs. On top of that, a higher conservation of OsUSP members has been exhibited with a monocot genome (Zea mays L.) as compared to a dicot genome (Arabidopsis thaliana L.). Expression profiling of the identified genes led to the discovery of multiple OsUSP genes that showed pronounced transcript alteration under various abiotic stress conditions, indicating their potential role as multi-functional stress-specific modules. Furthermore, expression validation of OsUSP genes using qRT-PCR provided a strong evidence for the utility OsUSP genes in building multi-stress tolerant plants. Altogether, this study provides leads to suitable USP candidates that could be targeted for plant breeding and genetic engineering experiments to develop stress resilient crop species.