Articles Online (Volume 9, Issue 6)

Review

Plant Small RNAs: Biogenesis, Mode of Action and Their Roles in Abiotic Stresses

Praveen Guleria, Monika Mahajan, Jyoti Bhardwaj, Sudesh Kumar Yadav

Small RNAs (sRNAs) are 18-30 nt non-coding regulatory elements found in diverse organisms, which were initially identified as small double-stranded RNAs in Caenorhabditis elegans. With the development of new and improved technologies, sRNAs have also been identified and characterized in plant systems. Among them, micro RNAs (miRNAs) and small interfering RNAs (siRNAs) are found to be very important riboregulators in plants. Various types of sRNAs differ in their mode of biogenesis and in their function of gene regulation. sRNAs are involved in gene regulation at both transcriptional and post-transcriptional levels. They are known to regulate growth and development of plants. Furthermore, sRNAs especially plant miRNAs have been found to be involved in various stress responses, such as oxidative, mineral nutrient deficiency, dehydration, and even mechanical stimulus. Therefore, in the present review, we focus on the current understanding of biogenesis and regulatory mechanisms of plant sRNAs and their responses to various abiotic stresses.

Page 183–199


Review Article

Computational Identification of Sweet Wormwood (Artemisia annua) microRNA and Their mRNA Targets

annua) microRNA and Their mRNA Targets Alok Pani, Rajani Kanta Mahapatra , Niranjan Behera , Pradeep Kumar Naik

Despite its efficacy against malaria, the relatively low yield (0.01%-0.8%) of artemisinin in Artemisia annua is a serious limitation to the commercialization of the drug. A better understanding of the biosynthetic pathway of artemisinin and its regulation by both exogenous and endogenous factors is essential to improve artemisinin yield. Increasing evidence has shown that microRNAs (miRNAs) play multiple roles in various biological processes. In this study, we used previously known miRNAs from Arabidopsis and rice against expressed sequence tag (EST) database of A. annua to search for potential miRNAs and their targets in A. annua. A total of six potential miRNAs were predicted, which belong to the miR414 and miR1310 families. Furthermore, eight potential target genes were identified in this species. Among them, seven genes encode proteins that play important roles in artemisinin biosynthesis, including HMG-CoA reductase (HMGR), amorpha-4,11-diene synthase (ADS), farnesyl pyrophosphate synthase (FPS) and cytochrome P450. In addition, a gene coding for putative AINTEGUMENTA, which is involved in signal transduction and development, was also predicted as one of the targets. This is the first in silico study to indicate that miRNAs target genes encoding enzymes involved in artemisinin biosynthesis, which may help to understand the miRNA-mediated regulation of artemisinin biosynthesis in A. annua.

Page 200–210


Review Article

Identification of miR414 and Expression Analysis of Conserved miRNAs from Stevia rebaudiana

Praveen Guleria, Sudesh Kumar Yadav

MicroRNAs (miRNAs) usually contain 19-24 nucleotides and have been identified as important eukaryotic gene regulators. Applications of various computational approaches have simplified the task by predicting miRNAs from available sequence data sources. In this study, we identified a conserved miR414 from a computational analysis of EST sequence data available from Stevia rebaudiana. In addition, we also identified six conserved miRNAs namely miR169, miR319, miR414, miR164, miR167 and miR398 using stem-loop RT-PCR analysis. Hence, miR414 was commonly identified using both methods. The expression analysis of these miRNAs documented their roles in growth and development of Stevia. Furthermore, the detected miRNAs were found to target genes involved in plant growth, development, metabolism and signal transduction. This is the first study reporting these conserved miRNAs and their expression in Stevia.

Page 211–217


Review Article

Comparative Multivariate Analysis of Codon and Amino Acid Usage in Three Leishmania Genomes

Nutan Chauhan, Ambarish Sharan Vidyarthi, Raju Poddar

Multivariate analysis of codon and amino acid usage was performed for three Leishmania species, including L. donovani, L. infantum and L. major. It was revealed that all three species are under mutational bias and translational selection. Lower GC12 and higher GC3S in all three parasites suggests that the ancestral highly expressed genes (HEGs), compared to lowly expressed genes (LEGs), might have been rich in AT-content. This also suggests that there must have been a faster rate of evolution under GC-bias in LEGs. It was observed from the estimation of synonymous/non-synonymous substitutions in HEGs that the HEG dataset of L. donovani is much closer to L. major evolutionarily. This is also supported by the higher dN value as compared to dS between L. donovani and L. major, suggesting the conservation of synonymous codon positions between these two species and the role of translational selection in shaping the composition of protein-coding genes.

Page 218–228


Method

Evaluation of Protocols Used in 2-D Electrophoresis for Proteome Analysis of Young Rice Caryopsis

Jiang-Lin Liao, Ying-Jin Huang

In order to obtain a high-resolution electrophorogram of rice young panicle proteome, we evaluated various protocols commonly used in two-dimensional (2D) polyacrylamide gel electrophoresis (PAGE) of proteins, including gel staining protocol, pH range of immobilized pH gradient (IPG) strips and sample loading quantity. Results showed that a silver staining protocol using sensitized solution containing glacial acetic acid, sodium acetate and sodium thiosulfate (reported by Heukeshoven and Dernick in 1988) and a Coomassie Brilliant Blue staining method using solution containing G-250, ammonium sulfate and phosphoric acid (reported by Pink et al in 2010) demonstrated the superior staining effect. In addition, we also showed that higher resolution was achieved when IPG gel strip with pH range of 5-8 was used, compared to that with pH range of 4-7. Finally, the optimal loading quantity was determined as 130 μg using the 17 cm-long nonlinear IPG strip with pH 5-8 in combination with the silver nitrate staining protocol. The evaluated results would be helpful in proteome analysis of young rice caryopsis.

Page 229–237


Application Note

BIGpre: A Quality Assessment Package for Next-Generation Sequencing Data

Tongwu Zhang, Yingfeng Luo, Kan Liu, Linlin Pan, Bing Zhang, Jun Yu, Songnian Hu

The emergence of next-generation sequencing (NGS) technologies has significantly improved sequencing throughput and reduced costs. However, the short read length, duplicate reads and massive volume of data make the data processing much more difficult and complicated than the first-generation sequencing technology. Although there are some software packages developed to assess the data quality, those packages either are not easily available to users or require bioinformatics skills and computer resources. Moreover, almost all the quality assessment software currently available didn't taken into account the sequencing errors when dealing with the duplicate assessment in NGS data. Here, we present a new user-friendly quality assessment software package called BIGpre, which works for both Illumina and 454 platforms. BIGpre contains all the functions of other quality assessment software, such as the correlation between forward and reverse reads, read GC-content distribution, and base Ns quality. More importantly, BIGpre incorporates associated programs to detect and remove duplicate reads after taking sequencing errors into account and trimming low quality reads from raw data as well. BIGpre is primarily written in Perl and integrates graphical capability from the statistics package R. This package produces both tabular and graphical summaries of data quality for sequencing datasets from Illumina and 454 platforms. Processing hundreds of millions reads within minutes, this package provides immediate diagnostic information for user to manipulate sequencing data for downstream analyses. BIGpre is freely available at http://bigpre.sourceforge.net.

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