In silico identification and computational characterization of endogenous small interfering RNAs from diverse grapevine tissues and stages

Small interfering RNAs (siRNAs) are effectors of regulatory pathways underlying plant development, metabolism, and stress- and nutrient-signaling regulatory networks. The endogenous siRNAs are generally not conserved between plants; consequently, it is necessary and important to identify and characterize siRNAs from various plants. To address the nature and functions of siRNAs, and understand the biological roles of the huge siRNA population in grapevine (Vitis vinifera L.). The high-throughput sequencing technology was used to identify a large set of putative endogenous siRNAs from six grapevine tissues/organs. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was performed to classify the target genes of siRNA. In total, 520,519 candidate siRNAs were identified and their expression profiles exhibited typical temporal characters during grapevine development. In addition, we identified two grapevine trans-acting siRNA (TAS) gene homologs (VvTAS3 and VvTAS4) and the derived trans-acting siRNAs (tasiRNAs) that could target grapevine auxin response factor (ARF) and myeloblastosis (MYB) genes. Furthermore, the GO and KEGG analysis of target genes showed that most of them covered a broad range of functional categories, especially involving in disease-resistance process. The large-scale and completely genome-wide level identification and characterization of grapevine endogenous siRNAs from the diverse tissues by high throughput technology revealed the nature and functions of siRNAs in grapevine.     

New resources for functional analysis of omics data for the genus <Emphasis Type="Italic">Aspergillus</Emphasis>

Background

Detailed and comprehensive genome annotation can be considered a prerequisite for effective analysis and interpretation of omics data. As such, Gene Ontology (GO) annotation has become a well accepted framework for functional annotation. The genus Aspergillus comprises fungal species that are important model organisms, plant and human pathogens as well as industrial workhorses. However, GO annotation based on both computational predictions and extended manual curation has so far only been available for one of its species, namely A. nidulans.

Results

Based on protein homology, we mapped 97% of the 3,498 GO annotated A. nidulans genes to at least one of seven other Aspergillus species: A. niger, A. fumigatus, A. flavus, A. clavatus, A. terreus, A. oryzae and Neosartorya fischeri. GO annotation files compatible with diverse publicly available tools have been generated and deposited online. To further improve their accessibility, we developed a web application for GO enrichment analysis named FetGOat and integrated GO annotations for all Aspergillus species with public genome sequences. Both the annotation files and the web application FetGOat are accessible via the Broad Institute's website (http://www.broadinstitute.org/fetgoat/index.html). To demonstrate the value of those new resources for functional analysis of omics data for the genus Aspergillus, we performed two case studies analyzing microarray data recently published for A. nidulans, A. niger and A. oryzae.

Conclusions

We mapped A. nidulans GO annotation to seven other Aspergilli. By depositing the newly mapped GO annotation online as well as integrating it into the web tool FetGOat, we provide new, valuable and easily accessible resources for omics data analysis and interpretation for the genus Aspergillus. Furthermore, we have given a general example of how a well annotated genome can help improving GO annotation of related species to subsequently facilitate the interpretation of omics data.