Searching the Resource Information Network
Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.
With the ongoing climate change, African rainforests are expected to experience severe drought events in the future. In Africa, the tropical genus Erythrophleum (Fabaceae) includes two forest sister timber tree species displaying contrasting geographical distributions. Erythrophleum ivorense is adapted to wet evergreen Guineo-Congolian forests, whereas E. suaveolens occurs in a wider range of climates, being found in moist dense forests but also in gallery forests under a relatively drier climate. This geographical distribution pattern suggests that the two species might cope differently to drought at the genomic level. Yet, the genetic basis of tolerance response to drought stress in both species is still uncharacterized. To bridge this gap, we performed an RNA-seq approach on seedlings from each species to monitor their transcriptional responses at different levels of drought stress (0, 2 and 6 weeks after stopping watering seedlings). Monitoring of wilting symptoms revealed that E. suaveolens displayed an earlier phenotypic response to drought stress than E. ivorense. At the transcriptomic level, results revealed 2020 (1204 down-regulated/816 up-regulated) and 1495 differentially expressed genes (DEGs) in response to drought stress from a total of 67,432 and 66,605 contigs assembled in E. ivorense and E. suaveolens, respectively. After identifying 30,374 orthologs between species, we found that only 7 of them were DEGs shared between species, while 587 and 458 were differentially expressed only in E. ivorense or E. suaveolens, respectively. GO and KEGG enrichment analysis revealed that the two species differ in terms of significantly regulated pathways as well as the number and expression profile of DEGs (Up/Down) associated with each pathway in the two stress stages. Our results suggested that the two studied species react differently to drought. E. suaveolens seems displaying a prompt response to drought at its early stage strengthened by the down-regulation of many DEGs encoding for signaling and metabolism-related pathways. A considerable up-regulation of these pathways was also found in E. ivorense at the late stage of drought, suggesting this species may be a late responder. Overall, our data may serve as basis for further understanding the genetic control of drought tolerance in tropical trees and favor the selection of crucial genes for genetically enhancing drought resistance.
Pubmed ID: 30716444
Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.
Web application to search nucleotide databases using a nucleotide query. Algorithms: blastn, megablast, discontiguous megablast.
View all literature mentionsWeb application to search protein databases using a translated nucleotide query. Translated BLAST services are useful when trying to find homologous proteins to a nucleotide coding region. Blastx compares translational products of the nucleotide query sequence to a protein database. Because blastx translates the query sequence in all six reading frames and provides combined significance statistics for hits to different frames, it is particularly useful when the reading frame of the query sequence is unknown or it contains errors that may lead to frame shifts or other coding errors. Thus blastx is often the first analysis performed with a newly determined nucleotide sequence and is used extensively in analyzing EST sequences. This search is more sensitive than nucleotide blast since the comparison is performed at the protein level.
View all literature mentionsA database of orthologous groups of genes. The orthologous groups are annotated with functional description lines (derived by identifying a common denominator for the genes based on their various annotations), with functional categories (i.e derived from the original COG/KOG categories). eggNOG's database currently counts 1.7 million orthologous groups in 3686 species, covering over 7.7 million proteins (built from 9.6 million proteins). (Jan 30, 2014)
View all literature mentionsA database of protein families, each represented by multiple sequence alignments and hidden Markov models (HMMs). Users can analyze protein sequences for Pfam matches, view Pfam family annotation and alignments, see groups of related families, look at the domain organization of a protein sequence, find the domains on a PDB structure, and query Pfam by keywords. There are two components to Pfam: Pfam-A and Pfam-B. Pfam-A entries are high quality, manually curated families that may automatically generate a supplement using the ADDA database. These automatically generated entries are called Pfam-B. Although of lower quality, Pfam-B families can be useful for identifying functionally conserved regions when no Pfam-A entries are found. Pfam also generates higher-level groupings of related families, known as clans (collections of Pfam-A entries which are related by similarity of sequence, structure or profile-HMM).
View all literature mentionsTool for searching sequence databases for homologs of protein sequences, and for making protein sequence alignments. It implements methods using probabilistic models called profile hidden Markov models (profile HMMs). Compared to BLAST, FASTA, and other sequence alignment and database search tools based on older scoring methodology, HMMER aims to be significantly more accurate and more able to detect remote homologs because of the strength of its underlying mathematical models. In the past, this strength came at significant computational expense, but in the new HMMER3 project, HMMER is now essentially as fast as BLAST.
View all literature mentionsA web-based tool and database for the gene ontology analysis. Its focus is on agricultural species and is user-friendly. The agriGO is designed to provide deep support to agricultural community in the realm of ontology analysis. Compared to other available GO analysis tools, unique advantages and features of agriGO are: # The agriGO especially focuses on agricultural species. It supports 45 species and 292 datatypes currently. And agriGO is designed as an user-friendly web server. # New tools including PAGE (Parametric Analysis of Gene set Enrichment), BLAST4ID (Transfer IDs by BLAST) and SEACOMPARE (Cross comparison of SEA) were developed. The arrival of these tools provides users with possibilities for data mining and systematic result exploration and will allow better data analysis and interpretation. # The exploratory capability and result visualization are enhanced. Results are provided in different formats: HTML tables, tabulated text files, hierarchical tree graphs, and flash bar graphs. # In agriGO, PAGE and SEACOMPARE can be used to carry out cross-comparisons of results derived from different data sets, which is very important when studying multiple groups of experiments, such as in time-course research. Platform: Online tool
View all literature mentionsSoftware Java pipeline for trimming tasks for Illumina paired end and single ended data. Flexible Trimmer for Illumina Sequence Data. Pair aware preprocessing tool optimized for Illumina next generation sequencing data. Includes several processing steps for read trimming and filtering. Operating systems Unix/Linux, Mac OS, Windows.
View all literature mentionsIntegrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information. In particular, gene catalogs in completely sequenced genomes are linked to higher-level systemic functions of cell, organism, and ecosystem. Analysis tools are also available. KEGG may be used as reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.
View all literature mentionsBioconductor software package for Empirical analysis of Digital Gene Expression data in R. Used for differential expression analysis of RNA-seq and digital gene expression data with biological replication.
View all literature mentionsSoftware for the efficient and robust de novo reconstruction of transcriptomes from RNA-seq data.
View all literature mentionsSoftware tool to quantitatively measure genome assembly and annotation completeness based on evolutionarily informed expectations of gene content.
View all literature mentions