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Drought is an important abiotic factor that threatens the growth and development of plants. Verbena bonariensis is a widely used landscape plant with a very high ornamental value. We found that Verbena has drought tolerance in production practice, so in order to delve into its mechanism of drought resistance and screen out its drought-resistance genes, we used the RNA-Seq platform to perform a de novo transcriptome assembly to analyze Verbena transcription response to drought stress. By high-throughput sequencing with Illumina Hiseq Xten, a total of 44.59 Gb clean data was obtained from T01 (control group) and T02 (drought experiment group). After assembly, 111,313 unigenes were obtained, and 53,757 of them were annotated by compared databases. In this study, 4829 differentially expressed genes were obtained, of which 4165 were annotated. We performed GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analyses, and explored a lot of differently expressed genes related to plant energy production, hormone synthesis, cell signal transduction, and metabolism to understand the stress response of Verbena in drought stress. In addition, we also found that a series of TFs related to drought-resistance of Verbena and provide excellent genetic resources for improving the drought tolerance of crops.
Pubmed ID: 29899256 RIS Download
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A 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 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 mentionsThe SciCrunch Infrastructure was developed as a cooperative data platform to be used by diverse communities in making data more FAIR.
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