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.
Amaranthus palmeri (Amaranthaceae) is a noxious weed in several agroecosystems and in some cases seriously threatens the sustainability of crop production in North America. Glyphosate-resistant Amaranthus species are widespread, prompting the use of alternatives to glyphosate such as glufosinate, in conjunction with glufosinate-resistant crop cultivars, to help control glyphosate-resistant weeds. An experiment was conducted to analyze the transcriptome of A. palmeri plants that survived exposure to 0.55 kg ha-1 glufosinate. Since there was no record of glufosinate use at the collection site, survival of plants within the population are likely due to genetic expression that pre-dates selection; in the formal parlance of weed science this is described as natural tolerance. Leaf tissues from glufosinate-treated and non-treated seedlings were harvested 24 h after treatment (HAT) for RNA-Seq analysis. Global gene expression was measured using Illumina DNA sequence reads from non-treated and treated surviving (presumably tolerant, T) and susceptible (S) plants. The same plants were used to determine the mechanisms conferring differential tolerance to glufosinate. The S plants accumulated twice as much ammonia as did the T plants, 24 HAT. The relative copy number of the glufosinate target gene GS2 did not differ between T and S plants, with 1 to 3 GS2 copies in both biotypes. A reference cDNA transcriptome consisting of 72,780 contigs was assembled, with 65,282 sequences putatively annotated. Sequences of GS2 from the transcriptome assembly did not have polymorphisms unique to the tolerant plants. Five hundred sixty-seven genes were differentially expressed between treated T and S plants. Of the upregulated genes in treated T plants, 210 were more highly induced than were the upregulated genes in the treated S plants. Glufosinate-tolerant plants had greater induction of ABC transporter, glutathione S-transferase (GST), NAC transcription factor, nitronate monooxygenase (NMO), chitin elicitor receptor kinase (CERK1), heat shock protein 83, ethylene transcription factor, heat stress transcription factor, NADH-ubiquinone oxidoreductase, ABA 8'-hydroxylase, and cytochrome P450 genes (CYP72A, CYP94A1). Seven candidate genes were selected for validation using quantitative real time-PCR. While GST was upregulated in treated tolerant plants in at least one population, CYP72A219 was consistently highly expressed in all treated tolerant biotypes. These genes are candidates for contributing tolerance to glufosinate. Taken together, these results show that differential induction of stress-protection genes in a population can enable some individuals to survive herbicide application. Elevated expression of detoxification-related genes can get fixed in a population with sustained selection pressure, leading to evolution of resistance. Alternatively, sustained selection pressure could select for mutation(s) in the GS2 gene with the same consequence.
Pubmed ID: 29672568
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.
Commercial instrument and chemical vendor. Developer and manufacturer of specialized technological products for life science research and clinical diagnostics markets.
View all literature mentionsThe Center for Biological Sequence Analysis of the Technical University of Denmark conducts basic research in the field of bioinformatics and systems biology and directs its research primarily towards topics related to the elucidation of the functional aspects of complex biological mechanisms. A large number of computational methods have been produced, which are offered to others via WWW servers. Several data sets are also available. The center also has experimental efforts in gene expression analysis using DNA chips and data generation in relation to the physical and structural properties of DNA. The on-line prediction services at CBS are available as interactive input forms. Most of the servers are also available as stand-alone software packages with the same functionality. In addition, for some servers, programmatic access is provided in the form of SOAP-based Web Services. The center also educates engineering students in biotechnology and systems biology and offers a wide range of courses in bioinformatics, systems biology, human health, microbiology and nutrigenomics.
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 mentionsQuality control software that perform checks on raw sequence data coming from high throughput sequencing pipelines. This software also provides a modular set of analyses which can give a quick impression of the quality of the data prior to further analysis.
View all literature mentionsTool used to design PCR primers from DNA sequence - often in high-throughput genomics applications. It does everything from mispriming libraries to sequence quality data to the generation of internal oligos.
View all literature mentionsStatistical analysis and scientific graphing software for Windows OS.
View all literature mentionsSoftware for Next-Generation DNA sequencing, Sanger DNA analysis, and RNA sequencing. It contains sequence analysis tools which include reference-guided alignments, de novo assembly, variant calling, and SNP analyses. It has integrated the Cufflinks suite for in-depth transcript analysis and differential gene expression of RNA-Seq data.
View all literature mentionsDatabase of biological data related to a single initiative, originating from a single organization or from a consortium. A BioProject record provides users a single place to find links to the diverse data types generated for that project. It is a searchable collection of complete and incomplete (in-progress) large-scale sequencing, assembly, annotation, and mapping projects for cellular organisms. Submissions are supported by a web-based Submission Portal. The database facilitates organization and classification of project data submitted to NCBI, EBI and DDBJ databases that captures descriptive information about research projects that result in high volume submissions to archival databases, ties together related data across multiple archives and serves as a central portal by which to inform users of data availability. BioProject records link to corresponding data stored in archival repositories. The BioProject resource is a redesigned, expanded, replacement of the NCBI Genome Project resource. The redesign adds tracking of several data elements including more precise information about a project''''s scope, material, and objectives. Genome Project identifiers are retained in the BioProject as the ID value for a record, and an Accession number has been added. Database content is exchanged with other members of the International Nucleotide Sequence Database Collaboration (INSDC). BioProject is accessible via FTP.
View all literature mentionsSoftware repository for R packages related to analysis and comprehension of high throughput genomic data. Uses separate set of commands for installation of packages. Software project based on R programming language that provides tools for analysis and comprehension of high throughput genomic data.
View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Software program for clustering biological sequences with many applications in various fields such as making non-redundant databases, finding duplicates, identifying protein families, filtering sequence errors and improving sequence assembly etc. It is very fast and can handle extremely large databases. CD-HIT helps to significantly reduce the computational and manual efforts in many sequence analysis tasks and aids in understanding the data structure and correct the bias within a dataset. The CD-HIT package has CD-HIT, CD-HIT-2D, CD-HIT-EST, CD-HIT-EST-2D, CD-HIT-454, CD-HIT-PARA, PSI-CD-HIT, CD-HIT-OTU and over a dozen scripts. * CD-HIT (CD-HIT-EST) clusters similar proteins (DNAs) into clusters that meet a user-defined similarity threshold. * CD-HIT-2D (CD-HIT-EST-2D) compares 2 datasets and identifies the sequences in db2 that are similar to db1 above a threshold. * CD-HIT-454 identifies natural and artificial duplicates from pyrosequencing reads. * CD-HIT-OTU cluster rRNA tags into OTUs The usage of other programs and scripts can be found in CD-HIT user''s guide. CD-HIT was originally developed by Dr. Weizhong Li at Dr. Adam Godzik''s Lab at the Burnham Institute (now Sanford-Burnham Medical Research Institute).
View all literature mentionsSoftware tool as biological sequence alignment editor written for Windows 95/98/NT/2000/XP/7 and sequence analysis program. Provides sequence manipulation and analysis options and links to external analysis programs to view and manipulate sequences with simple point and click operations.
View all literature mentionsA curated, open-source, web-accessible resource for functional analysis of agricultural plant and animal gene products. Our long-term goal is to serve the needs of the agricultural research communities by facilitating post-genome biology for agriculture researchers and for those researchers primarily using agricultural species as biomedical models. AgBase provides tools designed to assist with the analysis of proteomics data and tools to evaluate experimental datasets using the GO. Additional tools for sequence analysis are also provided. We use controlled vocabularies developed by the Gene Ontology (GO) Consortium to describe molecular function, biological process, and cellular component for genes and gene products in agricultural species. AgBase will also accept annotations from any interested party in the research communities. AgBase develops freely available tools for functional analysis, including tools for using GO. We appreciate any and all questions, comments, and suggestions. AgBase uses the NCBI Blast program for searches for similar sequences. And the Taxonomy Browser allows users to find the NCBI defined taxon ID for or taxon name for different organisms.
View all literature mentionsSoftware package for high-performance read alignment, quantification and mutation discovery.General purpose read aligner which can be used to map both genomic DNA-seq reads and RNA-seq reads. Subread aligner as fast, accurate and scalable read mapping by seed-and-vote.These programs were also implemented in Bioconductor R package Rsubread.
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 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 mentionsWeb application for prediction of the presence and location of signal peptide cleavage sites in amino acid sequences from different organisms. The method incorporates a prediction of cleavage sites and a signal peptide/non-signal peptide prediction based on a combination of several artificial neural networks.
View all literature mentions