83 research outputs found
Thermostability in endoglucanases is fold-specific
<p>Abstract</p> <p>Background</p> <p>Endoglucanases are usually considered to be synergistically involved in the initial stages of cellulose breakdown-an essential step in the bioprocessing of lignocellulosic plant materials into bioethanol. Despite their economic importance, we currently lack a basic understanding of how some endoglucanases can sustain their ability to function at elevated temperatures required for bioprocessing, while others cannot. In this study, we present a detailed comparative analysis of both thermophilic and mesophilic endoglucanases in order to gain insights into origins of thermostability. We analyzed the sequences and structures for sets of endoglucanase proteins drawn from the Carbohydrate-Active enZymes (CAZy) database.</p> <p>Results</p> <p>Our results demonstrate that thermophilic endoglucanases and their mesophilic counterparts differ significantly in their amino acid compositions. Strikingly, these compositional differences are specific to protein folds and enzyme families, and lead to differences in intramolecular interactions in a fold-dependent fashion.</p> <p>Conclusions</p> <p>Here, we provide fold-specific guidelines to control thermostability in endoglucanases that will aid in making production of biofuels from plant biomass more efficient.</p
The Locus Lookup tool at MaizeGDB: identification of genomic regions in maize by integrating sequence information with physical and genetic maps
Methods to automatically integrate sequence information with physical and genetic maps are scarce. The Locus Lookup tool enables researchers to define windows of genomic sequence likely to contain loci of interest where only genetic or physical mapping associations are reported. Using the Locus Lookup tool, researchers will be able to locate specific genes more efficiently that will ultimately help them develop a better maize plant. With the availability of the well-documented source code, the tool can be easily adapted to other biological systems
Data sharing and ontology use among agricultural genetics, genomics, and breeding databases and resources of the AgBioData Consortium
Over the last several decades, there has been rapid growth in the number and
scope of agricultural genetics, genomics and breeding (GGB) databases and
resources. The AgBioData Consortium (https://www.agbiodata.org/) currently
represents 44 databases and resources covering model or crop plant and animal
GGB data, ontologies, pathways, genetic variation and breeding platforms
(referred to as 'databases' throughout). One of the goals of the Consortium is
to facilitate FAIR (Findable, Accessible, Interoperable, and Reusable) data
management and the integration of datasets which requires data sharing, along
with structured vocabularies and/or ontologies. Two AgBioData working groups,
focused on Data Sharing and Ontologies, conducted a survey to assess the status
and future needs of the members in those areas. A total of 33 researchers
responded to the survey, representing 37 databases. Results suggest that data
sharing practices by AgBioData databases are in a healthy state, but it is not
clear whether this is true for all metadata and data types across all
databases; and that ontology use has not substantially changed since a similar
survey was conducted in 2017. We recommend 1) providing training for database
personnel in specific data sharing techniques, as well as in ontology use; 2)
further study on what metadata is shared, and how well it is shared among
databases; 3) promoting an understanding of data sharing and ontologies in the
stakeholder community; 4) improving data sharing and ontologies for specific
phenotypic data types and formats; and 5) lowering specific barriers to data
sharing and ontology use, by identifying sustainability solutions, and the
identification, promotion, or development of data standards. Combined, these
improvements are likely to help AgBioData databases increase development
efforts towards improved ontology use, and data sharing via programmatic means.Comment: 17 pages, 8 figure
AgBioData consortium recommendations for sustainable genomics and genetics databases for agriculture
The future of agricultural research depends on data. The sheer volume of agricultural biological data being produced today makes excellent data management essential. Governmental agencies, publishers and science funders require data management plans for publicly funded research. Furthermore, the value of data increases exponentially when they are properly stored, described, integrated and shared, so that they can be easily utilized in future analyses. AgBioData (https://www.agbiodata.org) is a consortium of people working at agricultural biological databases, data archives and knowledgbases who strive to identify common issues in database development, curation and management, with the goal of creating database products that are more Findable, Accessible, Interoperable and Reusable. We strive to promote authentic, detailed, accurate and explicit communication between all parties involved in scientific data. As a step toward this goal, we present the current state of biocuration, ontologies, metadata and persistence, database platforms, programmatic (machine) access to data, communication and sustainability with regard to data curation. Each section describes challenges and opportunities for these topics, along with recommendations and best practices
Chromosome-scale genome assembly of bread wheat’s wild relative Triticum timopheevii
Wheat (Triticum aestivum) is one of the most important food crops with an urgent need for increase in its production to feed the growing world. Triticum timopheevii (2n = 4x = 28) is an allotetraploid wheat wild relative species containing the At and G genomes that has been exploited in many pre-breeding programmes for wheat improvement. In this study, we report the generation of a chromosome-scale reference genome assembly of T. timopheevii accession PI 94760 based on PacBio HiFi reads and chromosome conformation capture (Hi-C). The assembly comprised a total size of 9.35 Gb, featuring a contig N50 of 42.4 Mb and included the mitochondrial and plastid genome sequences. Genome annotation predicted 166,325 gene models including 70,365 genes with high confidence. DNA methylation analysis showed that the G genome had on average more methylated bases than the At genome. In summary, the T. timopheevii genome assembly provides a valuable resource for genome-informed discovery of agronomically important genes for food security
Choosing a genome browser for a Model Organism Database: surveying the Maize community
As the B73 maize genome sequencing project neared completion, MaizeGDB began to integrate a graphical genome browser with its existing web interface and database. To ensure that maize researchers would optimally benefit from the potential addition of a genome browser to the existing MaizeGDB resource, personnel at MaizeGDB surveyed researchers’ needs. Collected data indicate that existing genome browsers for maize were inadequate and suggest implementation of a browser with quick interface and intuitive tools would meet most researchers’ needs. Here, we document the survey’s outcomes, review functionalities of available genome browser software platforms and offer our rationale for choosing the GBrowse software suite for MaizeGDB. Because the genome as represented within the MaizeGDB Genome Browser is tied to detailed phenotypic data, molecular marker information, available stocks, etc., the MaizeGDB Genome Browser represents a novel mechanism by which the researchers can leverage maize sequence information toward crop improvement directly
Recommended from our members
Maize Metabolic Network Construction and Transcriptome Analysis
A framework for understanding the synthesis and catalysis of metabolites and other biochemicals by proteins is crucial for unraveling the physiology of cells. To create such a framework for Zea mays L. subsp. mays (maize), we developed MaizeCyc, a metabolic network of enzyme catalysts, proteins, carbohydrates, lipids, amino acids, secondary plant products, and other metabolites by annotating the genes identified in the maize reference genome sequenced from the B73 variety. MaizeCyc version 2.0.2 is a collection of 391 maize pathways involving 8889 enzyme mapped to 2110 reactions and 1468 metabolites. We used MaizeCyc to describe the development and function of maize organs including leaf, root, anther, embryo, and endosperm by exploring the recently published microarray-based maize gene expression atlas. We found that 1062 differentially expressed metabolic genes mapped to 524 unique enzymatic reactions associated with 310 pathways. The MaizeCyc pathway database was created by running a library of evidences collected from the maize genome annotation, gene-based phylogeny trees, and comparison to known genes and pathways from rice (Oryza sativa L.) and Arabidopsis thaliana (L.) Heynh. against the PathoLogic module of Pathway Tools. The network and the database that were also developed as a community resource are freely accessible online at http://maizecyc.maizegdb.org to facilitate analysis and promote studies on metabolic genes in maize.Keywords: Arabidopsis,
Bundle sheath,
Leaves,
C-4 photosynthesis,
Evolution,
Systems biology,
Plant,
Genome,
Biochemical pathway database,
Mode
POPcorn: An Online Resource Providing Access to Distributed and Diverse Maize Project Data
The purpose of the online resource presented here, POPcorn (Project Portal for corn), is to enhance accessibility of maize genetic and genomic resources for plant biologists. Currently, many online locations are difficult to find, some are best searched independently, and individual project websites often degrade over time—sometimes disappearing entirely. The POPcorn site makes available (1) a centralized, web-accessible resource to search and browse descriptions of ongoing maize genomics projects, (2) a single, stand-alone tool that uses web Services and minimal data warehousing to search for sequence matches in online resources of diverse offsite projects, and (3) a set of tools that enables researchers to migrate their data to the long-term model organism database for maize genetic and genomic information: MaizeGDB. Examples demonstrating POPcorn's utility are provided herein
- …