scholarly journals Using online tools at the Bovine Genome Database to manually annotate genes in the new reference genome

2020 ◽  
Vol 51 (5) ◽  
pp. 675-682
Author(s):  
D. A. Triant ◽  
J. J. Le Tourneau ◽  
C. M. Diesh ◽  
D. R. Unni ◽  
M. Shamimuzzaman ◽  
...  
Keyword(s):  
Reference Genome ◽  
Bovine Genome ◽  
Genome Database ◽  
Online Tools

scholarly journals Bovine Genome Database: new annotation tools for a new reference genome

2019 ◽  
Author(s):  
Md Shamimuzzaman ◽  
Justin J Le Tourneau ◽  
Deepak R Unni ◽  
Colin M Diesh ◽  
Deborah A Triant ◽  
...  
Keyword(s):  
Genome Assembly ◽  
Genome Annotation ◽  
Reference Genome ◽  
Gene Annotation ◽  
Bovine Genome ◽  
Data Retrieval ◽  
Genome Database ◽  
Ruminant Species ◽  
Search Tool ◽  
Efficient Data

Abstract The Bovine Genome Database (BGD) (http://bovinegenome.org) has been the key community bovine genomics database for more than a decade. To accommodate the increasing amount and complexity of bovine genomics data, BGD continues to advance its practices in data acquisition, curation, integration and efficient data retrieval. BGD provides tools for genome browsing (JBrowse), genome annotation (Apollo), data mining (BovineMine) and sequence database searching (BLAST). To augment the BGD genome annotation capabilities, we have developed a new Apollo plug-in, called the Locus-Specific Alternate Assembly (LSAA) tool, which enables users to identify and report potential genome assembly errors and structural variants. BGD now hosts both the newest bovine reference genome assembly, ARS-UCD1.2, as well as the previous reference genome, UMD3.1.1, with cross-genome navigation and queries supported in JBrowse and BovineMine, respectively. Other notable enhancements to BovineMine include the incorporation of genomes and gene annotation datasets for non-bovine ruminant species (goat and sheep), support for multiple assemblies per organism in the Regions Search tool, integration of additional ontologies and development of many new template queries. To better serve the research community, we continue to focus on improving existing tools, developing new tools, adding new datasets and encouraging researchers to use these resources.

Bovine Genome Database: Tools for Mining the Bos taurus Genome

2018 ◽  
pp. 211-249 ◽  
Author(s):  
Darren E. Hagen ◽  
Deepak R. Unni ◽  
Aditi Tayal ◽  
Gregory W. Burns ◽  
Christine G. Elsik
Keyword(s):  
Bos Taurus ◽  
Bovine Genome ◽  
Genome Database

scholarly journals Bovine Genome Database: new tools for gleaning function from theBos taurusgenome

2015 ◽  
Vol 44 (D1) ◽  
pp. D834-D839 ◽  
Author(s):  
Christine G. Elsik ◽  
Deepak R. Unni ◽  
Colin M. Diesh ◽  
Aditi Tayal ◽  
Marianne L. Emery ◽  
...  
Keyword(s):  
Bovine Genome ◽  
Genome Database

scholarly journals Bovine Genome Database: integrated tools for genome annotation and discovery

2010 ◽  
Vol 39 (suppl_1) ◽  
pp. D830-D834 ◽  
Author(s):  
Christopher P. Childers ◽  
Justin T. Reese ◽  
Jaideep P. Sundaram ◽  
Donald C. Vile ◽  
C. Michael Dickens ◽  
...  
Keyword(s):  
Genome Annotation ◽  
Bovine Genome ◽  
Genome Database

scholarly journals In silico identification of bacteriocin gene clusters in the gastrointestinal tract, based on the Human Microbiome Project’s reference genome database

2015 ◽  
Vol 15 (1) ◽  
Author(s):  
Calum J. Walsh ◽  
Caitriona M. Guinane ◽  
Colin Hill ◽  
R. Paul Ross ◽  
Paul W. O’Toole ◽  
...  
Keyword(s):  
Gastrointestinal Tract ◽  
In Silico ◽  
Reference Genome ◽  
Human Microbiome ◽  
Gene Clusters ◽  
Genome Database ◽  
In Silico Identification ◽  
Reference Genome Database ◽  
Bacteriocin Gene

scholarly journals Investigating the accuracy of imputed genotypes in Nellore cattle using the ARS-UCD1.2 assembly of the bovine genome

2020 ◽  
Author(s):  
Isis da Costa Hermisdorff ◽  
Raphael Bermal Costa ◽  
Lucia Galvão de Albuquerque ◽  
Hubert Pausch ◽  
Naveen Kumar Kadri
Keyword(s):  
Genome Assembly ◽  
Reference Genome ◽  
Bovine Genome ◽  
Imputation Accuracy ◽  
Quality Score ◽  
Reference Panel ◽  
Marker Density ◽  
Model Based ◽  
Reference Genome Assembly ◽  
Nellore Cattle

AbstractBackgroundImputation accuracy among other things depends on the size of the reference panel, the marker’s minor allele frequency (MAF), and the correct placement of variants on the reference genome assembly. Using high-density genotypes of 3938 Nellore cattle from Brazil, we investigated the accuracy of imputation from 50K to 777K SNP density, using map positions determined according to the bovine genome assemblies UMD3.1 and ARS-UCD1.2. We assessed the effect of reference and target panel sizes on the pre-phasing-based imputation quality using ten-fold cross-validation. Further, we compared the reliability of the model-based imputation quality score (Rsq) from Minimac3 to empirical imputation accuracy.ResultsThe overall accuracy of imputation measured as the squared correlation between true and imputed allele dosages (R2dose) was virtually identical using either the UMD3.1 or ARS-UCD1.2 genome assembly. When the size of the reference panel increased from 250 to 2000, R2dose increased from 0.845 to 0.917, and the number of polymorphic markers in the imputed data set increased from 586,701 to 618,660. Advantages in both accuracy and marker density were also observed when larger target panels were imputed, likely resulting from more accurate haplotype inference. Imputation accuracy and the marker density in the imputed data increased from 0.903 to 0.913 and from 593,239 to 595,570 when haplotypes were inferred in 500 and 2900 target animals, respectively. The model-based imputation quality scores from Minimac3 (Rsq) were highly correlated to but systematically higher than empirically estimated accuracies. The correlation between these metrics increased with the size of the reference panel and MAF of imputed variants.ConclusionsAccurate imputation of BovineHD BeadChip markers is possible in Nellore cattle using the new bovine reference genome assembly ARS-UCD1.2. The use of large reference and target panels improves the accuracy of the imputed genotypes and provides genotypes for more markers segregating at low frequency for downstream genomic analyses. The model-based imputation quality score from Minimac3 (Rsq) can be used to detect poorly imputed variants but its reliability depends on the size of the reference panel used and MAF of the imputed variants.

scholarly journals Improving the usability and comprehensiveness of microbial databases

2018 ◽  
Author(s):  
Caitlin Loeffler ◽  
Aaron Karlsberg ◽  
Lana S. Martin ◽  
Eleazar Eskin ◽  
David Koslicki ◽  
...  
Keyword(s):  
Translational Research ◽  
Basic Science ◽  
Reference Genome ◽  
Reference Database ◽  
Data Preparation ◽  
Genome Database ◽  
Reference Databases ◽  
Reference Genome Database

AbstractMetagenomics studies leverage genomic reference databases to generate discoveries in basic science and translational research. However, current microbial studies use disparate reference databases that lack consistent standards of specimen inclusion, data preparation, taxon labelling and accessibility, hindering their quality and comprehensiveness, and calling for the establishment of recommendations for reference genome database assembly. Here, we analyze existing fungal and bacterial databases and discuss guidelines for the development of a master reference database that promises to improve the quality and quantity of omics research.

scholarly journals Ares-GT: design of guide RNAs targeting multiple genes for CRISPR-Cas experiments

2020 ◽  
Author(s):  
Eugenio G. Minguet
Keyword(s):  
Reference Genome ◽  
Query Sequence ◽  
Gene Families ◽  
Guide Rna ◽  
Guide Rnas ◽  
Online Tools ◽  
Multiple Input ◽  
Design Guide ◽  
Command Line Tool ◽  
Selection Of

ABSTRACTMotivationThere is a lack of tools to design guide RNA for CRISPR genome editing of gene families and usually good candidate sgRNAs are tagged with low scores precisely because they match several locations in the genome, thus time-consuming manual evaluation of targets is required. Moreover, online tools are limited to a restricted list of reference genome and lack the flexibility to incorporate unpublished genomes or contemplate genomes of populations with allelic variants.ResultsTo address these issues, I have developed the ARES-GT, a local command line tool in Python software. ARES-GT allows the selection of candidate sgRNAs that match multiple input query sequences, in addition of candidate sgRNAs that specifically match each query sequence. It also contemplates the use of unmapped contigs apart from complete genomes thus allowing the use of any genome provided by user and being able to handle intraspecies allelic variability and individual polymorphisms.AvailabilityARES-GT is available at GitHub (https://github.com/eugomin/ARES-GT.git).

scholarly journals Scalable metagenomic taxonomy classification using a reference genome database

2013 ◽  
Vol 29 (18) ◽  
pp. 2253-2260 ◽  
Author(s):  
Sasha K. Ames ◽  
David A. Hysom ◽  
Shea N. Gardner ◽  
G. Scott Lloyd ◽  
Maya B. Gokhale ◽  
...  
Keyword(s):  
Reference Genome ◽  
Genome Database ◽  
Reference Genome Database

scholarly journals Ensembl Genomes 2020—enabling non-vertebrate genomic research

2019 ◽  
Vol 48 (D1) ◽  
pp. D689-D695 ◽  
Author(s):  
Kevin L Howe ◽  
Bruno Contreras-Moreira ◽  
Nishadi De Silva ◽  
Gareth Maslen ◽  
Wasiu Akanni ◽  
...  
Keyword(s):  
Reference Genome ◽  
Analysis Data ◽  
Tree Of Life ◽  
Genomic Research ◽  
Vertebrate Species ◽  
Online Tools ◽  
Recent Developments ◽  
Future Strategy ◽  
Genome Scale ◽  
Scale Data

Abstract Ensembl Genomes (http://www.ensemblgenomes.org) is an integrating resource for genome-scale data from non-vertebrate species, complementing the resources for vertebrate genomics developed in the context of the Ensembl project (http://www.ensembl.org). Together, the two resources provide a consistent set of interfaces to genomic data across the tree of life, including reference genome sequence, gene models, transcriptional data, genetic variation and comparative analysis. Data may be accessed via our website, online tools platform and programmatic interfaces, with updates made four times per year (in synchrony with Ensembl). Here, we provide an overview of Ensembl Genomes, with a focus on recent developments. These include the continued growth, more robust and reproducible sets of orthologues and paralogues, and enriched views of gene expression and gene function in plants. Finally, we report on our continued deeper integration with the Ensembl project, which forms a key part of our future strategy for dealing with the increasing quantity of available genome-scale data across the tree of life.

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