Progress 01/15/16 to 01/14/20
Outputs
Target Audience: geneticists (human and livestock) animal breeders animal scientists progressive livestock producers Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?
Nothing Reported
How have the results been disseminated to communities of interest?All new QTLdb data are ported to NCBI, Ensembl, UCSC genome browser, and Reuters Data Citation Index upon each data release. Results were also presented at national and international conferences and in published journal articles. What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
Overall impact statement: The focus of this project was to better understand the relationships between livestock traits and to efficiently comprehend large amounts of genotype/phenotype association data that are being published at an accelerating rate. Our goal was to develop integrated resources that leverage prior national funding in cyberinfrastructure to help researchers maximize the utility of genotype-to-phenotype data to ultimately address issues important to the livestock industry. We made significant progress toward our goals by vigorously curating new data into the QTLdb and CorrDB and diligently improving the database infrastructure and tools for improved efficiency and functionality. The progress was highlighted by three database releases each year on each database (see https://www.animalgenome.org/QTLdb/release/#2016, https://www.animalgenome.org/QTLdb/release/#2017, https://www.animalgenome.org/QTLdb/release/#2018, https://www.animalgenome.org/QTLdb/release/#2019, https://www.animalgenome.org/CorrDB/release/#2017, https://www.animalgenome.org/CorrDB/release/#2018, https://www.animalgenome.org/CorrDB/release/#2019). Our accomplishments are in accordance with or exceeding the planned goals. These tools are expected to have significant positive effects on researchers' ability to analyze genotype/phenotype data associated with traits of economic and health importance in livestock. In 2019, web hits from visitors worldwide to the QTLdb exceeded 2 million (2,206,756) from 28,005 unique users, who downloaded 35.9GB of data. Objective 1: Curation of genotype-to-phenotype data to annotate livestock genomes. In 2019, a total of 13,229 new QTL/association data were curated into QTLdb, bringing the total number of data added during the granting period to 129,944, which represents a nearly 3.7-fold increase from the project start date. Currently, there are 30,170 porcine QTL/associations, 130,407 bovine QTL/associations, 11,818 chicken QTL/associations, 2,413 horse QTL/associations, 3,099 sheep QTL/associations, and 584 rainbow trout QTL/associations in the database. All new data have been ported to NCBI, Ensembl, UCSC genome browser, and Reuters Data Citation Index for data sharing upon each data release. Therefore, users can utilize the browsing and data mining tools at these database sites to explore animal QTL/association data. In 2019, a total of 6,123 new correlations and 1,037 heritability estimates were curated into CorrDB. Currently, the CorrDB contains 18,638 correlations (10,076 cattle; 1,221 chicken; 5,982 pig; and 1,150 sheep) and 3,251 heritabilities (1,391 cattle; 272 chicken; 1,378 pig; and 92 sheep). Objective 2: Continued development of new tools to facilitate genotype-to-phenotype data analysis. Throughout the reporting period, many updates and improvements have been made to the curator and public tools within CorrDB and QTLdb. QTLdb curator tools were repurposed in CorrDB, facilitating the curation of correlation and heritability data described above. New web portals have been developed to allow gene-centric and trait-centric views of QTL and association data. Recently, a new version of the QTL/association data enrichment test tool has been implemented in the Animal QTLdb that allows users to select traits and multiple sub-chromosomal regions to perform a genome-wide data enrichment analysis with Chi-square test of a two-way contingency table (traits by chromosomes) to identify the most plausible locations where certain traits may be over-represented. The tool is intuitive to use, and it is easily accessible from a number of points on the QTLdb web site. The tool also allows for enrichment testing on user-defined sizes of chromosomal sub-regions. During 2019, extensive improvements were made to the curator tools to better streamline workflows and create more intuitive curation environments. Among the new tools there are also newly added internal data uploads and workflows within the curation environment for between-curator collaboration. In the QTLdb public portal, data displays were added for epistatic and pleiotropic data that were introduced for curation in 2009 and 2014, respectively, and for linked references data introduced in 2013. In addition, capability for dynamic data download per user view on the gene-centric view and trait-centric view environments were also added. For CorrDB, there is a new revision of the front page where users can now easily access data by species. Continued development of VT/LPT: As an important part of Animal QTLdb/CorrDB development, expansion and improvement of the Vertebrate Trait Ontology (VT) and Livestock Product Trait Ontology (LPT) have been ongoing. During the reporting period, we released 24 new versions of VT and five new versions of LPT. In addition, we have released 22 versions of the Livestock Breed Ontology (LBO), which is used for annotation of QTL/associations with breed data. Each release of the updated VT/LPT/LBO data has been made available on BioPortal, Github, and the AnimalGenome.ORG web site. In summary, combining our works/reports in the past 4 year, our curation works have increased data 3.7 fold for QTLdb and 5.13 fold for CorrDB, respectively. We have re-developed the CorrDB curator tools, added/revised curator tools, user data portal, and analysis tools, in accordance with or exceeding the planned goals.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2019
Citation:
Zhi-Liang Hu, Carissa A. Park, and James M. Reecy (2019). Building a livestock genetic and genomic information knowledgebase through integrative developments of Animal QTLdb and CorrDB. Nucleic Acids Research, Volume 47, Issue D1, 8 January 2019, Pages D701D710.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2019
Citation:
Zhi-Liang Hu, Carissa Park, James M. Reecy (2019). Implementation of a new data enrichment analysis tool in the Animal QTL Database. Plant & Animal Genomes XXVII Conference, January 11-16, 2019. Town & Country Convention Center, San Diego, CA.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2018
Citation:
Zhi-Liang Hu, Carissa A. Park, and James M. Reecy (2018). Development of Animal QTLdb and CorrDB: Resynthesizing Big Data to Improve Meta-analysis of Genetic and Genomic Information. The 11th World Congress on Genetics Applied to Livestock Production (WCGALP). New Zealand, February 11-16, 2018.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2018
Citation:
Zhi-Liang Hu, Carissa A. Park, and James M. Reecy (2018). Animal QTLdb and CorrDB updates: integrative development of genetics/genomics databases and tools to meet new challenges. Plant & Animal Genomes XXVI Conference, January 13-17, 2018. Town & Country Convention Center, San Diego, CA.
- Type:
Journal Articles
Status:
Published
Year Published:
2018
Citation:
Harper L, Campbell J, Cannon EKS, et al. AgBioData consortium recommendations for sustainable genomics and genetics databases for agriculture. Database (Oxford). 2018. Published 2018 Sep 18. doi:10.1093/database/bay088
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Progress 01/15/18 to 01/14/19
Outputs
Target Audience:This project period, the target audiences were geneticists (human and livestock) and animal scientists. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?
Nothing Reported
How have the results been disseminated to communities of interest?All new QTLdb data are ported to NCBI, Ensembl, UCSC genome browser, and Reuters Data Citation Index upon each data release. Results were also presented at national and international conferences and in published journal articles. What do you plan to do during the next reporting period to accomplish the goals?We will continue to curate QTL/association data into Animal QTLdb and CorrDB. Furthermore, we are continuing to develop a trait enrichment tool, which will allow users to querry multiple regions of the genome simultaneously.
Impacts
What was accomplished under these goals?
Overall impact statement: The focus of this project is to better understand the relationships between livestock traits and to efficiently comprehend large amounts of genotype/phenotype association data that are being published at an accelerating rate. Our goal is to develop integrated resources that leverage prior national funding in cyberinfrastructure to help researchers maximize the utility of genotype-to-phenotype data to ultimately address issues important to the livestock industry. We have made significant progress toward our goals by vigorously curating new data into the QTLdb and CorrDB and diligently improving the database infrastructure and tools for improved efficiency and functionality. This progress is highlighted by three database releases in 2018 (see: https://www.animalgenome.org/QTLdb/release/ for #35, 36, and 37 and https://www.animalgenome.org/CorrDB/release/ for #3, 4 and 5). Our accomplishments are in accordance with or exceeding the planned goals. These tools are expected to have significant positive effects on researchers' ability to analyze genotype/phenotype data associated with traits of economic and health importance in livestock. Data downloads from the QTLdb in 2018 increased 26% compared to the previous year. Objective 1: Curation of genotype-to-phenotype data to annotate livestock genomes. In 2018, a total of 18,393 new QTL/association data were curated into QTLdb, representing a 12.6% data increase from the previous total. Currently, there are 28,720 curated porcine QTL/associations, 120,122 curated bovine QTL/associations, 10,944 curated chicken QTL/associations, 2,023 curated horse QTL/associations, 2,325 curated sheep QTL/associations, and 128 curated rainbow trout QTL in the database. All new data have been ported to NCBI, Ensembl, UCSC genome browser, and Reuters Data Citation Index for data sharing upon each data release. Therefore, users can utilize the browsing and data mining tools at these database sites to explore animal QTL/association data. In 2018, a total of 11,673 new correlations and 1,689 heritability estimates were curated into CorrDB. Currently, the database contains 12,515 correlations (7,767 cattle; 1,119 chicken; 2,481 pig; and 1,148 sheep) and 2,227 heritabilities (1,019 cattle; 247 chicken; 872 pig; and 89 sheep). This net increase takes into account the removal of 3,628 historic correlation data through a new data quality control process, followed by re-entry of many of them using data integrity check mechanisms newly built into the CorrDB. Objective 2: Continued development of new tools to facilitate genotype-to-phenotype data analysis. QTL/association data enrichment test tool: A new tool has been implemented in the Animal QTLdb to use a set of selected traits to perform a genome-wide data distribution analysis with Chi-square test of a two-way contingency table (traits by chromosomes) to identify the most plausible locations where certain traits may be over-represented. The tool is intuitive to use, and it is easily accessible from a number of points on the QTLdb web site. The tool also allows for enrichment testing on user-defined sizes of chromosome regions. Digital Object Identifiers (DOI): We have introduced the use of DOI on data that have such records available. This helps to facilitate data linking within and outside of the QTL database. Continued development of VT/LPT: As an important part of Animal QTLdb/CorrDB development, expansion and improvement of the Vertebrate Trait Ontology (VT) and Livestock Product Trait Ontology (LPT) have been ongoing. In 2018, we released eight new versions of VT (v.8.1-v.8.8) and two new versions of LPT (v.2.1 & 2.2). The updated VT/LPT data has been made available upon release on BioPortal, Github, and/or the AnimalGenome.ORG web site.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2018
Citation:
Harper L, Campbell J, Cannon EKS, et al. AgBioData consortium recommendations for sustainable genomics and genetics databases for agriculture. Database (Oxford). 2018. Published 2018 Sep 18. doi:10.1093/database/bay088
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2018
Citation:
Zhi-Liang Hu, Carissa A. Park, and James M. Reecy (2018). Animal QTLdb and CorrDB updates: integrative development of genetics/genomics databases and tools to meet new challenges. Plant & Animal Genomes XXVI Conference, January 13-17, 2018. Town & Country Convention Center, San Diego, CA.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2018
Citation:
Zhi-Liang Hu, Carissa A. Park, and James M. Reecy (2018). Development of Animal QTLdb and CorrDB: Resynthesizing Big Data to Improve Meta-analysis of Genetic and Genomic Information. The 11th World Congress on Genetics Applied to Livestock Production (WCGALP). New Zealand, February 11-16, 2018.
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Progress 01/15/17 to 01/14/18
Outputs
Target Audience:The results of this project will be of interest to geneticists (human and livestock), animal breeders, animal scientists, and progressive livestock producers. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?
Nothing Reported
How have the results been disseminated to communities of interest?All new QTLdb data are ported to NCBI, Ensembl, UCSC genome browser, and Reuters Data Citation Index upon each data release. What do you plan to do during the next reporting period to accomplish the goals?In 2018, we will continue to curate relevant data into the QTLdb and CorrDB. We will also develop and implement the Trait Enrichment Analysis tool in the QTLdb.
Impacts
What was accomplished under these goals?
Overall impact statement: The focus of this project is to better understand the relationships between livestock traits and to efficiently comprehend large amounts of genotype/phenotype association data that are being published at an accelerating rate. Our goal is to develop integrated resources that leverage prior national funding in cyberinfrastructure to help researchers maximize the utility of genotype-to-phenotype data to ultimately address issues important to the livestock industry. We have made significant progress toward our goals by vigorously curating new data into the QTLdb and diligently improving the database infrastructure and tools for improved efficiency and functionality. This progress is highlighted by three database releases in 2017 (see: http://www.animalgenome.org/QTLdb/release#2017). Our accomplishments are in accordance with or exceeding the planned goals. These tools are expected to have significant positive effects on researchers' ability to analyze genotype/phenotype data associated with traits of economic and health importance in livestock. Objective 1: Curation of genotype-to-phenotype data to annotate livestock genomes. In 2017, a total of 41,093 new QTL/association data were curated into the database, representing a 25% data increase from the previous total. Currently, there are 26,076 curated porcine QTL/associations, 108,040 curated bovine QTL/associations, 8,363 curated chicken QTL/associations, 1,304 curated horse QTL/associations, 1,932 curated sheep QTL/associations, and 127 curated rainbow trout QTL in the database. All new data have been ported to NCBI, Ensembl, UCSC genome browser, and Reuters Data Citation Index for data sharing upon each data release. Therefore, users can utilize the browsing and data mining tools at these database sites to explore animal QTL/association data. We have continued improvements of our batch-load tool which have greatly helped speed up the curation process for large quantities of well-formatted data in Excel. These include some new codes and procedures to convert tables in PDF to Excel. We have continued improvements and enforced use of the "Minimum information required for Animal QTLdb data entry" (http://www.animalgenome.org/QTLdb/doc/minfo/). Several updates were made with new information. For example, we have added newly required Digital Object Identifier information, newly available genome build information, etc. Objective 2: Development of new tools to visualize, extract, and compare genotype-to-phenotype data. Gene/trait-centric view of QTL/association data: New web portals have been developed for display of "gene-centric view" and "trait-centric view" of QTL/association data when underlying gene information is available. This tool helps users to relatively quickly interrogate and retrieve genotype-to-phenotype information in a synopsis. CorrDB curator tools: The development of CorrDB has picked up speed. Several major components of the CorrDB curation tools have been developed and tested successfully. The curator tools were significantly improved from the incorporated QTLdb curation tools, especially in terms of data quality assurance by tightening up the workflow from experiment information to correlation data curation. For example, trait information is set up for entry once in the experiment and picked up in trait measurement and correlation data entry, without curators having to manually enter the trait ID. All trait information management tasks are left to QTLdb tools. To accommodate the needs of CorrDB, the QTLdb trait management system has introduced traits with modifiers, which are more often seen in correlation studies. In addition, reciprocal dynamic links between QTL data and correlation data have been implemented where common traits are found. Continued development of VT/PT: As an important part of Animal QTLdb/CorrDB development, expansion and improvement of the Vertebrate Trait Ontology (VT) and Livestock Product Trait Ontology (LPT) have been ongoing. In 2017, we released seven new versions of VT (v.7.1-v.7.7). An updated version of the LPT is expected to be released in early 2018, and we anticipate multiple releases of the VT throughout the year. Trait Enrichment Analysis: We are engaged in the development of this tool right now and anticipate it to be implemented by mid-2018.
Publications
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Progress 01/15/16 to 01/14/17
Outputs
Target Audience:Researchers' who utilize genotype/phenotype data for livestock research Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?
Nothing Reported
How have the results been disseminated to communities of interest?All new QTLdb data are ported to NCBI, Ensembl, UCSC genome browser, and Reuters Data Citation Index upon each data release. What do you plan to do during the next reporting period to accomplish the goals? Continued curation of genotype-to-phenotype data to annotate livestock genomes. Customizing WebVOWL software as described above. Release of CorrDB curator tools for public data entry. Continued development of Vertebrate Trait Ontology (VT) and Livestock Product Trait Ontology (LPT). We anticipate beginning work on trait enrichment analysis in late 2017 or early 2018.
Impacts
What was accomplished under these goals?
IMPACT: There is a need to better understand the relationships between livestock traits and to efficiently comprehend large amounts of genotype/phenotype association data that are being published at an accelerating rate. Our goal is to develop integrated resources that leverage prior national funding in cyberinfrastructure to help researchers maximize the utility of genotype-to-phenotype data to ultimately address issues important to the livestock industry. We have made significant progress toward our goals by vigorously curating new data into the QTLdb and diligently improving the database infrastructure and tools for improved efficiency and functionality. This progress is highlighted by three database releases in 2016 (see: http://www.animalgenome.org/QTLdb/release#2016). Our accomplishments are in accordance with or exceeding the planned goals. These tools are expected to have significant positive effects on researchers' ability to analyze genotype/phenotype data associated with traits of economic and health importance in livestock. Objective 1: Curation of genotype-to-phenotype data to annotate livestock genomes. In 2016, a total of 57,229 new QTL/association data were curated into the database, representing a 47% data increase from the previous year. Currently, there are 16,516 curated porcine QTL, 95,332 curated bovine QTL, 6,633 curated chicken QTL, 1,245 curated horse QTL, 1,412 curated sheep QTL, and 127 curated rainbow trout QTL in the database. All new data have been ported to NCBI, Ensembl, UCSC genome browser, and Reuters Data Citation Index for data sharing upon each data release. Therefore, users can utilize the browsing and data mining tools at these database sites to explore animal QTL/association data. To speed up data curation, we have previously implemented a batch-load tool for large quantities of well-formatted data, to help curators avoid tedious manual processes. New efforts have been made to implement quality control procedures to catch data errors, report odd situations, and establish steps where intermediate curation data can be temporarily stored and available for correction/reference during data QC/release processes. To assist users in preparing their data for entry, we have published a protocol called "minimum information required for Animal QTLdb data entry" in the form of a public web page (http://www.animalgenome.org/QTLdb/doc/minfo/), where data templates in the form of Microsoft Excel sheets are available. In 2016, more than 27 minor improvements were made to the curation tools; continued curator/user tool improvements and bug fixes have been, and will continue to be, part of Animal QTLdb/CorrDB development. Objective 2: Development of new tools to visualize, extract, and compare genotype-to-phenotype data. Progress has been made on the Animal QTLdb (http://www.animalgenome.org/QTLdb): Gene/trait-centric view of QTL/association data: a preliminary/experimental implementation of gene/trait-centric views can be seen at http://www.animalgenome.org/cgi-bin/QTLdb/BT/genesrch. Work is underway to refine the searches and to improve visualization formats with a design that will make it easier for users to get an overview as well as to explore further using built-in dynamic hyperlink options. This work is expected to be finished before mid-2017. Improvements to CorrDB and ontology visualizations: We have recently employed publicly available software called WebVOWL (http://vowl.visualdataweb.org/webvowl.html) that has great flexibility and potential to be further developed or customized for correlation/trait ontology network display. A preliminary implementation has been made at the AnimalGenome.ORG site (http://www.animalgenome.org/bioinfo/projects/ato/webVOWL/). Current work is focused on customizing it for local use, before new developmental work is carried out. This work is expected to roll into the production line in the latter half of 2017. CorrDB curator tools: CorrDB curation tools have been under active development to allow remote curators to curate trait correlation data into the database. Efforts have been made to make use of resources and tools already in the QTLdb for trait ontology development and management, literature management, and bug reporting tools for data quality control. The tools are nearly ready to release for public data entry. We anticipate this set of tools will be released very soon (expected early in 2017). Continued development of VT/PT: As an important part of Animal QTLdb/CorrDB development, expansion and improvement of the Vertebrate Trait Ontology (VT) and Livestock Product Trait Ontology (LPT) have been ongoing. In 2016, we released nine new versions of VT (v.6.1-v.6.9), and two versions of LPT (v.1.3-v1.4). In 2017 a similar release pace is expected. Trait Enrichment Analysis: We have not started our work on this. We anticipate beginning work on this in late 2017 or early 2018.
Publications
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