BACKGROUND: The advancement of sequencing technologies today has made a plethora of whole-genome re-sequenced (WGRS) data publicly available. However, research utilizing the WGRS data without further configuration is nearly impossible. To solve this problem, our research group has developed an interactive Allele Catalog Tool to enable researchers to explore the coding region allelic variation present in over 1,000 re-sequenced accessions each for soybean, Arabidopsis, and maize. RESULTS: The Allele Catalog Tool was designed originally with soybean genomic data and resources. The Allele Catalog datasets were generated using our variant calling pipeline (SnakyVC) and the Allele Catalog pipeline (AlleleCatalog). The variant calling pipeline is developed to parallelly process raw sequencing reads to generate the Variant Call Format (VCF) files, and the Allele Catalog pipeline takes VCF files to perform imputations, functional effect predictions, and assemble alleles for each gene to generate curated Allele Catalog datasets. Both pipelines were utilized to generate the data panels (VCF files and Allele Catalog files) in which the accessions of the WGRS datasets were collected from various sources, currently representing over 1,000 diverse accessions for soybean, Arabidopsis, and maize individually. The main features of the Allele Catalog Tool include data query, visualization of results, categorical filtering, and download functions. Queries are performed from user input, and results are a tabular format of summary results by categorical description and genotype results of the alleles for each gene. The categorical information is specific to each species; additionally, available detailed meta-information is provided in modal popups. The genotypic information contains the variant positions, reference or alternate genotypes, the functional effect classes, and the amino-acid changes of each accession. Besides that, the results can also be downloaded for other research purposes. CONCLUSIONS: The Allele Catalog Tool is a web-based tool that currently supports three species: soybean, Arabidopsis, and maize. The Soybean Allele Catalog Tool is hosted on the SoyKB website ( https://soykb.org/SoybeanAlleleCatalogTool/ ), while the Allele Catalog Tool for Arabidopsis and maize is hosted on the KBCommons website ( https://kbcommons.org/system/tools/AlleleCatalogTool/Zmays and https://kbcommons.org/system/tools/AlleleCatalogTool/Athaliana ). Researchers can use this tool to connect variant alleles of genes with meta-information of species.

• MeSH
• alely * MeSH
• Arabidopsis * genetika   MeSH
• data mining * metody   MeSH
• datové soubory jako téma * MeSH
• frekvence genu MeSH
• genotyp MeSH
• Glycine max * genetika   MeSH
• internet * MeSH
• kukuřice setá * genetika   MeSH
• metadata MeSH
• mutace MeSH
• pigmentace genetika   MeSH
• rostlinné geny genetika   MeSH
• software * MeSH
• substituce aminokyselin MeSH
• vegetační klid genetika   MeSH
• vizualizace dat MeSH
• Publikační typ
• časopisecké články MeSH

The genome-wide association study (GWAS) is a popular genomic approach that identifies genomic regions associated with a phenotype and, thus, aims to discover causative mutations (CM) in the genes underlying the phenotype. However, GWAS discoveries are limited by many factors and typically identify associated genomic regions without the further ability to compare the viability of candidate genes and actual CMs. Therefore, the current methodology is limited to CM identification. In our recent work, we presented a novel approach to an empowered "GWAS to Genes" strategy that we named Synthetic phenotype to causative mutation (SP2CM). We established this strategy to identify CMs in soybean genes and developed a web-based tool for accuracy calculation (AccuTool) for a reference panel of soybean accessions. Here, we describe our further development of the tool that extends its utilization for other species and named it AccuCalc. We enhanced the tool for the analysis of datasets with a low-frequency distribution of a rare phenotype by automated formatting of a synthetic phenotype and added another accuracy-based GWAS evaluation criterion to the accuracy calculation. We designed AccuCalc as a Python package for GWAS data analysis for any user-defined species-independent variant calling format (vcf) or HapMap format (hmp) as input data. AccuCalc saves analysis outputs in user-friendly tab-delimited formats and also offers visualization of the GWAS results as Manhattan plots accentuated by accuracy. Under the hood of Python, AccuCalc is publicly available and, thus, can be used conveniently for the SP2CM strategy utilization for every species.

• MeSH
• celogenomová asociační studie * metody   MeSH
• fenotyp MeSH
• genom MeSH
• genomika * metody   MeSH
• mutace MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH