A high-performance computational workflow to accelerate GATK SNP detection across a 25-genome dataset
Background Single-nucleotide polymorphisms (SNPs) are the most widely used form of molecular genetic variation studies. As reference genomes and resequencing data sets expand exponentially, tools must be in place to call SNPs at a similar pace. The genome analysis toolkit (GATK) is one of the most w...
| Main Authors: | , , , , , , , , , , , , , , , , , , |
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| Format: | Journal Article |
| Language: | Inglés |
| Published: |
Springer
2024
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/163079 |
| _version_ | 1855539219800260608 |
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| author | Zhou, Yong Kathiresan, Nagarajan Yu, Zhichao Rivera, Luis F. Yang, Yujian Thimma, Manjula Manickam, Keerthana Chebotarov, Dmytro Mauleon, Ramil Chougule, Kapeel Wei, Sharon Gao, Tingting Green, Carl D. Zuccolo, Andrea Xie, Weibo Ware, Doreen Zhang, Jianwei McNally, Kenneth L. Wing, Rod A. |
| author_browse | Chebotarov, Dmytro Chougule, Kapeel Gao, Tingting Green, Carl D. Kathiresan, Nagarajan Manickam, Keerthana Mauleon, Ramil McNally, Kenneth L. Rivera, Luis F. Thimma, Manjula Ware, Doreen Wei, Sharon Wing, Rod A. Xie, Weibo Yang, Yujian Yu, Zhichao Zhang, Jianwei Zhou, Yong Zuccolo, Andrea |
| author_facet | Zhou, Yong Kathiresan, Nagarajan Yu, Zhichao Rivera, Luis F. Yang, Yujian Thimma, Manjula Manickam, Keerthana Chebotarov, Dmytro Mauleon, Ramil Chougule, Kapeel Wei, Sharon Gao, Tingting Green, Carl D. Zuccolo, Andrea Xie, Weibo Ware, Doreen Zhang, Jianwei McNally, Kenneth L. Wing, Rod A. |
| author_sort | Zhou, Yong |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Background
Single-nucleotide polymorphisms (SNPs) are the most widely used form of molecular genetic variation studies. As reference genomes and resequencing data sets expand exponentially, tools must be in place to call SNPs at a similar pace. The genome analysis toolkit (GATK) is one of the most widely used SNP calling software tools publicly available, but unfortunately, high-performance computing versions of this tool have yet to become widely available and affordable.
Results
Here we report an open-source high-performance computing genome variant calling workflow (HPC-GVCW) for GATK that can run on multiple computing platforms from supercomputers to desktop machines. We benchmarked HPC-GVCW on multiple crop species for performance and accuracy with comparable results with previously published reports (using GATK alone). Finally, we used HPC-GVCW in production mode to call SNPs on a “subpopulation aware” 16-genome rice reference panel with ~ 3000 resequenced rice accessions. The entire process took ~ 16 weeks and resulted in the identification of an average of 27.3 M SNPs/genome and the discovery of ~ 2.3 million novel SNPs that were not present in the flagship reference genome for rice (i.e., IRGSP RefSeq).
Conclusions
This study developed an open-source pipeline (HPC-GVCW) to run GATK on HPC platforms, which significantly improved the speed at which SNPs can be called. The workflow is widely applicable as demonstrated successfully for four major crop species with genomes ranging in size from 400 Mb to 2.4 Gb. Using HPC-GVCW in production mode to call SNPs on a 25 multi-crop-reference genome data set produced over 1.1 billion SNPs that were publicly released for functional and breeding studies. For rice, many novel SNPs were identified and were found to reside within genes and open chromatin regions that are predicted to have functional consequences. Combined, our results demonstrate the usefulness of combining a high-performance SNP calling architecture solution with a subpopulation-aware reference genome panel for rapid SNP discovery and public deployment. |
| format | Journal Article |
| id | CGSpace163079 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | Springer |
| publisherStr | Springer |
| record_format | dspace |
| spelling | CGSpace1630792025-12-08T10:06:44Z A high-performance computational workflow to accelerate GATK SNP detection across a 25-genome dataset Zhou, Yong Kathiresan, Nagarajan Yu, Zhichao Rivera, Luis F. Yang, Yujian Thimma, Manjula Manickam, Keerthana Chebotarov, Dmytro Mauleon, Ramil Chougule, Kapeel Wei, Sharon Gao, Tingting Green, Carl D. Zuccolo, Andrea Xie, Weibo Ware, Doreen Zhang, Jianwei McNally, Kenneth L. Wing, Rod A. single nucleotide polymorphisms genomes rice sorghum maize soybeans food crops Background Single-nucleotide polymorphisms (SNPs) are the most widely used form of molecular genetic variation studies. As reference genomes and resequencing data sets expand exponentially, tools must be in place to call SNPs at a similar pace. The genome analysis toolkit (GATK) is one of the most widely used SNP calling software tools publicly available, but unfortunately, high-performance computing versions of this tool have yet to become widely available and affordable. Results Here we report an open-source high-performance computing genome variant calling workflow (HPC-GVCW) for GATK that can run on multiple computing platforms from supercomputers to desktop machines. We benchmarked HPC-GVCW on multiple crop species for performance and accuracy with comparable results with previously published reports (using GATK alone). Finally, we used HPC-GVCW in production mode to call SNPs on a “subpopulation aware” 16-genome rice reference panel with ~ 3000 resequenced rice accessions. The entire process took ~ 16 weeks and resulted in the identification of an average of 27.3 M SNPs/genome and the discovery of ~ 2.3 million novel SNPs that were not present in the flagship reference genome for rice (i.e., IRGSP RefSeq). Conclusions This study developed an open-source pipeline (HPC-GVCW) to run GATK on HPC platforms, which significantly improved the speed at which SNPs can be called. The workflow is widely applicable as demonstrated successfully for four major crop species with genomes ranging in size from 400 Mb to 2.4 Gb. Using HPC-GVCW in production mode to call SNPs on a 25 multi-crop-reference genome data set produced over 1.1 billion SNPs that were publicly released for functional and breeding studies. For rice, many novel SNPs were identified and were found to reside within genes and open chromatin regions that are predicted to have functional consequences. Combined, our results demonstrate the usefulness of combining a high-performance SNP calling architecture solution with a subpopulation-aware reference genome panel for rapid SNP discovery and public deployment. 2024-01-25 2024-12-05T16:04:15Z 2024-12-05T16:04:15Z Journal Article https://hdl.handle.net/10568/163079 en Open Access application/pdf Springer Zhou, Y., Kathiresan, N., Yu, Z. et al. A high-performance computational workflow to accelerate GATK SNP detection across a 25-genome dataset. BMC Biol 22, 13 (2024). https://doi.org/10.1186/s12915-024-01820-5 |
| spellingShingle | single nucleotide polymorphisms genomes rice sorghum maize soybeans food crops Zhou, Yong Kathiresan, Nagarajan Yu, Zhichao Rivera, Luis F. Yang, Yujian Thimma, Manjula Manickam, Keerthana Chebotarov, Dmytro Mauleon, Ramil Chougule, Kapeel Wei, Sharon Gao, Tingting Green, Carl D. Zuccolo, Andrea Xie, Weibo Ware, Doreen Zhang, Jianwei McNally, Kenneth L. Wing, Rod A. A high-performance computational workflow to accelerate GATK SNP detection across a 25-genome dataset |
| title | A high-performance computational workflow to accelerate GATK SNP detection across a 25-genome dataset |
| title_full | A high-performance computational workflow to accelerate GATK SNP detection across a 25-genome dataset |
| title_fullStr | A high-performance computational workflow to accelerate GATK SNP detection across a 25-genome dataset |
| title_full_unstemmed | A high-performance computational workflow to accelerate GATK SNP detection across a 25-genome dataset |
| title_short | A high-performance computational workflow to accelerate GATK SNP detection across a 25-genome dataset |
| title_sort | high performance computational workflow to accelerate gatk snp detection across a 25 genome dataset |
| topic | single nucleotide polymorphisms genomes rice sorghum maize soybeans food crops |
| url | https://hdl.handle.net/10568/163079 |
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