GeneToCN: an alignment-free method for gene copy number estimation directly from next-generation sequencing reads
Abstract Genomes exhibit large regions with segmental copy number variation, many of which include entire genes and are multiallelic. We have developed a computational method GeneToCN that counts the frequencies of gene-specific k-mers in FASTQ files and uses this information to infer copy number of...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-10-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-44636-z |
| _version_ | 1797453144940085248 |
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| author | Fanny-Dhelia Pajuste Maido Remm |
| author_facet | Fanny-Dhelia Pajuste Maido Remm |
| author_sort | Fanny-Dhelia Pajuste |
| collection | DOAJ |
| description | Abstract Genomes exhibit large regions with segmental copy number variation, many of which include entire genes and are multiallelic. We have developed a computational method GeneToCN that counts the frequencies of gene-specific k-mers in FASTQ files and uses this information to infer copy number of the gene. We validated the copy number predictions for amylase genes (AMY1, AMY2A, AMY2B) using experimental data from digital droplet PCR (ddPCR) on 39 individuals and observed a strong correlation (R = 0.99) between GeneToCN predictions and experimentally determined copy numbers. An additional validation on FCGR3 genes showed a higher concordance for FCGR3A compared to two other methods, but reduced accuracy for FCGR3B. We further tested the method on three different genomic regions (SMN, NPY4R, and LPA Kringle IV-2 domain). Predicted copy number distributions of these genes in a set of 500 individuals from the Estonian Biobank were in good agreement with the previously published studies. In addition, we investigated the possibility to use GeneToCN on sequencing data generated by different technologies by comparing copy number predictions from Illumina, PacBio, and Oxford Nanopore data of the same sample. Despite the differences in variability of k-mer frequencies, all three sequencing technologies give similar predictions with GeneToCN. |
| first_indexed | 2024-03-09T15:18:37Z |
| format | Article |
| id | doaj.art-7f41ced26aeb4e4f854aca02f2348d37 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-09T15:18:37Z |
| publishDate | 2023-10-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-7f41ced26aeb4e4f854aca02f2348d372023-11-26T12:58:18ZengNature PortfolioScientific Reports2045-23222023-10-0113111010.1038/s41598-023-44636-zGeneToCN: an alignment-free method for gene copy number estimation directly from next-generation sequencing readsFanny-Dhelia Pajuste0Maido Remm1Institute of Molecular and Cell Biology, University of TartuInstitute of Molecular and Cell Biology, University of TartuAbstract Genomes exhibit large regions with segmental copy number variation, many of which include entire genes and are multiallelic. We have developed a computational method GeneToCN that counts the frequencies of gene-specific k-mers in FASTQ files and uses this information to infer copy number of the gene. We validated the copy number predictions for amylase genes (AMY1, AMY2A, AMY2B) using experimental data from digital droplet PCR (ddPCR) on 39 individuals and observed a strong correlation (R = 0.99) between GeneToCN predictions and experimentally determined copy numbers. An additional validation on FCGR3 genes showed a higher concordance for FCGR3A compared to two other methods, but reduced accuracy for FCGR3B. We further tested the method on three different genomic regions (SMN, NPY4R, and LPA Kringle IV-2 domain). Predicted copy number distributions of these genes in a set of 500 individuals from the Estonian Biobank were in good agreement with the previously published studies. In addition, we investigated the possibility to use GeneToCN on sequencing data generated by different technologies by comparing copy number predictions from Illumina, PacBio, and Oxford Nanopore data of the same sample. Despite the differences in variability of k-mer frequencies, all three sequencing technologies give similar predictions with GeneToCN.https://doi.org/10.1038/s41598-023-44636-z |
| spellingShingle | Fanny-Dhelia Pajuste Maido Remm GeneToCN: an alignment-free method for gene copy number estimation directly from next-generation sequencing reads Scientific Reports |
| title | GeneToCN: an alignment-free method for gene copy number estimation directly from next-generation sequencing reads |
| title_full | GeneToCN: an alignment-free method for gene copy number estimation directly from next-generation sequencing reads |
| title_fullStr | GeneToCN: an alignment-free method for gene copy number estimation directly from next-generation sequencing reads |
| title_full_unstemmed | GeneToCN: an alignment-free method for gene copy number estimation directly from next-generation sequencing reads |
| title_short | GeneToCN: an alignment-free method for gene copy number estimation directly from next-generation sequencing reads |
| title_sort | genetocn an alignment free method for gene copy number estimation directly from next generation sequencing reads |
| url | https://doi.org/10.1038/s41598-023-44636-z |
| work_keys_str_mv | AT fannydheliapajuste genetocnanalignmentfreemethodforgenecopynumberestimationdirectlyfromnextgenerationsequencingreads AT maidoremm genetocnanalignmentfreemethodforgenecopynumberestimationdirectlyfromnextgenerationsequencingreads |