Rapid fine mapping of causative mutations from sets of unordered, contig-sized fragments of genome sequence
| العنوان: | Rapid fine mapping of causative mutations from sets of unordered, contig-sized fragments of genome sequence |
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| المؤلفون: | Pilar Corredor-Moreno, Martin Page, Edward Chalstrey, Ghanasyam Rallapalli, Dan MacLean |
| المصدر: | BMC Bioinformatics BMC Bioinformatics, Vol 20, Iss 1, Pp 1-7 (2019) |
| بيانات النشر: | Springer Science and Business Media LLC, 2019. |
| سنة النشر: | 2019 |
| مصطلحات موضوعية: | Computer science, Arabidopsis, Sequence assembly, Computational biology, lcsh:Computer applications to medicine. Medical informatics, Genes, Plant, Polymorphism, Single Nucleotide, Zea mays, Biochemistry, Genome, Chromosomes, Plant, DNA sequencing, 03 medical and health sciences, 0302 clinical medicine, Bulk segregant analysis, Structural Biology, Mapping by sequencing, Allele, lcsh:QH301-705.5, Molecular Biology, Next generation mapping, 030304 developmental biology, Cloning, Whole genome sequencing, 0303 health sciences, Cloning (programming), Contig, Applied Mathematics, Homozygote, Mutagenesis, Chromosome Mapping, High-Throughput Nucleotide Sequencing, Hordeum, Sequence Analysis, DNA, Computer Science Applications, lcsh:Biology (General), 030220 oncology & carcinogenesis, Mutation, lcsh:R858-859.7, Identification (biology), DNA microarray, Software, Genome, Plant |
| الوصف: | Background Traditional Map based Cloning approaches, used for the identification of desirable alleles, are extremely labour intensive and years can elapse between the mutagenesis and the detection of the polymorphism. High throughput sequencing based Mapping-by-sequencing approach requires an ordered genome assembly and cannot be used with fragmented, un-scaffolded draft genomes, limiting its application to model species and precluding many important organisms. Results We addressed this gap in resource and presented a computational method and software implementations called CHERIPIC (Computing Homozygosity Enriched Regions In genomes to Prioritise Identification of Candidate variants). We have successfully validated implementation of CHERIPIC using three different types of bulk segregant sequence data from Arabidopsis, maize and barley, respectively. Conclusions CHERIPIC allows users to rapidly analyse bulk segregant sequence data and we have made it available as a pre-packaged binary with all dependencies for Linux and MacOS and as Galaxy tool. Electronic supplementary material The online version of this article (10.1186/s12859-018-2515-5) contains supplementary material, which is available to authorized users. |
| وصف الملف: | application/pdf |
| تدمد: | 1471-2105 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::af8b0275e94b4656cb976974ed785c9b https://doi.org/10.1186/s12859-018-2515-5 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....af8b0275e94b4656cb976974ed785c9b |
| قاعدة البيانات: | OpenAIRE |
Find this article in full text from Springer Verlag. | تدمد: | 14712105 |
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