Forward genetic screens have successfully identified many genes and continue to be powerful tools for dissecting biological processes in Arabidopsis and other model species. Next-generation sequencing technologies have revolutionized the time-consuming process of identifying the mutations that cause a phenotype of interest. However, due to the cost of such mapping-by-sequencing experiments, special attention should be paid to experimental design and technical decisions so that the read data allows to map the desired mutation. Here, we simulated different mapping-by-sequencing scenarios. We first evaluated which short-read technology was best suited for analyzing gene-rich genomic regions in Arabidopsis and determined the minimum sequencing depth required to confidently call single nucleotide variants. We also designed ways to discriminate mutagenesis-induced mutations from background Single Nucleotide Polymorphisms in mutants isolated in Arabidopsis non-reference lines. In addition, we simulated bulked segregant mapping populations for identifying point mutations and monitored how the size of the mapping population and the sequencing depth affect mapping precision. Finally, we provide the computational basis of a protocol that we already used to map T-DNA insertions with paired-end Illumina-like reads, using very low sequencing depths and pooling several mutants together; this approach can also be used with single-end reads as well as to map any other insertional mutagen. All these simulations proved useful for designing experiments that allowed us to map several mutations in Arabidopsis.
Mapping-by-sequencing strategies combine next-generation sequencing (NGS) with classical linkage analysis, allowing rapid identification of the causal mutations of the phenotypes exhibited by mutants isolated in a genetic screen. Computer programs that analyze NGS data obtained from a mapping population of individuals derived from a mutant of interest to identify a causal mutation are available; however, the installation and usage of such programs requires bioinformatic skills, modifying or combining pieces of existing software, or purchasing licenses. To ease this process, we developed Easymap, an open-source program that simplifies the data analysis workflows from raw NGS reads to candidate mutations. Easymap can perform bulked segregant mapping of point mutations induced by ethyl methanesulfonate (EMS) with DNA-seq or RNA-seq datasets, as well as tagged-sequence mapping for large insertions, such as transposons or T-DNAs. The mapping analyses implemented in Easymap have been validated with experimental and simulated datasets from different plant and animal model species. Easymap was designed to be accessible to all users regardless of their bioinformatics skills by implementing a user-friendly graphical interface, a simple universal installation script, and detailed mapping reports, including informative images and complementary data for assessment of the mapping results. Easymap is available at http://genetics.edu.umh.es/resources/easymap; its Quickstart Installation Guide details the recommended procedure for installation.
Mapping-by-sequencing strategies combine next-generation sequencing (NGS) with classical linkage analysis, allowing rapid identification of the causal mutations of the phenotypes exhibited by mutants isolated in a genetic screen. Computer programs that analyze NGS data obtained from a mapping population of individuals derived from a mutant of interest in order to identify a causal mutation are available; however, the installation and usage of such programs requires bioinformatic skills, modifying or combining pieces of existing software, or purchasing licenses. To ease this process, we developed Easymap, an open-source program that simplifies the data analysis workflows from raw NGS reads to candidate mutations. Easymap can perform bulked segregant mapping of point mutations induced by ethyl methanesulfonate (EMS) with DNA-seq or RNA-seq datasets, as well as tagged-sequence mapping for large insertions, such as transposons or T-DNAs. The mapping analyses implemented in Easymap have been validated with experimental and simulated datasets from different plant and animal model species. Easymap was designed to be accessible to all users regardless of their bioinformatics skills by implementing a user-friendly graphical interface, a simple universal installation script, and detailed mapping reports, including informative images and complementary data for assessment of the mapping results.One sentence summaryEasymap is a versatile user-friendly software tool that facilitates mapping-by-sequencing of large insertions and point mutations in plant and animal genomes
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