[ Software Initial Letter ]
[ G ]
PCR-based gene deletion and tagging is a simple and powerful approach for studying gene functions. Here we present GetPrimers, a generalized computational framework and web tool for automatically designing primers of PCR-based gene deletion and tagging. Two modes of gene targeting strategies are supported: the long primer strategy and the short primer strategy. The long primer strategy is conventionally used but the sizes of the homoglous regions that it creates for recombination-mediated gene targeting are usually limited (e.g. ~ 40 bp). In contrast, the short primer strategy can create homologous regions that are an order of magnitude larger (e.g. ~ 200-600 bp) and therefore substantially increases the efficiency of recombination-mediated gene targeting. While pre-computed genome-wide results are provided for Saccharomyces cerevisiae and Schizosaccharomyces pombe reference genomes out of the box, the input genome, gene annotation, and plasmid sequences can be fully customized based on any given species and genetic backgrounds.
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[ L ]
Long-read sequencing technologies have become increasingly popular in genome projects due to their strengths in resolving complex genomic regions. As a leading model organism with small genome size and great biotechnological importance, the budding yeast, Saccharomyces cerevisiae, has many isolates currently being sequenced with long reads. However, analyzing long-read sequencing data to produce high-quality genome assembly and annotation remains challenging. LRSDAY is the first one-stop solution to streamline this process. LRSDAY can produce chromosome-level end-to-end genome assembly and comprehensive annotations for various genomic features (including centromeres, protein-coding genes, tRNAs, transposable elements and telomere-associated elements) that are ready for downstream analysis. Although tailored for S. cerevisiae, we designed LRSDAY to be highly modular and customizable, making it adaptable for virtually any eukaryotic organisms.
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[ R ]
Meiotic recombination is an essential biological process that ensures faithful chromosome segregation and promotes parental allele reshuffling. Tetrad analysis is a powerful approach to quantify the genetic makeups and recombination landscapes of meiotic products. Here we present RecombineX, an integrated computational framework that automates the full workflow of marker identification, gamete genotyping, and tetrad-based recombination profiling in a high-throughput fashion, capable of processing hundreds of tetrads in a single batch. Aside from conventional reference-based analysis, RecombineX can also perform analysis based on parental genome assemblies, which enables analyzing meiotic recombination landscapes in their native genomic contexts. Additional features such as copy number variation profiling and missing genotype inference further enhance downstream analysis. RecombineX also includes a dedicate module for simulating the genomes and reads of recombinant tetrads for any given organisms, which enables fine-tuned simulation-based hypothesis testing.
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[ S ]
Simulated genomes with pre-defined and random genomic variants can be very useful for benchmarking genomic and bioinformatics analyses. Here we introduce simuG as a light-weighted tool for simulating the full spectrum of genomic variants (SNPs, INDELs, CNVs, inversions, and translocations). It also provides a rich array of options for fine-grained controls on the specific type and properties of variants to be introduced. The simplicity and versatility of simuG make it a unique general purpose genome simulator for a wide-range of simulation-based applications.