Piercing the dark matter: bioinformatics of long-range sequencing and mapping

• Published in: Nature reviews. Genetics Vol. 19; no. 6; pp. 329 - 346
• Main Authors: Sedlazeck, Fritz J., Lee, Hayan, Darby, Charlotte A., Schatz, Michael C.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01-06-2018; Nature Publishing Group
• Subjects: 38/39; 631/1647/48; 631/208/212/2302; 631/208/514/2254; 631/208/726; Agriculture; Animal Genetics and Genomics; Animals; Bioinformatics; Biomedical and Life Sciences; Biomedicine; Cancer Research; Chromosome mapping; Chromosome Mapping - methods; Computational biology; Computational Biology - methods; DNA sequencing; Gene Expression Profiling - methods; Gene Function; Gene mapping; Genetic research; Genomes; Genomics; Genomics - methods; High-Throughput Nucleotide Sequencing - methods; Human Genetics; Humans; Review Article; Technology; Transcriptome
• ISSN: 1471-0056; 1471-0064
• DOI: 10.1038/s41576-018-0003-4

Several new genomics technologies have become available that offer long-read sequencing or long-range mapping with higher throughput and higher resolution analysis than ever before. These long-range technologies are rapidly advancing the field with improved reference genomes, more comprehensive variant identification and more complete views of transcriptomes and epigenomes. However, they also require new bioinformatics approaches to take full advantage of their unique characteristics while overcoming their complex errors and modalities. Here, we discuss several of the most important applications of the new technologies, focusing on both the currently available bioinformatics tools and opportunities for future research.
Various genomics-related fields are increasingly taking advantage of long-read sequencing and long-range mapping technologies, but making sense of the data requires new analysis strategies. This Review discusses bioinformatics tools that have been devised to handle the numerous characteristic features of these long-range data types, with applications in genome assembly, genetic variant detection, haplotype phasing, transcriptomics and epigenomics.