Article: Revisiting genomes of non-model species with long reads yields new insights into their biology and evolution.
2024 Volume 15, Page(s) 1308527
Abstract: High-quality genomes obtained using long-read data allow not only for a better understanding of heterozygosity levels, repeat content, and more accurate gene annotation and prediction when compared to those obtained with short-read technologies, but also ...
| Abstract | High-quality genomes obtained using long-read data allow not only for a better understanding of heterozygosity levels, repeat content, and more accurate gene annotation and prediction when compared to those obtained with short-read technologies, but also allow to understand haplotype divergence. Advances in long-read sequencing technologies in the last years have made it possible to produce such high-quality assemblies for non-model organisms. This allows us to revisit genomes, which have been problematic to scaffold to chromosome-scale with previous generations of data and assembly software. Nematoda, one of the most diverse and speciose animal phyla within metazoans, remains poorly studied, and many previously assembled genomes are fragmented. Using long reads obtained with Nanopore R10.4.1 and PacBio HiFi, we generated highly contiguous assemblies of a diploid nematode of the Mermithidae family, for which no closely related genomes are available to date, as well as a collapsed assembly and a phased assembly for a triploid nematode from the Panagrolaimidae family. Both genomes had been analysed before, but the fragmented assemblies had scaffold sizes comparable to the length of long reads prior to assembly. Our new assemblies illustrate how long-read technologies allow for a much better representation of species genomes. We are now able to conduct more accurate downstream assays based on more complete gene and transposable element predictions. |
|---|---|
| Language | English |
| Publishing date | 2024-02-07 |
| Publishing country | Switzerland |
| Document type | Journal Article |
| ZDB-ID | 2606823-0 |
| ISSN | 1664-8021 |
| ISSN | 1664-8021 |
| DOI | 10.3389/fgene.2024.1308527 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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