Medico, J. A. | Search bioRxiv

bioRxiv2025

The complete genome of a songbird

Bird genomes are the smallest among amniotes, but remain challenging to assemble due to their structural complexity. This study presents the first fully phased, diploid, telomere-to-telomere (T2T) reference genome for the zebra finch (Taeniopygia guttata), a model organism for neuroscience and evolutionary genomics. Combining multiple sequencing strategies resulted in closing nearly all gaps, adding [~]90 Mbp of previously missing sequence (7.8%). This includes T2T assemblies for all microchromosomes, including dot chromosomes, and the previously almost entirely missing chr16. The T2T genome is comprehensively annotated for genes, repeats, structural variants, and long-read methylation calls. Complete centromeric structures were assembled and annotated along with kinetochore binding sites. Relative to the previous high-quality reference of the Vertebrate Genomes Project, 2,778 (8.51%) previously unassembled or unannotated genes were identified, of which 9% overlap with segmental duplications. This first complete genome of a songbird, now the new public reference, illuminates avian genome architecture and function.

genomics↗

bioRxiv2025

Evaluation of sequencing reads at scale using rdeval

MotivationLarge sequencing data sets are produced and deposited into public archives at unprecedented rates. The availability of tools that can reliably and efficiently generate and store sequencing read summary statistics has become critical. ResultsAs part of the effort by the Vertebrate Genomes Project (VGP) to generate high-quality reference genomes at scale, we sought to address the community need for efficient sequencing data evaluation by developing rdeval, a standalone tool to quickly compute and dynamically display sequencing read metrics. Rdeval can either run on the fly or store key sequence data metrics in read sketches, with dramatic compression gains. Statistics can then be efficiently recalled from sketches for additional processing. Rdeval can convert fa*[.gz] files to and from other popular formats including BAM and CRAM for better compression. Overall, while CRAM achieves the best compression, the gain is marginal, and BAM achieves the best compromise between data compression and accessing speed. Rdeval also generates a detailed visual report with multiple data analytics that can be exported in various formats. We showcase rdevals functionalities using human and VGP read data from different sequencing platforms and species. For PacBio long-read sequencing, our analysis shows dramatic improvements both in read length and quality over time, and a benefit of additional coverage for genome assembly. Availability and implementationRdeval is implemented in C++ for data processivity and in R for data visualization. Precompiled releases (Linux, MacOS, Windows) and commented source code for rdeval are available under MIT license at https://github.com/vgl-hub/rdeval. Documentation is available using ReadTheDocs (https://rdeval-documentation.readthedocs.io). Rdeval is also available in Bioconda and in Galaxy (https://usegalaxy.org). An automated test workflow ensures the consistency of software updates. Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗