Biology subjects

Abueg, L.

Publications and source records attributed to Abueg, L..

4 recordsLinked to original sources

bioRxiv2023

Scalable, accessible, and reproducible reference genome assembly and evaluation in Galaxy

Improvements in genome sequencing and assembly are enabling high-quality reference genomes for all species. However, the assembly process is still laborious, computationally and technically demanding, lacks standards for reproducibility, and is not readily scalable. Here we present the latest Vertebrate Genomes Project assembly pipeline and demonstrate that it delivers high-quality reference genomes at scale across a set of vertebrate species arising over the last [~]500 million years. The pipeline is versatile and combines PacBio HiFi long-reads and Hi-C-based haplotype phasing in a new graph-based paradigm. Standardized quality control is performed automatically to troubleshoot assembly issues and assess biological complexities. We make the pipeline freely accessible through Galaxy, accommodating researchers even without local computational resources and enhanced reproducibility by democratizing the training and assembly process. We demonstrate the flexibility and reliability of the pipeline by assembling reference genomes for 51 vertebrate species from major taxonomic groups (fish, amphibians, reptiles, birds, and mammals).

bioinformatics↗

bioRxiv2022

MitoHiFi: a python pipeline for mitochondrial genome assembly from PacBio High Fidelity reads

BackgroundPacBio high fidelity (HiFi) sequencing reads are both long (15-20 kb) and highly accurate (>Q20). Because of these properties, they have revolutionised genome assembly leading to more accurate and contiguous genomes. In eukaryotes the mitochondrial genome is sequenced alongside the nuclear genome often at very high coverage. A dedicated tool for mitochondrial genome assembly using HiFi reads is still missing. ResultsMitoHiFi was developed within the Darwin Tree of Life Project to assemble mitochondrial genomes from the HiFi reads generated for target species. The input for MitoHiFi is either the raw reads or the assembled contigs, and the tool outputs a mitochondrial genome sequence fasta file along with annotation of protein and RNA genes. Variants arising from heteroplasmy are assembled independently, and nuclear insertions of mitochondrial sequences are identified and not used in organellar genome assembly. MitoHiFi has been used to assemble 374 mitochondrial genomes (369 from 12 phyla and 39 orders of Metazoa and from 6 species of Fungi) for the Darwin Tree of Life Project, the Vertebrate Genomes Project and the Aquatic Symbiosis Genome Project. Inspection of 60 mitochondrial genomes assembled with MitoHiFi for species that already have reference sequences in public databases showed the widespread presence of previously unreported repeats. ConclusionsMitoHiFi is able to assemble mitochondrial genomes from a wide phylogenetic range of taxa from Pacbio HiFi data. MitoHiFi is written in python and is freely available on github (https://github.com/marcelauliano/MitoHiFi). MitoHiFi is available with its dependencies as a singularity image on github (ghcr.io/marcelauliano/mitohifi:master).

bioinformatics↗

bioRxiv2022

Pangenomics provides insights into the role of synanthropy in barn swallow evolution

Insights into the evolution of non-model organisms are often limited by the lack of reference genomes. As part of the Vertebrate Genomes Project, we present a new reference genome and a pangenome produced with High-Fidelity long reads for the barn swallow Hirundo rustica. We then generated a reference-free multialignment with other bird genomes to identify genes under selection. Conservation analyses pointed at genes enriched for transcriptional regulation and neurodevelopment. The most conserved gene is CAMK2N2, with a potential role in fear memory formation. In addition, using all publicly available data, we generated a comprehensive catalogue of genetic markers. Genome-wide linkage disequilibrium scans identified potential selection signatures at multiple loci. The top candidate region comprises several genes and includes BDNF, a gene involved in stress response, fear memory formation, and tameness. We propose that the strict association with humans in this species is linked with the evolution of pathways typically under selection in domesticated taxa.

genomics↗

bioRxiv2022

Gfastats: conversion, evaluation and manipulation of genome sequences using assembly graphs

MotivationWith the current pace at which reference genomes are being produced, the availability of tools that can reliably and efficiently generate genome assembly summary statistics has become critical. Additionally, with the emergence of new algorithms and data types, tools that can improve the quality of existing assemblies through automated and manual curation are required. ResultsWe sought to address both these needs by developing gfastats, as part of the Vertebrate Genomes Project (VGP) effort to generate high-quality reference genomes at scale. Gfastats is a standalone tool to compute assembly summary statistics and manipulate assembly sequences in fasta, fastq, or gfa [.gz] format. Gfastats stores assembly sequences internally in a gfa-like format. This feature allows gfastats to seamlessly convert fast* to and from gfa [.gz] files. Gfastats can also build an assembly graph that can in turn be used to manipulate the underlying sequences following instructions provided by the user, while simultaneously generating key metrics for the new sequences. Availability and implementationGfastats is implemented in C++. Precompiled releases (Linux, MacOS, Windows) and commented source code for gfastats are available under MIT license at https://github.com/vgl-hub/gfastats. Examples of how to run gfastats are provided in the Github. Gfastats is also available in Bioconda, in Galaxy (https://assembly.usegalaxy.eu) and as a MultiQC module [1] (https://github.com/ewels/MultiQC). An automated test workflow is available to ensure consistency of software updates. Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗