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Biology subjects

Amos, T. G.

Publications and source records attributed to Amos, T. G..

3 recordsLinked to original sources

Mitochondrial genome analyses uncover intriguing population structure across the invasive trajectory of an iconic invader

Invasive species offer insights into rapid adaptations in novel environments. The iconic cane toad (Rhinella marina) is an excellent model for studying rapid adaptation during invasion. Previous research using the mitochondrial NADH dehydrogenase 3 (ND3) gene in the Hawaiian and Australian invasive populations found a single haplotype, indicating an extreme genetic bottleneck following introduction. Nuclear genetic diversity also exhibited reductions across the genome in these two populations. Here, we investigated the mitochondrial genome diversity of cane toads across this invasion trajectory. We created the first reference mitochondrial genome of the cane toad with long-read sequencing and constructed a phylogeny of Anura full mitochondrial genomes. We used transcriptomic data of 125 individuals from the native (French Guiana) and introduced (Hawaii and Australia) ranges to construct nearly-complete mitochondrial genomes for population genomics analyses. As expected, the cane toad belongs to family Bufonidae, distinct from genus Bufo. In agreement with previous investigations of these populations, we identified genetic bottlenecks in both Hawaiian and Australian introduced populations, alongside evidence of population expansion in the invasive ranges. Although mitochondrial genetic diversity in introduced populations was reduced, our results revealed that it had been underestimated: we identified 45 mitochondrial haplotypes in Hawaiian and Australian samples, none of which were found in the native range. Additionally, we identified two distinct groups of haplotypes from the native range, separated by a minimum of 110 base pairs (0.6%). These findings enhance our understanding of Anura phylogenetics and how invasion has shaped the genetic landscape of this species.

genomics↗

Flexible and efficient handling of nanopore sequencing signal data with slow5tools

BackgroundNanopore sequencing is an emerging technology that is being rapidly adopted in research and clinical genomics. We recently developed SLOW5, a new file format for storage and analysis of raw data from nanopore sequencing experiments. SLOW5 is a community-centric, open source format that offers considerable performance benefits over the existing nanopore data format, known as FAST5. Here we introduce slow5tools, a simple, intuitive toolkit for handling nanopore raw signal data in SLOW5 format. ResultsSlow5tools enables lossless FAST5-to-SLOW5 and SLOW5-to-FAST5 data conversion, and a range of tools for structuring, indexing, viewing and querying SLOW5 files. Slow5tools uses multi-threading, multi-processing and other engineering strategies to achieve fast data conversion and manipulation, including live FAST5-to-SLOW5 conversion during sequencing. We outline a series of examples and benchmarking experiments to illustrate slow5tools usage, and describe the engineering principles underpinning its high performance. ConclusionSlow5tools is an essential toolkit for handling nanopore signal data, which was developed to support adoption of SLOW5 by the nanopore community. Slow5tools is written in C/C++ with minimal dependencies and is freely available as an open-source program under an MIT licence: https://github.com/hasindu2008/slow5tools.

bioinformatics↗

SLOW5: a new file format enables massive acceleration of nanopore sequencing data analysis

Nanopore sequencing is an emerging genomic technology with great potential. However, the storage and analysis of nanopore sequencing data have become major bottlenecks preventing more widespread adoption in research and clinical genomics. Here, we elucidate an inherent limitation in the file format used to store raw nanopore data - known as FAST5 - that prevents efficient analysis on high-performance computing (HPC) systems. To overcome this, we have developed SLOW5, an alternative file format that permits efficient parallelisation and, thereby, acceleration of nanopore data analysis. For example, we show that using SLOW5 format, instead of FAST5, reduces the time and cost of genome-wide DNA methylation profiling by an order of magnitude on common HPC systems, and delivers consistent improvements on a wide range of different architectures. With a simple, accessible file structure and a ~25% reduction in size compared to FAST5, SLOW5 format will deliver substantial benefits to all areas of the nanopore community.

genomics↗