Dataset Information

HiFiAdapterFilt, a memory efficient read processing pipeline, prevents occurrence of adapter sequence in PacBio HiFi reads and their negative impacts on genome assembly.

ABSTRACT:

Background

Pacific Biosciences HiFi read technology is currently the industry standard for high accuracy long-read sequencing that has been widely adopted by large sequencing and assembly initiatives for generation of de novo assemblies in non-model organisms. Though adapter contamination filtering is routine in traditional short-read analysis pipelines, it has not been widely adopted for HiFi workflows.

Results

Analysis of 55 publicly available HiFi datasets revealed that a read-sanitation step to remove sequence artifacts derived from PacBio library preparation from read pools is necessary as adapter sequences can be erroneously integrated into assemblies.

Conclusions

Here we describe the nature of adapter contaminated reads, their consequences in assembly, and present HiFiAdapterFilt, a simple and memory efficient solution for removing adapter contaminated reads prior to assembly.

SUBMITTER: Sim SB

PROVIDER: S-EPMC8864876 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

HiFiAdapterFilt, a memory efficient read processing pipeline, prevents occurrence of adapter sequence in PacBio HiFi reads and their negative impacts on genome assembly.

Sim Sheina B SB Corpuz Renee L RL Simmonds Tyler J TJ Geib Scott M SM

BMC genomics 20220222 1

<h4>Background</h4>Pacific Biosciences HiFi read technology is currently the industry standard for high accuracy long-read sequencing that has been widely adopted by large sequencing and assembly initiatives for generation of de novo assemblies in non-model organisms. Though adapter contamination filtering is routine in traditional short-read analysis pipelines, it has not been widely adopted for HiFi workflows.<h4>Results</h4>Analysis of 55 publicly available HiFi datasets revealed that a read- ...[more]

PMID: 35193521

Similar Datasets

Project description:BackgroundMicrobes produce diverse bioactive natural products with applications in fields such as medicine and agriculture. In their genomes, these natural products are encoded by physically clustered genes known as biosynthetic gene clusters (BGCs). Genome and metagenome sequencing advances have enabled high-throughput identification of BGCs as a promising avenue for natural product discovery. BGC mining from (meta)genomes using in silico tools has allowed access to a vast diversity of potentially novel natural products. However, a fundamental limitation has been the ability to assemble complete BGCs, especially from complex metagenomes. With their fragmented assemblies, short-read technologies struggle to recover complete BGCs, such as the long and repetitive nonribosomal peptide synthetase (NRPS) and polyketide synthase (PKS). Recent advances in long-read sequencing, such as the High Fidelity (HiFi) technology from PacBio, have reduced this limitation and can help retrieve both accurate and complete BGCs from metagenomes, warranting improvement in the existing BGC identification approach for better utilization of HiFi data.ResultsHere, we present HiFiBGC, a command-line-based workflow to identify BGCs in PacBio HiFi metagenomes. HiFiBGC leverages an ensemble of assemblies from three HiFi-tailored metagenome assemblers and the reads not represented in these assemblies. Based on our analyses of four HiFi metagenomic datasets from four different environments, we show that HiFiBGC identifies, on average, 78% more BGCs than the top-performing single-assembler-based method. This increase is due to HiFiBGC's ensemble assembly approach, which improves recovery by 25%, as well as from the inclusion of mostly fragmented BGCs identified in the unmapped reads.ConclusionsHiFiBGC is a computational workflow for identifying BGCs in long-read HiFi metagenomes, implemented majorly using Python programming language and workflow manager Snakemake. HiFiBGC is available on GitHub at https://github.com/ay-amityadav/HiFiBGC under the MIT license. The code related to the figures and analyses presented in the manuscript is available at https://github.com/ay-amityadav/HiFiBGC_analyses .

Dataset Information

HiFiAdapterFilt, a memory efficient read processing pipeline, prevents occurrence of adapter sequence in PacBio HiFi reads and their negative impacts on genome assembly.

Background

Results

Conclusions

Publications

HiFiAdapterFilt, a memory efficient read processing pipeline, prevents occurrence of adapter sequence in PacBio HiFi reads and their negative impacts on genome assembly.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets