Dataset Information

De Novo Whole-Genome Assembly of the Swede Midge (Contarinia nasturtii), a Specialist of Brassicaceae, Using Linked-Read Sequencing.

ABSTRACT: The swede midge, Contarinia nasturtii, is a cecidomyiid fly that feeds specifically on plants within the Brassicaceae. Plants in this family employ a glucosinolate-myrosinase defense system, which can be highly toxic to nonspecialist feeders. Feeding by C. nasturtii larvae induces gall formation, which can cause substantial yield losses thus making it a significant agricultural pest. A lack of genomic resources, in particular a reference genome, has limited deciphering the mechanisms underlying glucosinolate tolerance in C. nasturtii, which is of particular importance for managing this species. Here, we present an annotated, scaffolded reference genome of C. nasturtii using linked-read sequencing from a single individual and explore systems involved in glucosinolate detoxification. The C. nasturtii genome is similar in size and annotation completeness to that of the Hessian fly, Mayetiola destructor, but has greater contiguity. Several genes encoding enzymes involved in glucosinolate detoxification in other insect pests, including myrosinases, sulfatases, and glutathione S-transferases, were found, suggesting that C. nasturtii has developed similar strategies for feeding on Brassicaceae. The C. nasturtii genome will, therefore, be integral to continued research on plant-insect interactions in this system and contribute to effective pest management strategies.

SUBMITTER: Mori BA

PROVIDER: S-EPMC8011032 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BACKGROUND: RNA-seq has shown huge potential for phylogenomic inferences in non-model organisms. However, error, incompleteness, and redundant assembled transcripts for each gene in de novo assembly of short reads cause noise in analyses and a large amount of missing data in the aligned matrix. To address these problems, we compare de novo assemblies of paired end 90 bp RNA-seq reads using Oases, Trinity, Trans-ABySS and SOAPdenovo-Trans to transcripts from genome annotation of the model plant Ricinus communis. By doing so we evaluate strategies for optimizing total gene coverage and minimizing assembly chimeras and redundancy. RESULTS: We found that the frequency and structure of chimeras vary dramatically among different software packages. The differences were largely due to the number of trans-self chimeras that contain repeats in the opposite direction. More than half of the total chimeras in Oases and Trinity were trans-self chimeras. Within each package, we found a trade-off between maximizing reference coverage and minimizing redundancy and chimera rate. In order to reduce redundancy, we investigated three methods: 1) using cap3 and CD-HIT-EST to combine highly similar transcripts, 2) only retaining the transcript with the highest read coverage, or removing the transcript with the lowest read coverage for each subcomponent in Trinity, and 3) filtering Oases single k-mer assemblies by number of transcripts per locus and relative transcript length, and then finding the transcript with the highest read coverage. We then utilized results from blastx against model protein sequences to effectively remove trans chimeras. After optimization, seven assembly strategies among all four packages successfully assembled 42.9-47.1% of reference genes to more than 200 bp, with a chimera rate of 0.92-2.21%, and on average 1.8-3.1 transcripts per reference gene assembled. CONCLUSIONS: With rapidly improving sequencing and assembly tools, our study provides a framework to benchmark and optimize performance before choosing tools or parameter combinations for analyzing short-read RNA-seq data. Our study demonstrates that choice of assembly package, k-mer sizes, post-assembly redundancy-reduction and chimera cleanup, and strand-specific RNA-seq library preparation and assembly dramatically improves gene coverage by non-redundant and non-chimeric transcripts that are optimized for downstream phylogenomic analyses.

Dataset Information

De Novo Whole-Genome Assembly of the Swede Midge (Contarinia nasturtii), a Specialist of Brassicaceae, Using Linked-Read Sequencing.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets