Haplotype-resolved genome assembly enables gene discovery in the red palm weevil Rhynchophorus ferrugineus.
Guilherme Borges DiasMusaad A AltammamiHamadttu A F El-ShafieFahad M AlhoshaniMohamed B Al-FageehCasey M BergmanManee M ManeePublished in: Scientific reports (2021)
The red palm weevil Rhynchophorus ferrugineus (Coleoptera: Curculionidae) is an economically-important invasive species that attacks multiple species of palm trees around the world. A better understanding of gene content and function in R. ferrugineus has the potential to inform pest control strategies and thereby mitigate economic and biodiversity losses caused by this species. Using 10x Genomics linked-read sequencing, we produced a haplotype-resolved diploid genome assembly for R. ferrugineus from a single heterozygous individual with modest sequencing coverage ([Formula: see text] 62x). Benchmarking against conserved single-copy Arthropod orthologs suggests both pseudo-haplotypes in our R. ferrugineus genome assembly are highly complete with respect to gene content, and do not suffer from haplotype-induced duplication artifacts present in a recently published hybrid assembly for this species. Annotation of the larger pseudo-haplotype in our assembly provides evidence for 23,413 protein-coding loci in R. ferrugineus, including over 13,000 predicted proteins annotated with Gene Ontology terms and over 6000 loci independently supported by high-quality Iso-Seq transcriptomic data. Our assembly also includes 95% of R. ferrugineus chemosensory, detoxification and neuropeptide-related transcripts identified previously using RNA-seq transcriptomic data, and provides a platform for the molecular analysis of these and other functionally-relevant genes that can help guide management of this widespread insect pest.
Keyphrases
- genome wide
- single cell
- rna seq
- dna methylation
- copy number
- high throughput
- genome wide identification
- transcription factor
- genetic diversity
- magnetic resonance
- healthcare
- electronic health record
- gene expression
- systematic review
- high glucose
- risk assessment
- single molecule
- genome wide analysis
- climate change
- drug induced
- data analysis
- endothelial cells
- machine learning