Annotation and analysis of yellow genes in Asian citrus psyllid, Diaphorina citri, vector for the Huanglongbing disease
Massimino, C.; Vosburg, C.; Shippy, T.; Hosmani, P. S.; Flores-Gonzalez, M.; Mueller, L. A.; Hunter, W. B.; Benoit, J. B.; Brown, S. J.; D'elia, T.; Saha, S.
Show abstract
Huanglongbing (HLB), also known as citrus greening disease, is caused by the bacterium Candidatus Liberibacter asiaticus (CLas) and represents a serious threat to global citrus production. This bacteria is transmitted by the Asian citrus psyllid, Diaphorina citri (Hemiptera) and there are no effective in-planta treatments for CLas. Therefore, one strategy is to manage the psyllid population. Manual annotation of the D. citri genome can identify and characterize gene families that could serve as novel targets for psyllid control. The yellow gene family represents an excellent target as yellow genes are linked to development and immunity due to their roles in melanization. Combined analysis of the genome with RNA-seq datasets, sequence homology, and phylogenetic trees were used to identify and annotate nine yellow genes for the D. citri genome. Phylogenetic analysis shows a unique duplication of yellow-y in D. citri, with life stage specific expression for these two genes. Genomic analysis also indicated the loss of a gene vital to the process of melanization, yellow-f, and the gain of a gene which seems to be unique to hemipterans, yellow 9. We suggest that yellow 9 or the gene yellow 8 (c), which consistently groups closely to yellow-f, may take on this role. Manual curation of genes in D. citri has provided an in-depth analysis of the yellow family among hemipteran insects and provides new targets for molecular control of this psyllid pest. Manual annotation was done as part of a collaborative community annotation project (https://citrusgreening.org/annotation/index).
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Annotation of glycolysis, gluconeogenesis, and trehaloneogenesis pathways provide insight into carbohydrate metabolism in the Asian citrus psyllid 98%
- Manual curation and phylogenetic analysis of chitinase family genes in the Asian citrus psyllid, Diaphorina citri 98%
- Segmentation pathway genes in the Asian citrus psyllid, Diaphorina citri 97%
Similar papers in this journal
- Meta-analysis of transcriptomes in insects showing density-dependent polyphenism 95%
- Real-time feeding behavior monitoring by electrical penetration graph rapidly reveals host plant susceptibility to crapemyrtle bark scale (Hemiptera: Eriococcidae) 95%
- Reference genome sequences of the oriental armyworm, Myth-imna separata (Lepidoptera: Noctuidae) 94%
Similar papers in this journal
- Amplitude of circadian rhythms becomes weaker in the north, but there is no cline in the period of rhythm in a beetle 95%
- BIN overlap confirms transcontinental distribution of pest aphids (Hemiptera: Aphididae) 95%
- Expression of a gene for an MLX56 defense protein derived from mulberry latex confers strong resistance against a broad range of insect pests on transgenic tomato lines 95%
Similar papers in this journal
- The cys-loop ligand-gated ion channel gene superfamily of the Colorado potato beetle, Leptinotarsa decemlineata 96%
- Integration of transcriptomics and network analysis reveals co-expressed genes in Frankliniella occidentalis larval guts that respond to tomato spotted wilt virus infection 93%
- A toolkit for studying Varroa genomics and transcriptomics: Preservation, extraction, and sequencing library preparation 92%
Similar papers in this journal
- Population dynamics of fruit flies (Diptera: Tephritidae) in a semirural area under subtropical monsoon climate of Bangladesh 94%
- Sugar-feeding by invasive mosquito species on ornamental and wild plants 93%
- Comparative morphological and transcriptomic analyses reveal novel chemosensory genes in the poultry red mite, Dermanyssus gallinae and knockdown by RNA interference 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.