Characterization of Dendrolimus houi Lajonquiere (Lepidoptera: Lasiocampidae) Transcriptome across All Life Stages.
Xiaohong HanCiding LuScott M GeibJunxian ZhengSongqing WuFeiping ZhangGuanghong LiangPublished in: Insects (2019)
Dendrolimus houi Lajonquiere is a phytophagous caterpillar infesting many economically important coniferous tree species in China, causing serious economic and ecological environment losses. Based on previous research, it has one generation per year in South China and East China in contrast to two generations per year in Yunnan province in southwestern China. The species is potentially resilient to climatic extremes in these regions with the eggs and 1st instar larvae surviving in the winter (5 °C), older instar larvae and pupae surviving high temperatures in the summer (35 °C), suggesting some temperature stress tolerance during different developmental stages. However, little is known in this species at the genetic and genomic level. In this study, we used high throughput sequencing to obtain transcriptome data from different developmental stages (eggs, 1st-3rd instar larvae, 4th-5th instar larvae, 6th-7th instar larvae, pupae, male and female adults), which were collected from Fujian province. In total, we obtained approximately 90 Gb of data, from which 33,720 unigenes were assembled and 17,797 unigenes were annotated. We furtherly analyzed the differentially expressed genes (DGEs) across all stages, the largest number between the eggs and 1st instar larvae stage and gene expression varied significantly in different developmental stages. Furthermore, 4138 SSR genes and 114,977 SNP loci were screened from transcriptome data. This paper will be a foundation for further study towards improved integrated pest management strategies for this species.
Keyphrases
- genome wide
- gene expression
- aedes aegypti
- dna methylation
- drosophila melanogaster
- genetic diversity
- electronic health record
- single cell
- rna seq
- south africa
- big data
- high throughput sequencing
- magnetic resonance
- zika virus
- heat stress
- risk assessment
- machine learning
- bioinformatics analysis
- genome wide identification
- genome wide association study
- genome wide association