Literature DB >> 31518402

Genome sequence of the Chinese white wax scale insect Ericerus pela: the first draft genome for the Coccidae family of scale insects.

Pu Yang1, Shuhui Yu2, Junjun Hao3, Wei Liu1, Zunling Zhao1, Zengrong Zhu4, Tao Sun1, Xueqing Wang1, Qisheng Song5.   

Abstract

BACKGROUND: The Chinese white wax scale insect, Ericerus pela, is best known for producing wax, which has been widely used in candle production, casting, Chinese medicine, and wax printing products for thousands of years. The secretion of wax, and other unusual features of scale insects, is thought to be an adaptation to their change from an ancestral ground-dwelling lifestyle to a sedentary lifestyle on the higher parts of plants. As well as helping to improve its economic value, studies of E. pela might also help to explain the adaptation of scale insects. However, no genomic data are currently available for E. pela.
FINDINGS: To assemble the E. pela genome, 303.92 Gb of data were generated using Illumina and Pacific Biosciences sequencing, producing 277.22 Gb of clean data for assembly. The assembled genome size was 0.66 Gb, with 1,979 scaffolds and a scaffold N50 of 735 kb. The guanine + cytosine content was 33.80%. A total of 12,022 protein-coding genes were predicted, with a mean coding sequence length of 1,370 bp. Twenty-six fatty acyl-CoA reductase genes and 35 acyltransferase genes were identified. Evolutionary analysis revealed that E. pela and aphids formed a sister group and split ∼241.1 million years ago. There were 214 expanded gene families and 2,219 contracted gene families in E. pela.
CONCLUSION: We present the first genome sequence from the Coccidae family. These results will help to increase our understanding of the evolution of unique features in scale insects, and provide important genetic information for further research.
© The Author(s) 2019. Published by Oxford University Press.

Entities:  

Keywords:  zzm321990 Ericerus pelazzm321990 ; Chinese white wax scale insect; adaptation; genome; wax secretion

Year:  2019        PMID: 31518402      PMCID: PMC6743827          DOI: 10.1093/gigascience/giz113

Source DB:  PubMed          Journal:  Gigascience        ISSN: 2047-217X            Impact factor:   6.524


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