Contamination Survey of Insect Genomic and Transcriptomic Data
The rapid advancement of high-throughput sequencing has led to a great increase in sequencing data, resulting in a significant accumulation of contamination, for example, sequences from non-target species may be present in the target species’ sequencing data. Insecta, the most diverse group within A...
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MDPI AG
2024-11-01
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| Online Access: | https://www.mdpi.com/2076-2615/14/23/3432 |
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| author | Jiali Zhou Xinrui Zhang Yujie Wang Haoxian Liang Yuhao Yang Xiaolei Huang Jun Deng |
| author_facet | Jiali Zhou Xinrui Zhang Yujie Wang Haoxian Liang Yuhao Yang Xiaolei Huang Jun Deng |
| author_sort | Jiali Zhou |
| collection | DOAJ |
| description | The rapid advancement of high-throughput sequencing has led to a great increase in sequencing data, resulting in a significant accumulation of contamination, for example, sequences from non-target species may be present in the target species’ sequencing data. Insecta, the most diverse group within Arthropoda, still lacks a comprehensive evaluation of contamination prevalence in public databases and an analysis of potential contamination causes. In this study, COI barcodes were used to investigate contamination from insects and mammals in GenBank’s genomic and transcriptomic data across four insect orders. Among the 2796 WGS and 1382 TSA assemblies analyzed, contamination was detected in 32 (1.14%) WGS and 152 (11.0%) TSA assemblies. Key findings from this study include the following: (1) TSA data exhibited more severe contamination than WGS data; (2) contamination levels varied significantly among the four orders, with Hemiptera showing 9.22%, Coleoptera 3.48%, Hymenoptera 7.66%, and Diptera 1.89% contamination rates; (3) possible causes of contamination, such as food, parasitism, sample collection, and cross-contamination, were analyzed. Overall, this study proposes a workflow for checking the existence of contamination in WGS and TSA data and some suggestions to mitigate it. |
| format | Article |
| id | doaj-art-948a6b3ea5f64e5e9fdf4d50afe0dce9 |
| institution | OA Journals |
| issn | 2076-2615 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
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| series | Animals |
| spelling | doaj-art-948a6b3ea5f64e5e9fdf4d50afe0dce92025-08-20T01:55:34ZengMDPI AGAnimals2076-26152024-11-011423343210.3390/ani14233432Contamination Survey of Insect Genomic and Transcriptomic DataJiali Zhou0Xinrui Zhang1Yujie Wang2Haoxian Liang3Yuhao Yang4Xiaolei Huang5Jun Deng6State Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, College of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou 350002, ChinaState Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, College of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou 350002, ChinaState Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, College of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou 350002, ChinaState Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, College of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou 350002, ChinaState Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, College of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou 350002, ChinaState Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, College of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou 350002, ChinaState Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, College of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou 350002, ChinaThe rapid advancement of high-throughput sequencing has led to a great increase in sequencing data, resulting in a significant accumulation of contamination, for example, sequences from non-target species may be present in the target species’ sequencing data. Insecta, the most diverse group within Arthropoda, still lacks a comprehensive evaluation of contamination prevalence in public databases and an analysis of potential contamination causes. In this study, COI barcodes were used to investigate contamination from insects and mammals in GenBank’s genomic and transcriptomic data across four insect orders. Among the 2796 WGS and 1382 TSA assemblies analyzed, contamination was detected in 32 (1.14%) WGS and 152 (11.0%) TSA assemblies. Key findings from this study include the following: (1) TSA data exhibited more severe contamination than WGS data; (2) contamination levels varied significantly among the four orders, with Hemiptera showing 9.22%, Coleoptera 3.48%, Hymenoptera 7.66%, and Diptera 1.89% contamination rates; (3) possible causes of contamination, such as food, parasitism, sample collection, and cross-contamination, were analyzed. Overall, this study proposes a workflow for checking the existence of contamination in WGS and TSA data and some suggestions to mitigate it.https://www.mdpi.com/2076-2615/14/23/3432contaminationgenomic/transcriptomic databaseInsectaCOI barcodingsource |
| spellingShingle | Jiali Zhou Xinrui Zhang Yujie Wang Haoxian Liang Yuhao Yang Xiaolei Huang Jun Deng Contamination Survey of Insect Genomic and Transcriptomic Data Animals contamination genomic/transcriptomic database Insecta COI barcoding source |
| title | Contamination Survey of Insect Genomic and Transcriptomic Data |
| title_full | Contamination Survey of Insect Genomic and Transcriptomic Data |
| title_fullStr | Contamination Survey of Insect Genomic and Transcriptomic Data |
| title_full_unstemmed | Contamination Survey of Insect Genomic and Transcriptomic Data |
| title_short | Contamination Survey of Insect Genomic and Transcriptomic Data |
| title_sort | contamination survey of insect genomic and transcriptomic data |
| topic | contamination genomic/transcriptomic database Insecta COI barcoding source |
| url | https://www.mdpi.com/2076-2615/14/23/3432 |
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