Standard

RNA-Seq contamination as a metatranscriptomic data for screening of plant pests and symbionts. / Зыкин, Павел Александрович; Андреева, Елена Александровна; Цветкова, Наталья Владимировна; Буланов, Андрей Николаевич; Войлоков, Анатолий Васильевич.

в: Ecological Genetics, 30.09.2025.

Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование

Harvard

Зыкин, ПА, Андреева, ЕА, Цветкова, НВ, Буланов, АН & Войлоков, АВ 2025, 'RNA-Seq contamination as a metatranscriptomic data for screening of plant pests and symbionts', Ecological Genetics. https://doi.org/10.17816/ecogen642484

APA

Зыкин, П. А., Андреева, Е. А., Цветкова, Н. В., Буланов, А. Н., & Войлоков, А. В. (2025). RNA-Seq contamination as a metatranscriptomic data for screening of plant pests and symbionts. Ecological Genetics, [642484]. https://doi.org/10.17816/ecogen642484

Vancouver

Зыкин ПА, Андреева ЕА, Цветкова НВ, Буланов АН, Войлоков АВ. RNA-Seq contamination as a metatranscriptomic data for screening of plant pests and symbionts. Ecological Genetics. 2025 Сент. 30. 642484. https://doi.org/10.17816/ecogen642484

Author

Зыкин, Павел Александрович ; Андреева, Елена Александровна ; Цветкова, Наталья Владимировна ; Буланов, Андрей Николаевич ; Войлоков, Анатолий Васильевич. / RNA-Seq contamination as a metatranscriptomic data for screening of plant pests and symbionts. в: Ecological Genetics. 2025.

BibTeX

@article{0cff3531c7d84a299953057811121462,
title = "RNA-Seq contamination as a metatranscriptomic data for screening of plant pests and symbionts",
abstract = "Background: Transcriptome sequencing data can contain up to 30% contaminating reads. These may originate from laboratory contamination or biologically relevant sources, amenable to metatranscriptomics analysis. Aim: to evaluate the utility of contaminating reads for large-scale screening of plant pests and symbionts.Materials and methods: We analyzed the data of RNA-seq experiments of rye (Secale cereale L.) including five in-house accessions and 50 public datasets from NCBI SRA archive. Reads with good mapping to the rye genome were filtered out, retaining putative contaminats for downstream analysis.Results: After removing laboratory contaminants, we compared aphids, symbiotic fungi, bacteria and viruses across accessions. Symbiome-derived reads were reproducible in biological replicates and varied by location, condition, and plant species, enabling post-hoc metatranscriptomic analysis.Conclusion: Contaminating reads correlated with field-observed species or expected symbionts. Distribution patterns across accessions support repurposing existing and future sequencing data to screen for plant pests, monitor symbiotic organisms, and plan eradication strategies amid global climate change.",
author = "Зыкин, {Павел Александрович} and Андреева, {Елена Александровна} and Цветкова, {Наталья Владимировна} and Буланов, {Андрей Николаевич} and Войлоков, {Анатолий Васильевич}",
year = "2025",
month = sep,
day = "30",
doi = "10.17816/ecogen642484",
language = "English",
journal = "ЭКОЛОГИЧЕСКАЯ ГЕНЕТИКА",
issn = "1811-0932",
publisher = "Эко-Вектор",

}

RIS

TY - JOUR

T1 - RNA-Seq contamination as a metatranscriptomic data for screening of plant pests and symbionts

AU - Зыкин, Павел Александрович

AU - Андреева, Елена Александровна

AU - Цветкова, Наталья Владимировна

AU - Буланов, Андрей Николаевич

AU - Войлоков, Анатолий Васильевич

PY - 2025/9/30

Y1 - 2025/9/30

N2 - Background: Transcriptome sequencing data can contain up to 30% contaminating reads. These may originate from laboratory contamination or biologically relevant sources, amenable to metatranscriptomics analysis. Aim: to evaluate the utility of contaminating reads for large-scale screening of plant pests and symbionts.Materials and methods: We analyzed the data of RNA-seq experiments of rye (Secale cereale L.) including five in-house accessions and 50 public datasets from NCBI SRA archive. Reads with good mapping to the rye genome were filtered out, retaining putative contaminats for downstream analysis.Results: After removing laboratory contaminants, we compared aphids, symbiotic fungi, bacteria and viruses across accessions. Symbiome-derived reads were reproducible in biological replicates and varied by location, condition, and plant species, enabling post-hoc metatranscriptomic analysis.Conclusion: Contaminating reads correlated with field-observed species or expected symbionts. Distribution patterns across accessions support repurposing existing and future sequencing data to screen for plant pests, monitor symbiotic organisms, and plan eradication strategies amid global climate change.

AB - Background: Transcriptome sequencing data can contain up to 30% contaminating reads. These may originate from laboratory contamination or biologically relevant sources, amenable to metatranscriptomics analysis. Aim: to evaluate the utility of contaminating reads for large-scale screening of plant pests and symbionts.Materials and methods: We analyzed the data of RNA-seq experiments of rye (Secale cereale L.) including five in-house accessions and 50 public datasets from NCBI SRA archive. Reads with good mapping to the rye genome were filtered out, retaining putative contaminats for downstream analysis.Results: After removing laboratory contaminants, we compared aphids, symbiotic fungi, bacteria and viruses across accessions. Symbiome-derived reads were reproducible in biological replicates and varied by location, condition, and plant species, enabling post-hoc metatranscriptomic analysis.Conclusion: Contaminating reads correlated with field-observed species or expected symbionts. Distribution patterns across accessions support repurposing existing and future sequencing data to screen for plant pests, monitor symbiotic organisms, and plan eradication strategies amid global climate change.

UR - https://journals.eco-vector.com/ecolgenet/article/view/642484

U2 - 10.17816/ecogen642484

DO - 10.17816/ecogen642484

M3 - Article

JO - ЭКОЛОГИЧЕСКАЯ ГЕНЕТИКА

JF - ЭКОЛОГИЧЕСКАЯ ГЕНЕТИКА

SN - 1811-0932

M1 - 642484

ER -

ID: 141749582