Search bioRxiv⌕ Search

bioRxiv · 10.1101/702613

Tree Lab: Portable genomics for early detection of plant viruses and pests in Sub-Saharan Africa

Abstract

In this case study we successfully teamed the PDQeX DNA purification technology developed by MicroGEM, New Zealand, with the MinION and MinIT mobile sequencing devices developed by Oxford Nanopore Technologies to produce an effective point-of-need field diagnostic system. The PDQeX extracts DNA using a cocktail of thermophilic proteinases and cell wall degrading enzymes, thermo-responsive extractor cartridges and a temperature control unit. This single-step closed system delivers purified DNA with no cross contamination. The MinIT is a newly released data processing unit that converts MinION raw signal output into base called data locally in real time, removing the need for high specification computers and large file transfers from the field. All three devices are battery powered with an exceptionally small footprint that facilitates transport and set up.\n\nTo evaluate and validate capability of the system for unbiased pathogen identification by realtime sequencing in a farmers field setting, we analysed samples collected from cassava plants grown by subsistence farmers in three sub-Sahara African countries (Tanzania, Uganda and Kenya). A range of viral pathogens, all with similar symptoms, greatly reduce yield or completely destroy cassava crops. 800 million people worldwide depend on cassava for food and yearly income, and viral diseases are a significant constraint on its production (https://cassavavirusactionproject.com). Early pathogen detection at a molecular level has great potential to rescue crops within a single growing season by providing results that inform decisions on disease management, use of appropriate virus resistant or replacement planting.\n\nThis case study presented conditions of working in-field with limited or no access to mains power, laboratory infrastructure, internet connectivity and highly variable ambient temperature. An additional challenge is that, generally, plant material contains inhibitors of downstream molecular processes making effective DNA purification critical. We successfully undertook real-time on-farm genome sequencing of samples collected from cassava plants on three farms, one in each country. Cassava mosaic begomoviruses were detected by sequencing leaf, stem, tuber and insect samples. The entire process, from arrival on farm to diagnosis including sample collection, processing and provisional sequencing results was complete in under 4 hours. The need for accurate, rapid and on-site diagnosis grows as globalized human activity accelerates. This technical breakthrough has applications that are relevant to human and animal health, environmental management and conservation.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Boykin, L. M., Sseruwagi, P., Alicai, T., Ateka, E., Mohammed, I. U., Stanton, J.-A., Kayuki, C., Mark, D., Fute, T., Erasto, J., Bachwenkizi, H., Muga, B., Mwangi, J., Mumo, N., Abidrabo, P., Okao-Okuja, G., Omuut, G., Akol, J., Apio, H. B., Osingada, F., Kehoe, M., Eccles, D., Savill, A., Lamb, S., Kinene, T., Rawle, C. B., Muralidhar, A., Mayall, K., Tairo, F., Ndunguru, J.. 2019-07-20. Tree Lab: Portable genomics for early detection of plant viruses and pests in Sub-Saharan Africa. https://doi.org/10.1101/702613

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

MicroDUET: a dual-headed genomic foundation model for pathogen surveillance

Pathogen genomic surveillance works from raw reads, assembled genomes and alignments, representations that are slow and costly to compare at scale. Compact embeddings from genomic language models offer an alternative, but surveillance requires resolving both evolutionary ancestry (phylogeny) and phenotypic capability (function) - which need not co-vary. Here we present MicroDUET, which adapts a 26.6-million-parameter ProkBERT backbone with two 3.5-million-parameter adapter heads: a phylogeny head trained contrastively on genome windows from the same microbes, and a function head trained to identify genes across taxa. On held-out retrieval benchmarks, the phylogeny head returned the correct species for 80.3% and 66.6% of cellular and viral queries, and the function head the correct gene family for 97.3% and 97.2%, reaching 74.4% accuracy on an independent antimicrobial resistance-class benchmark. Across all three benchmarks MicroDUET outranked 17 other genomic encoders. Without training on lineage, clade or drug-susceptibility tasks, MicroDUET identified Mycobacterium tuberculosis and mpox virus lineages and clades (0.965, 0.975 accuracy), discriminated rifampicin resistance without lineage adjustment (AUROC 0.985), and retrospectively identified an emerging mpox lineage as anomalous (AUROC 0.974). MicroDUET operates 10^3 - 10^4 times faster than single-threaded sequence-based alignments. MicroDUET therefore provides a compact, reusable representation for scalable pathogen surveillance and sequence triage.

genomics↗

A chromosome-level genome assembly of northern dragonhead, Dracocephalum ruyschiana L., 1753

We present a chromosome-level genome assembly for the vascular plant northern dragonhead, Dracocephalum ruyschiana. The assembly comprises two pseudo-haplotypes, hap1 and hap2, of 661 Mb and 681 Mb, with 93.6% and 92.5%, respectively, scaffolded into seven chromosomes each - in line with the known karyotype. Assembly quality was high, with conserved single-copy ortholog completeness scores of 97.9% and 97.8%, combined k-mer completeness of 98.1%, and 38,141 and 38,617 annotated protein-coding genes for hap1 and hap2, respectively. This assembly provides a high-quality genomic resource for future research and conservation of northern dragonhead, as well as the endangered northern dragonhead sap beetle, which depends on the plant for reproduction and whose genome assembly is described in a complementary genome note.

genomics↗

Elucidating Bat SuperImmunity: Insights from the Bent-Wing Bat Genome Assembly and Multi-Omics Analysis

Bats have evolved a range of unique adaptations, including powered flight, echolocation, and exceptional longevity. They have also attracted considerable scientific attention, particularly since the COVID-19 pandemic, due to their association with a broad diversity of viruses and their potential role in zoonotic transmission and emerging infectious diseases. Despite hosting numerous viruses, bats often exhibit limited clinical manifestations of infection, suggesting the evolution of distinctive mechanisms of immune regulation and tolerance. Understanding the molecular basis of these mechanisms has become a major focus of current research, with genome-wide analyses providing important insights into the genetic adaptations underlying bat immunity. Nevertheless, the regulatory complexity of bat genomes, particularly the contribution of non-coding RNAs and post-transcriptional RNA editing, remains comparatively underexplored. Here, we present an integrated multi-omic framework for the common bent-wing bat (Miniopterus schreibersii), combining a contiguous chromosome-scale genome assembly with multi-tissue transcriptomic profiling, long non-coding RNA (lncRNA) identification and synteny analysis, endogenous viral elements (EVE) mapping, and same-individual RNA editomic analyses. This study provides a comprehensive resource for investigating genome organization, transcriptional regulation, evolutionary relationships, and post-transcriptional modifications in this species. In particular, it offers an opportunity to explore the potential contribution of non-coding regulatory elements and RNA editing to the molecular mechanisms underlying viral interactions and immune regulation in bats. Collectively, these resources provide a valuable foundation for advancing our understanding of bat genome evolution and the regulatory mechanisms potentially associated with their distinctive responses to viral infections.

genomics↗