Mottle: Accurate pairwise substitution distance at high divergence through the exploitation of short-read mappers and gradient descent

Current tools for estimating the substitution distance between two related sequences struggle to remain accurate at a high divergence. Difficulties at distant homologies, such as false seeding and over-alignment, create a high barrier for the development of a stable estimator. This is especially true for viral genomes, which carry a high rate of mutation, small size, and sparse taxonomy. Developing an accurate substitution distance measure would help to elucidate the relationship between highly divergent sequences, interrogate their evolutionary history, and better facilitate the discovery of new viral genomes. To tackle these problems, we propose an approach that uses short-read mappers to create whole-genome maps, and gradient descent to isolate the homologous fraction and calculate the final distance value. We implement this approach as Mottle. With the use of simulated and biological sequences, Mottle was able to remain stable to 0.66–0.96 substitutions per base pair and identify viral outgroup genomes with 95% accuracy at the family-order level. Our results indicate that Mottle performs as well as existing programs in identifying taxonomic relationships, with more accurate numerical estimation of genomic distance over greater divergences. By contrast, one limitation is a reduced numerical accuracy at low divergences, and on genomes where insertions and deletions are uncommon, when compared to alternative approaches. We propose that Mottle may therefore be of particular interest in the study of viruses, viral relationships, and notably for viral discovery platforms, helping in benchmarking of homology search tools and defining the limits of taxonomic classification methods. The code for Mottle is available at https://github.com/tphoward/Mottle_Repo

Monitoring root rot in flat-leaf parsley via machine vision by unsupervised multivariate analysis of morphometric and spectral parameters

\ua9 The Author(s) 2024.Use of vertical farms is increasing rapidly as it enables year-round crop production, made possible by fully controlled growing environments situated within supply chains. However, intensive planting and high relative humidity make such systems ideal for the proliferation of fungal pathogens. Thus, despite the use of bio-fungicides and enhanced biosecurity measures, contamination of crops does happen, leading to extensive crop loss, necessitating the use of high-throughput monitoring for early detection of infected plants. In the present study, progression of foliar symptoms caused by Pythium irregulare-induced root rot was monitored for flat-leaf parsley grown in an experimental hydroponic vertical farming setup. Structural and spectral changes in plant canopy were recorded non-invasively at regular intervals using a 3D multispectral scanner. Five morphometric and nine spectral features were selected, and different combinations of these features were subjected to multivariate data analysis via principal component analysis to identify temporal trends for early segregation of healthy and infected samples. Combining morphometric and spectral features enabled a clear distinction between healthy and diseased plants at 4–7 days post inoculation (DPI), whereas use of only morphometric or spectral features allowed this at 7–9 DPI. Minimal datasets combining the six most effective features also resulted in effective grouping of healthy and diseased plants at 4–7 DPI. This suggests that selectively combining morphometric and spectral features can enable accurate early identification of infected plants, thus creating the scope for improving high-throughput crop monitoring in vertical farms

Needle in a haystack? A comparison of eDNA metabarcoding and targeted qPCR for detection of the great crested newt (Triturus cristatus)

Environmental DNA (eDNA ) analysis is a rapid, cost‐effective, non‐invasive biodiversity monitoring tool which utilises DNA left behind in the environment by organisms for species detection. The method is used as a species‐specific survey tool for rare or invasive species across a broad range of ecosystems. Recently, eDNA and “metabarcoding” have been combined to describe whole communities rather than focusing on single target species. However, whether metabarcoding is as sensitive as targeted approaches for rare species detection remains to be evaluated. The great crested newt Triturus cristatus is a flagship pond species of international conservation concern and the first UK species to be routinely monitored using eDNA . We evaluate whether eDNA metabarcoding has comparable sensitivity to targeted real‐time quantitative PCR (qPCR ) for T. cristatus detection. Extracted eDNA samples (N = 532) were screened for T. cristatus by qPCR and analysed for all vertebrate species using high‐throughput sequencing technology. With qPCR and a detection threshold of 1 of 12 positive qPCR replicates, newts were detected in 50% of ponds. Detection decreased to 32% when the threshold was increased to 4 of 12 positive qPCR replicates. With metabarcoding, newts were detected in 34% of ponds without a detection threshold, and in 28% of ponds when a threshold (0.028%) was applied. Therefore, qPCR provided greater detection than metabarcoding but metabarcoding detection with no threshold was equivalent to qPCR with a stringent detection threshold. The proportion of T. cristatus sequences in each sample was positively associated with the number of positive qPCR replicates (qPCR score) suggesting eDNA metabarcoding may be indicative of eDNA concentration. eDNA metabarcoding holds enormous potential for holistic biodiversity assessment and routine freshwater monitoring. We advocate this community approach to freshwater monitoring to guide management and conservation, whereby entire communities can be initially surveyed to best inform use of funding and time for species‐specific surveys

Generating and testing ecological hypotheses at the pondscape with environmental DNA metabarcoding: a case study on a threatened amphibian

Abstract Environmental DNA (eDNA) metabarcoding is revolutionising biodiversity monitoring, but has unrealised potential for ecological hypothesis generation and testing. Here, we validate this potential in a large-scale analysis of vertebrate community data generated by eDNA metabarcoding of 532 UK ponds. We test biotic associations between the threatened great crested newt ( Triturus cristatus ) and other vertebrates as well as abiotic factors influencing T. cristatus detection at the pondscape. Furthermore, we test the status of T. cristatus as an umbrella species for pond conservation by assessing whether vertebrate species richness is greater in ponds with T. cristatus and higher T. cristatus Habitat Suitability Index (HSI) scores. T. cristatus detection was positively correlated with amphibian and waterfowl species richness. Specifically, T. cristatus was positively associated with smooth newt ( Lissotriton vulgaris ), common coot ( Fulica atra ), and common moorhen ( Gallinula chloropus ), but negatively associated with common toad ( Bufo bufo ). T. cristatus detection did not significantly decrease as fish species richness increased, but negative associations with common carp ( Cyprinus carpio ), three-spined stickleback ( Gasterosteus aculeatus ) and ninespine stickleback ( Pungitius pungitius ) were identified. T. cristatus detection was negatively correlated with mammal species richness, and T. cristatus was negatively associated with grey squirrel ( Sciurus carolinensis ). T. cristatus detection was negatively correlated with larger pond area, presence of inflow, and higher percentage of shading, but positively correlated with HSI score, supporting its application to T. cristatus survey. Vertebrate species richness was significantly higher in T. cristatus ponds and broadly increased as T. cristatus HSI scores increased. We reaffirm reported associations (e.g. T. cristatus preference for smaller ponds) but also provide novel insights, including a negative effect of pond inflow on T. cristatus . Our findings demonstrate the prospects of eDNA metabarcoding for ecological hypothesis generation and testing at landscape scale, and dramatic enhancement of freshwater conservation, management, monitoring and research