Unsupervised contrastive peak caller for ATAC-seq

The assay for transposase-accessible chromatin with sequencing (ATAC-seq) is a common assay to identify chromatin accessible regions by using a Tn5 transposase that can access, cut, and ligate adapters to DNA fragments for subsequent amplification and sequencing. These sequenced regions are quantified and tested for enrichment in a process referred to as "peak calling." Most unsupervised peak calling methods are based on simple statistical models and suffer from elevated false positive rates. Newly developed supervised deep learning methods can be successful, but they rely on high quality labeled data for training, which can be difficult to obtain. Moreover, though biological replicates are recognized to be important, there are no established approaches for using replicates in the deep learning tools, and the approaches available for traditional methods either cannot be applied to ATAC-seq, where control samples may be unavailable, or are post hoc and do not capitalize on potentially complex, but reproducible signal in the read enrichment data. Here, we propose a novel peak caller that uses unsupervised contrastive learning to extract shared signals from multiple replicates. Raw coverage data are encoded to obtain low-dimensional embeddings and optimized to minimize a contrastive loss over biological replicates. These embeddings are passed to another contrastive loss for learning and predicting peaks and decoded to denoised data under an autoencoder loss. We compared our replicative contrastive learner (RCL) method with other existing methods on ATAC-seq data, using annotations from ChromHMM genomic labels and transcription factor ChIP-seq as noisy truth. RCL consistently achieved the best performance.

Quantification of gray mold infection in lettuce using a bispectral imaging system under laboratory conditions

Gray mold disease caused by the fungus Botrytis cinerea damages many crop hosts worldwide and is responsible for heavy economic losses. Early diagnosis and detection of the disease would allow for more effective crop management practices to prevent outbreaks in field or greenhouse settings. Furthermore, having a simple, non-invasive way to quantify the extent of gray mold disease is important for plant pathologists interested in measuring infection rates. In this paper, we design and build a bispectral imaging system for discriminating between leaf regions infected with gray mold and those that remain unharmed on a lettuce (Lactuca spp.) host. First, we describe a method to select two optimal (high contrast) spectral bands from continuous hyperspectral imagery (450-800 nm). We then explain the process of building a system based on these two spectral bands, located at 540 and 670 nm. The resultant system uses two cameras, with a narrow band-pass spectral filter mounted on each, to measure the bispectral reflectance of a lettuce leaf. The two resulting images are combined using a normalized difference calculation that produces a single image with high contrast between the leaves' infected and healthy regions. A classifier was then created based on the thresholding of single pixel values. We demonstrate that this simple classification produces a true-positive rate of 95.25% with a false-positive rate of 9.316% in laboratory conditions.

Ecological drivers of African swine fever virus persistence in wild boar populations: Insight for control

Environmental sources of infection can play a primary role in shaping epidemiological dynamics; however, the relative impact of environmental transmission on host-pathogen systems is rarely estimated. We developed and fit a spatially explicit model of African swine fever virus (ASFV) in wild boar to estimate what proportion of carcass-based transmission is contributing to the low-level persistence of ASFV in Eastern European wild boar. Our model was developed based on ecological insight and data from field studies of ASFV and wild boar in Eastern Poland. We predicted that carcass-based transmission would play a substantial role in persistence, especially in low-density host populations where contact rates are low. By fitting the model to outbreak data using approximate Bayesian computation, we inferred that between 53% and 66% of transmission events were carcass-based that is, transmitted through contact of a live host with a contaminated carcass. Model fitting and sensitivity analyses showed that the frequency of carcass-based transmission increased with decreasing host density, suggesting that management policies should emphasize the removal of carcasses and consider how reductions in host densities may drive carcass-based transmission. Sensitivity analyses also demonstrated that carcass-based transmission is necessary for the autonomous persistence of ASFV under realistic parameters. Autonomous persistence through direct transmission alone required high host densities; otherwise re-introduction of virus periodically was required for persistence when direct transmission probabilities were moderately high. We quantify the relative role of different persistence mechanisms for a low-prevalence disease using readily collected ecological data and viral surveillance data. Understanding how the frequency of different transmission mechanisms vary across host densities can help identify optimal management strategies across changing ecological conditions.

Molecular insight into cotton leaf curl geminivirus disease resistance in cultivated cotton (Gossypium hirsutum)

Cultivated cotton (Gossypium hirsutum) is the most important fibre crop in the world. Cotton leaf curl disease (CLCuD) is the major limiting factor and a threat to textile industry in India and Pakistan. All the local cotton cultivars exhibit moderate to no resistance against CLCuD. In this study, we evaluated an exotic cotton accession Mac7 as a resistance source to CLCuD by challenging it with viruliferous whiteflies and performing qPCR to evaluate the presence/absence and relative titre of CLCuD-associated geminiviruses/betasatellites. The results indicated that replication of pathogenicity determinant betasatellite is significantly attenuated in Mac7 and probably responsible for resistance phenotype. Afterwards, to decipher the genetic basis of CLCuD resistance in Mac7, we performed RNA sequencing on CLCuD-infested Mac7 and validated RNA-Seq data with qPCR on 24 independent genes. We performed co-expression network and pathway analysis for regulation of geminivirus/betasatellite-interacting genes. We identified nine novel modules with 52 hubs of highly connected genes in network topology within the co-expression network. Analysis of these hubs indicated the differential regulation of auxin stimulus and cellular localization pathways in response to CLCuD. We also analysed the differential regulation of geminivirus/betasatellite-interacting genes in Mac7. We further performed the functional validation of selected candidate genes via virus-induced gene silencing (VIGS). Finally, we evaluated the genomic context of resistance responsive genes and found that these genes are not specific to A or D sub-genomes of G. hirsutum. These results have important implications in understanding CLCuD resistance mechanism and developing a durable resistance in cultivated cotton.

Conformational flexibility in the enterovirus RNA replication platform

A presumed RNA cloverleaf (5'CL), located at the 5'-most end of the noncoding region of the enterovirus genome, is the primary established site for initiation of genomic replication. Stem-loop B (SLB) and stem-loop D (SLD), the two largest stem-loops within the 5'CL, serve as recognition sites for protein interactions that are essential for replication. Here we present the solution structure of rhinovirus serotype 14 5'CL using a combination of nuclear magnetic resonance spectroscopy and small-angle X-ray scattering. In the absence of magnesium, the structure adopts an open, somewhat extended conformation. In the presence of magnesium, the structure compacts, bringing SLB and SLD into close contact, a geometry that creates an extensive accessible major groove surface, and permits interaction between the proteins that target each stem-loop.