A Rapid Detection Method for Tomato Gray Mold Spores in Greenhouse Based on Microfluidic Chip Enrichment and Lens-Less Diffraction Image Processing

It is of great significance to find tomato gray mold in time and take corresponding control measures to ensure the production of tomato crops. This study proposed a rapid detection method for spores of Botrytis cinerea in green-house based on microfluidic chip enrichment and lens-free diffraction image processing. Microfluidic chip with a regular triangular inner rib structure was designed to achieve the enrichment of Botrytis cinerea spores. In order to obtain the diffraction image of the diseased spores, a lens-less diffraction imaging system was built. Furthermore, the collected spore diffraction images were processed and counted. The simulation results showed that the collection efficiency of 16 μm particles was 79%, 100%, and 89% at the inlet flow rate of 12, 14 and 16 mL/min, respectively. The experimental verification results were observed under a microscope. The results showed that when the flow rate of the microfluidic chip was 12, 14 and 16 mL/min, the collection efficiency of Botrytis cinerea spores was 70.65%, 87.52% and 77.96%, respectively. The Botrytis cinerea spores collected in the experiment were placed under a microscope for manual counting and compared with the automatic counting results based on diffraction image processing. A total of 10 sets of experiments were carried out, with an error range of the experiment was 5.13~8.57%, and the average error of the experiment was 6.42%. The Bland–Altman method was used to analyze two methods based on diffraction image processing and manual counting under a microscope. All points are within the 95% consistency interval. Therefore, this study can provide a basis for the research on the real-time monitoring technology of tomato gray mold spores in the greenhouse.

ASY1 acts as a dosage-dependent antagonist of telomere-led recombination and mediates crossover interference inArabidopsis

During meiosis, interhomolog recombination produces crossovers and noncrossovers to create genetic diversity. Meiotic recombination frequency varies at multiple scales, with high subtelomeric recombination and suppressed centromeric recombination typical in many eukaryotes. During recombination, sister chromatids are tethered as loops to a polymerized chromosome axis, which, in plants, includes the ASY1 HORMA domain protein and REC8–cohesin complexes. Using chromatin immunoprecipitation, we show an ascending telomere-to-centromere gradient of ASY1 enrichment, which correlates strongly with REC8–cohesin ChIP-seq data. We mapped crossovers genome-wide in the absence of ASY1 and observe that telomere-led recombination becomes dominant. Surprisingly,asy1/+heterozygotes also remodel crossovers toward subtelomeric regions at the expense of the pericentromeres. Telomeric recombination increases inasy1/+occur in distal regions where ASY1 and REC8 ChIP enrichment are lowest in wild type. In wild type, the majority of crossovers show interference, meaning that they are more widely spaced along the chromosomes than expected by chance. To measure interference, we analyzed double crossover distances, MLH1 foci, and fluorescent pollen tetrads. Interestingly, while crossover interference is normal inasy1/+, it is undetectable inasy1mutants, indicating that ASY1 is required to mediate crossover interference. Together, this is consistent with ASY1 antagonizing telomere-led recombination and promoting spaced crossover formation along the chromosomes via interference. These findings provide insight into the role of the meiotic axis in patterning recombination frequency within plant genomes.

Building a robust chromatin immunoprecipitation (ChIP) method with substantially improved efficiency

ABSTRACTChromatin immunoprecipitation (ChIP) is the gold-standard method to detect the interactions between proteins and chromatin, and is a powerful tool to identify epigenetic modifications. Although ChIP protocols for plant species have been developed, many specific features of plants, especially woody plants, still hinder the efficiency of immunoprecipitation, resulting inefficient ChIP enrichment. There is an active demand for a highly efficient ChIP protocol. In the present study, we employed Betula platyphylla (birch) and Arabidopsis thaliana as the research materials, and five factors closely associated with ChIP efficiency were identified, including crosslinking, chromatin concentration using centrifugal filter, using new immunoprecipitation buffer, rescue DNA with proteinase K, and using sucrose to increase immunoprecipitation efficiency. Optimization of any these factors can significantly improve ChIP efficiency. Considering these factors together, a robust ChIP protocol was developed, for which the average fold enrichments were 16.88 and 6.43 fold of that gained using standard ChIP in birch and Arabidopsis, respectively. As this built ChIP method works well in both birch and Arabidopsis, it should be also suitable for other woody and herbaceous species. In addition, this ChIP method make it is possible to detect low-abundance TF-DNA interactions, and may extend the application of ChIP in plant kingdom.One sentence summaryBuilding a ChIP method that increases fold enrichment of birch by 16 folds in average and is adapted for both woody and herbaceous plants.

An integrated microfluidic system for on-chip enrichment and quantification of circulating extracellular vesicles from whole blood

An integrated microfluidic system was developed for extracellular vesicle (EV) enrichment and quantification by using anti-CD63-coated magnetic beads and an on-chip enzyme-linked immunosorbent assay in human whole blood.

Denoising Genome-wide Histone ChIP-seq with Convolutional Neural Networks

MotivationChromatin immunoprecipitation sequencing (ChIP-seq) experiments are commonly used to obtain genome-wide profiles of histone modifications associated with different types of functional genomic elements. However, the quality of histone ChIP-seq data is affected by a myriad of experimental parameters such as the amount of input DNA, antibody specificity, ChIP enrichment, and sequencing depth. Making accurate inferences from chromatin profiling experiments that involve diverse experimental parameters is challenging.ResultsWe introduce a convolutional denoising algorithm, Coda, that uses convolutional neural networks to learn a mapping from suboptimal to high-quality histone ChIP-seq data. This overcomes various sources of noise and variability, substantially enhancing and recovering signal when applied to low-quality chromatin profiling datasets across individuals, cell types, and species. Our method has the potential to improve data quality at reduced costs. More broadly, this approach – using a high-dimensional discriminative model to encode a generative noise process – is generally applicable to other biological domains where it is easy to generate noisy data but difficult to analytically characterize the noise or underlying data distribution.Availabilityhttps://github.com/kundajelab/[email protected]

Characterizing a collective and dynamic component of chromatin immunoprecipitation enrichment profiles in yeast

Recent chromatin immunoprecipitation (ChIP) experiments in fly, mouse, and human have revealed the existence of high-occupancy target (HOT) regions or “hotspots” that show enrichment across many assayed DNA-binding proteins. Similar co-enrichment observed in yeast so far has been treated as artifactual, and has not been fully characterized. Here we reanalyze ChIP data from both array-based and sequencing-based experiments to show that in the yeast S. cerevisiae, the collective enrichment phenomenon is strongly associated with proximity to noncoding RNA genes and with nucleosome depletion. DNA sequence motifs that confer binding affinity for the proteins are largely absent from these hotspots, suggesting that protein-protein interactions play a prominent role. The hotspots are condition-specific, suggesting that they reflect a chromatin state or protein state, and are not a static feature of underlying sequence. Additionally, only a subset of all assayed factors is associated with these loci, suggesting that the co-enrichment cannot be simply explained by a chromatin state that is universally more prone to immunoprecipitation. Together our results suggest that the co-enrichment patterns observed in yeast represent transcription factor co-occupancy. More generally, they make clear that great caution must be used when interpreting ChIP enrichment profiles for individual factors in isolation, as they will include factor-specific as well as collective contributions.