Abstract Certain CRISPR-Cas elements integrate into Tn7-like transposons, forming CRISPR-associated transposon (CAST) systems. How the activity of these systems is controlled in situ has remained largely unknown. Here we characterize the MerR-type transcriptional regulator Alr3614 that is encoded by one of the CAST (AnCAST) system genes in the genome of cyanobacterium Anabaena sp. PCC 7120. We identify a number of Alr3614 homologs across cyanobacteria and suggest naming these regulators CvkR for Cas V-K repressors. Alr3614/CvkR is translated from leaderless mRNA and represses the AnCAST core modules cas12k and tnsB directly, and indirectly the abundance of the tracr-CRISPR RNA. We identify a widely conserved CvkR binding motif 5’-AnnACATnATGTnnT-3’. Crystal structure of CvkR at 1.6 Å resolution reveals that it comprises distinct dimerization and potential effector-binding domains and that it assembles into a homodimer, representing a discrete structural subfamily of MerR regulators. CvkR repressors are at the core of a widely conserved regulatory mechanism that controls type V-K CAST systems.

Since emerging in Brazil in 1985, wheat blast has spread throughout South America and recently appeared in Bangladesh and Zambia. Here we show that two wheat resistance genes, Rwt3 and Rwt4, acting as host-specificity barriers against non-Triticum blast pathotypes encode a nucleotide-binding leucine-rich repeat immune receptor and a tandem kinase, respectively. Molecular isolation of these genes will enable study of the molecular interaction between pathogen effector and host resistance genes.

Nucleus, chromatin, and chromosome organization studies heavily rely on fluorescence microscopy imaging to elucidate the distribution and abundance of structural and regulatory components. Three-dimensional (3D) image stacks are a source of quantitative data on signal intensity level and distribution and on the type and shape of distribution patterns in space. Their analysis can lead to novel insights that are otherwise missed in qualitative-only analyses. Quantitative image analysis requires specific software and workflows for image rendering, processing, segmentation, setting measurement points and reference frames and exporting target data before further numerical processing and plotting. These tasks often call for the development of customized computational scripts and require an expertise that is not broadly available to the community of experimental biologists. Yet, the increasing accessibility of high- and super-resolution imaging methods fuels the demand for user-friendly image analysis workflows. Here, we provide a compendium of strategies developed by participants of a training school from the COST action INDEPTH to analyze the spatial distribution of nuclear and chromosomal signals from 3D image stacks, acquired by diffraction-limited confocal microscopy and super-resolution microscopy methods (SIM and STED). While the examples make use of one specific commercial software package, the workflows can easily be adapted to concurrent commercial and open-source software. The aim is to encourage biologists lacking custom-script-based expertise to venture into quantitative image analysis and to better exploit the discovery potential of their images.

Cell-free (cf)DNA signatures are quickly becoming the target of choice for non-invasive screening, diagnosis, treatment and monitoring of human tumors. DNA methylation changes occur early in tumorigenesis and are widespread, making cfDNA methylation an attractive cancer biomarker. Already a proven technology for targeted genome sequencing, hybridization probe capture is emerging as a method for high-throughput targeted methylation profiling suitable to liquid biopsy samples. However, to date there are no reports describing the performance of this approach in terms of reproducibility, scalability, and accuracy. In the current study we performed hybridization probe capture using the myBaits® Custom Methyl-seq kit on 172 plasma samples and standards to evaluate its performance on cfDNA methylation analysis. The myBaits® assay showed high target recovery (>90%), demonstrated excellent reproducibility between captures (R2 = 0.92 on average), and was unaffected by increasing the number of targets in a capture. Finally, myBaits® accurately replicated ‘gold standard’ beta values from WGBS (average R2 = 0.79). The results of this study show that custom targeted methylation sequencing with myBaits® offers a cost-effective, reliable platform to profile DNA methylation at a set of discrete custom regions, with potential applicability to liquid biopsies for cancer monitoring.

Although wheat (Triticum aestivum L.) is the main staple crop in the world and a major source of carbohydrates and proteins, functional genomics and allele mining are still big challenges. Given the advances in next-generation sequencing (NGS) technologies, the identification of causal variants associated with a target phenotype has become feasible. For these reasons, here, by combining sequence capture and target-enrichment methods with high-throughput NGS re-sequencing, we were able to scan at exome-wide level 46 randomly selected bread wheat individuals from a recombinant inbred line population and to identify and classify a large number of single nucleotide polymorphisms (SNPs). For technical validation of results, eight randomly selected SNPs were converted into Kompetitive Allele-Specific PCR (KASP) markers. This resource was established as an accessible and reusable molecular toolkit for allele data mining. The dataset we are making available could be exploited for novel studies on bread wheat genetics and as a foundation for starting breeding programs aimed at improving different key agronomic traits.