Fragile X syndrome (FXS) is the most common form of inherited intellectual disability, resulting from a CGG repeat expansion in the fragile X mental retardation 1 (FMR1) gene. Here, we report a strategy for CGG repeat correction using CRISPR/Cas9 for targeted deletion in both embryonic stem cells and induced pluripotent stem cells derived from FXS patients. Following gene correction in FXS induced pluripotent stem cells, FMR1 expression was restored and sustained in neural precursor cells and mature neurons. Strikingly, after removal of the CGG repeats, the upstream CpG island of the FMR1 promoter showed extensive demethylation, an open chromatin state, and transcription initiation. These results suggest a silencing maintenance mechanism for the FMR1 promoter that is dependent on the existence of the CGG repeat expansion. Our strategy for deletion of trinucleotide repeats provides further insights into the molecular mechanisms of FXS and future therapies of trinucleotide repeat disorders.

https://ir.ymlib.yonsei.ac.kr/bitstream/22282913/141555/1/T201504015.pdf

Reversion of FMR1 Methylation and Silencing by Editing the Triplet Repeats in Fragile X iPSC-Derived Neurons

Methods for profiling RNA and protein expression in a spatially resolved manner are rapidly evolving, making it possible to comprehensively characterize cells and tissues in health and disease. To maximize the biological insights obtained using these techniques, it is critical to both clearly articulate the key biological questions in spatial analysis of tissues and develop the requisite computational tools to address them. Developers of analytical tools need to decide on the intrinsic molecular features of each cell that need to be considered, and how cell shape and morphological features are incorporated into the analysis. Also, optimal ways to compare different tissue samples at various length scales are still being sought. Grouping these biological problems and related computational algorithms into classes across length scales, thus characterizing common issues that need to be addressed, will facilitate further progress in spatial transcriptomics and proteomics. 

https://push-zb.helmholtz-muenchen.de/deliver.php?id=32310

Spatial components of molecular tissue biology

https://repub.eur.nl/pub/123102/Repub_123102_O-A.pdf

Sharpening the Molecular Scissors: Advances in Gene-Editing Technology.

Artificial intelligence in histopathology: enhancing cancer research and clinical oncology

http://www.cell.com/article/S0092867422001957/pdf

Spatial CRISPR genomics identifies regulators of the tumor microenvironment

The exact DNA mutation produced by cellular repair of a CRISPR/Cas9-generated double strand break determines its phenotypic effect. It is known that the mutational outcomes are not random, and depend on DNA sequence at the targeted location. Here, we present a systematic study of this link. We created a high throughput assay to directly measure the edits generated by over 40,000 guide RNAs, and applied it in a range of genetic backgrounds and for alternative CRISPR/Cas9 reagents. In total, we gathered data for over 1,000,000,000 mutational outcomes in synthetic constructs, which mirror those at endogenous loci. The majority of reproducible mutations are insertions of a single base, short deletions, or long microhomology-mediated deletions. gRNAs have a cell-line dependent preference for particular outcomes, especially favouring single base insertions and microhomology-mediated deletions. We uncover sequence determinants of the produced mutations at individual loci, and use these to derive a predictor of Cas9 editing outcomes with accuracy close to the theoretical maximum. This improved understanding of sequence repair allows better design of editing experiments, and may lead to future therapeutic applications.

/pdf/mutations-generated-by-repair-of-cas9-induced-double-strand-ijswloy0pp.pdf

Mutations generated by repair of Cas9-induced double strand breaks are predictable from surrounding sequence

Subclonality is a universal feature of cancers yet how clones grow, are spatially organised, differ phenotypically or influence clinical outcome is unclear. To address this, we developed base specific in situ sequencing (BaSISS). In fixed tissues, transcripts harbouring clone-defining mutations are detected, converted into quantitative clone maps and characterised through multi-layered data integration. Applied to 8 samples from key stages of breast cancer progression BaSISS localised 1.42 million genotype informative transcripts across 4.9cm2 of tissue. Microscopic clonal topographies are shaped by resident tissue architectures. Distinct transcriptional, histological and immunological features distinguish coexistent genetic clones. Spatial lineage tracing temporally orders clone features associated with the emergence of aggressive clinical traits. These results highlight the pivotal role of spatial genomics in deciphering the mechanisms underlying cancer progression.

/pdf/spatial-genomics-maps-the-structure-character-and-evolution-rf3spaql7j.pdf

Spatial genomics maps the structure, character and evolution of cancer clones

Linear motifs have an integral role in dynamic cell functions including cell signalling, the cell cycle and others. However, due to their small size, low complexity, degenerate nature, and frequent mutations, identifying novel functional motifs is a challenging task. Viral proteins rely extensively on the molecular mimicry of cellular linear motifs for modifying cell signalling and other processes in ways that favour viral infection. This study aims to discover human linear motifs convergently evolved also in disordered regions of viral proteins, under the hypothesis that these will result in enrichment in functional motif instances. We systematically apply computational motif prediction, combined with implementation of several functional and structural filters to the most recent publicly available human-viral and human-human protein interaction network. By limiting the search space to the sequences of viral proteins, we observed an increase in the sensitivity of motif prediction, as well as improved enrichment in known instances compared to the same analysis using only human protein interactions. We identified > 8,400 motif instances at various confidence levels, 105 of which were supported by all functional and structural filters applied. Overall, we provide a pipeline to improve the identification of functional linear motifs from interactomics datasets and a comprehensive catalogue of putative human motifs that can contribute to our understanding of the human domain-linear motif code and the mechanisms of viral interference with this.

https://www.biorxiv.org/content/biorxiv/early/2021/06/26/2021.06.25.449930.full.pdf

Kleshchevnikov

Papers

Mutations generated by repair of Cas9-induced double strand breaks are predictable from surrounding sequence

Spatial genomics maps the structure, character and evolution of cancer clones

Use of viral motif mimicry improves the proteome-wide discovery of human linear motifs