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PREMISE OF THE STUDY Leaves of monocots are typically linear with parallel venation, though a few taxa have broad leaves. Studies of stomatal patterning and development in monocots required updating in the context of rapidly improving knowledge of both the phylogenetic and development-genetic context of monocots that facilitate studies of character evolution. METHODS We used an existing microscope-slide collection to obtain data on stomatal structure across all the major monocot clades, including some species with relatively broad leaves. In addition, we used both light and electron microscopy to study stomatal development in 16 selected species. We evaluated these data in a phylogenetic context to assess stomatal character evolution. KEY RESULTS Mature stomatal patterning in monocots can be broadly categorized as anomocytic, paracytic-nonoblique, and paracytic/tetracytic oblique, depending on the presence, development, and arrangement of lateral subsidiary cells. Stomatal meristemoids invariably result from an asymmetric mitosis in monocots. In species where lateral subsidiary cells are present, they are perigene cells. Among monocots with relatively broad leaves, stomatal orientation is linear-axial in most taxa, but transverse in Lapageria and Stemona, and random in Dioscorea and some Araceae. Amplifying divisions are apparently absent in monocots. CONCLUSIONS Anomocytic stomata represent the likely ancestral (plesiomorphic) condition in monocots, though multiple evolutionary transitions and reversals have occurred. Paracytic-nonoblique stomata with highly modified perigene lateral neighbor cells characterize grasses and other Poales. The presence of anomocytic stomata in Japonolirion and Tofieldia reinforces the concept that these two genera have retained many ancestral monocot features and are critical in understanding character evolution in monocots.

Background:Genome editing by CRISPR-Cas9 technology allows large-scale screening of gene essentiality in cancer. A confounding factor when interpreting CRISPR-Cas9 screens is the high false-positive rate in detecting essential genes within copy number amplified regions of the genome. We have developed the computational toolCRISPRcleanRwhich is capable of identifying and correcting gene-independent responses to CRISPR-Cas9 targeting. CRISPRcleanR uses an unsupervised approach based on the segmentation of single-guide RNA fold change values across the genome, without making any assumption about the copy number status of the targeted genes.ResultsApplying our method to existing and newly generated genome-wide essentiality profiles from 15 cancer cell lines, we demonstrate that CRISPRcleanR reduces false positives when calling essential genes, correcting biases within and outside of amplified regions, while maintaining true positive rates. Established cancer dependencies and essentiality signals of amplified cancer driver genes are detectable post-correction. CRISPRcleanR reports sgRNA fold changes and normalised read counts, is therefore compatible with downstream analysis tools, and works with multiple sgRNA libraries.ConclusionsCRISPRcleanR is a versatile open-source tool for the analysis of CRISPR-Cas9 knockout screens to identify essential genes.

Introduction Translating our understanding of genetic alterations in cancer into clinical care remains a major challenge. The discovery of gene fusions such as EML4-ALK in lung cancer and BCR-ABL1 in chronic myeloid leukaemia have already led to changes in clinical care. Advances in next-generation sequencing have accelerated the rate at which novel gene fusions are discovered, but important questions remain about their roles in promoting oncogenic phenotypes and their relevance in drug response. Here, we combine RNA sequencing, CRISPR/Cas9 screens and high-throughput drug sensitivity data in a panel of 1000 human cancer cell lines to examine the occurrence and functional relevance of gene fusions in cancer. Material and methods We performed RNA-sequencing on 1015 human cancer cell lines, representing 42 cancer types. We called fusions using three algorithms: TopHat Fusion, DeFuse and RNA-STAR fusion. Further, we integrate high-throughput drug screening data across >350 compounds, single-nucleotide variants, copy number variation, gene expression data and genome-wide CRISPR/Cas9 dropout screening data to systematically search for gene fusions with functional relevance. Results and discussions We find 8546 distinct gene fusion events across our panel of cell lines. These include well understood gene fusions (e.g. ALK-fusions, BCR-ABL1 and EWSR1-FLI1), as well as novel fusions that involve known cancer driver genes. We are able to recapitulate previously identified gene fusion-drug response associations using an unguided statistical analysis. Furthermore, we developed a systematic unguided approach of using CRISPR/Cas9 gene essentiality data to identify essential gene fusions. This approach recapitulates known essential gene fusions and provides evidence for the oncogenic relevance for previously poorly understood gene fusions. Conclusion In this study, we provide an annotation of gene fusions in 1015 human cancer cell lines. Our systematic analysis of the functional role of gene fusions captures the oncogenic and therapeutic relevance of known gene fusions, and highlights potential therapeutic opportunities of previously uncharacterised gene fusions.