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The Greatwall kinase inhibits PP2A-B55 phosphatase activity during mitosis to stabilise critical Cdk1-driven mitotic phosphorylation. Although Greatwall represents a potential oncogene and prospective therapeutic target, our understanding of the cellular and molecular consequences of chemical Greatwall inactivation remains limited. To address this, we introduce C-604, a highly selective Greatwall inhibitor, and characterise both immediate and long-term cellular responses to the chemical attenuation of Greatwall activity. We demonstrate that Greatwall inhibition causes systemic destabilisation of the mitotic phosphoproteome, premature mitotic exit and pleiotropic cellular pathologies. Importantly, we show that the cellular and molecular abnormalities associated with reduced Greatwall activity are specifically dependent on the B55α isoform, rather than other B55 variants, underscoring PP2A-B55α phosphatases as key mediators of the cytotoxic effects of Greatwall-targeting agents in human cells. Additionally, we establish that sensitivity to Greatwall inhibition varies in different cell line models and that dependency on Greatwall activity reflects the balance between Greatwall and B55α expression levels. Our findings highlight Greatwall dependency as a cell-specific vulnerability and propose the B55α-to-Greatwall expression ratio as a predictive biomarker of cellular responses to Greatwall-targeted therapeutics. The authors develop and characterise a selective Greatwall inhibitor, C-604, and show that its cytotoxicity stems from PP2A-B55α hyperactivation. They identify B55α and Greatwall levels as biomarkers of responses to Greatwall-targeted therapy.

The Greatwall kinase inhibits PP2A-B55 phosphatase activity during mitosis to stabilise critical Cdk1-driven mitotic phosphorylation. Although Greatwall represents a potential oncogene and prospective therapeutic target, our understanding of cellular and molecular consequences of chemical Greatwall inactivation remains limited. To address this, we introduce C-604, a highly selective Greatwall inhibitor, and characterise both immediate and long-term cellular responses to the chemical attenuation of Greatwall activity. We demonstrate that Greatwall inhibition causes systemic destabilisation of the mitotic phosphoproteome, premature mitotic exit and pleiotropic cellular pathologies. Importantly, we demonstrate that the cellular and molecular abnormalities linked to reduced Greatwall activity are specifically dependent on the B55α isoform rather than other B55 variants, underscoring PP2A-B55α phosphatases as key mediators of cytotoxic effects of Greatwall-targeting agents in human cells. Additionally, we show that sensitivity to Greatwall inhibition varies in different cell line models and that dependency on Greatwall activity reflects the balance between Greatwall and B55α expression levels. Our findings highlight Greatwall dependency as a cell-specific vulnerability and propose the B55α-to-Greatwall expression ratio as a predictive biomarker of cellular responses to Greatwall-targeted therapeutics.

Genome graphs are emerging as an important novel approach to the analysis of high-throughput human sequencing data. By explicitly representing genetic variants and alternative haplotypes in a mappable data structure, they can enable the improved analysis of structurally variable and hyperpolymorphic regions of the genome. In most existing approaches, graphs are constructed from variant call sets derived from short-read sequencing. As long-read sequencing becomes more cost-effective and enables de novo assembly for increasing numbers of whole genomes, a method for the direct construction of a genome graph from sets of assembled human genomes would be desirable. Such assembly-based genome graphs would encompass the wide spectrum of genetic variation accessible to long-read-based de novo assembly, including large structural variants and divergent haplotypes. Here we present NovoGraph, a method for the construction of a human genome graph directly from a set of de novo assemblies. NovoGraph constructs a genome-wide multiple sequence alignment of all input contigs and creates a graph by merging the input sequences at positions that are both homologous and sequence-identical. NovoGraph outputs resulting graphs in VCF format that can be loaded into third-party genome graph toolkits. To demonstrate NovoGraph, we construct a genome graph with 23,478,835 variant sites and 30,582,795 variant alleles from de novo assemblies of seven ethnically diverse human genomes (AK1, CHM1, CHM13, HG003, HG004, HX1, NA19240). Initial evaluations show that mapping against the constructed graph reduces the average mismatch rate of reads from sample NA12878 by approximately 0.2%, albeit at a slightly increased rate of reads that remain unmapped.

Teachers’ perception of self-efficacy may have a significant impact on their ability to accept the challenges inherent in including children with autism in their classrooms. The Nominal Group Technique (NGT) was used to identify perceived challenges and needs of 31 graduate students in a university course of which 14 of the 23 students were actively teaching in rural schools located in southeast Alabama. Five faculty members used the resulting NGT data to draft six recommendations for improving the teacher preparation program at Troy University.  

Genome graphs are emerging as an important novel approach to the analysis of high-throughput sequencing data. By explicitly representing genetic variants and alternative haplotypes in a mappable data structure, they can enable the improved analysis of structurally variable and hyperpolymorphic regions of the genome. In most existing approaches, graphs are constructed from variant call sets derived from short-read sequencing. As long-read sequencing becomes more cost-effective and enables de novo assembly for increasing numbers of whole genomes, a method for the direct construction of a genome graph from sets of assembled human genomes would be desirable. Such assembly-based genome graphs would encompass the wide spectrum of genetic variation accessible to long-read-based de novo assembly, including large structural variants and divergent haplotypes. Here we present NovoGraph, a method for the construction of a genome graph directly from a set of de novo assemblies. NovoGraph constructs a genome-wide multiple sequence alignment of all input contigs and uses a simple criterion of homologous-identical recombination to convert the multiple sequence alignment into a graph. NovoGraph outputs resulting graphs in VCF format that can be loaded into third-party genome graph toolkits. To demonstrate NovoGraph, we construct a genome graph with 23,478,835 variant sites and 30,582,795 variant alleles from de novo assemblies of seven ethnically diverse human genomes (AK1, CHM1, CHM13, HG003, HG004, HX1, NA19240). Initial evaluations show that mapping against the constructed graph reduces the average mismatch rate of reads from sample NA12878 by approximately 0.2%, albeit at a slightly increased rate of reads that remain unmapped.

Teachers' perception of self-efficacy may have a significant impact on their ability to accept the challenges inherent in including children with autism in their classrooms. The Nominal Group Technique (NGT) was used to identify perceived challenges and needs of 31 graduate students in a university course of which 14 of the 23 students were actively teaching in rural schools located in southeast Alabama. Five faculty members used the resulting NGT data to draft six recommendations for improving the teacher preparation program at Troy University. (Contains 1 table.)