Biology subjects

Hansen, K.

Publications and source records attributed to Hansen, K..

6 recordsLinked to original sources

bioRxiv2018

A histone H4K20 methylation-mediated chromatin compaction threshold ensures genome integrity by limiting DNA replication licensing

The decompaction and re-establishment of chromatin organization immediately after mitosis is essential for genome regulation. The mechanisms underlying chromatin structure control in daughter cells are not fully understood. Here, we show that a chromatin compaction threshold in cells exiting mitosis ensures genome integrity by limiting replication licensing in G1 phase. Upon mitotic exit, appropriate chromatin relaxation is safeguarded by SET8-dependent methylation of histone H4 on lysine 20. Thus, in the absence of either SET8 or the H4K20 residue, substantial genome-wide chromatin decompaction occurs which allows excessive loading of the Origin Recognition Complex (ORC) in the daughter cells. ORC overloading stimulates aberrant recruitment of the MCM2-7 complex that promotes single-stranded DNA formation and DNA damage. Restoring chromatin compaction restrains excess replication licensing and the loss of genome integrity. Our findings identify a cell cycle-specific mechanism whereby fine-tuned chromatin relaxation suppresses excessive detrimental replication licensing and maintains genome integrity at the cellular transition from mitosis to G1 phase.

molecular biology↗

bioRxiv2018

Structural basis for isoform-specific kinesin-1 recognition of Y-acidic cargo adaptors

The light chains (KLCs) of the heterotetrameric microtubule motor kinesin-1, that bind to cargo adaptor proteins and regulate its activity, have a capacity to recognize short peptides via their tetratricopeptide repeat domains (KLCTPR). Here, using X-ray crystallography, we show how kinesin-1 recognizes a novel class of adaptor motifs that we call Y-acidic (tyrosine flanked by acidic residues), in a KLC-isoform specific manner. Binding specificities of Y-acidic motifs (present in JIP1 and in TorsinA) to KLC1TPR are distinct from those utilized for the recognition of W-acidic motifs found in adaptors that are KLC-isoform non-selective. However, a partial overlap on their receptor binding sites implies that adaptors relying on Y-acidic and W-acidic motifs must act independently. We propose a model to explain why these two classes of motifs that bind to the concave surface of KLCTPR with similar low micromolar affinity can exhibit different capacities to promote kinesin-1 activity.

biochemistry↗

bioRxiv2017

Linear models enable powerful differential activity analysis in massively parallel reporter assays

Massively parallel reporter assays (MPRAs) have emerged as a popular means for understanding noncoding variation in a variety of conditions. While a large number of experiments have been described in the literature, analysis typically uses ad-hoc methods. There has been little attention to comparing performance of methods across datasets. We present the mpralm method which we show is calibrated and powerful, by analyzing its performance on multiple MPRA datasets. We show that it outperforms existing statistical methods for analysis of this data type, in the first comprehensive evaluation of statistical methods on several datasets. We investigate theoretical and real-data properties of barcode summarization methods and show an unappreciated impact of summarization method for some datasets. Finally, we use our model to conduct a power analysis for this assay and show substantial improvements in power by performing up to 6 replicates per condition, whereas sequencing depth has smaller impact; we recommend to always use at least 4 replicates. Together, these results inform recommendations for differential analysis, general group comparisons, and power analysis and will help improve design and analysis of MPRA experiments. An R package is available from the Bioconductor project at https://bioconductor.org/packages/mpra.

bioinformatics↗

bioRxiv2017

Software For The Integration Of Multi-Omics Experiments In Bioconductor

Multi-omics experiments are increasingly commonplace in biomedical research, and add layers of complexity to experimental design, data integration, and analysis. R and Bioconductor provide a generic framework for statistical analysis and visualization, as well as specialized data classes for a variety of high-throughput data types, but methods are lacking for integrative analysis of multi-omics experiments. The MultiAssayExperiment software package, implemented in R and leveraging Bioconductor software and design principles, provides for the coordinated representation of, storage of, and operation on multiple diverse genomics data. We provide all of the multiple omics data for each cancer tissue in The Cancer Genome Atlas (TCGA) as ready-to-analyze MultiAssayExperiment objects, and demonstrate in these and other datasets how the software simplifies data representation, statistical analysis, and visualization. The MultiAssayExperiment Bioconductor package reduces major obstacles to efficient, scalable and reproducible statistical analysis of multi-omics data and enhances data science applications of multiple omics datasets.

bioinformatics↗

bioRxiv2017

Correcting For Cell-Type Heterogeneity In Epigenome-Wide Association Studies: Premature Analyses And Conclusions

Recently, a study by Rahmani et al [1] claimed that a reference-free cell-type deconvolution method, called ReFACTor, leads to improved power and improved estimates of cell-type composition compared to competing reference-free and reference-based methods in the context of Epigenome-Wide Association Studies (EWAS). However, we identified many critical flaws (both conceptual and statistical in nature), which seriously question the validity of their claims. We outlined constructive criticism in a recent correspondence letter, Zheng et al [2]. The purpose of this letter is two-fold. First, to present additional analyses, which demonstrate that our original criticism is statistically sound. Second, to highlight additional serious concerns, which Rahmani et al have not yet addressed. In summary, we find that ReFACTor has not been demonstrated to outperform state-of-the-art reference-free methods such as SVA or RefFreeEWAS, nor state-of-the-art reference-based methods. Thus, the claim by Rahmani et al (a claim reiterated in their recent response letter [3]) that ReFACT or represents an advance over the state-of-the-art is not supported by an objective and rigorous statistical analysis of the data.

bioinformatics↗

bioRxiv2017

Neuronal brain region-specific DNA methylation andchromatin accessibility are associated with neuropsychiatric disease heritability

Epigenetic modifications confer stable transcriptional patterns in the brain, and both normal and abnormal brain function involve specialized brain regions, yet little is known about brain region-specific epigenetic differences. Here, we compared prefrontal cortex, anterior cingulate gyrus, hippocampus and nucleus accumbens from 6 individuals, performing whole genome bisulfite sequencing for DNA methylation. In addition, we have performed ATAC-seq for chromatin accessibility, and RNA-seq for gene expression in the nucleus accumbens and prefrontal cortex from 6 additional individuals. We found substantial neuron- and brain region-specific differences in both DNA methylation and chromatin accessibility which were largely non-overlapping, and were greatest between nucleus accumbens and the other regions. In contrast, glial methylation and chromatin were relatively homogeneous across brain regions, although neuron/glia ratios varied greatly, demonstrating the necessity for cellular fractionation. Gene expression was also largely the same across glia from different brain regions and substantially different for neurons. Expression was correlated with methylation and accessibility across promoters and known enhancers. Several classes of transcription factor binding sites were enriched at regions of differential methylation and accessibility, including many that respond to synaptic activity. Finally, both regions of differential methylation and those of differential accessibility showed a surprising >10-fold enrichment of explained heritability associated with addictive behavior, as well as schizophrenia- and neuroticism-associated regions, suggesting that common psychiatric illness is mediated through brain region-specific epigenetic marks.

neuroscience↗