CRISPRCas9-based mutagenesis frequently provokes on-target mRNA misregulation, bioRxiv, 2019-03-20

The introduction of insertion-deletions (INDELs) by activation of the error-prone non-homologous end-joining (NHEJ) pathway underlies the mechanistic basis of CRISPRCas9-directed genome editing. The ability of CRISPRCas9 to achieve gene elimination (knockouts) is largely attributed to the emergence of a pre-mature termination codon (PTC) from a frameshift-inducing INDEL that elicits non-sense mediated decay (NMD) of the mutant mRNA. Yet, the impact on gene expression as a consequence of CRISPRCas9-introduced INDELs into RNA regulatory sequences has been largely left uninvestigated. By tracking DNA-mRNA-protein relationships in a collection of CRISPRCas9-edited cell lines that harbor frameshift-inducing INDELs in various targeted genes, we detected the production of foreign mRNAs or proteins in ∼50% of the cell lines. We demonstrate that these aberrant protein products are derived from the introduction of INDELs that promote internal ribosomal entry, convert pseudo-mRNAs into protein encoding molecules, or induce exon skipping by disruption of exon splicing enhancers (ESEs). Our results using CRISPRCas9-introduced INDELs reveal facets of an epigenetic genome buffering apparatus that likely evolved to mitigate the impact of such mutations introduced by pathogens and aberrant DNA damage repair, and that more recently pose challenges to manipulating gene expression outcomes using INDEL-based mutagenesis.

biorxiv molecular-biology 100-200-users 2019

Variations in Structural MRI Quality Impact Measures of Brain Anatomy Relations with Age and Other Sociodemographic Variables, bioRxiv, 2019-03-20

AbstractIn-scanner head movements can introduce artifacts to MRI images and increase errors in brain-behavior studies. The magnitude of in-scanner head movements varies widely across developmental and clinical samples, making it increasingly difficult to parse out “true signal” from motion related noise. Yet, the quantification of structural imaging quality is typically limited to subjective visual assessments andor proxy measures of motion. It is, however, unknown how direct measures of image quality relate to developmental and behavioral variables, as well as measures of brain morphometrics. To begin to answer this question, we leverage a multi-site dataset of structural MRI images, which includes a range of children and adolescents with varying degrees of psychopathology. We first find that a composite of structural image quality relates to important developmental and behavioral variables (e.g., IQ; clinical diagnoses). Additionally, we demonstrate that even among T1-weighted images which pass visual inspection, variations in image quality impact volumetric derivations of regional gray matter. Image quality was associated with wide-spread variations in gray matter, including in portions of the frontal, parietal, and temporal lobes, as well as the cerebellum. Further, our image quality composite partially mediated the relationship between age and total gray matter volume, explaining 23% of this relationship. Collectively, the effects underscore the need for volumetric studies to model or mitigate the effect of image quality when investigating brain-behavior relations.

biorxiv neuroscience 0-100-users 2019

 

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