A Systematic Evaluation of Single Cell RNA-Seq Analysis Pipelines Library preparation and normalisation methods have the biggest impact on the performance of scRNA-seq studies, bioRxiv, 2019-03-20
AbstractThe recent rapid spread of single cell RNA sequencing (scRNA-seq) methods has created a large variety of experimental and computational pipelines for which best practices have not been established yet. Here, we use simulations based on five scRNA-seq library protocols in combination with nine realistic differential expression (DE) setups to systematically evaluate three mapping, four imputation, seven normalisation and four differential expression testing approaches resulting in ~ 3,000 pipelines, allowing us to also assess interactions among pipeline steps.We find that choices of normalisation and library preparation protocols have the biggest impact on scRNA-seq analyses. Specifically, we find that library preparation determines the ability to detect symmetric expression differences, while normalisation dominates pipeline performance in asymmetric DE-setups. Finally, we illustrate the importance of informed choices by showing that a good scRNA-seq pipeline can have the same impact on detecting a biological signal as quadrupling the sample size.
biorxiv bioinformatics 100-200-users 2019A Systematic Evaluation of Single Cell RNA-Seq Analysis Pipelines, bioRxiv, 2019-03-20
AbstractThe recent rapid spread of single cell RNA sequencing (scRNA-seq) methods has created a large variety of experimental and computational pipelines for which best practices have not been established, yet. Here, we use simulations based on five scRNA-seq library protocols in combination with nine realistic differential expression (DE) setups to systematically evaluate three mapping, four imputation, seven normalisation and four differential expression testing approaches resulting in ∼ 3,000 pipelines, allowing us to also assess interactions among pipeline steps. We find that choices of normalisation and library preparation protocols have the biggest impact on scRNA-seq analyses. Specifically, we find that library preparation determines the ability to detect symmetric expression differences, while normalisation dominates pipeline performance in asymmetric DE-setups. Finally, we illustrate the importance of informed choices by showing that a good scRNA-seq pipeline can have the same impact on detecting a biological signal as quadrupling the sample size.
biorxiv bioinformatics 200-500-users 2019CRISPRCas9-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 2019Direct visualization of single nuclear pore complex proteins using genetically-encoded probes for DNA-PAINT, bioRxiv, 2019-03-20
The Nuclear Pore Complex (NPC) is one of the largest and most complex protein assemblies in the cell and – among other functions – serves as the gatekeeper of nucleocytoplasmic transport. Unraveling its molecular architecture and functioning has been an active research topic for decades with recent cryogenic electron microscopy and superresolution studies advancing our understanding of the NPC's complex architecture. However, the specific and direct visualization of single copies of NPC proteins and thus the ability to observe single-molecule heterogeneities of these complex structures is thus far elusive. Here, we combine genetically-encoded self-labeling enzymes such as SNAP-tag and HaloTag with DNA-PAINT microscopy. We employ the high localization precision in DNA-PAINT and molecular contrast of these protein tags to optically resolve single copies of nucleoporins in the human Y-complex in three dimensions with a precision of ~3 nm. This technological advancement now enables structural studies of multicomponent complexes on the level of single proteins in cells using optical fluorescence microscopy.
biorxiv cell-biology 0-100-users 2019Nuclear pores as versatile reference standards for quantitative superresolution microscopy, bioRxiv, 2019-03-20
AbstractQuantitative fluorescence and superresolution microscopy are often limited by insufficient data quality or artifacts. In this context, it is essential to have biologically relevant control samples to benchmark and optimize the quality of microscopes, labels and imaging conditions.Here we exploit the stereotypic arrangement of proteins in the nuclear pore complex as in situ reference structures to characterize the performance of a variety of microscopy modalities. We created four genome edited cell lines in which we endogenously labeled the nucleoporin Nup96 with mEGFP, SNAP-tag or HaloTag or the photoconvertible fluorescent protein mMaple. We demonstrate their use a) as 3D resolution standards for calibration and quality control, b) to quantify absolute labeling efficiencies and c) as precise reference standards for molecular counting.These cell lines will enable the broad community to assess the quality of their microscopes and labels, and to perform quantitative, absolute measurements.
biorxiv biophysics 100-200-users 2019Variations 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