RNA sequencing offers advantages over other quantification methods for microRNA (miRNA), yet numerous biases make reliable quantification challenging. Previous evaluations of these biases have ...focused on adapter ligation bias with limited evaluation of reverse transcription bias or amplification bias. Furthermore, evaluations of the quantification of isomiRs (miRNA isoforms) or the influence of starting amount on performance have been very limited. No study had yet evaluated the quantification of isomiRs of altered length or compared the consistency of results derived from multiple moderate starting inputs. We therefore evaluated quantifications of miRNA and isomiRs using four library preparation kits, with various starting amounts, as well as quantifications following removal of duplicate reads using unique molecular identifiers (UMIs) to mitigate reverse transcription and amplification biases.
All methods resulted in false isomiR detection; however, the adapter-free method tested was especially prone to false isomiR detection. We demonstrate that using UMIs improves accuracy and we provide a guide for input amounts to improve consistency.
Our data show differences and limitations of current methods, thus raising concerns about the validity of quantification of miRNA and isomiRs across studies. We advocate for the use of UMIs to improve accuracy and reliability of miRNA quantifications.
Abstract
Multiplex single-molecule fluorescent in situ hybridization (smFISH) is a powerful method for validating RNA sequencing and emerging spatial transcriptomic data, but quantification remains a ...computational challenge. We present a framework for generating and analyzing smFISH data in complex tissues while overcoming autofluorescence and increasing multiplexing capacity. We developed dotdotdot (https://github.com/LieberInstitute/dotdotdot) as a corresponding software package to quantify RNA transcripts in single nuclei and perform differential expression analysis. We first demonstrate robustness of our platform in single mouse neurons by quantifying differential expression of activity-regulated genes. We then quantify spatial gene expression in human dorsolateral prefrontal cortex (DLPFC) using spectral imaging and dotdotdot to mask lipofuscin autofluorescence. We lastly apply machine learning to predict cell types and perform downstream cell type-specific expression analysis. In summary, we provide experimental workflows, imaging acquisition and analytic strategies for quantification and biological interpretation of smFISH data in complex tissues.
Gravitational potentials that change in time induce fluctuations in the observed cosmic microwave background (CMB) temperature. Cosmological structure moving transverse to our line of sight provides ...a specific example known as the moving lens effect. Here, we explore how the observed CMB temperature fluctuations, combined with the observed matter overdensity, can be used to infer the transverse velocity of cosmological structures on large scales. We show that near-future CMB surveys and galaxy surveys will have the statistical power to make a first detection of the moving lens effect, and we discuss applications for the reconstructed transverse velocity.
Weak lensing with sizes, magnitudes and shapes Alsing, Justin; Kirk, Donnacha; Heavens, Alan ...
Monthly Notices of the Royal Astronomical Society,
09/2015, Letnik:
452, Številka:
2
Journal Article
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Weak lensing can be observed through a number of effects on the images of distant galaxies; their shapes are sheared, sizes and fluxes (magnitudes) are magnified and positions on the sky are modified ...by the lensing field. Galaxy shapes probe the shear field whilst size, magnitude and number density probe the convergence field. Both contain cosmological information. In this paper, we are concerned with the magnification of sizes and magnitudes of individual galaxies as a probe of cosmic convergence. We develop a Bayesian approach for inferring the convergence field from measured sizes, magnitudes and redshifts and demonstrate that this inference requires detailed knowledge of the joint distribution of intrinsic sizes and magnitudes. We build a simple parametrized model for the size–magnitude distribution and estimate this distribution for CFHTLenS galaxies. In light of the measured distribution, we show that the typical dispersion on convergence estimation is ∼0.8, compared to ∼0.38 for shear. We discuss the possibility of physical systematics for magnification (similar to intrinsic alignments for shear) and compute the expected gains in the dark energy figure-of-merit (FoM) from combining magnification with shear for different scenarios regarding systematics: accounting for intrinsic alignments but no systematics for magnification, including magnification could improve the FoM by up to a factor of ∼2.5, whilst when accounting for physical systematics in both shear and magnification we anticipate a gain between ∼25 and ∼65 per cent. The fact that shear and magnification are subject to different systematics makes magnification an attractive complement to any cosmic shear analysis.
Late-onset Alzheimer’s disease (AD) is a complex age-related neurodegenerative disorder that likely involves epigenetic factors. To better understand the epigenetic state associated with AD, we ...surveyed 420,852 DNA methylation (DNAm) sites from neurotypical controls (
N
= 49) and late-onset AD patients (
N
= 24) across four brain regions (hippocampus, entorhinal cortex, dorsolateral prefrontal cortex and cerebellum). We identified 858 sites with robust differential methylation collectively annotated to 772 possible genes (FDR < 5%, within 10 kb). These sites were overrepresented in AD genetic risk loci (
p
= 0.00655) and were enriched for changes during normal aging (
p
< 2.2 × 10
−16
), and nearby genes were enriched for processes related to cell-adhesion, immunity, and calcium homeostasis (FDR < 5%). To functionally validate these associations, we generated and analyzed corresponding transcriptome data to prioritize 130 genes within 10 kb of the differentially methylated sites. These 130 genes were differentially expressed between AD cases and controls and their expression was associated with nearby DNAm (
p
< 0.05). This integrated analysis implicates novel genes in Alzheimer’s disease, such as
ANKRD30B
. These results highlight DNAm differences in Alzheimer’s disease that have gene expression correlates, further implicating DNAm as an epigenetic mechanism underlying pathological molecular changes associated with AD. Furthermore, our framework illustrates the value of integrating epigenetic and transcriptomic data for understanding complex disease.
Single-cell gene expression technologies are powerful tools to study cell types in the human brain, but efforts have largely focused on cortical brain regions. We therefore created a single-nucleus ...RNA-sequencing resource of 70,615 high-quality nuclei to generate a molecular taxonomy of cell types across five human brain regions that serve as key nodes of the human brain reward circuitry: nucleus accumbens, amygdala, subgenual anterior cingulate cortex, hippocampus, and dorsolateral prefrontal cortex. We first identified novel subpopulations of interneurons and medium spiny neurons (MSNs) in the nucleus accumbens and further characterized robust GABAergic inhibitory cell populations in the amygdala. Joint analyses across the 107 reported cell classes revealed cell-type substructure and unique patterns of transcriptomic dynamics. We identified discrete subpopulations of D1- and D2-expressing MSNs in the nucleus accumbens to which we mapped cell-type-specific enrichment for genetic risk associated with both psychiatric disease and addiction.
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•snRNA sequencing (70,615 nuclei) of 5 human brain regions with roles in reward•Characterization of the transcriptomic architecture across 107 cell classes•Genetic risk association for substance use phenotypes in specific cell populations•Interactive app for each brain region to explore genes of interest in cell classes
For this NeuroResource, >100 cell classes from five brain regions in the human reward circuitry are characterized by single-nucleus RNA sequencing, with interactive apps made available. The molecular relationships across this circuitry are described, and genetic risk for various psychiatric and substance use phenotypes is quantified across all cell classes.
We outline an ambitious project to characterize the genetic and epigenetic regulation of multiple facets of transcription in distinct brain regions across the human lifespan in samples of major ...neuropsychiatric disorders and controls. Initially focused on schizophrenia and mood disorders, the goal of this consortium is to elucidate the underlying molecular mechanisms of genetic associations with the goal of identifying novel therapeutic targets. The consortium currently consists of seven pharmaceutical companies and a not-for-profit medical research institution working as a precompetitive team to generate and analyze publicly available archival brain genomic data related to neuropsychiatric illness.
The BrainSeq precompetitive consortium of seven pharmaceutical companies harnesses genomics, transcriptomics, and epigenomics from multiple brain regions across the human lifespan for spatio-temporal analyses of molecular mechanisms associated with psychiatric risk loci, empowering finding therapeutic solutions for psychiatric disorders.
Genome-wide association studies (GWASs) have reported many single nucleotide polymorphisms (SNPs) associated with psychiatric disorders, but knowledge is lacking regarding molecular mechanisms. Here ...we show that risk alleles spanning multiple genes across the 10q24.32 schizophrenia-related locus are associated in the human brain selectively with an increase in the expression of both BLOC-1 related complex subunit 7 (BORCS7) and a previously uncharacterized, human-specific arsenite methyltransferase (AS3MT) isoform (AS3MT(d2d3)), which lacks arsenite methyltransferase activity and is more abundant in individuals with schizophrenia than in controls. Conditional-expression analysis suggests that BORCS7 and AS3MT(d2d3) signals are largely independent. GWAS risk SNPs across this region are linked with a variable number tandem repeat (VNTR) polymorphism in the first exon of AS3MT that is associated with the expression of AS3MT(d2d3) in samples from both Caucasians and African Americans. The VNTR genotype predicts promoter activity in luciferase assays, as well as DNA methylation within the AS3MT gene. Both AS3MT(d2d3) and BORCS7 are expressed in adult human neurons and astrocytes, and they are upregulated during human stem cell differentiation toward neuronal fates. Our results provide a molecular explanation for the prominent 10q24.32 locus association, including a novel and evolutionarily recent protein that is involved in early brain development and confers risk for psychiatric illness.
Combining size and shape in weak lensing Heavens, Alan; Alsing, Justin; Jaffe, Andrew H
Monthly Notices of the Royal Astronomical Society Letters,
07/2013, Letnik:
433, Številka:
1
Journal Article
Recenzirano
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Weak lensing alters the size of images with a similar magnitude to the distortion due to shear. Galaxy size probes the convergence field and shapes the shear field, both of which contain cosmological ...information. We show the gains expected in the dark energy figure of merit if galaxy size information is used in combination with galaxy shape. In any normal analysis of cosmic shear, galaxy sizes are also studied, so this is extra statistical information that comes for free and is currently unused. There are two main results in this Letter: first, we show that size measurement can be made uncorrelated with ellipticity measurement, thus allowing the full statistical gain from the combination, provided that √area is used as a size indicator; secondly, as a proof of concept, we show that when the relevant modes are noise dominated, as is the norm for lensing surveys, the gains are substantial, with improvements of about 68 per cent in the figure of merit expected when systematic errors are ignored. An approximate treatment of such systematics such as intrinsic alignments and size-magnitude correlations, respectively, suggests that a much better improvement in the dark energy figure of merit of even a factor of ∼4 may be achieved.
Schizophrenia polygenic risk is plausibly manifested by complex transcriptional dysregulation in the brain, involving networks of co-expressed and functionally related genes. The main purpose of this ...study was to identify and prioritize co-expressed gene sets in a hierarchical manner, based on the strength of the relationships with clinical diagnosis and with polygenic risk for schizophrenia. Weighted Gene Co-expression Network Analysis (WGCNA) was applied to RNA-quality-adjusted DLPFC RNA-Seq data from the LIBD Postmortem Human Brain Repository (90 controls, 74 schizophrenia cases; all Caucasians) to construct co-expression networks and detect "modules" of co-expressed genes. After multiple internal and external validation procedures, modules of selected interest were tested for enrichment in biological ontologies, for association with schizophrenia polygenic risk scores (PRSs) and with diagnosis, and also for enrichment in genes within the significant GWAS loci reported by the Psychiatric Genomic Consortium (PGC2). The association between schizophrenia genetic signals and modules of co-expression converged on one module showing not only a significant association with both diagnosis and PRS but also significant overlap with 36 PGC2 loci genes, deemed the strongest candidates for drug targets. This module contained many genes involved in synaptic signaling and neuroplasticity. Fifty-three PGC2 genes were in modules associated only with diagnosis and 59 in modules unrelated to diagnosis or PRS. Our study highlights complex relationships between gene co-expression networks in the brain and clinical state and polygenic risk for SCZ and provides a strategy for using this information in selecting and prioritizing potentially targetable gene sets for therapeutic drug development.
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