Transcriptional linkage analysis with in vivo AAV-Perturb-seq.

The ever-growing compendium of genetic variants associated with human pathologies demands new methods to study genotype-phenotype relationships in complex tissues in a high-throughput manner1,2. Here we introduce adeno-associated virus (AAV)-mediated direct in vivo single-cell CRISPR screening, termed AAV-Perturb-seq, a tuneable and broadly applicable method for transcriptional linkage analysis as well as high-throughput and high-resolution phenotyping of genetic perturbations in vivo. We applied AAV-Perturb-seq using gene editing and transcriptional inhibition to systematically dissect the phenotypic landscape underlying 22q11.2 deletion syndrome3,4 genes in the adult mouse brain prefrontal cortex. We identified three 22q11.2-linked genes involved in known and previously undescribed pathways orchestrating neuronal functions in vivo that explain approximately 40% of the transcriptional changes observed in a 22q11.2-deletion mouse model. Our findings suggest that the 22q11.2-deletion syndrome transcriptional phenotype found in mature neurons may in part be due to the broad dysregulation of a class of genes associated with disease susceptibility that are important for dysfunctional RNA processing and synaptic function. Our study establishes a flexible and scalable direct in vivo method to facilitate causal understanding of biological and disease mechanisms with potential applications to identify genetic interventions and therapeutic targets for treating disease.

Transcriptional reprogramming of skeletal muscle stem cells by the niche environment.

Adult stem cells are indispensable for tissue regeneration, but their function declines with age. The niche environment in which the stem cells reside plays a critical role in their function. However, quantification of the niche effect on stem cell function is lacking. Using muscle stem cells (MuSC) as a model, we show that aging leads to a significant transcriptomic shift in their subpopulations accompanied by locus-specific gain and loss of chromatin accessibility and DNA methylation. By combining in vivo MuSC transplantation and computational methods, we show that the expression of approximately half of all age-altered genes in MuSCs from aged male mice can be restored by exposure to a young niche environment. While there is a correlation between gene reversibility and epigenetic alterations, restoration of gene expression occurs primarily at the level of transcription. The stem cell niche environment therefore represents an important therapeutic target to enhance tissue regeneration in aging.

Noninvasive assessment of gut function using transcriptional recording sentinel cells.

Transcriptional recording by CRISPR spacer acquisition from RNA endows engineered Escherichia coli with synthetic memory, which through Record-seq reveals transcriptome-scale records. Microbial sentinels that traverse the gastrointestinal tract capture a wide range of genes and pathways that describe interactions with the host, including quantitative shifts in the molecular environment that result from alterations in the host diet, induced inflammation, and microbiome complexity. We demonstrate multiplexed recording using barcoded CRISPR arrays, enabling the reconstruction of transcriptional histories of isogenic bacterial strains in vivo. Record-seq therefore provides a scalable, noninvasive platform for interrogating intestinal and microbial physiology throughout the length of the intestine without manipulations to host physiology and can determine how single microbial genetic differences alter the way in which the microbe adapts to the host intestinal environment.

Model-based analysis of sample index hopping reveals its widespread artifacts in multiplexed single-cell RNA-sequencing.

Index hopping is the main cause of incorrect sample assignment of sequencing reads in multiplexed pooled libraries. We introduce a statistical model for estimating the sample index-hopping rate in multiplexed droplet-based single-cell RNA-seq data and for probabilistic inference of the true sample of origin of hopped reads. We analyze several datasets and estimate the sample index hopping probability to range between 0.003-0.009, a small number that counter-intuitively gives rise to a large fraction of phantom molecules - the fraction of phantom molecules exceeds 8% in more than 25% of samples and reaches as high as 85% in low-complexity samples. Phantom molecules lead to widespread complications in downstream analyses, including transcriptome mixing across cells, emergence of phantom copies of cells from other samples, and misclassification of empty droplets as cells. We demonstrate that our approach can correct for these artifacts by accurately purging the majority of phantom molecules from the data.

Legacy Data Confound Genomics Studies.

Recent reports have identified differences in the mutational spectra across human populations. Although some of these reports have been replicated in other cohorts, most have been reported only in the 1000 Genomes Project (1kGP) data. While investigating an intriguing putative population stratification within the Japanese population, we identified a previously unreported batch effect leading to spurious mutation calls in the 1kGP data and to the apparent population stratification. Because the 1kGP data are used extensively, we find that the batch effects also lead to incorrect imputation by leading imputation servers and a small number of suspicious GWAS associations. Lower quality data from the early phases of the 1kGP thus continue to contaminate modern studies in hidden ways. It may be time to retire or upgrade such legacy sequencing data.

TAF5L and TAF6L Maintain Self-Renewal of Embryonic Stem Cells via the MYC Regulatory Network.

Self-renewal and pluripotency of the embryonic stem cell (ESC) state are established and maintained by multiple regulatory networks that comprise transcription factors and epigenetic regulators. While much has been learned regarding transcription factors, the function of epigenetic regulators in these networks is less well defined. We conducted a CRISPR-Cas9-mediated loss-of-function genetic screen that identified two epigenetic regulators, TAF5L and TAF6L, components or co-activators of the GNAT-HAT complexes for the mouse ESC (mESC) state. Detailed molecular studies demonstrate that TAF5L/TAF6L transcriptionally activate c-Myc and Oct4 and their corresponding MYC and CORE regulatory networks. Besides, TAF5L/TAF6L predominantly regulate their target genes through H3K9ac deposition and c-MYC recruitment that eventually activate the MYC regulatory network for self-renewal of mESCs. Thus, our findings uncover a role of TAF5L/TAF6L in directing the MYC regulatory network that orchestrates gene expression programs to control self-renewal for the maintenance of mESC state.

AmpUMI: design and analysis of unique molecular identifiers for deep amplicon sequencing.

Motivation: Unique molecular identifiers (UMIs) are added to DNA fragments before PCR amplification to discriminate between alleles arising from the same genomic locus and sequencing reads produced by PCR amplification. While computational methods have been developed to take into account UMI information in genome-wide and single-cell sequencing studies, they are not designed for modern amplicon-based sequencing experiments, especially in cases of high allelic diversity. Importantly, no guidelines are provided for the design of optimal UMI length for amplicon-based sequencing experiments. Results: Based on the total number of DNA fragments and the distribution of allele frequencies, we present a model for the determination of the minimum UMI length required to prevent UMI collisions and reduce allelic distortion. We also introduce a user-friendly software tool called AmpUMI to assist in the design and the analysis of UMI-based amplicon sequencing studies. AmpUMI provides quality control metrics on frequency and quality of UMIs, and trims and deduplicates amplicon sequences with user specified parameters for use in downstream analysis. Availability and implementation: AmpUMI is open-source and freely available at http://github.com/pinellolab/AmpUMI.

Haystack: systematic analysis of the variation of epigenetic states and cell-type specific regulatory elements.

Motivation: With the increasing amount of genomic and epigenomic data in the public domain, a pressing challenge is to integrate these data to investigate the role of epigenetic mechanisms in regulating gene expression and maintenance of cell-identity. To this end, we have implemented a computational pipeline to systematically study epigenetic variability and uncover regulatory DNA sequences. Results: Haystack is a bioinformatics pipeline to identify hotspots of epigenetic variability across different cell-types, cell-type specific cis-regulatory elements, and associated transcription factors. Haystack is generally applicable to any epigenetic mark and provides an important tool to investigate the mechanisms underlying epigenetic switches during development. This software is accompanied by a set of precomputed tracks, which may be used as a valuable resource for functional annotation of the human genome. Availability and implementation: The Haystack pipeline is implemented as an open-source, multiplatform, Python package called haystack_bio freely available at https://github.com/pinellolab/haystack_bio. Contact: lpinello@mgh.harvard.edu or gcyuan@jimmy.harvard.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

ALTRE: workflow for defining ALTered Regulatory Elements using chromatin accessibility data.

Summary: Regulatory elements regulate gene transcription, and their location and accessibility is cell-type specific, particularly for enhancers. Mapping and comparing chromatin accessibility between different cell types may identify mechanisms involved in cellular development and disease progression. To streamline and simplify differential analysis of regulatory elements genome-wide using chromatin accessibility data, such as DNase-seq, ATAC-seq, we developed ALTRE ( ALT ered R egulatory E lements), an R package and associated R Shiny web app. ALTRE makes such analysis accessible to a wide range of users-from novice to practiced computational biologists. Availability and Implementation: https://github.com/Mathelab/ALTRE. Contact: ewy.mathe@osumc.edu. Supplementary information: Supplementary data are available at Bioinformatics online.