Author Correction: Discovery of stimulation-responsive immune enhancers with CRISPR activation.

In this Letter, analysis of steady-state regulatory T (Treg) cell percentages from Il2ra enhancer deletion (EDEL) and wild-type (WT) mice revealed no differences between them (Extended Data Fig. 9d). This analysis included two mice whose genotypes were incorrectly assigned. Even after correction of the genotypes, no significant differences in Treg cell percentages were seen when data across experimental cohorts were averaged (as was done in Extended Data Fig. 9d). However, if we normalize the corrected data to account for variation among experimental cohorts, a subtle decrease in EDEL Treg cell percentages is revealed and, using the corrected and normalized data, we have redrawn Extended Data Fig. 9d in Supplementary Fig. 1. The Supplementary Information to this Amendment contains the corrected and reanalysed Extended Data Fig. 9d. The sentence "This enhancer deletion (EDEL) strain also had no obvious T cell phenotypes at steady state (Extended Data Fig. 9)." should read: "This enhancer deletion (EDEL) strain had a small decrease in the percentage of Treg cells (Extended Data Fig. 9).". This error does not affect any of the main figures in the Letter or the data from mice with the human autoimmune-associated single nucleotide polymorphism (SNP) knocked in or with a 12-base-pair deletion at the site (12DEL). In addition, we stated in the Methods that we observed consistent immunophenotypes of EDEL mice across three founders, but in fact, we observed consistent phenotypes in mice from two founders. This does not change any of our conclusions and the original Letter has not been corrected.

Discovery of stimulation-responsive immune enhancers with CRISPR activation.

The majority of genetic variants associated with common human diseases map to enhancers, non-coding elements that shape cell-type-specific transcriptional programs and responses to extracellular cues. Systematic mapping of functional enhancers and their biological contexts is required to understand the mechanisms by which variation in non-coding genetic sequences contributes to disease. Functional enhancers can be mapped by genomic sequence disruption, but this approach is limited to the subset of enhancers that are necessary in the particular cellular context being studied. We hypothesized that recruitment of a strong transcriptional activator to an enhancer would be sufficient to drive target gene expression, even if that enhancer was not currently active in the assayed cells. Here we describe a discovery platform that can identify stimulus-responsive enhancers for a target gene independent of stimulus exposure. We used tiled CRISPR activation (CRISPRa) to synthetically recruit a transcriptional activator to sites across large genomic regions (more than 100 kilobases) surrounding two key autoimmunity risk loci, CD69 and IL2RA. We identified several CRISPRa-responsive elements with chromatin features of stimulus-responsive enhancers, including an IL2RA enhancer that harbours an autoimmunity risk variant. Using engineered mouse models, we found that sequence perturbation of the disease-associated Il2ra enhancer did not entirely block Il2ra expression, but rather delayed the timing of gene activation in response to specific extracellular signals. Enhancer deletion skewed polarization of naive T cells towards a pro-inflammatory T helper (TH17) cell state and away from a regulatory T cell state. This integrated approach identifies functional enhancers and reveals how non-coding variation associated with human immune dysfunction alters context-specific gene programs.

Expression reflects population structure.

Population structure in genotype data has been extensively studied, and is revealed by looking at the principal components of the genotype matrix. However, no similar analysis of population structure in gene expression data has been conducted, in part because a naïve principal components analysis of the gene expression matrix does not cluster by population. We identify a linear projection that reveals population structure in gene expression data. Our approach relies on the coupling of the principal components of genotype to the principal components of gene expression via canonical correlation analysis. Our method is able to determine the significance of the variance in the canonical correlation projection explained by each gene. We identify 3,571 significant genes, only 837 of which had been previously reported to have an associated eQTL in the GEUVADIS results. We show that our projections are not primarily driven by differences in allele frequency at known cis-eQTLs and that similar projections can be recovered using only several hundred randomly selected genes and SNPs. Finally, we present preliminary work on the consequences for eQTL analysis. We observe that using our projection co-ordinates as covariates results in the discovery of slightly fewer genes with eQTLs, but that these genes replicate in GTEx matched tissue at a slightly higher rate.

Differential analysis of RNA-seq incorporating quantification uncertainty.

We describe sleuth (http://pachterlab.github.io/sleuth), a method for the differential analysis of gene expression data that utilizes bootstrapping in conjunction with response error linear modeling to decouple biological variance from inferential variance. sleuth is implemented in an interactive shiny app that utilizes kallisto quantifications and bootstraps for fast and accurate analysis of data from RNA-seq experiments.

The Lair: a resource for exploratory analysis of published RNA-Seq data.

Increased emphasis on reproducibility of published research in the last few years has led to the large-scale archiving of sequencing data. While this data can, in theory, be used to reproduce results in papers, it is difficult to use in practice. We introduce a series of tools for processing and analyzing RNA-Seq data in the Sequence Read Archive, that together have allowed us to build an easily extendable resource for analysis of data underlying published papers. Our system makes the exploration of data easily accessible and usable without technical expertise. Our database and associated tools can be accessed at The Lair: http://pachterlab.github.io/lair .

kallisto, bustools, and kb-python for quantifying bulk, single-cell, and single-nucleus RNA-seq.

The term "RNA-seq" refers to a collection of assays based on sequencing experiments that involve quantifying RNA species from bulk tissue, from single cells, or from single nuclei. The kallisto, bustools, and kb-python programs are free, open-source software tools for performing this analysis that together can produce gene expression quantification from raw sequencing reads. The quantifications can be individualized for multiple cells, multiple samples, or both. Additionally, these tools allow gene expression values to be classified as originating from nascent RNA species or mature RNA species, making this workflow amenable to both cell-based and nucleus-based assays. This protocol describes in detail how to use kallisto and bustools in conjunction with a wrapper, kb-python, to preprocess RNA-seq data.

The impact of package selection and versioning on single-cell RNA-seq analysis.

Standard single-cell RNA-sequencing analysis (scRNA-seq) workflows consist of converting raw read data into cell-gene count matrices through sequence alignment, followed by analyses including filtering, highly variable gene selection, dimensionality reduction, clustering, and differential expression analysis. Seurat and Scanpy are the most widely-used packages implementing such workflows, and are generally thought to implement individual steps similarly. We investigate in detail the algorithms and methods underlying Seurat and Scanpy and find that there are, in fact, considerable differences in the outputs of Seurat and Scanpy. The extent of differences between the programs is approximately equivalent to the variability that would be introduced in benchmarking scRNA-seq datasets by sequencing less than 5% of the reads or analyzing less than 20% of the cell population. Additionally, distinct versions of Seurat and Scanpy can produce very different results, especially during parts of differential expression analysis. Our analysis highlights the need for users of scRNA-seq to carefully assess the tools on which they rely, and the importance of developers of scientific software to prioritize transparency, consistency, and reproducibility for their tools.

Voyager: exploratory single-cell genomics data analysis with geospatial statistics.

Exploratory spatial data analysis (ESDA) can be a powerful approach to understanding single-cell genomics datasets, but it is not yet part of standard data analysis workflows. In particular, geospatial analyses, which have been developed and refined for decades, have yet to be fully adapted and applied to spatial single-cell analysis. We introduce the Voyager platform, which systematically brings the geospatial ESDA tradition to (spatial) -omics, with local, bivariate, and multivariate spatial methods not yet commonly applied to spatial -omics, united by a uniform user interface. Using Voyager, we showcase biological insights that can be derived with its methods, such as biologically relevant negative spatial autocorrelation. Underlying Voyager is the SpatialFeatureExperiment data structure, which combines Simple Feature with SingleCellExperiment and AnnData to represent and operate on geometries bundled with gene expression data. Voyager has comprehensive tutorials demonstrating ESDA built on GitHub Actions to ensure reproducibility and scalability, using data from popular commercial technologies. Voyager is implemented in both R/Bioconductor and Python/PyPI, and features compatibility tests to ensure that both implementations return consistent results.

Controlled Cycling and Quiescence Enables Efficient HDR in Engraftment-Enriched Adult Hematopoietic Stem and Progenitor Cells.

Genome editing often takes the form of either error-prone sequence disruption by non-homologous end joining (NHEJ) or sequence replacement by homology-directed repair (HDR). Although NHEJ is generally effective, HDR is often difficult in primary cells. Here, we use a combination of immunophenotyping, next-generation sequencing, and single-cell RNA sequencing to investigate and reprogram genome editing outcomes in subpopulations of adult hematopoietic stem and progenitor cells. We find that although quiescent stem-enriched cells mostly use NHEJ, non-quiescent cells with the same immunophenotype use both NHEJ and HDR. Inducing quiescence before editing results in a loss of HDR in all cell subtypes. We develop a strategy of controlled cycling and quiescence that yields a 6-fold increase in the HDR/NHEJ ratio in quiescent stem cells ex vivo and in vivo. Our results highlight the tension between editing and cellular physiology and suggest strategies to manipulate quiescent cells for research and therapeutic genome editing.

A genome-wide map of conserved microRNA targets in C. elegans.

BACKGROUND: Metazoan miRNAs regulate protein-coding genes by binding the 3' UTR of cognate mRNAs. Identifying targets for the 115 known C. elegans miRNAs is essential for understanding their function. RESULTS: By using a new version of PicTar and sequence alignments of three nematodes, we predict that miRNAs regulate at least 10% of C. elegans genes through conserved interactions. We have developed a new experimental pipeline to assay 3' UTR-mediated posttranscriptional gene regulation via an endogenous reporter expression system amenable to high-throughput cloning, demonstrating the utility of this system using one of the most intensely studied miRNAs, let-7. Our expression analyses uncover several new potential let-7 targets and suggest a new let-7 activity in head muscle and neurons. To explore genome-wide trends in miRNA function, we analyzed functional categories of predicted target genes, finding that one-third of C. elegans miRNAs target gene sets are enriched for specific functional annotations. We have also integrated miRNA target predictions with other functional genomic data from C. elegans. CONCLUSIONS: At least 10% of C. elegans genes are predicted miRNA targets, and a number of nematode miRNAs seem to regulate biological processes by targeting functionally related genes. We have also developed and successfully utilized an in vivo system for testing miRNA target predictions in likely endogenous expression domains. The thousands of genome-wide miRNA target predictions for nematodes, humans, and flies are available from the PicTar website and are linked to an accessible graphical network-browsing tool allowing exploration of miRNA target predictions in the context of various functional genomic data resources.

Gene-level differential analysis at transcript-level resolution.

Compared to RNA-sequencing transcript differential analysis, gene-level differential expression analysis is more robust and experimentally actionable. However, the use of gene counts for statistical analysis can mask transcript-level dynamics. We demonstrate that 'analysis first, aggregation second,' where the p values derived from transcript analysis are aggregated to obtain gene-level results, increase sensitivity and accuracy. The method we propose can also be applied to transcript compatibility counts obtained from pseudoalignment of reads, which circumvents the need for quantification and is fast, accurate, and model-free. The method generalizes to various levels of biology and we showcase an application to gene ontologies.

Disabling Cas9 by an anti-CRISPR DNA mimic.

CRISPR (clustered regularly interspaced short palindromic repeats)-Cas9 gene editing technology is derived from a microbial adaptive immune system, where bacteriophages are often the intended target. Natural inhibitors of CRISPR-Cas9 enable phages to evade immunity and show promise in controlling Cas9-mediated gene editing in human cells. However, the mechanism of CRISPR-Cas9 inhibition is not known, and the potential applications for Cas9 inhibitor proteins in mammalian cells have not been fully established. We show that the anti-CRISPR protein AcrIIA4 binds only to assembled Cas9-single-guide RNA (sgRNA) complexes and not to Cas9 protein alone. A 3.9 Å resolution cryo-electron microscopy structure of the Cas9-sgRNA-AcrIIA4 complex revealed that the surface of AcrIIA4 is highly acidic and binds with a 1:1 stoichiometry to a region of Cas9 that normally engages the DNA protospacer adjacent motif. Consistent with this binding mode, order-of-addition experiments showed that AcrIIA4 interferes with DNA recognition but has no effect on preformed Cas9-sgRNA-DNA complexes. Timed delivery of AcrIIA4 into human cells as either protein or expression plasmid allows on-target Cas9-mediated gene editing while reducing off-target edits. These results provide a mechanistic understanding of AcrIIA4 function and demonstrate that inhibitors can modulate the extent and outcomes of Cas9-mediated gene editing.

Nanoparticle delivery of Cas9 ribonucleoprotein and donor DNA in vivo induces homology-directed DNA repair.

CRISPR/Cas9-based therapeutics, especially those that can correct gene mutations via homology directed repair (HDR), have the potential to revolutionize the treatment of genetic diseases. However, HDR-based therapeutics are challenging to develop because they require simultaneous in vivo delivery of Cas9 protein, guide RNA and donor DNA. Here, we demonstrate that a delivery vehicle composed of gold nanoparticles conjugated to DNA and complexed with cationic endosomal disruptive polymers can deliver Cas9 ribonucleoprotein and donor DNA into a wide variety of cell types, and efficiently correct the DNA mutation that causes Duchenne muscular dystrophy in mice via local injection, with minimal off-target DNA damage.

MAVID multiple alignment server.

MAVID is a multiple alignment program suitable for many large genomic regions. The MAVID web server allows biomedical researchers to quickly obtain multiple alignments for genomic sequences and to subsequently analyse the alignments for conserved regions. MAVID has been successfully used for the alignment of closely related species such as primates and also for the alignment of more distant organisms such as human and fugu. The server is fast, capable of aligning hundreds of kilobases in less than a minute. The multiple alignment is used to build a phylogenetic tree for the sequences, which is subsequently used as a basis for identifying conserved regions in the alignment. The server can be accessed at http://baboon.math.berkeley.edu/mavid/.

Near-optimal probabilistic RNA-seq quantification.

We present kallisto, an RNA-seq quantification program that is two orders of magnitude faster than previous approaches and achieves similar accuracy. Kallisto pseudoaligns reads to a reference, producing a list of transcripts that are compatible with each read while avoiding alignment of individual bases. We use kallisto to analyze 30 million unaligned paired-end RNA-seq reads in <10 min on a standard laptop computer. This removes a major computational bottleneck in RNA-seq analysis.

Selection-free genome editing of the sickle mutation in human adult hematopoietic stem/progenitor cells.

Genetic diseases of blood cells are prime candidates for treatment through ex vivo gene editing of CD34+ hematopoietic stem/progenitor cells (HSPCs), and a variety of technologies have been proposed to treat these disorders. Sickle cell disease (SCD) is a recessive genetic disorder caused by a single-nucleotide polymorphism in the ß-globin gene (HBB). Sickle hemoglobin damages erythrocytes, causing vasoocclusion, severe pain, progressive organ damage, and premature death. We optimize design and delivery parameters of a ribonucleoprotein (RNP) complex comprising Cas9 protein and unmodified single guide RNA, together with a single-stranded DNA oligonucleotide donor (ssODN), to enable efficient replacement of the SCD mutation in human HSPCs. Corrected HSPCs from SCD patients produced less sickle hemoglobin RNA and protein and correspondingly increased wild-type hemoglobin when differentiated into erythroblasts. When engrafted into immunocompromised mice, ex vivo treated human HSPCs maintain SCD gene edits throughout 16 weeks at a level likely to have clinical benefit. These results demonstrate that an accessible approach combining Cas9 RNP with an ssODN can mediate efficient HSPC genome editing, enables investigator-led exploration of gene editing reagents in primary hematopoietic stem cells, and suggests a path toward the development of new gene editing treatments for SCD and other hematopoietic diseases.

A high-resolution atlas of nucleosome occupancy in yeast.

We present the first complete high-resolution map of nucleosome occupancy across the whole Saccharomyces cerevisiae genome, identifying over 70,000 positioned nucleosomes occupying 81% of the genome. On a genome-wide scale, the persistent nucleosome-depleted region identified previously in a subset of genes demarcates the transcription start site. Both nucleosome occupancy signatures and overall occupancy correlate with transcript abundance and transcription rate. In addition, functionally related genes can be clustered on the basis of the nucleosome occupancy patterns observed at their promoters. A quantitative model of nucleosome occupancy indicates that DNA structural features may account for much of the global nucleosome occupancy.

MAVID: constrained ancestral alignment of multiple sequences.

We describe a new global multiple-alignment program capable of aligning a large number of genomic regions. Our progressive-alignment approach incorporates the following ideas: maximum-likelihood inference of ancestral sequences, automatic guide-tree construction, protein-based anchoring of ab-initio gene predictions, and constraints derived from a global homology map of the sequences. We have implemented these ideas in the MAVID program, which is able to accurately align multiple genomic regions up to megabases long. MAVID is able to effectively align divergent sequences, as well as incomplete unfinished sequences. We demonstrate the capabilities of the program on the benchmark CFTR region, which consists of 1.8 Mb of human sequence and 20 orthologous regions in marsupials, birds, fish, and mammals. Finally, we describe two large MAVID alignments, an alignment of all the available HIV genomes and a multiple alignment of the entire human, mouse, and rat genomes.

Strategies and tools for whole-genome alignments.

The availability of the assembled mouse genome makes possible, for the first time, an alignment and comparison of two large vertebrate genomes. We investigated different strategies of alignment for the subsequent analysis of conservation of genomes that are effective for assemblies of different quality. These strategies were applied to the comparison of the working draft of the human genome with the Mouse Genome Sequencing Consortium assembly, as well as other intermediate mouse assemblies. Our methods are fast and the resulting alignments exhibit a high degree of sensitivity, covering more than 90% of known coding exons in the human genome. We obtained such coverage while preserving specificity. With a view towards the end user, we developed a suite of tools and Web sites for automatically aligning and subsequently browsing and working with whole-genome comparisons. We describe the use of these tools to identify conserved non-coding regions between the human and mouse genomes, some of which have not been identified by other methods.