Single-cell analysis reveals the Comma-1D cell line as a unique model for mammary gland development and breast cancer.

The mammary gland epithelial tree contains two distinct cell populations, luminal and basal. The investigation of how this heterogeneity is developed and how it influences tumorigenesis has been hampered by the need to perform studies on these populations using animal models. Comma-1D is an immortalized mouse mammary epithelial cell line that has unique morphogenetic properties. By performing single-cell RNA-seq studies, we found that Comma-1D cultures consist of two main populations with luminal and basal features, and a smaller population with mixed lineage and bipotent characteristics. We demonstrated that multiple transcription factors associated with the differentiation of the mammary epithelium in vivo also modulate this process in Comma-1D cultures. Additionally, we found that only cells with luminal features were able to acquire transformed characteristics after an oncogenic HER2 (also known as ERBB2) mutant was introduced in their genomes. Overall, our studies characterize, at a single-cell level, the heterogeneity of the Comma-1D cell line and illustrate how Comma-1D cells can be used as an experimental model to study both the differentiation and the transformation processes in vitro.

Accurate genomic variant detection in single cells with primary template-directed amplification.

Improvements in whole genome amplification (WGA) would enable new types of basic and applied biomedical research, including studies of intratissue genetic diversity that require more accurate single-cell genotyping. Here, we present primary template-directed amplification (PTA), an isothermal WGA method that reproducibly captures >95% of the genomes of single cells in a more uniform and accurate manner than existing approaches, resulting in significantly improved variant calling sensitivity and precision. To illustrate the types of studies that are enabled by PTA, we developed direct measurement of environmental mutagenicity (DMEM), a tool for mapping genome-wide interactions of mutagens with single living human cells at base-pair resolution. In addition, we utilized PTA for genome-wide off-target indel and structural variant detection in cells that had undergone CRISPR-mediated genome editing, establishing the feasibility for performing single-cell evaluations of biopsies from edited tissues. The improved precision and accuracy of variant detection with PTA overcomes the current limitations of accurate WGA, which is the major obstacle to studying genetic diversity and evolution at cellular resolution.

Integrome signatures of lentiviral gene therapy for SCID-X1 patients.

Lentiviral vector (LV)-based gene therapy holds promise for a broad range of diseases. Analyzing more than 280,000 vector integration sites (VISs) in 273 samples from 10 patients with X-linked severe combined immunodeficiency (SCID-X1), we discovered shared LV integrome signatures in 9 of 10 patients in relation to the genomics, epigenomics, and 3D structure of the human genome. VISs were enriched in the nuclear subcompartment A1 and integrated into super-enhancers close to nuclear pore complexes. These signatures were validated in T cells transduced with an LV encoding a CD19-specific chimeric antigen receptor. Intriguingly, the one patient whose VISs deviated from the identified integrome signatures had a distinct clinical course. Comparison of LV and gamma retrovirus integromes regarding their 3D genome signatures identified differences that might explain the lower risk of insertional mutagenesis in LV-based gene therapy. Our findings suggest that LV integrome signatures, shaped by common features such as genome organization, may affect the efficacy of LV-based cellular therapies.

Convergent evolution and multi-wave clonal invasion in H3 K27-altered diffuse midline gliomas treated with a PDGFR inhibitor.

The majority of diffuse midline gliomas, H3 K27-altered (DMG-H3 K27-a), are infiltrating pediatric brain tumors that arise in the pons with no effective treatment. To understand how clonal evolution contributes to the tumor's invasive spread, we performed exome sequencing and SNP array profiling on 49 multi-region autopsy samples from 11 patients with pontine DMG-H3 K27-a enrolled in a phase I clinical trial of PDGFR inhibitor crenolanib. For each patient, a phylogenetic tree was constructed by testing multiple possible clonal evolution models to select the one consistent with somatic mutations and copy number variations across all tumor regions. The tree was then used to deconvolute subclonal composition and prevalence at each tumor region to study convergent evolution and invasion patterns. Somatic variants in the PI3K pathway, a late event, are enriched in our cohort, affecting 70% of patients. Convergent evolution of PI3K at distinct phylogenetic branches was detected in 40% of the patients. 24 (~ 50%) of tumor regions were occupied by subclones of mixed lineages with varying molecular ages, indicating multiple waves of invasion across the pons and extrapontine. Subclones harboring a PDGFRA amplicon, including one that amplified a PDGRFAY849C mutant allele, were detected in four patients; their presence in extrapontine tumor and normal brain samples imply their involvement in extrapontine invasion. Our study expands the current knowledge on tumor invasion patterns in DMG-H3 K27-a, which may inform the design of future clinical trials.

The miR-424(322)/503 gene cluster regulates pro- versus anti-inflammatory skin DC subset differentiation by modulating TGF-ß signaling.

Transforming growth factor ß (TGF-ß) family ligands are key regulators of dendritic cell (DC) differentiation and activation. Epidermal Langerhans cells (LCs) require TGF-ß family signaling for their differentiation, and canonical TGF-ß1 signaling secures a non-activated LC state. LCs reportedly control skin inflammation and are replenished from peripheral blood monocytes, which also give rise to pro-inflammatory monocyte-derived DCs (moDCs). By studying mechanisms in inflammation, we previously screened LCs versus moDCs for differentially expressed microRNAs (miRNAs). This revealed that miR-424/503 is the most strongly inversely regulated (moDCs > LCs). We here demonstrate that miR-424/503 is induced during moDC differentiation and promotes moDC differentiation in human and mouse. Inversely, forced repression of miR-424 during moDC differentiation facilitates TGF-ß1-dependent LC differentiation. Mechanistically, miR-424/503 deficiency in monocyte/DC precursors leads to the induction of TGF-ß1 response genes critical for LC differentiation. Therefore, the miR-424/503 gene cluster plays a decisive role in anti-inflammatory LC versus pro-inflammatory moDC differentiation from monocytes.

SequencErr: measuring and suppressing sequencer errors in next-generation sequencing data.

BACKGROUND: There is currently no method to precisely measure the errors that occur in the sequencing instrument/sequencer, which is critical for next-generation sequencing applications aimed at discovering the genetic makeup of heterogeneous cellular populations. RESULTS: We propose a novel computational method, SequencErr, to address this challenge by measuring the base correspondence between overlapping regions in forward and reverse reads. An analysis of 3777 public datasets from 75 research institutions in 18 countries revealed the sequencer error rate to be ~ 10 per million (pm) and 1.4% of sequencers and 2.7% of flow cells have error rates > 100 pm. At the flow cell level, error rates are elevated in the bottom surfaces and > 90% of HiSeq and NovaSeq flow cells have at least one outlier error-prone tile. By sequencing a common DNA library on different sequencers, we demonstrate that sequencers with high error rates have reduced overall sequencing accuracy, and removal of outlier error-prone tiles improves sequencing accuracy. We demonstrate that SequencErr can reveal novel insights relative to the popular quality control method FastQC and achieve a 10-fold lower error rate than popular error correction methods including Lighter and Musket. CONCLUSIONS: Our study reveals novel insights into the nature of DNA sequencing errors incurred on DNA sequencers. Our method can be used to assess, calibrate, and monitor sequencer accuracy, and to computationally suppress sequencer errors in existing datasets.

Integrative network analysis reveals USP7 haploinsufficiency inhibits E-protein activity in pediatric T-lineage acute lymphoblastic leukemia (T-ALL).

USP7, which encodes a deubiquitylating enzyme, is among the most frequently mutated genes in pediatric T-ALL, with somatic heterozygous loss-of-function mutations (haploinsufficiency) predominantly affecting the subgroup that has aberrant TAL1 oncogene activation. Network analysis of > 200 T-ALL transcriptomes linked USP7 haploinsufficiency with decreased activities of E-proteins. E-proteins are also negatively regulated by TAL1, leading to concerted down-regulation of E-protein target genes involved in T-cell development. In T-ALL cell lines, we showed the physical interaction of USP7 with E-proteins and TAL1 by mass spectrometry and ChIP-seq. Haploinsufficient but not complete CRISPR knock-out of USP7 showed accelerated cell growth and validated transcriptional down-regulation of E-protein targets. Our study unveiled the synergistic effect of USP7 haploinsufficiency with aberrant TAL1 activation on T-ALL, implicating USP7 as a haploinsufficient tumor suppressor in T-ALL. Our findings caution against a universal oncogene designation for USP7 while emphasizing the dosage-dependent consequences of USP7 inhibitors currently under development as potential cancer therapeutics.

A comparison of methods accounting for batch effects in differential expression analysis of UMI count based single cell RNA sequencing.

Accounting for batch effects, especially latent batch effects, in differential expression (DE) analysis is critical for identifying true biological effects. Single-cell RNA sequencing (scRNA-seq) is a powerful tool for quantifying cell-to-cell variation in transcript abundance and characterizing cellular dynamics. Although many scRNA-seq DE analysis methods accommodate known batch variables, their performance has not been systematically evaluated. Moreover, the challenge of accounting for latent batch variables in scRNA-seq DE analysis is largely unmet. In contrast, many methods have been developed to account for batch variables (either known or latent) in other high-dimensional data, especially bulk RNA-seq. We extensively evaluate 11 methods for batch variables in different scRNA-seq DE analysis scenarios, with a primary focus on latent batch variables. We demonstrate that for known batch variables, incorporating them as covariates into a regression model outperformed approaches using a batch-corrected matrix. For latent batches, fixed effects models have inflated FDRs, whereas aggregation-based methods and mixed effects models have significant power loss. Surrogate variable based methods generally control the FDR well while achieving good power with small group effects. However, their performance (except that of SVA) deteriorated substantially in scenarios involving large group effects and/or group label impurity. In these settings, SVA achieves relatively good performance despite an occasionally inflated FDR (up to 0.2). Finally we make the following recommendations for scRNA-seq DE analysis: 1) incorporate known batch variables instead of using batch-corrected data; and 2) employ SVA for latent batch correction. However, better methods are still needed to fully unleash the power of scRNA-seq.

Clinical genome sequencing uncovers potentially targetable truncations and fusions of MAP3K8 in spitzoid and other melanomas.

Spitzoid melanoma is a specific morphologic variant of melanoma that most commonly affects children and adolescents, and ranges on the spectrum of malignancy from low grade to overtly malignant. These tumors are generally driven by fusions of ALK, RET, NTRK1/3, MET, ROS1 and BRAF1,2. However, in approximately 50% of cases no genetic driver has been established2. Clinical whole-genome and transcriptome sequencing (RNA-Seq) of a spitzoid tumor from an adolescent revealed a novel gene fusion of MAP3K8, encoding a serine-threonine kinase that activates MEK3,4. The patient, who had exhausted all other therapeutic options, was treated with a MEK inhibitor and underwent a transient clinical response. We subsequently analyzed spitzoid tumors from 49 patients by RNA-Seq and found in-frame fusions or C-terminal truncations of MAP3K8 in 33% of cases. The fusion transcripts and truncated genes all contained MAP3K8 exons 1-8 but lacked the autoinhibitory final exon. Data mining of RNA-Seq from the Cancer Genome Atlas (TCGA) uncovered analogous MAP3K8 rearrangements in 1.5% of adult melanomas. Thus, MAP3K8 rearrangements-uncovered by comprehensive clinical sequencing of a single case-are the most common genetic event in spitzoid melanoma, are present in adult melanomas and could be amenable to MEK inhibition.