Ines Hellmann

• Ludwig-Maximilians-Universität in Munich

The identification of cell types remains a major challenge. Even after a decade of single-cell RNA sequencing (scRNA-seq), reasonable cell type annotations almost always include manual non-automated steps. The identification of orthologous cell types across species complicates matters even more, but at the same time strengthens the confidence in th...

The identification of cell types remains a major challenge. Even after a decade of single-cell RNA sequencing (scRNA-seq), reasonable cell type annotations almost always include manual non-automated steps. The identification of orthologous cell types across species complicates matters even more, but at the same time strengthens the confidence in th...

The identification of cell types remains a major challenge. Even after a decade of single-cell RNA sequencing (scRNA-seq), reasonable cell type annotations almost always include manual non-automated steps. The identification of orthologous cell types across species complicates matters even more, but at the same time strengthens the confidence in th...

Pleiotropy, measured as expression breadth across tissues, is one of the best predictors for protein sequence and expression conservation. In this study, we investigated its effect on the evolution of cis -regulatory elements (CREs). To this end, we carefully reanalyzed the Epigenomics Roadmap data for nine fetal tissues, assigning a measure of ple...

Pleiotropy, measured as expression breadth across tissues, is one of the best predictors for protein sequence and expression conservation. In this study, we investigated its effect on the evolution of cis-regulatory elements (CREs). To this end, we carefully reanalyzed the Epigenomics Roadmap data for nine fetal tissues, assigning a measure of plei...

Background In droplet-based single-cell and single-nucleus RNA-seq experiments, not all reads associated with one cell barcode originate from the encapsulated cell. Such background noise is attributed to spillage from cell-free ambient RNA or barcode swapping events. Results Here, we characterize this background noise exemplified by three scRNA-se...

Brain size and cortical folding have increased and decreased recurrently during mammalian evolution. Identifying genetic elements whose sequence or functional properties co-evolve with these traits can provide unique information on evolutionary and developmental mechanisms. A good candidate for such a comparative approach is TRNP1, as it controls p...

Acute myeloid leukemia (AML) patients suffer dismal prognosis upon treatment resistance. To study functional heterogeneity of resistance, we generated serially transplantable patient-derived xenograft (PDX) models from one patient with AML and twelve clones thereof, each derived from a single stem cell, as proven by genetic barcoding. Transcriptome...

BACKGROUND: In droplet-based single-cell and single-nucleus RNA-seq experiments, not all reads associated with one cell barcode originate from the encapsulated cell. Such background noise is attributed to spillage from cell-free ambient RNA or barcode swapping events. Here, we perform an in-depth characterization of this background noise exemplifie...

Cost-efficient library generation by early barcoding has been central in propelling single-cell RNA sequencing. Here, we optimize and validate prime-seq, an early barcoding bulk RNA-seq method. We show that it performs equivalently to TruSeq, a standard bulk RNA-seq method, but is fourfold more cost-efficient due to almost 50-fold cheaper library c...

Aggressive brain tumors like glioblastoma depend on support by their local environment and subsets of tumor-parenchymal cells may promote specific phases of disease-progression. We investigated the glioblastoma microenvironment with transgenic lineage-tracing models, intravital imaging, single-cell transcriptomics, immunofluorescence analysis as we...

With the advent of Next Generation Sequencing, RNA-sequencing (RNA-seq) has become the major method for quantitative gene expression analysis. Reducing library costs by early barcoding has propelled single-cell RNA-seq, but has not yet caught on for bulk RNA-seq. Here, we optimized and validated a bulk RNA-seq method we call prime-seq. We show that...

Aggressive brain tumors like glioblastoma depend on support by their local environment and subsets of tumor parenchymal cells may promote specific phases of disease progression. We investigated the glioblastoma microenvironment with transgenic lineage-tracing models, intravital imaging, single-cell transcriptomics, immunofluorescence analysis as we...

Human pluripotent stem cells (PSCs) express human endogenous retrovirus type-H (HERV-H), which exists as more than a thousand copies on the human genome and frequently produces chimeric transcripts as long-non-coding RNAs (lncRNAs) fused with downstream neighbor genes. Previous studies showed that HERV-H expression is required for the maintenance o...

e14044 Background: Aggressive brain tumors like glioblastoma depend on support by their local environment. While the role of tumor-associated myeloid cells on glioblastoma progression is well-documented, we have only partial knowledge of the pathological impact of glioblastoma -parenchymal progenitor cells. Methods: We investigated the glioblastoma...

gmcSCRB-seq is an alternative lysis protocol to mcSCRB-seq (Publication and Protocol). gmcSCRB-seq uses Guanidine Hydrochloride in the lysis buffer and requires an additional cean up step. We recommend using this alternative lysis protocol in cases where cells are difficult to lyse or where the DNA appears degraded following the pre-amplification s...

gmcSCRB-seq is an alternative lysis protocol to mcSCRB-seq (Publication and Protocol). gmcSCRB-seq uses Guanidine Hydrochloride in the lysis buffer and requires an additional cean up step. We recommend using this alternative lysis protocol in cases where cells are difficult to lyse or where the DNA appears degraded following the pre-amplification s...

The 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 system...

Single-cell RNA sequencing (scRNA-seq) has emerged as a central method to characterize cellular identities and processes. However, as there is no optimal, one-size-fits all protocol, various inherent strengths and trade-offs exist. Among flexible, plate-based methods, “Single-Cell RNA-Barcoding and Sequencing” (SCRB-seq) is one of the most powerful...

Single-cell RNA sequencing (scRNA-seq) has emerged as a central genome-wide method to characterize cellular identities and processes. Consequently, improving its sensitivity, flexibility, and cost-efficiency can advance many research questions. Among the flexible plate-based methods, single-cell RNA barcoding and sequencing (SCRB-seq) is highly sen...

Background Single cell RNA-seq (scRNA-seq) experiments typically analyze hundreds or thousands of cells after amplification of the cDNA. The high throughput is made possible by the early introduction of sample-specific barcodes (BCs) and the amplification bias is alleviated by unique molecular identifiers (UMIs). Thus the ideal analysis pipeline fo...

Single-cell RNA sequencing (scRNA-seq) has emerged as a central genome-wide method to characterize cellular identities and processes. Consequently, improving its sensitivity, flexibility and cost-efficiency can advance many research questions. Among the flexible plate-based methods, “Single-Cell RNA-Barcoding and Sequencing” (SCRB-seq) is one of th...

With the growing appreciation for the role of regulatory differences in evolution, researchers need to reliably quantify expression levels within and among species. However, for non-model organisms genome assemblies and annotations are often not available or have inferior quality, biasing the inference of expression changes to an unknown extent. He...

Single cell RNA-seq (scRNA-seq) experiments typically analyze hundreds or thousands of cells after amplification of the cDNA. The high throughput is made possible by the early introduction of sample-specific barcodes (BCs) and the amplification bias is alleviated by unique molecular identifiers (UMIs). Thus the ideal analysis pipeline for scRNA-seq...

Single-cell RNA sequencing (scRNA-seq) is currently transforming our understanding of biology, as it is a powerful tool to resolve cellular heterogeneity and molecular networks. Over 50 protocols have been developed in recent years and also data processing and analyzes tools are evolving fast. Here, we review the basic principles underlying the dif...

Single-cell RNA sequencing (scRNA-seq) has emerged as a central genome-wide method to characterize cellular identities and processes. Consequently, improving its sensitivity, flexibility and cost-efficiency can advance many research questions. Among the flexible plate-based methods, “Single-Cell RNA-Barcoding and Sequencing” (SCRB-seq) is one of th...

Single-cell RNA sequencing (scRNA-seq) has emerged as the central genome-wide method to characterize cellular identities and processes. While performance of scRNA-seq methods is improving, an optimum in terms of sensitivity, cost-efficiency and flexibility has not yet been reached. Among the flexible plate-based methods “Single-Cell RNA-Barcoding a...

Background The association of active transcription regulatory elements (TREs) with DNAse I hypersensitivity (DHS[+]) and an ‘open’ local chromatin configuration has long been known. However, the 3D topography of TREs within the nuclear landscape of individual cells in relation to their active or inactive status has remained elusive. Here, we explor...

Power analysis is essential to optimize the design of RNA-seq experiments and to assess and compare the power to detect differentially expressed genes in RNA-seq data. PowsimR is a flexible tool to simulate and evaluate differential expression from bulk and especially single-cell RNA-seq data making it suitable for a priori and posterior power anal...

One of the major functions of DNA methylation is the repression of transposable elements, such as the long-interspersed nuclear element 1 (L1). The underlying mechanism(s), however, are unclear. Here, we addressed how retrotransposon activation and mobilization are regulated by methyl-cytosine modifying ten-eleven-translocation (Tet) proteins and h...

Single-cell RNA sequencing (scRNA-seq) offers new possibilities to address biological and medical questions. However, systematic comparisons of the performance of diverse scRNA-seq protocols are lacking. We generated data from 583 mouse embryonic stem cells to evaluate six prominent scRNA-seq methods: CEL-seq2, Drop-seq, MARS-seq, SCRB-seq, Smart-s...

Aberrant DNA methylation is a hallmark of various human disorders, indicating that the spatial and temporal regulation of methylation readers and modifiers is imperative for development and differentiation. In particular, the cross-regulation between 5-methylcytosine binders (MBD) and modifiers (Tet) has not been investigated. Here, we show that bi...

Currently, quantitative RNA-seq methods are pushed to work with increasingly small starting amounts of RNA that require amplification. However, it is unclear how much noise or bias amplification introduces and how this affects precision and accuracy of RNA quantification. To assess the effects of amplification, reads that originated from the same R...

Background Single-cell RNA sequencing (scRNA-seq) offers exciting possibilities to address biological and medical questions, but a systematic comparison of recently developed protocols is still lacking. Results We generated data from 447 mouse embryonic stem cells using Drop-seq, SCRB-seq, Smart-seq (on Fluidigm C1) and Smart-seq2 and analyzed exi...

Appendix S1. Command line for msms (Ewing & Hermisson 2010) simulations. Fig. S1 Power of the CLR tests for data with different levels of divergence from the outgroup. Fig. S2 Boxplot of the distribution of the number of segregating sites for the 18 different bottleneck scenarios, calculated for the simulated 100 kb sequence and 200 replications...

Background Currently quantitative RNA-Seq methods are pushed to work with increasingly small starting amounts of RNA that require PCR amplification to generate libraries. However, it is unclear how much noise or bias amplification introduces and how this effects precision and accuracy of RNA quantification. To assess the effects of amplification,...

A composite likelihood ratio test implemented in the program SweepFinder is a commonly used method for scanning a genome for recent selective sweeps. SweepFinder uses information on the spatial pattern (along the chromosome) of the site frequency spectrum (SFS) around the selected locus. To avoid confounding effects of background selection and vari...

SweepFinder is a popular program that implements a powerful likelihood-based method for detecting recent positive selection, or selective sweeps. Here, we present SweepFinder2, an extension of SweepFinder with increased sensitivity and robustness to the confounding effects of mutation rate variation and background selection, as well as increased fl...

SweepFinder is a popular program that implements a powerful likelihood-based method for detecting recent positive selection, or selective sweeps. Here, we present SweepFinder2, an extension of SweepFinder with increased sensitivity and robustness to the confounding effects of mutation rate variation and background selection, as well as increased fl...

A composite likelihood ratio test implemented in the program SweepFinder is a commonly used method for scanning a genome for recent selective sweeps. SweepFinder uses information on the spatial pattern of the site frequency spectrum (SFS) around the selected locus. To avoid confounding effects of background selection and variation in the mutation p...

Detecting positive selection in species with heterogeneous habitats and complex demography is notoriously difficult and prone to statistical biases. The model plant Arabidopsis thaliana exemplifies this problem: in spite of the large amounts of data, little evidence for classic selective sweeps has been found. Moreover, many aspects of the demograp...

We present a high-quality genome sequence of a Neanderthal woman from Siberia. We show that her parents were related at the level of half-siblings and that mating among close relatives was common among her recent ancestors. We also sequenced the genome of a Neanderthal from the Caucasus to low coverage. An analysis of the relationships and populati...

Despite advances in sequencing, the goal of obtaining a comprehensive view of genetic variation in populations is still far from reached. We sequenced 180 lines of A. thaliana from Sweden to obtain as complete a picture as possible of variation in a single region. Whereas simple polymorphisms in the unique portion of the genome are readily identifi...

Two African apes are the closest living relatives of humans: the chimpanzee (Pan troglodytes) and the bonobo (Pan paniscus). Although they are similar in many respects, bonobos and chimpanzees differ strikingly in key social and sexual behaviours, and for some of these traits they show more similarity with humans than with each other. Here we repor...

Correlations between the average MAF among the three different datasets. The red line denotes the lowess curve fit to the two variables. The value of Spearman's for each pairwise correlation is shown in each panel. Note that several outlier data points fell outside the plotting area. (TIFF)

Correlations between the number of bases covered per window among the three different datasets. The red line denotes the lowess curve fit to the two variables. The value of Spearman's for each pairwise correlation is shown in each panel. Note that several outlier data points fell outside the plotting area. (TIFF)

Correlation coefficients (Spearman's ) between coding region divergence and neutral diversity (Snorm). (PDF)

Correlation coefficients (Spearman's ) between coding region divergence and neutral diversity (Snorm) for windows in the upper 90th percentile of nonsynonymous divergence per site (dN) or synonymous divergence per site (dS). (PDF)

Correlations between the number of SNPs per covered base among the three different datasets. The red line denotes the lowess curve fit to the two variables. The value of Spearman's for each pairwise correlation is shown in each panel. Note that several outlier data points fell outside the plotting area. (TIFF)

Correlations between summaries of genetic variation and recombination rate in the CGS dataset dividing the data into genic and non-genic windows (see text). (A) Number of SNPs per covered base divided by human-chimp divergence (Snorm) versus recombination rate. (B) Average minor allele frequency versus recombination rate. Red and green lines denote...

Structure of a simulated window. Each window contains 8 exons, 7 introns, and a 53 kb neutral intergenic sequence in the middle. Some models of selection included negative selection only on coding sites. Other models included negative and positive selection on coding sites. A third set of models added negative selection on a fraction of intronic si...

Comparison of Spearman's for genic regions with the expected values based on forward simulations for the higher-coverage dataset. (A) Number of SNPs per covered base divided by human-chimp divergence (Snorm) versus recombination rate. (B) Average minor allele frequency versus recombination rate. (C) Number of SNPs per covered base divided by human-...