RNA-sequencing protocols can quantify gene expression regulation from transcription to protein synthesis. Ribosome profiling (Ribo-seq) maps the positions of translating ribosomes over the entire transcriptome. We have developed RiboTaper (available at https://ohlerlab.mdc-berlin.de/software/), a rigorous statistical approach that identifies translated regions on the basis of the characteristic three-nucleotide periodicity of Ribo-seq data. We used RiboTaper with deep Ribo-seq data from HEK293 cells to derive an extensive map of translation that covered open reading frame (ORF) annotations for more than 11,000 protein-coding genes. We also found distinct ribosomal signatures for several hundred upstream ORFs and ORFs in annotated noncoding genes (ncORFs). Mass spectrometry data confirmed that RiboTaper achieved excellent coverage of the cellular proteome. Although dozens of novel peptide products were validated in this manner, few of the currently annotated long noncoding RNAs appeared to encode stable polypeptides. RiboTaper is a powerful method for comprehensive de novo identification of actively used ORFs from Ribo-seq data.

Efforts to precisely identify tumor human leukocyte antigen (HLA) bound peptides capable of mediating T cell-based tumor rejection still face important challenges. Recent studies suggest that non-canonical tumor-specific HLA peptides derived from annotated non-coding regions could elicit anti-tumor immune responses. However, sensitive and accurate mass spectrometry (MS)-based proteogenomics approaches are required to robustly identify these noncanonical peptides. We present an MS-based analytical approach that characterizes the noncanonical tumor HLA peptide repertoire, by incorporating whole exome sequencing, bulk and single-cell transcriptomics, ribosome profiling, and two MS/MS search tools in combination. This approach results in the accurate identification of hundreds of shared and tumor-specific non-canonical HLA peptides, including an immunogenic peptide derived from an open reading frame downstream of the melanoma stem cell marker gene ABCB5. These findings hold great promise for the discovery of previously unknown tumor antigens for cancer immunotherapy.

Pervasive transcription of the human genome results in a heterogeneous mix of coding RNAs and long noncoding RNAs (lncRNAs). Only a small fraction of lncRNAs have demonstrated regulatory functions, thus making functional lncRNAs difficult to distinguish from nonfunctional transcriptional byproducts. This difficulty has resulted in numerous competing human lncRNA classifications that are complicated by a steady increase in the number of annotated lncRNAs. To address these challenges, we quantitatively examined transcription, splicing, degradation, localization and translation for coding and noncoding human genes. We observed that annotated lncRNAs had lower synthesis and higher degradation rates than mRNAs and discovered mechanistic differences explaining slower lncRNA splicing. We grouped genes into classes with similar RNA metabolism profiles, containing both mRNAs and lncRNAs to varying extents. These classes exhibited distinct RNA metabolism, different evolutionary patterns and differential sensitivity to cellular RNA-regulatory pathways. Our classification provides an alternative to genomic context-driven annotations of lncRNAs.

SummaryThe chromatin regulator FACT (facilitates chromatin transcription) is essential for ensuring stable gene expression by promoting transcription. In a genetic screen using Caenorhabditis elegans, we identified that FACT maintains cell identities and acts as a barrier for transcription factor-mediated cell fate reprogramming. Strikingly, FACT’s role as a barrier to cell fate conversion is conserved in humans as we show that FACT depletion enhances reprogramming of fibroblasts. Such activity is unexpected because FACT is known as a positive regulator of gene expression, and previously described reprogramming barriers typically repress gene expression. While FACT depletion in human fibroblasts results in decreased expression of many genes, a number of FACT-occupied genes, including reprogramming-promoting factors, show increased expression upon FACT depletion, suggesting a repressive function of FACT. Our findings identify FACT as a cellular reprogramming barrier in C. elegans and humans, revealing an evolutionarily conserved mechanism for cell fate protection.

SUMMARY Direct cell programming via overexpression of transcription factors (TFs) aims to control cell fate with the degree of precision needed for clinical applications. However, the regulatory steps involved in successful terminal cell fate programming remain obscure. We have investigated the underlying mechanisms by looking at gene expression, chromatin states, and transcription factor binding during the uniquely efficient Ngn2, Isl1, and Lhx3 motor neuron programming pathway. Our analysis reveals a highly dynamic process in which Ngn2 and the Isl1/Lhx3 pair initially engage distinct regulatory regions. Subsequently, Isl1/Lhx3 binding shifts from one set of targets to another, controlling regulatory region activity and gene expression as cell differentiation progresses. Binding of Isl1/Lhx3 to later motor neuron enhancers depends on the TFs Ebf and Onecut, which are induced by Ngn2 during the programming process. Thus, motor neuron programming is the product of two initially independent transcriptional modules that converge with a feedforward transcriptional logic.

Background DNase-seq and ATAC-seq are broadly used methods to assay open chromatin regions genome-wide. The single nucleotide resolution of DNase-seq has been further exploited to infer transcription factor binding sites (TFBSs) in regulatory regions through footprinting. Recent studies have demonstrated the sequence bias of DNase I and its adverse effects on footprinting efficiency. However, footprinting and the impact of sequence bias have not been extensively studied for ATAC-seq. Results Here, we undertake a systematic comparison of the two methods and show that a modification to the ATAC-seq protocol increases its yield and its agreement with DNase-seq data from the same cell line. We demonstrate that the two methods have distinct sequence biases and correct for these protocol-specific biases when performing footprinting. Despite the differences in footprint shapes, the locations of the inferred footprints in ATAC-seq and DNase-seq are largely concordant. However, the protocol-specific sequence biases in conjunction with the sequence content of TFBSs impact the discrimination of footprint from the background, which leads to one method outperforming the other for some TFs. Finally, we address the depth required for reproducible identification of open chromatin regions and TF footprints. Conclusions We demonstrate that the impact of bias correction on footprinting performance is greater for DNase-seq than for ATAC-seq and that DNase-seq footprinting leads to better performance. It is possible to infer concordant footprints by using replicates, highlighting the importance of reproducibility assessment. The results presented here provide an overview of the advantages and limitations of footprinting analyses using ATAC-seq and DNase-seq. Electronic supplementary material The online version of this article (10.1186/s13059-019-1654-y) contains supplementary material, which is available to authorized users.

Efforts to precisely identify tumor human leukocyte antigen (HLA) bound peptides capable of mediating T cell-based tumor rejection still face important challenges. Recent studies suggest that non-canonical tumor-specific HLA peptides that derive from annotated non-coding regions could elicit anti-tumor immune responses. However, sensitive and accurate massspectrometry (MS)-based proteogenomics approaches are required to robustly identify these non-canonical peptides. We present an MS-based analytical approach that characterizes the non-canonical tumor HLA peptide repertoire, by incorporating whole exome sequencing, bulk and single cell transcriptomics, ribosome profiling, and a combination of two MS/MS search tools. This approach results in the accurate identification of hundreds of shared and tumorspecific non-canonical HLA peptides and of an immunogenic peptide from a downstream reading frame in the melanoma stem cell marker gene ABCB5. It holds great promise for the discovery of novel cancer antigens for cancer immunotherapy.

Deep sequencing methods have matured to comprehensively detect the full set of transcribed loci, but there is a gap to determine the function of the resulting highly complex transcriptomes. At the center of the gene expression cascade, translation is fundamental in defining the fate of much of the transcribed genome. We have developed a new approach (SaTAnn, Splice-aware Translatome Annotation) to annotate and quantify translation at the single open reading frame (ORF) level, that uses information from ribosome profiling to determine the translational state of each isoform in a comprehensive annotation.For most genes, one ORF represents the dominant translation product, but our approach also detects translation from ORFs belonging to multiple transcripts per gene, including targets of RNA surveillance mechanisms such as nonsense-mediated decay. Diversity in the translation output across human cell lines reveals the extent of gene-specific differences in protein production, which are supported by steady-state protein abundance estimates. Computational analysis of Ribo-seq data with SaTAnn (available at https://github.com/lcalviell/SaTAnn) provides a window into the functions of the heterogeneous transcriptome..