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The biological importance of RNA has expanded as our appreciation of the complexity of its multiple types, structures, chemical compositions and biological roles. Research in RNA has been instrumental in revealing insights into fundamental biological processes including: the organization of information within genomes, the mechanisms of control of gene expression at the transcriptional (providing scaffolds for transcription factors and chromatin-modifying proteins) and post-transcriptional (RNA editing and modifications, translation, sponging) levels, spatiotemporal localization of elements involved in developmental and cell biology, and the evolution of first RNA genomes. Most recently, studies of RNA have expanded their clinical roles as diagnostics to the realm of therapeutic treatment for detected diseases. Finally, advances in RNA studies have been prompted by and contributed to the development of many novel methodological and computational approaches. The future of RNA research will add even more to our understanding of the origins of endophenotypes and these findings will be the focus of the Frontiers in RNA Research.

Genes specifying long non-coding RNAs (lncRNAs) occupy a large fraction of the genomes of complex organisms. The term 'lncRNAs' encompasses RNA polymerase I (Pol I), Pol II and Pol III transcribed RNAs, and RNAs from processed introns. The various functions of lncRNAs and their many isoforms and interleaved relationships with other genes make lncRNA classification and annotation difficult. Most lncRNAs evolve more rapidly than protein-coding sequences, are cell type specific and regulate many aspects of cell differentiation and development and other physiological processes. Many lncRNAs associate with chromatin-modifying complexes, are transcribed from enhancers and nucleate phase separation of nuclear condensates and domains, indicating an intimate link between lncRNA expression and the spatial control of gene expression during development. lncRNAs also have important roles in the cytoplasm and beyond, including in the regulation of translation, metabolism and signalling. lncRNAs often have a modular structure and are rich in repeats, which are increasingly being shown to be relevant to their function. In this Consensus Statement, we address the definition and nomenclature of lncRNAs and their conservation, expression, phenotypic visibility, structure and functions. We also discuss research challenges and provide recommendations to advance the understanding of the roles of lncRNAs in development, cell biology and disease.

Understanding how genetic variants impact molecular phenotypes is a key goal of functional genomics, currently hindered by reliance on a single haploid reference genome. Here, we present the EN-TEx resource of 1,635 open-access datasets from four donors (∼30 tissues × ∼15 assays). The datasets are mapped to matched, diploid genomes with long-read phasing and structural variants, instantiating a catalog of >1 million allele-specific loci. These loci exhibit coordinated activity along haplotypes and are less conserved than corresponding, non-allele-specific ones. Surprisingly, a deep-learning transformer model can predict the allele-specific activity based only on local nucleotide-sequence context, highlighting the importance of transcription-factor-binding motifs particularly sensitive to variants. Furthermore, combining EN-TEx with existing genome annotations reveals strong associations between allele-specific and GWAS loci. It also enables models for transferring known eQTLs to difficult-to-profile tissues (e.g., from skin to heart). Overall, EN-TEx provides rich data and generalizable models for more accurate personal functional genomics.

Most plant roots have multiple cortex layers that make up the bulk of the organ and play key roles in physiology, such as flood tolerance and symbiosis. However, little is known about the formation of cortical layers outside of the highly reduced anatomy of Arabidopsis. Here we use single-cell RNAseq to rapidly generate a cell resolution map of the maize root, revealing an alternative configuration of the tissue formative transcription factor SHORT-ROOT (SHR) adjacent to an expanded cortex. We show that maize SHR protein is hypermobile, moving at least eight cell layers into the cortex. Higher-order SHR mutants in both maize and Setaria have reduced numbers of cortical layers, showing that the SHR pathway controls expansion of cortical tissue to elaborate anatomical complexity.

Extracellular RNAs participate in intercellular communication, and are being studied as promising minimally invasive diagnostic markers. Several studies in recent years showed that tRNA halves and distinct Y RNA fragments are abundant in the extracellular space, including in biofluids. While their regulatory and diagnostic potential has gained a substantial amount of attention, the biogenesis of these extracellular RNA fragments remains largely unexplored. Here, we demonstrate that these fragments are produced by RNase 1, a highly active secreted nuclease. We use RNA sequencing to investigate the effect of a null mutation of RNase 1 on the levels of tRNA halves and Y RNA fragments in the extracellular environment of cultured human cells. We complement and extend our RNA sequencing results with northern blots, showing that tRNAs and Y RNAs in the non-vesicular extracellular compartment are released from cells as full-length precursors and are subsequently cleaved to distinct fragments. In support of these results, formation of tRNA halves is recapitulated by recombinant human RNase 1 in our in vitro assay. These findings assign a novel function for RNase 1, and position it as a strong candidate for generation of tRNA halves and Y RNA fragments in biofluids.

Alu elements are one of the most successful families of transposons in the human genome. A portion of Alu elements is transcribed by RNA Pol III, whereas the remaining ones are part of Pol II transcripts. Because Alu elements are highly repetitive, it has been difficult to identify the Pol III–transcribed elements and quantify their expression levels. In this study, we generated high-resolution, long-genomic-span RAMPAGE data in 155 biosamples all with matching RNA-seq data and built an atlas of 17,249 Pol III–transcribed Alu elements. We further performed an integrative analysis on the ChIP-seq data of 10 histone marks and hundreds of transcription factors, whole-genome bisulfite sequencing data, ChIA-PET data, and functional data in several biosamples, and our results revealed that although the human-specific Alu elements are transcriptionally repressed, the older, expressed Alu elements may be exapted by the human host to function as cell-type–specific enhancers for their nearby protein-coding genes.

Most plant roots have multiple cortex layers that make up the bulk of the organ and play key roles in physiology, such as flood tolerance and symbiosis. However, little is known about the formation of cortical layers outside of the highly reduced anatomy of the model Arabidopsis. Here we use single-cell RNAseq to rapidly generate a cell resolution map of the maize root, revealing an alternative configuration of the tissue formative SHORT-ROOT (SHR) signaling pathway adjacent to an expanded cortex. We show that maize SHR protein is hypermobile, moving at least eight cell layers into the cortex. Higher-order SHR mutants in both maize and Setaria have reduced numbers of cortical layers, showing that the SHR pathway controls expansion of cortical tissue in grasses that sets up anatomical complexity and a host of key traits.One sentence summarySingle-cell RNA-seq maps the maize root transcriptome uncovering a mechanism that regulates cortex layer number.

Understanding how genetic variants impact molecular phenotypes is a key goal of functional genomics, currently hindered by reliance on a single haploid reference genome. Here, we present the EN-TEx resource of personal epigenomes, for ∼25 tissues and >10 assays in four donors (>1500 open-access functional genomic and proteomic datasets, in total). Each dataset is mapped to a matched, diploid personal genome, which has long-read phasing and structural variants. The mappings enable us to identify >1 million loci with allele-specific behavior. These loci exhibit coordinated epigenetic activity along haplotypes and less conservation than matched, non-allele-specific loci, in a fashion broadly paralleling tissue-specificity. Surprisingly, they can be accurately modelled just based on local nucleotide-sequence context. Combining EN-TEx with existing genome annotations reveals strong associations between allele-specific and GWAS loci and enables models for transferring known eQTLs to difficult-to-profile tissues. Overall, EN-TEx provides rich data and generalizable models for more accurate personal functional genomics.

As a means to understand human neuropsychiatric disorders from human brain samples, we compared the transcription patterns and histological features of postmortem brain to fresh human neocortex isolated immediately following surgical removal. Compared to a number of neuropsychiatric disease-associated postmortem transcriptomes, the fresh human brain transcriptome had an entirely unique transcriptional pattern. To understand this difference, we measured genome-wide transcription as a function of time after fresh tissue removal to mimic the postmortem interval. Within a few hours, a selective reduction in the number of neuronal activity-dependent transcripts occurred with relative preservation of housekeeping genes commonly used as a reference for RNA normalization. Gene clustering indicated a rapid reduction in neuronal gene expression with a reciprocal time-dependent increase in astroglial and microglial gene expression that continued to increase for at least 24 h after tissue resection. Predicted transcriptional changes were confirmed histologically on the same tissue demonstrating that while neurons were degenerating, glial cells underwent an outgrowth of their processes. The rapid loss of neuronal genes and reciprocal expression of glial genes highlights highly dynamic transcriptional and cellular changes that occur during the postmortem interval. Understanding these time-dependent changes in gene expression in post mortem brain samples is critical for the interpretation of research studies on human brain disorders.

Sorghum bicolor, one of the most important grass crops around the world, harbors a high degree of genetic diversity. We constructed chromosome-level genome assemblies for two important sorghum inbred lines, Tx2783 and RTx436. The final high-quality reference assemblies consist of 19 and 18 scaffolds, respectively, with contig N50 values of 25.6 and 20.3 Mb. Genes were annotated using evidence-based and de novo gene predictors, and RAMPAGE data demonstrate that transcription start sites were effectively captured. Together with other public sorghum genomes, BTx623, RTx430, and Rio, extensive structural variations (SVs) of various sizes were characterized using Tx2783 as a reference. Genome-wide scanning for disease resistance (R) genes revealed high levels of diversity among these five sorghum accessions. To characterize sugarcane aphid (SCA) resistance in Tx2783, we mapped the resistance region on chromosome 6 using a recombinant inbred line (RIL) population and found a SV of 191 kb containing a cluster of R genes in Tx2783. Using Tx2783 as a backbone, along with the SVs, we constructed a pan-genome to support alignment of resequencing data from 62 sorghum accessions, and then identified core and dispensable genes using this population. This study provides the first overview of the extent of genomic structural variations and R genes in the sorghum population, and reveals potential targets for breeding of SCA resistance.

Crop productivity depends on activity of meristems that produce optimized plant architectures, including that of the maize ear. A comprehensive understanding of development requires insight into the full diversity of cell types and developmental domains and the gene networks required to specify them. Until now, these were identified primarily by morphology and insights from classical genetics, which are limited by genetic redundancy and pleiotropy. Here, we investigated the transcriptional profiles of 12,525 single cells from developing maize ears. The resulting developmental atlas provides a single-cell RNA sequencing (scRNA-seq) map of an inflorescence. We validated our results by mRNA in situ hybridization and by fluorescence-activated cell sorting (FACS) RNA-seq, and we show how these data may facilitate genetic studies by predicting genetic redundancy, integrating transcriptional networks, and identifying candidate genes associated with crop yield traits.

The human and mouse genomes contain instructions that specify RNAs and proteins and govern the timing, magnitude, and cellular context of their production. To better delineate these elements, phase III of the Encyclopedia of DNA Elements (ENCODE) Project has expanded analysis of the cell and tissue repertoires of RNA transcription, chromatin structure and modification, DNA methylation, chromatin looping, and occupancy by transcription factors and RNA-binding proteins. Here we summarize these efforts, which have produced 5,992 new experimental datasets, including systematic determinations across mouse fetal development. All data are available through the ENCODE data portal (https://www.encodeproject.org), including phase II ENCODE1 and Roadmap Epigenomics2 data. We have developed a registry of 926,535 human and 339,815 mouse candidate cis-regulatory elements, covering 7.9 and 3.4% of their respective genomes, by integrating selected datatypes associated with gene regulation, and constructed a web-based server (SCREEN; http://screen.encodeproject.org) to provide flexible, user-defined access to this resource. Collectively, the ENCODE data and registry provide an expansive resource for the scientific community to build a better understanding of the organization and function of the human and mouse genomes., The authors summarize the data produced by phase III of the Encyclopedia of DNA Elements (ENCODE) project, a resource for better understanding of the human and mouse genomes.

We have produced RNA sequencing data for 53 primary cells from different locations in the human body. The clustering of these primary cells reveals that most cells in the human body share a few broad transcriptional programs, which define five major cell types: epithelial, endothelial, mesenchymal, neural, and blood cells. These act as basic components of many tissues and organs. Based on gene expression, these cell types redefine the basic histological types by which tissues have been traditionally classified. We identified genes whose expression is specific to these cell types, and from these genes, we estimated the contribution of the major cell types to the composition of human tissues. We found this cellular composition to be a characteristic signature of tissues and to reflect tissue morphological heterogeneity and histology. We identified changes in cellular composition in different tissues associated with age and sex, and found that departures from the normal cellular composition correlate with histological phenotypes associated with disease. This project was supported by awards U54HG007004, U41HG007234, and R01MH101814 from the National Human Genome Research Institute of the National Institutes of Health, as well as from the Spanish Ministry of Economy and Competitiveness, Centro de Excelencia Severo Ochoa 2013–2017, SEV-2012-0208, Programa de Ayudas FPI del Ministerio de Economía y Competitividad BES-2012-055848 to A.B., and Ministerio de Educación, Cultura y Deporte, under the FPU programme (Formación de Profesorado Universitario) with predoctoral fellowship FPU15/03635 to M.M.A., as well as the support of the CERCA programme/Generalitat de Catalunya. D.G.M. is supported by a “la Caixa”-Severo Ochoa predoctoral fellowship LCF/BQ/SO15/52260001. We also acknowledge support from the European Research Council (ERC) under the European Union's Seventh Framework Programme (FP7/2007-2013)/ERC grant agreement 294653.

MaizeCODE is a project aimed at identifying and analyzing functional elements in the maize genome. In its initial phase, MaizeCODE assayed up to five tissues from four maize strains (B73, NC350, W22, TIL11) by RNA-Seq, Chip-Seq, RAMPAGE, and small RNA sequencing. To facilitate reproducible science and provide both human and machine access to the MaizeCODE data, we enhanced SciApps, a cloud-based portal, for analysis and distribution of both raw data and analysis results. Based on the SciApps workflow platform, we generated new components to support the complete cycle of MaizeCODE data management. These include publicly accessible scientific workflows for the reproducible and shareable analysis of various functional data, a RESTful API for batch processing and distribution of data and metadata, a searchable data page that lists each MaizeCODE experiment as a reproducible workflow, and integrated JBrowse genome browser tracks linked with workflows and metadata. The SciApps portal is a flexible platform that allows the integration of new analysis tools, workflows, and genomic data from multiple projects. Through metadata and a ready-to-compute cloud-based platform, the portal experience improves access to the MaizeCODE data and facilitates its analysis.

Crop productivity depends on activity of meristems that produce optimized plant architectures, including that of the maize ear. A comprehensive understanding of development requires insight into the full diversity of cell types and developmental domains, and the gene networks required to specify them. Until now, these were identified primarily by morphology and insights from classical genetics, and insights are limited by genetic redundancy and pleiotropy. Here, we investigated the transcriptional profiles of 12,525 single cells from developing maize ear inflorescence primordia. The resulting developmental atlas provides the first comprehensive single-cell RNA sequencing (scRNA-seq) map of an inflorescence. We validated our results by mRNA in situ hybridization and by Fluorescence-Activated Cell Sorting (FACS) RNA-seq, and show how these data may facilitate genetic studies by predicting genetic redundancy, integrating transcriptional networks, and identifying candidate genes associated with crop yield traits.

Accurate annotations of genes and their transcripts is a foundation of genomics, but no annotation technique presently combines throughput and accuracy. As a result, reference gene collections remain incomplete: many gene models are fragmentary, while thousands more remain uncatalogued–particularly for long noncoding RNAs (lncRNAs). To accelerate lncRNA annotation, the GENCODE consortium has developed RNA Capture Long Seq (CLS), combining targeted RNA capture with third-generation long-read sequencing. We present an experimental re-annotation of the GENCODE intergenic lncRNA population in matched human and mouse tissues, resulting in novel transcript models for 3574 / 561 gene loci, respectively. CLS approximately doubles the annotated complexity of targeted loci, outperforming existing short-read techniques. Full-length transcript models produced by CLS enable us to definitively characterize the genomic features of lncRNAs, including promoter- and gene-structure, and protein-coding potential. Thus CLS removes a longstanding bottleneck of transcriptome annotation, generating manual-quality full-length transcript models at high-throughput scales.Abbreviationsbpbase pairFLfull lengthntnucleotideROIread of insert, i.e. PacBio readSJsplice junctionSMRTsingle-molecule real-timeTMtranscript model

Cross-species comparisons of genomes, transcriptomes and gene regulation are now feasible at unprecedented resolution and throughput, enabling the comparison of human and mouse biology at the molecular level. Insights have been gained into the degree of conservation between human and mouse at the level of not only gene expression but also epigenetics and inter-individual variation. However, a number of limitations exist, including incomplete transcriptome characterization and difficulties in identifying orthologous phenotypes and cell types, which are beginning to be addressed by emerging technologies. Ultimately, these comparisons will help to identify the conditions under which the mouse is a suitable model of human physiology and disease, and optimize the use of animal models.

Long noncoding RNAs (lncRNAs) can regulate target gene expression by acting in cis (locally) or in trans (non-locally). Here, we performed genome-wide expression analysis of Toll-like receptor (TLR)-stimulated human macrophages to identify pairs of cis-acting lncRNAs and protein-coding genes involved in innate immunity. A total of 229 gene pairs were identified, many of which were commonly regulated by signaling through multiple TLRs and were involved in the cytokine responses to infection by group B Streptococcus We focused on elucidating the function of one lncRNA, named lnc-MARCKS or ROCKI (Regulator of Cytokines and Inflammation), which was induced by multiple TLR stimuli and acted as a master regulator of inflammatory responses. ROCKI interacted with APEX1 (apurinic/apyrimidinic endodeoxyribonuclease 1) to form a ribonucleoprotein complex at the MARCKS promoter. In turn, ROCKI-APEX1 recruited the histone deacetylase HDAC1, which removed the H3K27ac modification from the promoter, thus reducing MARCKS transcription and subsequent Ca2+ signaling and inflammatory gene expression. Finally, genetic variants affecting ROCKI expression were linked to a reduced risk of certain inflammatory and infectious disease in humans, including inflammatory bowel disease and tuberculosis. Collectively, these data highlight the importance of cis-acting lncRNAs in TLR signaling, innate immunity, and pathophysiological inflammation.

MicroRNAs (miRNAs) play a critical role as post-transcriptional regulators of gene expression. The ENCODE project profiled the expression of miRNAs in a comprehensive set of tissues during a time-course of mouse embryonic development and captured the expression dynamics of 785 miRNAs. We found distinct tissue and developmental stage specific miRNA expression clusters, with an overall pattern of increasing tissue specific expression as development proceeds. Comparative analysis of conserved miRNAs in mouse and human revealed stronger clustering of expression patterns by tissue types rather than by species. An analysis of messenger RNA gene expression clusters compared with miRNA expression clusters identifies the potential role of specific miRNA expression clusters in suppressing the expression of mRNAs specific to other developmental programs in the tissue where these microRNAs are expressed during embryonic development. Our results provide the most comprehensive timecourse of miRNA expression as an integrated part of the ENCODE reference dataset for mouse embryonic development.

Long noncoding RNAs (lncRNAs) can regulate target gene expression by acting in cis (locally) or in trans (non‐locally). Here, we performed genome‐wide expression analysis of Toll‐like receptor (TLR)‐stimulated human macrophages to identify pairs of cis‐acting lncRNAs and protein‐coding genes involved in innate immunity. A total of 229 gene pairs were identified, many of which were commonly regulated by signaling through multiple TLRs and were involved in the cytokine responses to infection by group B Streptococcus. We focused on elucidating the function of one lncRNA, named lnc‐MARCKS or ROCKI (Regulator of Cytokines and Inflammation), which was induced by multiple TLR stimuli and acted as a master regulator of inflammatory responses. ROCKI interacted with APEX1 (apurinic/apyrimidinic endodeoxyribonuclease 1) to form a ribonucleoprotein complex at the MARCKS promoter. In turn, ROCKI–APEX1 recruited the histone deacetylase HDAC1, which removed the H3K27ac modification from the promoter, thus reducing MARCKS transcription and subsequent Ca2+ signaling and inflammatory gene expression. Finally, genetic variants affecting ROCKI expression were linked to a reduced risk of certain inflammatory and infectious disease in humans, including inflammatory bowel disease and tuberculosis. Collectively, these data highlight the importance of cis‐acting lncRNAs in TLR signaling, innate immunity, and pathophysiological inflammation.

Extracellular RNA (exRNA) has emerged as an important transducer of intercellular communication. Advancing exRNA research promises to revolutionize biology and transform clinical practice. Recent efforts have led to cutting-edge research and expanded knowledge of this new paradigm in cell-to-cell crosstalk; however, gaps in our understanding of EV heterogeneity and exRNA diversity pose significant challenges for continued development of exRNA diagnostics and therapeutics. To unravel this complexity, the NIH convened expert teams to discuss the current state of the science, define the significant bottlenecks, and brainstorm potential solutions across the entire exRNA research field. The NIH Strategic Workshop on Extracellular RNA Transport helped identify mechanistic and clinical research opportunities for exRNA biology and provided recommendations on high priority areas of research that will advance the exRNA field.

Many tools are available for RNA-seq alignment and expression quantification, with comparative value being hard to establish. Benchmarking assessments often highlight methods’ good performance, but are focused on either model data or fail to explain variation in performance. This leaves us to ask, what is the most meaningful way to assess different alignment choices? And importantly, where is there room for progress? In this work, we explore the answers to these two questions by performing an exhaustive assessment of the STAR aligner. We assess STAR’s performance across a range of alignment parameters using common metrics, and then on biologically focused tasks. We find technical metrics such as fraction mapping or expression profile correlation to be uninformative, capturing properties unlikely to have any role in biological discovery. Surprisingly, we find that changes in alignment parameters within a wide range have little impact on both technical and biological performance. Yet, when performance finally does break, it happens in difficult regions, such as X-Y paralogs and MHC genes. We believe improved reporting by developers will help establish where results are likely to be robust or fragile, providing a better baseline to establish where methodological progress can still occur.

Scientific Data, 4, ISSN:2052-4463

Multicellular development is largely determined by transcriptional regulatory programs that orchestrate the expression of thousands of protein-coding and noncoding genes. To decipher the genomic regulatory code that specifies these programs, and to investigate globally the developmental relevance of noncoding transcription, we profiled genome-wide promoter activity throughout embryonic development in 5 Drosophila species. We show that core promoters, generally not thought to play a significant regulatory role, in fact impart broad restrictions on the developmental timing of gene expression on a genome-wide scale. We propose a hierarchical model of transcriptional regulation during development in which core promoters define broad windows of opportunity for expression, by defining a limited range of transcription factors from which they are able to receive regulatory inputs. This two-tiered mechanism globally orchestrates developmental gene expression, including noncoding transcription on a scale that defies our current understanding of ontogenesis. Indeed, noncoding transcripts are far more prevalent than ever reported before, with ∼4,000 long noncoding RNAs expressed during embryogenesis. Over 1,500 are functionally conserved throughout the melanogaster subgroup, and hundreds are under strong purifying selection. Overall, this work introduces a hierarchical model for the developmental regulation of transcription, and reveals the central role of noncoding transcription in animal development.

MotivationFusion genes created by genomic rearrangements can be potent drivers of tumorigenesis. However, accurate identification of functionally fusion genes from genomic sequencing requires whole genome sequencing, since exonic sequencing alone is often insufficient. Transcriptome sequencing provides a direct, highly effective alternative for capturing molecular evidence of expressed fusions in the precision medicine pipeline, but current methods tend to be inefficient or insufficiently accurate, lacking in sensitivity or predicting large numbers of false positives. Here, we describe STAR-Fusion, a method that is both fast and accurate in identifying fusion transcripts from RNA-Seq data.ResultsWe benchmarked STAR-Fusion’s fusion detection accuracy using both simulated and genuine Illumina paired-end RNA-Seq data, and show that it has superior performance compared to popular alternative fusion detection methods.Availability and implementationSTAR-Fusion is implemented in Perl, freely available as open source software at http://star-fusion.github.io, and supported on Linux.Contactbhaas@broadinstitute.org

The transcriptome is the readout of the genome. Identifying common features in it across distant species can reveal fundamental principles. To this end, the ENCODE and modENCODE consortia have generated large amounts of matched RNA-sequencing data for human, worm and fly. Uniform processing and comprehensive annotation of these data allow comparison across metazoan phyla, extending beyond earlier within-phylum transcriptome comparisons and revealing ancient, conserved features1, 2, 3, 4, 5, 6. Specifically, we discover co-expression modules shared across animals, many of which are enriched in developmental genes. Moreover, we use expression patterns to align the stages in worm and fly development and find a novel pairing between worm embryo and fly pupae, in addition to the embryo-to-embryo and larvae-to-larvae pairings. Furthermore, we find that the extent of non-canonical, non-coding transcription is similar in each organism, per base pair. Finally, we find in all three organisms that the gene-expression levels, both coding and non-coding, can be quantitatively predicted from chromatin features at the promoter using a ‘universal model’ based on a single set of organism-independent parameters. In particular, this work was funded by a contract from the National Human Genome Research Institute modENCODE Project, contract U01 HG004271 and U54 HG006944, to S.E.C. (principal investigator) and P.C., T.R.G., R.A.H. and B.R.G. (co-principal investigators) with additional support from R01 GM076655 (S.E.C.) both under Department of Energy contract no. DE-AC02-05CH11231, and U54 HG007005 to B.R.G. J.B.B.’s work was supported by NHGRI K99 HG006698 and DOE DE-AC02-05CH11231. Work in P.J.B.’s group was supported by the modENCODE DAC sub award 5710003102, 1U01HG007031-01 and the ENCODE DAC 5U01HG004695-04. Work in M.B.G.’s group was supported by NIH grants HG007000 and HG007355. Work in Bloomington was supported in part by the Indiana METACyt Initiative of Indiana University, funded by an award from the Lilly Endowment, Inc. Work in E.C.L.’s group was supported by U01-HG004261 and RC2-HG005639. P.J.P. acknowledges support from the National Institutes of Health (grant no. U01HG004258). We thank the HAVANA team for providing annotation of the human reference genome, whose work is supported by National Institutes of Health (grant no. 5U54HG004555), the Wellcome Trust (grant no. WT098051). R.G. acknowledges support from the Spanish Ministry of Education (grant BIO2011-26205). We also acknowledge use of the Yale University Biomedical High Performance Computing Center. R.W.'s lab was supported by grant no. U01 HG 004263.

Long noncoding RNAs (lncRNAs) can regulate target gene expression by acting in cis (locally) or in trans (non-locally). Here, we performed genome-wide expression analysis of Toll-like receptor (TLR)-stimulated human macrophages to identify pairs of cis-acting lncRNAs and protein-coding genes involved in innate immunity. A total of 229 gene pairs were identified, many of which were commonly regulated by signaling through multiple TLRs and were involved in the cytokine responses to infection by group B Streptococcus. We focused on elucidating the function of one lncRNA, named lnc-MARCKS or ROCKI (Regulator of Cytokines and Inflammation), which was induced by multiple TLR stimuli and acted as a master regulator of inflammatory responses. ROCKI interacted with APEX1 (apurinic/apyrimidinic endodeoxyribonuclease 1) to form a ribonucleoprotein complex at the MARCKS promoter. In turn, ROCKI–APEX1 recruited the histone deacetylase HDAC1, which removed the H3K27ac modification from the promoter, thus reducing MARCKS transcription and subsequent Ca2+ signaling and inflammatory gene expression. Finally, genetic variants affecting ROCKI expression were linked to a reduced risk of certain inflammatory and infectious disease in humans, including inflammatory bowel disease and tuberculosis. Collectively, these data highlight the importance of cis-acting lncRNAs in TLR signaling, innate immunity, and pathophysiological inflammation.

The transcriptional landscape in embryonic stem cells (ESCs) and during ESC differentiation has received considerable attention, albeit mostly confined to the polyadenylated fraction of RNA, whereas the non-polyadenylated (NPA) fraction remained largely unexplored. Notwithstanding, the NPA RNA super-family has every potential to participate in the regulation of pluripotency and stem cell fate. We conducted a comprehensive analysis of NPA RNA in ESCs using a combination of whole-genome tiling arrays and deep sequencing technologies. In addition to identifying previously characterized and new non-coding RNA members, we describe a group of novel conserved RNAs (snacRNAs: small NPA conserved), some of which are differentially expressed between ESC and neuronal progenitor cells, providing the first evidence of a novel group of potentially functional NPA RNA involved in the regulation of pluripotency and stem cell fate. We further show that minor spliceosomal small nuclear RNAs, which are NPA, are almost completely absent in ESCs and are upregulated in differentiation. Finally, we show differential processing of the minor intron of the polycomb group gene Eed. Our data suggest that NPA RNA, both known and novel, play important roles in ESCs.

Recent advances in high-throughput sequencing technology made it possible to probe the cell transcriptomes by generating hundreds of millions of short reads which represent the fragments of the transcribed RNA molecules. The first and the most crucial task in the RNA-seq data analysis is mapping of the reads to the reference genome. STAR (Spliced Transcripts Alignment to a Reference) is an RNA-seq mapper that performs highly accurate spliced sequence alignment at an ultrafast speed. STAR alignment algorithm can be controlled by many user-defined parameters. Here, we describe the most important STAR options and parameters, as well as best practices for achieving the maximum mapping accuracy and speed.

Recent advances in high-throughput sequencing technology made it possible to probe the cell transcriptomes by generating hundreds of millions of short reads which represent the fragments of the transcribed RNA molecules. The first and the most crucial task in the RNA-seq data analysis is mapping of the reads to the reference genome. STAR (Spliced Transcripts Alignment to a Reference) is an RNA-seq mapper that performs highly accurate spliced sequence alignment at an ultrafast speed. STAR alignment algorithm can be controlled by many user-defined parameters. Here, we describe the most important STAR options and parameters, as well as best practices for achieving the maximum mapping accuracy and speed.

Background: A comparison of transcriptional profiles derived from different tissues in a given species or among different species assumes that commonalities reflect evolutionarily conserved programs and that differences reflect species or tissue responses to environmental conditions or developmental program staging. Apparently conflicting results have been published regarding whether organ-specific transcriptional patterns dominate over species-specific patterns, or vice versa, making it unclear to what extent the biology of a given organism can be extrapolated to another. These studies have in common that they treat the transcriptomes monolithically, implicitly ignoring that each gene is likely to have a specific pattern of transcriptional variation across organs and species. Results: We use linear models to quantify this pattern. We find a continuum in the spectrum of expression variation: the expression of some genes varies considerably across species and little across organs, and simply reflects evolutionary distance. At the other extreme are genes whose expression varies considerably across organs and little across species; these genes are much more likely to be associated with diseases than are genes whose expression varies predominantly across species. Conclusions: Whether transcriptomes, when considered globally, cluster preferentially according to one component or the other may not be a property of the transcriptomes, but rather a consequence of the dominant behavior of a subset of genes. Therefore, the values of the components of the variance of expression for each gene could become a useful resource when planning, interpreting, and extrapolating experimental data from mouse to humans. This project was supported by awards U54HG007004 and U41HG007234 from the National Human Genome Research Institute of the National Institutes of Health, as well as from the Spanish Ministry of Economy and Competitiveness, Centro de Excelencia Severo Ochoa 2013–2017, SEV-2012-0208, and Programa de Ayudas FPI del Ministerio de Economia y Competitividad, BES-2012-055848. We would also like to acknowledge support from the European Research Council (ERC) under the European Union’s Seventh Framework Programme (FP7/2007-2013)/ERC grant agreement 294653.

Many eukaryotic genes possess multiple alternative promoters with distinct expression specificities. Therefore, comprehensively annotating promoters and deciphering their individual regulatory dynamics is critical for gene expression profiling applications and for our understanding of regulatory complexity. We introduce RAMPAGE, a novel promoter activity profiling approach that combines extremely specific 5′-complete cDNA sequencing with an integrated data analysis workflow, to address the limitations of current techniques. RAMPAGE features a streamlined protocol for fast and easy generation of highly multiplexed sequencing libraries, offers very high transcription start site specificity, generates accurate and reproducible promoter expression measurements, and yields extensive transcript connectivity information through paired-end cDNA sequencing. We used RAMPAGE in a genome-wide study of promoter activity throughout 36 stages of the life cycle of Drosophila melanogaster, and describe here a comprehensive data set that represents the first available developmental time-course of promoter usage. We found that >40% of developmentally expressed genes have at least two promoters and that alternative promoters generally implement distinct regulatory programs. Transposable elements, long proposed to play a central role in the evolution of their host genomes through their ability to regulate gene expression, contribute at least 1300 promoters shaping the developmental transcriptome of D. melanogaster. Hundreds of these promoters drive the expression of annotated genes, and transposons often impart their own expression specificity upon the genes they regulate. These observations provide support for the theory that transposons may drive regulatory innovation through the distribution of stereotyped cis-regulatory modules throughout their host genomes.

Extracellular vesicles (EVs) have been proposed as a means to promote intercellular communication. We show that when human primary cells are exposed to cancer cell EVs, rapid cell death of the primary cells is observed, while cancer cells treated with primary or cancer cell EVs do not display this response. The active agents that trigger cell death are 29- to 31-nucleotide (nt) or 22- to 23-nt processed fragments of an 83-nt primary transcript of the human RNY5 gene that are highly likely to be formed within the EVs. Primary cells treated with either cancer cell EVs, deproteinized total RNA from either primary or cancer cell EVs, or synthetic versions of 31- and 23-nt fragments trigger rapid cell death in a dose-dependent manner. The transfer of processed RNY5 fragments through EVs may reflect a novel strategy used by cancer cells toward the establishment of a favorable microenvironment for their proliferation and invasion.

High-throughput sequencing of cDNA (RNA-seq) is a widely deployed transcriptome profiling and annotation technique, but questions about the performance of different protocols and platforms remain. We used a newly developed pool of 96 synthetic RNAs with various lengths, and GC content covering a 220 concentration range as spike-in controls to measure sensitivity, accuracy, and biases in RNA-seq experiments as well as to derive standard curves for quantifying the abundance of transcripts. We observed linearity between read density and RNA input over the entire detection range and excellent agreement between replicates, but we observed significantly larger imprecision than expected under pure Poisson sampling errors. We use the control RNAs to directly measure reproducible protocol-dependent biases due to GC content and transcript length as well as stereotypic heterogeneity in coverage across transcripts correlated with position relative to RNA termini and priming sequence bias. These effects lead to biased quantification for short transcripts and individual exons, which is a serious problem for measurements of isoform abundances, but that can partially be corrected using appropriate models of bias. By using the control RNAs, we derive limits for the discovery and detection of rare transcripts in RNA-seq experiments. By using data collected as part of the model organism and human Encyclopedia of DNA Elements projects (ENCODE and modENCODE), we demonstrate that external RNA controls are a useful resource for evaluating sensitivity and accuracy of RNA-seq experiments for transcriptome discovery and quantification. These quality metrics facilitate comparable analysis across different samples, protocols, and platforms.

Drosophila melanogaster cell lines are important resources for cell biologists. Here, we catalog the expression of exons, genes, and unannotated transcriptional signals for 25 lines. Unannotated transcription is substantial (typically 19% of euchro- matic signal). Conservatively, we identify 1405 novel transcribed regions; 684 of these appear to be new exons of neighboring, oftendistant, genes. Sixty-four percent of genes areexpressed detectably in atleastone line, but only 21%are detected in all lines. Each cell line expresses, on average, 5885 genes, including a common set of 3109. Expression levels vary over several orders of magnitude. Major signaling pathways are well represented: most differentiation pathways are ''off'' andsurvival/growth pathways''on.''Roughly 50%ofthe genesexpressed by eachlinearenot part ofthe commonset, and these show considerable individuality. Thirty-one percent are expressed at a higher level in at least one cell line than in any single developmental stage, suggesting that each line is enriched for genes characteristic of small sets of cells. Most re- markable is that imaginal disc-derived lines can generally be assigned, on the basis of expression, to small territories within developing discs. These mappings reveal unexpected stability of even fine-grained spatial determination. No two cell lines show identical transcription factor expression. We conclude that each line has retained features of an individual founder cell superimposed on a common ''cell line'' gene expression pattern. (Supplemental material is available for this article. The data from this study have been submitted to the NCBI Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo) under accession nos. GSE15596, GSE16269-GSE16290, GSE16321- GSE16322, GSE16325, and GSE18040. All of the microarray data, RNA-seq data, and expression scores for genes and exons are available from the Data Coordination Center of modENCODE (http://modencode.org), and much of the data are also available from the Drosophila Genomic Resources Center (https://dgrc.cgb.indiana.edu/) and FlyBase (http:// flybase.org/).)

Drosophila melanogaster is one of the most well studied genetic model organisms, nonetheless its genome still contains unannotated coding and non-coding genes, transcripts, exons, and RNA editing sites. Full discovery and annotation are prerequisites for understanding how the regulation of transcription, splicing, and RNA editing directs development of this complex organism. We used RNA-Seq, tiling microarrays, and cDNA sequencing to explore the transcriptome in 30 distinct developmental stages. We identified 111,195 new elements, including thousands of genes, coding and non-coding transcripts, exons, splicing and editing events and inferred protein isoforms that previously eluded discovery using established experimental, prediction and conservation-based approaches. Together, these data substantially expand the number of known transcribed elements in the Drosophila genome and provide a high-resolution view of transcriptome dynamics throughout development.

Large-scale sequencing projects have revealed an unexpected complexity in the origins, structures and functions of mammalian transcripts. Many loci are known to produce overlapping coding and non-coding RNAs with capped 5′ ends that vary in size. Methods that identify the 5′ ends of transcripts will facilitate the discovery of novel promoters and 5′ ends derived from secondary capping events. Such methods often require high input amounts of RNA not obtainable from highly refined samples such as tissue microdissections and subcellular fractions. Therefore, we have developed nanoCAGE (Cap Analysis of Gene Expression), a method that captures the 5′ ends of transcripts from as little as 10 nanograms of total RNA and CAGEscan, a mate-pair adaptation of nanoCAGE that captures the transcript 5′ ends linked to a downstream region. Both of these methods allow further annotation-agnostic studies of the complex human transcriptome.

We have identified an intergenic transcriptional activity that is located between the human HOXA1 and HOXA2 genes, shows myeloid-specific expression, and is up-regulated during granulocytic differentiation. The novel gene, termed HOTAIRM1 (HOX antisense intergenic RNA myeloid 1), is transcribed antisense to the HOXA genes and originates from the same CpG island that embeds the start site of HOXA1. The transcript appears to be a noncoding RNA containing no long open-reading frame; sucrose gradient analysis shows no association with polyribosomal fractions. HOTAIRM1 is the most prominent intergenic transcript expressed and up-regulated during induced granulocytic differentiation of NB4 promyelocytic leukemia and normal human hematopoietic cells; its expression is specific to the myeloid lineage. Its induction during retinoic acid (RA)–driven granulocytic differentiation is through RA receptor and may depend on the expression of myeloid cell development factors targeted by RA signaling. Knockdown of HOTAIRM1 quantitatively blunted RA-induced expression of HOXA1 and HOXA4 during the myeloid differentiation of NB4 cells, and selectively attenuated induction of transcripts for the myeloid differentiation genes CD11b and CD18, but did not noticeably impact the more distal HOXA genes. These findings suggest that HOTAIRM1 plays a role in the myelopoiesis through modulation of gene expression in the HOXA cluster.

A plan to ‘genomicize’ epigenomics research and pave the way for breakthroughs in the prevention, diagnosis and treatment of human disease.

While the concept of a gene has been helpful in defining the relationship of a portion of a genome to a phenotype, this traditional term may not be as useful as it once was. Currently, “gene” has come to refer principally to a genomic region producing a polyadenylated mRNA that encodes a protein. However, the recent emergence of a large collection of unannotated transcripts with apparently little protein coding capacity, collectively called transcripts of unknown function (TUFs), has begun to blur the physical boundaries and genomic organization of genic regions with noncoding transcripts often overlapping protein-coding genes on the same (sense) and opposite strand (antisense). Moreover, they are often located in intergenic regions, making the genic portions of the human genome an interleaved network of both annotated polyadenylated and nonpolyadenylated transcripts, including splice variants with novel 5′ ends extending hundreds of kilobases. This complex transcriptional organization and other recently observed features of genomes argue for the reconsideration of the term “gene” and suggests that transcripts may be used to define the operational unit of a genome.

Mapping of large sets of high-throughput sequencing reads to a reference genome is one of the foundational steps in RNA-seq data analysis. The STAR software package performs this task with high levels of accuracy and speed. In addition to detecting annotated and novel splice junctions, STAR is capable of discovering more complex RNA sequence arrangements, such as chimeric and circular RNA. STAR can align spliced sequences of any length with moderate error rates providing scalability for emerging sequencing technologies. STAR generates output files that can be used for many downstream analyses such as transcript/gene expression quantification, differential gene expression, novel isoform reconstruction, signal visualization, and so forth. In this unit we describe computational protocols that produce various output files, use different RNA-seq datatypes, and utilize different mapping strategies. STAR is Open Source software that can be run on Unix, Linux or Mac OS X systems.

Mice have been a long-standing model for human biology and disease. Here we characterize, by RNA sequencing, the transcriptional profiles of a large and heterogeneous collection of mouse tissues, augmenting the mouse transcriptome with thousands of novel transcript candidates. Comparison with transcriptome profiles in human cell lines reveals substantial conservation of transcriptional programmes, and uncovers a distinct class of genes with levels of expression that have been constrained early in vertebrate evolution. This core set of genes captures a substantial fraction of the transcriptional output of mammalian cells, and participates in basic functional and structural housekeeping processes common to all cell types. Perturbation of these constrained genes is associated with significant phenotypes including embryonic lethality and cancer. Evolutionary constraint in gene expression levels is not reflected in the conservation of the genomic sequences, but is associated with conserved epigenetic marking, as well as with characteristic post-transcriptional regulatory programme, in which sub-cellular localization and alternative splicing play comparatively large roles., The analysis of mammalian transcriptomes could provide new insights into human biology. Here the authors carry out RNA sequencing in a large collection of mouse tissues and compare these data to human transcriptome profiles, identifying a set of constrained genes that carry out basic cellular functions with remarkably constant expression levels across tissues and species.

Using tiled microarrays covering the entire human genome, we identify approximately 5800 target sites for p63, a p53 homolog essential for stratified epithelial development. p63 targets are enriched for genes involved in cell adhesion, proliferation, death, and signaling pathways. The quality of the derived DNA sequence motif for p63 targets correlates with binding strength binding in vivo, but only a small minority of motifs in the genome is bound by p63. Conversely, many p63 targets have motif scores expected for random genomic regions. Thus, p63 binding in vivo is highly selective and often requires additional factors beyond the simple protein-DNA interaction. There is a significant, but complex, relationship between p63 target sites and p63-responsive genes, with DeltaNp63 isoforms being linked to transcriptional activation. Many p63 binding regions are evolutionarily conserved and/or associated with sequence motifs for other transcription factors, suggesting that a substantial portion of p63 sites is biologically relevant.