Modern maize (Zea mays ssp. mays) was domesticated from Teosinte parviglumis (Zea mays ssp. parviglumis), with subsequent introgressions from Teosinte mexicana (Zea mays ssp. mexicana), yielding increased kernel row number, loss of the hard fruit case and dissociation from the cob upon maturity, as well as fewer tillers. Molecular approaches have identified transcription factors controlling these traits, yet revealed that a complex regulatory network is at play. MaizeCODE deploys ENCODE strategies to catalog regulatory regions in the maize genome, generating histone modification and transcription factor ChIP-seq in parallel with transcriptomics datasets in 5 tissues of 3 inbred lines which span the phenotypic diversity of maize, as well as the teosinte inbred TIL11. Transcriptomic analysis reveals that pollen grains share features with endosperm, and express dozens of "proto-miRNAs" potential vestiges of gene drive and hybrid incompatibility. Integrated analysis with chromatin modifications results in the identification of a comprehensive set of regulatory regions in each tissue of each inbred, and notably of distal enhancers expressing non-coding enhancer RNAs bi-directionally, reminiscent of "super enhancers" in animal genomes. Furthermore, the morphological traits selected during domestication are recapitulated, both in gene expression and within regulatory regions containing enhancer RNAs, while highlighting the conflict between enhancer activity and silencing of the neighboring transposable elements.

Sorghum bicolor (L.) Moench is a significant grass crop globally, known for its genetic diversity. High quality genome sequences are needed to capture the diversity. We constructed high-quality, chromosome-level genome assemblies for two vital sorghum inbred lines, Tx2783 and RTx436. Through advanced single-molecule techniques, long-read sequencing and optical maps, we improved average sequence continuity 19-fold and 11-fold higher compared to existing Btx623 v3.0 reference genome and obtained 19 and 18 scaffolds (N50 of 25.6 and 14.4) for Tx2783 and RTx436, respectively. Our gene annotation efforts resulted in 29 612 protein-coding genes for the Tx2783 genome and 29 265 protein-coding genes for the RTx436 genome. Comparative analyses with 26 plant genomes which included 18 sorghum genomes and 8 outgroup species identified around 31 210 protein-coding gene families, with about 13 956 specific to sorghum. Using representative models from gene trees across the 18 sorghum genomes, a total of 72 579 pan-genes were identified, with 14% core, 60% softcore and 26% shell genes. We identified 99 genes in Tx2783 and 107 genes in RTx436 that showed functional enrichment specifically in binding and metabolic processes, as revealed by the GO enrichment Pearson Chi-Square test. We detected 36 potential large inversions in the comparison between the BTx623 Bionano map and the BTx623 v3.1 reference sequence. Strikingly, these inversions were notably absent when comparing Tx2783 or RTx436 with the BTx623 Bionano map. These inversion were mostly in the pericentromeric region which is known to have low complexity regions and harder to assemble and suggests the presence of potential artifacts in the public BTx623 reference assembly. Furthermore, in comparison to Tx2783, RTx436 exhibited 324 883 additional Single Nucleotide Polymorphisms (SNPs) and 16 506 more Insertions/Deletions (INDELs) when using BTx623 as the reference genome. We also characterized approximately 348 nucleotide-binding leucine-rich repeat (NLR) disease resistance genes in the two genomes. These high-quality genomes serve as valuable resources for discovering agronomic traits and structural variation studies.

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.

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.

Extrachromosomal DNA is a common cause of oncogene amplification in cancer. The non-chromosomal inheritance of ecDNA enables tumors to rapidly evolve, contributing to treatment resistance and poor outcome for patients. The transcriptional context in which ecDNAs arise and progress, including chromosomally-driven transcription, is incompletely understood. We examined gene expression patterns of 870 tumors of varied histological types, to identify transcriptional correlates of ecDNA. Here we show that ecDNA containing tumors impact four major biological processes. Specifically, ecDNA containing tumors upregulate DNA damage and repair, cell cycle control, and mitotic processes, but downregulate global immune regulation pathways. Taken together, these results suggest profound alterations in gene regulation in ecDNA containing tumors, shedding light on molecular processes that give rise to their development and progression.

The protein diversity of mammalian cells is determined by arrays of isoforms from genes. Protein mutation is essential in species evolution and cancer development. Accurate Long-read transcriptome sequencing at single-cell level is required to decipher the spectrum of protein expressions in mammalian organisms. In this report, we developed a synthetic long-read single-cell sequencing technology based on LOOPseq technique. We applied this technology to analyze 447 transcriptomes of hepatocellular carcinoma (HCC) and benign liver from an individual. Through Uniform Manifold Approximation and Projection (UMAP) analysis, we identified a panel of mutation mRNA isoforms highly specific to HCC cells. The evolution pathways that led to the hyper-mutation clusters in single human leukocyte antigen (HLA) molecules were identified. Novel fusion transcripts were detected. The combination of gene expressions, fusion gene transcripts, and mutation gene expressions significantly improved the classification of liver cancer cells versus benign hepatocytes. In conclusion, LOOPseq single-cell technology may hold promise to provide a new level of precision analysis on the mammalian transcriptome.

Scientists have been trying to identify all of the genes in the human genome since the initial draft of the genome was published in 2001. Over the intervening years, much progress has been made in identifying protein-coding genes, and the estimated number has shrunk to fewer than 20,000, although the number of distinct protein-coding isoforms has expanded dramatically. The invention of high-throughput RNA sequencing and other technological breakthroughs have led to an explosion in the number of reported non-coding RNA genes, although most of them do not yet have any known function. A combination of recent advances offers a path forward to identifying these functions and towards eventually completing the human gene catalogue. However, much work remains to be done before we have a universal annotation standard that includes all medically significant genes, maintains their relationships with different reference genomes, and describes clinically relevant genetic variants.

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 ENCODE 1 and Roadmap Epigenomics 2 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.

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 used single-cell RNA sequencing 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.

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 summary Single-cell RNA-seq maps the maize root transcriptome uncovering a mechanism that regulates cortex layer number.

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.

Evaluating the impact of genetic variants on transcriptional regulation is a central goal in biological science that has been constrained by reliance on a single reference genome. To address this, we constructed phased, diploid genomes for four cadaveric donors (using long-read sequencing) and systematically charted noncoding regulatory elements and transcriptional activity across more than 25 tissues from these donors. Integrative analysis revealed over a million variants with allele-specific activity, coordinated, locus-scale allelic imbalances, and structural variants impacting proximal chromatin structure. We relate the personal genome analysis to the ENCODE encyclopedia, annotating allele- and tissue-specific elements that are strongly enriched for variants impacting expression and disease phenotypes. These experimental and statistical approaches, and the corresponding EN-TEx resource, provide a framework for personalized functional genomics. decorations. The heatmap (center) shows the GWAS tag SNP enrichment of distal active CTCF+ cCREs. The tissues (colored according to the GTEx convention from Fig. 1) run along the bottom, and phenotypes (usually diseases, not explicitly labeled) run along the vertical axis. Around the heatmap, we show zoomed-in views highlighting various comparisons. At the bottom, we show that the tissue specificity of the enrichment for the trait Granulocyte % of Myeloid WBC is much stronger for AS versus non-AS cCREs. On the left, we show higher LDSC enrichment for AS elements compared to the corresponding non-AS ones for one tissue (coronary artery) across many associated traits. Left-bottom extends this comparison (for a single tissue-trait pair) to include roadmap annotations.

ABSTRACTSorghum 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 andde novogene 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.

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.

The Encylopedia of DNA Elements (ENCODE) Project launched in 2003 with the long-term goal of developing a comprehensive map of functional elements in the human genome. These included genes, biochemical regions associated with gene regulation (for example, transcription factor binding sites, open chromatin, and histone marks) and transcript isoforms. The marks serve as sites for candidatecis-regulatory elements (cCREs) that may serve functional roles in regulating gene expression(1). The project has been extended to model organisms, particularly the mouse. In the third phase of ENCODE, nearly a million and more than 300,000 cCRE annotations have been generated for human and mouse, respectively, and these have provided a valuable resource for the scientific community. The authors summarize the history of the ENCODE Project, the achievements of ENCODE 1 and ENCODE 2, and how the new data generated and analysed in ENCODE 3 complement the previous phases.

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.