The rise in throughput and quality of long-read sequencing should allow unambiguous identification of full-length transcript isoforms. However, its application to single-cell RNA-seq has been limited by throughput and expense. Here we develop and characterize long-read Split-seq (LR-Split-seq), which uses combinatorial barcoding to sequence single cells with long reads. Applied to the C2C12 myogenic system, LR-split-seq associates isoforms to cell types with relative economy and design flexibility. We find widespread evidence of changing isoform expression during differentiation including alternative transcription start sites (TSS) and/or alternative internal exon usage. LR-Split-seq provides an affordable method for identifying cluster-specific isoforms in single cells.

BACKGROUND: Mammalian genomes contain millions of putative regulatory sequences, which are delineated by binding of multiple transcription factors. The degree to which spacing and orientation constraints among transcription factor binding sites contribute to the recognition and identity of regulatory sequence is an unresolved but important question that impacts our understanding of genome function and evolution. Global mechanisms that underlie phenomena including the size of regulatory sequences, their uniqueness, and their evolutionary turnover remain poorly described. RESULTS: Here, we ask whether models incorporating different degrees of spacing and orientation constraints among transcription factor binding sites are broadly consistent with several global properties of regulatory sequence. These properties include length, sequence diversity, turnover rate, and dominance of specific TFs in regulatory site identity and cell type specification. Models with and without spacing and orientation constraints are generally consistent with all observed properties of regulatory sequence, and with regulatory sequences being fundamentally small (~ 1 nucleosome). Uniqueness of regulatory regions and their rapid evolutionary turnover are expected under all models examined. An intriguing issue we identify is that the complexity of eukaryotic regulatory sites must scale with the number of active transcription factors, in order to accomplish observed specificity. CONCLUSIONS: Models of transcription factor binding with or without spacing and orientation constraints predict that regulatory sequences should be fundamentally short, unique, and turn over rapidly. We posit that the existence of master regulators may be, in part, a consequence of evolutionary pressure to limit the complexity and increase evolvability of regulatory sites.

BACKGROUND: The diversity of genomic alterations in cancer poses challenges to fully understanding the etiologies of the disease. Recent interest in infrequent mutations, in genes that reside in the "long tail" of the mutational distribution, uncovered new genes with significant implications in cancer development. The study of cancer-relevant genes often requires integrative approaches pooling together multiple types of biological data. Network propagation methods demonstrate high efficacy in achieving this integration. Yet, the majority of these methods focus their assessment on detecting known cancer genes or identifying altered subnetworks. In this paper, we introduce a network propagation approach that entirely focuses on prioritizing long tail genes with potential functional impact on cancer development. RESULTS: We identify sets of often overlooked, rarely to moderately mutated genes whose biological interactions significantly propel their mutation-frequency-based rank upwards during propagation in 17 cancer types. We call these sets "upward mobility genes" and hypothesize that their significant rank improvement indicates functional importance. We report new cancer-pathway associations based on upward mobility genes that are not previously identified using driver genes alone, validate their role in cancer cell survival in vitro using extensive genome-wide RNAi and CRISPR data repositories, and further conduct in vitro functional screenings resulting in the validation of 18 previously unreported genes. CONCLUSION: Our analysis extends the spectrum of cancer-relevant genes and identifies novel potential therapeutic targets.

BACKGROUND: Balancing the yield, quality and resistance to disease is a daunting challenge in crop breeding due to the negative relationship among these traits. Large-scale genomic landscape analysis of germplasm resources is considered to be an efficient approach to dissect the genetic basis of the complex traits. Central China is one of the main regions where the japonica rice is produced. However, dozens of high-yield rice varieties in this region still exist with low quality or susceptibility to blast disease, severely limiting their application in rice production. RESULTS: Here, we re-sequence 200 japonica rice varieties grown in central China over the past 30 years and analyze the genetic structure of these cultivars using 2.4 million polymorphic SNP markers. Genome-wide association mapping and selection scans indicate that strong selection for high-yield and taste quality associated with low-amylose content may have led to the loss of resistance to the rice blast fungus Magnaporthe oryzae. By extensive bioinformatic analyses of yield components, resistance to rice blast, and taste quality, we identify several superior alleles for these traits in the population. Based on this information, we successfully introduce excellent taste quality and blast-resistant alleles into the background of two high-yield cultivars and develop two elite lines, XY99 and JXY1, with excellent taste, high yield, and broad-spectrum of blast resistance. CONCLUSIONS: This is the first large-scale genomic landscape analysis of japonica rice varieties grown in central China and we demonstrate a balancing of multiple agronomic traits by genomic-based strategy.

BACKGROUND: Regulation of protein output at the level of translation allows for a rapid adaptation to dynamic changes to the cell's requirements. This precise control of gene expression is achieved by complex and interlinked biochemical processes that modulate both the protein synthesis rate and stability of each individual mRNA. A major factor coordinating this regulation is the Ccr4-Not complex. Despite playing a role in most stages of the mRNA life cycle, no attempt has been made to take a global integrated view of how the Ccr4-Not complex affects gene expression. RESULTS: This study has taken a comprehensive approach to investigate post-transcriptional regulation mediated by the Ccr4-Not complex assessing steady-state mRNA levels, ribosome position, mRNA stability, and protein production transcriptome-wide. Depletion of the scaffold protein CNOT1 results in a global upregulation of mRNA stability and the preferential stabilization of mRNAs enriched for G/C-ending codons. We also uncover that mRNAs targeted to the ER for their translation have reduced translational efficiency when CNOT1 is depleted, specifically downstream of the signal sequence cleavage site. In contrast, translationally upregulated mRNAs are normally localized in p-bodies, contain disorder-promoting amino acids, and encode nuclear localized proteins. Finally, we identify ribosome pause sites that are resolved or induced by the depletion of CNOT1. CONCLUSIONS: We define the key mRNA features that determine how the human Ccr4-Not complex differentially regulates mRNA fate and protein synthesis through a mechanism linked to codon composition, amino acid usage, and mRNA localization.

BACKGROUND: Zebrafish pigment cell differentiation provides an attractive model for studying cell fate progression as a neural crest progenitor engenders diverse cell types, including two morphologically distinct pigment cells: black melanophores and reflective iridophores. Nontrivial classical genetic and transcriptomic approaches have revealed essential molecular mechanisms and gene regulatory circuits that drive neural crest-derived cell fate decisions. However, how the epigenetic landscape contributes to pigment cell differentiation, especially in the context of iridophore cell fate, is poorly understood. RESULTS: We chart the global changes in the epigenetic landscape, including DNA methylation and chromatin accessibility, during neural crest differentiation into melanophores and iridophores to identify epigenetic determinants shaping cell type-specific gene expression. Motif enrichment in the epigenetically dynamic regions reveals putative transcription factors that might be responsible for driving pigment cell identity. Through this effort, in the relatively uncharacterized iridophores, we validate alx4a as a necessary and sufficient transcription factor for iridophore differentiation and present evidence on alx4a's potential regulatory role in guanine synthesis pathway. CONCLUSIONS: Pigment cell fate is marked by substantial DNA demethylation events coupled with dynamic chromatin accessibility to potentiate gene regulation through cis-regulatory control. Here, we provide a multi-omic resource for neural crest differentiation into melanophores and iridophores. This work led to the discovery and validation of iridophore-specific alx4a transcription factor.

Recent years have seen a revolution in single-cell RNA-sequencing (scRNA-seq) technologies, datasets, and analysis methods. Since 2016, the scRNA-tools database has cataloged software tools for analyzing scRNA-seq data. With the number of tools in the database passing 1000, we provide an update on the state of the project and the field. This data shows the evolution of the field and a change of focus from ordering cells on continuous trajectories to integrating multiple samples and making use of reference datasets. We also find that open science practices reward developers with increased recognition and help accelerate the field.

We present SquiggleNet, the first deep-learning model that can classify nanopore reads directly from their electrical signals. SquiggleNet operates faster than DNA passes through the pore, allowing real-time classification and read ejection. Using 1 s of sequencing data, the classifier achieves significantly higher accuracy than base calling followed by sequence alignment. Our approach is also faster and requires an order of magnitude less memory than alignment-based approaches. SquiggleNet distinguished human from bacterial DNA with over 90% accuracy, generalized to unseen bacterial species in a human respiratory meta genome sample, and accurately classified sequences containing human long interspersed repeat elements.

Haplotype-aware diploid genome assembly is crucial in genomics, precision medicine, and many other disciplines. Long-read sequencing technologies have greatly improved genome assembly. However, current long-read assemblers are either reference based, so introduce biases, or fail to capture the haplotype diversity of diploid genomes. We present phasebook, a de novo approach for reconstructing the haplotypes of diploid genomes from long reads. phasebook outperforms other approaches in terms of haplotype coverage by large margins, in addition to achieving competitive performance in terms of assembly errors and assembly contiguity.

BACKGROUND: Common walnut (Juglans regia L.) is one of the top four most consumed nuts in the world due to its health benefits and pleasant taste. Despite its economic importance, the evolutionary history and genetic control of its adaptation and agronomic traits remain largely unexplored. RESULTS: We report a comprehensive walnut genomic variation map based on whole-genome resequencing of 815 walnut accessions. Evolutionary analyses suggest that Chinese J. regia diverged from J. sigillata with extensive hybridizations after the split of the two species. In contrast to annual crops, the genetic diversity and heterozygous deleterious mutations of Chinese common walnut trees have continued to increase during the improvement process. Selective sweep analyses identify 902 genes uniquely selected in the improved common walnut compared to its progenitor population. Five major-effect loci are identified to be involved in walnut adaptations to temperature, precipitation, and altitude. Genome-wide association studies reveal 27 genomic loci responsible for 18 important agronomic traits, among which JrFAD2 and JrANR are the potentially major-effect causative genes controlling linoleic acid content and color of the endopleura of the nut, respectively. CONCLUSIONS: The largest genomic resource for walnuts to date has been generated and explored in this study, unveiling their evolutionary history and cracking the genetic code for agronomic traits and environmental adaptation of this economically crucial crop tree.

Erratum in Genome Biol. 2021 Nov 15;22(1):314.

Calling fusion genes from RNA-seq data is well established, but other transcriptional variants are difficult to detect using existing approaches. To identify all types of variants in transcriptomes we developed MINTIE, an integrated pipeline for RNA-seq data. We take a reference-free approach, combining de novo assembly of transcripts with differential expression analysis to identify up-regulated novel variants in a case sample. We compare MINTIE with eight other approaches, detecting > 85% of variants while no other method is able to achieve this. We posit that MINTIE will be able to identify new disease variants across a range of disease types.

BACKGROUND: Promoter-proximal pausing of RNA polymerase II (RNAPII) is a critical step for the precise regulation of gene expression. Despite the apparent close relationship between promoter-proximal pausing and nucleosome, the role of chromatin remodeler governing this step has mainly remained elusive. RESULTS: Here, we report highly confined RNAPII enrichments downstream of the transcriptional start site in Saccharomyces cerevisiae using PRO-seq experiments. This non-uniform distribution of RNAPII exhibits both similar and different characteristics with promoter-proximal pausing in Schizosaccharomyces pombe and metazoans. Interestingly, we find that Ino80p knockdown causes a significant upstream transition of promoter-proximal RNAPII for a subset of genes, relocating RNAPII from the main pausing site to the alternative pausing site. The proper positioning of RNAPII is largely dependent on nucleosome context. We reveal that the alternative pausing site is closely associated with the + 1 nucleosome, and nucleosome architecture around the main pausing site of these genes is highly phased. In addition, Ino80p knockdown results in an increase in fuzziness and a decrease in stability of the + 1 nucleosome. Furthermore, the loss of INO80 also leads to the shift of promoter-proximal RNAPII toward the alternative pausing site in mouse embryonic stem cells. CONCLUSIONS: Based on our collective results, we hypothesize that the highly conserved chromatin remodeler Ino80p is essential in establishing intact RNAPII pausing during early transcription elongation in various organisms, from budding yeast to mouse.

BACKGROUND: Nanopore long-read sequencing technology greatly expands the capacity of long-range, single-molecule DNA-modification detection. A growing number of analytical tools have been developed to detect DNA methylation from nanopore sequencing reads. Here, we assess the performance of different methylation-calling tools to provide a systematic evaluation to guide researchers performing human epigenome-wide studies. RESULTS: We compare seven analytic tools for detecting DNA methylation from nanopore long-read sequencing data generated from human natural DNA at a whole-genome scale. We evaluate the per-read and per-site performance of CpG methylation prediction across different genomic contexts, CpG site coverage, and computational resources consumed by each tool. The seven tools exhibit different performances across the evaluation criteria. We show that the methylation prediction at regions with discordant DNA methylation patterns, intergenic regions, low CG density regions, and repetitive regions show room for improvement across all tools. Furthermore, we demonstrate that 5hmC levels at least partly contribute to the discrepancy between bisulfite and nanopore sequencing. Lastly, we provide an online DNA methylation database ( https://nanome.jax.org ) to display the DNA methylation levels detected by nanopore sequencing and bisulfite sequencing data across different genomic contexts. CONCLUSIONS: Our study is the first systematic benchmark of computational methods for detection of mammalian whole-genome DNA modifications in nanopore sequencing. We provide a broad foundation for cross-platform standardization and an evaluation of analytical tools designed for genome-scale modified base detection using nanopore sequencing.

BACKGROUND: The 3' untranslated region (UTR) plays critical roles in determining the level of gene expression through effects on activities such as mRNA stability and translation. Functional elements within this region have largely been identified through analyses of native genes, which contain multiple co-evolved sequence features. RESULTS: To explore the effects of 3' UTR sequence elements outside of native sequence contexts, we analyze hundreds of thousands of random 50-mers inserted into the 3' UTR of a reporter gene in the yeast Saccharomyces cerevisiae. We determine relative protein expression levels from the fitness of transformants in a growth selection. We find that the consensus 3' UTR efficiency element significantly boosts expression, independent of sequence context; on the other hand, the consensus positioning element has only a small effect on expression. Some sequence motifs that are binding sites for Puf proteins substantially increase expression in the library, despite these proteins generally being associated with post-transcriptional downregulation of native mRNAs. Our measurements also allow a systematic examination of the effects of point mutations within efficiency element motifs across diverse sequence backgrounds. These mutational scans reveal the relative in vivo importance of individual bases in the efficiency element, which likely reflects their roles in binding the Hrp1 protein involved in cleavage and polyadenylation. CONCLUSIONS: The regulatory effects of some 3' UTR sequence features, like the efficiency element, are consistent regardless of sequence context. In contrast, the consequences of other 3' UTR features appear to be strongly dependent on their evolved context within native genes.

BACKGROUND: The endoplasmic reticulum (ER) is a membranous organelle that maintains proteostasis and cellular homeostasis, controlling the fine balance between health and disease. Dysregulation of the ER stress response has been implicated in intestinal inflammation associated with inflammatory bowel disease (IBD), a chronic condition characterized by changes to the mucosa and alteration of the gut microbiota. While the microbiota and microbially derived metabolites have also been implicated in ER stress, examples of this connection remain limited to a few observations from pathogenic bacteria. Furthermore, the mechanisms underlying the effects of bacterial metabolites on ER stress signaling have not been well established. RESULTS: Utilizing an XBP1s-GFP knock-in reporter colorectal epithelial cell line, we screened 399 microbiome-related metabolites for ER stress pathway modulation. We find both ER stress response inducers (acylated dipeptide aldehydes and bisindole methane derivatives) and suppressors (soraphen A) and characterize their activities on ER stress gene transcription and translation. We further demonstrate that these molecules modulate the ER stress pathway through protease inhibition or lipid metabolism interference. CONCLUSIONS: Our study identified novel links between classes of gut microbe-derived metabolites and the ER stress response, suggesting the potential for these metabolites to contribute to gut ER homeostasis and providing insight into the molecular mechanisms by which gut microbes impact intestinal epithelial cell homeostasis.

BACKGROUND: Alternative cleavage and polyadenylation (APA), an RNA processing event, occurs in over 70% of human protein-coding genes. APA results in mRNA transcripts with distinct 3' ends. Most APA occurs within 3' UTRs, which harbor regulatory elements that can impact mRNA stability, translation, and localization. RESULTS: APA can be profiled using a number of established computational tools that infer polyadenylation sites from standard, short-read RNA-seq datasets. Here, we benchmarked a number of such tools-TAPAS, QAPA, DaPars2, GETUTR, and APATrap- against 3'-Seq, a specialized RNA-seq protocol that enriches for reads at the 3' ends of genes, and Iso-Seq, a Pacific Biosciences (PacBio) single-molecule full-length RNA-seq method in their ability to identify polyadenylation sites and quantify polyadenylation site usage. We demonstrate that 3'-Seq and Iso-Seq are able to identify and quantify the usage of polyadenylation sites more reliably than computational tools that take short-read RNA-seq as input. However, we find that running one such tool, QAPA, with a set of polyadenylation site annotations derived from small quantities of 3'-Seq or Iso-Seq can reliably quantify variation in APA across conditions, such asacross genotypes, as demonstrated by the successful mapping of alternative polyadenylation quantitative trait loci (apaQTL). CONCLUSIONS: We envisage that our analyses will shed light on the advantages of studying APA with more specialized sequencing protocols, such as 3'-Seq or Iso-Seq, and the limitations of studying APA with short-read RNA-seq. We provide a computational pipeline to aid in the identification of polyadenylation sites and quantification of polyadenylation site usages using Iso-Seq data as input.

BACKGROUND: Pancreatic ductal adenocarcinoma initiation is most frequently caused by Kras mutations. RESULTS: Here, we apply biological, biochemical, and network biology methods to validate GEMM-derived cell models using inducible KrasG12D expression. We describe the time-dependent, chromatin remodeling program that impacts function during early oncogenic signaling. We find that the KrasG12D-induced transcriptional response is dominated by downregulated expression concordant with layers of epigenetic events. More open chromatin characterizes the ATAC-seq profile associated with a smaller group of upregulated genes and epigenetic marks. RRBS demonstrates that promoter hypermethylation does not account for the silencing of the extensive gene promoter network. Moreover, ChIP-Seq reveals that heterochromatin reorganization plays little role in this early transcriptional program. Notably, both gene activation and silencing primarily depend on the marking of genes with a combination of H3K27ac, H3K4me3, and H3K36me3. Indeed, integrated modeling of all these datasets shows that KrasG12D regulates its transcriptional program primarily through unique super-enhancers and enhancers, and marking specific gene promoters and bodies. We also report chromatin remodeling across genomic areas that, although not contributing directly to cis-gene transcription, are likely important for KrasG12D functions. CONCLUSIONS: In summary, we report a comprehensive, time-dependent, and coordinated early epigenomic program for KrasG12D in pancreatic cells, which is mechanistically relevant to understanding chromatin remodeling events underlying transcriptional outcomes needed for the function of this oncogene.

BACKGROUND: Cellular RNA-binding proteins (RBPs) have multiple roles in post-transcriptional control, and some are shown to bind DNA. However, the global localization and the general chromatin-binding ability of RBPs are not well-characterized and remain undefined in hematopoietic cells. RESULTS: We first provide a full view of RBPs' distribution pattern in the nucleus and screen for chromatin-enriched RBPs (Che-RBPs) in different human cells. Subsequently, by generating ChIP-seq, CLIP-seq, and RNA-seq datasets and conducting combined analysis, the transcriptional regulatory potentials of certain hematopoietic Che-RBPs are predicted. From this analysis, quaking (QKI5) emerges as a potential transcriptional activator during monocytic differentiation. QKI5 is over-represented in gene promoter regions, independent of RNA or transcription factors. Furthermore, DNA-bound QKI5 activates the transcription of several critical monocytic differentiation-associated genes, including CXCL2, IL16, and PTPN6. Finally, we show that the differentiation-promoting activity of QKI5 is largely dependent on CXCL2, irrespective of its RNA-binding capacity. CONCLUSIONS: Our study indicates that Che-RBPs are versatile factors that orchestrate gene expression in different cellular contexts, and identifies QKI5, a classic RBP regulating RNA processing, as a novel transcriptional activator during monocytic differentiation.

High-throughput biological data analysis commonly involves identifying features such as genes, genomic regions, and proteins, whose values differ between two conditions, from numerous features measured simultaneously. The most widely used criterion to ensure the analysis reliability is the false discovery rate (FDR), which is primarily controlled based on p-values. However, obtaining valid p-values relies on either reasonable assumptions of data distribution or large numbers of replicates under both conditions. Clipper is a general statistical framework for FDR control without relying on p-values or specific data distributions. Clipper outperforms existing methods for a broad range of applications in high-throughput data analysis.