A major challenge to long read sequencing data is their high error rate of up to 15%. We present Ratatosk, a method to correct long reads with short read data. We demonstrate on 5 human genome trios that Ratatosk reduces the error rate of long reads 6-fold on average with a median error rate as low as 0.22 %. SNP calls in Ratatosk corrected reads are nearly 99 % accurate and indel calls accuracy is increased by up to 37 %. An assembly of Ratatosk corrected reads from an Ashkenazi individual yields a contig N50 of 45 Mbp and less misassemblies than a PacBio HiFi reads assembly.

BACKGROUND: Polyploidization and introgression are major events driving plant genome evolution and influencing crop breeding. However, the mechanisms underlying the higher-order chromatin organization of subgenomes and alien chromosomes are largely unknown. RESULTS: We probe the three-dimensional chromatin architecture of Aikang 58 (AK58), a widely cultivated allohexaploid wheat variety in China carrying the 1RS/1BL translocation chromosome. The regions involved in inter-chromosomal interactions, both within and between subgenomes, have highly similar sequences. Subgenome-specific territories tend to be connected by subgenome-dominant homologous transposable elements (TEs). The alien 1RS chromosomal arm, which was introgressed from rye and differs from its wheat counterpart, has relatively few inter-chromosome interactions with wheat chromosomes. An analysis of local chromatin structures reveals topologically associating domain (TAD)-like regions covering 52% of the AK58 genome, the boundaries of which are enriched with active genes, zinc-finger factor-binding motifs, CHH methylation, and 24-nt small RNAs. The chromatin loops are mostly localized around TAD boundaries, and the number of gene loops is positively associated with gene activity. CONCLUSIONS: The present study reveals the impact of the genetic sequence context on the higher-order chromatin structure and subgenome stability in hexaploid wheat. Specifically, we characterized the sequence homology-mediated inter-chromosome interactions and the non-canonical role of subgenome-biased TEs. Our findings may have profound implications for future investigations of the interplay between genetic sequences and higher-order structures and their consequences on polyploid genome evolution and introgression-based breeding of crop plants.

PIWI proteins, a subfamily of PAZ/PIWI Domain family RNA-binding proteins, are best known for their function in silencing transposons and germline development by partnering with small noncoding RNAs called PIWI-interacting RNAs (piRNAs). However, recent studies have revealed multifaceted roles of the PIWI-piRNA pathway in regulating the expression of other major classes of RNAs in germ cells. In this review, we summarize how PIWI proteins and piRNAs regulate the expression of many disparate RNAs, describing a highly complex global genomic regulatory relationship at the RNA level through which piRNAs functionally connect all major constituents of the genome in the germline.

BACKGROUND: Seminal studies of vertebrate protein evolution speculated that gene regulatory changes can drive anatomical innovations. However, very little is known about gene regulatory network (GRN) evolution associated with phenotypic effect across ecologically diverse species. Here we use a novel approach for comparative GRN analysis in vertebrate species to study GRN evolution in representative species of the most striking examples of adaptive radiations, the East African cichlids. We previously demonstrated how the explosive phenotypic diversification of East African cichlids can be attributed to diverse molecular mechanisms, including accelerated regulatory sequence evolution and gene expression divergence. RESULTS: To investigate these mechanisms across species at a genome-wide scale, we develop a novel computational pipeline that predicts regulators for co-extant and ancestral co-expression modules along a phylogeny, and candidate regulatory regions associated with traits under selection in cichlids. As a case study, we apply our approach to a well-studied adaptive trait-the visual system-for which we report striking cases of network rewiring for visual opsin genes, identify discrete regulatory variants, and investigate their association with cichlid visual system evolution. In regulatory regions of visual opsin genes, in vitro assays confirm that transcription factor binding site mutations disrupt regulatory edges across species and segregate according to lake species phylogeny and ecology, suggesting GRN rewiring in radiating cichlids. CONCLUSIONS: Our approach reveals numerous novel potential candidate regulators and regulatory regions across cichlid genomes, including some novel and some previously reported associations to known adaptive evolutionary traits.

BACKGROUND: Metastatic progress is the primary cause of death in most cancers, yet the regulatory dynamics driving the cellular changes necessary for metastasis remain poorly understood. Multi-omics approaches hold great promise for addressing this challenge; however, current analysis tools have limited capabilities to systematically integrate transcriptomic, epigenomic, and cistromic information to accurately define the regulatory networks critical for metastasis. RESULTS: To address this limitation, we use a purposefully generated cellular model of colon cancer invasiveness to generate multi-omics data, including expression, accessibility, and selected histone modification profiles, for increasing levels of invasiveness. We then adopt a rigorous probabilistic framework for joint inference from the resulting heterogeneous data, along with transcription factor binding profiles. Our approach uses probabilistic graphical models to leverage the functional information provided by specific epigenomic changes, models the influence of multiple transcription factors simultaneously, and automatically learns the activating or repressive roles of cis-regulatory events. Global analysis of these relationships reveals key transcription factors driving invasiveness, as well as their likely target genes. Disrupting the expression of one of the highly ranked transcription factors JunD, an AP-1 complex protein, confirms functional relevance to colon cancer cell migration and invasion. Transcriptomic profiling confirms key regulatory targets of JunD, and a gene signature derived from the model demonstrates strong prognostic potential in TCGA colorectal cancer data. CONCLUSIONS: Our work sheds new light into the complex molecular processes driving colon cancer metastasis and presents a statistically sound integrative approach to analyze multi-omics profiles of a dynamic biological process.

Update of bioRxiv. 2020 Oct 03;:

BACKGROUND: Transcription factor (TF) binding specificity is determined via a complex interplay between the transcription factor's DNA binding preference and cell type-specific chromatin environments. The chromatin features that correlate with transcription factor binding in a given cell type have been well characterized. For instance, the binding sites for a majority of transcription factors display concurrent chromatin accessibility. However, concurrent chromatin features reflect the binding activities of the transcription factor itself and thus provide limited insight into how genome-wide TF-DNA binding patterns became established in the first place. To understand the determinants of transcription factor binding specificity, we therefore need to examine how newly activated transcription factors interact with sequence and preexisting chromatin landscapes. RESULTS: Here, we investigate the sequence and preexisting chromatin predictors of TF-DNA binding by examining the genome-wide occupancy of transcription factors that have been induced in well-characterized chromatin environments. We develop Bichrom, a bimodal neural network that jointly models sequence and preexisting chromatin data to interpret the genome-wide binding patterns of induced transcription factors. We find that the preexisting chromatin landscape is a differential global predictor of TF-DNA binding; incorporating preexisting chromatin features improves our ability to explain the binding specificity of some transcription factors substantially, but not others. Furthermore, by analyzing site-level predictors, we show that transcription factor binding in previously inaccessible chromatin tends to correspond to the presence of more favorable cognate DNA sequences. CONCLUSIONS: Bichrom thus provides a framework for modeling, interpreting, and visualizing the joint sequence and chromatin landscapes that determine TF-DNA binding dynamics.

There are no comprehensive methods to identify N6-methyladenosine (m6A) at single-base resolution for every single transcript, which is necessary for the estimation of m6A abundance. We develop a new pipeline called Nanom6A for the identification and quantification of m6A modification at single-base resolution using Nanopore direct RNA sequencing based on an XGBoost model. We validate our method using methylated RNA immunoprecipitation sequencing (MeRIP-Seq) and m6A-sensitive RNA-endoribonuclease-facilitated sequencing (m6A-REF-seq), confirming high accuracy. Using this method, we provide a transcriptome-wide quantification of m6A modification in stem-differentiating xylem and reveal that different alternative polyadenylation (APA) usage shows a different ratio of m6A.

BACKGROUND: Structural variations (SVs), a major resource of genomic variation, can have profound consequences on phenotypic variation, yet the impacts of SVs remain largely unexplored in crops. RESULTS: Here, we generate a high-quality de novo genome assembly for a flat-fruit peach cultivar and produce a comprehensive SV map for peach, as a high proportion of genomic sequence is occupied by heterozygous SVs in the peach genome. We conduct population-level analyses that indicate SVs have undergone strong purifying selection during peach domestication, and find evidence of positive selection, with a significant preference for upstream and intronic regions during later peach improvement. We perform a SV-based GWAS that identifies a large 1.67-Mb heterozygous inversion that segregates perfectly with flat-fruit shape. Mechanistically, this derived allele alters the expression of the PpOFP2 gene positioned near the proximal breakpoint of the inversion, and we confirm in transgenic tomatoes that PpOFP2 is causal for flat-fruit shape. CONCLUSIONS: Thus, beyond introducing new genomics resources for peach research, our study illustrates how focusing on SV data can drive basic functional discoveries in plant science.

BACKGROUND: The folding of proteins is challenging in the highly crowded and sticky environment of a cell. Regulation of translation elongation may play a crucial role in ensuring the correct folding of proteins. Much of our knowledge regarding translation elongation comes from the sequencing of mRNA fragments protected by single ribosomes by ribo-seq. However, larger protected mRNA fragments have been observed, suggesting the existence of an alternative and previously hidden layer of regulation. RESULTS: In this study, we performed disome-seq to sequence mRNA fragments protected by two stacked ribosomes, a product of translational pauses during which the 5'-elongating ribosome collides with the 3'-paused one. We detected widespread ribosome collisions that are related to slow ribosome release when stop codons are at the A-site, slow peptide bond formation from proline, glycine, asparagine, and cysteine when they are at the P-site, and slow leaving of polylysine from the exit tunnel of ribosomes. The structure of disomes obtained by cryo-electron microscopy suggests a different conformation from the substrate of the ribosome-associated protein quality control pathway. Collisions occurred more frequently in the gap regions between α-helices, where a translational pause can prevent the folding interference from the downstream peptides. Paused or collided ribosomes are associated with specific chaperones, which can aid in the cotranslational folding of the nascent peptides. CONCLUSIONS: Therefore, cells use regulated ribosome collisions to ensure protein homeostasis.

BACKGROUND: Small RNAs (sRNAs) including microRNAs (miRNAs) and small interfering RNAs (siRNAs) serve as core players in gene silencing at transcriptional and post-transcriptional levels in plants, but their subcellular localization has not yet been well studied, thus limiting our mechanistic understanding of sRNA action. RESULTS: We investigate the cytoplasmic partitioning of sRNAs and their targets globally in maize (Zea mays, inbred line "B73") and rice (Oryza sativa, cv. "Nipponbare") by high-throughput sequencing of polysome-associated sRNAs and 3' cleavage fragments, and find that both miRNAs and a subset of 21-nucleotide (nt)/22-nt siRNAs are enriched on membrane-bound polysomes (MBPs) relative to total polysomes (TPs) across different tissues. Most of the siRNAs are generated from transposable elements (TEs), and retrotransposons positively contributed to MBP overaccumulation of 22-nt TE-derived siRNAs (TE-siRNAs) as opposed to DNA transposons. Widespread occurrence of miRNA-mediated target cleavage is observed on MBPs, and a large proportion of these cleavage events are MBP-unique. Reproductive 21PHAS (21-nt phasiRNA-generating) and 24PHAS (24-nt phasiRNA-generating) precursors, which were commonly considered as noncoding RNAs, are bound by polysomes, and high-frequency cleavage of 21PHAS precursors by miR2118 and 24PHAS precursors by miR2275 is further detected on MBPs. Reproductive 21-nt phasiRNAs are enriched on MBPs as opposed to TPs, whereas 24-nt phasiRNAs are nearly completely devoid of polysome occupancy. CONCLUSIONS: MBP overaccumulation is a conserved pattern for cytoplasmic partitioning of sRNAs, and endoplasmic reticulum (ER)-bound ribosomes function as an independent regulatory layer for miRNA-induced gene silencing and reproductive phasiRNA biosynthesis in maize and rice.

BACKGROUND: Although the genomes of monozygotic twins are practically identical, their methylomes may evolve divergently throughout their lifetime as a consequence of factors such as the environment or aging. Particularly for young and healthy monozygotic twins, DNA methylation divergence, if any, may be restricted to stochastic processes occurring post-twinning during embryonic development and early life. However, to what extent such stochastic mechanisms can systematically provide a stable source of inter-individual epigenetic variation remains uncertain until now. RESULTS: We enriched for inter-individual stochastic variation by using an equivalence testing-based statistical approach on whole blood methylation microarray data from healthy adolescent monozygotic twins. As a result, we identified 333 CpGs displaying similarly large methylation variation between monozygotic co-twins and unrelated individuals. Although their methylation variation surpasses measurement error and is stable in a short timescale, susceptibility to aging is apparent in the long term. Additionally, 46% of these CpGs were replicated in adipose tissue. The identified sites are significantly enriched at the clustered protocadherin loci, known for stochastic methylation in developing neurons. We also confirmed an enrichment in monozygotic twin DNA methylation discordance at these loci in whole genome bisulfite sequencing data from blood and adipose tissue. CONCLUSIONS: We have isolated a component of stochastic methylation variation, distinct from genetic influence, measurement error, and epigenetic drift. Biomarkers enriched in this component may serve in the future as the basis for universal epigenetic fingerprinting, relevant for instance in the discrimination of monozygotic twin individuals in forensic applications, currently impossible with standard DNA profiling.

BACKGROUND: N6-methyladenosine (m6A) modification is known to impact many aspects of RNA metabolism, including mRNA stability and translation, and is highly prevalent in the brain. RESULTS: We show that m6A modification displays temporal and spatial dynamics during neurodevelopment and aging. Genes that are temporally differentially methylated are more prone to have mRNA expression changes and affect many pathways associated with nervous system development. Furthermore, m6A shows a distinct tissue-specific methylation profile, which is most pronounced in the hypothalamus. Tissue-specific methylation is associated with an increase in mRNA expression and is associated with tissue-specific developmental processes. During the aging process, we observe significantly more m6A sites as age increases, in both mouse and human. We show a high level of overlap between mouse and human; however, humans at both young and old ages consistently show more m6A sites compared to mice. Differential m6A sites are found to be enriched in alternative untranslated regions of genes that affect aging-related pathways. These m6A sites are associated with a strong negative effect on mRNA expression. We also show that many Alzheimer-related transcripts exhibit decreased m6A methylation in a mouse model of Alzheimer's disease, which is correlated with reduced protein levels. CONCLUSIONS: Our results suggest that m6A exerts a critical function in both early and late brain development in a spatio-temporal fashion. Furthermore, m6A controls protein levels of key genes involved in Alzheimer's disease-associated pathways, suggesting that m6A plays an important role in aging and neurodegenerative disease.

BACKGROUND: The regulation of messenger RNA (mRNA) stability has a profound impact on gene expression dynamics during embryogenesis. For example, in animals, maternally deposited mRNAs are degraded after fertilization to enable new developmental trajectories. Regulatory sequences in 3' untranslated regions (3'UTRs) have long been considered the central determinants of mRNA stability. However, recent work indicates that the coding sequence also possesses regulatory information. Specifically, translation in cis impacts mRNA stability in a codon-dependent manner. However, the strength of this mechanism during embryogenesis, as well as its relationship with other known regulatory elements, such as microRNA, remains unclear. RESULTS: Here, we show that codon composition is a major predictor of mRNA stability in the early embryo. We show that this mechanism works in combination with other cis-regulatory elements to dictate mRNA stability in zebrafish and Xenopus embryos as well as in mouse and human cells. Furthermore, we show that microRNA targeting efficacy can be affected by substantial enrichment of optimal (stabilizing) or non-optimal (destabilizing) codons. Lastly, we find that one microRNA, miR-430, antagonizes the stabilizing effect of optimal codons during early embryogenesis in zebrafish. CONCLUSIONS: By integrating the contributions of different regulatory mechanisms, our work provides a framework for understanding how combinatorial control of mRNA stability shapes the gene expression landscape.

BACKGROUND: Crosstalk between genetic, epigenetic, and immune alterations in upper tract urothelial carcinomas and their role in shaping muscle invasiveness and patient outcome are poorly understood. RESULTS: We perform an integrative genome- and methylome-wide profiling of diverse non-muscle-invasive and muscle-invasive upper tract urothelial carcinomas. In addition to mutations of FGFR3 and KDM6A, we identify ZFP36L1 as a novel, significantly mutated tumor suppressor gene. Overall, mutations of ZFP36 family genes (ZFP36, ZFP36L1, and ZFP36L2) are identified in 26.7% of cases, which display a high mutational load. Unsupervised DNA methylation subtype classification identifies two epi-clusters associated with distinct muscle-invasive status and patient outcome, namely, EpiC-low and EpiC-high. While the former is hypomethylated, immune-depleted, and enriched for FGFR3-mutated, the latter is hypermethylated, immune-infiltrated, and tightly associated with somatic mutations of SWI/SNF genes. CONCLUSIONS: Our study delineates for the first time the key role for convergence between genetic and epigenetic alterations in shaping clinicopathological and immune upper tract urothelial carcinoma features.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers due to its high metastasis rate in the liver. However, little is known about the molecular features of hepatic metastases due to difficulty in obtaining fresh tissues and low tumor cellularity. RESULTS: We conduct exome sequencing and RNA sequencing for synchronous surgically resected primary tumors and the paired hepatic metastases from 17 hepatic oligometastatic pancreatic ductal adenocarcinoma and validate our findings in specimens from 35 of such cases. The comprehensive analysis of somatic mutations, copy number alterations, and gene expressions show high similarity between primary tumors and hepatic metastases. However, hepatic metastases also show unique characteristics, such as a higher degree of 3p21.1 loss, stronger abilities of proliferation, downregulation of epithelial to mesenchymal transition activity, and metabolic rewiring. More interesting, altered tumor microenvironments are observed in hepatic metastases, especially a higher proportion of tumor infiltrating M2 macrophage and upregulation of complement cascade. Further experiments demonstrate that expression of C1q increases in primary tumors and hepatic metastases, C1q is mainly produced by M2 macrophage, and C1q promotes migration and invasion of PDAC cells. CONCLUSION: Taken together, we find potential factors that contribute to different stages of PDAC metastasis. Our study broadens the understanding of molecular mechanisms driving PDAC metastasis.

Most sequencing data analyses start by aligning sequencing reads to a linear reference genome, but failure to account for genetic variation leads to reference bias and confounding of results downstream. Other approaches replace the linear reference with structures like graphs that can include genetic variation, incurring major computational overhead. We propose the reference flow alignment method that uses multiple population reference genomes to improve alignment accuracy and reduce reference bias. Compared to the graph aligner vg, reference flow achieves a similar level of accuracy and bias avoidance but with 14% of the memory footprint and 5.5 times the speed.

BACKGROUND: Long-read sequencing of full-length cDNAs enables the detection of structures of aberrant splicing isoforms in cancer cells. These isoforms are occasionally translated, presented by HLA molecules, and recognized as neoantigens. This study used a long-read sequencer (MinION) to construct a comprehensive catalog of aberrant splicing isoforms in non-small-cell lung cancers, by which novel isoforms and potential neoantigens are identified. RESULTS: Full-length cDNA sequencing is performed using 22 cell lines, and a total of 2021 novel splicing isoforms are identified. The protein expression of some of these isoforms is then validated by proteome analysis. Ablations of a nonsense-mediated mRNA decay (NMD) factor, UPF1, and a splicing factor, SF3B1, are found to increase the proportion of aberrant transcripts. NetMHC evaluation of the binding affinities to each type of HLA molecule reveals that some of the isoforms potentially generate neoantigen candidates. We also identify aberrant splicing isoforms in seven non-small-cell lung cancer specimens. An enzyme-linked immune absorbent spot assay indicates that approximately half the peptide candidates have the potential to activate T cell responses through their interaction with HLA molecules. Finally, we estimate the number of isoforms in The Cancer Genome Atlas (TCGA) datasets by referring to the constructed catalog and found that disruption of NMD factors is significantly correlated with the number of splicing isoforms found in the TCGA-Lung Adenocarcinoma data collection. CONCLUSIONS: Our results indicate that long-read sequencing of full-length cDNAs is essential for the precise identification of aberrant transcript structures in cancer cells.

BACKGROUND: Plant genome engineering mediated by various CRISPR-based tools requires specific protospacer adjacent motifs (PAMs), such as the well-performed NGG, NG, and NNG, to initiate target recognition, which notably restricts the editable range of the plant genome. RESULTS: In this study, we thoroughly investigate the nuclease activity and the PAM preference of two structurally engineered SpCas9 variants, SpG and SpRY, in transgenic rice. Our study shows that SpG nuclease favors NGD PAMs, albeit less efficiently than the previously described SpCas9-NG, and that SpRY nuclease achieves efficient editing across a wide range of genomic loci, exhibiting a preference of NGD as well as NAN PAMs. Furthermore, SpRY-fused cytidine deaminase hAID*Δ and adenosine deaminase TadA8e are generated, respectively. These constructs efficiently induce C-to-T and A-to-G conversions in the target genes toward various non-canonical PAMs, including non-G PAMs. Remarkably, high-frequency self-editing events (indels and DNA fragments deletion) in the integrated T-DNA fragments as a result of the nuclease activity of SpRY are observed, whereas the self-editing of SpRY nickase-mediated base editor is quite low in transgenic rice lines. CONCLUSIONS: The broad PAM compatibility of SpRY greatly expands the targeting scope of CRISPR-based tools in plant genome engineering.

BACKGROUND: mRNA processing is critical for gene expression. A challenge in regulating mRNA processing is how to recognize the actual mRNA processing sites, such as splice and polyadenylation sites, when the sequence content is insufficient for this purpose. Previous studies suggested that RNA structure affects mRNA processing. However, the regulatory role of RNA structure in mRNA processing remains unclear. RESULTS: Here, we perform in vivo selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) chemical profiling on Arabidopsis and generate the in vivo nuclear RNA structure landscape. We find that nuclear mRNAs fold differently from cytosolic mRNAs across translation start and stop sites. Notably, we discover a two-nucleotide single-stranded RNA structure feature upstream of 5' splice sites that is strongly associated with splicing and the selection of alternative 5' splice sites. The regulatory role of this RNA structure feature is further confirmed by experimental validation. Moreover, we find the single-strandedness of branch sites is also associated with 3' splice site recognition. We also identify an RNA structure feature comprising two close-by single-stranded regions that is specifically associated with both polyadenylation and alternative polyadenylation events. CONCLUSIONS: We successfully identify pre-mRNA structure features associated with splicing and polyadenylation at whole-genome scale and validate an RNA structure feature which can regulate splicing. Our study unveils a new RNA structure regulatory mechanism for mRNA processing.

Distinguishing biological from technical variation is crucial when integrating and comparing single-cell genomics datasets across different experiments. Existing methods lack the capability in explicitly distinguishing these two variations, often leading to the removal of both variations. Here, we present an integration method scMC to remove the technical variation while preserving the intrinsic biological variation. scMC learns biological variation via variance analysis to subtract technical variation inferred in an unsupervised manner. Application of scMC to both simulated and real datasets from single-cell RNA-seq and ATAC-seq experiments demonstrates its capability of detecting context-shared and context-specific biological signals via accurate alignment.

BACKGROUND: Bone accrual impacts lifelong skeletal health, but genetic discovery has been primarily limited to cross-sectional study designs and hampered by uncertainty about target effector genes. Here, we capture this dynamic phenotype by modeling longitudinal bone accrual across 11,000 bone scans in a cohort of healthy children and adolescents, followed by genome-wide association studies (GWAS) and variant-to-gene mapping with functional follow-up. RESULTS: We identify 40 loci, 35 not previously reported, with various degrees of supportive evidence, half residing in topological associated domains harboring known bone genes. Of several loci potentially associated with later-life fracture risk, a candidate SNP lookup provides the most compelling evidence for rs11195210 (SMC3). Variant-to-gene mapping combining ATAC-seq to assay open chromatin with high-resolution promoter-focused Capture C identifies contacts between GWAS loci and nearby gene promoters. siRNA knockdown of gene expression supports the putative effector gene at three specific loci in two osteoblast cell models. Finally, using CRISPR-Cas9 genome editing, we confirm that the immediate genomic region harboring the putative causal SNP influences PRPF38A expression, a location which is predicted to coincide with a set of binding sites for relevant transcription factors. CONCLUSIONS: Using a new longitudinal approach, we expand the number of genetic loci putatively associated with pediatric bone gain. Functional follow-up in appropriate cell models finds novel candidate genes impacting bone accrual. Our data also raise the possibility that the cell fate decision between osteogenic and adipogenic lineages is important in normal bone accrual.

Crop genomics has seen dramatic advances in recent years due to improvements in sequencing technology, assembly methods, and computational resources. These advances have led to the development of new tools to facilitate crop improvement. The study of structural variation within species and the characterization of the pan-genome has revealed extensive genome content variation among individuals within a species that is paradigm shifting to crop genomics and improvement. Here, we review advances in crop genomics and how utilization of these tools is shifting in light of pan-genomes that are becoming available for many crop species.

BACKGROUND: Redundancy is a common feature of genomes, presumably to ensure robust growth under different and changing conditions. Genome compaction, removing sequences nonessential for given conditions, provides a novel way to understand the core principles of life. The synthetic chromosome rearrangement and modification by loxP-mediated evolution (SCRaMbLE) system is a unique feature implanted in the synthetic yeast genome (Sc2.0), which is proposed as an effective tool for genome minimization. As the Sc2.0 project is nearing its completion, we have begun to explore the application of the SCRaMbLE system in genome compaction. RESULTS: We develop a method termed SCRaMbLE-based genome compaction (SGC) and demonstrate that a synthetic chromosome arm (synXIIL) can be efficiently reduced. The pre-introduced episomal essential gene array significantly enhances the compacting ability of SGC, not only by enabling the deletion of nonessential genes located in essential gene containing loxPsym units but also by allowing more chromosomal sequences to be removed in a single SGC process. Further compaction is achieved through iterative SGC, revealing that at least 39 out of 65 nonessential genes in synXIIL can be removed collectively without affecting cell viability at 30 °C in rich medium. Approximately 40% of the synthetic sequence, encoding 28 genes, is found to be dispensable for cell growth at 30 °C in rich medium and several genes whose functions are needed under specified conditions are identified. CONCLUSIONS: We develop iterative SGC with the aid of eArray as a generic yet effective tool to compact the synthetic yeast genome.

BACKGROUND: Brown algae evolved complex multicellularity independently of the animal and land plant lineages and are the third most developmentally complex phylogenetic group on the planet. An understanding of developmental processes in this group is expected to provide important insights into the evolutionary events necessary for the emergence of complex multicellularity. Here, we focus on mechanisms of epigenetic regulation involving post-translational modifications of histone proteins. RESULTS: A total of 47 histone post-translational modifications are identified, including a novel mark H2AZR38me1, but Ectocarpus lacks both H3K27me3 and the major polycomb complexes. ChIP-seq identifies modifications associated with transcription start sites and gene bodies of active genes and with transposons. H3K79me2 exhibits an unusual pattern, often marking large genomic regions spanning several genes. Transcription start sites of closely spaced, divergently transcribed gene pairs share a common nucleosome-depleted region and exhibit shared histone modification peaks. Overall, patterns of histone modifications are stable through the life cycle. Analysis of histone modifications at generation-biased genes identifies a correlation between the presence of specific chromatin marks and the level of gene expression. CONCLUSIONS: The overview of histone post-translational modifications in the brown alga presented here will provide a foundation for future studies aimed at understanding the role of chromatin modifications in the regulation of brown algal genomes.

BACKGROUND: Mouse models have allowed for the direct interrogation of genetic effects on molecular, physiological, and behavioral brain phenotypes. However, it is unknown to what extent neurological or psychiatric traits may be human- or primate-specific and therefore which components can be faithfully recapitulated in mouse models. RESULTS: We compare conservation of co-expression in 116 independent data sets derived from human, mouse, and non-human primate representing more than 15,000 total samples. We observe greater changes occurring on the human lineage than mouse, and substantial regional variation that highlights cerebral cortex as the most diverged region. Glia, notably microglia, astrocytes, and oligodendrocytes are the most divergent cell type, three times more on average than neurons. We show that cis-regulatory sequence divergence explains a significant fraction of co-expression divergence. Moreover, protein coding sequence constraint parallels co-expression conservation, such that genes with loss of function intolerance are enriched in neuronal, rather than glial modules. We identify dozens of human neuropsychiatric and neurodegenerative disease risk genes, such as COMT, PSEN-1, LRRK2, SHANK3, and SNCA, with highly divergent co-expression between mouse and human and show that 3D human brain organoids recapitulate in vivo co-expression modules representing several human cell types. CONCLUSIONS: We identify robust co-expression modules reflecting whole-brain and regional patterns of gene expression. Compared with those that represent basic metabolic processes, cell-type-specific modules, most prominently glial modules, are the most divergent between species. These data and analyses serve as a foundational resource to guide human disease modeling and its interpretation.

BACKGROUND: Frequent activation of the co-transcriptional factor YAP is observed in a large number of solid tumors. Activated YAP associates with enhancer loci via TEAD4-DNA-binding protein and stimulates cancer aggressiveness. Although thousands of YAP/TEAD4 binding-sites are annotated, their functional importance is unknown. Here, we aim at further identification of enhancer elements that are required for YAP functions. RESULTS: We first apply genome-wide ChIP profiling of YAP to systematically identify enhancers that are bound by YAP/TEAD4. Next, we implement a genetic approach to uncover functions of YAP/TEAD4-associated enhancers, demonstrate its robustness, and use it to reveal a network of enhancers required for YAP-mediated proliferation. We focus on EnhancerTRAM2, as its target gene TRAM2 shows the strongest expression-correlation with YAP activity in nearly all tumor types. Interestingly, TRAM2 phenocopies the YAP-induced cell proliferation, migration, and invasion phenotypes and correlates with poor patient survival. Mechanistically, we identify FSTL-1 as a major direct client of TRAM2 that is involved in these phenotypes. Thus, TRAM2 is a key novel mediator of YAP-induced oncogenic proliferation and cellular invasiveness. CONCLUSIONS: YAP is a transcription co-factor that binds to thousands of enhancer loci and stimulates tumor aggressiveness. Using unbiased functional approaches, we dissect YAP enhancer network and characterize TRAM2 as a novel mediator of cellular proliferation, migration, and invasion. Our findings elucidate how YAP induces cancer aggressiveness and may assist diagnosis of cancer metastasis.

Massive genome sequencing data have inspired new challenges in personalized treatments and facilitated oncological drug discovery. We present a comprehensive database, My Personal Mutanome (MPM), for accelerating the development of precision cancer medicine protocols. MPM contains 490,245 mutations from over 10,800 tumor exomes across 33 cancer types in The Cancer Genome Atlas mapped to 94,563 structure-resolved/predicted protein-protein interaction interfaces ("edgetic") and 311,022 functional sites ("nodetic"), including ligand-protein binding sites and 8 types of protein posttranslational modifications. In total, 8884 survival results and 1,271,132 drug responses are obtained for these mapped interactions. MPM is available at https://mutanome.lerner.ccf.org .

BACKGROUND: N6-methyladenosine (m6A) and adenosine-to-inosine (A-to-I) RNA editing are two of the most abundant RNA modification events affecting adenosines in mammals. Both these RNA modifications determine mRNA fate and play a pivotal role in tumor development and progression. RESULTS: Here, we show that METTL3, upregulated in glioblastoma, methylates ADAR1 mRNA and increases its protein level leading to a pro-tumorigenic mechanism connecting METTL3, YTHDF1, and ADAR1. We show that ADAR1 plays a cancer-promoting role independently of its deaminase activity by binding CDK2 mRNA, underlining the importance of ADARs as essential RNA-binding proteins for cell homeostasis as well as cancer progression. Additionally, we show that ADAR1 knockdown is sufficient to strongly inhibit glioblastoma growth in vivo. CONCLUSIONS: Hence, our findings underscore METTL3/ADAR1 axis as a novel crucial pathway in cancer progression that connects m6A and A-to-I editing post-transcriptional events.

Comment in Nat Methods. 2021 Aug;18(8):856.

BACKGROUND: Alternative splicing is a rich source of tumor-specific neoantigen targets for immunotherapy. This holds promise for glioblastomas (GBMs), the most common primary tumors of the adult brain, which are resistant to standard-of-care therapy. Although most clinical trials enroll patients at recurrence, most preclinical studies have been done with specimens from primary disease. There are limited expression data from GBMs at recurrence and surprisingly little is known about the evolution of splicing patterns under therapy. RESULT: We profile 37 primary-recurrent paired human GBM specimens via RNA sequencing. We describe the landscape of alternative splicing in GBM at recurrence and contrast that to primary and non-malignant brain-tissue specimens. By screening single-cell atlases, we identify cell-type-specific splicing patterns and novel splicing events in cell-surface proteins that are suitable targets for engineered T cell therapies. We identify recurrent-specific isoforms of mitogen-activated kinase pathway genes that enhance invasiveness and are preferentially expressed by stem-like cells. CONCLUSION: These studies shed light on gene expression in recurrent GBM and identify novel targets for therapeutic development.

The resources generated by the GTEx consortium offer unprecedented opportunities to advance our understanding of the biology of human diseases. Here, we present an in-depth examination of the phenotypic consequences of transcriptome regulation and a blueprint for the functional interpretation of genome-wide association study-discovered loci. Across a broad set of complex traits and diseases, we demonstrate widespread dose-dependent effects of RNA expression and splicing. We develop a data-driven framework to benchmark methods that prioritize causal genes and find no single approach outperforms the combination of multiple approaches. Using colocalization and association approaches that take into account the observed allelic heterogeneity of gene expression, we propose potential target genes for 47% (2519 out of 5385) of the GWAS loci examined.

Erratum in Genome Biol. 2021 Mar 25;22(1):88.

Topologically associating domains (TADs) are the organizational units of chromosome structures. TADs can contain TADs, thus forming a hierarchy. TAD hierarchies can be inferred from Hi-C data through coding trees. However, the current method for computing coding trees is not optimal. In this paper, we propose optimal algorithms for this computation. In comparison with seven state-of-art methods using two public datasets, from GM12878 and IMR90 cells, SuperTAD shows a significant enrichment of structural proteins around detected boundaries and histone modifications within TADs and displays a high consistency between various resolutions of identical Hi-C matrices.

BACKGROUND: There is currently no method to precisely measure the errors that occur in the sequencing instrument/sequencer, which is critical for next-generation sequencing applications aimed at discovering the genetic makeup of heterogeneous cellular populations. RESULTS: We propose a novel computational method, SequencErr, to address this challenge by measuring the base correspondence between overlapping regions in forward and reverse reads. An analysis of 3777 public datasets from 75 research institutions in 18 countries revealed the sequencer error rate to be ~ 10 per million (pm) and 1.4% of sequencers and 2.7% of flow cells have error rates > 100 pm. At the flow cell level, error rates are elevated in the bottom surfaces and > 90% of HiSeq and NovaSeq flow cells have at least one outlier error-prone tile. By sequencing a common DNA library on different sequencers, we demonstrate that sequencers with high error rates have reduced overall sequencing accuracy, and removal of outlier error-prone tiles improves sequencing accuracy. We demonstrate that SequencErr can reveal novel insights relative to the popular quality control method FastQC and achieve a 10-fold lower error rate than popular error correction methods including Lighter and Musket. CONCLUSIONS: Our study reveals novel insights into the nature of DNA sequencing errors incurred on DNA sequencers. Our method can be used to assess, calibrate, and monitor sequencer accuracy, and to computationally suppress sequencer errors in existing datasets.

BACKGROUND: Deregulated gene expression is a hallmark of cancer; however, most studies to date have analyzed short-read RNA sequencing data with inherent limitations. Here, we combine PacBio long-read isoform sequencing (Iso-Seq) and Illumina paired-end short-read RNA sequencing to comprehensively survey the transcriptome of gastric cancer (GC), a leading cause of global cancer mortality. RESULTS: We performed full-length transcriptome analysis across 10 GC cell lines covering four major GC molecular subtypes (chromosomal unstable, Epstein-Barr positive, genome stable and microsatellite unstable). We identify 60,239 non-redundant full-length transcripts, of which > 66% are novel compared to current transcriptome databases. Novel isoforms are more likely to be cell line and subtype specific, expressed at lower levels with larger number of exons, with longer isoform/coding sequence lengths. Most novel isoforms utilize an alternate first exon, and compared to other alternative splicing categories, are expressed at higher levels and exhibit higher variability. Collectively, we observe alternate promoter usage in 25% of detected genes, with the majority (84.2%) of known/novel promoter pairs exhibiting potential changes in their coding sequences. Mapping these alternate promoters to TCGA GC samples, we identify several cancer-associated isoforms, including novel variants of oncogenes. Tumor-specific transcript isoforms tend to alter protein coding sequences to a larger extent than other isoforms. Analysis of outcome data suggests that novel isoforms may impart additional prognostic information. CONCLUSIONS: Our results provide a rich resource of full-length transcriptome data for deeper studies of GC and other gastrointestinal malignancies.

BACKGROUND: Microexons, exons that are ≤ 30 nucleotides, are a highly conserved and dynamically regulated set of cassette exons. They have key roles in nervous system development and function, as evidenced by recent results demonstrating the impact of microexons on behaviour and cognition. However, microexons are often overlooked due to the difficulty of detecting them using standard RNA-seq aligners. RESULTS: Here, we present MicroExonator, a novel pipeline for reproducible de novo discovery and quantification of microexons. We process 289 RNA-seq datasets from eighteen mouse tissues corresponding to nine embryonic and postnatal stages, providing the most comprehensive survey of microexons available for mice. We detect 2984 microexons, 332 of which are differentially spliced throughout mouse embryonic brain development, including 29 that are not present in mouse transcript annotation databases. Unsupervised clustering of microexons based on their inclusion patterns segregates brain tissues by developmental time, and further analysis suggests a key function for microexons in axon growth and synapse formation. Finally, we analyse single-cell RNA-seq data from the mouse visual cortex, and for the first time, we report differential inclusion between neuronal subpopulations, suggesting that some microexons could be cell type-specific. CONCLUSIONS: MicroExonator facilitates the investigation of microexons in transcriptome studies, particularly when analysing large volumes of data. As a proof of principle, we use MicroExonator to analyse a large collection of both mouse bulk and single-cell RNA-seq datasets. The analyses enabled the discovery of previously uncharacterized microexons, and our study provides a comprehensive microexon inclusion catalogue during mouse development.

Recently, efforts have been made toward the harmonization of transcriptomic data structures and workflows using the concept of data tidiness, to facilitate modularisation. We present tidybulk, a modular framework for bulk transcriptional analyses that introduces a tidy transcriptomic data structure paradigm and analysis grammar. Tidybulk covers a wide variety of analysis procedures and integrates a large ecosystem of publicly available analysis algorithms under a common framework. Tidybulk decreases coding burden, facilitates reproducibility, increases efficiency for expert users, lowers the learning curve for inexperienced users, and bridges transcriptional data analysis with the tidyverse. Tidybulk is available at R/Bioconductor bioconductor.org/packages/tidybulk .

BACKGROUND: The Environmental Determinants of Diabetes in the Young (TEDDY) is a prospective birth cohort designed to study type 1 diabetes (T1D) by following children with high genetic risk. An integrative multi-omics approach was used to evaluate islet autoimmunity etiology, identify disease biomarkers, and understand progression over time. RESULTS: We identify a multi-omics signature that was predictive of islet autoimmunity (IA) as early as 1 year before seroconversion. At this time, abnormalities in lipid metabolism, decreased capacity for nutrient absorption, and intracellular ROS accumulation are detected in children progressing towards IA. Additionally, extracellular matrix remodeling, inflammation, cytotoxicity, angiogenesis, and increased activity of antigen-presenting cells are observed, which may contribute to beta cell destruction. Our results indicate that altered molecular homeostasis is present in IA-developing children months before the actual detection of islet autoantibodies, which opens an interesting window of opportunity for therapeutic intervention. CONCLUSIONS: The approach employed herein for assessment of the TEDDY cohort showcases the utilization of multi-omics data for the modeling of complex, multifactorial diseases, like T1D.

Short hairpin RNAs (shRNAs) are used to deplete circRNAs by targeting back-splicing junction (BSJ) sites. However, frequent discrepancies exist between shRNA-mediated circRNA knockdown and the corresponding biological effect, querying their robustness. By leveraging CRISPR/Cas13d tool and optimizing the strategy for designing single-guide RNAs against circRNA BSJ sites, we markedly enhance specificity of circRNA silencing. This specificity is validated in parallel screenings by shRNA and CRISPR/Cas13d libraries. Using a CRISPR/Cas13d screening library targeting > 2500 human hepatocellular carcinoma-related circRNAs, we subsequently identify a subset of sorafenib-resistant circRNAs. Thus, CRISPR/Cas13d represents an effective approach for high-throughput study of functional circRNAs.

CRISPR guide RNA libraries have been iteratively improved to provide increasingly efficient reagents, although their large size is a barrier for many applications. We design an optimised minimal genome-wide human CRISPR-Cas9 library (MinLibCas9) by mining existing large-scale gene loss-of-function datasets, resulting in a greater than 42% reduction in size compared to other CRISPR-Cas9 libraries while preserving assay sensitivity and specificity. MinLibCas9 provides backward compatibility with existing datasets, increases the dynamic range of CRISPR-Cas9 screens and extends their application to complex models and assays.

We develop a general computational approach for improving the accuracy of basecalling with Oxford Nanopore's 1D2 and related sequencing protocols. Our software PoreOver ( https://github.com/jordisr/poreover ) finds the consensus of two neural networks by aligning their probability profiles, and is compatible with multiple nanopore basecallers. When applied to the recently-released Bonito basecaller, our method reduces the median sequencing error by more than half.

Although genome-wide DNA methylomes have demonstrated their clinical value as reliable biomarkers for tumor detection, subtyping, and classification, their direct biological impacts at the individual gene level remain elusive. Here we present MethylationToActivity (M2A), a machine learning framework that uses convolutional neural networks to infer promoter activities based on H3K4me3 and H3K27ac enrichment, from DNA methylation patterns for individual genes. Using publicly available datasets in real-world test scenarios, we demonstrate that M2A is highly accurate and robust in revealing promoter activity landscapes in various pediatric and adult cancers, including both solid and hematologic malignant neoplasms.

BACKGROUND: Aberrant activation of the Hedgehog pathway drives tumorigenesis of many cancers, including glioblastoma. However, the sensitization mechanism of the G protein-coupled-like receptor smoothened (SMO), a key component of Hedgehog signaling, remains largely unknown. RESULTS: In this study, we describe a novel protein SMO-193a.a. that is essential for Hedgehog signaling activation in glioblastoma. Encoded by circular SMO (circ-SMO), SMO-193a.a. is required for sonic hedgehog (Shh) induced SMO activation, via interacting with SMO, enhancing SMO cholesterol modification, and releasing SMO from the inhibition of patched transmembrane receptors. Deprivation of SMO-193a.a. in brain cancer stem cells attenuates Hedgehog signaling intensity and suppresses self-renewal, proliferation in vitro, and tumorigenicity in vivo. Moreover, circ-SMO/SMO-193a.a. is positively regulated by FUS, a direct transcriptional target of Gli1. Shh/Gli1/FUS/SMO-193a.a. form a positive feedback loop to sustain Hedgehog signaling activation in glioblastoma. Clinically, SMO-193a.a. is more specifically expressed in glioblastoma than SMO and is relevant to Gli1 expression. Higher expression of SMO-193a.a. predicts worse overall survival of glioblastoma patients, indicating its prognostic value. CONCLUSIONS: Our study reveals that SMO-193a.a., a novel protein encoded by circular SMO, is critical for Hedgehog signaling, drives glioblastoma tumorigenesis and is a novel target for glioblastoma treatment.

We report SPIN, an integrative computational method to reveal genome-wide intranuclear chromosome positioning and nuclear compartmentalization relative to multiple nuclear structures, which are pivotal for modulating genome function. As a proof-of-principle, we use SPIN to integrate nuclear compartment mapping (TSA-seq and DamID) and chromatin interaction data (Hi-C) from K562 cells to identify 10 spatial compartmentalization states genome-wide relative to nuclear speckles, lamina, and putative associations with nucleoli. These SPIN states show novel patterns of genome spatial organization and their relation to other 3D genome features and genome function (transcription and replication timing). SPIN provides critical insights into nuclear spatial and functional compartmentalization.

BACKGROUND: Alternative splicing (AS) is a widespread regulatory mechanism in multicellular organisms. Numerous transcriptomic and single-gene studies in plants have investigated AS in response to specific conditions, especially environmental stress, unveiling substantial amounts of intron retention that modulate gene expression. However, a comprehensive study contrasting stress-response and tissue-specific AS patterns and directly comparing them with those of animal models is still missing. RESULTS: We generate a massive resource for Arabidopsis thaliana, PastDB, comprising AS and gene expression quantifications across tissues, development and environmental conditions, including abiotic and biotic stresses. Harmonized analysis of these datasets reveals that A. thaliana shows high levels of AS, similar to fruitflies, and that, compared to animals, disproportionately uses AS for stress responses. We identify core sets of genes regulated specifically by either AS or transcription upon stresses or among tissues, a regulatory specialization that is tightly mirrored by the genomic features of these genes. Unexpectedly, non-intron retention events, including exon skipping, are overrepresented across regulated AS sets in A. thaliana, being also largely involved in modulating gene expression through NMD and uORF inclusion. CONCLUSIONS: Non-intron retention events have likely been functionally underrated in plants. AS constitutes a distinct regulatory layer controlling gene expression upon internal and external stimuli whose target genes and master regulators are hardwired at the genomic level to specifically undergo post-transcriptional regulation. Given the higher relevance of AS in the response to different stresses when compared to animals, this molecular hardwiring is likely required for a proper environmental response in A. thaliana.

Erratum in Genome Biol. 2021 Jan 25;22(1):46.

GWAS summary statistics are fundamental for a variety of research applications yet no common storage format has been widely adopted. Existing tabular formats ambiguously or incompletely store information about genetic variants and associations, lack essential metadata and are typically not indexed yielding poor query performance and increasing the possibility of errors in data interpretation and post-GWAS analyses. To address these issues, we adapted the variant call format to store GWAS summary statistics (GWAS-VCF) and developed open-source tools to use this format in downstream analyses. We provide open access to over 10,000 complete GWAS summary datasets converted to this format ( https://gwas.mrcieu.ac.uk ).

BACKGROUND: Tartary buckwheat (Fagopyrum tataricum) is a nutritionally balanced and flavonoid-rich crop plant that has been in cultivation for 4000 years and is now grown globally. Despite its nutraceutical and agricultural value, the characterization of its genetics and its domestication history is limited. RESULTS: Here, we report a comprehensive database of Tartary buckwheat genomic variation based on whole-genome resequencing of 510 germplasms. Our analysis suggests that two independent domestication events occurred in southwestern and northern China, resulting in diverse characteristics of modern Tartary buckwheat varieties. Genome-wide association studies for important agricultural traits identify several candidate genes, including FtUFGT3 and FtAP2YT1 that significantly correlate with flavonoid accumulation and grain weight, respectively. CONCLUSIONS: We describe the domestication history of Tartary buckwheat and provide a detailed resource of genomic variation to allow for genomic-assisted breeding in the improvement of elite cultivars.

BACKGROUND: Animal genomes contain thousands of long noncoding RNA (lncRNA) genes, a growing subset of which are thought to be functionally important. This functionality is often mediated by short sequence elements scattered throughout the RNA sequence that correspond to binding sites for small RNAs and RNA binding proteins. Throughout vertebrate evolution, the sequences of lncRNA genes changed extensively, so that it is often impossible to obtain significant alignments between sequences of lncRNAs from evolutionary distant species, even when synteny is evident. This often prohibits identifying conserved lncRNAs that are likely to be functional or prioritizing constrained regions for experimental interrogation. RESULTS: We introduce here LncLOOM, a novel algorithmic framework for the discovery and evaluation of syntenic combinations of short motifs. LncLOOM is based on a graph representation of the input sequences and uses integer linear programming to efficiently compare dozens of sequences that have thousands of bases each and to evaluate the significance of the recovered motifs. We show that LncLOOM is capable of identifying specific, biologically relevant motifs which are conserved throughout vertebrates and beyond in lncRNAs and 3'UTRs, including novel functional RNA elements in the CHASERR lncRNA that are required for regulation of CHD2 expression. CONCLUSIONS: We expect that LncLOOM will become a broadly used approach for the discovery of functionally relevant elements in the noncoding genome.

BlastFrost is a highly efficient method for querying 100,000s of genome assemblies, building on Bifrost, a dynamic data structure for compacted and colored de Bruijn graphs. BlastFrost queries a Bifrost data structure for sequences of interest and extracts local subgraphs, enabling the identification of the presence or absence of individual genes or single nucleotide sequence variants. We show two examples using Salmonella genomes: finding within minutes the presence of genes in the SPI-2 pathogenicity island in a collection of 926 genomes and identifying single nucleotide polymorphisms associated with fluoroquinolone resistance in three genes among 190,209 genomes. BlastFrost is available at https://github.com/nluhmann/BlastFrost/tree/master/data .