Single-cell m6A mapping in vivo using picoMeRIP-seq.

Current N6-methyladenosine (m6A) mapping methods need large amounts of RNA or are limited to cultured cells. Through optimized sample recovery and signal-to-noise ratio, we developed picogram-scale m6A RNA immunoprecipitation and sequencing (picoMeRIP-seq) for studying m6A in vivo in single cells and scarce cell types using standard laboratory equipment. We benchmark m6A mapping on titrations of poly(A) RNA and embryonic stem cells and in single zebrafish zygotes, mouse oocytes and embryos.

The RNA m6A landscape of mouse oocytes and preimplantation embryos.

Despite the significance of N6-methyladenosine (m6A) in gene regulation, the requirement for large amounts of RNA has hindered m6A profiling in mammalian early embryos. Here we apply low-input methyl RNA immunoprecipitation and sequencing to map m6A in mouse oocytes and preimplantation embryos. We define the landscape of m6A during the maternal-to-zygotic transition, including stage-specifically expressed transcription factors essential for cell fate determination. Both the maternally inherited transcripts to be degraded post fertilization and the zygotically activated genes during zygotic genome activation are widely marked by m6A. In contrast to m6A-marked zygotic ally-activated genes, m6A-marked maternally inherited transcripts have a higher tendency to be targeted by microRNAs. Moreover, RNAs derived from retrotransposons, such as MTA that is maternally expressed and MERVL that is transcriptionally activated at the two-cell stage, are largely marked by m6A. Our results provide a foundation for future studies exploring the regulatory roles of m6A in mammalian early embryonic development.

CEDA: integrating gene expression data with CRISPR-pooled screen data identifies essential genes with higher expression.

MOTIVATION: Clustered regularly interspaced short palindromic repeats (CRISPR)-based genetic perturbation screen is a powerful tool to probe gene function. However, experimental noises, especially for the lowly expressed genes, need to be accounted for to maintain proper control of false positive rate. METHODS: We develop a statistical method, named CRISPR screen with Expression Data Analysis (CEDA), to integrate gene expression profiles and CRISPR screen data for identifying essential genes. CEDA stratifies genes based on expression level and adopts a three-component mixture model for the log-fold change of single-guide RNAs (sgRNAs). Empirical Bayesian prior and expectation-maximization algorithm are used for parameter estimation and false discovery rate inference. RESULTS: Taking advantage of gene expression data, CEDA identifies essential genes with higher expression. Compared to existing methods, CEDA shows comparable reliability but higher sensitivity in detecting essential genes with moderate sgRNA fold change. Therefore, using the same CRISPR data, CEDA generates an additional hit gene list. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Nanopore sequencing technology, bioinformatics and applications.

Rapid advances in nanopore technologies for sequencing single long DNA and RNA molecules have led to substantial improvements in accuracy, read length and throughput. These breakthroughs have required extensive development of experimental and bioinformatics methods to fully exploit nanopore long reads for investigations of genomes, transcriptomes, epigenomes and epitranscriptomes. Nanopore sequencing is being applied in genome assembly, full-length transcript detection and base modification detection and in more specialized areas, such as rapid clinical diagnoses and outbreak surveillance. Many opportunities remain for improving data quality and analytical approaches through the development of new nanopores, base-calling methods and experimental protocols tailored to particular applications.

Real-time mapping of nanopore raw signals.

MOTIVATION: Oxford Nanopore Technologies sequencing devices support adaptive sequencing, in which undesired reads can be ejected from a pore in real time. This feature allows targeted sequencing aided by computational methods for mapping partial reads, rather than complex library preparation protocols. However, existing mapping methods either require a computationally expensive base-calling procedure before using aligners to map partial reads or work well only on small genomes. RESULTS: In this work, we present a new streaming method that can map nanopore raw signals for real-time selective sequencing. Rather than converting read signals to bases, we propose to convert reference genomes to signals and fully operate in the signal space. Our method features a new way to index reference genomes using k-d trees, a novel seed selection strategy and a seed chaining algorithm tailored toward the current signal characteristics. We implemented the method as a tool Sigmap. Then we evaluated it on both simulated and real data and compared it to the state-of-the-art nanopore raw signal mapper Uncalled. Our results show that Sigmap yields comparable performance on mapping yeast simulated raw signals, and better mapping accuracy on mapping yeast real raw signals with a 4.4× speedup. Moreover, our method performed well on mapping raw signals to genomes of size >100 Mbp and correctly mapped 11.49% more real raw signals of green algae, which leads to a significantly higher F1-score (0.9354 versus 0.8660). AVAILABILITY AND IMPLEMENTATION: Sigmap code is accessible at https://github.com/haowenz/sigmap. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Single-molecule long-read sequencing reveals a conserved intact long RNA profile in sperm.

Sperm contributes diverse RNAs to the zygote. While sperm small RNAs have been shown to impact offspring phenotypes, our knowledge of the sperm transcriptome, especially the composition of long RNAs, has been limited by the lack of sensitive, high-throughput experimental techniques that can distinguish intact RNAs from fragmented RNAs, known to abound in sperm. Here, we integrate single-molecule long-read sequencing with short-read sequencing to detect sperm intact RNAs (spiRNAs). We identify 3440 spiRNA species in mice and 4100 in humans. The spiRNA profile consists of both mRNAs and long non-coding RNAs, is evolutionarily conserved between mice and humans, and displays an enrichment in mRNAs encoding for ribosome. In sum, we characterize the landscape of intact long RNAs in sperm, paving the way for future studies on their biogenesis and functions. Our experimental and bioinformatics approaches can be applied to other tissues and organisms to detect intact transcripts.

Performance difference of graph-based and alignment-based hybrid error correction methods for error-prone long reads.

The error-prone third-generation sequencing (TGS) long reads can be corrected by the high-quality second-generation sequencing (SGS) short reads, which is referred to as hybrid error correction. We here investigate the influences of the principal algorithmic factors of two major types of hybrid error correction methods by mathematical modeling and analysis on both simulated and real data. Our study reveals the distribution of accuracy gain with respect to the original long read error rate. We also demonstrate that the original error rate of 19% is the limit for perfect correction, beyond which long reads are too error-prone to be corrected by these methods.

iASPP mediates p53 selectivity through a modular mechanism fine-tuning DNA recognition.

The most frequently mutated protein in human cancer is p53, a transcription factor (TF) that regulates myriad genes instrumental in diverse cellular outcomes including growth arrest and cell death. Cell context-dependent p53 modulation is critical for this life-or-death balance, yet remains incompletely understood. Here we identify sequence signatures enriched in genomic p53-binding sites modulated by the transcription cofactor iASPP. Moreover, our p53-iASPP crystal structure reveals that iASPP displaces the p53 L1 loop-which mediates sequence-specific interactions with the signature-corresponding base-without perturbing other DNA-recognizing modules of the p53 DNA-binding domain. A TF commonly uses multiple structural modules to recognize its cognate DNA, and thus this mechanism of a cofactor fine-tuning TF-DNA interactions through targeting a particular module is likely widespread. Previously, all tumor suppressors and oncoproteins that associate with the p53 DNA-binding domain-except the oncogenic E6 from human papillomaviruses (HPVs)-structurally cluster at the DNA-binding site of p53, complicating drug design. By contrast, iASPP inhibits p53 through a distinct surface overlapping the E6 footprint, opening prospects for p53-targeting precision medicine to improve cancer therapy.

Single-molecule long-read sequencing reveals the chromatin basis of gene expression.

Genome-wide chromatin accessibility and nucleosome occupancy profiles have been widely investigated, while the long-range dynamics remain poorly studied at the single-cell level. Here, we present a new experimental approach, methyltransferase treatment followed by single-molecule long-read sequencing (MeSMLR-seq), for long-range mapping of nucleosomes and chromatin accessibility at single DNA molecules and thus achieve comprehensive-coverage characterization of the corresponding heterogeneity. MeSMLR-seq offers direct measurements of both nucleosome-occupied and nucleosome-evicted regions on a single DNA molecule, which is challenging for many existing methods. We applied MeSMLR-seq to haploid yeast, where single DNA molecules represent single cells, and thus we could investigate the combinatorics of many (up to 356) nucleosomes at long range in single cells. We illustrated the differential organization principles of nucleosomes surrounding the transcription start site for silent and actively transcribed genes, at the single-cell level and in the long-range scale. The heterogeneous patterns of chromatin status spanning multiple genes were phased. Together with single-cell RNA-seq data, we quantitatively revealed how chromatin accessibility correlated with gene transcription positively in a highly heterogeneous scenario. Moreover, we quantified the openness of promoters and investigated the coupled chromatin changes of adjacent genes at single DNA molecules during transcription reprogramming. In addition, we revealed the coupled changes of chromatin accessibility for two neighboring glucose transporter genes in response to changes in glucose concentration.

A comparative evaluation of hybrid error correction methods for error-prone long reads.

BACKGROUND: Third-generation sequencing technologies have advanced the progress of the biological research by generating reads that are substantially longer than second-generation sequencing technologies. However, their notorious high error rate impedes straightforward data analysis and limits their application. A handful of error correction methods for these error-prone long reads have been developed to date. The output data quality is very important for downstream analysis, whereas computing resources could limit the utility of some computing-intense tools. There is a lack of standardized assessments for these long-read error-correction methods. RESULTS: Here, we present a comparative performance assessment of ten state-of-the-art error-correction methods for long reads. We established a common set of benchmarks for performance assessment, including sensitivity, accuracy, output rate, alignment rate, output read length, run time, and memory usage, as well as the effects of error correction on two downstream applications of long reads: de novo assembly and resolving haplotype sequences. CONCLUSIONS: Taking into account all of these metrics, we provide a suggestive guideline for method choice based on available data size, computing resources, and individual research goals.

Revealing tumor heterogeneity of breast cancer by utilizing the linkage between somatic and germline mutations.

The intra-tumor heterogeneity is associated with cancer progression and therapeutic resistance, such as in breast cancer. While the existing methods for studying tumor heterogeneity only analyze variant allele frequency (VAF), the genotype of variant is also informative for inferring subclones, which can be detected by long reads or paired-end reads. We developed GenoClone to integrate VAF with the genotype of variant innovatively, so it showed superior performance of inferring the number of subclones, estimating the fractions of subclones and identifying somatic single-nucleotide variants composition of subclones. When GenoClone was applied to 389 TCGA breast cancer samples, it revealed extensive intra-tumor heterogeneity. We further found that a few somatic mutations were relevant to the late stage of tumor evolution, including the ones at the oncogene PIK3CA and the tumor suppress gene TP53. Moreover, 52 subclones that were identified from 167 samples shared high similarity of somatic mutations, which were clustered into three groups with the sizes of 24, 14 and 14. It is helpful for understanding the development of breast cancer in certain subgroups of people and the drug development for population level. Furthermore, GenoClone also identified the tumor heterogeneity in different aliquots of the same samples. The implementation of GenoClone is available at http://www.healthcare.uiowa.edu/labs/au/GenoClone/.

E-C coupling structural protein junctophilin-2 encodes a stress-adaptive transcription regulator.

Junctophilin-2 (JP2) is a structural protein required for normal excitation-contraction (E-C) coupling. After cardiac stress, JP2 is cleaved by the calcium ion-dependent protease calpain, which disrupts the E-C coupling ultrastructural machinery and drives heart failure progression. We found that stress-induced proteolysis of JP2 liberates an N-terminal fragment (JP2NT) that translocates to the nucleus, binds to genomic DNA, and controls expression of a spectrum of genes in cardiomyocytes. Transgenic overexpression of JP2NT in mice modifies the transcriptional profile, resulting in attenuated pathological remodeling in response to cardiac stress. Conversely, loss of nuclear JP2NT function accelerates stress-induced development of hypertrophy and heart failure in mutant mice. These data reveal a self-protective mechanism in failing cardiomyocytes that transduce mechanical information (E-C uncoupling) into salutary transcriptional reprogramming in the stressed heart.

A Statistical Method for Observing Personal Diploid Methylomes and Transcriptomes with Single-Molecule Real-Time Sequencing.

We address the problem of observing personal diploid methylomes, CpG methylome pairs of homologous chromosomes that are distinguishable with respect to phased heterozygous variants (PHVs), which is challenging due to scarcity of PHVs in personal genomes. Single molecule real-time (SMRT) sequencing is promising as it outputs long reads with CpG methylation information, but a serious concern is whether reliable PHVs are available in erroneous SMRT reads with an error rate of ∼15%. To overcome the issue, we propose a statistical model that reduces the error rate of phasing CpG site to 1%, thereby calling CpG hypomethylation in each haplotype with >90% precision and sensitivity. Using our statistical model, we examined GNAS complex locus known for a combination of maternally, paternally, or biallelically expressed isoforms, and observed allele-specific methylation pattern almost perfectly reflecting their respective allele-specific expression status, demonstrating the merit of elucidating comprehensive personal diploid methylomes and transcriptomes.

Single cell expression analysis of primate-specific retroviruses-derived HPAT lincRNAs in viable human blastocysts identifies embryonic cells co-expressing genetic markers of multiple lineages.

Chromosome instability and aneuploidies occur very frequently in human embryos, impairing proper embryogenesis and leading to cell cycle arrest, loss of cell viability, and developmental failures in 50-80% of cleavage-stage embryos. This high frequency of cellular extinction events represents a significant experimental obstacle challenging analyses of individual cells isolated from human preimplantation embryos. We carried out single cell expression profiling of 241 individual cells recovered from 32 human embryos during the early and late stages of viable human blastocyst (VHB) differentiation. Classification of embryonic cells was performed solely based on expression patterns of human pluripotency-associated transcripts (HPAT), which represent a family of primate-specific transposable element-derived lincRNAs highly expressed in human embryonic stem cells and regulating nuclear reprogramming and pluripotency induction. We then validated our findings by analyzing transcriptomes of 1,708 individual cells recovered from more than 100 human embryos and 259 mouse cells from more than 40 mouse embryos at different stages of preimplantation embryogenesis. HPAT's expression-guided spatiotemporal reconstruction of human embryonic development inferred from single-cell expression analysis of VHB differentiation enabled identification of telomerase-positive embryonic cells co-expressing key pluripotency regulatory genes and genetic markers of three major lineages. Follow-up validation analyses confirmed the emergence in human embryos prior to lineage segregation of telomerase-positive cells co-expressing genetic markers of multiple lineages. Observations reported in this contribution support the hypothesis of a developmental pathway of creation embryonic lineages and extraembryonic tissues from telomerase-positive pre-lineage cells manifesting multi-lineage precursor phenotype.

IDP-denovo: de novo transcriptome assembly and isoform annotation by hybrid sequencing.

Motivation: In the past years, the long read (LR) sequencing technologies, such as Pacific Biosciences and Oxford Nanopore Technologies, have been demonstrated to substantially improve the quality of genome assembly and transcriptome characterization. Compared to the high cost of genome assembly by LR sequencing, it is more affordable to generate LRs for transcriptome characterization. That is, when informative transcriptome LR data are available without a high-quality genome, a method for de novo transcriptome assembly and annotation is of high demand. Results: Without a reference genome, IDP-denovo performs de novo transcriptome assembly, isoform annotation and quantification by integrating the strengths of LRs and short reads. Using the GM12878 human data as a gold standard, we demonstrated that IDP-denovo had superior sensitivity of transcript assembly and high accuracy of isoform annotation. In addition, IDP-denovo outputs two abundance indices to provide a comprehensive expression profile of genes/isoforms. IDP-denovo represents a robust approach for transcriptome assembly, isoform annotation and quantification for non-model organism studies. Applying IDP-denovo to a non-model organism, Dendrobium officinale, we discovered a number of novel genes and novel isoforms that were not reported by the existing annotation library. These results reveal the high diversity of gene isoforms in D.officinale, which was not reported in the existing annotation library. Availability and implementation: The dataset of Dendrobium officinale used/analyzed during the current study has been deposited in SRA, with accession code SRP094520. IDP-denovo is available for download at www.healthcare.uiowa.edu/labs/au/IDP-denovo/. Supplementary information: Supplementary data are available at Bioinformatics online.

Hybrid Sequencing of Full-Length cDNA Transcripts of Stems and Leaves in Dendrobium officinale.

Dendrobium officinale is an extremely valuable orchid used in traditional Chinese medicine, so sought after that it has a higher market value than gold. Although the expression profiles of some genes involved in the polysaccharide synthesis have previously been investigated, little research has been carried out on their alternatively spliced isoforms in D. officinale. In addition, information regarding the translocation of sugars from leaves to stems in D. officinale also remains limited. We analyzed the polysaccharide content of D. officinale leaves and stems, and completed in-depth transcriptome sequencing of these two diverse tissue types using second-generation sequencing (SGS) and single-molecule real-time (SMRT) sequencing technology. The results of this study yielded a digital inventory of gene and mRNA isoform expressions. A comparative analysis of both transcriptomes uncovered a total of 1414 differentially expressed genes, including 844 that were up-regulated and 570 that were down-regulated in stems. Of these genes, one sugars will eventually be exported transporter (SWEET) and one sucrose transporter (SUT) are expressed to a greater extent in D. officinale stems than in leaves. Two glycosyltransferase (GT) and four cellulose synthase (Ces) genes undergo a distinct degree of alternative splicing. In the stems, the content of polysaccharides is twice as much as that in the leaves. The differentially expressed GT and transcription factor (TF) genes will be the focus of further study. The genes DoSWEET4 and DoSUT1 are significantly expressed in the stem, and are likely to be involved in sugar loading in the phloem.

CF airway smooth muscle transcriptome reveals a role for PYK2.

Abnormal airway smooth muscle function can contribute to cystic fibrosis (CF) airway disease. We previously found that airway smooth muscle from newborn CF pigs had increased basal tone, an increased bronchodilator response, and abnormal calcium handling. Since CF pigs lack airway infection and inflammation at birth, these findings suggest intrinsic airway smooth muscle dysfunction in CF. In this study, we tested the hypothesis that CFTR loss in airway smooth muscle would produce a distinct set of changes in the airway smooth muscle transcriptome that we could use to develop novel therapeutic targets. Total RNA sequencing of newborn wild-type and CF airway smooth muscle revealed changes in muscle contraction-related genes, ontologies, and pathways. Using connectivity mapping, we identified several small molecules that elicit transcriptional signatures opposite of CF airway smooth muscle, including NVP-TAE684, an inhibitor of proline-rich tyrosine kinase 2 (PYK2). In CF airway smooth muscle tissue, PYK2 phosphorylation was increased and PYK2 inhibition decreased smooth muscle contraction. In vivo NVP-TAE684 treatment of wild-type mice reduced methacholine-induced airway smooth muscle contraction. These findings suggest that studies in the newborn CF pig may provide an important approach to enhance our understanding of airway smooth muscle biology and for discovery of novel airway smooth muscle therapeutics for CF and other diseases of airway hyperreactivity.

Comprehensive comparison of Pacific Biosciences and Oxford Nanopore Technologies and their applications to transcriptome analysis.

Background: Given the demonstrated utility of Third Generation Sequencing [Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT)] long reads in many studies, a comprehensive analysis and comparison of their data quality and applications is in high demand. Methods: Based on the transcriptome sequencing data from human embryonic stem cells, we analyzed multiple data features of PacBio and ONT, including error pattern, length, mappability and technical improvements over previous platforms. We also evaluated their application to transcriptome analyses, such as isoform identification and quantification and characterization of transcriptome complexity, by comparing the performance of PacBio, ONT and their corresponding Hybrid-Seq strategies (PacBio+Illumina and ONT+Illumina). Results: PacBio shows overall better data quality, while ONT provides a higher yield. As with data quality, PacBio performs marginally better than ONT in most aspects for both long reads only and Hybrid-Seq strategies in transcriptome analysis. In addition, Hybrid-Seq shows superior performance over long reads only in most transcriptome analyses. Conclusions: Both PacBio and ONT sequencing are suitable for full-length single-molecule transcriptome analysis. As this first use of ONT reads in a Hybrid-Seq analysis has shown, both PacBio and ONT can benefit from a combined Illumina strategy. The tools and analytical methods developed here provide a resource for future applications and evaluations of these rapidly-changing technologies.