DNA-m6A calling and integrated long-read epigenetic and genetic analysis with fibertools.

Long-read DNA sequencing has recently emerged as a powerful tool for studying both genetic and epigenetic architectures at single-molecule and single-nucleotide resolution. Long-read epigenetic studies encompass both the direct identification of native cytosine methylation as well as the identification of exogenously placed DNA N6-methyladenine (DNA-m6A). However, detecting DNA-m6A modifications using single-molecule sequencing, as well as coprocessing single-molecule genetic and epigenetic architectures, is limited by computational demands and a lack of supporting tools. Here, we introduce fibertools, a state-of-the-art toolkit that features a semisupervised convolutional neural network for fast and accurate identification of m6A-marked bases using PacBio single-molecule long-read sequencing, as well as the coprocessing of long-read genetic and epigenetic data produced using either PacBio or Oxford Nanopore sequencing platforms. We demonstrate accurate DNA-m6A identification (>90% precision and recall) along >20 kilobase long DNA molecules with a ~1,000-fold improvement in speed. In addition, we demonstrate that fibertools can readily integrate genetic and epigenetic data at single-molecule resolution, including the seamless conversion between molecular and reference coordinate systems, allowing for accurate genetic and epigenetic analyses of long-read data within structurally and somatically variable genomic regions.

Enhancing Hi-C contact matrices for loop detection with Capricorn: a multiview diffusion model.

MOTIVATION: High-resolution Hi-C contact matrices reveal the detailed three-dimensional architecture of the genome, but high-coverage experimental Hi-C data are expensive to generate. Simultaneously, chromatin structure analyses struggle with extremely sparse contact matrices. To address this problem, computational methods to enhance low-coverage contact matrices have been developed, but existing methods are largely based on resolution enhancement methods for natural images and hence often employ models that do not distinguish between biologically meaningful contacts, such as loops and other stochastic contacts. RESULTS: We present Capricorn, a machine learning model for Hi-C resolution enhancement that incorporates small-scale chromatin features as additional views of the input Hi-C contact matrix and leverages a diffusion probability model backbone to generate a high-coverage matrix. We show that Capricorn outperforms the state of the art in a cross-cell-line setting, improving on existing methods by 17% in mean squared error and 26% in F1 score for chromatin loop identification from the generated high-coverage data. We also demonstrate that Capricorn performs well in the cross-chromosome setting and cross-chromosome, cross-cell-line setting, improving the downstream loop F1 score by 14% relative to existing methods. We further show that our multiview idea can also be used to improve several existing methods, HiCARN and HiCNN, indicating the wide applicability of this approach. Finally, we use DNA sequence to validate discovered loops and find that the fraction of CTCF-supported loops from Capricorn is similar to those identified from the high-coverage data. Capricorn is a powerful Hi-C resolution enhancement method that enables scientists to find chromatin features that cannot be identified in the low-coverage contact matrix. AVAILABILITY AND IMPLEMENTATION: Implementation of Capricorn and source code for reproducing all figures in this paper are available at https://github.com/CHNFTQ/Capricorn.

Ancient antagonism between CELF and RBFOX families tunes mRNA splicing outcomes.

Over 95% of human multi-exon genes undergo alternative splicing, a process important in normal development and often dysregulated in disease. We sought to analyze the global splicing regulatory network of CELF2 in human T cells, a well-studied splicing regulator critical to T cell development and function. By integrating high-throughput sequencing data for binding and splicing quantification with sequence features and probabilistic splicing code models, we find evidence of splicing antagonism between CELF2 and the RBFOX family of splicing factors. We validate this functional antagonism through knockdown and overexpression experiments in human cells and find CELF2 represses RBFOX2 mRNA and protein levels. Because both families of proteins have been implicated in the development and maintenance of neuronal, muscle, and heart tissues, we analyzed publicly available data in these systems. Our analysis suggests global, antagonistic coregulation of splicing by the CELF and RBFOX proteins in mouse muscle and heart in several physiologically relevant targets, including proteins involved in calcium signaling and members of the MEF2 family of transcription factors. Importantly, a number of these coregulated events are aberrantly spliced in mouse models and human patients with diseases that affect these tissues, including heart failure, diabetes, or myotonic dystrophy. Finally, analysis of exons regulated by ancient CELF family homologs in chicken, Drosophila, and Caenorhabditis elegans suggests this antagonism is conserved throughout evolution.

Integrative deep models for alternative splicing.

MOTIVATION: Advancements in sequencing technologies have highlighted the role of alternative splicing (AS) in increasing transcriptome complexity. This role of AS, combined with the relation of aberrant splicing to malignant states, motivated two streams of research, experimental and computational. The first involves a myriad of techniques such as RNA-Seq and CLIP-Seq to identify splicing regulators and their putative targets. The second involves probabilistic models, also known as splicing codes, which infer regulatory mechanisms and predict splicing outcome directly from genomic sequence. To date, these models have utilized only expression data. In this work, we address two related challenges: Can we improve on previous models for AS outcome prediction and can we integrate additional sources of data to improve predictions for AS regulatory factors. RESULTS: We perform a detailed comparison of two previous modeling approaches, Bayesian and Deep Neural networks, dissecting the confounding effects of datasets and target functions. We then develop a new target function for AS prediction in exon skipping events and show it significantly improves model accuracy. Next, we develop a modeling framework that leverages transfer learning to incorporate CLIP-Seq, knockdown and over expression experiments, which are inherently noisy and suffer from missing values. Using several datasets involving key splice factors in mouse brain, muscle and heart we demonstrate both the prediction improvements and biological insights offered by our new models. Overall, the framework we propose offers a scalable integrative solution to improve splicing code modeling as vast amounts of relevant genomic data become available. AVAILABILITY AND IMPLEMENTATION: Code and data available at: majiq.biociphers.org/jha_et_al_2017/. CONTACT: yosephb@upenn.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

High-Grade Urothelial Carcinoma of Bladder Transforming to Micropapillary Variant on Follow-Up.

Micropapillary variant of urothelial carcinoma (UC) of the bladder is an aggressive tumour, comprising 0.6-6% of all UC. It generally presents with high-grade and stage, and has been reported as having a worse prognosis when compared to traditional UC. We report the case of a 58-year-old man who presented with macroscopic haematuria. The patient was diagnosed with high-grade urothelial carcinoma and returned with recurrence after 16 months. Histopathology after transurethral biopsy revealed a non-muscle invasive high-grade bladder tumour at first presentation, whereas tumour recurrence was reported after 1.5years. The histopathology at recurrence revealed a high-grade, muscle invasive, micropapillary variant of urothelial carcinoma with focal adenomatous morphology. Immunohistochemical expression of CK7+/CK20+ in tumour cells and negativity for PSA, AMACR, and CDX2 in paraffin section helped in identifying the tumour as primary in the urinary bladder. Radical cystectomy was performed and the patient has no distant metastases on follow-up. The specific morphology even within the high-grade urothelial cancer cases is important to discern for proper treatment.

RNA splicing analysis using heterogeneous and large RNA-seq datasets.

The ubiquity of RNA-seq has led to many methods that use RNA-seq data to analyze variations in RNA splicing. However, available methods are not well suited for handling heterogeneous and large datasets. Such datasets scale to thousands of samples across dozens of experimental conditions, exhibit increased variability compared to biological replicates, and involve thousands of unannotated splice variants resulting in increased transcriptome complexity. We describe here a suite of algorithms and tools implemented in the MAJIQ v2 package to address challenges in detection, quantification, and visualization of splicing variations from such datasets. Using both large scale synthetic data and GTEx v8 as benchmark datasets, we assess the advantages of MAJIQ v2 compared to existing methods. We then apply MAJIQ v2 package to analyze differential splicing across 2,335 samples from 13 brain subregions, demonstrating its ability to offer insights into brain subregion-specific splicing regulation.

DNA-m6A calling and integrated long-read epigenetic and genetic analysis with fibertools.

Long-read DNA sequencing has recently emerged as a powerful tool for studying both genetic and epigenetic architectures at single-molecule and single-nucleotide resolution. Long-read epigenetic studies encompass both the direct identification of native cytosine methylation as well as the identification of exogenously placed DNA N6-methyladenine (DNA-m6A). However, detecting DNA-m6A modifications using single-molecule sequencing, as well as co-processing single-molecule genetic and epigenetic architectures, is limited by computational demands and a lack of supporting tools. Here, we introduce fibertools, a state-of-the-art toolkit that features a semi-supervised convolutional neural network for fast and accurate identification of m6A-marked bases using PacBio single-molecule long-read sequencing, as well as the co-processing of long-read genetic and epigenetic data produced using either PacBio or Oxford Nanopore sequencing platforms. We demonstrate accurate DNA-m6A identification (>90% precision and recall) along >20 kilobase long DNA molecules with a ~1,000-fold improvement in speed. In addition, we demonstrate that fibertools can readily integrate genetic and epigenetic data at single-molecule resolution, including the seamless conversion between molecular and reference coordinate systems, allowing for accurate genetic and epigenetic analyses of long-read data within structurally and somatically variable genomic regions.

The SbSOS1 gene from the extreme halophyte Salicornia brachiata enhances Na(+) loading in xylem and confers salt tolerance in transgenic tobacco.

BACKGROUND: Soil salinity adversely affects plant growth and development and disturbs intracellular ion homeostasis resulting cellular toxicity. The Salt Overly Sensitive 1 (SOS1) gene encodes a plasma membrane Na(+)/H(+) antiporter that plays an important role in imparting salt stress tolerance to plants. Here, we report the cloning and characterisation of the SbSOS1 gene from Salicornia brachiata, an extreme halophyte. RESULTS: The SbSOS1 gene is 3774 bp long and encodes a protein of 1159 amino acids. SbSOS1 exhibited a greater level of constitutive expression in roots than in shoots and was further increased by salt stress. Overexpressing the S. brachiata SbSOS1 gene in tobacco conferred high salt tolerance, promoted seed germination and increased root length, shoot length, leaf area, fresh weight, dry weight, relative water content (RWC), chlorophyll, K(+)/Na(+) ratio, membrane stability index, soluble sugar, proline and amino acid content relative to wild type (WT) plants. Transgenic plants exhibited reductions in electrolyte leakage, reactive oxygen species (ROS) and MDA content in response to salt stress, which probably occurred because of reduced cytosolic Na(+) content and oxidative damage. At higher salt stress, transgenic tobacco plants exhibited reduced Na(+) content in root and leaf and higher concentrations in stem and xylem sap relative to WT, which suggests a role of SbSOS1 in Na(+) loading to xylem from root and leaf tissues. Transgenic lines also showed increased K(+) and Ca(2+) content in root tissue compared to WT, which reflect that SbSOS1 indirectly affects the other transporters activity. CONCLUSIONS: Overexpression of SbSOS1 in tobacco conferred a high degree of salt tolerance, enhanced plant growth and altered physiological and biochemical parameters in response to salt stress. In addition to Na(+) efflux outside the plasma membrane, SbSOS1 also helps to maintain variable Na(+) content in different organs and also affect the other transporters activity indirectly. These results broaden the role of SbSOS1 in planta and suggest that this gene could be used to develop salt-tolerant transgenic crops.

Identifying common transcriptome signatures of cancer by interpreting deep learning models.

BACKGROUND: Cancer is a set of diseases characterized by unchecked cell proliferation and invasion of surrounding tissues. The many genes that have been genetically associated with cancer or shown to directly contribute to oncogenesis vary widely between tumor types, but common gene signatures that relate to core cancer pathways have also been identified. It is not clear, however, whether there exist additional sets of genes or transcriptomic features that are less well known in cancer biology but that are also commonly deregulated across several cancer types. RESULTS: Here, we agnostically identify transcriptomic features that are commonly shared between cancer types using 13,461 RNA-seq samples from 19 normal tissue types and 18 solid tumor types to train three feed-forward neural networks, based either on protein-coding gene expression, lncRNA expression, or splice junction use, to distinguish between normal and tumor samples. All three models recognize transcriptome signatures that are consistent across tumors. Analysis of attribution values extracted from our models reveals that genes that are commonly altered in cancer by expression or splicing variations are under strong evolutionary and selective constraints. Importantly, we find that genes composing our cancer transcriptome signatures are not frequently affected by mutations or genomic alterations and that their functions differ widely from the genes genetically associated with cancer. CONCLUSIONS: Our results highlighted that deregulation of RNA-processing genes and aberrant splicing are pervasive features on which core cancer pathways might converge across a large array of solid tumor types.

Cloning and characterization of the Salicornia brachiata Na(+)/H(+) antiporter gene SbNHX1 and its expression by abiotic stress.

Salinity causes multifarious adverse effects to plants. Plants response to salt stress involves numerous processes that function in coordination to alleviate both cellular hyperosmolarity and ion disequilibrium. A Na(+)/H(+) antiporter NHX1 gene has been isolated from a halophytic plant Salicornia brachiata in this study. Predicted amino acid sequence similarity, protein topology and the presence of functional domains conserved in SbNHX1 classify it as a plant vacuolar NHX gene. The SbNHX1 cDNA has an open reading frame of 1,683 bp, encoding a polypeptide of 560 amino acid residues with an estimated molecular mass 62.44 kDa. The SbNHX1 shows high amino acid similarity with other halophytic NHX gene and belongs to Class-I type NHXs. TMpred suggests that SbNHX1 contains 11 strong transmembrane (TM). Real time PCR analysis revealed that SbNHX1 transcript expresses maximum at 0.5 M. Transcript increases gradually by increasing the treatment duration at 0.5 M NaCl, however, maximum expression was observed at 48 h. The overexpression of SbNHX1 gene in tobacco plant showed NaCl tolerance. This study shows that SbNHX1 is a potential gene for salt tolerance, and can be used in future for developing salt tolerant crops.

RNA-Binding Proteins PCBP1 and PCBP2 Are Critical Determinants of Murine Erythropoiesis.

We previously demonstrated that the two paralogous RNA-binding proteins PCBP1 and PCBP2 are individually essential for mouse development: Pcbp1-null embryos are peri-implantation lethal, while Pcbp2-null embryos lose viability at midgestation. Midgestation Pcbp2-/- embryos revealed a complex phenotype that included loss of certain hematopoietic determinants. Whether PCBP2 directly contributes to erythropoietic differentiation and whether PCBP1 has a role in this process remained undetermined. Here, we selectively inactivated the genes encoding these two RNA-binding proteins during differentiation of the erythroid lineage in the developing mouse embryo. Individual inactivation of either locus failed to impact viability or blood formation. However, combined inactivation of the two loci resulted in midgestational repression of erythroid/hematopoietic gene expression, loss of blood formation, and fetal demise. Orthogonal ex vivo analyses of primary erythroid progenitors selectively depleted of these two RNA-binding proteins revealed that they mediate a combination of overlapping and isoform-specific impacts on hematopoietic lineage transcriptome, impacting both mRNA representation and exon splicing. These data lead us to conclude that PCBP1 and PCBP2 mediate functions critical to differentiation of the erythroid lineage.

Multi-trait association studies discover pleiotropic loci between Alzheimer's disease and cardiometabolic traits.

BACKGROUND: Identification of genetic risk factors that are shared between Alzheimer's disease (AD) and other traits, i.e., pleiotropy, can help improve our understanding of the etiology of AD and potentially detect new therapeutic targets. Previous epidemiological correlations observed between cardiometabolic traits and AD led us to assess the pleiotropy between these traits. METHODS: We performed a set of bivariate genome-wide association studies coupled with colocalization analysis to identify loci that are shared between AD and eleven cardiometabolic traits. For each of these loci, we performed colocalization with Genotype-Tissue Expression (GTEx) project expression quantitative trait loci (eQTL) to identify candidate causal genes. RESULTS: We identified three previously unreported pleiotropic trait associations at known AD loci as well as four novel pleiotropic loci. One associated locus was tagged by a low-frequency coding variant in the gene DOCK4 and is potentially implicated in its alternative splicing. Colocalization with GTEx eQTL data identified additional candidate genes for the loci we detected, including ACE, the target of the hypertensive drug class of ACE inhibitors. We found that the allele associated with decreased ACE expression in brain tissue was also associated with increased risk of AD, providing human genetic evidence of a potential increase in AD risk from use of an established anti-hypertensive therapeutic. CONCLUSION: Our results support a complex genetic relationship between AD and these cardiometabolic traits, and the candidate causal genes identified suggest that blood pressure and immune response play a role in the pleiotropy between these traits.

MOCCASIN: a method for correcting for known and unknown confounders in RNA splicing analysis.

The effects of confounding factors on gene expression analysis have been extensively studied following the introduction of high-throughput microarrays and subsequently RNA sequencing. In contrast, there is a lack of equivalent analysis and tools for RNA splicing. Here we first assess the effect of confounders on both expression and splicing quantifications in two large public RNA-Seq datasets (TARGET, ENCODE). We show quantification of splicing variations are affected at least as much as those of gene expression, revealing unwanted sources of variations in both datasets. Next, we develop MOCCASIN, a method to correct the effect of both known and unknown confounders on RNA splicing quantification and demonstrate MOCCASIN's effectiveness on both synthetic and real data. Code, synthetic and corrected datasets are all made available as resources.

Enhanced Integrated Gradients: improving interpretability of deep learning models using splicing codes as a case study.

Despite the success and fast adaptation of deep learning models in biomedical domains, their lack of interpretability remains an issue. Here, we introduce Enhanced Integrated Gradients (EIG), a method to identify significant features associated with a specific prediction task. Using RNA splicing prediction as well as digit classification as case studies, we demonstrate that EIG improves upon the original Integrated Gradients method and produces sets of informative features. We then apply EIG to identify A1CF as a key regulator of liver-specific alternative splicing, supporting this finding with subsequent analysis of relevant A1CF functional (RNA-seq) and binding data (PAR-CLIP).

Developing transgenic Jatropha using the SbNHX1 gene from an extreme halophyte for cultivation in saline wasteland.

Jatropha is an important second-generation biofuel plant. Salinity is a major factor adversely impacting the growth and yield of several plants including Jatropha. SbNHX1 is a vacuolar Na⁺/H⁺ antiporter gene that compartmentalises excess Na⁺ ions into the vacuole and maintains ion homeostasis. We have previously cloned and characterised the SbNHX1 gene from an extreme halophyte, Salicornia brachiata. Transgenic plants of Jatropha curcas with the SbNHX1 gene were developed using microprojectile bombardment mediated transformation. Integration of the transgene was confirmed by PCR and Rt-PCR and the copy number was determined by real time qPCR. The present study of engineering salt tolerance in Jatropha is the first report to date. Salt tolerance of the transgenic lines JL2, JL8 and JL19 was confirmed by leaf senescence assay, chlorophyll estimation, plant growth, ion content, electrolyte leakage and malondialdehyde (MDA) content analysis. Transgenic lines showed better salt tolerance than WT up to 200 mM NaCl. Imparting salt tolerance to Jatropha using the SbNHX1 gene may open up the possibility of cultivating it in marginal salty land, releasing arable land presently under Jatropha cultivation for agriculture purposes. Apart from this, transgenic Jatropha can be cultivated with brackish water, opening up the possibility of sustainable cultivation of this biofuel plant in salty coastal areas.