scholarly journals Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Mathys Grapotte ◽  
Manu Saraswat ◽  
Chloé Bessière ◽  
Christophe Menichelli ◽  
Jordan A. Ramilowski ◽  
...  
Keyword(s):  
Transcription Initiation ◽  
Tandem Repeats ◽  
Specific Gene ◽  
Rna Seq ◽  
Transcription Start Sites ◽  
Long Read ◽  
Cap Analysis ◽  
Dna Tandem Repeats ◽  
Short Tandem ◽  
Str Polymorphism

AbstractUsing the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we develop Cap Trap RNA-seq, a technology which combines cap trapping and long read MinION sequencing. We train sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveil the importance of STR surrounding sequences not only to distinguish STR classes, but also to predict the level of transcription initiation. Importantly, genetic variants linked to human diseases are preferentially found at STRs with high transcription initiation level, supporting the biological and clinical relevance of transcription initiation at STRs. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism.

scholarly journals Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network

2020 ◽  
Author(s):  
Mathys Grapotte ◽  
Manu Saraswat ◽  
Chloé Bessière ◽  
Christophe Menichelli ◽  
Jordan A. Ramilowski ◽  
...  
Keyword(s):  
Transcription Initiation ◽  
Tandem Repeats ◽  
Specific Gene ◽  
Rna Seq ◽  
Transcription Start Sites ◽  
Dna Motif ◽  
Long Reads ◽  
Cap Analysis ◽  
Dna Tandem Repeats ◽  
Short Tandem

Using the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of Transcription Start Sites (TSSs) in several species. Strikingly, ~ 72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probed these unassigned TSSs and showed that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we developed Cap Trap RNA-seq, a technology which combines cap trapping and long reads MinION sequencing. We trained sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveiled the importance of STR surrounding sequences not only to distinguish STR classes, as defined by the repeated DNA motif, one from each other, but also to predict their transcription. Excitingly, our models predicted that genetic variants linked to human diseases affect STR-associated transcription and correspond precisely to the key positions identified by our models to predict transcription. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism.

scholarly journals Evidence of transcription at polyT short tandem repeats

2019 ◽  
Author(s):  
Chloé Bessière ◽  
Manu Saraswat ◽  
Mathys Grapotte ◽  
Christophe Menichelli ◽  
Jordan A. Ramilowski ◽  
...  
Keyword(s):  
Complex Traits ◽  
Short Tandem Repeats ◽  
Tandem Repeats ◽  
Specific Gene ◽  
Transcription Start Sites ◽  
Cap Analysis ◽  
Dna Tandem Repeats ◽  
Deep Learning Model ◽  
Short Tandem ◽  
Str Polymorphism

AbstractBackgroundUsing the Cap Analysis of Gene Expression technology, the FANTOM5 consortium provided one of the most comprehensive maps of Transcription Start Sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers.ResultsHere, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at short tandem repeats (STRs) corresponding to homopolymers of thymidines (T). Additional analyse confirm that these CAGEs are truly associated with transcriptionally active chromatin marks. Furthermore, we train a sequence-based deep learning model able to predict CAGE signal at T STRs with high accuracy (~81%) Extracting features learned by this model reveals that transcription at T STRs is mostly directed by STR length but also instructions lying in the downstream sequence. Excitingly, our model also predicts that genetic variants linked to human diseases affect this STR-associated transcription.ConclusionsTogether, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism. We also provide a new metric that can be considered in future studies of STR-related complex traits.

scholarly journals Comprehensive genetic diagnosis of tandem repeat expansion disorders with programmable targeted nanopore sequencing

2021 ◽  
Author(s):  
Igor Stevanovski ◽  
Sanjog R. Chintalaphani ◽  
Hasindu Gamaarachchi ◽  
James M. Ferguson ◽  
Sandy S. Pineda ◽  
...  
Keyword(s):  
Tandem Repeat ◽  
Tandem Repeats ◽  
Fragile X ◽  
Genetic Diagnosis ◽  
Neuromuscular Diseases ◽  
Nanopore Sequencing ◽  
Molecular Tests ◽  
Genetic Landscape ◽  
Long Read ◽  
Short Tandem

ABSTRACTShort-tandem repeat (STR) expansions are an important class of pathogenic genetic variants. Over forty neurological and neuromuscular diseases are caused by STR expansions, with 37 different genes implicated to date. Here we describe the use of programmable targeted long-read sequencing with Oxford Nanopore’s ReadUntil function for parallel genotyping of all known neuropathogenic STRs in a single, simple assay. Our approach enables accurate, haplotype-resolved assembly and DNA methylation profiling of expanded and non-expanded STR sites. In doing so, the assay correctly diagnoses all individuals in a cohort of patients (n = 27) with various neurogenetic diseases, including Huntington’s disease, fragile X syndrome and cerebellar ataxia (CANVAS) and others. Targeted long-read sequencing solves large and complex STR expansions that confound established molecular tests and short-read sequencing, and identifies non-canonical STR motif conformations and internal sequence interruptions. Even in our relatively small cohort, we observe a wide diversity of STR alleles of known and unknown pathogenicity, suggesting that long-read sequencing will redefine the genetic landscape of STR expansion disorders. Finally, we show how the flexible inclusion of pharmacogenomics (PGx) genes as secondary ReadUntil targets can identify clinically actionable PGx genotypes to further inform patient care, at no extra cost. Our study addresses the need for improved techniques for genetic diagnosis of STR expansion disorders and illustrates the broad utility of programmable long-read sequencing for clinical genomics.One sentence summaryThis study describes the development and validation of a programmable targeted nanopore sequencing assay for parallel genetic diagnosis of all known pathogenic short-tandem repeats (STRs) in a single, simple test.

scholarly journals LIQA: long-read isoform quantification and analysis

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yu Hu ◽  
Li Fang ◽  
Xuelian Chen ◽  
Jiang F. Zhong ◽  
Mingyao Li ◽  
...  
Keyword(s):  
Alternative Splicing ◽  
Myeloid Leukemia ◽  
Expectation Maximization Algorithm ◽  
Read Length ◽  
Specific Gene ◽  
Rna Seq ◽  
Sequencing Data ◽  
Long Read ◽  
Isoform Quantification ◽  
Universal Human Reference

AbstractLong-read RNA sequencing (RNA-seq) technologies can sequence full-length transcripts, facilitating the exploration of isoform-specific gene expression over short-read RNA-seq. We present LIQA to quantify isoform expression and detect differential alternative splicing (DAS) events using long-read direct mRNA sequencing or cDNA sequencing data. LIQA incorporates base pair quality score and isoform-specific read length information in a survival model to assign different weights across reads, and uses an expectation-maximization algorithm for parameter estimation. We apply LIQA to long-read RNA-seq data from the Universal Human Reference, acute myeloid leukemia, and esophageal squamous epithelial cells and demonstrate its high accuracy in profiling alternative splicing events.

scholarly journals Isoform-level transcriptome Atlas of Macrophage Activation

2020 ◽  
Author(s):  
Apple Cortez Vollmers ◽  
Honey E. Mekonen ◽  
Sophia Campos ◽  
Susan Carpenter ◽  
Christopher Vollmers
Keyword(s):  
Macrophage Activation ◽  
Target Gene ◽  
Target Genes ◽  
Human Monocyte ◽  
Innate Immune ◽  
Rna Seq ◽  
Transcription Start Sites ◽  
Long Read ◽  
Highly Expressed Genes

AbstractRNA-seq is routinely used to measure gene expression changes in response to cell perturbation. Genes that are up or down-regulated following perturbation in RNA-seq studies are designated as target genes for follow-up. However, RNA-seq is limited in its ability to capture the complexity of gene isoforms, defined by the exact composition of exons and transcription start sites (TSS) and poly(A) sites they contain, as well as the expression of these isoforms. Without knowing the composition of the most dominant isoform(s) of a target gene, a minority or non-existent isoform could be selected for follow-up solely based on available annotations for that target gene from databases that are incomplete, or by their nature not tissue specific, or do not provide key information on expression levels. In all, this can lead to loss in valuable resources and time. As the vast majority of genes in the human genome express more than one isoform, there is a great need to identify the complete range of isoforms present for each gene along with their corresponding levels of expression.Here, using the long-read nanopore-based R2C2 method, we generated an Isoform-level transcriptome Atlas of Macrophage Activation (IAMA) that identifies full-length isoforms in primary human monocyte-derived macrophages (MDMs). Macrophages are critical innate immune cells important for recognizing pathogens through use of Toll-like receptors (TLRs), culminating in the initiation of host defense pathways. We characterized isoforms for most moderate to highly expressed genes in resting and TLR-activated MDMs and generated a user-friendly portal built into the UCSC Genome Browser to explore the data (https://genome.ucsc.edu/s/vollmers/IAMA). Our atlas represents a valuable resource for innate immune research as it provides unprecedented isoform information for primary human macrophages.

scholarly journals LIQA: Long-read Isoform Quantification and Analysis

2020 ◽  
Author(s):  
Yu Hu ◽  
Li Fang ◽  
Xuelian Chen ◽  
Jiang F. Zhong ◽  
Mingyao Li ◽  
...  
Keyword(s):  
Simulated Data ◽  
Read Length ◽  
Specific Gene ◽  
Rna Seq ◽  
Short Read ◽  
Oxford Nanopore ◽  
Long Read ◽  
Low Coverage ◽  
Read Distribution ◽  
Isoform Quantification

AbstractLong-read RNA sequencing (RNA-seq) technologies have made it possible to sequence full-length transcripts, facilitating the exploration of isoform-specific gene expression over conventional short-read RNA-seq. However, long-read RNA-seq suffers from high per-base error rate, presence of chimeric reads and alternative alignments, and other biases, which require different analysis methods than short-read RNA-seq. Here we present LIQA (Long-read Isoform Quantification and Analysis), an Expectation-Maximization based statistical method to quantify isoform expression and detect differential alternative splicing (DAS) events using long-read RNA-seq data. Rather than summarizing isoform-specific read counts directly as done in short-read methods, LIQA incorporates base-pair quality score and isoform-specific read length information to assign different weights across reads, which reflects alignment confidence. Moreover, given isoform usage estimates, LIQA can detect DAS events between conditions. We evaluated LIQA’s performance on simulated data and demonstrated that it outperforms other approaches in rare isoform characterization and in detecting DAS events between two groups. We also generated one direct mRNA sequencing dataset and one cDNA sequencing dataset using the Oxford Nanopore long-read platform, both with paired short-read RNA-seq data and qPCR data on selected genes, and we demonstrated that LIQA performs well in isoform discovery and quantification. Finally, we evaluated LIQA on a PacBio dataset on esophageal squamous epithelial cells, and demonstrated that LIQA recovered DAS events on FGFR3 that failed to be detected in short-read data. In summary, LIQA leverages the power of long-read RNA-seq and achieves higher accuracy in estimating isoform abundance than existing approaches, especially for isoforms with low coverage and biased read distribution. LIQA is freely available for download at https://github.com/WGLab/LIQA.

scholarly journals Assessment of mapping strategies for determining the 5□-end of mRNAs and long-noncoding RNAs with short read sequences

2020 ◽  
Author(s):  
Shuhei Noguchi ◽  
Hideya Kawaji ◽  
Takeya Kasukawa
Keyword(s):  
Genome Mapping ◽  
Rna Seq ◽  
Reference Transcriptome ◽  
Transcription Start Sites ◽  
Mapping Software ◽  
Genome Wide ◽  
Biological Interpretation ◽  
Exon Junctions ◽  
Cap Analysis ◽  
Splice Junctions

AbstractBackgroundGenome mapping is an essential step in data processing for transcriptome analysis, and many previous studies have evaluated various methods and strategies for mapping RNA-seq data. Cap Analysis of Gene Expression (CAGE) is a sequencing-based protocol particularly designed to capture the 5□-ends of transcripts for quantitatively measuring the expression levels of transcription start sites genome-wide. Because CAGE analysis can also predict the activities of promoters and enhancers, this protocol has been an essential tool in studies of transcriptional regulation. Typically, the same mapping software is used to align both RNA-seq data and CAGE reads to a reference genome, but which mapping software and options are most appropriate for mapping the 5□-end sequence reads obtained through CAGE has not previously been evaluated systematically.ResultsHere we assessed various strategies for aligning CAGE reads, particularly ∼50-bp sequences, with the human genome by using the HISAT2, LAST, and STAR programs both with and without a reference transcriptome. One of the major inconsistencies among the tested strategies involves alignments to pseudogenes and parent genes: some of the strategies prioritized alignments with pseudogenes even when the read could be aligned with coding genes with fewer mismatches. Another inconsistency concerned the detection of exon-exon junctions. These preferences depended on the program applied and whether a reference transcriptome was included. Overall, the choice of strategy yielded different mapping results for approximately 2% of all promoters.ConclusionsAlthough the various alignment strategies produced very similar results overall, we noted several important and measurable differences. In particular, using the reference transcriptome in STAR yielded alignments with the fewest mismatches. In addition, the inconsistencies among the strategies were especially noticeable regarding alignments to pseudogenes and novel splice junctions. Our results indicate that the choice of alignment strategy is important because it might affect the biological interpretation of the data.

scholarly journals Distinct core promoter codes drive transcription initiation at key developmental transitions in a marine chordate

2017 ◽  
Author(s):  
Gemma B. Danks ◽  
Pavla Navratilova ◽  
Boris Lenhard ◽  
Eric Thompson
Keyword(s):  
Transcription Initiation ◽  
Core Promoter ◽  
Ribosomal Protein Genes ◽  
Oikopleura Dioica ◽  
Transcription Start Sites ◽  
Spliced Leader ◽  
Genome Wide ◽  
A Genome ◽  
Cap Analysis ◽  
Male Specific

AbstractDevelopment is largely driven by transitions between transcriptional programs. The initiation of transcription at appropriate sites in the genome is a key component of this and yet few rules governing selection are known. Here, we used cap analysis of gene expression (CAGE) to generate bp-resolution maps of transcription start sites (TSSs) across the genome of Oikopleura dioica, a member of the closest living relatives to vertebrates. Our TSS maps revealed promoter features in common with vertebrates, as well as striking differences, and uncovered key roles for core promoter elements in the regulation of development. During spermatogenesis there is a genome-wide shift in mode of transcription initiation characterized by a novel core promoter element. This element was associated with > 70% of transcription in the testis, including the male-specific use of cryptic internal promoters within operons. In many cases this led to the exclusion of trans-splice sites, revealing a novel mechanism for regulating which mRNAs receive the spliced leader. During oogenesis the cell cycle regulator, E2F1, has been co-opted in regulating maternal transcription in endocycling nurse nuclei. In addition, maternal promoters lack the TATA-like element found in vertebrates and have broad, rather than sharp, architectures with ordered nucleosomes. Promoters of ribosomal protein genes lack the highly conserved TCT initiator. We also report an association between DNA methylation on transcribed gene bodies and the TATA-box, which indicates that this ancient promoter motif may play a role in selecting DNA for transcription-associated methylation in invertebrate genomes.

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