Biology subjects

Uszczynska-Ratajczak, B.

Publications and source records attributed to Uszczynska-Ratajczak, B..

7 recordsLinked to original sources

bioRxiv2025

CapTrap-seq: Advancing zebrafish transcriptomic research through high-fidelity full-length RNA sequencing

Zebrafish is a valuable model organism thanks to its genetic and anatomical similarities to humans, offering a more relevant system for studying human biology and disease than in vitro or non-vertebrate models. However, its use in large-scale transcriptomic research is still limited. Most zebrafish studies focus on global expression profiling in specific developmental contexts, contributing little toward improving and expanding gene annotations. These gaps lead to inaccuracies in gene quantification and downstream functional analyses, ultimately reducing the effectiveness of zebrafish as a model system. Further challenges include ineffective ribodepletion methods and limited resources for validate transcript boundaries and splicing patterns. To overcome these challenges, we applied CapTrap-seq, a long-read sequencing method that combines Cap-trapping with oligo(dT) priming to identify 5-capped, full-length transcripts from both developmental and adult tissue samples. To promote detection of longer RNA molecules, we introduced a size-selection step into CapTrap-seq protocol, which further improved detection of transcript ends without compromising its quantitative accuracy. Our results highlight the genome-agnostic nature of CapTrap-seq, enabling generation of accurate transcript models in non-mammalian systems at high-throughput. CapTrap-seq also facilitates functional annotation of zebrafish genes by uncovering novel, spliced transcript isoforms with potential biological significance.

genomics↗

bioRxiv2023

CapTrap-Seq: A platform-agnostic and quantitative approach for high-fidelity full-length RNA transcript sequencing

Long-read RNA sequencing is essential to produce accurate and exhaustive annotation of eukaryotic genomes. Despite advancements in throughput and accuracy, achieving reliable end-to-end identification of RNA transcripts remains a challenge for long-read sequencing methods. To address this limitation, we developed CapTrap-seq, a cDNA library preparation method, which combines the Cap-trapping strategy with oligo(dT) priming to detect 5capped, full-length transcripts, together with the data processing pipeline LyRic. We benchmarked CapTrap-seq and other popular RNA-seq library preparation protocols in a number of human tissues using both ONT and PacBio sequencing. To assess the accuracy of the transcript models produced, we introduced a capping strategy for synthetic RNA spike-in sequences that mimics the natural 5cap formation in RNA spike-in molecules. We found that the vast majority (up to 90%) of transcript models that LyRic derives from CapTrap-seq reads are full-length. This makes it possible to produce highly accurate annotations with minimal human intervention.

genomics↗

bioRxiv2021

Profiling subcellular localization of nuclear-encoded mitochondrial gene products in zebrafish

Most mitochondrial proteins are encoded by nuclear genes, synthetized in the cytosol and targeted into the organelle. The import of some, but not all, nuclear-encoded mitochondrial proteins begins with translation of messenger RNAs (mRNAs) on the surface of mitochondria. To characterize the spatial organization of mitochondrial gene products in zebrafish (Danio rerio), we sequenced RNA from different cellular fractions. Our results confirmed the presence of nuclear-encoded mRNAs in the mitochondrial fraction, which in unperturbed conditions, are mainly transcripts encoding large proteins with specific properties, like transmembrane domains. To further explore the principles of mitochondrial protein compartmentalization in zebrafish, we quantified the transcriptomic changes for each subcellular fraction triggered by the chchd4a-/- mutation, causing the disorders in the mitochondrial protein import. Our results indicate that the proteostatic stress further restricts the population of transcripts on the mitochondrial surface, allowing only the largest and the most evolutionary conserved proteins to be synthetized there. We also show that many nuclear-encoded mitochondrial transcripts translated by the cytosolic ribosomes stay resistant to the global translation shutdown. Thus, vertebrates, in contrast to yeast, are not likely to employ localized translation to facilitate synthesis of mitochondrial proteins under proteostatic stress conditions.

genomics↗

bioRxiv2021

Cytosolic aggregation of mitochondrial proteins disrupts cellular homeostasis by stimulating other proteins aggregation

Mitochondria are organelles with their own genomes, but they rely on the import of nuclear-encoded proteins that are translated by cytosolic ribosomes. Therefore, it is important to understand whether failures in the mitochondrial uptake of these nuclear-encoded proteins can cause proteotoxic stress and identify response mechanisms that may counteract it. Here, we report that upon impairments in mitochondrial protein import, high-risk precursor and immature forms of mitochondrial proteins form aberrant deposits in the cytosol. These deposits then cause further cytosolic accumulation and consequently aggregation of other mitochondrial proteins and disease-related proteins, including -synuclein and amyloid {beta}. This aggregation triggers a cytosolic protein homeostasis imbalance that is accompanied by specific molecular chaperone responses at both the transcriptomic and protein levels. Altogether, our results provide evidence that mitochondrial dysfunction, specifically protein import defects, contributes to impairments in protein homeostasis, thus revealing a possible molecular mechanism by which mitochondria are involved in neurodegenerative diseases.

molecular biology↗

bioRxiv2019

Systematic re-annotation of 191 genes associated with early-onset epilepsy unmasks de novo variants linked to Dravet syndrome in novel SCN1A exons

The early infantile epileptic encephalopathies (EIEE) are a group of rare, severe neurodevelopmental disorders, where even the most thorough sequencing studies leave 60-65% of patients without a molecular diagnosis. Here, we explore the incompleteness of transcript models used for exome and genome analysis as one potential explanation for lack of current diagnoses. Therefore, we have updated the GENCODE gene annotation for 191 epilepsy-associated genes, using human brain-derived transcriptomic libraries and other data to build 3,550 novel putative transcript models. The extended transcriptional footprint of these genes allowed for 294 intronic or intergenic variants, found in human mutation databases, to be reclassified as exonic, while a further 70 intronic variants were reclassified as splice-site proximal. Using SCN1A as a case study due to its close phenotype/genotype correlation with Dravet syndrome, we screened 122 people with Dravet syndrome, or a similar phenotype, with a panel of novel exon sequences representing eight established genes and identified two de novo SCN1A variants that now, through improved gene annotation can be ascribed to residing among novel exons. These two (from 122 screened patients, 1.6%) new molecular diagnoses carry significant clinical implications. Furthermore, we identified a previously-classified SCN1A intronic Dravet-associated variant that now lies within a deeply conserved novel exon. Our findings illustrate the potential gains of thorough gene annotation in improving diagnostic yields for genetic disorders. We would expect to find new molecular diagnoses in our 191 genes that were originally suspected by clinicians for patients, with a negative diagnosis.

genomics↗

bioRxiv2018

Nearly all new protein-coding predictions in the CHESS database are not protein-coding

In a 2018 paper posted to bioRxiv, Pertea et al. presented the CHESS database, a new catalog of human gene annotations that includes 1,178 new protein-coding predictions. These are based on evidence of transcription in human tissues and homology to earlier annotations in human and other mammals. Here, we reanalyze the evidence used by CHESS, and find that nearly all protein-coding predictions are false positives. We find that 86% overlap transposons marked by RepeatMasker that are known to frequently result in false positive protein-coding predictions. More than half are homologous to only nine Alu-derived primate sequences corresponding to an erroneous and previously withdrawn Pfam protein domain. The entire set shows poor evolutionary conservation and PhyloCSF protein-coding evolutionary signatures indistinguishable from noncoding RNAs, indicating lack of protein-coding constraint. Only four predictions are supported by mass spectrometry evidence, and even those matches are inconclusive. Overall, the new protein-coding predictions are unsupported by any credible experimental or evolutionary evidence of function, result primarily from homology to genes incorrectly classified as protein-coding, and are unlikely to encode functional proteins.

genomics↗

bioRxiv2017

High-throughput annotation of full-length long noncoding RNAs with Capture Long-Read Sequencing (CLS)

Accurate annotations of genes and their transcripts is a foundation of genomics, but no annotation technique presently combines throughput and accuracy. As a result, reference gene collections remain incomplete: many gene models are fragmentary, while thousands more remain uncatalogued-particularly for long noncoding RNAs (lncRNAs). To accelerate lncRNA annotation, the GENCODE consortium has developed RNA Capture Long Seq (CLS), combining targeted RNA capture with third-generation long-read sequencing. We present an experimental re-annotation of the GENCODE intergenic lncRNA population in matched human and mouse tissues, resulting in novel transcript models for 3574 / 561 gene loci, respectively. CLS approximately doubles the annotated complexity of targeted loci, outperforming existing short-read techniques. Full-length transcript models produced by CLS enable us to definitively characterize the genomic features of lncRNAs, including promoter- and gene-structure, and protein-coding potential. Thus CLS removes a longstanding bottleneck of transcriptome annotation, generating manual-quality full-length transcript models at high-throughput scales.\n\nAbbreviations

genomics↗