Biology subjects

Prjibelski, A. D.

Publications and source records attributed to Prjibelski, A. D..

6 recordsLinked to original sources

bioRxiv2025

Spatial isoform sequencing at sub-micrometer single-cell resolution reveals novel patterns of spatial isoform variability in brain cell types

Spatial long-read technologies are becoming increasingly common but lack nanometer and therefore often single-cell resolution. This leaves the question unanswered of whether spatially variable isoforms represent spatial variability within one cell type or differences in cell-type composition between different regions. Here, we developed Spl-ISO-Seq2 (220nm spot size and 500nm resolution), and the accompanying software packages Spl-IsoQuant-2 and Spl-IsoFind, enabling long-read sequencing using up to 500 million barcodes compared to 80,000 previously. Applying this to the adult mouse brain, we compared spatial variability by examining (a) differential isoform abundance between known brain regions and (b) spatial isoform patterns that do not align with predefined regions. While the former revealed more spatial isoform differences, both approaches identified overlapping hits, e.g., Rps24 in oligodendrocytes. For Snap25, previously known to exhibit spatial isoform variation, we now show that this variability occurs in excitatory neurons. The second approach also uncovered patterns not captured by predefined-region comparisons, e.g., Tnnc1 in excitatory neurons. Furthermore, we show that a surprising number of spatial isoform signals is not driven by cell-type composition alone. Finally, we applied our software to newly generated Visium HD 3 long-read data to demonstrate its applicability and strong reproducibility across protocols and biological replicates. Taken together, our experimental and analytical methods enrich spatial transcriptomics with a so-far elusive isoform view of spatial variation for individual cell types.

neuroscience↗

bioRxiv2025

A spatial long-read approach at near-single-cell resolution reveals developmental regulation of splicing and polyadenylation sites in distinct cortical layers and cell types.

Genome-wide single-cell and spatial long-read approaches have gained traction, but mostly lack single-cell resolution - and yield limited read lengths. Here, we introduce spatial ISOform sequencing (Spl-ISO-Seq), which reveals exons and polyadenylation sites from long reads with near-single-cell resolution. Spl-ISO-Seq selects long cDNAs and doubles to triples read lengths compared to standard preparations. Adding a highly specific software tool (Spl-ISOquant) and comparing human post-mortem pre-puberty samples of the visual cortex (8-11 years) to post-puberty samples (16-19 years), we find that cortical layers harbor stronger splicing and poly(A)-site regulation than the adjacent white matter, with enrichment of multiple protein-domain types. For oligodendrocytes however, developmental splicing changes are stronger in white matter. Among cortical layers, layer 4 has the most developmental changes in alternative-exon inclusion in excitatory neurons and in poly(A) sites. We also find many repeat elements, especially ERV1 long terminal repeats downstream of developmentally-regulated layer 4 exons. Overall, alternative splicing changes are linked to synapses - specifically at the post-synapse. Age-linked splicing changes in layers 1-3 and 4 are associated with autism spectrum disorder but not with schizophrenia, amyotrophic lateral sclerosis and Alzheimers disease. These results root developmental splicing changes during puberty and the resulting protein changes in specific layers and cell types. More generally, our new technologies enable new observations for any complex tissue.

genomics↗

bioRxiv2023

Systematic assessment of long-read RNA-seq methods for transcript identification and quantification

AbstractThe Long-read RNA-Seq Genome Annotation Assessment Project (LRGASP) Consortium was formed to evaluate the effectiveness of long-read approaches for transcriptome analysis. The consortium generated over 427 million long-read sequences from cDNA and direct RNA datasets, encompassing human, mouse, and manatee species, using different protocols and sequencing platforms. These data were utilized by developers to address challenges in transcript isoform detection and quantification, as well as de novo transcript isoform identification. The study revealed that libraries with longer, more accurate sequences produce more accurate transcripts than those with increased read depth, whereas greater read depth improved quantification accuracy. In well-annotated genomes, tools based on reference sequences demonstrated the best performance. When aiming to detect rare and novel transcripts or when using reference-free approaches, incorporating additional orthogonal data and replicate samples are advised. This collaborative study offers a benchmark for current practices and provides direction for future method development in transcriptome analysis.

genomics↗

bioRxiv2022

Sequencing of individual barcoded cDNAs on Pacific Biosciences and Oxford Nanopore reveals platform-specific error patterns

Long-read transcriptomics requires understanding error sources inherent to technologies. Current approaches cannot compare methods for an individual RNA molecule. Here, we present a novel platform comparison method that combined barcoding strategies and long-read sequencing to sequence cDNA copies representing an individual RNA molecule on both Pacific Biosciences and Oxford Nanopore. We compared these long reads pairs in terms of sequence content and splicing structure. Although individual read pairs show high similarity, we found differences in (i) aligned length, (ii) TSS and (iii) polyA-site assignment, and (iv) exon-intron structures. Overall 25% of read pairs disagreed on either TSS, polyA-site, or a splice site. Intron-chain disagreement typically arises from alignment errors of microexons and complicated splice sites. Our single-molecule technology comparison revealed that inconsistencies are often caused by sequencing-error induced inaccurate ONT alignments, especially to downstream GTNNGT donor motifs. However, annotation-disagreeing upstream shifts in NAGNAG acceptors in ONT are often confirmed by PacBio and thus likely real. In both barcoded and non-barcoded ONT reads, we found that intron number and proximity of other GT/AGs better predict inconsistency with the annotation than read quality alone. We summarized these findings in an annotation-based algorithm for spliced alignment correction that improves subsequent transcript construction with ONT reads.

bioinformatics↗

bioRxiv2021

Single-nuclei isoform RNA sequencing reveals combination patterns of transcript elements across human brain cell types

Single-nuclei RNA-Seq is being widely employed to investigate cell types, especially of human brain and other frozen samples. In contrast to single-cell approaches, however, the majority of single-nuclei RNA counts originate from partially processed RNA leading to intronic cDNAs, thus hindering the investigation of complete isoforms. Here, using microfluidics, PCR-based artifact removal, target enrichment, and long-read sequencing, we developed single-nuclei isoform RNA-sequencing ( SnISOr-Seq), and applied it to the analysis of human adult frontal cortex samples. We found that exons associated with autism exhibit coordinated and more cell-type specific inclusion than exons associated with schizophrenia or ALS. We discovered two distinct modes of combination patterns: first, those distinguishing cell types in the human brain. These are enriched in combinations of TSS-exon, exon-polyA site, and distant (non-adjacent) exon pairs. Second, those with all isoform combinations found within one neural cell type, which are enriched in adjacent exon pairs. Furthermore, adjacent exon pairs are predominantly mutually associated, while distant pairs are frequently mutually exclusive. Finally, we observed that human-specific exons are as tightly coordinated as conserved exons, pointing to an efficient evolutionary mechanism underpinning coordination. SnISOr-Seq opens the door to single-nuclei long-read isoform analysis in the human brain, and in any frozen, archived or hard-to-dissociate sample.

genomics↗

bioRxiv2020

Extending rnaSPAdes functionality for hybridtranscriptome assembly

BackgroundDe novo RNA-Seq assembly is a powerful method for analysing transcriptomes when the reference genome is not available or poorly annotated. However, due to the short length of Illumina reads it is usually impossible to reconstruct complete sequences of complex genes and alternative isoforms. Recently emerged possibility to generate long RNA reads, such as PacBio and Oxford Nanopores, may dramatically improve the assembly quality, and thus the consecutive analysis. While reference-based tools for analysing long RNA reads were recently developed, there is no established pipeline for de novo assembly of such data. ResultsIn this work we present a novel method that allows to perform high-quality de novo transcriptome assemblies by combining accuracy and reliability of short reads with exon structure information carried out from long error-prone reads. The algorithm is designed by incorporating existing hybridSPAdes approach into rnaSPAdes pipeline and adapting it for transcriptomic data. ConclusionTo evaluate the benefit of using long RNA reads we selected several datasets containing both Illumina and Iso-seq or Oxford Nanopore Technologies (ONT) reads. Using an existing quality assessment software, we show that hybrid assemblies performed with rnaSPAdes contain more full-length genes and alternative isoforms comparing to the case when only short-read data is used. Availability and implementationrnaSPAdes is implemented in C++ and Python and is freely available for Linux and MacOS under GPLv2 license at cab.spbu.ru/software/rnaspades/ and github.com/ablab/spades.

bioinformatics↗