hdWGCNA identifies co-expression networks in high-dimensional transcriptomics data

Cell Reports Methods, Год журнала: 2023, Номер 3(6), С. 100498 - 100498

Опубликована: Июнь 1, 2023

Biological systems are immensely complex, organized into a multi-scale hierarchy of functional units based on tightly regulated interactions between distinct molecules, cells, organs, and organisms. While experimental methods enable transcriptome-wide measurements across millions popular bioinformatic tools do not support systems-level analysis. Here we present hdWGCNA, comprehensive framework for analyzing co-expression networks in high-dimensional transcriptomics data such as single-cell spatial RNA sequencing (RNA-seq). hdWGCNA provides functions network inference, gene module identification, enrichment analysis, statistical tests, visualization. Beyond conventional RNA-seq, is capable performing isoform-level analysis using long-read data. We showcase from autism spectrum disorder Alzheimer's disease brain samples, identifying disease-relevant modules. directly compatible with Seurat, widely used R package demonstrate the scalability by dataset containing nearly 1 million cells.

Язык: Английский

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RNA splicing dysregulation and the hallmarks of cancer

Nature reviews. Cancer, Год журнала: 2023, Номер 23(3), С. 135 - 155

Опубликована: Янв. 10, 2023

Язык: Английский

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Single-cell and spatial transcriptomics: deciphering brain complexity in health and disease

Nature Reviews Neurology, Год журнала: 2023, Номер 19(6), С. 346 - 362

Опубликована: Май 17, 2023

Язык: Английский

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Global detection of human variants and isoforms by deep proteome sequencing

Nature Biotechnology, Год журнала: 2023, Номер 41(12), С. 1776 - 1786

Опубликована: Март 23, 2023

Abstract An average shotgun proteomics experiment detects approximately 10,000 human proteins from a single sample. However, individual are typically identified by peptide sequences representing small fraction of their total amino acids. Hence, an fails to distinguish different protein variants and isoforms. Deeper proteome sequencing is therefore required for the global discovery Using six cell lines, proteases, deep fractionation three tandem mass spectrometry fragmentation methods, we identify million unique peptides 17,717 groups, with median sequence coverage 80%. Direct comparison RNA expression data provides evidence translation most nonsynonymous variants. We have also hypothesized that undetected likely arise mutation-induced instability. further observe comparable detection rates exon–exon junction constitutive alternative splicing events. Our dataset represents resource proteoform direct frame-preserving alternatively spliced isoforms translated.

Язык: Английский

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Advances in single-cell omics and multiomics for high-resolution molecular profiling

Experimental & Molecular Medicine, Год журнала: 2024, Номер 56(3), С. 515 - 526

Опубликована: Март 5, 2024

Abstract Single-cell omics technologies have revolutionized molecular profiling by providing high-resolution insights into cellular heterogeneity and complexity. Traditional bulk approaches average signals from heterogeneous cell populations, thereby obscuring important nuances. studies enable the analysis of individual cells reveal diverse types, dynamic states, rare populations. These techniques offer unprecedented resolution sensitivity, enabling researchers to unravel landscape cells. Furthermore, integration multimodal data within a single provides comprehensive holistic view processes. By combining multiple dimensions, can facilitate elucidation complex interactions, regulatory networks, mechanisms. This integrative approach enhances our understanding systems, development disease. review an overview recent advances in single-cell for profiling. We discuss principles methodologies representatives each method, highlighting strengths limitations different techniques. In addition, we present case demonstrating applications various fields, including developmental biology, neurobiology, cancer research, immunology, precision medicine.

Язык: Английский

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Single-cell long-read sequencing-based mapping reveals specialized splicing patterns in developing and adult mouse and human brain

Nature Neuroscience, Год журнала: 2024, Номер 27(6), С. 1051 - 1063

Опубликована: Апрель 9, 2024

Abstract RNA isoforms influence cell identity and function. However, a comprehensive brain isoform map was lacking. We analyze single-cell across regions, subtypes, developmental time points species. For 72% of genes, full-length expression varies along one or more axes. Splicing, transcription start polyadenylation sites vary strongly between types, protein architecture associate with disease-linked variation. Additionally, neurotransmitter transport synapse turnover genes harbor cell-type variability anatomical regions. Regulation cell-type-specific splicing is pronounced in the postnatal day 21-to-postnatal 28 adolescent transition. Developmental regulation stronger than regional for same type. Cell-type-specific mice mostly maintained human hippocampus, allowing extrapolation to brain. Conversely, harbors additional specificity, suggesting gain-of-function isoforms. Together, this detailed atlas development, regions species reveals an unappreciated degree multiple

Язык: Английский

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Developmental isoform diversity in the human neocortex informs neuropsychiatric risk mechanisms

Science, Год журнала: 2024, Номер 384(6698)

Опубликована: Май 23, 2024

RNA splicing is highly prevalent in the brain and has strong links to neuropsychiatric disorders; yet, role of cell type-specific transcript-isoform diversity during human development not been systematically investigated. In this work, we leveraged single-molecule long-read sequencing deeply profile full-length transcriptome germinal zone cortical plate regions developing neocortex at tissue single-cell resolution. We identified 214,516 distinct isoforms, which 72.6% were novel (not previously annotated Gencode version 33), uncovered a substantial contribution diversity-regulated by binding proteins-in defining cellular identity neocortex. comprehensive isoform-centric gene annotation reprioritize thousands rare de novo risk variants elucidate genetic mechanisms for disorders.

Язык: Английский

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Neurovascular dysfunction in GRN-associated frontotemporal dementia identified by single-nucleus RNA sequencing of human cerebral cortex

Nature Neuroscience, Год журнала: 2022, Номер 25(8), С. 1034 - 1048

Опубликована: Июль 25, 2022

Язык: Английский

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High dimensional co-expression networks enable discovery of transcriptomic drivers in complex biological systems

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2022, Номер unknown

Опубликована: Сен. 23, 2022

Biological systems are immensely complex, organized into a multi-scale hierarchy of functional units based on tightly-regulated interactions between distinct molecules, cells, organs, and organisms. While experimental methods enable transcriptome-wide measurements across millions the most ubiquitous bioinformatic tools do not support systems-level analysis. Here we present hdWGCNA, comprehensive framework for analyzing co-expression networks in high dimensional transcriptomics data such as single-cell spatial RNA-seq. hdWGCNA provides built-in functions network inference, gene module identification, enrichment analysis, statistical tests reproducibility, visualization. In addition to conventional RNA-seq, is capable performing isoform-level analysis using long-read data. We showcase publicly available datasets from Autism spectrum disorder Alzheimer’s disease brain samples, identifying disease-relevant modules specific cell populations. directly compatible with Seurat, widely-used R package demonstrate scalability by dataset containing nearly one million cells.

Язык: Английский

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High-throughput and high-accuracy single-cell RNA isoform analysis using PacBio circular consensus sequencing

Nature Communications, Год журнала: 2023, Номер 14(1)

Опубликована: Май 6, 2023

Although long-read single-cell RNA isoform sequencing (scISO-Seq) can reveal alternative splicing in individual cells, it suffers from a low read throughput. Here, we introduce HIT-scISOseq, method that removes most artifact cDNAs and concatenates multiple for PacBio circular consensus (CCS) to achieve high-throughput high-accuracy sequencing. HIT-scISOseq yield >10 million long-reads single Sequel II SMRT Cell 8M. We also report the development of scISA-Tools demultiplex concatenated reads into cDNA with >99.99% accuracy specificity. apply characterize transcriptomes 3375 corneal limbus cells cell-type-specific expression them. is high-throughput, high-accuracy, technically accessible accelerate burgeoning field transcriptomics.

Язык: Английский

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