FAVA: High-quality functional association networks inferred from scRNA-seq and proteomics data DOI Creative Commons
Mikaela Koutrouli, Pau Piera Líndez, Katerina Nastou

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2022, Volume and Issue: unknown

Published: July 7, 2022

Abstract Protein networks are commonly used for understanding how proteins interact. However, they typically biased by data availability, favoring well-studied with more interactions. To uncover functions of understudied proteins, we must use that not affected this literature bias, such as single-cell RNA-seq and proteomics. Due to sparseness redundancy, co-expression analysis becomes complex. address this, have developed FAVA (Functional Associations using Variational Autoencoders), which compresses high-dimensional into a low-dimensional space. infers from omics much higher accuracy than existing methods, across diverse collection real well simulated datasets. can process large datasets over 0.5 million conditions has predicted 4,210 interactions between 1,039 proteins. Our findings showcase FAVA’s capability offer novel perspectives on protein within the scverse ecosystem, employing AnnData its input source.

Language: Английский

Triosephosphate isomerase 1 may be a risk predictor in laryngeal squamous cell carcinoma: a multi-centered study integrating bulk RNA, single-cell RNA, and protein immunohistochemistry DOI Creative Commons
Jian‐Di Li, Yi Chen,

Shu-Wen Jing

et al.

European journal of medical research, Journal Year: 2023, Volume and Issue: 28(1)

Published: Dec. 15, 2023

Although great progress has been made in anti-cancer therapy, the prognosis of laryngeal squamous cell carcinoma (LSCC) patients remains unsatisfied. Quantities studies demonstrate that glycolytic reprograming is essential for progression cancers, where triosephosphate isomerase 1 (TPI1) serves as a catalytic enzyme. However, clinicopathological significance and potential biological functions TPI1 underlying LSCC obscure.We collected in-house 82 tissue specimens 56 non-tumor specimens. Tissue microarrays (TMA) immunohistochemical (IHC) experiments were performed. External bulk RNA sequencing data integrated to evaluate expression TPI1. We used log-rank test CIBERSORT algorithm assess prognostic value its association with microenvironment. Malignant epithelial cells immune-stromal identified using inferCNV CellTypist. conducted comprehensive analysis elucidate molecular single Pearson correlation analysis, high dimensional weighted gene co-expression set enrichment clustered regularly interspaced short palindromic repeats (CRISPR) screen. explored intercellular communication patterns between predicted several therapeutic agents targeting TPI1.Based on TMA IHC protein was found have strong positive nucleus but only weakly activity cytoplasm normal (p < 0.0001). Further confirmation elevated mRNA obtained from external datasets, comparing 251 samples 136 non-LSCC (standardized mean difference = 1.06). The upregulated demonstrated discriminative ability (area under curve 0.91; sensitivity 0.87; specificity 0.79), suggesting predictive marker poor 0.037). Lower infiltration abundance plasma cells, naïve B monocytes, neutrophils TPI-high tissue. Glycolysis cycle significantly enriched pathways both heat shock family member 1, TPI1, enolase occupied central position. Four outgoing two incoming networks. an oncogene LSCC, CRISPR scores less than -1 across 71.43% lines. positively correlated half maximal inhibitory concentration gemcitabine cladribine.TPI1 dramatically overexpressed tissue, may promote deterioration through metabolic non-metabolic functions. This study contributes advancing our knowledge pathogenesis implications development targeted therapies future.

Language: Английский

Citations

4
Molecular and circuit determinants in the globus pallidus mediating control of cocaine-induced behavioral plasticity DOI Open Access

Guilian Tian,

Katrina Bartas, May Hui

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: May 31, 2024

The globus pallidus externus (GPe) is a central component of the basal ganglia circuit, receiving strong input from indirect pathway and regulating variety functions, including locomotor output habit formation. We recently showed that it also acts as gatekeeper cocaine-induced behavioral plasticity, inhibition parvalbumin-positive cells in GPe (GPe

Language: Английский

Citations

1
Atrial fibrillation variant-to-gene prioritization through cross-ancestry eQTL and single-nucleus multiomic analyses DOI Creative Commons
Francis Leblanc,

Xuexin Jin,

Kai Kang

et al.

iScience, Journal Year: 2024, Volume and Issue: 27(9), P. 110660 - 110660

Published: Aug. 5, 2024

Highlights•Bulk and single-nucleus RNA-seq data from human atria help interpret AF GWAS results•Co-localization fine-mapping implicate 14 genes at 9 loci•LINC01629 is involved in the development of atrial tissue conduction systemSummaryAtrial fibrillation (AF) most common arrhythmia world. Human genetics can provide strong therapeutic candidates, but identification causal their functions remains challenging. Here, we applied an strategy that leverages results a previously published cross-ancestry genome-wide association study (GWAS), expression quantitative trait loci (eQTLs) left appendages (LAAs) obtained two cohorts with distinct ancestry, paired RNA sequencing (RNA-seq) ATAC (ATAC-seq) LAA assay (sn-multiome). At nine loci, our co-localization analyses implicated genes. Data integration identified several candidate variants, including rs7612445 GNB4 rs242557 MAPT. Finally, showed repression strongest AF-associated eQTL gene, LINC01629, embryonic stem cell-derived cardiomyocytes using CRISPR inhibition dysregulation pathways linked to cardiac system.Graphical abstract

Language: Английский

Citations

1
Unveiling Osmoregulation and Immunological Adaptations in Eleutheronema tetradactylum Gills through High-Throughput Single-Cell Transcriptome Sequencing DOI
Xiaoli Ma, Wen‐Xiong Wang

Fish & Shellfish Immunology, Journal Year: 2024, Volume and Issue: 154, P. 109878 - 109878

Published: Sept. 6, 2024

Language: Английский

Citations

1
FAVA: High-quality functional association networks inferred from scRNA-seq and proteomics data DOI Creative Commons
Mikaela Koutrouli, Pau Piera Líndez, Katerina Nastou

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2022, Volume and Issue: unknown

Published: July 7, 2022

Abstract Protein networks are commonly used for understanding how proteins interact. However, they typically biased by data availability, favoring well-studied with more interactions. To uncover functions of understudied proteins, we must use that not affected this literature bias, such as single-cell RNA-seq and proteomics. Due to sparseness redundancy, co-expression analysis becomes complex. address this, have developed FAVA (Functional Associations using Variational Autoencoders), which compresses high-dimensional into a low-dimensional space. infers from omics much higher accuracy than existing methods, across diverse collection real well simulated datasets. can process large datasets over 0.5 million conditions has predicted 4,210 interactions between 1,039 proteins. Our findings showcase FAVA’s capability offer novel perspectives on protein within the scverse ecosystem, employing AnnData its input source.

Language: Английский

Citations

6