Dataset Information

Kallisto, bustools, and kb-python for quantifying bulk, single-cell, and single-nucleus RNA-seq.

ABSTRACT: The term "RNA-seq" refers to a collection of assays based on sequencing experiments that involve quantifying RNA species from bulk tissue, from single cells, or from single nuclei. The kallisto, bustools, and kb-python programs are free, open-source software tools for performing this analysis that together can produce gene expression quantification from raw sequencing reads. The quantifications can be individualized for multiple cells, multiple samples, or both. Additionally, these tools allow gene expression values to be classified as originating from nascent RNA species or mature RNA species, making this workflow amenable to both cell-based and nucleus-based assays. This protocol describes in detail how to use kallisto and bustools in conjunction with a wrapper, kb-python, to preprocess RNA-seq data.

SUBMITTER: Sullivan DK

PROVIDER: S-EPMC10690192 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature

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kallisto, bustools, and kb-python for quantifying bulk, single-cell, and single-nucleus RNA-seq.

Sullivan Delaney K DK Min Kyung Hoi Joseph KHJ Hjörleifsson Kristján Eldjárn KE Luebbert Laura L Holley Guillaume G Moses Lambda L Gustafsson Johan J Bray Nicolas L NL Pimentel Harold H Booeshaghi A Sina AS Melsted Páll P Pachter Lior L

bioRxiv : the preprint server for biology 20240123

The term "RNA-seq" refers to a collection of assays based on sequencing experiments that involve quantifying RNA species from bulk tissue, from single cells, or from single nuclei. The kallisto, bustools, and kb-python programs are free, open-source software tools for performing this analysis that together can produce gene expression quantification from raw sequencing reads. The quantifications can be individualized for multiple cells, multiple samples, or both. Additionally, these tools allow g ...[more]

PMID: 38045414

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Project description:Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by progressive and selective degeneration of motor neurons in the motor cortex of brain and spinal cord. Ferroptosis is a newly discovered form of cell death and reported to mediate selective motor neuron death in the mouse model of ALS. The growing awareness of ferroptosis and iron metabolism dysfunction in ALS prompted us to investigate the expression pattern of ferroptosis and iron metabolism-related genes (FIRGs) in ALS. Here, we performed a conjoint analysis of bulk-RNA sequence and single-nucleus RNA sequence data using the datasets from Gene Expression Omnibus (GEO) to reveal the role of FIRGs in ALS, especially in selective motor neuron death of ALS. We first investigated the differentially expressed genes (DEGs) between ALS and non-neurological controls. Weighted gene co-expression network analysis constructed the gene co-expression network and identified three modules closely associated with ALS. Fifteen FIRGs was identified as target genes based on least absolute shrinkage and selection operator regression analysis as follows: ACSL4, ANO6, ATP6V0E1, B2M, CD44, CHMP5, CYBB, CYBRD1, HIF1A, MOSPD1, NCF2, SDCBP, STEAP2, TMEM14C, ULK1. These genes could differentiate ALS patients from non-neurological controls (p < 2.2e-16) and had a valid value in predicting and diagnosing ALS (AUC = 0.881 in primary dataset and AUC = 0.768 in validation dataset). Then we performed the functional enrichment analysis of DEGs between ALS cases, the most significantly influenced by target genes, and non-neurological controls. The result indicated that the most significantly influenced functions in ALS pathogenesis by these identified FIRGs are synapse pathways, calcium signaling pathway, cAMP signaling pathway, and phagosome and several immune pathways. At last, the analysis of single- nuclear seq found that CHMP5, one of the 15 FIRGs identified by bulk single-nucleus RNA-seq data, was expressed significantly higher in ALS than pathologically normal (PN), specifically in excitatory neuron populations with layer 2 and layer 3 markers (Ex L2_L3), layer 3 and layer 5 markers (Ex L3_L5). Taken together, our study indicates the positive correlation between FIRGs and ALS, presents potential markers for ALS diagnosis and provides new research directions of CHMP5 function in selective motor neuron death in ALS.

Dataset Information

Kallisto, bustools, and kb-python for quantifying bulk, single-cell, and single-nucleus RNA-seq.

Publications

kallisto, bustools, and kb-python for quantifying bulk, single-cell, and single-nucleus RNA-seq.

Similar Datasets

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