Data from: A novel mouse model for LAMA2-related muscular dystrophy with analysis of molecular pathogenesis and clinical phenotype
Data files
Abstract
Our understanding of the molecular pathogenesis of LAMA2-related muscular dystrophy (LAMA2-MD) requires improvement. Here, we report the phenotype, neuropathology, and transcriptomics data (scRNA-seq and bulk RNA-seq) of a new Lama2 knockout mouse (dyH/dyH), which was created based on the human LAMA2-MD mutation hotspot region using CRISPR-Cas9. The dyH/dyH mice presented a severe phenotype with muscular dystrophy. Mouse brain scRNA-seq showed that the Lama2 gene was expressed predominantly and specifically in vascular and leptomeningeal fibroblasts and vascular smooth muscle cells, and weakly in astrocytes in wild-type mice. Laminin α2 expression on the cortical surface was observed with immunofluorescence. In dyH/dyH, Lama2 expression was decreased in those cell types, which might be associated with the disruption of gliovascular basal lamina assembly. Additionally, transcriptomic investigation of muscles showed 2020 differentially expressed genes, mainly associated with the impaired muscle cytoskeleton and development. In summary, this study provided potentially useful information for understanding the molecular pathogenesis of LAMA2-MD.
Dataset DOI: 10.5061/dryad.3j9kd51xs
Description of the data and file structure
We have generated a novel dyH/dyH knockout mouse with ΔExon 3 at the Lama2 locus. The bulk RNA-seq data of the biceps femoris of the dyH/dyH and wild-type (WT) mice have been deposited.
RNA sequencing data of the biceps femoris obtained from 14-day-old mice of WT (n = 4) and dyH/dyH (KO- LAMMA2 knockout) (n = 6) has been shown with files WT1, WT2, WT3, WT4, KO1, KO2, KO3, KO4, KO5, and KO6.
The RNA samples were submitted to CapitalBio (https://www.capitalbiotech.com) for next-generation sequencing with the TruSeq RNA Exome. Paired-end sequencing (2 × 150 bp reads) was performed on successful RNA libraries using the Illumina HiSeq X-Ten platform. During the experiment, investigators were blinded to the samples’ information. The quality of raw reads was first assessed using FastQC. After filtering out low-quality bases and adaptors using FastP, reads were mapped to the mouse genome assembly GRCh38 (Mus_musculus.GRCm38.dna.toplevel.REF.fa) using Hisat2. Samples were subjected to quality control by examining the percentage of reads uniquely mapping to the genome, the percentage of reads mapping to known protein-coding sequences, and the number of genes with 90% base coverage. Gene fusions were identified by mapping reads to the mouse genome using StringTie.
Files and variables
File: WT1.zip
Description: RNA sequencing data of biceps femoris obtained from a 14-day-old WT mouse 1
File: WT2.zip
Description: RNA sequencing data of biceps femoris obtained from a 14-day-old WT mouse 2
File: WT3.zip
Description: RNA sequencing data of biceps femoris obtained from a 14-day-old WT mouse 3
File: WT4.zip
Description: RNA sequencing data of biceps femoris obtained from a 14-day-old WT mouse 4
File: KO4.zip
Description: RNA sequencing data of biceps femoris obtained from a 14-day-old KO mouse 4
File: KO1.zip
Description: RNA sequencing data of the biceps femoris obtained from a 14-day-old KO mouse 1
File: KO2.zip
Description: RNA sequencing data of the biceps femoris obtained from a 14-day-old KO mouse 2
File: KO5.zip
Description: RNA sequencing data of biceps femoris obtained from a 14-day-old KO mouse 5
File: KO3.zip
Description: RNA sequencing data of biceps femoris obtained from a 14-day-old KO mouse 3
File: KO6.zip
Description: RNA sequencing data of biceps femoris obtained from a 14-day-old KO mouse 6