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Mucopolysaccharidosis (MPS) encompasses a heterogeneous group of lysosomal storage diseases resulting from mutations in genes encoding lysosomal enzymes responsible for the degradation of mucopolysaccharides, also known as glycosaminoglycans (GAGs). Current therapeutic strategies for MPS include hematopoietic stem cell transplantation (HSCT), enzyme replacement therapy (ERT), and symptomatic therapy. This study investigated dynamic changes in MPS type II (MPS-II) through genomic and single-cell sequencing in a patient undergoing ERT. Analysis of peripheral blood mononuclear cells (PBMCs) from one MPS-II patient of 10 year old at different disease stages through scRNA-seq identified various immune cell types, including natural killer (NK) cells, NKT cells, CD4 + and CD8 + T cells, CD14 + and CD16 + monocytes, and B cells. Monocytes and macrophages were significantly reduced during the severe stage of MPS-II but increased during the recovery stage following ERT. Notably, monocyte subtype mono3 was exclusively expressed in the severe stage, while mono1_2, a subtype of mono1, was absent during the severe stage and exhibited distinct biological functions. These findings suggest that monocytes and macrophages play critical roles in the pathogenesis of MPS-II and in the response to ERT. Pseudotime, Gene Ontology, and cell-communication analyses revealed unique functions for the different cellular subtypes. Notably, key molecules mediating cellular interactions during ERT in MPS-II included CXCR3, PF4, APP, and C5AR1 in macrophages, RPS19 in T cells, HLA-DPB1 in B cells, ADRB2 in NK cells, and IL1B, C5AR1, RPS19, and TNFSF13B in monocytes. Overall, integrative analysis delineated the expression dynamics of various cell types and identified mutations in MPS-II, providing a comprehensive atlas of transcriptional programs, cellular characterizations, and genomic variation profiles in MPS-II. This dataset, along with advanced integrative analysis, represents a valuable resource for the discovery of drug targets and the improvement of therapeutic strategies for MPS-II.
Pubmed ID: 40210734
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A software package to analyze next-generation resequencing data. The toolkit offers a wide variety of tools, with a primary focus on variant discovery and genotyping as well as strong emphasis on data quality assurance. Its robust architecture, powerful processing engine and high-performance computing features make it capable of taking on projects of any size. This software library makes writing efficient analysis tools using next-generation sequencing data very easy, and second it's a suite of tools for working with human medical resequencing projects such as 1000 Genomes and The Cancer Genome Atlas. These tools include things like a depth of coverage analyzers, a quality score recalibrator, a SNP/indel caller and a local realigner. (entry from Genetic Analysis Software)
View all literature mentionsSoftware package for interpreting gene expression data. Used for interpretation of a large-scale experiment by identifying pathways and processes.
View all literature mentionsInternational collaboration producing an extensive public catalog of human genetic variation, including SNPs and structural variants, and their haplotype contexts, in an effort to provide a foundation for investigating the relationship between genotype and phenotype. The genomes of about 2500 unidentified people from about 25 populations around the world were sequenced using next-generation sequencing technologies. Redundant sequencing on various platforms and by different groups of scientists of the same samples can be compared. The results of the study are freely and publicly accessible to researchers worldwide. The consortium identified the following populations whose DNA will be sequenced: Yoruba in Ibadan, Nigeria; Japanese in Tokyo; Chinese in Beijing; Utah residents with ancestry from northern and western Europe; Luhya in Webuye, Kenya; Maasai in Kinyawa, Kenya; Toscani in Italy; Gujarati Indians in Houston; Chinese in metropolitan Denver; people of Mexican ancestry in Los Angeles; and people of African ancestry in the southwestern United States. The goal Project is to find most genetic variants that have frequencies of at least 1% in the populations studied. Sequencing is still too expensive to deeply sequence the many samples being studied for this project. However, any particular region of the genome generally contains a limited number of haplotypes. Data can be combined across many samples to allow efficient detection of most of the variants in a region. The Project currently plans to sequence each sample to about 4X coverage; at this depth sequencing cannot provide the complete genotype of each sample, but should allow the detection of most variants with frequencies as low as 1%. Combining the data from 2500 samples should allow highly accurate estimation (imputation) of the variants and genotypes for each sample that were not seen directly by the light sequencing. All samples from the 1000 genomes are available as lymphoblastoid cell lines (LCLs) and LCL derived DNA from the Coriell Cell Repository as part of the NHGRI Catalog. The sequence and alignment data generated by the 1000genomes project is made available as quickly as possible via their mirrored ftp sites. ftp://ftp.1000genomes.ebi.ac.uk ftp://ftp-trace.ncbi.nlm.nih.gov/1000genomes
View all literature mentionsSoftware R package for statistical analysis and visualization of functional profiles for genes and gene clusters.
View all literature mentionsSoftware tool for sequence mapping.The next version of BWA-MEM. Used for aligning sequencing reads against large reference genome.
View all literature mentionsDatabase of human regulatory elements like enhancers and promoters, and their inferred target genes which is embedded in GeneCards, human gene compendium. Associations between regulatory elements and target genes were based on multiple sources of linking molecular data, along with distance.
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