Dataset Information

Predictive modeling provides insight into the clinical heterogeneity associated with TARS1 loss-of-function mutations.

ABSTRACT: Aminoacyl-tRNA synthetases (ARSs) are ubiquitously expressed, essential enzymes that complete the first step of protein translation: ligation of amino acids to cognate tRNAs. Genes encoding ARSs have been implicated in myriad dominant and recessive phenotypes, the latter often affecting multiple tissues but with frequent involvement of the central and peripheral nervous system, liver, and lungs. Threonyl-tRNA synthetase (TARS1) encodes the enzyme that ligates threonine to tRNA^THR in the cytoplasm. To date, TARS1 variants have been implicated in a recessive brittle hair phenotype. To better understand TARS1-related recessive phenotypes, we engineered three TARS1 missense mutations predicted to cause a loss-of-function effect and studied these variants in yeast and worm models. This revealed two loss-of-function mutations, including one hypomorphic allele (R433H). We next used R433H to study the effects of partial loss of TARS1 function in a compound heterozygous mouse model (R433H/null). This model presents with phenotypes reminiscent of patients with TARS1 variants and with distinct lung and skin defects. This study expands the potential clinical heterogeneity of TARS1-related recessive disease, which should guide future clinical and genetic evaluations of patient populations.

SUBMITTER: Meyer-Schuman R

PROVIDER: S-EPMC10996635 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature

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Predictive modeling provides insight into the clinical heterogeneity associated with TARS1 loss-of-function mutations.

Meyer-Schuman Rebecca R Cale Allison R AR Pierluissi Jennifer A JA Jonatzke Kira E KE Park Young N YN Lenk Guy M GM Oprescu Stephanie N SN Grachtchouk Marina A MA Dlugosz Andrzej A AA Beg Asim A AA Meisler Miriam H MH Antonellis Anthony A

bioRxiv : the preprint server for biology 20240327

Aminoacyl-tRNA synthetases (ARSs) are ubiquitously expressed, essential enzymes that complete the first step of protein translation: ligation of amino acids to cognate tRNAs. Genes encoding ARSs have been implicated in myriad dominant and recessive phenotypes, the latter often affecting multiple tissues but with frequent involvement of the central and peripheral nervous system, liver, and lungs. Threonyl-tRNA synthetase (TARS1) encodes the enzyme that ligates threonine to tRNATHR</su ...[more]

PMID: 38585737

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Project description:MECP2 Duplication Syndrome, also known as X-linked intellectual developmental disorder Lubs type (MRXSL; MIM: 300260), is a neurodevelopmental disorder caused by copy number gains spanning MECP2. Despite varying genomic rearrangement structures, including duplications and triplications, and a wide range of duplication sizes, no clear correlation exists between DNA rearrangement and clinical features. We had previously demonstrated that up to 38% of MRXLS families are characterized by complex genomic rearrangements (CGRs) of intermediate complexity (2 ≤ CNV breakpoints < 5), yet the impact of these genomic structures on regulation of gene expression and phenotypic manifestations have not been investigated. To study the role of the genomic rearrangement structures on an individual’s clinical phenotypic variability, we employed a comprehensive genomics, transcriptomics, and deep phenotyping analysis approach on 137 individuals affected by MRXSL. Genomic structural information was correlated with transcriptomic and quantitative phenotypic analysis using Human Phenotype Ontology (HPO) semantic similarity scores. Duplication sizes in the cohort ranging from 64 kb to 16.5 Mb were classified into four categories comprising of tandem duplications (47%), terminal duplications (23%), inverted triplication structures (23%), and other CGRs (7%). A majority of the terminal duplication structures consist of translocations (65%) followed by recombinant chromosomes (23%). Notably, 67% of de novo events occurred in the terminal duplication group in contrast with 17% observed in tandem duplications. RNAseq data from lymphoblastoid cell lines indicated that the MECP2 transcript quantity in MECP2 triplications is statistically different from all duplications, but not between other classes of genomic structures. We also observed a significant (p < 0.05) correlation (Pearson R = 0.6, Spearman = 0.63) between the log-transformed MECP2 RNA levels and MeCP2 protein levels, demonstrating that genomic aberrations spanning MECP2 lead to altered MECP2 RNA and MeCP2 protein levels. Genotype-phenotype analyses indicated a gradual worsening of phenotypic features, including overall survival, developmental levels, microcephaly, epilepsy, and genitourinary/eye abnormalities in the following order: tandem duplications, other CGRs, terminal duplications/translocations, and triplications encompassing MECP2. In aggregate, this combined analysis uncovers an interplay between MECP2 dosage, genomic rearrangement structure and phenotypic traits. Whereas the level of MeCP2 is a key determinant of the phenotype, the DNA rearrangement structure can contribute to clinical severity and disease expression variability. Employing this type of analytical approach will advance our understanding of the impact of genomic rearrangements on genomic disorders and may help guide more targeted therapeutic approaches.

Project description:BackgroundMECP2 Duplication Syndrome, also known as X-linked intellectual developmental disorder Lubs type (MRXSL; MIM: 300260), is a neurodevelopmental disorder caused by copy number gains spanning MECP2. Despite varying genomic rearrangement structures, including duplications and triplications, and a wide range of duplication sizes, no clear correlation exists between DNA rearrangement and clinical features. We had previously demonstrated that up to 38% of MRXSL families are characterized by complex genomic rearrangements (CGRs) of intermediate complexity (2 ≤ copy number variant breakpoints < 5), yet the impact of these genomic structures on regulation of gene expression and phenotypic manifestations have not been investigated.MethodsTo study the role of the genomic rearrangement structures on an individual's clinical phenotypic variability, we employed a comprehensive genomics, transcriptomics, and deep phenotyping analysis approach on 137 individuals affected by MRXSL. Genomic structural information was correlated with transcriptomic and quantitative phenotypic analysis using Human Phenotype Ontology (HPO) semantic similarity scores.ResultsDuplication sizes in the cohort ranging from 64.6 kb to 16.5 Mb were classified into four categories comprising of tandem duplications (48%), terminal duplications (22%), inverted triplications (20%), and other CGRs (10%). Most of the terminal duplication structures consist of translocations (65%) followed by recombinant chromosomes (23%). Notably, 65% of de novo events occurred in the Terminal duplication group in contrast with 17% observed in Tandem duplications. RNA-seq data from lymphoblastoid cell lines indicated that the MECP2 transcript quantity in MECP2 triplications is statistically different from all duplications, but not between other classes of genomic structures. We also observed a significant (p < 0.05) correlation (Pearson R = 0.6, Spearman p = 0.63) between the log-transformed MECP2 RNA levels and MECP2 protein levels, demonstrating that genomic aberrations spanning MECP2 lead to altered MECP2 RNA and MECP2 protein levels. Genotype-phenotype analyses indicated a gradual worsening of phenotypic features, including overall survival, developmental levels, microcephaly, epilepsy, and genitourinary/eye abnormalities in the following order: Tandem duplications, Other complex duplications, Terminal duplications/Translocations, and Triplications encompassing MECP2.ConclusionIn aggregate, this combined analysis uncovers an interplay between MECP2 dosage, genomic rearrangement structure and phenotypic traits. Whereas the level of MECP2 is a key determinant of the phenotype, the DNA rearrangement structure can contribute to clinical severity and disease expression variability. Employing this type of analytical approach will advance our understanding of the impact of genomic rearrangements on genomic disorders and may help guide more targeted therapeutic approaches.

Dataset Information

Predictive modeling provides insight into the clinical heterogeneity associated with TARS1 loss-of-function mutations.

Publications

Predictive modeling provides insight into the clinical heterogeneity associated with <i>TARS1</i> loss-of-function mutations.

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