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

Rebecca Meyer-Schuman, Allison R Cale, Jennifer A Pierluissi, Kira E Jonatzke,Young N Park,Guy M Lenk, Stephanie N Oprescu, Marina A Grachtchouk,Andrzej A Dlugosz, Asim A Beg,Miriam H Meisler,Anthony Antonellis

bioRxiv : the preprint server for biology(2024)

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摘要
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. SUMMARY STATEMENT:This study leverages an engineered, hypomorphic variant of threonyl-tRNA synthetase ( TARS1 ) to capture TARS1 -associated recessive phenotypes. This strategy revealed both known and previously unappreciated phenotypes, expanding the clinical heterogeneity associated with TARS1 and informing future genetic and clinical evaluations of patient populations.
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