Predicting the functional effect of compound heterozygous genotypes from large scale variant effect maps.
bioRxiv
; 2023 Jan 27.
Article
em En
| MEDLINE
| ID: mdl-36711904
Background: Pathogenic variants in PHGDH, PSAT1 , and PSPH cause a set of rare, autosomal recessive diseases known as serine biosynthesis defects. Serine biosynthesis defects present in a broad phenotypic spectrum that includes, at the severe end, Neu-Laxova syndrome, a lethal multiple congenital anomaly disease, intermediately in the form of infantile serine biosynthesis defects with severe neurological manifestations and growth deficiency, and at the mild end, as childhood disease with intellectual disability. However, because L-serine supplementation, especially if started early, can ameliorate and in some cases even prevent symptoms, knowledge of pathogenic variants is highly actionable. Methods: Recently, our laboratory established a yeast-based assay for human PSAT1 function. We have now applied it at scale to assay the functional impact of 1,914 SNV-accessible amino acid substitutions. In addition to assaying the functional impact of individual variants in yeast haploid cells, we can assay pairwise combinations of PSAT1 alleles that recapitulate human genotypes, including compound heterozygotes, in yeast diploids. Results: Results of our assays of individual variants (in haploid yeast cells) agree well with clinical interpretations and protein structure-function relationships, supporting the use of our data as functional evidence under the ACMG interpretation guidelines. Results from our diploid assay successfully distinguish patient genotypes from those of healthy carriers and agree well with disease severity. Finally, we present a linear model that uses individual allele measurements (in haploid yeast cells) to accurately predict the biallelic function (in diploid yeast cells) of ~ 1.8 million allele combinations corresponding to potential human genotypes. Conclusions: Taken together, our work provides an example of how large-scale functional assays in model systems can be powerfully applied to the study of a rare disease.
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Base de dados:
MEDLINE
Tipo de estudo:
Guideline
/
Prognostic_studies
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Risk_factors_studies
Idioma:
En
Revista:
BioRxiv
Ano de publicação:
2023
Tipo de documento:
Article