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1.
Int J Mol Sci ; 24(11)2023 May 24.
Artículo en Inglés | MEDLINE | ID: mdl-37298131

RESUMEN

Understanding how genetic variation affects phenotypes represents a major challenge, particularly in the context of human disease. Although numerous disease-associated genes have been identified, the clinical significance of most human variants remains unknown. Despite unparalleled advances in genomics, functional assays often lack sufficient throughput, hindering efficient variant functionalization. There is a critical need for the development of more potent, high-throughput methods for characterizing human genetic variants. Here, we review how yeast helps tackle this challenge, both as a valuable model organism and as an experimental tool for investigating the molecular basis of phenotypic perturbation upon genetic variation. In systems biology, yeast has played a pivotal role as a highly scalable platform which has allowed us to gain extensive genetic and molecular knowledge, including the construction of comprehensive interactome maps at the proteome scale for various organisms. By leveraging interactome networks, one can view biology from a systems perspective, unravel the molecular mechanisms underlying genetic diseases, and identify therapeutic targets. The use of yeast to assess the molecular impacts of genetic variants, including those associated with viral interactions, cancer, and rare and complex diseases, has the potential to bridge the gap between genotype and phenotype, opening the door for precision medicine approaches and therapeutic development.


Asunto(s)
Neoplasias , Saccharomyces cerevisiae , Humanos , Saccharomyces cerevisiae/genética , Genómica , Proteoma/genética , Fenotipo
2.
PLoS Pathog ; 17(9): e1009919, 2021 09.
Artículo en Inglés | MEDLINE | ID: mdl-34543356

RESUMEN

Viral infections are known to hijack the transcription and translation of the host cell. However, the extent to which viral proteins coordinate these perturbations remains unclear. Here we used a model system, the human T-cell leukemia virus type 1 (HTLV-1), and systematically analyzed the transcriptome and interactome of key effectors oncoviral proteins Tax and HBZ. We showed that Tax and HBZ target distinct but also common transcription factors. Unexpectedly, we also uncovered a large set of interactions with RNA-binding proteins, including the U2 auxiliary factor large subunit (U2AF2), a key cellular regulator of pre-mRNA splicing. We discovered that Tax and HBZ perturb the splicing landscape by altering cassette exons in opposing manners, with Tax inducing exon inclusion while HBZ induces exon exclusion. Among Tax- and HBZ-dependent splicing changes, we identify events that are also altered in Adult T cell leukemia/lymphoma (ATLL) samples from two independent patient cohorts, and in well-known cancer census genes. Our interactome mapping approach, applicable to other viral oncogenes, has identified spliceosome perturbation as a novel mechanism coordinated by Tax and HBZ to reprogram the transcriptome.


Asunto(s)
Factores de Transcripción con Cremalleras de Leucina de Carácter Básico/metabolismo , Productos del Gen tax/metabolismo , Infecciones por HTLV-I/metabolismo , Leucemia-Linfoma de Células T del Adulto/virología , Proteínas de los Retroviridae/metabolismo , Células HEK293 , Infecciones por HTLV-I/etiología , Virus Linfotrópico T Tipo 1 Humano , Humanos , Células Jurkat , Empalme del ARN , ARN Mensajero , Factor de Empalme U2AF/metabolismo
3.
Nature ; 580(7803): 402-408, 2020 04.
Artículo en Inglés | MEDLINE | ID: mdl-32296183

RESUMEN

Global insights into cellular organization and genome function require comprehensive understanding of the interactome networks that mediate genotype-phenotype relationships1,2. Here we present a human 'all-by-all' reference interactome map of human binary protein interactions, or 'HuRI'. With approximately 53,000 protein-protein interactions, HuRI has approximately four times as many such interactions as there are high-quality curated interactions from small-scale studies. The integration of HuRI with genome3, transcriptome4 and proteome5 data enables cellular function to be studied within most physiological or pathological cellular contexts. We demonstrate the utility of HuRI in identifying the specific subcellular roles of protein-protein interactions. Inferred tissue-specific networks reveal general principles for the formation of cellular context-specific functions and elucidate potential molecular mechanisms that might underlie tissue-specific phenotypes of Mendelian diseases. HuRI is a systematic proteome-wide reference that links genomic variation to phenotypic outcomes.


Asunto(s)
Proteoma/metabolismo , Espacio Extracelular/metabolismo , Humanos , Especificidad de Órganos , Mapeo de Interacción de Proteínas
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