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1.
PLoS One ; 14(11): e0225206, 2019.
Artículo en Inglés | MEDLINE | ID: mdl-31725765

RESUMEN

The engineered AAV-PHP.B family of adeno-associated virus efficiently delivers genes throughout the mouse central nervous system. To guide their application across disease models, and to inspire the development of translational gene therapy vectors for targeting neurological diseases in humans, we sought to elucidate the host factors responsible for the CNS tropism of the AAV-PHP.B vectors. Leveraging CNS tropism differences across 13 mouse strains, we systematically determined a set of genetic variants that segregate with the permissivity phenotype, and rapidly identified LY6A as an essential receptor for the AAV-PHP.B vectors. Interfering with LY6A by CRISPR/Cas9-mediated Ly6a disruption or with blocking antibodies reduced transduction of mouse brain endothelial cells by AAV-PHP.eB, while ectopic expression of Ly6a increased AAV-PHP.eB transduction of HEK293T and CHO cells by 30-fold or more. Importantly, we demonstrate that this newly discovered mode of AAV binding and transduction can occur independently of other known AAV receptors. These findings illuminate the previously reported species- and strain-specific tropism characteristics of the AAV-PHP.B vectors and inform ongoing efforts to develop next-generation AAV vehicles for human CNS gene therapy.


Asunto(s)
Barrera Hematoencefálica/metabolismo , Técnicas de Transferencia de Gen , Transducción Genética , Transgenes , Animales , Antígenos Ly/química , Antígenos Ly/genética , Encéfalo/metabolismo , Línea Celular , Dependovirus/genética , Variación Genética , Vectores Genéticos/administración & dosificación , Vectores Genéticos/genética , Humanos , Proteínas de la Membrana/química , Proteínas de la Membrana/genética , Ratones , Neuronas/metabolismo , Tropismo
2.
Nat Methods ; 15(8): 595-597, 2018 08.
Artículo en Inglés | MEDLINE | ID: mdl-30013044

RESUMEN

Existing benchmark datasets for use in evaluating variant-calling accuracy are constructed from a consensus of known short-variant callers, and they are thus biased toward easy regions that are accessible by these algorithms. We derived a new benchmark dataset from the de novo PacBio assemblies of two fully homozygous human cell lines, which provides a relatively more accurate and less biased estimate of small-variant-calling error rates in a realistic context.


Asunto(s)
Bases de Datos Genéticas/estadística & datos numéricos , Variación Genética , Algoritmos , Benchmarking , Línea Celular Tumoral , Bases de Datos Genéticas/normas , Diploidia , Femenino , Genoma Humano , Homocigoto , Humanos , Mola Hidatiforme/genética , Embarazo , Biología Sintética , Neoplasias Uterinas/genética , Secuenciación Completa del Genoma/estadística & datos numéricos
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