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Detección y análisis de variaciones estructurales complejas en los genomas humanos entre poblaciones y en los cerebros de donantes con trastornos psiquiátricos

Bo Zhou ¹, Joseph G Arthur ², Hanmin Guo ³

¹Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA; Maternal and Child Health Research Institute, Stanford University School of Medicine, Stanford, CA 94305, USA.
²Department of Statistics, Stanford University, Stanford, CA 94305, USA.
³Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA; Maternal and Child Health Research Institute, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Statistics, Stanford University, Stanford, CA 94305, USA; Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA.
⁴School of Computer Science and Engineering, Pusan National University, Busan 46241, South Korea.
⁵Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA.
⁶Department of Genetics, Stanford University, Stanford, CA 94305, USA.
⁷Department of Genetics, Stanford University, Stanford, CA 94305, USA; Department of Computer Science, Stanford University, Stanford, CA 94305, USA.
⁸Division of Oncology, Department of Medicine, Stanford University, Stanford, CA 94305, USA.
⁹Department of Pathology, Stanford University, Stanford, CA 94305, USA.
¹⁰Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Genetics and Genomics Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
¹¹Department of Statistics, Stanford University, Stanford, CA 94305, USA; Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA.
¹²Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA.
¹³Department of Statistics, Stanford University, Stanford, CA 94305, USA; Department of Statistics, Pennsylvania State University, University Park, PA 16802, USA; Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA 16802, USA.
¹⁴School of Computer Science and Engineering, Pusan National University, Busan 46241, South Korea; Center for Artificial Intelligence Research, Pusan National University, Busan 46241, South Korea.
¹⁵Department of Genetics, Stanford University, Stanford, CA 94305, USA; Maternal and Child Health Research Institute, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA; Department of Pathology, Stanford University, Stanford, CA 94305, USA.
¹⁶Institute of Mathematics and Informatics, Bulgarian Academy of Sciences, Sofia 1113, Bulgaria.
¹⁷Department of Biology, American University of Beirut, Beirut 11-0236, Lebanon.
¹⁸Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Genetics and Genomics Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY 10468, USA; Mental Illness Research Education and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, NY 10468, USA.

⁰Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA; Maternal and Child Health Research Institute, Stanford University School of Medicine, Stanford, CA 94305, USA.

Cell +

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1 de octubre de 2024

Ver abstracta en PubMed

Resumen

Las variaciones estructurales complejas (cxSV) son una fuente significativa de diversidad genética humana. Nuestro nuevo método, ARC-SV, detecta con precisión los cxSV, revelando su papel en la evolución de genes neuronales y trastornos psiquiátricos.

Área De La Ciencia

La genómica
La genética humana
La neurociencia

Sus Antecedentes

Las variaciones estructurales complejas (cxSV) son difíciles de detectar, lo que limita su estudio en los análisis del genoma.
La comprensión de los cxSV es crucial para comprender la diversidad genética humana y la etiología de la enfermedad.

Objetivo Del Estudio

Desarrollar y validar el ARC-SV, un nuevo método para la detección y reconstrucción precisas del cxSV.
Investigar el papel de los cxSV en la variación y evolución genética humana.
Explorar la asociación de los cxSV con la expresión génica, la accesibilidad de la cromatina y los trastornos psiquiátricos en el cerebro humano.

Principales Métodos

Desarrollo de ARC-SV, una herramienta de detección probabilística y basada en el aprendizaje automático.
Aplicación de ARC-SV para analizar 4.262 genomas humanos de diversas poblaciones.
Multiómica de un solo núcleo (expresión génica, accesibilidad de la cromatina) en el tejido cerebral humano postmortem.
Integración de los datos de cxSV con el estudio de asociación genómica (GWAS) de alelos de riesgo para trastornos psiquiátricos.

Principales Resultados

ARC-SV permite la detección y reconstrucción precisas de los cxSV a partir de datos genómicos estándar.
Los cxSV representan una fuente significativa de variación genética humana natural, en particular las variantes raras en los genes neuronales.
Los cxSV están relacionados con la expresión génica diferencial y la accesibilidad de la cromatina en regiones y tipos de células cerebrales humanas.
Los cxSV en casos psiquiátricos muestran enriquecimiento para la vinculación con alelos de riesgo GWAS psiquiátricos y están asociados con una disminución de la expresión génica en regiones cerebrales / tipos de células específicas.

Conclusiones

Los cxSV son un componente sustancial y hasta ahora subestimado de la diversidad genética humana.
El ARC-SV es una herramienta eficaz para la caracterización de los cxSV en grandes cohortes.
Los cxSV juegan un papel en la evolución del cerebro humano y están implicados en la patología molecular de los trastornos neuropsiquiátricos.

Palabras clave:

El ARC-SV GTEx (en inglés) Psicología Variación estructural compleja CxSVs La evolución del hombre genética de poblaciones genética psiquiátrica multiómica de una sola célula Variación estructural

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