Non-coding-regulatory regions of human brain genes delineated by bacterial artificial chromosome knock-in mice
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Published:2013-10-14
Issue:1
Volume:11
Page:
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ISSN:1741-7007
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Container-title:BMC Biology
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language:en
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Short-container-title:BMC Biol
Author:
Schmouth Jean-François,Castellarin Mauro,Laprise Stéphanie,Banks Kathleen G,Bonaguro Russell J,McInerny Simone C,Borretta Lisa,Amirabbasi Mahsa,Korecki Andrea J,Portales-Casamar Elodie,Wilson Gary,Dreolini Lisa,Jones Steven JM,Wasserman Wyeth W,Goldowitz Daniel,Holt Robert A,Simpson Elizabeth M
Abstract
Abstract
Background
The next big challenge in human genetics is understanding the 98% of the genome that comprises non-coding DNA. Hidden in this DNA are sequences critical for gene regulation, and new experimental strategies are needed to understand the functional role of gene-regulation sequences in health and disease. In this study, we build upon our HuGX ('high-throughput human genes on the X chromosome’) strategy to expand our understanding of human gene regulation in vivo.
Results
In all, ten human genes known to express in therapeutically important brain regions were chosen for study. For eight of these genes, human bacterial artificial chromosome clones were identified, retrofitted with a reporter, knocked single-copy into the Hprt locus in mouse embryonic stem cells, and mouse strains derived. Five of these human genes expressed in mouse, and all expressed in the adult brain region for which they were chosen. This defined the boundaries of the genomic DNA sufficient for brain expression, and refined our knowledge regarding the complexity of gene regulation. We also characterized for the first time the expression of human MAOA and NR2F2, two genes for which the mouse homologs have been extensively studied in the central nervous system (CNS), and AMOTL1 and NOV, for which roles in CNS have been unclear.
Conclusions
We have demonstrated the use of the HuGX strategy to functionally delineate non-coding-regulatory regions of therapeutically important human brain genes. Our results also show that a careful investigation, using publicly available resources and bioinformatics, can lead to accurate predictions of gene expression.
Publisher
Springer Science and Business Media LLC
Subject
Cell Biology,Developmental Biology,Plant Science,General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,Physiology,Ecology, Evolution, Behavior and Systematics,Structural Biology,Biotechnology
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