Browsing by keyword "Quantitative Trait Loci"
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Ly6a Differential Expression in Blood-Brain Barrier Is Responsible for Strain Specific Central Nervous System Transduction Profile of AAV-PHP.BAdeno-associated virus (AAV) gene therapy for neurological diseases was revolutionized by the discovery that AAV9 crosses the blood-brain barrier (BBB) after systemic administration. Transformative results have been documented in various inherited diseases, but overall neuronal transduction efficiency is relatively low. The recent development of AAV-PHP.B with ∼60-fold higher efficiency than AAV9 in transducing the adult mouse brain was the major first step toward acquiring the ability to deliver genes to the majority of cells in the central nervous system (CNS). However, little is known about the mechanism utilized by AAV to cross the BBB, and how it may diverge across species. In this study, we show that AAV-PHP.B is ineffective for systemic CNS gene transfer in the inbred strains BALB/cJ, BALB/cByJ, A/J, NOD/ShiLtJ, NZO/HILtJ, C3H/HeJ, and CBA/J mice, but it is highly potent in C57BL/6J, FVB/NJ, DBA/2J, 129S1/SvImJ, and AKR/J mice and also the outbred strain CD-1. We used the power of classical genetics to uncover the molecular mechanisms AAV-PHP.B engages to transduce CNS at high efficiency, and by quantitative trait locus mapping we identify a 6 Mb region in chromosome 15 with an logarithm of the odds (LOD) score ∼20, including single nucleotide polymorphisms in the coding region of 9 different genes. Comparison of the publicly available data on the genome sequence of 16 different mouse strains, combined with RNA-seq data analysis of brain microcapillary endothelia, led us to conclude that the expression level of Ly6a is likely the determining factor for differential efficacy of AAV-PHP.B in transducing the CNS across different mouse strains.
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Using gene expression databases for classical trait QTL candidate gene discovery in the BXD recombinant inbred genetic reference population: mouse forebrain weightBACKGROUND: Successful strategies for QTL gene identification benefit from combined experimental and bioinformatic approaches. Unique design aspects of the BXD recombinant inbred line mapping panel allow use of archived gene microarray expression data to filter likely from unlikely candidates. This prompted us to propose a simple five-filter protocol for candidate nomination. To filter more likely from less likely candidates, we required candidate genes near to the QTL to have mRNA abundance that correlated with the phenotype among the BXD lines as well as differed between the parental lines C57BL/6J and DBA/2J. We also required verification of mRNA abundance by an independent method, and finally we required either differences in protein levels or confirmed DNA sequence differences. RESULTS: QTL mapping of mouse forebrain weight in 34 BXD RI lines found significant association on chromosomes 1 and 11, with each C57BL/6J allele increasing weight by more than half a standard deviation. The intersection of gene lists that were within +/- 10 Mb of the strongest associated location, that had forebrain mRNA abundance correlated with forebrain weight among the BXD, and that had forebrain mRNA abundance differing between C57BL/6J and DBA/2J, produced two candidates, Tnni1 (troponin 1) and Asb3 (ankyrin repeat and SOCS box-containing protein 3). Quantitative RT-PCR confirmed the direction of an increased expression in C57BL/6J genotype over the DBA/2J genotype for both genes, a difference that translated to a 2-fold difference in Asb3 protein. Although Tnni1 protein differences could not be confirmed, a 273 bp indel polymorphism was discovered 1 Kb upstream of the transcription start site. CONCLUSION: Delivery of well supported candidate genes following a single quantitative trait locus mapping experiment is difficult. However, by combining available gene expression data with QTL mapping, we illustrated a five-filter protocol that nominated Asb3 and Tnni1 as candidates affecting increased mouse forebrain weight. We recommend our approach when (1) investigators are working with phenotypic differences between C57BL/6J and DBA/2J, and (2) gene expression data are available on http://www.genenetwork.org that relate to the phenotype of interest. Under these circumstances, measurement of the phenotype in the BXD lines will likely also deliver excellent candidate genes.
