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John Belknap

Publications and source records attributed to John Belknap.

4 recordsLinked to original sources

Further studies on using multiple-cross mapping (MCM) to map quantitative trait loci.

We have completed whole-genome scans for quantitative trait loci (QTLs) associated with acute ethanol-induced activation in the six F(2) intercrosses that can be formed from the C57BL/6J (B6), DBA/2J (D2) , BALB/cJ (C), and LP/J (LP) inbred strains. The goal was to test the hypothesis that given the relatively simple structure of the laboratory mouse genome, the same QTLs will be detected in multiple crosses which in turn will provide support for the strategy of multiple-cross mapping (MCM). QTLs with LOD scores greater than 4 were detected on Chrs 1, 2, 3, 8, 9, 13, 14, and 16. Only for the QTL on distal Chr 1 was there convincing evidence that the same or at least a very similar QTL was detected in multiple crosses. We also mapped the Chr 2 QTL directly in heterogeneous stock (HS) animals derived from the four inbred strains. At G(19) the QTL was mapped to an approximately 3-Mbp interval and this interval was associated with a haplotype block with a largely biallelic structure: B6-L:C-D2. We conclude that mapping in HS animals not only provides significantly greater QTL resolution, at least in some cases it provides significantly more information about the QTL haplotype structure.

Animals↗

Candidate genes and their regulatory elements: alcohol preference and tolerance.

QTL analysis of behavioral traits and mouse brain gene expression studies were combined to identify candidate genes involved in the traits of alcohol preference and acute functional alcohol tolerance. The systematic application of normalization and statistical analysis of differential gene expression, behavioral and expression QTL location, and informatics methodologies resulted in identification of 8 candidate genes for the trait of alcohol preference and 22 candidate genes for acute functional tolerance. Pathway analysis, combined with clustering by ontology, indicated the importance of transcriptional regulation and DNA and protein binding elements in the acute functional tolerance trait, and protein kinases and intracellular signal transduction elements in the alcohol preference trait. A rudimentary search for transcription control elements that could indicate coregulation of the panels of candidate genes produced modest results, implicating SMAD-3 in the regulation of four of the eight candidate genes for alcohol preference. However, the realization of the many caveats related to transcription factor binding site analysis, and attempts to correlate between transcription factor binding and function, forestalled any definitive global analysis of transcriptional control of differentially expressed candidate genes.

Alcohol Drinking↗

DNA microarray and proteomic strategies for understanding alcohol action.

This article summarizes the proceedings of a symposium presented at the 2005 annual meeting of the Research Society on Alcoholism in Santa Barbara, California. The organizer was James M. Sikela, and he and Michael F. Miles were chairs. The presentations were (1) Genomewide Surveys of Gene Copy Number Variation in Human and Mouse: Implications for the Genetics of Alcohol Action, by James M. Sikela; (2) Regional Differences in the Regulation of Brain Gene Expression: Relevance to the Detection of Genes Associated with Alcohol-Related Traits, by Robert Hitzemann; (3) Identification of Ethanol Quantitative Trait Loci Candidate Genes by Expression Profiling in Inbred Long Sleep/Inbred Short Sleep Congenic Mice, by Robnet T. Kerns; and (4) Quantitative Proteomic Analysis of AC7-Modified Mice, by Kathleen J. Grant.

Alcoholism↗

On the integration of alcohol-related quantitative trait loci and gene expression analyses.

BACKGROUND: Quantitative trait loci (QTLs) have been detected for a wide variety of ethanol-related phenotypes, including acute and chronic ethanol withdrawal, acute locomotor activation, and ethanol preference. This study was undertaken to determine whether the process of moving from QTL to quantitative trait gene (QTG) could be accelerated by the integration of functional genomics (gene expression) into the analysis strategy. METHODS: Six ethanol-related QTLs, all detected in C57BL/6J and DBA/2J intercrosses were entered into the analysis. Each of the QTLs had been confirmed in independent genetic models at least once; the cumulative probabilities for QTL existence ranged from 10 to 10. Brain gene expression data for the C57BL/6 and DBA/2 strains (n = 6 per strain) and an F2 intercross sample (n = 56) derived from these strains were obtained by using the Affymetrix U74Av2 and 430A arrays; additional data with the U74Av2 array were available for the extended amygdala, dorsomedial striatum, and hippocampus. Low-level analysis was performed by using multiple methods to determine the likelihood that a transcript was truly differentially expressed. For the 430A array data, the F2 sample was used to determine which of the differentially expressed transcripts within the QTL intervals were cis-regulated and, thus, strong candidates for QTGs. RESULTS: Within the 6 QTL intervals, 39 transcripts (430A array) were identified as being highly likely to be differentially expressed between the C57BL/6 and DBA/2 strains at a false discovery rate of 0.01 or better. Twenty-eight of these transcripts showed significant (logarithm of odds > or =3.6) to highly significant (logarithm of odds >7) cis-regulation. The process correctly detected Mpdz (chromosome 4) as a candidate QTG for acute withdrawal. CONCLUSIONS: Although improvements are needed in the expression databases, the integration of QTL and gene expression analyses seems to have potential as a high-throughput strategy for moving from QTL to QTG.

Alcohol Drinking↗