In:
Alcoholism: Clinical and Experimental Research, Wiley, Vol. 38, No. 12 ( 2014-12), p. 2915-2924
Abstract:
Data from C57BL/6J (B6) × DBA/2J (D2) F 2 intercrosses (B6xD2 F 2 ), standard and recombinant inbred strains, and heterogeneous stock mice indicate that a reciprocal (or inverse) genetic relationship exists between alcohol consumption and withdrawal severity. Furthermore, some genetic studies have detected reciprocal quantitative trait loci ( QTL s) for these traits. We used a novel mouse model developed by simultaneous selection for both high alcohol consumption/low withdrawal and low alcohol consumption/high withdrawal and analyzed the gene expression and genome‐wide genotypic differences. Methods Randomly chosen third selected generation (S 3 ) mice ( N = 24/sex/line), bred from a B6xD2 F 2 , were genotyped using the Mouse Universal Genotyping Array, which provided 2,760 informative markers. QTL analysis used a marker‐by‐marker strategy with the threshold for a significant log of the odds ( LOD ) set at 10. Gene expression in the ventral striatum was measured using the Illumina Mouse 8.2 array. Differential gene expression and the weighted gene co‐expression network analysis ( WGCNA ) were implemented. Results Significant QTLs for consumption/withdrawal were detected on chromosomes (Chr) 2, 4, 9, and 12. A suggestive QTL mapped to Chr 6. Some of the QTLs overlapped with known QTLs mapped for 1 of the traits individually. One thousand seven hundred and forty‐five transcripts were detected as being differentially expressed between the lines; there was some overlap with known withdrawal genes (e.g., Mpdz ) located within QTL regions. WGCNA revealed several modules of co‐expressed genes showing significant effects in both differential expression and intramodular connectivity; a module richly annotated with kinase‐related annotations was most affected. Conclusions Marked effects of selection on expression and network structure were detected. QTLs overlapping with differentially expressed genes on Chr 2 (distal) and 4 suggest that these are cis‐eQTLs (Chr 2: Kif3b , Kcnq2 ; Chr 4: Mpdz , Snapc3 ). Other QTLs identified were on Chr 2 (proximal), 9, and 12. Network results point to involvement of kinase‐related mechanisms and outline the need for further efforts such as interrogation of noncoding RNAs.
Type of Medium:
Online Resource
ISSN:
0145-6008
,
1530-0277
DOI:
10.1111/acer.2014.38.issue-12
Language:
English
Publisher:
Wiley
Publication Date:
2014
detail.hit.zdb_id:
2046886-6
detail.hit.zdb_id:
3167872-5
SSG:
15,3
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