Genomic regions controlling corticosterone levels in rats
Marc N. PotenzaEdward S. BrodkinBina JoeXingguang LuοElaine F. RemmersRonald L. WilderEric J. NestlerJoel Gelernter
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Corticosterone
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Trait
Genetic analysis of polygenic traits in rats and mice has been very useful for finding the approximate chromosomal locations of the genes causing quantitative phenotypic variation, so-called quantitative trait loci (QTL). Further localization of the causative genes and their ultimate identification has, however, proven to be slow and frustrating. A major technique for gene identification in such models utilizes series of congenic strains with progressively smaller chromosomal segments introgressed from one inbred strain into another inbred strain. Under the assumption that a single causative locus underlies a QTL, nested series of congenic strains were earlier suggested as an appropriate configuration for the congenic strains. It is now known that most QTL are compound, that is, the QTL signal is caused by clusters of loci where alleles exert positive, negative, and interactive effects on the trait in a given strain comparison. It is argued that in this situation an initial series of nonoverlapping contiguous congenic strains over a relatively large chromosomal region will lead to a better appreciation of the underlying complexity of the QTL and therefore more rapid gene identification. Examples from the literature where this strategy would be helpful, as well as a case where it would be potentially counterproductive, are given.
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Abstract Niddm1i, a 16-Mb locus within the major diabetes QTL in the diabetic GK rat, causes impaired glucose tolerance in the congenic NIDDM1I strain. Niddm1i is homologous to both human and mouse regions linked with type 2 diabetes susceptibility. We employed multiple QTL analyses of congenic F2 progeny selected for one recombination event within Niddm1i combined with characterization of subcongenic strains. Fine mapping located one hyperglycemia locus within 700 kb (Niddm1i4, P = 5 × 10−6). Two adjacent loci were also detected, and the GK allele at Niddm1i2 (500 kb) showed a glucose-raising effect, whereas it had a glucose-lowering effect at Niddm1i3 (400 kb). Most proximally, Niddm1i1 (800 kb) affecting body weight was identified. Experimental data from subcongenics supported the four loci. Sorcs1, one of the two known diabetes susceptibility genes in the region, resides within Niddm1i3, while Tcf7l2 maps outside all four loci. Multiple-marker QTL analysis incorporating the effect of cosegregating QTL as cofactors together with genetically selected progeny can remarkably enhance resolution of QTL. The data demonstrate that the species-conserved Niddm1i is a composite of at least four QTL affecting type 2 diabetes susceptibility and that two adjacent QTL (Niddm1i2GK and Niddm1i3GK) act in opposite directions.
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Recently we have explored the use of knockout/congenic mouse strains for isolating and mapping quantitative trait loci (QTLs). Because most knockout strains have been bred to be B6.129 congenic strains, they can be used to test for QTLs in the targeted chromosomal area as long as there is a genetic difference between B6 and 129. Thus, we have tested a number of knockout/congenic strains in a series of behavioral tests in which mouse performance has a significant genetic component. We have also developed a breeding scheme for distinguishing the effects of background flanking genes from the targeted ablation. In screening several knockout/congenics, we have found at least one that harbors a behavioral QTL in the 129 chromosomal segment. The position of this QTL was confirmed subsequently by several F1 crosses.
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Candidate gene
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Chromosome 4
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We analyzed the genetic basis of morphological differences between two wild species of teosinte (Zea diploperennis and Z. mays ssp. parviglumis), which are relatives of maize. These two species differ in a number of taxonomically important traits including the structure of the tassel (male inflorescence), which is the focus of this report. To investigate the genetic inheritance of six tassel traits, quantitative trait locus (QTL) mapping with 95 RFLP markers was employed on a population of 425 F2 plants. Each trait was analyzed by interval mapping (IM) and composite interval mapping (CIM) to identify and characterize the QTL controlling the differences in tassel morphology. We detected two to eight QTL for each trait. In total, 30 QTL with IM and 33 QTL with CIM were found for tassel morphology. QTL for several of the traits mapped near each other, suggesting pleiotropy and/or linkage of QTL. The QTL showed small to moderate magnitudes of effect. No QTL of exceptionally large effect were found as seen under domestication and in the case of some other natural species. Thus, the model involving major QTL of large effect seems not to apply to the traits and species analyzed. A mixture of QTL with positive and negative allelic effects was found for most tassel traits and may suggest a history of periodic changes in the direction of selection during the divergence of Z. diploperennis and Z. mays ssp. parviglumis or fixation of QTL alleles by random genetic drift rather than selection.Corresponding Editor: J. Conner
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Inbred strain
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Family-based QTL mapping
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The genetic architecture of multifactorial traits such as obesity has been poorly understood. Quantitative trait locus (QTL) analysis is widely used to localize loci affecting multifactorial traits on chromosomal regions. However, large confidence intervals and small phenotypic effects of identified QTLs and closely linked loci are impeding the identification of causative genes that underlie the QTLs. Here we developed five subcongenic mouse strains with overlapping and non-overlapping wild-derived genomic regions from an F2 intercross of a previously developed congenic strain, B6.Cg-Pbwg1, and its genetic background strain, C57BL/6J (B6). The subcongenic strains developed were phenotyped on low-fat standard chow and a high-fat diet to fine-map a previously identified obesity QTL. Microarray analysis was performed with Affymetrix GeneChips to search for candidate genes of the QTL. The obesity QTL was physically mapped to an 8.8-Mb region of mouse chromosome 2. The wild-derived allele significantly decreased white fat pad weight, body weight and serum levels of glucose and triglyceride. It was also resistant to the high-fat diet. Among 29 genes residing within the 8.8-Mb region, Gpd2, Upp2, Acvr1c, March7 and Rbms1 showed great differential expression in livers and/or gonadal fat pads between B6.Cg-Pbwg1 and B6 mice. The wild-derived QTL allele prevented obesity in both mice fed a low-fat standard diet and mice fed a high-fat diet. This finding will pave the way for identification of causative genes for obesity. A further understanding of this unique QTL effect at genetic and molecular levels may lead to the discovery of new biological and pathologic pathways associated with obesity.
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Candidate gene
Family-based QTL mapping
Positional cloning
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Genetic architecture
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