Biomedical subjects

Renhua Li

Publications and source records attributed to Renhua Li.

At least 19 recordsLinked to original sources

PubMed2006

Discovery of potent, efficacious, and orally bioavailable inhibitors of blood coagulation factor Xa with neutral P1 moieties.

The bicyclic dihydropyrazolopyridinone scaffold allowed for incorporation of multiple P1 moieties with subnanomolar binding affinities for blood coagulation factor Xa. The compound 3-[6-(2'-dimethylaminomethyl-biphenyl-4-yl)-7-oxo-3-trifluoro-methyl-4,5,6,7-tetrahydro-pyrazolo[3,4-c]pyridine-l-yl]-benzamide 6d shows good fXa potency, selectivity, in vivo efficacy and oral bioavailability. Compound 6d was selected for further pre-clinical evaluations.

Administration, Oral↗

PubMed2006

Complex genetic architecture revealed by analysis of high-density lipoprotein cholesterol in chromosome substitution strains and F2 crosses.

Intercrosses between inbred lines provide a traditional approach to analysis of polygenic inheritance in model organisms. Chromosome substitution strains (CSSs) have been developed as an alternative to accelerate the pace of gene identification in quantitative trait mapping. We compared a classical intercross and three CSS intercrosses to examine the genetic architecture underlying plasma high-density lipoprotein cholesterol (HDL) levels in the C57BL/6J (B) and A/J (A) mouse strains. The B x A intercross revealed significant quantitative trait loci (QTL) for HDL on chromosomes 1, 4, 8, 15, 17, 18, and 19. A CSS survey revealed that many have significantly different HDL levels compared to the background strain B, including chromosomes with no significant QTL in the intercross and, in some cases (CSS-1, CSS-17), effects that are opposite to those observed in the B x A intercross population. Intercrosses between B and three CSSs (CSS-3, CSS-11, and CSS-8) revealed significant QTL but with some unexpected differences from the B x A intercross. Our inability to predict the results of CSS intercrosses suggests that additional complexity will be revealed by further crosses and that the CSS mapping strategy should be viewed as a complement to, rather than a replacement for, classical intercross mapping.

Animals↗

PubMed2006

Genetic analysis of the stress-responsive adrenocortical axis.

The underlying genetic components contributing to individual variability in functions of the stress-responsive hypothalamic-pituitary-adrenal (HPA) axis are poorly understood. To determine genetic loci mediating three aspects of the adrenocortical function, we conducted a quantitative trait locus (QTL) analysis in the segregating F2 generation of a Wistar Kyoto (WKY) x Fischer 344 (F344) cross, two inbred rat strains that differ in several HPA axis measures. The following three components of adrenocortical function are known to be regulated by different mechanisms that are mediated via suprahypothalamic, hypothalamic, pituitary, and intra-adrenal influences: basal plasma corticosterone (Cort) levels, plasma Cort response to a 10-min restraint stress, and adrenal weight. Genome scans identified a complex genetic architecture for the basal Cort phenotype, including sex and maternal lineage effects. Pairwise interactions were also identified for this trait. We identified three significant and two suggestive QTLs for stress Cort, along with two pairs of interacting loci for this trait. Four highly significant and two suggestive loci were identified for adrenal weight, with no interacting loci. In contrast to basal Cort, no sex- or lineage-dependent QTL were identified for stress Cort or adrenal weight, despite the large sex differences in these phenotypes. We identified three nucleotide alterations in an obvious candidate gene mapped to the most significant QTL for stress Cort, Cort-binding globulin (CBG), one of which is known to alter CBG binding. This analysis confirms that three separate traits regulated by the HPA axis are controlled by multiple, but mainly nonoverlapping, QTLs.

Adrenal Glands↗

PubMed2006

Structural model analysis of multiple quantitative traits.

We introduce a method for the analysis of multilocus, multitrait genetic data that provides an intuitive and precise characterization of genetic architecture. We show that it is possible to infer the magnitude and direction of causal relationships among multiple correlated phenotypes and illustrate the technique using body composition and bone density data from mouse intercross populations. Using these techniques we are able to distinguish genetic loci that affect adiposity from those that affect overall body size and thus reveal a shortcoming of standardized measures such as body mass index that are widely used in obesity research. The identification of causal networks sheds light on the nature of genetic heterogeneity and pleiotropy in complex genetic systems.

Adipose Tissue↗

PubMed2006

QTL mapping for genetic determinants of lipoprotein cholesterol levels in combined crosses of inbred mouse strains.

To identify additional loci that influence lipoprotein cholesterol levels, we performed quantitative trait locus (QTL) mapping in offspring of PERA/EiJxI/LnJ and PERA/EiJxDBA/2J intercrosses and in a combined data set from both crosses after 8 weeks of consumption of a high fat-diet. Most QTLs identified were concordant with homologous chromosomal regions that were associated with lipoprotein levels in human studies. We detected significant new loci for HDL cholesterol levels on chromosome (Chr) 5 (Hdlq34) and for non-HDL cholesterol levels on Chrs 15 (Nhdlq9) and 16 (Nhdlq10). In addition, the analysis of combined data sets identified a QTL for HDL cholesterol on Chr 17 that was shared between both crosses; lower HDL cholesterol levels were conferred by strain PERA. This QTL colocalized with a shared QTL for cholesterol gallstone formation detected in the same crosses. Haplotype analysis narrowed this QTL, and sequencing of the candidate genes Abcg5 and Abcg8 confirmed shared alleles in strains I/LnJ and DBA/2J that differed from the alleles in strain PERA/EiJ. In conclusion, our analysis furthers the knowledge of genetic determinants of lipoprotein cholesterol levels in inbred mice and substantiates the hypothesis that polymorphisms of Abcg5/Abcg8 contribute to individual variation in both plasma HDL cholesterol levels and susceptibility to cholesterol gallstone formation.

Alleles↗

PubMed2006

Femur mechanical properties in the F2 progeny of an NZB/B1NJ x RF/J cross are regulated predominantly by genetic loci that regulate bone geometry.

UNLABELLED: Genetic analysis of an NZB/B1NJ x RF/J cross has identified QTLs for femur mechanical, geometric, and densitometric phenotypes. Most mechanical QTLs were associated with geometric QTLs, strongly suggesting common genetic regulation. INTRODUCTION: Previous studies have shown that bone architecture and BMD are important factors affecting bone strength, and both are genetically regulated. We conducted genetic analyses for loci regulating femur mechanical properties, geometric properties, and BMD in a cohort of F2 mice derived from intercross matings of (NZB/B1NJ x RF/J)F1 parents. MATERIALS AND METHODS: Femurs were isolated from 662 10-week-old females. Mechanical properties were determined for a femur from each animal by three-point bending. Geometric properties and volumetric BMD (vBMD) were determined by pQCT. Genotype data were obtained by PCR assays for polymorphic markers carried in the genomic DNA of each mouse. Genome-wide scans were carried out for co-segregation of genetic marker data with values from 23 different phenotypes. Quantitative trait loci (QTLs) were identified for mechanical, geometric, and mineral density phenotypes. RESULTS: QTLs for many phenotypes were significantly refined by covariate analyses using body weight and femur length. Major QTLs for mechanical and geometric phenotypes were found on chromosomes 5, 7, 9, 11, and 12. Nine chromosomal locations were identified with mechanical QTLs and 17 locations with one or more geometric QTLs. The significance of five mechanical and nine geometric QTLs was affected by the inclusion of covariates. These changes included both decreases and increases in significance. The QTLs on chromosomes 5 and 12 were decreased by inclusion of the covariates in the analysis, but QTLs on 7 and 11 were unaffected. Mechanical QTLs were almost always associated with geometric QTLs and less commonly (two of six) with vBMD QTLs. CONCLUSIONS: Genetic regulation of mechanical properties in the F(2) mice of this NZB/B1NJ x RF/J cross seems to be caused by genes regulating femur geometry.

Animals↗

PubMed2005

Quantitative trait loci that determine BMD in C57BL/6J and 129S1/SvImJ inbred mice.

UNLABELLED: BMD is highly heritable; however, little is known about the genes. To identify loci controlling BMD, we conducted a QTL analysis in a (B6 x 129) F2 population of mice. We report on additional QTLs and also narrow one QTL by combining the data from multiple crosses and through haplotype analysis. INTRODUCTION: Previous studies have identified quantitative trait loci (QTL) that determine BMD in mice; however, identification of genes underlying QTLs is impeded by the large size of QTL regions. MATERIALS AND METHODS: To identify loci controlling BMD, we performed a QTL analysis of 291 (B6 x 129) F2 females. Total body and vertebral areal BMD (aBMD) were determined by peripheral DXA when mice were 20 weeks old and had consumed a high-fat diet for 14 weeks. RESULTS AND CONCLUSIONS: Two QTLs were common for both total body and vertebral aBMD: Bmd20 on chromosome (Chr) 6 (total aBMD; peak cM 26, logarithm of odds [LOD] 3.8, and vertebral aBMD; cM 32, LOD 3.6) and Bmd22 on Chr 1 (total aBMD; cM 104, LOD 2.5, and vertebral aBMD; cM 98, LOD 2.6). A QTL on Chr 10 (Bmd21, cM 68, LOD 3.0) affected total body aBMD and a QTL on Chr 7 (Bmd9, cM 44, LOD 2.7) affected vertebral aBMD. A pairwise genome-wide search did not reveal significant gene-gene interactions. Collectively, the QTLs accounted for 21.6% of total aBMD and 17.3% of vertebral aBMD of the F(2) population variances. Bmd9 was previously identified in a cross between C57BL/6J and C3H/HeJ mice, and we narrowed this QTL from 34 to 22 cM by combining the data from these crosses. By examining the Bmd9 region for conservation of ancestral alleles among the low allele strains (129S1/SvImJ and C3H/HeJ) that differed from the high allele strain (C57BL/6J), we further narrowed the region to approximately 9.9 cM, where the low allele strains share a common haplotype. Identifying the genes for these QTLs will enhance our understanding of skeletal biology.

Animals↗

PubMed2005

Discovery of 1-(3'-aminobenzisoxazol-5'-yl)-3-trifluoromethyl-N-[2-fluoro-4- [(2'-dimethylaminomethyl)imidazol-1-yl]phenyl]-1H-pyrazole-5-carboxyamide hydrochloride (razaxaban), a highly potent, selective, and orally bioavailable factor Xa inhibitor.

Modification of a series of pyrazole factor Xa inhibitors to incorporate an aminobenzisoxazole as the P(1) ligand resulted in compounds with improved selectivity for factor Xa relative to trypsin and plasma kallikrein. Further optimization of the P(4) moiety led to compounds with enhanced permeability and reduced protein binding. The SAR and pharmacokinetic profile of this series of compounds is described herein. These efforts culminated in 1-(3'-aminobenzisoxazol-5'-yl)-3-trifluoromethyl-N-[2-fluoro-4-[(2'-dimethylaminomethyl)imidazol-1-yl]phenyl]-1H-pyrazole-5-carboxyamide (11d), a potent, selective, and orally bioavailable inhibitor of factor Xa. On the basis of its excellent in vitro potency and selectivity profile, high free fraction in human plasma, good oral bioavailability, and in vivo efficacy in antithrombotic models, the HCl salt of this compound was selected for clinical development as razaxaban (DPC 906, BMS-561389).

Administration, Oral↗

PubMed2005

Kinesin family member 12 is a candidate polycystic kidney disease modifier in the cpk mouse.

The cpk mouse is the most extensively characterized model of autosomal recessive polycystic kidney disease (ARPKD). The major ARPKD-related renal and biliary phenotypes are modulated in F2 mutants by genetic background, suggesting that quantitative trait loci (QTL) modulate disease severity. In 461 F2 cpk mice, kidney length, weight, and volume were scored as quantitative traits (QT), and a semiquantitative method to assess biliary duct number, area (BDA), portal vein area, and total area of each portal field, as well as the severity of cholangitis, was developed. QTL mapping was performed with Pseudomarker v1.02. Candidate genes were identified within the QTL intervals on the basis of expression profiling, reverse transcriptase-PCR, haplotypes, and sequence analysis. The renal QT were normally distributed in the F2 cohort and strongly correlated (P < 0.001). Among the biliary QT, only BDA correlated with the renal QT (P < 0.01). Genome-wide scan identified a major effect QTL on chromosome (Chr) 4 for the renal traits, adjusted BDA, and cholangitis with logarithm of odds scores of 18, 8, and 5, respectively. Regression modeling refined the Chr 4 main effect into an approximately 50-cM region with three distinct QTL peaks at 16, 34, and 54 cM. Kif12, a gene encoding a novel kinesin, mapped beneath the 34 cM QTL peak and has expression level variants and strain-specific sequences that were associated with renal disease severity in affected mice. Therefore, the positional candidate gene, Kif12, fulfills the major criteria for QTL gene discovery established by the Complex Trait Consortium, and, thus, it is proposed that Kif12 is a cpk modifier gene.

Animals↗

PubMed2005

Distal Chr 4 harbors a genetic locus (Gct1) fundamental for spontaneous ovarian granulosa cell tumorigenesis in a mouse model.

The spontaneous development of juvenile-onset ovarian granulosa cell tumors in mice of the SWXJ-9 recombinant inbred strain is a model for juvenile-type granulosa cell tumors that appear in very young girls. To expedite gene discovery in this mouse model of childhood cancer, we did a gene mapping study with the SWXJ-9 recombinant inbred strain and the evolutionarily divergent Mus musculus castaneus (CAST/Ei) strain as a mapping partner. Our mapping strategy focused on autosomal determinants of susceptibility with a backcross scheme that exploited a paternal, parent-of-origin effect for a X-linked gene (Gct4) that strongly supports granulosa cell tumor development. Of 1,968 backcross females examined, we detected 81 granulosa cell tumor-bearing animals and compared their allelic inheritance patterns to non-tumor-bearing siblings in a case-control analysis. The results of our study have confirmed an important locus on mouse chromosome (Chr) 4 (Gct1) and have revealed new loci for granulosa cell tumor susceptibility (Gct7-Gct9) on Chrs 1, 2, and 13 with susceptibility alleles contributed by the SWXJ-9 progenitor. Two novel gene-gene interactions supportive for granulosa cell tumor development were also observed between loci on Chrs 17 and 18 and loci on Chrs 2 and 10. Our data substantiate the evidence that Gct1 on Chr 4 is a fundamental oncogene for granulosa cell tumorigenesis in mice and has identified additional interacting autosomal loci that support tumor development.

Animals↗

PubMed2005

Combining data from multiple inbred line crosses improves the power and resolution of quantitative trait loci mapping.

Rodent inbred line crosses are widely used to map genetic loci associated with complex traits. This approach has proven to be powerful for detecting quantitative trait loci (QTL); however, the resolution of QTL locations, typically approximately 20 cM, means that hundreds of genes are implicated as potential candidates. We describe analytical methods based on linear models to combine information available in two or more inbred line crosses. Our strategy is motivated by the hypothesis that common inbred strains of the laboratory mouse are derived from a limited ancestral gene pool and thus QTL detected in multiple crosses are likely to represent shared ancestral polymorphisms. We demonstrate that the combined-cross analysis can improve the power to detect weak QTL, can narrow support intervals for QTL regions, and can be used to separate multiple QTL that colocalize by chance. Moreover, combined-cross analysis can establish the allelic states of a QTL among a set of parental lines, thus providing critical information for narrowing QTL regions by haplotype analysis.

Cholesterol, HDL↗

PubMed2005

Single and interacting QTLs for cholesterol gallstones revealed in an intercross between mouse strains NZB and SM.

Quantitative trait locus (QTL) mapping was employed to investigate the genetic determinants of cholesterol gallstone formation in a large intercross between mouse strains SM/J (resistant) and NZB/B1NJ (susceptible). Animals consumed a gallstone-promoting diet for 18 weeks. QTL analyses were performed using gallstone weight and gallstone absence/presence as phenotypes; various models were explored for genome scans. We detected seven single QTLs: three new, significant QTLs were named Lith17 [chromosome (Chr) 5, peak=60 cM, LOD=5.4], Lith18 (Chr 5, 76 cM, LOD=4.3), and Lith19 (Chr 8, 0 cM, LOD=5.3); two confirmed QTLs identified previously and were named Lith20 (Chr 9, 44 cM, LOD=2.7) and Lith21 (Chr 10, 24 cM, LOD=2.9); one new, suggestive QTL (Chr 17) remains unnamed. Upon searching for epistatic interactions that contributed to gallstone susceptibility, the final suggestive QTL on Chr 7 was determined to interact significantly with Lith18 and, therefore, was named Lith22 (65 cM). A second interaction was identified between Lith19 and a locus on Chr 11; this QTL was named Lith23 (13 cM). mRNA expression analyses and amino acid haplotype analyses likely eliminated Slc10a2 as a candidate gene for Lith19. The QTLs identified herein largely contributed to gallstone formation rather than gallstone severity. Cloning the genes underlying these murine QTLs should facilitate prediction and cloning of the orthologous human genes.

Animals↗

PubMed2005

Association of a lithogenic Abcg5/Abcg8 allele on Chromosome 17 (Lith9) with cholesterol gallstone formation in PERA/EiJ mice.

To examine further the genetic determinants of cholesterol gallstone susceptibility in inbred mice, we performed quantitative trait locus (QTL) analysis of an intercross of gallstone-susceptible PERA/EiJ and gallstone-resistant DBA/2J inbred mice. Three hundred twenty-four F2 offspring were phenotyped for cholelithiasis during consumption of a lithogenic diet and genotyped using microsatellite markers. Linkage analysis was performed by interval mapping. In addition, we analyzed the combined datasets from this cross and from an independent cross of strain PERA and gallstone-resistant I/Ln mice. QTL mapping detected one significant new gallstone susceptibility (Lith) locus on Chromosome 13 (Lith15). A second significant QTL on Chr 6 (Lith16) confirmed a previous QTL. Furthermore, suggestive QTLs confirmed Lith loci from previous crosses on Chromosomes 1, 2, 5, 16 and X. QTL analysis of the dataset derived from the combined crosses increased the detection power and narrowed confidence intervals of Lith loci on Chromosomes 2, 6, 13, and 16. Moreover, the analysis of combined datasets revealed a shared QTL between both crosses on Chromosome 17 (Lith9). Significantly higher mRNA expression of Abcg5 and Abcg8 in strain PERA compared with strains I/Ln and DBA/2 further substantiated that the PERA allele of Abcg5/Abcg8 was responsible for lithogenicity underlying Lith9.

ATP Binding Cassette Transporter, Subfamily G, Mem↗

PubMed2004

Quantitative trait loci that determine plasma lipids and obesity in C57BL/6J and 129S1/SvImJ inbred mice.

The plasma lipid concentrations and obesity of C57BL/6J (B6) and 129S1/SvImJ (129) inbred mouse strains fed a high-fat diet containing 15% dairy fat, 1% cholesterol, and 0.5% cholic acid differ markedly. To identify the loci controlling these traits, we conducted a quantitative trait loci (QTL) analysis of 294 (B6 x 129) F(2) females fed a high-fat diet for 14 weeks. Non-HDL cholesterol concentrations were affected by five significant loci: Nhdlq1 [chromosome 8, peak centimorgan (cM) 38, logarithm of odds [LOD] 4.4); Nhdlq4 (chromosome 10, cM 70, LOD 4.0); Nhdlq5 (chromosome 6, cM 0) interacting with Nhdlq4; Nhdlq6 (chromosome 7, cM 10) interacting with Nhdlq1; and Nhdlq7 (chromosome 15, cM 0) interacting with Nhdlq4. Triglyceride (TG) concentrations were affected by three significant loci: Tgq1 (chromosome 18, cM 42, LOD 3.2) and Tgq2 (chromosome 9, cM 66) interacting with Tgq3 (chromosome 4, cM 58). Obesity measured by percentage of body fat mass and body mass index was affected by two significant loci: Obq16 (chromosome 8, cM 48, LOD 10.0) interacting with Obq18 (chromosome 9, cM 65). Knowing the genes for these QTL will enhance our understanding of obesity and lipid metabolism.

Animals↗

PubMed2004

Genetic contributors to lipoprotein cholesterol levels in an intercross of 129S1/SvImJ and RIIIS/J inbred mice.

To determine the genetic contribution to variation among lipoprotein cholesterol levels, we performed quantitative trait locus (QTL) analyses on an intercross between mouse strains RIIIS/J and 129S1/SvImJ. Male mice of the parental strains and the reciprocal F1 and F2 populations were fed a high-cholesterol, cholic acid-containing diet for 8-12 wk. At the end of the feeding period, plasma total, high-density lipoprotein (HDL), and non-HDL cholesterol were determined. For HDL cholesterol, we identified three significant QTLs on chromosomes (Chrs) 1 (D1Mit507, 88 cM, 72-105 cM, 4.8 LOD), 9 (D11Mit149, 14 cM, 10-25 cM, 9.4 LOD), and 12 (D12Mit60, 20 cM, 0-50 cM, 5.0 LOD). These QTLs were considered identical to QTLs previously named Hdlq5, Hdlq17, and Hdlq18, respectively, in crosses sharing strain 129. For total cholesterol, we identified two significant QTLs on Chrs 1 and 9, which were named Chol10 (D1Mit507, 88 cM, 10-105 cM, 3.9 LOD) and Chol11 (D11Mit149, 14 cM, 0-30 cM, 4.4 LOD), respectively. In addition, for total cholesterol, we identified two suggestive QTLs on Chrs 12 (distal) and 17, which remain unnamed. For non-HDL cholesterol, we identified and named one new QTL on Chr 17, Nhdlq3 (D17Mit221, 58 cM, 45-60 cM, 3.4 LOD). Nhdlq3 colocalized with orthologous human QTLs for lipoprotein phenotypes, and with Abcg5 and Abcg8. Overall, we detected eight QTLs for lipoprotein cholesterol concentrations on Chrs 1, 9, 12, and 17 (each two per chromosome), including a new QTL for non-HDL cholesterol, Nhdlq3, on Chr 17.

Animals↗

PubMed2004

Quantitative trait loci that determine lipoprotein cholesterol levels in an intercross of 129S1/SvImJ and CAST/Ei inbred mice.

To identify genetic determinants of lipoprotein levels, we are performing quantitative trait locus (QTL) analysis on a series of mouse intercrosses in a "daisy chain" experimental design, to increase the power of detecting QTL and to identify common variants that should segregate in multiple intercrosses. In this study, we intercrossed strains CAST/Ei and 129S1/SvImJ, determined HDL, total, and non-HDL cholesterol levels, and performed QTL mapping using Pseudomarker software. For HDL cholesterol, we identified two significant QTL on chromosome (Chr) 1 (Hdlq5, 82 cM, 60-100 cM) and Chr 4 (Hdlq10, 20 cM, 10-30 cM). For total cholesterol, we identified three significant QTL on Chr 1 (Chol7, 74 cM, 65-80 cM), Chr 4 (Chol8, 12 cM, 0-30 cM), and Chr 17 (Chol9, 54 cM, 20-60 cM). For non-HDL cholesterol, we identified significant QTL on Chr 8 (Nhdlq1, 34 cM, 20-60 cM) and Chr X (Nhdlq2, 6 cM, 0-18 cM). Hdlq10 was the only QTL detected in two intercrosses involving strain CAST/Ei. Hdlq5, Hdlq10, Nhdlq1, and two suggestive QTL at D7Mit246 and D15Mit115 coincided with orthologous human lipoprotein QTL. Our analysis furthers the knowledge of the genetic control of lipoprotein levels and points to the importance of Hdlq10, which was detected repeatedly in multiple studies.

ATP Binding Cassette Transporter 1↗

PubMed2004

Influence of sex and diet on quantitative trait loci for HDL cholesterol levels in an SM/J by NZB/BlNJ intercross population.

To investigate the dependence of HDL quantitative trait loci (QTL) on sex and diet, we generated a large intercross population of mice from parental strains SM/J and NZB/BlNJ. We measured HDL levels in progeny fed a chow diet and measured them again after 6, 12, and 16 weeks of feeding a high-fat, high-cholesterol diet. QTL analysis was performed on the 260 female and 253 male F(2) progeny. A total of 13 significant QTL were found. Four QTL were specific to female mice: Hdlq23 (Chr 6, 26 cM), Hdlq26 (Chr 10, 70 cM), Hdlq27 (Chr 15, 48 cM), and Hdlq32 (Chr 19, 40 cM). One significant QTL was specific to male mice: Hdlq29 (Chr 17, 36 cM). In addition, several QTL were found to have effects that were dependent on diet. Sex- and diet-dependent effects were characterized using a linear model-based genome scan method that avoids the potential pitfalls of subdivided data analysis. The dependence of QTL effects on sex suggests an important role for the sex hormones in HDL regulation. We recommend that sex should be explicitly accounted for in future studies in the genetics of HDL regulation in both mice and humans.

Animals↗

PubMed2004

Sex- and lineage-specific inheritance of depression-like behavior in the rat.

The Wistar-Kyoto (WKY) rat exhibits physiological and behavioral similarities to endophenotypes of human depression. In the forced swim test (FST), a well-characterized antidepressant-reversible test for behavioral despair in rodents, WKYs express characteristics of behavioral despair; increased immobility, and decreased climbing. To map genetic loci linked to behavior in the FST, we conducted a quantitative trait loci (QTL) analysis of the segregating F2 generation of a WKY x Fisher 344 (F344) reciprocal intercross. Using linear-model-based genome scans to include covariate (sex or lineage)-by-QTL interaction effects, four significant QTL influencing climbing behavior were identified. In addition, we identified three, seven, and two suggestive QTL for climbing, immobility, and swimming, respectively. One of these loci was pleiotropic, affecting both immobility and climbing. As found in human linkage studies, several of these QTL showed sex- and/or lineage-dependent effects. A simultaneous search strategy identified three epistatic locus pairs for climbing. Multiple regression analysis was employed to characterize the joint contributions of these QTL and to clarify the sex- and lineage-dependent effects. As expected for complex traits, FST behavior is influenced by multiple QTL of small effect, each contributing 5%-10%, accounting for a total 10%-30% of the phenotypic variance. A number of loci mapped in this study share overlapping candidate regions with previously identified emotionality QTL in mice as well as with susceptibility loci recognized by linkage or genome scan analyses for major depression or bipolar disorder in humans. The presence of these loci across species suggests that these QTL may represent universal genetic factors contributing to mood disorders.

Animals↗