Integration of QTL and bioinformatic tools to identify candidate genes for triglycerides in mice

To identify genetic loci influencing lipid levels, we performed quantitative trait loci (QTL) analysis between inbred mouse strains MRL/MpJ and SM/J, measuring triglyceride levels at 8 weeks of age in F2 mice fed a chow diet. We identified one significant QTL on chromosome (Chr) 15 and three suggestive QTL on Chrs 2, 7, and 17. We also carried out microarray analysis on the livers of parental strains of 282 F2 mice and used these data to find cis-regulated expression QTL. We then narrowed the list of candidate genes under significant QTL using a "toolbox" of bioinformatic resources, including haplotype analysis; parental strain comparison for gene expression differences and nonsynonymous coding single nucleotide polymorphisms (SNP); cis-regulated eQTL in livers of F2 mice; correlation between gene expression and phenotype; and conditioning of expression on the phenotype. We suggest Slc25a7 as a candidate gene for the Chr 7 QTL and, based on expression differences, five genes (Polr3 h, Cyp2d22, Cyp2d26, Tspo, and Ttll12) as candidate genes for Chr 15 QTL. This study shows how bioinformatics can be used effectively to reduce candidate gene lists for QTL related to complex traits.     

Congenic Mice Provide Evidence for a Genetic Locus That Modulates Spontaneous Arthritis Caused by Deficiency of IL-1RA

To understand the role of genetic factors involved in the development of spontaneous arthritis in mice deficient in IL-1 receptor antagonist protein (IL_1RA), we have identified a genomic region containing a major quantitative trait locus (QTL) for this disease. The QTL is on chromosome 1 and appears to be the strongest genetic region regulating arthritis. To confirm the importance of the QTL and to identify potential candidate genes within it, we conducted speed congenic breeding to transfer the QTL region from DBA/1 mice that are resistant to spontaneous arthritis into BALB/c^−/− which are susceptible. Genetic markers along every chromosome were used to assist in the selection of progeny in each generation to backcross to BALB/c^−/−. By the 6th generation we determined that all of the chromosomes in the progeny were of BALB/c origin with the exception of portions of chromosome 1. At this stage we intercrossed selected mice to produce homozygous strains containing the genomic background of BALB/c^−/− except for the QTL region on chromosome 1, which was from DBA/1. We were able to establish two congenic strains with overlapping DBA/1 DNA segments. These strains were observed for the development of spontaneous arthritis. Both congenic strains were relatively resistant to spontaneous arthritis and had delayed onset and reduced severity of disease. The gene/s that regulates this major QTL would appear to be located in the region of the QTL that is shared by both strains. The common transferred region is between D1Mit110 and D1Mit209 on chromosome 1. We evaluated this region for candidate genes and have identified a limited number of candidates. Confirmation of the identity and precise role of the candidates will require additional study.     

Genomic dissection and prioritizing of candidate genes of QTL for regulating spontaneous arthritis on chromosome 1 in mice deficient for interleukin-1 receptor antagonist

Rheumatoid arthritis is a heterogeneous disease with clinical and biological polymorphisms. IL-1RN is a protein that binds to interleukin-1 (IL-1) receptors and inhibits the binding of IL-1-alpha and IL-1-beta. IL-1RN levels are elevated in the blood of patients with a variety of infectious, immune, and traumatic conditions. Balb/c mice deficient in IL-1ra (mouse gene of IL-1RN) develop spontaneous autoimmune arthritis while DBA/1 mice deficient in IL-1ra do not. Previously, we identified a major QTL that regulates the susceptibility to arthritis in Balb/c mice with IL-1ra deficiency. In this study, we found that the QTL may contain two peaks that are regulated by two sets of candidate genes. By haplotype analysis, the total genomic regions of candidate genes were reduced from about 19 Mbp to approximately 9 Mbp. The total number of candidate genes was reduced from 208 to 21.     

Variation in Galr1 expression determines susceptibility to exocitotoxin-induced cell death in mice

Inbred strains of mice differ in their susceptibility to excitotoxin-induced cell death, but the genetic basis of individual variation in differential susceptibility is unknown. Previously, we identified a highly significant quantitative trait locus (QTL) on chromosome 18 that influenced susceptibility to kainic acid-induced cell death ( Sicd1 ). Comparison of susceptibility to seizure-induced cell death between reciprocal congenic lines for Sicd1 and parental background mice indicates that genes influencing this trait were captured in both strains. Two positional gene candidates, Galr1 and Mbp , map to 55 cM, where the Sicd1 QTL had been previously mapped. Thus, this study was undertaken to determine if Galr1 and/or Mbp could be considered as candidate genes. Genomic sequence comparison of these two functional candidate genes from the C57BL/6J (resistant at Sicd1 ) and the FVB/NJ (susceptible at Sicd1 ) strains showed no single-nucleotide polymorphisms. However, expression studies confirmed that Galr1 shows significant differential expression in the congenic and parental inbred strains. Galr1 expression was downregulated in the hippocampus of C57BL/6J mice and FVB.B6- Sicd1 congenic mice when compared with FVB/NJ or B6.FVB- Sicd1 congenic mice. A survey of Galr1 expression among other inbred strains showed a significant effect such that 'susceptible' strains showed a reduction in Galr1 expression as compared with 'resistant' strains. In contrast, no differences in Mbp expression were observed. In summary, these results suggest that differential expression of Galr1 may contribute to the differences in susceptibility to seizure-induced cell death between cell death-resistant and cell death-susceptible strains.     

Using bioinformatics and systems genetics to dissect HDL-cholesterol genetics in an MRL/MpJ x SM/J intercross

A higher incidence of coronary artery disease is associated with a lower level of HDL-cholesterol. We searched for genetic loci influencing HDL-cholesterol in F2 mice from a cross between MRL/MpJ and SM/J mice. Quantitative trait loci (QTL) mapping revealed one significant HDL QTL (Apoa2 locus), four suggestive QTL on chromosomes 10, 11, 13, and 18 and four additional QTL on chromosomes 1 proximal, 3, 4, and 7 after adjusting HDL for the strong Apoa2 locus. A novel nonsynonymous polymorphism supports Lipg as the QTL gene for the chromosome 18 QTL, and a difference in Abca1 expression in liver tissue supports it as the QTL gene for the chromosome 4 QTL. Using weighted gene co-expression network analysis, we identified a module that after adjustment for Apoa2, correlated with HDL, was genetically determined by a QTL on chromosome 11, and overlapped with the HDL QTL. A combination of bioinformatics tools and systems genetics helped identify several candidate genes for both the chromosome 11 HDL and module QTL based on differential expression between the parental strains, cis regulation of expression, and causality modeling. We conclude that integrating systems genetics to a more-traditional genetics approach improves the power of complex trait gene identification.     

Identification of Aortic Arch-Specific Quantitative Trait Loci for Atherosclerosis by an Intercross of DBA/2J and 129S6 Apolipoprotein E-Deficient Mice

The genetic background of apolipoprotein E (apoE) deficient mice influences atherosclerotic plaque development. We previously reported three quantitative trait loci (QTL), Aath1–Aath3, that affect aortic arch atherosclerosis independently of those in the aortic root in a cross between C57BL6 apoEKO mice (B6-apoE) and 129S6 apoEKO mice (129-apoE). To gain further insight into genetic factors that influence atherosclerosis at different vascular locations, we analyzed 335 F2 mice from an intercross between 129-apoE and apoEKO mice on a DBA/2J genetic background (DBA-apoE). The extent of atherosclerosis in the aortic arch was very similar in the two parental strains. Nevertheless, a genome-wide scan identified two significant QTL for plaque size in the aortic arch: Aath4 on Chromosome (Chr) 2 at 137 Mb and Aath5 on Chr 10 at 51 Mb. The DBA alleles of Aath4 and Aath5 respectively confer susceptibility and resistance to aortic arch atherosclerosis over 129 alleles. Both QTL are also independent of those affecting plaque size at the aortic root. Genome analysis suggests that athero-susceptibility of Aath4 in DBA may be contributed by multiple genes, including Mertk and Cd93, that play roles in phagocytosis of apoptotic cells and modulate inflammation. A candidate gene for Aath5 is Stab2, the DBA allele of which is associated with 10 times higher plasma hyaluronan than the 129 allele. Overall, our identification of two new QTL that affect atherosclerosis in an aortic arch-specific manner further supports the involvement of distinct pathological processes at different vascular locations.     

Analysis of the QTL for sleep homeostasis in mice: Homer1a is a likely candidate.

Electroencephalographic oscillations in the frequency range of 0.5-4 Hz, characteristic of slow-wave sleep (SWS), are often referred to as the delta oscillation or delta power. Delta power reflects sleep intensity and correlates with the homeostatic response to sleep loss. A published survey of inbred strains of mice demonstrated that the time course of accumulation of delta power varied among inbred strains, and the segregation of the rebound of delta power in BxD recombinant inbred strains identified a genomic region on chromosome 13 referred to as the delta power in SWS (or Dps1). The quantitative trait locus (QTL) contains genes that modify the accumulation of delta power after sleep deprivation. Here, we narrow the QTL using interval-specific haplotype analysis and present a comprehensive annotation of the remaining genes in the Dps1 region with sequence comparisons to identify polymorphisms within the coding and regulatory regions. We established the expression pattern of selected genes located in the Dps1 interval in sleep and wakefulness in B6 and D2 parental strains. Taken together, these steps reduced the number of potential candidate genes that may underlie the accumulation of delta power after sleep deprivation and explain the Dps1 QTL. The strongest candidate gene is Homer1a, which is supported by expression differences between sleep and wakefulness and the SNP polymorphism in the upstream regulatory regions.     

Genetic analysis of tongue size and taste papillae number and size in recombinant inbred strains of mice

Quantitative trait loci (QTLs) analysis has been used to examine natural variation of phenotypes in the mouse somatosensory cortex, hippocampus, cerebellum, and amygdala. QTL analysis has also been utilized to map and identify genes underlying anatomical features such as muscle, organ, and body weights. However, this methodology has not been previously applied to identification of anatomical structures related to gustatory phenotypes. In this study, we used QTL analysis to map and characterize genes underlying tongue size, papillae number, and papillae area. In a set of 43 BXD recombinant inbred (RI) mice (n = 111) and 2 parental strains (C57BL/6J and DBA/2J; n = 7), we measured tongue length, width, and weight. In a subset of 23 BXD RI mice and the parental mice, we measured filiform and fungiform papillae number and fungiform papillae area. Using QTL linkage analysis (through WebQTL), we detected 2 significant and noninteracting QTLs influencing tongue length on chromosomes 5 and 7. We also found a significant QTL on chromosome 19 underlying fungiform papillae area and a suggestive QTL on chromosome 2 linked to fungiform papillae number. From these QTLs, we identified a number of candidate genes within the QTL intervals that include SRY-box containing gene, nebulin-related anchoring protein, and actin-binding LIM protein 1. This study is an important first step in identifying genetic factors underlying tongue size, papillae size, and papillae number using QTL analysis.     

Identification of candidate genes in the type 2 diabetes modifier locus using expression QTL

To identify new genetic determinants relevant to type 2 diabetes (T2D), diabetic F2 progeny were generated by intercrossing F1 mice obtained from a cross of BKS.Cg-Lepr(db)+/+m and DBA/2, and T2D-related phenotypes were measured. In the F2 population, increased susceptibility to diabetes and obesity was observed. We also detected the major quantitative trait loci (QTL) modifying the severity of diabetes on chromosome 9, where peaks of logarithm of odds (LOD) overlapped for three traits. To identify candidate genes in the QTL intervals, we combined "expression QTL" (eQTL), taking mRNA levels as quantitative traits, and "interstrain sequence variations, including cSNPs." As a result, four genes were identified from cosegregation of clinical QTL with eQTL and 13 genes were found from interstrain cSNPs as candidates in the T2D modifier QTL. Our combined approach shows the acceleration of the discovery of candidate genes in the QTL of interest, spanning several megabases.     

Untangling HDL quantitative trait loci on mouse chromosome 5 and identifying Scarb1 and Acads as the underlying genes

Two high-density lipoprotein cholesterol quantitative trait loci (QTL), Hdlq1 at 125 Mb and Hdlq8 at 113 Mb, were previously identified on mouse distal chromosome 5. Our objective was to identify the underlying genes. We first used bioinformatics to narrow the Hdlq1 locus to 56 genes. The most likely candidate, Scarb1 (scavenger receptor B1), was supported by gene expression data consistent with knockout and transgenic mouse models. Then we confirmed Hdlq8 as an independent QTL by detecting it in an intercross between NZB and NZW (LOD = 12.7), two mouse strains that have identical genotypes for Scarb1. Haplotyping narrowed this QTL to 9 genes; the most likely candidate was Acads (acyl-coenzymeA dehydrogenase, short chain). Sequencing showed that Acads had an amino acid polymorphism, Gly94Asp, in a conserved region; Western blotting showed that protein levels were significantly different between parental strains. A previously known spontaneous deletion causes loss of ACADS activity in BALB/cBy mice. We showed that HDL levels were significantly elevated in BALB/cBy compared with BALB/c mice and that this HDL difference cosegregated with the Acads mutation. We confirmed that Hdlq1 and Hdlq8 are independent QTL on mouse chromosome 5 and demonstrated that Scarb1 and Acads are the underlying genes.     

Modulation of F1 cytotoxic potentials by GvHR: role and mode of action of non-MHC genes that determine the hybrid resistance to GvHR-associated suppression of F1 cytotoxic potential

The resistance of unirradiated F1 mice against graft-vs-host reaction (GvHR) induced by lymphocytes from certain parental strains is apparently a violation of the basic law in classical transplantation immunity. To explore genetic mechanisms of this peculiar phenomenon, GvHR-associated immunosuppression was examined on various kinds of F1 mice undergoing GvHR induced by parental lymphocytes. In F1 mice raised by crossing DBA/2 mice with various H-2-congeneic B10-series strains, parental lymphocytes having non-H-2 genetic background of DBA (DBA/2 and DBA/1) invariably could not induce GvHR-associated immunosuppression, irrespective of the H-2 haplotype incompatibility involved, whereas lymphocytes of the partner parental strain induced the immunosuppression. The number of the relevant loci in the DBA non-H-2 was assessed to be three recessive loci by examination of the capability to induce the GvHR-associated immunosuppression on lymphocytes from individual (B 10.D2 X DBA/2)F1 X DBA/2 backcross mice. On the other hand, in F1 mice raised by crossing C3H/He or AKR/J mice with various H-2-congeneic B10-series strains, parental lymphocytes of H-2k haplotype, irrespective of their non-H-2 haplotype, invariably could not induce the GvHR-associated immunosuppression. Furthermore, it was revealed that non-H-2 genes of parental C3H or AKR incorporated in the F1 mice determine the resistance of the F1 mice against the H-2k-induced GvHR. The results of examination of the resistance on individual (B10 X [B10.BR X C3H/He]F1) and (B10 X [B10.BR X AKR/J]F1) mice suggested that three non-H-2 loci of C3H/He or two non-2 loci of AKR/J incorporated in F1 hybrids could determine the resistance of the respective F1 mice.     

Genetic regulation of endotoxin-induced airway disease

To identify novel genes regulating the biologic response to lipopolysaccharide (LPS), we used a combination of quantitative trait locus (QTL) analysis and microarray-based gene expression studies of C57BL/6J x DBA/2J(BXD) F2 and recombinant inbred (RI) mice. A QTL affecting pulmonary TNF-alpha production was identified on chromosome 2, and a region affecting both polymorphonuclear leukocyte recruitment and TNF-alpha levels was identified on chromosome 11. Microarray analyses of unchallenged and LPS-challenged BXD RI strains identified approximately 500 genes whose expression was significantly changed by inhalation of LPS. Of these genes, 28 reside within the chromosomal regions identified by the QTL analyses, implicating these genes as high priority candidates for functional studies. Additional high priority candidate genes were identified based on their differential expression in mice having high and low responses to LPS. Functional studies of these genes are expected to reveal important molecular mechanisms regulating the magnitude of biologic responses to LPS.     

Genetic regulation of T regulatory, CD4, and CD8 cell numbers by the arthritis severity loci Cia5a, Cia5d, and the MHC/Cia1 in the rat

T cells have a central role in the pathogenesis of autoimmune arthritis, and several abnormalities in T cell homeostasis have been described in rheumatoid arthritis (RA). We hypothesized that T cell phenotypes, including frequencies of different subsets of T regulatory (Treg) cells and in vitro functional responses could be genetically determined. Furthermore, we considered that the genetic contribution would be accounted for by one of the arthritis regulatory quantitative trait loci (QTL), thus providing novel clues to gene mode of action. T cells were isolated from thymus, peripheral blood, and spleen from DA (arthritis-susceptible) and ACI and F344 (arthritis-resistant) strains and from F344.DA(Cia1), DA.F344(Cia5a), and DA.F344(Cia5d) rats congenic for arthritis QTL. T cell subpopulations differed significantly between DA, F344, and ACI. DA rats had an increased frequency of CD4(+) cells, and a reduction in CD8(+) and CD4(+)CD45RC(|o) Treg cells, compared with F344. The differences in CD4/CD8 and CD4(+)CD45RC(|o) Treg cells were accounted for by Cia5a. DA rats also had a reduced frequency of CD8(+)CD45RC(|o) CD25(+) Treg cells compared with F344, and that difference was explained by Cia5d. DA rats also had a significantly lower frequency of CD4(+)CD25(+) and CD8(+)CD25(+) thymocytes, and of peripheral blood CD8(+)CD45RC(|o) Treg cells, compared with F344 rats, and that difference was accounted for by the MHC. This is the first identification of arthritis severity QTL regulating numbers of CD4(+)CD45RC(|o) (Cia5a) and CD8(+)CD45RC(|o) CD25(+) (Cia5d) Treg cells. The MHC effect on CD8(+) Treg cells and CD25(+) thymocytes raises a novel potential explanation for its association with arthritis.     

The genetic basis of adrenal gland weight and structure in BXD recombinant inbred mice

Adrenal gland function is mediated through secreted hormones, which play a vital role in the autonomic and hypothalamic-pituitary-adrenal (HPA)-axis-mediated stress response. The genetic underpinnings of the stress response can be approached using a quantitative trait locus (QTL) analysis. This method has been used to investigate genomic regions associated with variation in complex phenotypes, but it has not been used to explore the structure of the adrenal. We used QTL analyses to identify candidate genes underlying adrenal weight and adrenal cortical zone and medulla widths. We used 64 BXD recombinant inbred (RI) strains of mice (n?=?528) and 2 parental strains (C57BL/6J and DBA/2J; n?=?20) to measure adrenal weights and adrenal zone widths. For adrenal weight, we found significant QTLs on chromosome 3 for females (Fawq1) and Chr 4 for males (Mawq1) and suggestive QTLs on Chrs 1, 3, 10, and 14 for females and Chrs 2, 4, 10, 17, and X for males. We identified a significant QTL on Chr 10 (Mawdq1) and a suggestive QTL on Chr 13 for male adrenal total width. For male adrenal medulla width, we found a significant QTL on Chr 5 (Mmwdq1) and a suggestive QTL on Chr 1. We also identified significant QTLs on Chrs 10 (Mxwdq1) and 14 (Mxwdq2) for male X-zone width. There are 113 genes that mapped within the significant QTL intervals, and we identified 4 candidate genes associated with adrenal structure and/or function. In summary, this study is an important first step for detecting genetic factors influencing the structure of the adrenal component of the HPA axis using QTL analyses, which may relate to adrenal function and provide further insights into elucidating genes critical for stress-related phenotypes.     

Mapping of a Chromosome 12 Region Associated with Airway Hyperresponsiveness in a Recombinant Congenic Mouse Strain and Selection of Potential Candidate Genes by Expression and Sequence Variation Analyses

In a previous study we determined that BcA86 mice, a strain belonging to a panel of AcB/BcA recombinant congenic strains, have an airway responsiveness phenotype resembling mice from the airway hyperresponsive A/J strain. The majority of the BcA86 genome is however from the hyporesponsive C57BL/6J strain. The aim of this study was to identify candidate regions and genes associated with airway hyperresponsiveness (AHR) by quantitative trait locus (QTL) analysis using the BcA86 strain. Airway responsiveness of 205 F2 mice generated from backcrossing BcA86 strain to C57BL/6J strain was measured and used for QTL analysis to identify genomic regions in linkage with AHR. Consomic mice for the QTL containing chromosomes were phenotyped to study the contribution of each chromosome to lung responsiveness. Candidate genes within the QTL were selected based on expression differences in mRNA from whole lungs, and the presence of coding non-synonymous mutations that were predicted to have a functional effect by amino acid substitution prediction tools. One QTL for AHR was identified on Chromosome 12 with its 95% confidence interval ranging from 54.6 to 82.6 Mbp and a maximum LOD score of 5.11 (p = 3.68×10⁻³). We confirmed that the genotype of mouse Chromosome 12 is an important determinant of lung responsiveness using a Chromosome 12 substitution strain. Mice with an A/J Chromosome 12 on a C57BL/6J background have an AHR phenotype similar to hyperresponsive strains A/J and BcA86. Within the QTL, genes with deleterious coding variants, such as Foxa1, and genes with expression differences, such as Mettl21d and Snapc1, were selected as possible candidates for the AHR phenotype. Overall, through QTL analysis of a recombinant congenic strain, microarray analysis and coding variant analysis we identified Chromosome 12 and three potential candidate genes to be in linkage with airway responsiveness.