High resolution mapping of trypanosomosis resistance loci Tir 2 and Tir 3 using F12 advanced intercross lines with major locus Tir 1 fixed for the susceptible allele
© Nganga et al; licensee BioMed Central Ltd. 2010
Received: 7 January 2010
Accepted: 22 June 2010
Published: 22 June 2010
Trypanosomosis is the most economically important disease constraint to livestock productivity in Africa. A number of trypanotolerant cattle breeds are found in West Africa, and identification of the genes conferring trypanotolerance could lead to effective means of genetic selection for trypanotolerance. In this context, high resolution mapping in mouse models are a promising approach to identifying the genes associated with trypanotolerance. In previous studies, using F2 C57BL/6J × A/J and C57BL/6J × BALB/cJ mouse resource populations, trypanotolerance QTL were mapped within a large genomic intervals of 20-40 cM to chromosomes MMU17, 5 and 1, and denoted Tir 1, Tir 2 and Tir 3 respectively. Subsequently, using F6 C57BL/6J × A/J and C57BL/6J × BALB/cJ F6 advanced intercross lines (AIL), Tir 1 was fine mapped to a confidence interval (CI) of less than 1 cM, while Tir 2 and Tir 3, were mapped within 5-12 cM. Tir 1 represents the major trypanotolerance QTL.
In order to improve map resolutions of Tir 2 and Tir 3, an F12 C57BL/6J × A/J AIL population fixed for the susceptible alleles at Tir 1 QTL was generated. An F12 C57BL/6J × A/J AIL population, fixed for the resistant alleles at Tir 1 QTL was also generated to provide an additional estimate of the gene effect of Tir 1. The AIL populations homozygous for the resistant and susceptible Tir 1 alleles and the parental controls were challenged with T. congolense and followed for survival times over 180 days. Mice from the two survival extremes of the F12 AIL population fixed for the susceptible alleles at Tir 1 were genotyped with a dense panel of microsatellite markers spanning the Tir 2 and Tir 3 genomic regions and QTL mapping was performed. Tir 2 was fine mapped to less than 1 cM CI while Tir 3 was mapped to three intervals named Tir 3a, Tir 3b and Tir 3c with 95% confidence intervals (CI) of 6, 7.2 and 2.2 cM, respectively.
The mapped QTL regions encompass genes that are vital to innate immune response and can be potential candidate genes for the underlying QTL.
Trypanosome infection (Trypanosomosis) is a disease of man, domestic livestock and wildlife. Trypanosomosis is the most economically important disease constraint to livestock productivity in Africa [1, 2]. The major pathogenic trypanosomes transmitted by the tsetse fly include T. congolense, T. vivax, T. brucei, and T. evansi, which cause the disease either as single or multiple infections. The disease is characterized by anemia as evidenced by reduction in packed cell volume due to erythrophagocytosis) fever, weight loss, fatigue and heart failure . This results in loss of production, and in more severe cases, death of the animal . Certain breeds of cattle show a remarkable resistance to the effects of trypanosomosis. This phenomenon is termed 'trypanotolerance' because the host tolerates the presence of the parasites, while not showing the severe anemia and production loss that characterize the infection in susceptible breeds . Selective breeding of livestock for trypanotolerant traits would provide a partial solution to livestock based agriculture in tsetse-infested areas . Recently, quantitative trait loci (QTL) associated with trypanotolerance traits in cattle were reported .
Parallel to QTL mapping in cattle, experimental studies in mice have also been used to map trypanotolerance QTL [7, 8]. The mouse offers a powerful model for studying the genetics of disease resistance . Inbred strains of mice show different responses to trypanosomosis , and different capacity of controlling anemia during infection . In particular, the C57BL/6J strain of inbred mice presents a higher degree of resistance to T. congolense than the A/J and BALB/cJ mouse strains [10, 12]. Trypanotolerance in mice is related to early control of parasitemia , a capacity that is associated with genes that are expressed early in the course of the infection. These early genes regulate parasite growth and determine how rapidly the immune response is triggered. Susceptible mouse strains show sustained high levels of parasitemia after challenge by T. congolense whereas low levels are shown by the resistant strains . Thus, mapping QTL affecting trypanotolerance in mice provides an alternative approach to identifying the genes associated with trypanotolerance.
In previous studies of survival time following T. congolense challenge in F2 crosses between the susceptible A/J and BALB/cJ strains and the resistant C57BL/6J mice, three trypanosomosis resistance QTL (denoted, Tir 1, Tir 2 and Tir 3) were identified and mapped to large genomic intervals on mouse chromosome MMU17, MMU5 and MMU1 respectively . Tir 1 represents the major trypanotolerance QTL with an additive effect of 31 days on survival time . Following the initial QTL mapping results, the advanced intercross lines (AIL) approach  was exploited for further fine mapping of trypanotolerance QTL in mice . Using F6 C57BL/6J × A/J and C57BL/6J × BALB/cJ AIL populations, Tir 1 was indeed mapped to a 95% confidence interval (CI) of 1.3 cM (17.3--18.6 cM) on MMU17 . In the same AIL, however, Tir 2, and Tir 3 were only mapped to much larger CIs: Tir 2, to a 95% CI of 12 cM (39-51 cM), on MMU5; while Tir 3 resolved into three distinct peaks on MMU1, each representing a different putative QTL (denoted, Tir 3a, Tir 3b and Tir 3c). These three QTL mapped to 95% CIs of 10 cM (68-78 cM), 1.8 cM (58.8-60.6 cM) and 8 cM (90-98 cM) on MMU1, respectively . Thus, high resolution mapping of Tir 2 and Tir 3 to a small genomic confidence interval, as required for positional cloning of genes underlying the QTL remained to be achieved.
Here, we report further fine mapping of Tir 2 and Tir 3, using an F12 AIL fixed for the susceptible allele at Tir 1. The underlying rationale is that fixing Tir 1 would reduce residual ("error") variance and hence result in stronger relative effects of Tir 2 and Tir 3, while the use of an F12 AIL would increase recombination events facilitating fine mapping. To fully exploit the additional recombination events at the F12 AIL, it was necessary to employ a denser set of markers than those used in F6 mapping. Hence, selective genotyping  was employed in order to reduce the associated genotyping load. This procedure has been shown to reduce genotyping load with little reduction in the power of QTL detection .
Summary table of QTL comparing results of the F21, F62 and F123 AIL mapping populations.
Map Location (cM)
Map Location (cM)
Map Location (cM)
Map Location (cM)
Map Location (cM)
Marker positions and map expansion
MMU1, marker position (cM and Mbp) and marker to marker distances on the MGD and F12 linkage maps.
MGD linkage map
F12 linkage map
Distance in cM
Distance in cM
MMU5, marker position (cM and Mbp) and marker to marker distances on the MGD and F12 linkage maps.
MGD linkage map
F12 linkage map
MGD Marker order
Distance in cM
Distance in cM
LOD score plots
Effects of the Tir QTL
Table 1 shows position and effects of Tir 2 and the three Tir 3 QTL as were estimated from the F12-AIL. The three Tir 3 loci had roughly equal effect, with the susceptibility allele at each of the loci reducing survival time by 11 to 12 days. Tir 3a was almost completely additive, while Tir 3b and Tir 3c showed partial dominance in the direction of resistance (dominance ratios 0.51 and 0.42, respectively). Total summed additive effect of all three Tir 3 loci was 34.64 days. The effect of Tir 2 (8.91 days; 4.5% of variance explained)) was quite a bit less than that of the Tir 3 loci; and in contrast to Tir 3, dominance at Tir 2 was in the direction of susceptibility.
Locations and confidence intervals of the Tir QTL
Tir 2 mapped to a confidence interval of 1 cM in the present study, at 41 cM on MMU5. This is comfortably within the region 39 - 51 cM with peak at 44 cM found in the previous F6 AIL study  so that the two experiments are almost certainly identifying the same QTL. The CI of 1 cM obtained in the present study is a distinct improvement on the CI of 12 cM obtained in the F6 study.
The F12 mapping results fully confirmed the complex tripartite substructure of Tir 3 as hinted at in the F2 mapping results and clearly expressed in the F6 AIL . However, correspondence of the F6 and F12 mapping results was not as close for the three Tir 3 loci as for Tir 2, and the reduction in CI was for the most part marginal. For Tir 3a, the F12 CI (64 - 70 cM) was distal to the corresponding F6 CI (58.8 - 60.6 cM) and considerably larger (6 cM and 1.8 cM, respectively). For Tir 3b, the F12 CI (72.2 -- 79.3 cM) corresponded closely to the Tir 3b F6 CI (68 - 78 cM). However, improvement in CI was slight (from 10 cM in the F6 to 7 cM in the F12). For Tir 3c, F12 CI (85-87.2 cM) was proximal to the F6 CI (90-98 cM), but was considerably narrower (2 cM and 8 cM, respectively). Thus, Tir 3b which is the central QTL in this region mapped to the same location as in the F6, while Tir 3a and Tir 3c both appear to have moved toward the center. We return to this in the Discussion.
Parental C57BL/6J mice had a 21 day higher mean survival time than parental A/J mice. This agrees with the purported higher resistance of the C57BL/6J compared to A/J mice. However, the absolute magnitude of the difference was much less than the 75 days previously reported . We believe that this is best explained by factors associated with the source supplier of the parental lines. Variation in the T. congolense clones might also be considered, but this would be expected to affect the estimated effects at the Tir 1 locus as well. This was not found; allele substitution effects at Tir 1 were similar in all three experiments.
In addition, in the original study of the F2 of a cross between these two lines  the F2 was intermediate in resistance between the two parental lines; while in the present study the D17SS AIL (fixed for the susceptible allele at Tir 1) was more resistant than the resistant C56BL/6J parent line. The F6 AIL also displayed higher resistance than the C56BL/6J parent line (data not shown). A genetic explanation for these results is not evident, and hence we believe they too should be attributed to some factor associated with the source supplier of the parental lines. A further possibility is an accumulated effect of environmental factors on the AIL populations that improved their phenotypic response to the infection, especially considering that the AIL population were developed during a period of three years at ILRI in an open environment mouse facility. More speculatively, this increase might also be due to dissociation of suppressor factors linked to host resistant genes due to increase in the recombination events in AIL generations. Such a dissociation might lead to an increase in the expression of resistant phenotypes in these mouse populations.
Table 1 summarizes the results of the present study, and of the previous F2  and F6 AIL [16, 19] studies of these lines. With minor exceptions, the results are quite consistent across the three studies. Tir1 mapped to same general location in F2 and F6 AIL (17.9 cM), with very narrow CI, and hence was not mapped again in the F12 AIL. Effect of the locus on 50% survival time was consistent in all three studies (33.5, 38.8 and 30.0 days for the F2, F6 AIL and F12 AIL, respectively. Tir 2 mapped to the same general location in F6 and F12 AIL but more proximally in the F2. Estimate of effects differed across the three studies, from 22, 14.7 and 8.9 days, respectively. Estimate of location had very narrow CI in the F12 AIL. Tir 3 mapped to the same general location in all three studies, but was resolved into three distinct peaks in the two AIL analyses. Summed effect of the Tir 3 chromosomal region was similar in all three studies: 32.0, 45.2 and 34.64, for F2, F6 AIL, and F12 AIL, respectively. The proportion of phenotypic variance explained by Tir 2, and Tir 3c in the present study was comparable to that found in the F2  and in the F6 AIL studies . The proportion of variance explained by Tir 3a and Tir 3b in the present study, however, was considerably greater than found in the F6 AIL. Overall, the proportion of variance explained by Tir 2 and Tir 3 was somewhat greater in the present study than in the F6 AIL. This may be attributed to the fixing of the strong Tir 1 locus, which contributed 11.8% and 19.6% of phenotypic variance in the F2 and F6 AIL populations, respectively. Tir 3b mapped to about the same location in both the F6 and F12 AIL, but with fairly wide CI in both (10 cM and 7 cM, respectively). Tir 3a and Tir 3b in the F6 AIL, however, mapped a bit proximal (Tir 3a) and a bit distal (Tir 3c) to their F6 AIL locations, bringing them each somewhat closer to Tir 3b in the F12. A narrow CI was achieved for Tir 3a in the F6 AIL, and for Tir 3c in the F12 AIL. Analysis of map order in the F6 AIL marker map showed a large number of discrepancies between the map order inferred from the F6 AIL genotypes, and the standard MGD map order of that time (Data not shown). In contrast, map order of the F6 and F12 AIL marker maps was fully consistent with the current MGD map. For this reason we favor the map locations of the QTL obtained in the F12 population.
Thus, of the four Tir QTL mapped in the F12 AIL, higher map resolution was achieved for Tir 2 and Tir 3c, but not for Tir 3a or Tir 3b. However, Tir 3a had already been mapped to a narrow CI in the F6 AIL. Taken as a whole then, the AIL approach successfully resolved the complex Tir 3 locus into three component loci, and together with Tir 1 and Tir 2 mapped four of the resultant five Tir loci (all except for Tir 3b) to CI that are sufficiently narrow (<2 cM), to make positional cloning feasible. It is quite possible that combining the F6 and F12 data might yield higher resolution for Tir 3b as well.
As an alternative to the AIL approach for high resolution mapping, it may have been possible to generate Interval Specific Congenic Lines  for each of the Tir QTL. These have been used successfully for high resolution of individual QTL, (see, e.g., [21, 22]). However, in these cases, a single QTL was dissected. The present study involved five QTL; thus, five series of ICSL lines would have had to be developed. Logistically, the AIL seems to have delivered about the same degree of map resolution with far less resources.
A number of candidate trypanotolerance genes within the fine mapped Tir 2 loci were identified from the public databases http://www.informatics.jax.org/. We have identified forty three genes mapped within the fine mapped intervals of Tir 2 QTL (between D5MIT258-D5MIT58). Of these, the most attractive candidate genes which may underly the QTL are Toll-like receptor 1, Toll-like receptor 6, both of which are well known to be associated innate immunity and host response to infection diseases and are important for the elimination of invading pathogens. Toll-like receptors (TLRs) are members of the pattern-recognition receptor (PRR) family and play a central role in initiation of innate cellular immune response and subsequently adaptive immune response to pathogens. TLRs can recognize diverse pathogen-associated molecular patters (PAMPs) make it an early warning system against invading pathogens. Activation of TRL signal initiates pathways, which leads to activation of variety of genes that function in host defense mechanism, including those of inflammatory cytokines, chemokines, and antigen presenting molecules. These genes are the most relevance for our studied phenotype and can be involved in clearance of trypanosma parasite from the infected mice.
For the Tir 3 region, attractive candidate genes include Interleukin 10 and its regulator CYPr2 gene on Tir 3a and b respectively, and various tumor necrosis factor ligand super-family members, interferon related segments, and Toll like receptor 5 genes. These genes are involved in host response to various pathogenic infections hence may play a role in trypanotolerance.
The cumulative results of the mouse F2 and AIL mapping studies provide essential mapping information for the identification of candidate trypanotolerance genes in mice, and may be useful for the identification of the homologous genes in livestock. Further analysis of these and other candidate genes is vital in order to ascertain their role in trypanotolerance. In future studies, we plan to examine the candidate genes for suggestive polymorphisms, and perform expression assays for these and other candidate genes under control and challenge conditions as the next step to identify the actual genes involved in resistance.
Development and selection of Tir1 fixed lines
Experimental lines fixed for the susceptible allele at Tir 1 were generated by genotyping 200 mice of each sex from the F9 C57BL/6J × A/J AIL with a panel of 12 microsatellite markers spanning the Tir 1 QTL region from 15.9 cM (D17Mit29) to 21.95 cM (D17Mit11). Males and females of the F9 AIL population were selected depending on whether they were homozygous for the chromosomal haplotypes representing the susceptible or resistance alleles at Tir 1, with the rest of the genome being random. These animals (10 breeding pairs of each designated genotype) were intermated by genotype to produce two lines, one (designated D17SS), putatively homozygous for the susceptibility allele at Tir 1 and the other (designated D17RR), putatively homozygous for the resistance allele. In order to expand the population, the F9 Tir 1 homozygous lines were then intermated for three further generations to produce 600 and 100 of D17SS and D17RR F12 mice respectively. D17SS and D17RR were generated at the International Livestock Research Institute (ILRI) small animal facility (SAU). In addition, 30 animals each of the two parental inbred mouse lines, A/J and C57BL/6J, were purchased from Harlan UK Ltd., (Bicester, Oxon, U.K). At age of 12 weeks, all animals (i.e., the 600 D17SS and 100 D17RR F12 animals, and the 30 mice of each of the parental inbred lines, A/J and C57BL/6J), were challenged by intraperitoneal injection of 104 bloodstream forms of T. congolense clone 1180 in a total volume of 200 μl phosphate-buffered saline glucose . Survival time for each individual was recorded over a period of 180 days, with mice surviving longer than 180 days, being assigned a survival time of 180 days. Differences between mean survival time of the various lines were tested for significance by t-test, using R/4 as an estimate of the SD of survival time within each line, where R is the range that includes 95% of the individuals in each line, averaged over all four lines. All experimental mice and protocols were approved by the Institutional Animal Care and Use Committee of ILRI. During the experiment, mice were housed on hardwood chip bedding in cages at an open environment animal facility and were given tap water and rodent chow ad libitum. The parental and D17RR lines were included in the experiment to serve as a positive control for the challenge protocol. Studies in mice show that animals of the same inbred strain reared in different facilities, behave differently when tested by the same protocol (see, e.g., . Consequently, since the F12 animals and the parental lines were produced under different conditions, and are separated by many generations from the time the AIL was initiated, it is not appropriate to make direct comparisons between the survival curves of the parental lines and the F12 populations.
One hundred mice representing 16.5% of the 600 T. congolense-inoculated F12 D17SS mice were selected from each of the phenotypic extremes for genotyping (total, 200 mice). These were the first 100 and the last 100 D17SS mice to succumb, including mice that survived the full 180 days. Fluorescent dye labeled microsatellite markers (Research Genetics, Huntsville Ala USA) within the previously mapped Tir 2 and Tir 3 QTL regions on MMU1 and MMU5 were selected for genotyping from the mouse genome databases at http://www.broadinstitute.org/science/projects/mammals-models/mouse/mouse-genome-links. At MMU1 an additional 13 markers were genotyped, giving a total of 21 markers covering 51.8 cM, with mean marker interval of 2.59 cM; while at MMU5 an additional 14 markers were genotyped, giving a total of 20 markers covering 53.0 cM, with mean marker interval of 2.79 cM (see Figure 2 for details). Tables 2 and 3 show all markers used, and their location on the MGD marker map. Marker order was the same on the EMSEMBL marker map, with the exception of D1MIT102 and D1MIT288 whose order is reversed on the EMSEMBL map, relative to the MGD map.
Mouse genomic DNA was extracted from tail tissue by standard phenol chloroform extraction  and suspended in Tris EDTA buffer (pH 7.6). PCR amplification was carried out in a DNA thermal cycler 9600 (Perkin-Elmer Cetus, Norwalk, Conn.) as described earlier . Fluorescent PCR products were loaded and separated on automated DNA sequencers (ABI PRISM® 377, Applied Biosystems). The genotypes were assigned using Genescan® 672 (Version 2.0.2 Applied Biosystems) and Genotyper® (Version 2.0 Applied Biosystems) software.
Linkage analysis and QTL mapping
Based on the F12 genotyping results, microsatellite markers used for fine mapping Tir 2 and Tir 3 loci on MMU1 and MMU5 were mapped and best ordered on each chromosome, using the MapMaker/QTL program . MapMaker/QTL was also used for mapping on these chromosomes of QTL having an effect on mean survival time following T. congolense challenge. MapMaker/QTL provides an estimate of additive and dominance effects at each of the QTL, and the proportion of the phenotypic variance explained by each of the putative QTL. Threshold effects for declaring significance and bootstrap estimates of confidence intervals of QTL map location were obtained using the QTL Express program http://qtl.cap.ed.ac.uk/.
When selective genotyping is employed, estimates of QTL effect are biased upward . However, unbiased estimates are obtained when maximum likelihood methods are employed that make use of the entire phenotypic distribution, including the animals that were not genotyped . This is the procedure used by Mapmaker/QTL, and hence the results provided by this program are unbiased by the applied selection.
We wish to thank John Wambugu, Moses Ogugo, Daniel Mwangi and Nemwal Nyamweya from ILRI for their excellent technical assistance. Special thanks also goes to, Prof Mabel Imbuga of Jomo Kenyatta University of Agriculture and Technology (JKUAT) for her support and advice. We also wish to acknowledge the contribution JKUAT, the International Livestock Research Institute training unit under Dr Rob Eley for the graduate fellowship. This work was directly funded by the Welcome Trust, United Kingdom, Japan and European Union through the CGIAR.
Advanced Intercross Line
Quantitative trait locus
Toll like receptor
- World Health Organization. Tropical Disease Research: Thirteenth Programme Report. UNDP/World Bank/WHO Special Programme for Research and Training in Tropical Disease (TDR). 1997, 125-126.Google Scholar
- World Health Organization: Control and surveillance of African trypanosomiasis. Report of a WHO Expert Committee. World Health Organ Tech Rep Ser. 1998, 881: I-VI. 1-114Google Scholar
- Murray M, Dexter TM: Anaemia in bovine African trypanosomiasis. Acta Trop. 1988, 45: 389-432.PubMedGoogle Scholar
- Gardiner PR, Assoku RK, Whitelaw DD, Murray M: Haemorrhagic lesions resulting from Trypanosoma vivax infection in Ayrshire cattle. Vet Parasitol. 1989, 31: 187-197. 10.1016/0304-4017(89)90069-1.PubMedView ArticleGoogle Scholar
- Roelants GE, Fumoux F, Pinder M, Queval R, Bassinga A, Authie E: Identification and selection of cattle naturally resistant to African trypanosomiasis. Acta Trop. 1987, 44: 55-66.PubMedGoogle Scholar
- Hanotte O, Ronin Y, Agaba M, Gelhaus A, Horstmann R, Sugimoto Y, Kemp S, Gibson J, Korol A, Soller M, Teale A: Mapping of quantitative trait loci controlling trypanotolerance in a cross of tolerant West African N'Dama and susceptible East African Boran cattle. Proc Natl Acad Sci USA. 2003, 100: 7443-7448. 10.1073/pnas.1232392100.PubMed CentralPubMedView ArticleGoogle Scholar
- Kemp SJ, Darvasi A, Soller M, Teale AJ: Genetic control of resistance to trypanosomiasis. Veterinary Immunology and Immunopathology. 1996, 54: 239-243. 10.1016/S0165-2427(96)05692-9.PubMedView ArticleGoogle Scholar
- Kemp SJ, Iraqi F, Darvasi A, Soller M, Teale AJ: Localization of genes controlling resistance to trypanosomiasis in mice. Nat Genet. 1997, 16: 194-196. 10.1038/ng0697-194.PubMedView ArticleGoogle Scholar
- Moore KJ, Nagle DL: Complex trait analysis in the mouse: The strengths, the limitations and the promise yet to come. Annu Rev Genet. 2000, 34: 653-686. 10.1146/annurev.genet.34.1.653.PubMedView ArticleGoogle Scholar
- Morrison WI, Roelants GE, Mayor-Withey KS, Murray M: Susceptibility of inbred strains of mice to Trypanosoma congolense: correlation with changes in spleen lymphocyte populations. Clin Exp Immunol. 1978, 32: 25-40.PubMed CentralPubMedGoogle Scholar
- Noyes HA, Alimohammadian MH, Agaba M, Brass A, Fuchs H, Gailus-Durner V, Hulme H, Iraqi FA, Kemp SJ, Rathkolb B, Wolf E, Hrabé de Angelis M, Roshandel D, Naessens J: Mechanisms controlling anaemia in Trypanosoma congolense infected mice. PLOS One. 2009, 4 (4): e5170-10.1371/journal.pone.0005170.PubMed CentralPubMedView ArticleGoogle Scholar
- Whitelaw DD, Holmes PH, Urquhart GM: The susceptibility of strains of mice to infection with Trypanosoma congolense. Res Vet Sci. 1978, 25: 399-400.PubMedGoogle Scholar
- Murray M, Gray RA: The current situation in animal trypanosomosis in Africa. Preventive Veterinary Medicine. 1984, 2: 23-30. 10.1016/0167-5877(84)90045-X.View ArticleGoogle Scholar
- Whitelaw DD, Macaskill JA, Holmes PH, Jennings FW, Urquhart GM: Genetic resistance to Trypanosoma congolense infections in mice. Infect Immun. 1980, 27: 707-713.PubMed CentralPubMedGoogle Scholar
- Darvasi A, Soller M: Advanced intercross lines, an experimental population for fine genetic mapping. Genetics. 1995, 141: 1199-1207.PubMed CentralPubMedGoogle Scholar
- Iraqi F, Clapcott SJ, Kumari P, Haley CS, Kemp SJ, Teale AJ: Fine mapping of trypanosomiasis resistance loci in murine advanced intercross lines. Mammalian Genome. 2000, 11: 645-648. 10.1007/s003350010133.PubMedView ArticleGoogle Scholar
- Darvasi A, Soller M: Selective genotyping for determination of linkage between a marker locus and a quantitative trait locus. Theoretical and applied Genetics. 1992, 85: 353-359. 10.1007/BF00222881.PubMedGoogle Scholar
- Churchill GA, Doerge RW: Empirical threshold values for quantitative trait mapping. Genetics1. 1994, 38: 963-971.Google Scholar
- Clapcott S: Localization of Genes Controlling Resistance to Trypanosomiasis in Mice (Mus musculus L.). PhD thesis. 1998, Conducted at the University of Liverpool, UKGoogle Scholar
- Darvasi A: Interval specific congenic strains (ISCS): an experimental design for mapping a QTL into a 1-centimorgan interval. Mammalian Genome. 1997, 8: 163-167. 10.1007/s003359900382.PubMedView ArticleGoogle Scholar
- Fehr C, Shirley R, Belknap JK, Crabbel JC, Buck KJ: Congenic Mapping of Alcohol and Pentobarbital Withdrawal Liability Loci to a <1 Centimorgan Interval of Murine Chromosome 4: Identification of Mpdz as a Candidate Gene. The Journal of Neuroscience. 2002, 22: 3730-3738.PubMedGoogle Scholar
- Baguet A, Epler J, Wen KW, Bix M: A Leishmania major Response Locus Identified by Interval-specific Congenic Mapping of a T Helper Type 2 Cell Bias-controlling Quantitative Trait Locus. Journal of Experimental Medicine. 2004, 200: 1605-1612. 10.1084/jem.20040334.PubMed CentralPubMedView ArticleGoogle Scholar
- Crabbe JC, Dudek BC: Genetics of mouse behavior, interactions with laboratory environment. Science. 1999, 284: 1670-1672. 10.1126/science.284.5420.1670.PubMedView ArticleGoogle Scholar
- Sambrook J, Fritsch EF, Maniatis T: Molecular Cloning a Laboratory Manual. 1989, Cold Spring Harbor Laboratory Press, NYGoogle Scholar
- Kruglyak L, Lander ES: A nonparametric approach for mapping quantitative trait loci. Genetics. 1995, 139: 1421-1428.PubMed CentralPubMedGoogle Scholar
- Haley CS, Knott SA: A simple regression method for mapping quantitative trait loci in line crosses using flanking markers. Heredity. 1992, 69: 315-324.PubMedView ArticleGoogle Scholar
- Ronin YI, Korol AB, Weller JI: Selective genotyping to detect quantitative trait lociaffecting multiple traits: interval mapping analysis. Theoretical and Applied Genetics. 1998, 97: 1169-1178. 10.1007/s001220051006.View ArticleGoogle Scholar
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