Interval Mapping of Quantitative Trait Loci Controlling ...

Interval Mapping of Quantitative Trait Loci Controlling Humoral Immunity to Exogenous Antigens Evidence that Non-MHC Immune Response Genes May Also Influence Susceptibility to Autoimmunity' Jian-mingW U , ~ * + Jeffery A. Longmate,* Crazyna A d a m u ~ ,Paul ~ ~ A. Hargrave,§ and Edward K. Wakeland4*+ IgC Ab titers elicited to bovine rhodopsin in CFAdiffer 8- to 10-fold between H F identical inbred strainsA.SW/snJ (high responder) and SJL/snJ (low responder). This variation in IgC Ab titer resulted from a dramatic difference in the rise in Ab titer occurring during the maturation of the T-dependent humoral immune response. To determine the positions of non-MHC genes controlling this quantitative variation in T-dependent humoral immune responsiveness, 206 reciprocal (A.SW/snJ X SJL/snJ)F, female progeny were immunized and assayed for anti-rhodopsin responsiveness. The genomes of these progeny were screened with 115 polymorphic simplesequence repeat markers covering >90% of the mousegenome. Interval mapping analysis localized the positions of these non-MHC immune response genes to genomic intervals on chromosomes 1, 5, and 13. Interestingly, thesethree intervals coincide exactly with three intervals recently shown to contain genes contributing to susceptibility to systemic lupus erythematosus and/or the production of autoimmune anti-dsDNA Abs. These results suggest that some genes affecting levels of humoral immune responsiveness to exogenous Ag may also play a role in genetic susceptibility to humoral autoimmune diseases. Analyses of the modes of inheritance demonstrated that high responder alleleswere inherited from both parental genomes, indicative of epistatic interactions among genes influencing humoral immune responsiveness. The Journal of Immunology, 1996,157: 2498-2505.

T

he genetic basis for quantitative variations in humoral immune responsiveness has been investigated for over two decades ( I ) . Early studies demonstrated the importance of genes encoded within the MHC in dictating immune responsiveness to numerous Ags (2-4),and the immune response (Ir)s gene properties of MHC class I1 molecules have been characterized in detail (forreview, see Refs. 5 and 6). In contrast, despite the presence of substantial evidenceindicating that nonMHC genes also contribute tothe control of Ab responsiveness, little information about the properties of non-MHC Ir genes is currently available (7-17).

'Center for Mammalian Genetics, College of Medicine; 'Department of Pathology and Laboratory Medicine; *Division of Biostatistics, Department of Statistics; 'DepartmentofOphthalmology,CollegeofMedicine.UniversityofFlorida, Gainesvilie. FL 32610 Received iorpublicationJanuary 12, 1996.

25,1996.

Acceptedforpublicationlune

The costs o i puhllcation of thls article were defrayed in part by the payment of page charges. T h s article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

'

This work was supported by Public Health Service Grants AI-1 7966 and AR42563 to E.K.W. and EY-06225, EY-06226, and EY-09571 to P.A.H. from the Natlonal Institutes of Health. Current address: The Department of Neurology, Johns HopklnsSchool of Medicine, Myer Buildlng 5-1 19, 600 N. Wolfe Street, Baltimore, MD 21287-7519. I Current addres: The K. S. D o w Neurological Sclence institute, 1120 N.W. 20th Avenue, Portland, O R 97209.

Address correspondence and reprintrequests to Dr. Edward K. Wakeland, Center ior Mammalian Genetics, College of Medicine, University of Florida, Cainesville, FL 32610. Abbreviations used In this paper: lr, immune response; SSR, simple sequence repeat; QTL, quantitative trait locus; SLE, systemic lupus erythematosus; Rh, rhodopsin; HEL, hen egg lysozyme Copyright 0 1996 by The American Association of lmmunologlsts

Classic studies by Biozzi and co-workers demonstrated that non-MHC Ir genes strongly impacted quantitative variations in the titers of Abs produced against many Ags (7, 8). These investigators used bi-directional selective breeding to establish a collection of high andlow responder mouse strains exhibiting as much as 250-fold variations in Ab titers to specific Ags (8). Analyses of the F, and F, intercrossprogeny via traditional quantitative genetic techniques led to an estimation of 5 to 10 genes affecting Ab titers. These workers also hypothesizedthatthe same genes were involved in controlling Ab titers against many different Ags. basedontheobservation that selection for high responsiveness to one Ag simultaneously selected for high responsiveness to other Ags (7, 18-21), Recent advances in molecular genetics have resulted in the development of molecular tools and analytical procedures that allow a detailed characterization of the inheritance of quantitative variations in complex traits such as immune responsiveness (22-28). The description of over 4000 highly polymorphic simple sequence repeat (SSR) marker loci in the mouse genome (241, and the availability of sophisticated computer programs for the generation of linkage maps (29) and localization of quantitative trait loci (QTL) (22),have made feasible an assessment of the number and location of non-MHC Ir genes affecting humoral Irs. A recent genome scanning study of two of Biozzi's strains using these techniques led to the detection of loci potentially affecting immune responsiveness on chromosomes 4, 6 (near CD8 or Ig kappa), 12 (near IgH), and 17 (near H 2 ) (30). We have used this methodology to identify regions of the genome containing loci effecting susceptibility to systemic lupus erythematosus (SLE)(28) and have also been interested in identifying the positions of QTL loci affecting humoral immune responsiveness. An 0022-1 767/96/$02.00

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opportunity to assess the inheritance of QTLs affecting humoral immunity arose from observations by Adamus and co-workers conceming murineimmune responsiveness to bovine rhodopsin (Rh) (31).Rh is a photoreceptor molecule uniquely expressed in an immunologically privileged site (the eye). Although bovine Rh can induce a form of experimental autoimmune uveitis in some mouse strains as a consequence of aggressive immunization protocols (32), immunization of mice with bovine Rh in CFA commonly results in the production of Abs specific for epitopes throughout the molecule, in the absence of detectable autoimmunity (31). Whlle producing a battery of mAbs specific for Rh via such immunization protocols, Adamus and coworkers found that the levels of IgG anti-Rh Abs elicited by immunization with bovine Rh varied quantitatively among inbred strains and that both MHC and non-MHCgenes contributed to this variation in Ab responsiveness (31). Although the variations in anti-Rh titers among standard inbred strains were about sevenfold less than those reported for Biozzi’s strains, this system has the advantage of allowingbreeding strategies that exclude the MHC as a segregating component. Here we report an interval mapping analysis of the inheritance of immune responsiveness to bovine Rh via an F, intercross of the H2 identical strains A.SW and SJL. The locations of three strong QTLs were identified, all of which mapped into genomic intervals previously shown to be associated with susceptibility to SLE in the NZW/NZB model. The modes of inheritance and the parental origins of high responder alleles indicate that the inheritance of Ab responsiveness is genetically interactive and complex.

Materials and Methods Mice Initial breeder pairs for A/J, A.SW/snJ, and SJL/snJ were purchased from The Jackson Laboratory (Bar Harbor, ME). All mice used in this study were bred and maintained in a specific pathogen-free environment in our colony at the University of Florida. Only female mice 16 to 20 wks of age were used for the analysis of humoral immune responsiveness to bovine Rh. Intercross progeny were produced by mating A.SW/snJ with SJL/snJ, and their F, progeny were mated to produce a total of 206 female F? progeny.

Immunization The F, mice were bred and immunized in 4 groups of about 50 mice, because of logistic and colony constraints. Purified membrane-bound bovine Rh was prepared as described previously (33), suspended in PBS ( I mg/ml), and emulsified with CFA (Sigma Chemical Co.). Each mouse was injected i.p. with 200 pl of emulsion containing I 0 0 p g of bovine Rh. Blood samples were collected at various times via the orbital sinus. and serum samples were harvested by standard procedures.

Antibody assay An indirect immunosorbent binding assay was used to determine the titers of anti-Rh IgM and IgG Abs in serum samples as described previously (34, 35). The titers for all samples, both F, progeny and parental strains, were measured in a single large assay to minimize experimental variation. Briefly, microtiter plates (Coming, NY)were pre-coated with Rh (2 pg/ml) and nonspecific binding was blocked with BSA. Diluted samples (100 pl) were added and incubated at room temperature for 2 h, followed by incubation with goat anti-mouse IgM or IgG alkaline phosphatase conjugate (Sigma). Color reactions were developed by alkaline phosphatase substrate (nitrophenyl phosphate; Sigma),and absorbance at 450nm was determined on a microplate reader (Molecular Devices, Palo Alto, CA). Each sample was titrated in fourfold dilutions ranging from 1:lOO to 1: 102400, The IgM and IgG titration curves for each sample were plotted, and Ab titers were determined as the log,,, values of the maximum serum dilutions yielding 1 .O absorbance at 450 nm.

Genotypic analysis Genomic DNA was prepared from liver tissue using standard techniques (36). Primers of SSR markers were synthesized according to previously published sequences (24) or purchased as Mappairs (Research Genetics, Huntsville, AL). Genomic DNA (50 ng) was PCR amplified in 15.~1re-

actions with 0.3 p M of synthesized primers or 0.1 pM of Mappair primers, 0.2 mM of dNTPs (Pharmacia, Uppsala, Sweden), 0.75 U of Taq DNA polymerase (Boehringer Mannheim, Indianapolis, IN), in a standard incubation buffer with 1.5 mM MgCI,. Amplifications were conducted in a Perkin-Elmer Cetus 9600 thermal cycler (Norwalk, CT) under the following conditions: 1 cycle at 94°C for 2 min; 35 cycles at 94°C for 30 s, 50 to 62°C for 45 s, and 72°C for 30 s; and 1 cycle at 72°C for 2 min. The optimal annealing temperature (which varied from 50 to 62°C among the selected SSR primer pairs) was determined for each primer pair. For loci with size differences between A.SW/snJ and SJL/snJ alleles greater than 8 to I O bp, the PCR products were electrophoresed and visualized on 3% agarose gels (Fisher, Fair Lawn, NJ), stained with 5 pg/ml of ethidium bromide (Sigma). For loci with smaller allelic size differences, the PCR products were visualized by electrophoresis on 8% polyacrylamide gels, with 30% urea, and visualized by staining with ethidium bromide. Linkage relationships between the 115 polymorphic markers were determined by analysis of their segregation patterns among the 206 F, progeny using the MAPMAKER-EXP (29) computer package as previously described (28). The positions of all anchor loci were obtained from the GBASE (37) and MIT maps (24). Linkage groups for each chromosome were established and distances between adjacent markers were calculated using Kosambi’s mapping function. The percentage of the mouse genome covered by markers was estimated assuming that each marker covered I O cM in both directions.

Genetic analysis of quantitative trait loci affecting the humoral immune response to bovine rhodopsin The Ir phenotype for each F, progeny was determined by two methods: I ) the anti-Rh IgG Ab titer; and 2) the normalized Ab titer. The Ab titers for the 206 F, progeny were normalized for experimental variance in Ab titer between the four experimental groups of F, progeny by subtracting the mean titer for each experimental group of F? progeny from the titer of each individual in the group. Analysis of both values identified the same QTLs, however, normalization for variation between experimental groups was clearly beneficial. Consequently, results obtained with the normalized values are presented. Interval mapping was performed using the MAPMAKER-QTL package (22, 38), which makes efficient use of flanking marker information to improve the detection of genes between markers. A theoretical treatment of the potential power of interval mapping for the detection of QTLs has been published (38), and the choice of 20 cM spacing for marker loci is based on guidelines suggested by Lander and Botstein. The proportion of total variance in IgG Ab titer attributable to genetic variation was estimated using standard analysis of variance methods (39), and the percentage of total variance attributable to individual loci was calculated using the MAPMAKER-QTL (22, 38). The joint effect associated with peak markers was modeled by standard analysis of variance methods (40). The modes of inheritance and origins of high Ab mediating alleles in mapped QTL intervals were determined by comparing the mean anti-Rh IgG titers for different genotypes at peak markers using the Student t test and verified with MAPMAKER-QTL.

Results Genetic control of humoral immune responsiveness to bovine rhodopsin

Previous studies demonstrated significant variations in the titers of anti-Rh IgG Abs elicited by immunization of various inbred mouse strains with bovine Rh (31). These findings suggested that both MHC and non-MHC Ir genes impacted responsiveness, and consequently, we initiated a series of experiments to identify a strain combination that could be used to map the positions of non-MHC Ir genes affecting humoral immunity to Rh. To minimize intrastrain variation in humoral responsiveness, only age-matched (16-20 wk of age), female mice were used for all experiments. The relative contributions of MHC and non-MHC Ir genes controlling Rh responsiveness were assessed by comparing the antiRh Ab titers produced by SJUsnJ ( H T ) , A.SW/snJ ( H T ) , A/J ( H T ) , (A.SW/snJ X SJL/snJ)F, hybrid, and ( N J X SJL/snJ)F, hybrid mice. As illustrated in Figure 1, significant variations in the log,, titers of IgG anti-Rh Abs were elicited by immunization of these strains with 100 pg of bovine Rh in CFA. A/J and SJL/snJ,

2500

POLYGENIC INHERITANCE OF HUMORALIMMUNERESPONSIVENESS 5 0

4.5 4 3.5

~

0 Strain

Mhc

SJL

A.SW

NJ

"2'

H-2"

H-2'

sJL

Non-Mhc Genome

AIJ AIJ

Fl(A.SWxSJL) Fl(AIJxSJL) H-2'

H-2' I H-2'

SJLI NJ

SJL/ AIJ

Anti-Rh IgG Ab responses by various mouse strains. Mice were immunized with 100 pg of Rh in CFA, and anti-Rh IgG Ab titers were assayed at day 28. Eachbar representsthemeananti-Rh IgG titer t SD ( n = 5). FIGURE 1.

h

..i :

:

0

SJL

A.SW

F1

16

21

24

F2 47

FIGURE 3. Range of Ab titers elicited by immunization with Rh in A.SW/snJ, SJL/snJ, their F, hybrid, and F, progeny. Mice were immunized with 100 pg of Rh and anti-Rh IgC Ab titers was determined at day 28. Each dot represents the Ab titer for a single mouse in each strain and the number of mice assayed is listed below each strain. The horizontal lines indicate the mean Ab titers for each strain.

4 -

PI

14

21

1

20

35

Days After Immunization FIGURE 2. Kinetic analysis of IgM and IgC Ab responsesto Rh in A.SW/snJ, SJL/snJ,and their F, hybrid. Mice were immunized with100 pg of Rh in CFA and anti-Rh IgM and IgG Ab titers were determined at days 14, 21, 28, and 35. PI represents the Ab titer of preimmune sera. Data are expressed as mean Ab titer 2 SD ( n = 5).

which differ for both MHC and non-MHC Ir genes, had the greatest disparity, with A/J mice producing roughly 36 times more IgG Ab (4.90 -C 0.14, n = 5 ) than SJWsnJ (3.34 ? 0.09, n = 5; p < IOp5). The MHC Ir genes in the H2" haplotype of A/J mice were responsible for about one-half of this increase in IgG Ab, as illustrated by comparison of A/J to the H2"-congenic A.SW/snJ strain The remainder of the variation (4.09 -t 0.13, n = 5 ; p < reflects the contribution of non-MHC Ir genes, as illustrated by comparison of the anti-Rh titer elicited in the H2 identical strains A.SW/snJ and SJWsnJ (4.09 2 0.13 vs 3.34 ? 0.09, p < lop5). Both (A/J X SJL/snJ)F, hybrids (4.88 2 0.32, n = 5 ) and (A.SW/ snJ X SJL/snJ)F, hybrids (4.13 ? 0.23, n = 5 ) were high responders, consistent with the dominant inheritance of high responsiveness for both MHC and non-MHC Ir genes, if this were a case of simple Mendelian inheritance. Mode of action of non-MHC immune response genes

The manner in which non-MHC Ir genes affect the development of the anti-Rh humoral response was examined by quantitative analysis of the kinetics of IgM and IgG anti-Rh responsiveness in

A.SW/snJ, SJL/snJ, and their F, hybrid. As shown in Figure 2, A.SW/snJ and SJWsnJ produced similar levels of anti-Rh IgM Ab. Their anti-Rh IgG Ab titers also were similar early in the response (2.95 ? 0.35 and 3.04 ? 0.05, respectively, at day 14), and only began to vary significantly at day 21. The high responsiveness of A.SW/snJ and the F, hybrid predominantly resulted from a rapid rise in Ab titer occurring from day 14 to 28 (4.09 ? 0.16,4.19 0.1 1, respectively, at day 28). This rise was virtually absent in SJWsnJ (3.04 ? 0.05,3.34 2 0.12, at day 14 and 28, respectively). These results indicate that these non-MHC Ir genes predominantly effect the clonal expansion phase of the maturing T-dependent Ir rather than the primary Ir. Assessment of the genetic contribution of non-MHC immune response genes to quantitative variations in anti-rhodopsin IgG antibody

The total variation in humoral immune responsiveness observed between A.SW/snJ and SJWsnJ can be described by V, = V, + V,, where V, is equal to the total variance observed, V, represents the variance due to environmental influences, and V, represents the genetic variance (adapted from Ref. 22). Since all members of an inbred mouse strain have identical germ-line genomes, variations in the titers of individuals within a strain result from "environmental" variations. When dealing with traits of the immune system, environmental variation will include variations resulting from stochastic processes associated with the ontogeny of T and B lymphocytes, as well as normal variation in experimental technique and environmental influences. V, can be estimated as the variance in anti-Rh Ab titers among individuals from the same inbred strains (Le., within A.SW/snJ, SJWsnJ, and (A.SW/sd X SJWsnJ)F, hybrids), while V, can be estimated as the variance among F, progeny (in which all relevant genes are segregating and titers also will vary due to environmental effects). Since estimates of variance require relatively large sample sizes for accuracy, we compared the anti-Rh IgG titers at day 28 from large groups of the parental strains, their F, hybrid, and F, intercross progeny. The data from this experiment are presented in Figure 3, which plots the individual titers observed for anti-Rh IgG Abs from each

2501

The Journal of Immunology

i

Ckmm

Dl Nds4

D7Mil26 -D7M,llB

01MiU2' 01Ml17

-D7Mi137

DlMitll DlMitlBB DlMit30

- D7M1l6.9

DlMitM

\DlMitl4 DlMi136

-D7M,112

DIMi137

c4

c 3c 1

c11

c5

c2

c12

I

C13

C14

C76

C15

c7

C8

c9

C70

C17

C18

c19

cx

1OcM FIGURE 4. Linkage maps of polymorphic SSR markers in F, progeny. Linkage relationships for the 1 15 polymorphic markers were determined by analysis of their segregation patterns among 412 meioses. Genetic maps for each chromosome was established using the MAPMAKER.EXP. Thick stippled bars adjacent to chromosomes indicate regions of genomic coverage by marker loci, assuming that each marker covered a 1 0-cM region in both the proximal and distal directions.

of these groups of mice. Inspection of these results support the notion that intra-strain variations are much less than the amount of variation detected among the F, progeny. Calculations of the variance based on these results yielded: V, = 0.21 ( n = 61) and V, = 0.64 (n = 47), thus indicating that V, = 0.43, or 67% of the total variance observed among the F, progeny. This result, together with the observation that the mean anti-Rh IgG Ab titers of the parental strains differed by A = 6.8 standard deviations, strongly supports the feasibility of identifying the positions of the genes responsible for this variation by interval mapping analysis of the F, progeny. Linkage analysis with simple sequence repeat marker loci

A panel of 206 age-matched, female F, progeny were bred and genotyped with a battery of polymorphic SSR marker loci as previously described (28). In total, more than 450 SSR markers were screened for polymorphisms between the two parental strains and subsequently 1 15 polymorphic markers were selected for maximal coverage of the mouse genome. The linkage groups formed by these markers were deduced using MAPMAKER-EXP as described (24, 29, 37). As shown in Figure 4, this collection of marker loci produced a linkage map covering more than 90% of the murine genome.

Each F, animal was immunized with 100 pg of Rh in CFA and titered for anti-Rh IgG Ab at day 28. Because of the logistics of orchestrating such a large experiment, the 206 F, progeny was bred and immunized in four separate experimental groups, each consisting of about 50 animals. To minimize the introduction of experimental variation in the titers obtained in separate immunizations, all titers were normalized to the mean titer of the specific experimental group (see Materials andMethods). Thus, all anti-Rh IgG Ab titers within the F, progeny have been normalized to a mean of 0, with low responding animals having negative titers and high responding animals having positive values. The positions of QTLs affecting anti-Rh IgG titers were sought using MAPMAKER-QTL and ANOVA analysis with analogous results. As shown in Table I, three genomic intervals associated with anti-Rh responsiveness were detected with log of the likelihood ratio (LOD) scores in excess of the 2.4 threshold recommended by Lander and Botstein, and Paterson et al. (22, 23, 38). The first interval is located in the telomeric region of chromosome I , most closely linked to DlMitlC ( p < 0.0013, LOD 2.94), with a 95% confidence support interval of 20 cM. The second interval is located on the telomeric end of chromosome 5, most closely linked to D5Mit122 ( p < 0.0028, LOD 2.59), with a 95% confidence support interval of about 20 cM. The third interval is located

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INHERITANCE POLYGENIC

RESPONSIVENESS

Linkage analysis of QTLs associated with anti-Rh lgG response

T a b l e I.

Chromosome Distance"

Locusb

16.1 6.8 12.7 2.7 6.7 11.7 0.0 8.0 5.4

1

7.7 14.5 13.4 14.6 6.5

5

13

26.4 14.7 5.8 2.4 3.6 3.7 8.1

p Value'

D 1 Nds4 D 1Mit22* D 1Mit7 DlMitl3 DlMit188 D lMit30 DlMit34 DlMitl4 DlMit36 D7Mit37 D5Mit55* D5Nds2 D5Mit24 D5Mit30 D5Mit43 D5Mit 122

0.1 06 0.0067 0.0028

D 13Mit57 D 13Mit39* D13Mit147 D 13Mit30 D 13Mit74 D 13Mit45 D 13Mit53 D T 3Mit35

0.1 47 0.1 47 0.271 0.021 0.01 7 0.008 0.0025 0.001 5

LODd

Chromosome Distance"

7

0.121 0.001 3 0.001 3 0.0046 0.031

1.04 2.93 2.93 2.35

16

19 2.21 2.59

Locusb

p Value'

LOD"

17.4 4.2 16.9 14.7 12.8

Ckmm D7Mit26 D7Mit 18* D7Mit37 D7Mit68 D7Mit 12

0.101 0.0084 0.0080

1.43 2.20

5.8 21.1 9.9 13.7

D 16Mit9 D 16Mit79* D 16Mit29 D 16Mit14 D 16Mit5

0.082 0.01 7 0.01 3

1.80 1.90

15.7 8.0 20.8 15.4

D 19Mit59 D 19Mit23 D 19Mit30 D 19Mit53 D 19Mit33

0.546 0.008 0.221

2.00

2.05 2.64 3.00

Distance i n c M (Kosambi function) between two consecutive markers as calculated by MAPMAKER.EXP. Markers are arranged from centromeric to telomeric. 'Anchor markers adapted from MIT map. p values of ANOVA analysis. Log of the likelihood ratio (LOD) scores analyzed by MAPMAKER.QTL.

lnheritance modes and QTL allelic origins associated with anti-Rh IgG A b response"

T a b l e II.

Means of Normalized Anti-Rh Titers Origin of High AA

Peak Allele Locus of

Ab Mode

DlMitl4 D5Mit 7 22 D13Mit35

lnheritance

SJL D o m i n a n t * SJL Dominant**

51L SlL

A.SWDorninant***

ASW

-0.25 f 0.07 (34) -0.19 f 0.06 (49) 0.08 f 0.07 (44)

AS

ss

0.06 f 0.04 (1 08) 0.06 2 0.04 (1 00) 0.08 f 0.04 (96)

0.04 ? 0.05 (62) 0.06 ? 0.06 (55) -0.1 6 ? 0.05 (64)

Means of normalized anti-Rh titers (mean 2 SE) for different genotypes (AA, SS homozygous for ASW, SJL, respectively; AS for heterozygous) were calculated according to genotypes at each QTL-associated peak locus. The modes of inheritance were determined by comparing the means of normalized IgC titers of dlferent genotypes with the Student t test at peak loci. SJL dominant (or A S W dominant) was defined as the means of normalized anti-Rh IgG titers for AS and SS (or AS and AA) where both are different from AA (or SS) by the Student ttest ( p < 0.0251, while there was no significant difference between AS and SS (or AA). *AA vs AS, P < 0.01; AA vs SS, p < 0.025; and ASvs SS, p > 0.50. **AA vsAS, p < 0.005; AA vs SS, p < 0.010; and ASvs SS, p > 0.50. ***AA vsAS, p > 0.50; AA vs SS, p < 0.01 ; and ASvs SS, p < 0.005

T a b l e 111.

Contribution of each locus to total genetic variance in

A b titer Chromosomal Contributed lnterval Variance Genetic

chromosome 16 ( p < 0.013, LOD 1.9); and D19MIT53 on the telomeric end of chromosome 19 ( p < 0.008, LOD 2.00). These results may indicate that additional QTLs with relatively weaker effects in this cross are located within these regions.

Strong QTL

cl c5 cl3

11.7 11.8 13.6

Weak QTL

c7 cl6 cl9

9.2 7.3

in the telomeric region of chromosome 13, most closely linked with D13Mit35 ( p < 0.0015, LOD 3.00), with a 95% confidence support interval of 22 cM. In addition to these strong QTLs, three other intervals showed weaker associations with anti-Rh immune responsiveness. These were as follows: D7Mit12 in the telomeric region of chromosome 7 ( p < 0.0084, LOD 2.20); D16MlT5 on the telomeric end of

Modes of inheritance of individual quantitative trait loci

The genotype at the peak marker locus within each interval can be used to determine 10.4the mode of inheritance and the parental origin of high and low responder alleles for that QTL (41-43). As shown in Table 11, the high responder alleles associated with DlMitl4 and D5Mit122 were dominant alleles derived from the SJL/snJ genome. Since SJWsnJ is the low responding parental strain, these results indicate that the effects of these alleles must be modified by other genes in the SJLlsnJ genome, indicating that genetic interactions have a significant influence on the inheritance of immune responsiveness. For Dl3Mit53, A.SW/snJ homozygotes and heterozygotes had significantly higher mean relative IgG quantities than SJL/snJ homozygotes, indicating that the A.SW/snJ strain contains a dominant high responder allele in this interval. These

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The Journal of Immunology

D13Mit57-

D 1 Nds4 D5Mit551

FIGURE 5 . Genetic maps of mouse chromosomes 1 , 5, and 13, each containing a QTL associated with the inheritance of anti-Rh IgG Ab

responsiveness.Numbersbeside chromosomes indicate the distances (cM) between adjacent markers. Lines parallel to chromosomes represent the 95% confidence support intervals for each QTL, and dotted regionsrepresent the overlapped chromosomal interval associated withSLE in different studies (28, 44-46). Candidate genes locatedwithin these intervals are indicated on the right side of each support interval.

D5Nds2

Z6.0

DlMitZ; DlMit7 D5Mit24 -

27

DlMitl: DlMifld

7

D13Mif39.

r~ sie-7. Lbw-7 14.7

D 1 Mit30

D5Mit30 -

Dl3Mit147 58

D13Mit30.

DlMitl4, DlMit3 DlMit31 D5Mit43 -

D 1Mit3

D13Mit74. D13Mit45' D13Mit53.

24

3.6 3.1

51

D5Mit122-

Chromosome 1

results were confirmed by similar analyses using MAPMAKERQTL under fixed modes of inheritance (data not shown). The relative contribution of each QTL to anti-Rh immune responsiveness canbe estimated using MAPMAKER-QTL and analysis of variance (22, 39). As shown in Table 111, the contributions of these three major QTLs were roughly equivalent and jointly accounted for about 35% of the genetic variance detected between the parental strains. Inclusion of the three weaker QTLs adds an additional 25%, accounting for a total of 60% of the genetic variance with all loci detected. The 40% of the genetic variance not accounted for by these QTLs may reflect the accumulative contribution of several weaker loci, or may indicate that epistatic interactions are masking or weakening the contributions of some QTLs.

Discussion This study presents interval mapping analysis of the genomic positions of QTL loci affecting levels of humoral immunity elicited by immunization with exogenous Ag. Our results indicate that quantitative variations in humoral immunity are inherited in a complex fashion, and that genetic interactions or epistasis must play a major role in dictating overall humoral immune responsiveness. Given the complexity of immune interactions and the multitude of genes involved in Irs, this result is not surprising. However, the influence of these genetic interactions on the inheritance of Ir phenotypes will complicate the identification of the causative genes. The support intervals for the three major QTLs detected and a listing of potential candidate genes within these intervals are presented in Figure 5. Several aspects of this result are intriguing. First, the positions of these loci differ from those reported by h e 1 and co-workers in their analysis of responsiveness to SRBC in Biozzi's mice (30). This result is not especially surprising in that classic studies of the genetic inheritance of immune responsiveness suggested that non-MHC Ir genes were often Ag-specific (12-

Chromosome 5

D13Mit35

Chromosome 13

14, 16). In this regard, we have also analyzed the inheritance of humoral immune responsiveness to hen egg lysozyme (HEL) in our cross of A.SW and SJL. In a study that will be published separately (Wu et al., manuscript in preparation). We found that although responsiveness to HEL was identical to that of bovine Rh among the parental strains and F, hybrids, only some of the QTLs were shared between bovine Rh and HEL in this cross. Interestingly, HEL responsiveness did share some loci in common with those reported for Biozzi's mice. Takentogether, these results suggest that polymorphisms at several loci can contribute to humoral immune responsiveness, and that the inheritance of humoral responses to individual Ags will often be affected by specific subsets of these loci, only some of which will be overlapping for any pair of Ags. A second interesting result of our analysis of Rh is that all three of the Rh QTL intervals coincide precisely with genomic intervals previously shown to contain loci associated with susceptibility to murine SLE and/or anti-dsDNA autoantibody production in the NZBNZW model. The interval on chromosome 1 was associated with susceptibility to lupus in three separate crosses of the NZB/ NZW model (28,44,45). Similarly, the Ir locus on chromosome 5 coincides precisely with the interval for Lbw-5 defined by Kono and co-workers ( 4 3 , and two separate studies have linked the telomeric end of chromosome 13 to susceptibility to lupus (44) and the production of anti-dsDNA autoantibodies (28). In addition to these co-localizations, one of the QTLs found by Puel et al. for immune responsiveness to SRBCin Biozzi's mice overlaps precisely with the genomic interval on chromosome 4, which we defined for Sle2 in NZM2410 (28). Taken together,these results suggest that some of the genes associated with responsiveness to exogenous Ags may also influence Ab-mediated autoimmune diseases. Although it is possible that the co-localization of these Ir gene intervals with those predisposing for SLE is coincidental, this is

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statistically unlikely. Thus far, a total of eight intervals have been associated with autoimmunity in the NZB/NZW model (28, 4447). If the mouse genome were divided arbitrarily into 60 distinct 20-cMintervals(consistentwithagenome size of 1200 cM (2411, then the probability of matching three of the eight SLE intervals currently identified by choosing three intervals at random is extremely low ( p < 0,001). Althoughthis statistical exercise does not prove that the same genes are involved with both traits, it indicates that the co-localization of these intervals by chance is unlikely. The notion that the same genes may affect humoral immune responsiveness and susceptibility to B cell autoimmunity is not unreasonable. Our data suggest that the Ir genes affecting anti-Rh responsiveness influence the clonal expansion of B cells subsequent to class switching. This may be mediated by genetic polymorphisms affecting the T and/or B cell lineages. Whatever mechanism(s) are involved, variations in this phase of B cell activation could also influence susceptibility to the development of high titers of IgG autoantibodies recognizing nuclear Ags, which is a key feature of SLE. Thus, genetic polymorphisms that potentiate the rapid expansion of B cell clones activated by exogenous Ag may, when expressed in combination with specific sets of alleles of other polymorphic genes, also potentiate the expansion of autoimmune B cell clones. These genetic polymorphisms probably arise as a consequence of two antagonistic selective pressures that operate on genes whose functions impact immune responsiveness. On the one hand, the extensive antigenic heterogeneity and rapid evolution of pathogenic microorganisms will favor individuals with genomes that potentiate high immune responsiveness. At the same time, the deleterious effects of autoimmunity and auto-aggressive reactions will favor individuals with genomes that potentiate lower immune responsiveness. Given the complexity of host-pathogen interactions and the antagonistic nature of these selective pressures, no single genetic solution will be favored in all situations. As a result, allelic polymorphisms in genes that functionally diversify immune responsiveness will be favored in natural populations. The classic example of this evolutionary process is the extensive polymorphisms of MHC genes (for review, see Ref. 48). It is reasonable to predict that similar selective pressures may influence other genes with functions capable of modulating immune responsiveness. The prevalence of autoimmune diseases may be in part a direct consequence of these polymorphisms. In outbred populations, independently segregating polymorphic genes affecting immune responsiveness will beshuffled into numerous combinations, and some of these combinations will potentiate autoimmunity. This notion predicts that susceptibility to autoimmunity will be inherited as a polygenic, threshold liability (49), in which multiple combinations of susceptibility alleles can potentiate the development of autoimmune diseases with specific degrees of penetrance. Morel and co-workers (28) have recently shown that susceptibility to SLE in the NZM/Aeg2410 model is inherited in this fashion. It is reasonable to predict that some of the alleles predisposing to autoimmunity in one genomic combination will be beneficial to immune responsiveness in other combinations. Consequently, these alleles are only deleterious in specific combinations, thus weakening the ability of purifying selective pressures to decrease their frequencies in natural populations. As a result, genotypic combinations with high susceptibility to autoimmune diseases will be produced with a consistent frequency in outbred populations. Our analysis of the inheritance of immune responsiveness to Rh also provides clear indications that high immune responsiveness will not be inherited in a simple, dominant fashion. Although the analysis of F, hybrids suggested this simple mode of inheritance

OF IMMUNE HUMORAL

RESPONSIVENESS

for immune responsiveness to Rh, the underlying segregation of QTLs was much more complex. In fact, two high responding alleles were inherited in a dominant fashion from the low responder SJLlsnJ genome. This seemingly paradoxical result has been observed in analogous studies of a variety of biologic systems (27, 50, 51) and indicates that genetic interactions and epistasis are modulating the functional expression of these genes. These tindings indicate that our current understanding of the inheritance of immune responsiveness is extremely superficial. A thorough analysis of the genetic interactions mediating the inheritance immune responsiveness to exogenous Ags should provide important new insights into the genetic basis for variations in a variety of immune functions, including resistance to infectious diseases and autoimmunity.

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