Nov 19, 2009 - Key words: Heligmosomoides bakeri, Heligmosomoides polygyrus, QTL, resistance, .... Hpnr1 to Hpnr8 for H. polygyrus nematode resistance.
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Quantitative trait loci for resistance to Heligmosomoides bakeri and associated immunological and pathological traits in mice : comparison of loci on chromosomes 5, 8 and 11 in F2 and F6/7 inter-cross lines of mice J. M. BEHNKE 1*, D. M. MENGE 2#, S. NAGDA 2, H. NOYES 3, F. A. IRAQI 2·, S. J. KEMP 3, R. J. M. MUGAMBI 2, R. L. BAKER 2, D. WAKELIN 1 and J. P. GIBSON 2" 1
School of Biology, University of Nottingham, Nottingham NG7 2RD, UK International Livestock Research Institute (ILRI), P.O. Box 30709, Nairobi, Kenya 3 School of Biological Sciences, University of Liverpool, Liverpool L69 7ZB, UK 2
(Received 23 March 2009; revised 9 June and 15 June 2009; accepted 15 June 2009; first published online 19 November 2009) SUMMARY
A comparison of F2 and F6/7 inter-cross lines of mice, derived from CBA and SWR parental strains, has provided strong evidence for several previously undetected quantitative trait loci (QTL) for resistance to Heligmosomoides bakeri. Five QTL affecting average faecal egg counts and/or worm burdens in week 6 were detected on mouse chromosomes 5 (Hbnr9 and Hbnr10), 8 (Hbnr11) and 11 (Hbnr13 and Hbnr14). Three QTL for faecal egg counts in weeks 4 and 6 were found on both chromosomes 5 (Hbnr9) and 11 (Hbnr13 and Hbnr14). Two QTL for the mucosal mast cell protease 1 (MCPT1) response were located on chromosomes 8 (Hbnr11) and 11 (Hbnr13), two for the IgG1 antibody response to adult worms on chromosomes 5 (Hbnr10) and 8 (Hbnr11), two for PCV in week 6 on chromosomes 5 (Hbnr9) and 11 (Hbnr13), and two for the granulomatous response on chromosome 8 (Hbnr12) and 11 (Hbnr15). Our data emphasize that the control of resistance to H. bakeri is multigenic, and regulated by genes within QTL regions that have a complex range of hierarchical relationships. Key words: Heligmosomoides bakeri, Heligmosomoides polygyrus, QTL, resistance, nematodes, antibody, IgG1, Mcpt1, MCPT1, granulomatous response.
INTRODUCTION
As resistance of gastrointestinal (GI) nematodes to currently available anthelmintics continues to spread around the globe (Kaplan, 2004 ; Gilleard, 2006), the need to develop genetically resistant breeds of livestock, as an alternative measure for controlling infections among domestic animals, becomes even more acute (Kloosterman et al. 1992 ; Waller, 2006 ; Stear et al. 2007). It is now well established that resistance, like other genetic traits, can be manipulated by selective breeding of animals to enhance their * Corresponding author : School of Biology, University of Nottingham, Nottingham NG7 2RD, UK Tel : +44(0)115 951 3208. E-mail jerzy.behnke@nottingham. ac.uk # Current address : Center for Infectious Diseases and Microbiology Translational Research, University of Minnesota, MTRF 2001 6th St SE, Minneapolis MN 55455, USA. · Current address : Department of Clinical Microbiology and Immunology, Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, Israel. " Current address : The Institute for Genetics and Bioinformatics, University of New England, Armidale, NSW 2351, Australia.
capacity to control infection (Albers and Gray, 1987 ; Kloosterman et al. 1992 ; Bishop and Morris, 2007), but the lack of reliable genetic markers that are linked closely with genes for resistance, means that this is still a very imprecise art, requiring the evaluation of breeding stock by conventional methods based on tests of acquired worm burdens under experimental or field conditions, or failure to lose condition (production traits) under high worm challenge (Baker et al. 2003 ; Stear et al. 2007). Although considerable progress has been made in livestock genetics, especially in breeding for resistance and resilience to infection with GI nematodes (Dominik, 2005), a complementary approach has exploited mouse models that facilitate much more rapid progress because of their relatively short generation times (Behnke et al. 2003 a). The parallel search for the genes that control GI nematode infections in mice, and the identification of the alleles that impart resistance, has made some progress in recent years, but even this has been disappointingly slow and, perhaps surprisingly, even today no specific genes have been clearly identified as the key players in mouse models of infection (Peters et al. 2007 ; Behnke et al. 2009).
Parasitology (2010), 137, 311–320. f Cambridge University Press 2009 doi:10.1017/S0031182009991028 Printed in the United Kingdom
J. M. Behnke and others
Earlier, based on an F2 inter-crossed resource population of mice derived from resistant SWR and susceptible CBA strains, we identified 7 QTL located on 6 chromosomes for traits associated with resistance to worm infections (Iraqi et al. 2003). Subsequently, we described a range of additional QTL for the individual immunological traits associated with resistance (Menge et al. 2003). Our study clearly indicated that the situation was complex with many genes involved, alleles for resistance not only residing in mouse strains known to be strongly resistant to infection, but also in some cases in a susceptible strain where their full expression was presumably overshadowed by alleles facilitating poor responsiveness to infection and allowing the persistence of chronic infections (Iraqi et al. 2003). In a subsequent publication, exploiting F6/7 intercross lines, we focused on chromosomes 1 and 17 where the most prominent QTL with the highest LOD scores for resistance traits were observed in the F2 study (Behnke et al. 2006 a). We were able to confirm QTL on both chromosomes and refined the locus of the QTL on Mmu 17 in particular. The QTL on Mmu1 proved more difficult to refine further. It is known to reside in a relatively gene-poor region centred on a recombination ‘ cold spot ’, but nevertheless progress is being made to identify the key gene/s involved (Behnke et al. 2009). In this paper we report strong evidence for significant QTL identified on chromosomes 5, 8 and 11 by analysis of the F6/7 data. Additional support for the existence of these QTL is provided by reanalyses of data for the same chromosomes in the F2 study which shows clear indications of the existence of candidate QTL that were not statistically significant but had estimated effects in the same direction as those detected in the F6/7.
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exposure to infective larvae each week. The traits recorded were faecal egg counts at weeks 2, 4 and 6 (FEC2, FEC4 and FEC6), worm counts in week 6, blood packed cell volume at week 2, 4 and 6 (PCV2, PCV4 and PCV6), the granulomatous response in week 6, specific IgG1 antibody response to adult worm antigens (IgG1 to Ad) in week 6, specific IgG1 antibody response to L4 larvae (IgG1 to L4) in week 6, specific IgE antibody response to L4 larvae (IgE to L4) in week 6 and the mast cell protease response in plasma samples (MCPT1) in week 3. Details of the methods used for infection, the methods of recording traits and the observed changes in worm burdens, faecal egg counts and associated immunological responses have all been thoroughly documented in earlier publications (Behnke et al. 2003 b, 2006 a,b). Genetic methods This study reports data on the QTL identified using an F2 resource population of 516 mice obtained from crosses of the susceptible CBA mouse strains with the highly resistant SWR mouse. A subsequent study was based on selective genotyping of a larger resource population of 1100 mice of an F6/F7 advanced intercross line developed through strategic breeding at the International Livestock Research Institute in Nairobi, Kenya. Both maximum likelihood and least squares analyses were carried out and chromosomewide thresholds for significance of tests of the presence of a QTL were obtained by permutation testing. The results are presented in the figures as F ratios. The conventional LOD 2 threshold is equivalent to about a 4.76 F ratio, and this gives an approximate value for visual interpretation of the figures. Full details of study design, statistical methods and software employed for detection and evaluation of QTL were presented by Iraqi et al. (2003), Menge et al. (2003) and Behnke et al. (2006 a).
MATERIALS AND METHODS
Parasites and mice
Naming the QTL
This study is based on infections in mice with the trichostrongyloid intestinal nematode Heligmosomoides bakeri that, until recently, was known as H. polygyrus and H. polygyrus bakeri (but see Cable et al. (2006) and Behnke et al. (2009)). In older literature this parasite has also been referred to as Nematospiroides dubius (Behnke et al. 1991). This study is based on the F6/7 hybrids of CBA and SWR parental mice that differ genetically in their ability to deal with internal parasite infections. CBA are less resistant to intestinal nematode infections compared to SWR mice. When CBA mice are exposed to weekly infections with H. bakeri, worm burdens accumulate for 5–6 weeks. In contrast, in SWR mice, worm burdens are controlled from week 2 onwards and then decline, so that by week 6 virtually all mice are without adult worms, despite continued
We adhered to the nomenclature policies of the International Committee for Standardized Genetic Nomenclature for Mice (http://www.informatics. jax.org/nomen/, Eppig 2006). The 8 QTL discovered in previous studies were originally named Hpnr1 to Hpnr8 for H. polygyrus nematode resistance by Mouse Genome Informatics (MGI). Since the name of H. polygyrus has now changed to H. bakeri MGI has now changed these names to Hbnr. The 7 QTL described here were named Hbnr9 to Hbnr15 in numerical order as shown in Table 1, beginning with Mmu5, then Mmu 8 and Mmu11. Identification of haplotype differences Boundaries of haplotypes (NCBI37) identified within the Perlegen SNP data set were downloaded
QTL for resistance to H. bakeri
RESULTS
Chromosome 5 – parasitological traits In the F2 study we found evidence for 1 QTL controlling a parasitological trait, FEC4. This was also significant in the F6/7 study and mapped within the confidence limits of the original QTL (57 cM, MGD). However, the F6/7 study also revealed QTL for FEC6, average FEC and worm counts in the same chromosomal region (Table 1, Hbnr9/ Hbnr10, and Fig. 1). The additive effects of all these significant QTL for parasitological traits were negative, indicating that the alleles for resistance (lowering the mean value of the trait) came from SWR mice.
F-ratio
10 9 8 7 6 5 4 3 2 1 0
A
0
10
20
FEC2 FEC4 FEC6 Average FEC Worm counts
Hbnr10
Hbnr9
81
30
40
50
259
58
60
70
80
20 172 239
90
210
100
139
F6/7 distance and marker positions 6
FEC2 FEC4 FEC6 Average FEC Worm counts
B
5
F-ratio
4 3 2 1 0 0
10
20
30
48
81
40
50
58
20
60
70
80
90
210 30 221 239
F2 distance and marker positions
F-ratio
from http://mouse.perlegen.com/mouse/download. html (Frazer et al. 2007). Mouse strains were allocated to haplotypes at each haplotype block using a local Perl script that extracted all alleles from the Perlegen dataset within a haplotype block, aligned them on the basis of genomic positions provided with the data and submitted them to the Jukes-Cantor algorithm in DNADIST in PHYLIP to calculate genetic distances between strains (Felsenstein, 2005). The distribution of distances was examined and a threshold of 0.01 was selected, such that strains within a genetic distance of 0.01 were considered to share the same haplotype. C57BL/6 was used as the reference strain (see Supplementary methods (Online version only) for a more detailed description of this method). Haplotype assignments for each haplotype block are shown in Supplementary data (Online version only) : File_Haplotype_distances_ and Candidate_Genes.xls. Gene positions were downloaded from Ensembl52. For all haplotypes for which CBA and SWR had different alleles, the genes within the haplotype were obtained and are shown in the Supplementary data (Online version only). Where there were no genes within the haplotype block the names of the nearest upstream and downstream genes were recorded in the list.
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12 11 10 9 8 7 6 5 4 3 2 1 0
C
IgG1 to adult worms PCV week 6
Hbnr9 Hbnr10
0
81
10
20
30
58
40
259
50
60
70
20 172 239
80
210
90
100
139
F6/7 distance and marker positions
Fig. 1. F-ratios for QTL for parasite (A and B) and immunological/pathological (C) traits on chromosome 5 as detected in the F6/7 (A and C) and F2 (B) resource populations. Markers used in both studies are given on the figures and the numbers correspond to D5Mit.
Chromosome 8 – parasitological traits Chromosome 5 – immunological traits No significant QTL for immunological traits were detected in the F2 study on Mmu5, but two significant QTL were found in the F6/7 study, one for the IgG1 antibody response to adult worm antigens, mapping within the confidence limits of the QTL for the parasitological traits (Hbnr10), and another for PCV6 located more proximal but still within the confidence limits of the parasitological traits (Table 1, Hbnr9 and Fig. 1C). The additive effects for both of these QTL were positive indicating that the alleles from SWR raised the value of the trait, consistent with a resistance allele.
The F2 study revealed 3 significant QTL for parasitological traits, i.e. FEC2 and FEC4 and average FEC (Table 1 and Fig. 2B). Only the QTL for average FEC was confirmed in the F6/7 study, although as can be seen from Fig. 2A, there was a strong indication that all parasitological traits were affected by the same chromosomal region (Hbnr11). Perhaps surprisingly, the additive effects are mostly positive suggesting that SWR alleles in this case impair resistance. Chromosome 8 – immunological traits The 2 QTL for immunological traits map also within the confidence limits of the QTL for parasitological
QTL-ID
Chr
PCV week 6 Worm counts Worm counts FEC4 FEC4 FEC6 FEC6 Average FEC Average FEC IgG1 to Ad IgG1 to Ad Worm counts Worm counts FEC2 FEC2 FEC4 FEC4 Average FEC Average FEC Granulomatous Granulomatous MCPT1 MCPT1 IgG1 to Ad IgG1 to Ad PCV week 6 Worm counts Worm counts FEC2 FEC2 FEC4 FEC4 FEC6 FEC6 Average FEC Average FEC
Hbnr9
5 5 5 5 5 5 5 5 5 5 5 8 8 8 8 8 8 8 8 8 8 8 8 8 8 11 11 11 11 11 11 11 11 11 11 11
F6/7 F2 F6/7 F2 F6/7 F2 F6/7 F2 F6/7 F2 F6/7 F2 F6/7 F2 F6/7 F2 F6/7 F2 F6/7 F2 F6/7 F2 F6/7 F2 F6/7 F6/7 F2 F6/7 F2 F6/7 F2 F6/7 F2 F6/7 F2 F6/7
Hbnr9/Hbnr10 Hbnr9 Hbnr9/Hbnr10 Hbnr10 Hbnr10 Hbnr11 Hbnr11 Hbnr11 Hbnr11 Hbnr12 Hbnr11 Hbnr11 Hbnr14 Hbnr13/Hbnr14 Hbnr13/Hbnr14 Hbnr13/Hbnr14 Hbnr13/Hbnr14 Hbnr13/Hbnr14
Pos. (cM) F6/7
Pos. (cM) F2 (MGD)a
LOD score
4 — 8 — 13 — 5 — 49 — 26 — 70 — 72 — 66 — 69 — 16 — 103 — 95 184 — 187 — 173 — 188 — 183 — 185
29.8 77 31.7 57 34 36 30.3 57 48.8 83 39.9 27 39.8 33 40.5 28 38.5 28 39.5 45 23.7 14 50.1 15 47.1 58.76 55.82 55.19 17.02 56.03 59.35 59.33 47.3 58.61 57.7 58.9
4.3 1.1 3.4 2 3 1 2.76 1 2.7 0.9 3.1 1.4 2.9 2.1 1.2 2.5 1.8 3.3 2 0.9 3 2 2.1 0.4 2.2 3.1 2.1 9.7 0.5 3.2 1.7 6.6 1.2 4.7 1.3 6.8
2 QTL Model
F-Ratio
Additive effects (s.d.)
Dominance effects (s.d)
10.22** 2.6 8.0** 4.78* 6.96* 2.39 6.43* 2.32 6.34* 2.1 7.28** 3.16 6.81* 5.03* 2.73 5.80** 4.11 7.84** 4.70* 2.02 7.01* 4.78* 4.86* 0.82 5.1* 7.3* 4.89 16.0* 1.07 7.6* 3.97 15.6* 2.8 11.2* 3.06 16.2*
0.302 0 x0.274 x0.314 x0.304 x0.3 x0.167 x0.176 x0.214 0.207 0.239 0.298 0.12 0.321 0.129 0.202 0.116 0.248 0.069 0.105 0.317 0.276 0.278 0.055 x0.254 0.272 x0.235 x0.48 0.065 x0.245 x0.252 x0.374 x0.243 x0.291 x0.174 x0.303
0.314 0.464 x0.554 x0.118 x0.304 0.04 x0.442 x0.023 0.038 x0.092 x0.199 x0.283 0.532 x0.493 0.135 x0.493 0.282 x0.379 0.28 x0.281 x0.201 x0.158 x0.373 0.178 0.065 0.028 x0.164 x0.308 x0.2 x0.083 0.072 x0.309 x0.091 x0.416 x0.082 x0.263
Pos1b
Pos2b
5(30.3)
49(48.5)
3(29.4)
51(48.5)
90(35.13)
186(59.04)
127(45.81)
168(54.31)
52(20)
187(59.18)
91(35.5)
182(58.44)
90(35.13)
185(58.9)
CI (cM)c 0–19(28–36.7) 0–83 0–71(28–58.5) 0–83 0–75(28–60) 0–83 0–76(28.0–60.4) 0–82 1–83.5(37.2–63.3) 0–83 15–99(34.9–68.8) 0–45 48–174(34.2–60.9) 0–45 9.5–164.5(20.6–59.9) 0–37 10–174(20.8–59.9) 24–36.5 41.5–168.5 0–45 0–151(16–58.4) 9–31 0–155(16–58.9) 0–45 13.5–157(22.5–59.2) 85.5–250(30.57–74.07) 32–73 66–193(23.53–60.39) 0–75.6 39–197(17.81–61.33) 0–69.4 42–217(18.51–65.77) 5.1–75.6 61–195(21.73–60.86) 0–75.6 48–191(19.91–59.92)
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Trait
Mapping Pop.
J. M. Behnke and others
Table 1. Comparison of location and effects of QTL for parasitological traits in the F2 and F6/7 resource populations for chromosomes 5, 8 and 11
Interpolated back from the expanded F6/7 map position to the F2 mouse genome database (MGD) map positions. * P
