Application of Computer Software in Mapping
Quantitative Trait Loci
Chindo Hicks

Chicks@niai.affrc.go.jp

Eiji Kobayashi

ekoba@niai.affrc.go.jp

Kazuo Ishii

Masahiro Satohhereford@niai.affrc.go.jp

Tsutomu Furukawa

kazishi@niai.affrc.go.jp

furukawa@niai.affrc.go.jp

National Institute of Animal Industry, Department of Animal Breeding and Genetics
P.O. Box 5, Tsukuba Norindanchi, Ibaraki-ken 305-0901, Japan

1 Introduction
The process of locating quantitative trait loci (QTLs) using genetic linkage maps, an ordered array ofgenetic markers placed along the chromosome, could be facilitated by applying ecient computer software packages. Construction of linkage maps requires that the rate of recombination be converted todistance in cM using appropriate mapping functions. However, computer software packages di er withrespect to methods of computing relative distance between markers, for example, while Map Manager
QT [3] does not include a mapping function and instead computes recombination frequencies in genetic
linkage map, Mapmaker/QTL [2] includes a mapping function. Furthermore, Mapmaker/QTL computes the LOD score directly, whereas in Map Manager QT it has to be computed from the Likelihood
ratio statistic (LRS). The purpose of this paper is to investigate the e ectiveness of Map Manager QT
in comparison to Mapmaker/QTL in mapping quantitative trait loci.

2 Material and Methods
F-2 mouse data from Horvat and Medrano [1] was used to examine the e ectiveness of Mapmanager
QT in mapping quantitative trait loci. Details regarding experimental design and data structure
are given by Horvat and Medrano. Brie y the data consists of 403 F-2 progeny, (213 females and190 males), scored at 9 genetic markers (microsatellites), with an average density of 3.83 cM. The
measured trait was weight gain from 14 to 63 days. The goal is to locate the high growth (hg) locus(QTL), a region in the mouse genome that increases body weigh and body size. The data was checked
for any missing information. One marker was not informative and hence was removed from the data,
this may cause slight di erence in relative distance between makers in this study and that reportedby Horvat and Medrano. However, the e ect is assumed to be negligible. It was assumed that there
is a single QTL segregating, thus no control for other QTL is envisaged in this study. The data was
not transformed, thus the distribution worked with here is an approximation of normal distribution
and interpretation of the results may therefore be conservative. Two genetic linkage maps one for thefemales and the other for males were constructed and subsequently used for locating QTL using Map
Manager QT. In either case, interval mapping was used on chromosome 10 assuming a free regression
model. The LOD score was computed from the LRS. The results were compared to those reported byHorvat and Medrano computed using Mapmaker/QTL under the unrestricted model and are discussed
in the context of comparison of computer software packages, with respect to QTL mapping.

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3 Results and Conclusion
Results showing the position of the QTL of the high growth hg locus computed using Map Manager
QT are presented in Fig. 1. and Fig. 2. for F-2 females and males, respectively. The maximum
likelihood position of the hg locus for F-2 females was found between MIT10 and MIT41, with a LOD
Score of 27.6, accounting for 44% of the variance. The same locus was found between MIT10 andMIT41, with a LOD score of 24.81, accounting for 41.5% using Mapmaker/QTL. In F-2 males the hg
locus was found at MIT41 with a LOD Score of 10.1, accounting for 21% of the variance (Fig. 2.).
The same locus was found at MIT41 with a LOD score of 9.56, accounting for 22.2 of the variance [1].
From these results, we can conclude that Map Manager QT and Mapmaker/QTL produce identicalresults. Thus either of the two softwares can be used in QTL mapping, provided other conditions formapping QTL are met.

Acknowledgements
The authors wish to thank Horvat and Medrano for providing mouse data.

References[1] Horvat, S. and Medrano, J.F., Interval mapping of high growth (hg), a major locus that increases
weight gain in mice, Genetics, 139:1737{1748, 1995.
[2] Lincoln, S.E., Daly, M.J. and Lander, E.S., MAPMAKER/QTL: A Tutorial and Reference
Manual, Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA, Mapmaker@genome.wi.mit.edu, 1993.
[3] Manly, K.F., Map Manager QTL: User's Manual for Map Manager Classic and QT,
http://mcbio.med.bu alo.edu/MMM/MMM.html, 1998.
0.0 cM*MIT31*MIT42*IGF1*MIT98.1*MIT10*MIT41

12.0
13.4

MIT

*MIT1215.7

MIT

*CA20

IGF

5.7

*MIT14MIT

9.5

MIT

12.8
13.5
14.0

MITMITCA2MIThg
18.9
21.0

hg

18.
0
20.
6

28.5

Lodscore = 10.1
October 7, 1998
Mapping MQTL on chr Ten
with no control for other QTLs.

29.8 cM

Lodscore = 27.6

Figure 1: Interval mapping of thehigh growth locus (hg) in mouse forweight gain from 14 to 63 days ofage for females using free regression
model.

Figure 2: Interval mapping of thehigh growth locus (hg) in mouse forweight gain from 14 to 63 days ofage for males using free regression
model.
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