Copyright Ó 2005 by the Genetics Society of America DOI: 10.1534/genetics.104.028902 Using Progenitor Strain Information to Identify Quantitative Trait Nucleotides in Outbred Mice B. Yalcin, J. Flint and R. Mott1 Wellcome Trust Centre for Human Genetics, Oxford University, Oxford OX3 7BN, United Kingdom Manuscript received November 23, 2004 Accepted for publication July 1, 2005 ABSTRACT We have developed a fast and economical strategy for dissecting the genetic architecture of quantitative trait loci at a molecular level. The method uses two pieces of information: mapping data from crosses that involve more than two inbred strains and sequence variants in the progenitor strains within the interval containing a quantitative trait locus (QTL). By testing whether the strain distribution pattern in the pro- genitor strains is consistent with the observed genetic effect of the QTL we can assign a probability that any sequence variant is a quantitative trait nucleotide (QTN). It is not necessary to genotype the animals except at a skeleton of markers; the genotypes at all other polymorphisms are estimated by a multipoint analysis. We apply the method to a 4.8-Mb region on mouse chromosome 1 that contains a QTL influencing anxiety segregating in a heterogeneous stock and show that, under the assumption that a single QTN is present and lies in a region conserved between the human and mouse genomes, it is possible to reduce the number of variants likely to be the quantitative trait nucleotide from many thousands to ,20. LTHOUGH it is straightforward to map quantitative Sequence differences between inbred strains have A trait loci (QTL) in animal models such as rodents long been used to map QTL in panels of recombinant [.100 that influence behavioral variation alone have inbred lines (see http://www.webqtl.org). The key idea been identified (Flint 2003)], finding the quantitative is that allelic distribution across the panel at a locus trait nucleotides (QTN) that give rise to a QTL continues is characterized by its strain distribution pattern (SDP): to be difficult and expensive; cheaper and quicker ways a QTL must be contained in a locus where the SDP of moving from QTL to QTN are needed. Unfortunately correlates with the phenotypic distribution across the the genetic architecture of quantitative traits is complex panel. More recently, Hitzemann and colleagues have (Mackay 2001). Studies in yeast (Steinmetz et al. 2002) shown that when QTL have been mapped in different and Drosophila (Anholt et al. 2003) reveal interactions combinations of inbred strain crosses, allelic variation between sex, environment, and genotype and show that among the strains can be combined with mapping data no single variant within a locus may be sufficient to ex- to narrow the region containing the functional variant plain phenotypic variation. The individual contribution (Hitzemann et al. 2002). Further, it should be possible from each locus is usually small, and the responsible to exploit the SDP of multiple inbred strains for QTL sequence variants may lie within noncoding regions mapping in silico (Grupe et al. 2001). (Allen et al. 2003; Helms et al. 2003; Tokuhiro et al. Here, rather than map QTL, we show how to use SDPs 2003; Ueda et al. 2003; Van Laere et al. 2003; Zhang et al. to identify candidate QTN. We present a novel approach 2003). that combines the high-resolution mapping potential of The availability of complete genome sequences and genetically heterogeneous stock (HS) of mice with the dense single-nucleotide polymorphism (SNP) maps opens sequence information available from the HS progenitor up novel approaches to QTN identification (Lander et al. strains (Talbot et al. 1999; Mott et al. 2000). Our 2001; Sachidanandam et al. 2001; Wade et al. 2002; approach differs from that of other methods that use Waterston et al. 2002). Surveys of genetic variation in SDP information (for example, Hitzemann et al. 2002; the mouse indicate that sequence differences between in- Grupe et al. 2001), in that it incorporates the probabi- bred strains are not randomly distributed across the ge- listic ancestral haplotype reconstruction analysis de- nome. Wade and colleagues argue that 95% of genetic veloped for the analysis of HS populations. variationliesinone-thirdofthemousegenomeand As a test case, we analyzed a QTL that contributes to suggest that focusing on SNP dense regions of the genome ,10% of the phenotypic variance in a number of will accelerate QTL searches (Wade et al. 2002). behavioral tests of anxiety in the mouse (Turri et al. 2001a,b). The small-effect size is typical for a behavioral QTL and for many other phenotypes too (Flint 2003). 1Corresponding author: Wellcome Trust Centre for Human Genetics, Oxford University, Roosevelt Dr., Oxford OX3 7BN, United Kingdom. The QTL has been mapped to a 4.8-Mb region near E-mail: [email protected] position 143 Mb on chromosome 1 in HS mice that are Genetics 171: 673–681 (October 2005) 674 B. Yalcin, J. Flint and R. Mott derived from eight inbred progenitor strains, A/J, AKR, were purified on a 96-well Millipore purification plate and BALB/c, C3H, C57BL/6, DBA/2, I, and RIII (McClearn resuspended in 30 mlofH2O. Two sequencing reactions were et al. 1970). We screened the region for sequence variants prepared for each DNA sample, one with the forward primer and one with the reverse primer. PCR reagents were removed and identified 1720 (including 1325 SNPs) of an esti- from solution by an ethanol precipitation in the presence of mated total of 15,000 (Yalcinet al. 2004a). All the diallelic sodium acetate. All sequencing reactions were analyzed on an variants fall into 19 SDPs, none of which form a simple ABI3700 sequencer and edited using CONSED software haplotype block structure. These SDP complexities sug- (Gordon et al. 1998). Sequence variant information: We used the data set of 1720 gest that a way to test that each variant is a QTN is by com- alcin albot variants described in Y et al. (2004a), obtained by re- bining QTL mapping data in HS animals (T et al. sequencing 580 kb of the 4.8-Mb region in each of the eight HS 1999) with the SDPs of HS progenitor strains (Yalcinet al. founders. We used DNA from the following eight strains as 2004a) and thus avoiding the need to genotype every poly- representative of the founders of the HS: A/J, AKR, BALB/cJ, morphism. The problem this article addresses is equiva- C3H/HeJ, C57BL/6J, DBA/2J, I/LnJ, and RIII/DmmobJ lent to the hidden SNP problem in human genetics (hereafter referred to as A/J, AKR, BALB/c, C3H, C57BL/6, vans DBA/2, I, and RIII). Details of the sequencing strategy are (E et al. 2004). However, our solution differs in that given in Yalcin et al. (2004a); in brief, we resequenced all we can make use of the known haplotype structure of exons, including at least 1 kb of flanking sequence, all con- mouse inbred strains. served noncoding regions (defined as regions of .70% simi- larity over $100 bp in a comparison between mouse and human sequence), and finally a random selection of 1- to 2-kb segments, at intervals of 10 kb. The mean distance between MATERIALS AND METHODS sampled sequences was 8.2 kb. Heterogeneous stock mice: We used the same mice and Marker selection: We selected a set of SNPs for genotyping phenotype as described in Talbot et al. (1999). The stock is the HS animals on the basis of the informativeness of the maintained by breeding from 40 pairs and at the time of the haplotypes of the eight HS founder strains. The method was ckerman experiment reported here mice were at generation 58 at which originally developed for tagging SNPs in humans (A point the expected average length of unrecombined chromo- et al. 2003). Briefly, the method works on a moving window of some is ,2 cM, in agreement with experimental observation SNPs, prioritizing the SNPs in each window by their ability to (Talbot et al. 1999). Open-field activity was measured in 751 account for an entropy-based measure of diversity between the heterogeneous stock mice for 5 min in a white plastic 60-cm founder haplotypes. Each SNP is scored by summing its con- arena. Defecation was measured by recording the number of tributions in all the windows that overlap the SNP. Then the fecal boli produced in the open field during the 5-min test SNPs are ranked across the region by sorting their scores, and period. The phenotype we use, EMO, is the difference between the top SNPs are chosen for genotyping. For a detailed ex- the standardized scores for activity and defecation. planation the reader is referred to http://www.well.ox.ac. SNP genotyping: SNP genotyping was performed using the uk/rmott/SNPS. MassExtend system (Sequenom). Extension and amplification Testing for a QTL: The test for a QTL is an extension of the ott primers were designed using SpectroDesigner. Oligonucleo- treatment in M et al. (2000). A skeleton of markers is tides were synthesized at Metabion (Martinsried, Germany). genotyped in the HS over a region containing a QTL. The PCR was carried out with Hotstar Taq obtained from QIAGEN markers must be spaced close enough that on average more (Du¨sseldorf, Germany). A 5-ml PCR contained 2.5 ng of ge- than one marker will be present between any two historical nomic DNA, 0.2 units of HotStar Taq, 5 pmol forward and re- recombinants that have accumulated in the HS. We also verse primers, 2 mm of each dNTP, 13 HotStar Taq PCR buffer genotype the progenitor strains with the same markers.