Copyright Ó 2008 by the Society of America DOI: 10.1534/genetics.107.084434

Pleiotropic Patterns of Quantitative Trait Loci for 70 Murine Skeletal Traits

Jane P. Kenney-Hunt,*,1 Bing Wang,* Elizabeth A. Norgard,* Gloria Fawcett,* Doug Falk,* L. Susan Pletscher,* Joseph P. Jarvis,* Charles Roseman,† Jason Wolf‡ and James M. Cheverud* *Department of Anatomy and Neurobiology, Washington University School of Medicine, St. Louis, Missouri 63110, †Department of Anthropology, University of Illinois, Urbana, Illinois 61801 and ‡Faculty of Life Sciences, University of Manchester, Manchester M13 9PT, United Kingdom Manuscript received November 11, 2007 Accepted for publication February 1, 2008

ABSTRACT Quantitative trait (QTL) studies of a skeletal trait or a few related skeletal components are becoming commonplace, but as yet there has been no investigation of pleiotropic patterns throughout the skeleton. We present a comprehensive survey of pleiotropic patterns affecting mouse skeletal morphology in an intercross of LG/J and SM/J inbred strains (N ¼ 1040), using QTL analysis on 70 skeletal traits. We identify 798 single- trait QTL, coalescing to 105 loci that affect on average 7–8 traits each. The number of traits affected per locus ranges from only 1 trait to 30 traits. Individual traits average 11 QTL each, ranging from 4 to 20. Skeletal traits are affected by many, small-effect loci. Significant additive genotypic values average 0.23 standard deviation (SD) units. Fifty percent of loci show codominance with heterozygotes having intermediate phenotypic values. When does occur, the LG/J tends to be dominant to the SM/J allele (30% vs. 8%). Over- and underdominance are relatively rare (12%). Approximately one-fifth of QTL are sex specific, including many for pelvic traits. Evaluating the pleiotropic relationships of skeletal traits is important in understanding the role of genetic variation in the growth and development of the skeleton.

HE skeleton is a complex system composed of func- Lang et al. 2005; Ishimori et al. 2006; Kenney-Hunt T tionally interacting parts, with a variety of develop- et al. 2006; Wolf et al. 2006; Christians and Senger mental histories. Knowledge of the 2007; Farber and Medrano 2007; Yu et al. 2007; Zhou of the skeleton is important in exploring questions about et al. 2007). These studies are usually limited to a single the of the system as a whole in vertebrates as traitorafewtraitsofinterest,suchasbonemineral well as in biomedical research on the genetics of bone density, or to a specific region of the skeleton, such as growth and disease. Aspects of genetic architecture in- the innominate or mandible. While most loci are thought clude number and size of effects, dominance inter- to be pleiotropic, having effects on two or more traits actions within loci, epistatic interactions among loci, and (Wright 1980), very few studies have measured enough pleiotropic patterns. traits to make an overall analysis of pleiotropic patterns Studies of the genetic architecture of components in QTL meaningful. Here we present the results of a of body size are becoming more and more common search for QTL with effects on 70 traits throughout the (Cheverud et al. 2001; Leamy et al. 2002; Christians mouse skeleton and the pleiotropic relationships among et al. 2003; Lionikas et al. 2003; Brockmann et al. 2004; those single-trait QTL. To the best of our knowledge, this Rocha et al. 2004). Among components of body size, is the most comprehensive study of the genetic archi- there are now many published articles on the genetic tecture of the skeleton to date. architecture of skeletal traits and aspects of skeletal morphology using quantitative trait locus (QTL) anal- heverud eamy ysis (C et al. 1997, 2001; L et al. 1999; MATERIALS AND METHODS Klein et al. 2001; Klingenberg et al. 2001; Chase et al. 2002; Li et al. 2002; Shimizu et al. 2002; Christians The LG/J x SM/J intercross: The experimental population olkman ouxsein results from an intercross of inbred mouse strains LG/J and et al. 2003; V et al. 2003; B et al. 2004; heverud aughn uang lam arrier SM/J (C et al. 1996, 2001; V et al. 1999). LG/J H et al. 2004; A et al. 2005; C et al. 2005; and SM/J were selected for large and small body weight at 60 days of age, respectively (Goodale 1938; MacArthur 1949), and have been inbred for .100 generations. LG/J and SM/J hai 1Corresponding author: Department of Biological Sciences, Coker Life adult weight differed by .20 grams on average (C 1956a,b, Sciences Bldg., University of South Carolina, Columbia, SC 29208. 1957) in the 1950s, but SM/J has increased slightly in size since E-mail: [email protected] then (Kramer et al. 1998). Cheverud and Colleagues (1996)

Genetics 178: 2275–2288 (April 2008) 2276 J. P. Kenney-Hunt et al. crossed 10 LG/J females to 10 SM/J males in 1991. The F1 of fixed height. Skeletal measurements on the cranium, generation was intercrossed to produce the F2 generation scapula, innominate, sacrum, vertebrae, and foot were obtained (intercross I, n ¼ 533). The LG/J 3 SM/J intercross was to the nearest hundredth of a millimeter from the digital replicated in 1995 (intercross II, n ¼ 507) (Cheverud et al. images, using Scion (Frederick, MD) Image software. Traits on 2001). Intercrosses I and II are combined in this study for a the cranium, mandible, scapula, innominate, sacrum, verte- total of 1040 F2 mice. brae, and foot are shown in Figure 1. All measurements were Animals were weaned at 21 days of age and housed in single- taken on the animal’s right side (where applicable), unless a sex cages of no more than five animals per cage, except for missing or damaged specimen required the measurement to be breeding mice (intercross II only), which were housed in taken on the left. Table 1 describes the 70 traits included in the breeding pairs. The breeding mice were selected randomly study. Vertebral traits 1, 2, 3, and C were measured on the from intercross II individuals to form an advanced intercross cranial surface of the third thoracic, first lumbar, and fourth line (AIL) (Ehrich et al. 2005) and a panel of recombinant lumbar vertebrae and on the caudal surface of the eighth inbred lines (RILs) (Kramer et al. 1998; Cheverud et al. 1999; thoracic and third caudal vertebrae. The differences in which Hrbek et al. 2006). Standard mouse chow, an irradiated diet of surfaces were measured were due to different curvatures in the 20% protein and 4.5% fat ½Purina (St. Louis) PicoLab Rodent shape of those vertebrae. All measurements were highly repeat- Chow 20 (5353), was fed to the animals ad libitum postweaning. able as determined by the intraclass correlation of repeated The mice were weighed weekly for 10 weeks. At promptly 10 measures (r2 . 0.82 for all traits, mean r2 ¼ 0.93). Cranial traits weeks of age in intercross I and at variable times after 10 weeks vault height and face height, foot traits third metatarsal length in intercross II, the animals were killed by CO2 asphyxiation and calcaneus length, all vertebral traits on the third thoracic and necropsied. The ages at necropsy in intercross II range vertebra, eighth thoracic vertebra, and third caudal vertebra, between 72 and 237 days with a mean of 144 days (Kenney- and the lengths of the first and fourth lumbar vertebrae were Hunt et al. 2006). triple measured to ensure that repeatability of the average was : DNA was extracted from the spleens of in- .90%. All 7 mandible traits were initially measured as areas (in tercross I animals and from the livers of intercross II animals. square millimeters). Their square roots (in millimeters) were DNA extraction and PCR amplification protocols are outlined used in the quantitative genetic analysis so that the dimensions in Routman and Cheverud (1995). Intercross I was scored for of all traits would be the same. This had no effect on the 76 microsatellite markers on all 19 autosomes in 55 intervals identification of QTL. (Cheverud et al. 1996). Intercross II was scored for 95 markers Before analysis, extreme outliers were removed from the data in 71 intervals (Vaughn et al. 1999). The X was set to avoid biasing the data. Next, the effects of dam, litter size, not genotyped with microsatellites in either intercross. In- experimental block, and sex were removed as in Cheverud et al. tercross II was also genotyped commercially for 369 single- (1996) to reduce nongenetic variance and thus to increase the nucleotide polymorphisms (SNPs), including 16 SNPs on the ability to detect QTL. Effects were removed by adding the dif- X chromosome, using the GoldenGate assay (Illumina, San ference between the overall trait mean and the class mean for Diego). Supplemental Appendix A lists the markers and their that trait to each animal’s trait value, by class in a serial fashion. locations in the physical and genetic maps. Marker order was Litter size was divided into two classes, litter size of #10 and litter established using physical positions obtained from the En- size .10. Experimental block was based on date of birth, as sembl database (http://www.ensembl.org) or from Illumina animals were born at roughly monthly intervals. Experimental and verified in R/qtl (Broman et al. 2003). Haldane’s map block corrected for any change in the environment over time and distances were computed using R/qtl (Broman et al. 2003). any change in measurement practices over time, as mice were The combined map distance of all was 1796 cM, measured in birth order. Sex effects must be removed because with an average of 3.98 cM between the 471 markers. The mice are sexually dimorphic for body weight and for most largest intermarker distances were 17.1 cM on chromosome skeletal traits. The effects of age at necropsy were removed from 14 and 14.5 cM on chromosome 8. These regions lacked any intercross II individuals by multiplying the residuals from a linear detectable SNP variation between LG/J and SM/J despite regression by the value (necropsy age, 72 days) and subtracting being scored for .30 SNPs known to be polymorphic between that result from the trait value. Finally,theeffectofintercrosswas inbred mouse strains (Hrbek et al. 2006). In previously pub- removed and the intercrosses were combined. All QTL analysis lished work in this experimental population, for which only was performed on the combined and corrected data set. microsatellite genotypes were available, the average inter- Analysis: On the autosomes, QTL map positions and effects marker distance was 23 cM (Vaughnet al. 1999; Kenney-Hunt were calculated using interval mapping as described by Haley et al. 2006). and Knott (1992) and Vaughn et al. (1999). Marker positions : Body weights were collected at necropsy to the were assigned the additive genotypic scores –1 (SM/J homo- nearest hundredth of a gram, using a digital balance. Tail length zygotes), 0 (heterozygotes), and 11 (LG/J homozygotes) and measurements were collected at necropsy in intercross II, using the dominance genotypic scores 1 (heterozygotes) and 0 (both digital calipers to the nearest hundredth of a millimeter. Car- homozygotes). Genotypes were imputed every 1 cM along casses were frozen immediately after necropsy and then later each chromosome, using the genotypic scores of the flanking skinned and dried. Dermestid beetles were used to deflesh the markers and the recombination rate (Haley and Knott 1992). carcasses. Femur, tibia, humerus, and ulna lengths were mea- The SETCOR function in SYSTAT 10.2 (Systat Software, San sured using digital calipers, to the nearest hundredth of a Jose, CA) was used to regress trait values onto the additive and millimeter. Mandible landmarks were recorded by a camera dominance genotypic scores at each marker and imputed attached to a dissection microscope in intercross I (Cheverud position and to obtain F- and x2-statistics for the individual et al. 1997) and scanned using a UMAX scanner in intercross II traits under a null hypothesis of no gene effect. QTL positions (Ehrich et al. 2003). Any differences in measurement between were determined by the site with the least probability (p)ofthe intercross I and II mandibles due to the different procedures – correlation occurring by chance. The followed was accounted for by removing these effects from the likelihood probability ratio (LPR) score of a QTL is log10(p). data prior to mapping analysis (see below). Twenty-five digital Thus, the higher the LPR, the more confidence a QTL exists at images were obtained of 15 different bones from each indi- that location. vidual, using a Nikon Coolpix 4500 digital camera with an Chromosomewide and genomewide significance levels were effective resolution of 4.0 megapixels attached to a minitripod calculated using the effective marker number (Meff), in the Mouse Skeleton 2277

Figure 1.—Skeletal traits included in the study. (A–C) Cranial traits. (D) Mandible traits. (E) Innominate traits. (F) Vertebral traits, coded V#XN, where ‘‘#’’ is vertebral number, ‘‘X’’ is type (thoracic, lumbar, or caudal), and ‘‘N’’ is trait (1, 2, 3, C, or L, shown). (G) Foot traits. (H) Sacral traits. (I) Scapular traits. Not shown: body weights, tail length, long bone lengths. Figure after Anatomy of the Laboratory Mouse (Cook 1965).

2 Meff ¼ Mð1 ½ðM 1ÞVl=M Þ; Each single-trait QTL was examined for sex specificity by regressing the phenotype on the additive- and dominance-by- where M is the number of markers that were scored, and Vl is sex interaction terms, controlling for the main effects of sex and the variance of the eigenvalues of the intermarker correlation the additive and dominance genotype scores. A significant sex- matrix for each chromosome (Cheverud 2000). The Bonfer- by-QTL interaction at the 5% level indicates that the QTL roni-corrected 5% chromosomewide significance threshold is effects are sex specific. Functionally, our test is the same as the olberg calculated by dividing 0.05 by Meff for that chromosome. The one performed by S et al. (2004), but using a least- genomewide threshold is calculated by dividing 0.05 by the squares fit rather than maximum likelihood. This test for sex sum of Meff over all chromosomes. Chromosome-specific specificity is considered protected from multiple comparisons thresholds are given next to the chromosome name in sup- because the location was previously identified on the basis of its plemental Appendix C. The use of chromosomewide thresh- pooled-sex effect. Given a significant sex-by-genotype interac- olds for is recommended by Chen and Storey tion, separate analyses were performed in the two sexes. The (2006) as an appropriate balance to limit false positive sig- significance thresholds for single-sex QTL were roughly equiv- nificant results while still retaining as many true positives as alent to the thresholds for combined-sex QTL. Two-QTL tests possible. The genomewide significance threshold over the were also performed to test the model of two QTL for a single autosomes is 3.95. trait on one chromosome. If the data fit a two-QTL model better The X chromosome is a special case and must be analyzed than a single-QTL model at the 5% level (Haley and Knott differently. In the F2 generation of this intercross, males can be 1992), two QTL for the trait were located on the chromosome. hemizygous LG/J or SM/J. There is never any dominance in Next, formal tests for pleiotropy were performed, using the males because they have only one X chromosome. Females can multivariate tests for pleiotropy proposed by Knott and Haley either be homozygous LG/J or heterozygous. There are no (2000) and described by Ehrich et al. (2003). Residuals were female SM/J homozygotes at any loci on the X chromosome in obtained for each trait at its most likely location and then the the F2 generation due to the breeding scheme, in which two residuals were combined into a single residual sums-of-squares LG/J X chromosomes (P1 dams) but only one SM/J X chro- and cross-products (SSCP) matrix assuming each trait maps to mosome (P1 sires) were included in the original cross. The its own location. At the most likely location of the combined QTL analysis on the X chromosome was performed in R/qtl traits, a residual SSCP matrix was calculated assuming the traits 1.05 (Broman et al. 2003), to avoid false linkage caused by sex map to the same pleiotropic locus. The SSCP matrices were differences (Broman et al. 2006). Broman et al. (2006) de- compared using the equation scribed how to determine significance thresholds on the X chromosome using R/qtl. Here 8000 permutations were used 1 x2 ¼fd:f: ðn 1Þg 3 lnðjSSCP j=jSSCP jÞ; to find the X chromosome-specific threshold. 2 traits l p 2278 J. P. Kenney-Hunt et al.

TABLE 1 Skeletal traits

Abbreviation Trait Description General traits WTN Weight at necropsy W10 Weight at 10 wk of age TAIL Tail length

Skull traits BCL Basicranial length Foramen magnum to posterior palate CVW Cranial vault width Right to left external auditory meatus CVH Cranial vault height Top of parietal to bottom of tympanic bulla CVL Cranial vault length Dorsal length from bregma to inion FCL Face length Nasion to nasale FCH Face height From diastema anterior to zygomatic root to height of nasale orthogonal to alveolus FCW Face width Anterior interorbital width ZYW Zygomatic width Maximum width across zygomatic arches ZYL Zygomatic length Maximum length from malar to squamosal PLL Palate length Anterior of incisor to posterior of palate IOW Interorbital width Minimum frontal width FRL Frontal bone length Bregma to nasion

Mandible traits SRCRP Square root of coronoid process area SRCNP Square root of condyloid process area SRANP Square root of angular process area SRMSS Square root of masseteric area SRMAA Square root of molar alveolus area SRIAA Square root of incisor alveolus area SRCPA Square root of corpus area

Forelimb traits SNL Scapula spine length SPW Scapular width Maximum width SF1 Superior spinous length 1 Coracoid to maximum width point SF2 Superor spinous length 2 Maximum width point to border-spine point IF1 Infraspinous length 1 Coracoid to maximum width point IF2 Infraspinous length 2 Maximum width point to border-spine point HUM Humerus length Maximum length ULN Ulna length Maximum length

Hindlimb traits ILL Ilium length Iliac crest to acetabulum OFL Obturator foramen Maximum length INL Innominate length Iliac crest to most posterior ischium point PBL Pubis length Acetabulum to edge of symphysis ISL Ischium length Acetabulum to most posterior ischium point ICL Iliac crest length PSL Pubic symphysis length IPR Ischiac–pubic ramus length FEM Femur length Maximum length TIB Tibia length Maximum length TMT Third metatarsal length Maximum length CBL Calcaneus length

Vertebral traits V3T1 Third thoracic length 1 Centrum to neural spine V3T2 Third thoracic length 2 Neural spine to transverse V3T3 Third thoracic length 3 Centrum to transverse V3TL Third thoracic length Length along centrum (continued ) Pleiotropy in the Mouse Skeleton 2279

TABLE 1 (Continued)

Abbreviation Trait Description V3TC Third thoracic centrum height Height of centrum V8T1 Eighth thoracic length 1 Centrum to neural spine V8T2 Eighth thoracic length 2 Neural spine to transverse V8T3 Eighth thoracic length 3 Centrum to transverse V8TL Eighth thoracic length Length along centrum V8TC Eighth thoracic centrum height Height of centrum V1L1 First lumbar length 1 Centrum to neural spine V1L2 First lumbar length 2 Neural spine to transverse V1L3 First lumbar length 3 Centrum to transverse V1LL First lumbar length Length along centrum V1LC First lumbar centrum height Height of centrum V4L1 Fourth lumbar length 1 Centrum to neural spine V4L2 Fourth lumbar length 2 Neural spine to transverse V4L3 Fourth lumbar length 3 Centrum to transverse V4LL Fourth lumbar length Length along centrum V4LC Fourth lumbar centrum height Height of centrum V3C1 Third caudal length 1 Centrum to neural spine V3C2 Third caudal length 2 Neural spine to transverse V3C3 Third caudal length 3 Centrum to transverse V3CL Third caudal length Length along centrum V3CC Third caudal centrum height Height of centrum

Sacral traits SAW Sacrum width Maximum dorsal SAL Sacrum length Maximum dorsal along centrum SIJ Sacroilium joint length Perpendicular to SAW

where d.f. is the residual degrees of freedom based on the RESULTS number of individuals, SSCPl is from the model assuming individual linked locations, and SSCPp is from the pleiotropic Basic statistics: Standard deviations, means, and model (Knott and Haley 2000). Pleiotropy was the null sample sizes of all traits, after correction for the effects hypothesis. The separate locus model was accepted if the of dam, litter size, experimental block, necropsy age, sex, 2 probability of the x -test was #0.05. Traits were added to the and intercross, are shown in Table 2. Mice are highly pleiotropy model one chromosomal position at a time on the basis of proximity. For example, the two most closely sexually dimorphic in body weight with males larger than located QTL on a chromosome were tested for pleiotropy, females, and this is true for most skeletal traits as well. and, if positive, the pleiotropic QTL was placed at the location The exceptions were five of the eight innominate traits, for the combined traits. Then the next two closest QTL were the lengths of the first and fourth lumbar vertebrae, tested for pleiotropy, and so on. On the X chromosome, tests for pleiotropy were performed using only females, to avoid the sacroiliac joint length, and three of the seven mandibular problem with false linkage mentioned above. traits that were larger in females than in males. Seven To test for similarity between phenotypic correlations traits were found to have no difference in size between (supplemental Appendix B) and patterns of pleiotropy, a the sexes. These traits were iliac crest length (another matrix of pleiotropic scores was constructed (supplemental Appendix E). Each pair of traits was scored for the number of innominate trait), the centrum heights of the eighth times the traits co-occurred in a locus. To achieve the thoracic, first lumbar, and fourth lumbar vertebrae, and pleiotropic score, this value was divided by the sum of the three mandibular traits. The matrix of phenotypic cor- number of single-trait QTL for the trait pair divided by two. relations is shown in supplemental Appendix B. In this way, if there were 10 single-trait QTL for each trait in Individual-trait QTL: QTL analysis of the effects on the trait pair, and they co-occurred five times, the pleiotropic score was 0.5. A Mantel test (Mantel 1967) was performed to the 70 traits resulted in 798 individual-trait QTL (sup- test the similarity of the matrix of pleiotropic scores with the plemental Appendixes C and D). Of these, 14% were phenotypic correlation matrix. This test was performed using specific to males and 8% were specific to females. A the ‘‘mantel’’ function of the ‘‘vegan’’ package (http://cran. possible influence on the higher number of male QTL is r-project.org/web/packages/vegan/index.html) in the sta- tistical software R, using 50,000 permutations. The null that males were larger than females in nearly every trait hypothesis is that there is no association between the and thus had a higher variance. Fifty-nine percent of the matrices. individual-trait QTL exceeded the genomewide 5% sig- 20J .Kenney-Hunt P. J. 2280

TABLE 2 Basic statistics of the traits

W10 WTN TAIL FEM TIB HUM ULN FCL FRL FCW ZYW ZYL IOW N 1037 1031 488 1028 1016 1008 985 997 1028 1031 1013 1021 1032 Mean 29.20 31.75 90.63 15.43 17.18 12.15 14.01 8.13 7.62 4.52 12.49 10.97 4.13 SD 3.82 4.57 5.49 0.49 0.50 0.36 0.37 0.32 0.31 0.13 0.30 0.44 0.12 CVL CVW PLL BCL CVH FCH IF1 IF2 SPW SNL SF1 SF2 ILL N 1026 1030 993 1025 1025 1029 990 1022 1021 989 988 1020 1025 Mean 8.97 10.48 12.89 8.71 8.45 5.59 10.52 5.44 8.32 10.29 7.86 4.07 11.23 SD 0.31 0.23 0.42 0.30 0.32 0.22 0.43 0.30 0.38 0.40 0.38 0.31 0.46 OFL INL PBL ISL ICL PSL IPR TMT CBL V3T1 V3T2 V3T3 V3TC N 1019 1024 1020 1023 1010 1019 1020 1033 1029 982 982 982 983 Mean 5.51 15.39 6.87 4.80 1.89 1.76 7.48 7.18 3.80 2.93 2.28 2.91 0.79 SD 0.24 0.62 0.36 0.26 0.23 0.31 0.32 0.23 0.19 0.17 0.15 0.11 0.07 V3TL V8T1 V8T2 V8T3 V8TC V8TL V1L1 V1L2 V1L3 V1LC V1LL V4L1 V4L2 N 981 997 998 1002 1002 1002 987 982 983 988 988 982 978 al. et Mean 1.38 3.23 2.08 3.09 0.82 1.60 3.85 3.89 1.67 1.13 3.07 4.66 5.31 SD 0.12 0.19 0.20 0.15 0.07 0.15 0.22 0.26 0.16 0.11 0.25 0.26 0.31 V4L3 V4LC V4LL V3C1 V3C2 V3C3 V3CC V3CL SAL SIJ SAW CRP CNP N 1028 1032 1031 1013 1015 1016 1019 1018 1033 1033 1026 958 977 Mean 2.39 1.25 3.15 2.50 3.74 2.47 1.43 2.28 12.43 3.52 5.95 1.29 3.84 SD 0.19 0.12 0.22 0.25 0.24 0.23 0.12 0.25 0.64 0.31 0.34 0.14 0.17 ANP MSS CPA IAA MAA SRCRP SRCNP SRANP SRMSS SRCPA SRIAA SRMAA N 977 976 977 975 976 976 977 977 976 977 975 976 Mean 2.98 4.90 4.51 3.90 1.39 1.13 1.95 1.72 2.21 2.11 1.97 1.17 SD 0.17 0.19 0.19 0.17 0.06 0.06 0.04 0.05 0.04 0.05 0.04 0.03 Means are in millimeters except mandible traits CRP, CNP, ANP, MSS, CPA, IAA, and MAA (square millimeters) and weight traits W10 and WTN (grams). SD is the standard deviation of the trait. The effects of dam, litter size, experimental block, and sex were removed as described in the text. See Table 1 for definitions of abbreviations. Pleiotropy in the Mouse Skeleton 2281 nificance threshold of 3.95. The mean LPR was 5.76, with Pleiotropic loci: Formal tests for pleiotropy resulted in the scapula length trait on chromosome 6 having the 105 pleiotropic loci (Table 3 and Figure 2). The mean highest LPR (28.29). Confidence intervals, according to pleiotropic LPR was 10.10, a substantial increase from the convention, were defined as the region with LPRs within mean of 5.76 for individual-trait QTL. The highest LPR one of the peak LPR. The mean confidence interval was was 28.64 (locus Skl3.04). Eighty-eight of the loci (84%) 19.6 cM, with a range from 2 to 59 cM. In 65 cases there had LPRs .4.00, and 10 loci (9.5%) had LPRs .20. were 2 QTL for one trait on the same chromosome. The confidence intervals ranged from 3 to 50 cM, with Eighteen (28%) of these were on chromosome 6. The a mean confidence interval of 13.36 cM, smaller than the average number of QTL per trait was 11, with a minimum mean confidence interval for individual-trait QTL. The of 4 (three caudal vertebra traits) and a maximum of 20 mean number of traits per locus was 7.6. Seventy percent (innominate length). of these pleiotropic loci had a sex-specific effect on at Results for additive (a) and dominance (d) genotypic least one trait. The mean percentage of traits in a locus values are compared for the autosomes only. At most that were sex specific was 28%, but among those loci that of the 792 autosomal single-trait QTL the LG/J allele had at least one sex-specific trait, the percentage of sex- resulted in a larger skeletal element. A negative additive specific traits increased to 40%. The greatest number of genotypic value, indicating that the SM/J allele leads to sex-specific traits occurred at locus Skl15.04,atwhich8of larger size, occurred in only 11% of QTL. Negative the 10 traits were specific to males only. Of the 73 loci with additive genotypic values tended to be concentrated on sex-specific effects, 19% of them had both male-only and specific chromosomes. For example, 42% of the QTL on female-only trait QTL while the remainder (81%) had chromosome 5, 71% of the QTL on chromosome 18, effects restricted to either males or females. We also find and 38% of the QTL on chromosome 19 had negative that the matrix of pleiotropic scores and the phenotypic additive genotypic values. Using the absolute value of a correlation matrix are strongly correlated (P , 2 3 105, to compare the magnitude of effects, the mean stan- Mantel statistic r ¼ 0.52). This suggests that pleiotropic dardized absolute additive genotypic value (jaj/SD) was patterns are predictable from phenotypic correlations. 0.23 and the median was 0.22. As in Kenney-Hunt et al. While only 11% of single-trait QTL had negative addi- (2006), skeletal traits met quantitative genetic expect- tive genotypic values, 37% of the pleiotropic loci affected ations of having mostly small (,0.20–0.30) standardized at least one trait with a negative additive genotypic value. additive genotypic values. The largest a/SD value was Antagonistic pleiotropy with respect to skeletal size, in 0.55, belonging to the scapula-length QTL on chromo- which some traits at a locus are positively pleiotropic and some 6 that also has the highest overall LPR score. some are negatively pleiotropic, is expressed in quantita- To examine dominance relationships, the dominance tive genetic terms as a locus at which one or more traits genotypic value d is standardized by dividing it by the have a negative additive genotypic value (a) and one or additive genotypic value a. It is useful to divide these more traits have a positive additive genotypic value (1a). ratios (d/a) into broader categories (Kenney-Hunt et al. Here, a locus is considered to have antagonistic pleiot- 2006). Strongly underdominant QTL were defined as ropy when .25% of traits at a locus have significant (P # those with d/a ratios , 2.5. Only 1% of QTL fell in this 0.05) negative a values and .25% have significant (P # category, with the most underdominant being the an- 0.05) positive a values. Antagonistic pleiotropy can be terior interorbital width (FCW) locus on chromosome assessed for 92 of the pleiotropic loci, as it can be cal- 15 (d/a ¼37.62). Underdominant QTL (2% of loci) culated only for autosomal QTL with two or more traits. had d/a ratios between 1.5 and 2.5. Eight percent Of the 34 pleiotropic loci that included traits with both of loci had d/a ratios between 1.5 and 0.5, in which positive and negative additive genotypic values, 41% SM/J was considered dominant to LG/J. A locus that is exhibited antagonistic pleiotropy. exactly codominant has a d/a ratio of 0. Here, a locus was considered to be codominant if the d/a ratio was DISCUSSION between 0.5 and 0.5. Fifty percent of all QTL were codominant. With the exception of codominance, LG/J While mean LPRs and confidence intervals of in- dominant to SM/J (0.5 , d/a , 1.5) was the most dividual-trait QTL were similar to those of the micro- common dominance relationship in the study. Thirty satellite-only mapping studies in the same population percent of the loci had this relationship. LG/J over- (Vaughn et al. 1999; Cheverud et al. 2001; Kenney- dominance (1.5 , d/a , 2.5) occurs in 5% of loci. The Hunt et al. 2006), the ability to detect two QTL for the last category of dominance relationships, which oc- same trait on the same chromosome was greatly im- curred in 4% of loci, was strong overdominance, which proved by the increased marker density achieved through included those with dominance ratios .2.5. The great- intercross II for SNPs. For example, Kenney- est d/a ratio, 2115, belonged to the femur-length locus Hunt et al. (2006) included long bone lengths and on chromosome 19. The ulna-length QTL on the same necropsy weights for the same population of animals but chromosome was also strongly overdominant, with a d/a used only the microsatellite markers, which had an ratio of 26.64. average intermarker distance of 23 cM. In that study 2282 J. P. Kenney-Hunt et al.

TABLE 3 Pleiotropic loci

Chr. Locus Pos. No. traits Traits LPR C.I. 1 Skl1.01 12.0 2 OFL, SRANP 7.74 9–29 1 Skl1.02 27.6 14 FCW, ILL, INL, ULN, SAW, WTN, ZYW, 20.90 26–34 TAIL, TIB, FEM, HUM, IF2, SPW, TMT 1 Skl1.03 43.0 7 V8T3, ZYL, ICLf, SRIAA, V8T1f, IF1, SNL 6.78 30–49 1 Skl1.04 47.0 6 ISL, PLL, ULN, FCHm, V3T2, W10 18.46 44–53 1 Skl1.05 57.2 15 FCW, SRMSS, CVW, FCL, V3C1, V3C2, CBL, SRCNP, 24.16 55–59 V4L3, V8T2, HUM, TIB, SAL, OFL, TMT 1 Skl1.06 88.0 5 SRMAAm, V8T1m, V1L3, ZYW, CVL 10.58 81–95 1 Skl1.07 110.0 4 SAW, PSLf, FRLf, V4L3 6.30 106–118 2 Skl2.01 7.0 1 IOW 4.44 0–15 2 Skl2.02 41.0 2 V3CL, SRANP 10.38 37–44 2 Skl2.03 54.7 30 FCH, V3T1, ZYL, FCW, IF2, BCL, FEM, HUM, SIJ, 11.18 51–57 ULN, V1L1, V1L2, V1LL, V4L1, V4L2, ILL, ZYWm, IPRm, PLLm, WTNm, V4LLm, W10m, V8TCm, V8T3, FCL, IF1, INL, SAL, V3T3, V8T1 2 Skl2.04 65.0 10 V3C3f, TAIL, SF1, SNL, V3T2m, SAW, V3C1m, 10.75 63–76 TIB, V3C2, PBLm 2 Skl2.05 90.6 3 CVL, PSLm, CBL 8.70 88–93 2 Skl2.06 97.6 5 FRLf, ICL, SPW, SRCNPm, V4L3m 9.00 87–107 3 Skl3.01 14.0 1 PBLf 5.67 9–20 3 Skl3.02 19.7 2 V3CL, FCW 20.15 17–61 3 Skl3.03 40.0 29 CVL, CVW, IF1, ZYL, FCL, SRANP, INL, SPW, ISL, 20.80 38–44 V3TC, PLL, SRIAA, TAIL, V4L3, BCL, HUM, SNL, TIB, SAL, SF2, ULN, FEM, SRCRP, V3C2, CBL, SRCPA, SRMAA, V8TL, SF1 3 Skl3.04 49.0 10 V8T2f, FCW, ILL, SRMSS, V8T1f, ZYW, SAW, IOW, OFL, V4LL 28.64 46–53 3 Skl3.05 66.0 9 PBLm, IF2, SPW, SIJ, V4L3, IPR, BCL, V3T2, FCHm 16.15 61–72 3 Skl3.06 100.8 1 V8T3f 2.75 88–100 4 Skl4.01 0.0 1 CVWm 4.93 0–22 4 Skl4.02 18.1 5 FCW, IF2, V8T1, ZYW, HUM 6.58 11–22 4 Skl4.03 34.0 20 FEM, ISL, SPW, SRCRP, SRMSS, V8T2, SAL, V4L2, IPR, 17.49 29–38 V4L1, OFL, INL, V1L1, TIB, ULN, W10, SRIAA, V4LCf, WTN, TMTf 4 Skl4.04 41.0 7 SIJ, V1L2, SF2, SRCNP, SF1, V8TLf, SRMAA 18.16 38–44 4 Skl4.05 50.0 7 FCL, PLL, SNL, ZYL, SRCNP, IF1, IOW 23.19 48–53 4 Skl4.06 55.0 6 SAW, BCL, V8T3, CVL, ICLm, V3C3 13.48 53–59 4 Skl4.07 68.7 11 FEM, TAIL, V3CC, V3T3, V3C1, ILLm, SRMSS, 16.97 65–72 TIB, V4LLm, IOW, TMTm 5 Skl5.01 0.0 2 BCLf, V8T3f 2.90 0–8 5 Skl5.02 36.0 1 ICL 3.07 30–46 5 Skl5.03 53.9 6 FCWf, V1L3, ILLm, INLm, IOW, SNLm 5.27 46–57 5 Skl5.04 68.0 2 V8TC, V3T2 5.90 63–74 5 Skl5.05 76.0 5 PLLm, PBLf, SF1, OFL, SPWm 10.90 72–87 5 Skl5.06 104.2 4 SRCRP, HUMm, ZYWm, FEMm 2.89 80–110 6 Skl6.01 7.0 5 SAW, FCL, SRMAA, V1L3, FCW 8.05 0–32 6 Skl6.02 35.0 16 V8T3, ISL, OFL, V4LL, V8T2, SRCNP, CVH, WTN, 15.98 27–36 FCH, PLL, SF2, SRCRP, V8TCm, W10, CVW, ZYW 6 Skl6.03 41.7 3 ZYL, SPW, V4LC 13.20 39–46 6 Skl6.04 55.0 9 V3TC, V3TL, V3T3, ULN, IPR, TAIL, V8TLm, V3T1, V3T2 12.57 50–62 6 Skl6.05 65.8 8 V3C2, V4LL, BCL, CVL, SAL, V8T1, SIJ, SRANP 11.29 64–67 6 Skl6.06 79.0 26 CBLm, TMT, V1LL, V8TCm, FCL, SF1, SRCPA, ULN, 23.55 73–82 IF1, SRMAA, V4L1, FEM, ILL, OFL, SNL, TIB, V4LC, IF2, INL, ZYW, V1LC, V1L1, V4L2, HUM, IOWm, V1L2 6 Skl6.07 83.2 14 PBLf, V1L3, V3T3, V8TLf, FRL, SRMSS, W10, 13.10 80–89 WTN, SF2, ISL, CVW, SPW, V8T3, SRCRP 7 Skl7.01 3.0 1 CVLf 2.71 0–21 7 Skl7.02 29.0 5 IOW, ULN, INLm, TIB, ILLm 10.59 24–46 (continued ) Pleiotropy in the Mouse Skeleton 2283

TABLE 3 (Continued)

Chr. Locus Pos. No. traits Traits LPR C.I. 7 Skl7.03 42.0 3 PBL, V1LC, V4L3 8.30 35–46 7 Skl7.04 49.0 1 W10 17.14 43–51 7 Skl7.05 56.0 20 V8T3, CVW, FEM, INLf, ISL, SPW, 23.56 52–58 V3C2, V3TC, V8TL, ZYW, IF2, SRANPf, V3T3, V3TL, FRL, PLLf, SF1f, WTN, BCL, SNL 7 Skl7.06 63.7 9 SAL, SF2, SRMSSm, V4L2, IPR, V4L1, IF1, ILLf, INLf 13.31 61–69 7 Skl7.07 74.0 13 V4LL, V1L2, V1LL, V1L1, V3C1, SRMAAf, V8T1, 12.66 70–78 W10, SRCPAf, SIJ, CVH, V3CCf, ZYLf 7 Skl7.08 102.7 1 SAW 3.37 92–113 8 Skl8.01 5.0 9 ZYL, ISL, IPR, CVL, OFL, FCHf, PSLm, BCL, CVW 10.20 1–11 8 Skl8.02 20.0 4 V8T3f, V8T1, V3TC, V3T3 5.00 10–28 8 Skl8.03 32.6 9 IF1, ILL, INL, SIJ, HUM, FEM, TIB, TMT, TAIL 5.02 27–51 8 Skl8.04 45.7 16 SAL,SF1,ULN,W10,WTN,ZYW,CBL,SNL, 5.61 43–49 FCL, FCW, V3T1, ZYL, PBLf, V3TLf, SRMSS, V3CL 8 Skl8.05 90.0 2 IPR, SRANPf 6.47 52–91 9 Skl9.01 22.3 2 SAW, V4LL 4.13 0–28 9 Skl9.02 38.3 9 PBLm, WTN, SAL, SF2, V3C2m, V3C3m, W10, CVW, ZYW 7.12 36–42 9 Skl9.03 44.2 1 BCL 5.15 41–49 9 Skl9.04 66.8 6 SRCNP, V3TL, CVH, IPRm, SRIAA, TIB 12.01 59–70 9 Skl9.05 92.0 6 HUM, IF1, INL, PBLf, SRCRPf, TMT 2.55 71–94 10 Skl10.01 12.0 4 CVL, IOW, V1LCf, CVH 7.77 8–23 10 Skl10.02 30.0 3 SRCPA, ZYL, V8T1f 6.59 27–74 10 Skl10.03 55.6 14 SF1, FRL, IPR, SNL, IF1, BCL, FCW, SRANPm, 9.00 50–63 SRIAA, PLL, W10, ZYL, WTN, HUM 10 Skl10.04 70.3 14 V8TL, FCL, SRMSS, V3C2m, ZYW, ILL, SRMAA, 14.50 68–74 V3CL, SRCRP, V1LL, INL, TAIL, V4LL, ULN 10 Skl10.05 89.7 7 V1L3, ISL, V8T2, ICLf, SAL, V1L2, V4L1 10.22 85–90 11 Skl11.01 14.0 7 SRCRP, CBL, TIB, ILLm, INL, V3T3m, ZYWm 9.70 9–28 11 Skl11.02 34.0 3 SRMAA, IOW, V4L3 6.12 29–39 11 Skl11.03 46.0 12 CVW, SRMSS, V1L1, SRCRP, V3T1, SRIAA, 13.32 37–49 SAW, SRCPA, TMT, PLLm, SRCNP, FRL 11 Skl11.04 67.0 10 V8T1, SPWm, IF2m, CVH, FCL, OFL, SIJ, 14.21 64–69 IPR, V1L3, PSL 11 Skl11.05 86.0 12 V1L1, BCLm, ZYL, CBL, TAIL, SALm, V8T3m, 16.82 79–90 WTNm, ZYWm, SRANPm, V3T1, SRMSS 11 Skl11.06 108.0 3 SF1m, V8T2, V3T2m 5.95 101–109 12 Skl12.01 4.0 5 FCH, V8T2m, ZYWm, IOW, FRL 14.57 0–9 12 Skl12.02 24.0 7 V3C3, SRANPf, WTN, ILL, SRCRP, V1L3, FCH 15.05 15–27 12 Skl12.03 42.8 7 TMTm, V1L1, V3T1f, V4L1, PLL, V8T3, FCW 12.84 39–46 12 Skl12.04 83.0 4 ZYL, IPR, SRIAA, IOW 13.80 75–86 13 Skl13.01 6.8 2 SRANP, ICL 6.97 3–8 13 Skl13.02 24.0 18 IPR, HUM, BCL, V4LC, FEM, INL, ISL, SIJ, TIB, 13.76 22–27 V1L1, V1L2, ILL, V1LC, V3CC, V4L1, V4LL, TMT, V4L2 13 Skl13.03 31.0 8 V3TC, OFL, SPW, SAL, SNL, PBL, SRCRP, V8T3 17.15 28–35 13 Skl13.04 41.0 5 IF1, V1L3, V4L3, SF2, V3T3 14.24 38–44 13 Skl13.05 61.0 28 CVLf, TMT, ZYL, ISL, PLL, BCL, FCL, V3TL, 24.48 57–65 ZYW, CBL, V3CL, HUM, ULN, SF1, TAIL, SRIAAm, SRMSS, TIB, IOW, FCW, W10, WTN, INL, FEM, SNL, IF2, OFL, SPW 14 Skl14.01 10.0 5 FEMm, SF1m, V3T2f, SRCPA, OFLm 6.03 3–25 14 Skl14.02 20.6 13 ULN, ZYL, SRCNP, PLL, SF2m, TMTm, WTN, 5.09 11–25 ISL, SRMAA, FRL, V8T2, IF1, SPW 14 Skl14.03 28.0 12 FCW, CVH, INLm, SIJm, SRMSS, BCL, 9.00 18–42 CVL, CVW, V1L1m, V3TC, W10, ZYW 14 Skl14.04 43.0 11 FCH, V8T1, IOW, ILLm, V3CL, PSLm, 10.74 37–47 V4L1, INLf, V3T3, SRANP, V8T3 14 Skl14.05 60.0 8 V1L1f, SRMSS, IPR, V4LC, SIJf, V1L2, V1L3, V4L2 8.70 51–63 14 Skl14.06 69.4 2 V3C2, V3TC 3.49 61–73 (continued ) 2284 J. P. Kenney-Hunt et al.

TABLE 3 (Continued)

Chr. Locus Pos. No. traits Traits LPR C.I.

15 Skl15.01 28.1 17 FRLf, SRANP, CVW, IF1, SPW, SRMSS, 5.72 17–40 V1L1, IF2, W10, WTN, FCLm, CBL, SF1, SNL, SRCPA, V1L3, SRMAA 15 Skl15.02 38.0 6 V8T2, V8T1, OFL, SRCNP, FCWm, ULN 13.30 33–43 15 Skl15.03 50.5 8 CVW, PLL, ZYW, V8T3, TIB, TMT, V1LC, V3T1 5.53 40–57 15 Skl15.04 59.0 10 BCLm, FEMm, HUMm, ICLm, ILLm, INLm, ZYLm, 5.92 52–67 FCLm, V3T3, SRCRP 16 Skl16.01 0.0 5 FCHm, PLLm, SRCNPm, ULNm, ZYWm 3.30 0–5 16 Skl16.02 24.0 21 CVH, IF2m, V8T2, OFLf,SAWf, SIJm, SPWm, SRMAAm, 10.10 18–29 V3T2, SF2m, INLm, V8T1, ILLm, SRIAAm, V3T1, V3T3, CBL, CVW, SRMSS, W10, SRCPA 16 Skl16.03 39.0 6 ISL, SRMSS, FCW, TAILf, IOW, TMT 8.30 34–49 17 Skl17.01 4.8 6 FCLf, SAL, V8T2f, IF1, SAW, V4LL 4.02 0–17 17 Skl17.02 22.0 17 INL, V1LL, HUM, SRCRPm, V4LC, ULN, FEM, 21.56 16–27 TIB, ILL, PLL, FCW, V1LCf, IOW, SIJ, V8TLm, SRMAA, V1L1f 17 Skl17.03 30.0 6 V3CC, V8T1, SRMSS, FRL, SRCNP, WTNf 5.75 24–36 17 Skl17.04 71.0 8 TMTf, BCLm, V3TCf, CVLm, SF1m, SPWm, V3C2m, V8TLf 3.65 29–76 18 Skl18.01 9.0 2 OFL, V3CL 6.82 6–15 18 Skl18.02 31.7 4 FCHm, IOWm, SRANPm, WTN 5.68 30–35 18 Skl18.03 42.2 7 TMT, V1L1, V4L2, V1L2, SRCRP, V4L1, W10 17.34 39–47 18 Skl18.04 70.7 1 SALf 2.32 57–70 19 Skl19.01 0.0 3 OFLf, PBL, V1L2f 3.51 0–7 19 Skl19.02 12.9 5 FEMf, SALf, SRMSS, ULNf, V3CLf 3.83 9–18 19 Skl19.03 33.0 3 FRLm, SF1, CVL 5.18 26–43 19 Skl19.04 56.2 2 V8TCf, IF2 1.98 38–71 X Sklx.01 16.0 1 V3C2 3.99 7–22 X Sklx.02 25.0 2 V1L2, V3T2f 1.91 10–40 X Sklx.03 58.0 3 IOW, CVW, W10 2.44 57–61 The 5% genomewide significance threshold for the autosomes is 3.95. Chr. is the chromosome number. Locus indicates the name assigned to the pleiotropic locus. Pos. is the distance in centimorgans of the peak LPR from the centromeric marker. No. traits indicates the number of individual-trait QTL included in the pleiotropic locus. C.I. is the confidence interval in centimor- gans. The subscript m or f next to the trait name indicates the locus is sex specific for the trait. only one instance of two QTL on the same chromosome females, but three innominate traits were sex specific at was detected for necropsy weight or any of the four long 50% of their QTL, innominate length, ilium length, and bone lengths (two necropsy weight QTL on chromo- pubis length. This suggests the possibility of different some 6). With the new SNP marker genotypes, nine genetic systems for the male and the female pelvis, more instances of two-QTL chromosomes were identi- especially given that morphology in this region of the fied for these five traits. Femur length gained a second skeleton has an impact on reproduction. QTL on chromosomes 4 and 13, humerus length gained About 20% of the loci having sex-specific effects had a second QTL on chromosomes 1 and 13, tibia length both male- and female-specific effects on different traits gained a second QTL on chromosomes 1, 4, and 13, and at the same QTL. It is possible that these effects are ulna length gained a second QTL on chromosomes 1 actually due to separate loci too closely linked to be and 6. detected separately in an F2 population, one locus A very high number of single-trait QTL were identified affecting male traits and the other affecting female and many were strongly significant. While many of the traits. Further study in populations that have accumu- measurements were of small skeletal traits, in the 1- to 2- lated more recombination will be required to test this mm range, at least four QTL were identified for every more fully. However, if with such effects exist, trait included in the study. Dominance, including over- their evolutionary origins and effects would be of great and underdominance, was present at 50% of loci, and, interest. As an example, estrogen levels are known to where present, the LG/J allele was most often dominant have male- and female-specific effects on different fea- to the SM/J allele. When SM/J was dominant to LG/J, in tures relating to muscle and neural function (Gillies about one-third of loci the SM/J allele also resulted in a et al. 2004; Glenmark et al. 2004). Therefore, genes larger size. Overall 22% of QTL were specific to males or affecting estrogen levels or the density of estrogen Pleiotropy in the Mouse Skeleton 2285

Figure 2.—Map of pleiotropic loci. Lengths of chromosomes are shown at the bottom. Bars indicate confidence intervals. The pleiotropic locus name is located at the position of maximum LPR for the locus. receptors in various organs could produce the observed and Botstein 1989), are shown in Table 3. The utility of pattern where QTL variants affect different traits in the measure, however, is questionable when the average males and females. pleiotropic LPR is 10.10. A possible alternative for QTL Formal tests for pleiotropy (Knott and Haley 2000; studies with high LPRs is a range based on the drop-off Ehrich et al. 2003) were performed but the method of a percentage of the total LPR. For example, if the appeared to break down, especially when many traits had percentage chosen was 20%, then a QTL with a peak LPR peak LPR scores within a few centimorgans. After the first of 10 would include in the confidence interval positions set of tests was complete, no pleiotropic locus had .17 surrounding the peak with LPR . 8. individual-trait QTL included in it, but there were a Antagonistic pleiotropy for size, with a substantial and number of instances of loci that had highly overlapping significant mix of positive and negative additive geno- or even identical confidence intervals and/or LPR peaks typic values, occurred in 13% of all pleiotropic loci. In within 3 cM of each other. As the null hypothesis is these loci the LG/J allele results in some larger traits pleiotropy, judgment was used on each chromosome as and some smaller traits. This is in contrast to earlier to whether pleiotropy could really be rejected. This studies of the mandible (Ehrich et al. 2003) and the resulted in a reduction from an initial 132 pleiotropic skull (Leamy et al. 1999) in this population that found loci to the final 105. In most cases combining loci only two such loci. Further fine-mapping studies in later resulted in pleiotropic loci with very high numbers of generations of the AIL formed from intercross II will traits, for instance, the creation of 8 loci with effects on help determine whether these pleiotropic relationships $18 traits. One-LOD confidence intervals, traditional are further supported or resolved into closely linked since the beginning of QTL analysis (Ott 1985; Lander loci. 2286 J. P. Kenney-Hunt et al.

The number of traits affected by a pleiotropic locus cause genetic correlation (Cheverud 1984) and genetic varied, from 11 loci affecting single traits to loci with correlation makes up a substantial component of the phe- effects on as many as 30 traits. We expect pleiotropic loci notypic correlations measured here (Lynch and Walsh that affect a large number of traits to also affect one or 1998). Morphological evolution is facilitated when func- both of the body-weight traits (week-10 body weight or tionally and developmentally related traits are genetically weight at necropsy), as these loci may affect overall body correlated. Extensive pleiotropy of functionally or devel- size. Twenty-two percent of the pleiotropic QTL affected opmentally related characters has implications for artifi- one or both of the weight traits. Loci with effects on body cial as well as natural selection. For example, pleiotropy weight affected an average of 13.1 traits, while those loci in domesticated dogs (Chase et al. 2002) may be respon- that did not affect either body-weight trait had effects on sible for the enormous and rapid diversification of dog an average of 6.0 traits. Thus the presence of a body- breed phenotypes. Selection acting on a few loci could weight QTL frequently indicated a locus that influenced cause changes in many characters. Due to the similarity overall skeletal size as well. Pleiotropic loci affecting many of phenotypic correlation and pleiotropic patterns, it ap- traits and having high LPRs may include genes with pears that phenotypic correlations may be used to predict strong impacts on whole skeletal development, such as which traits will be pleiotropically linked. those that encode certain hormones. For example, we The study presented here, with a refined genetic map would expect to detect a QTL at insulin-like growth factor and a large number of traits encompassing the whole 1(Igf-1), given its known effects on skeletal growth (Niu skeleton, provides unprecedented detail about the ge- and Rosen 2005), and indeed it is located within the netic architecture of skeletal morphology and infor- confidence interval of pleiotropic locus Skl10.03,which mation about the role of genetic variation in skeletal affects 14 traits and has an LPR of 9.00. evolution. It is consistent with Chai’s premolecular genetics work The authors are grateful to Ty T. Vaughn, Andrea Peripato, Kilinyaa on body size (Chai 1956a,b, 1957) and this group’s work Cothran, Christy Perel, Safina Koreishi, Robin Linsey, Eric Routman, on body composition and a subset of skeletal-trait effects and all the cheerful participants in weekly peeling parties for their (Cheverud et al. 1996, 1997, 2001; Kramer et al. 1998; contributions to the project. This work was funded by the Biotechnol- Vaughn et al. 1999; Kenney-Hunt et al. 2006) that many ogy and Biological Sciences Research Council (BBSRC) (J.B.W.), by an Underwood Fellowship from the BBSRC (J.M.C.), by National Insti- loci with small, additive effects were identified. We expect tutes of Health grants DK055736 (J.M.C.) and AR053224 (J.M.C.), and that there are sizable epistatic effects as well, given that in by National Science Foundation doctoral dissertation improvement studies of a more limited number of skeletal traits (femur, grant DEB-0413039 (J.K.H. and J.M.C.). tibia, humerus, and ulna lengths), Cheverud and col- leagues found extensive (Pavlicev et al. 2007; Norgard et al. 2008). While multiple individual-trait LITERATURE CITED QTL may underlie the pleiotropic loci due to the level of Alam, I., Q. Sun,L.Liu,D.L.Koller,T.Fishburn et al., 2005 Whole-genome scan for linkage to bone strength and resolution of an F2 intercross study (Kenney-Hunt et al. hristians enger structure in inbred Fischer 344 and lewis rats. J. Bone Miner. 2006; C and S 2007), pleiotropy was Res. 20: 1589–1596. found to be widespread with most traits affected by Bouxsein,M.L.,T.Uchiyama,C.J.Rosen,K.L.Shultz,L.R.Donahue multiple loci of small individual effect. et al., 2004 Mapping quantitative trait loci for vertebral trabecular bonevolumefractionandmicroarchitectureinmice.J.BoneMiner. The extensive pleiotropy found here documents one Res. 19: 587–599. way in which traits can be co-inherited. At the phenotypic Brockmann,G.A.,E.Karatayli,C.S.Haley,U.Renne,O.J.Rottmann level, selection for compatible trait values of functionally et al., 2004 QTLs for pre- and postweaning body weight and body composition in selected mice. Mamm. Genome 15: 593–609. and developmentally related traits is predicted to cause Broman, K. W., H. Wu,S.Sen and G. A. Churchill, 2003 R/qtl: their co-inheritance and hence their genetic and pheno- QTL mapping in experimental crosses. Bioinformatics 19: 889– typic correlation (Olsen and Miller 1958; Lande 1980; 890. heverud Broman, K. W., S. Sen,S.E.Owens,A.Manichaikul,E.M.Southard- C 1982, 1984). More recently, Cheverud and Smith et al., 2006 The X chromosome in quantitative trait locus colleagues (Cheverud et al. 2004; Pavlicev et al. 2007; mapping. Genetics 174: 2151–2158. Wagner et al. 2007) have suggested that pleiotropic Carrier, D. R., K. Chase and K. G. Lark, 2005 Genetics of canid skeletal variation: size and shape of the pelvis. Genome Res. relationships should reflect the coselection of traits such 15: 1825–1830. that pleiotropic effects would be favored among traits Chai, C., 1956a Analysis of quantitative inheritance of body size in selected together and not favored among traits selected mice. I. Hybridization and maternal influences. Genetics 41: 157–164. independently. Our analysis of the relationship between Chai, C., 1956b Analysis of quantitative inheritance of body size in pleiotropy and phenotypic correlation indicates that mice. II. Gene action and segregation. Genetics 41: 167–178. these two measures of trait relationship are relatively Chai, C., 1957 Analysis of quantitative inheritance of body size in mice. III. Dominance. Genetics 42: 601–607. strongly correlated. Not surprisingly, traits that share Chase, K., D. R. Carrier,F.R.Adler,T.Jarvik,E.A.Ostrander pleiotropic effects at individual QTL tend to be pheno- et al., 2002 Genetic basis for systems of skeletal quantitative typically correlated. It is not possible to estimate genetic traits: principal component analysis of the canid skeleton. Proc. Natl. Acad. Sci. USA 99: 9930–9935. correlations in this F2 intercross population due to the Chen, L., and J. D. Storey, 2006 Relaxed significance criteria for lack of family structure but the pleiotropic effects of QTL linkage analysis. 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