In silico QTL mapping of maternal nurturing ability with the mouse diversity panel

Significant variation exists for maternal nurturing ability in inbred mice. Although classical mapping approaches have identified quantitative trait loci (QTL) that may account for this variation, the underlying genes are unknown. In this study, lactation performance data among the mouse diversity panel were used to map genomic regions associated with this variation. Females from each of 32 inbred strains (n = 8-19 dams/strain) were studied during the first 8 days of lactation by allowing them to raise weight- and size-normalized cross-foster litters (10 pups/litter). Average daily weight gain (ADG) of litters served as the primary indicator of milk production. The number of pups successfully reared to 8 days (PNUM8) also served as a related indicator of maternal performance. Initial haplotype association analysis using a Bonferroni-corrected, genome-wide threshold revealed 10 and 15 associations encompassing 11 and 13 genes for ADG and PNUM8, respectively. The most significant of these associated haplotype blocks were found on MMU 8, 11, and 19 and contained the genes Nr3c2, Egfr, Sec61g, and Gnaq. Lastly, two haplotype blocks on MMU9 were detected in association with PNUM8. These overlapped with the previously described maternal performance QTL, Neogq1. These results suggest that the application of in silico QTL mapping is a useful tool in discovering the presence of novel candidate genes involved in determining lactation capacity in mice.     

Identification of genetic regions of importance for reproductive performance in female mice

Both environmental and genetic factors can dramatically affect reproductive performance in mice. In this study we have focused on the identification of genetic regions, quantitative trait loci (QTL), which affect the breeding capacity of female mice. We have identified polymorphic microsatellite markers for the mouse strains used and performed a genomewide scan on 237 females from a gene-segregating backcross between a high breeder and a relatively poor breeder. The high-breeder mouse strain we used is the inbred NFR/N mouse (MHC haplotype H-2q), which has extraordinary good breeding properties. The moderate breeder chosen for F(1) and N2 progeny was B10.Q, which is a genetically well-characterized MHC-congenic mouse of the H-2q haplotype. Each of the 237 females of the N2 generation was allowed to mate twice with MHC-congenic B10.RIII (H-2r) males and twice with B10.Q males. A predetermined number of phenotypes related to reproductive performance were recorded, and these included litter size, neonatal growth, and pregnancy rate. Loci controlling litter size were detected on chromosomes 1 (Fecq3) and 9 (Fecq4). The neonatal growth phenotype was affected by Fecq3 and a locus on chromosome 9 (Neogq1). On chromosome 11 two loci affecting the pregnancy rate (Pregq1 and Pregq2) were identified. Furthermore, on chromosomes 13 and 17 we found loci (Pregq3 and Pregq4) influencing the outcome of allogeneic pregnancy (allogeneic by means of MHC disparity between mother and fetuses). A locus on chromosome 1 affecting maternal body weight was also identified and has been denoted Bwq7. It is well known that reproductive performance is polygenically controlled, and the identification of the major loci in this complex process opens the possibility of investigating the natural genetic control of reproduction.     

Integration of QTL and bioinformatic tools to identify candidate genes for triglycerides in mice

To identify genetic loci influencing lipid levels, we performed quantitative trait loci (QTL) analysis between inbred mouse strains MRL/MpJ and SM/J, measuring triglyceride levels at 8 weeks of age in F2 mice fed a chow diet. We identified one significant QTL on chromosome (Chr) 15 and three suggestive QTL on Chrs 2, 7, and 17. We also carried out microarray analysis on the livers of parental strains of 282 F2 mice and used these data to find cis-regulated expression QTL. We then narrowed the list of candidate genes under significant QTL using a "toolbox" of bioinformatic resources, including haplotype analysis; parental strain comparison for gene expression differences and nonsynonymous coding single nucleotide polymorphisms (SNP); cis-regulated eQTL in livers of F2 mice; correlation between gene expression and phenotype; and conditioning of expression on the phenotype. We suggest Slc25a7 as a candidate gene for the Chr 7 QTL and, based on expression differences, five genes (Polr3 h, Cyp2d22, Cyp2d26, Tspo, and Ttll12) as candidate genes for Chr 15 QTL. This study shows how bioinformatics can be used effectively to reduce candidate gene lists for QTL related to complex traits.     

特异区段替换小鼠性发育表型的研究

目的了解性发育相关数量性状基因座(quantitative trait locus,QTL)(DXMit68-rs29053133)在近交系小鼠A/J和C3H/HeJ(C3H)中是否存在影响表型的序列差异,以帮助对候选基因进行筛选。方法利用A/J和C3H构建了针对该区段的特异区段替换系小鼠,并对其雌鼠的性发育相关性状进行研究。结果 A/J和C3H在这一QTL中染色体的序列差异,没有引起相关性状的明显差异。结论研究结果显示,A/J和C3H小鼠中该QTL区段中存在序列差异的基因并不是引起性发育表型产生差异的候选基因。     

An Integrative Genomic Analysis of the Superior Fecundity Phenotype in QSi5 Mice

Laboratory inbred mouse models are a valuable resource to identify quantitative trait loci (QTL) for complex reproductive performance traits. Advances in mouse genomics and high density single nucleotide polymorphism mapping has enabled genome-wide association studies to identify genes linked with specific phenotypes. Gene expression profiles of reproductive tissues also provide potentially useful information for identifying genes that play an important role. We have developed a highly fecund inbred strain, QSi5, with accompanying genotyping for comparative analysis of reproductive performance. Here we analyzed the QSi5 phenotype using a comparative analysis with fecundity data derived from 22 inbred strains of mice from the Mouse Phenome Project, and integration with published expression data from mouse ovary development. Using a haplotype association approach, 400 fecundity-associated regions (FDR < 0.05) with 499 underlying genes were identified. The most significant associations were located on Chromosomes 14, 8, and 6, and the genes underlying these regions were extracted. When these genes were analyzed for expression in an ovarian development profile (GSE6916) several distinctive co-expression patterns across each developmental stage were identified. The genetic analysis also refined 21 fecundity associated intervals on Chromosomes 1, 6, 9, 13, and 17 that overlapped with previously reported reproductive performance QTL. The combined use of phenotypic and in silico data with an integrative genomic analysis provides a powerful tool for elucidating the molecular mechanisms underlying fecundity.     

Quantitative trait locus and haplotype mapping in closely related inbred strains identifies a locus for open field behavior

Quantitative trait locus (QTL) mapping in the mouse typically utilizes inbred strains that exhibit significant genetic and phenotypic diversity. The development of dense SNP panels in a large number of inbred strains has eliminated the need to maximize genetic diversity in QTL studies as plenty of SNP markers are now available for almost any combination of strains. We conducted a QTL mapping experiment using both a backcross (N₂) and an intercross (F₂) between two genetically similar inbred mouse strains: C57BL/6J (B6) and C57L/J (C57). A set of additive QTLs for activity behaviors was identified on Chrs 1, 9, 13, and 15. We also identified additive QTLs for anxiety-related behaviors on Chrs 7, 9, and 16. A QTL on Chr 11 is sex-specific, and we revealed pairwise interactions between QTLs on Chrs 1 and 13 and Chrs 10 and 18. The Chr 9 activity QTL accounts for the largest amount of phenotypic variance and was not present in our recent analysis of a B6 × C58/J (C58) intercross (Bailey et al. in Genes Brain Behav 7:761–769, 2008). To narrow this QTL interval, we used a dense SNP haplotype map with over 7 million real and imputed SNP markers across 74 inbred mouse strains (Szatkiewicz et al. in Mamm Genome 19(3):199–208, 2008). Evaluation of shared and divergent haplotype blocks among B6, C57, and C58 strains narrowed the Chr 9 QTL interval considerably and highlights the utility of QTL mapping in closely related inbred strains.     

Quantitative trait locus mapping of genes regulating pulmonary PKC activity and PKC-alpha content

Strain A/J mice, which are predisposed to experimentally induced asthma and adenocarcinoma, have the lowest pulmonary protein kinase (PK) C activity and content among 22 inbred mouse strains. PKC in neonatal A/J mice is similar to that in other strains, so this difference reflects strain-dependent postnatal regulation. PKC activity is 60% higher in C57BL/6J (B6) than in A/J lungs, and the protein and mRNA concentrations of PKC-alpha, the major pulmonary PKC isozyme, are two- to threefold higher in B6 mice. These differences result from more than a single gene as assessed in F(1), F(2), and backcross progeny of B6 and A/J parents. Quantitative trait locus (QTL) analysis of 23 AxB and BxA recombinant inbred strains derived from B6 and A/J progenitors indicates a major locus regulating lung PKC-alpha content that maps near the Pkcalpha structural gene on chromosome 11 (D11MIT333; likelihood ratio statistic = 12.5) and a major locus controlling PKC activity that maps on chromosome 3 (D3MIT19; likelihood ratio statistic = 15.4). The chromosome 11 QTL responsible for low PKC-alpha content falls within QTLs for susceptibilities to lung tumorigenesis and ozone-induced toxicity.     

New quantitative trait loci that regulate wound healing in an intercross progeny from DBA/1J and 129×1/SvJ inbred strains of mice

Wound healing/regeneration mouse models are few, and studies performed have mainly utilized crosses between MRL/MPJ (a good healer) and SJL/J (a poor healer) or MRL/lpr (a good healer) and C57BL/6J (a poor healer). Wound healing is a complex trait with many genes involved in the expression of the phenotype. Based on data from previous studies that common and additional quantitative trait loci (QTL) were identified using different crosses of inbred strains of mice for various complex traits, we hypothesized that a new cross would identify common and additional QTL, unique modes of inheritance, and interacting loci, which are responsible for variation in susceptibility to fast wound healing. In this study, we crossed DBA/1J (DBA, a good healer) and 129/SvJ (129, a poor healer) and performed a genome-wide scan using 492 (DBA×129) F2 mice and 98 markers to identify QTL that regulate wound healing/regeneration. Four QTL on chromosomes 1, 4, 12, and 18 were identified which contributed toward wound healing in F2 mice and accounted for 17.1% of the phenotypic variation in ear punch healing. Surprisingly, locus interactions contributed to 55.7% of the phenotype variation in ear punch healing. In conclusion, we have identified novel QTL and shown that minor interacting loci contribute significantly to wound healing in DBA×129 mice cross. The authors Masinde, Li, and Nguyen contributed equally to this article.     

Genetic dissection of testis weight in mice: quantitative trait locus analysis using F2 intercrosses between strains with extreme testis weight, and association study using Y-consomic strains

In the present study, dissection of genetic bases of testis weight in mice was performed. Autosomes and the X chromosome were searched using traditional quantitative trait locus (QTL) scans, and the Y chromosome was searched by association studies of Y-consomic strains. QTL analysis was performed in ??DDD?×???CBA F₂ mice; the inbred mouse DDD has the heaviest testes, whereas the inbred mouse CBA has the lightest testes. Two significant testis weight QTLs were identified on chromosomes 1 and X. A DDD allele was associated with increased and decreased testis weight at the locus on chromosomes 1 and X, respectively. In the reciprocal cross ??CBA?×???DDD F₂ mice, QTL on chromosome 1, and not on chromosome X, had a significant effect on testis weight. The DDD allele at the X-linked locus could not sustain testis weight in combination with the Y chromosome of the CBA strain. The Y chromosome per se had a significant effect on testis weight, i.e., DH-Chr Y^DDD had significantly heavier testes than DH-Chr Y^CBA. On the basis of the results of Y-chromosome-wide association studies using 17 Y-consomic strains, variations in Uty, Usp9y, and Sry were significantly associated with testis weight. Thus, testis weight is a complex quantitative phenotype controlled by multiple genes on autosomes and sex chromosomes and their interactions.     

Genetic dissection of testicular weight in the mouse with the BXD recombinant inbred strains

Testicular weights were studied in the mouse BXD recombinant inbred (RI) strains. These strains were derived from DBA/2J and C57BL/6J progenitors that differ significantly in their testicular weights (0.224 g ± 0.015 vs. 0.161 g ± 0.03, P < 0.0001). The heritability of testicular weights was calculated to be 0.53, and the minimum number of responsible effective factors was estimated to be 5.7. The total genome scanning of the BXD RI strains with over 1000 markers revealed a quantitative trait locus (QTL) on mouse Chromosome (Chr) 13 near the D13Mit3 marker (LOD score 6.9). This QTL region was designated Twq1 and associated with over 75% of genetic variability. Received: 23 January 1998 / Accepted: 16 March 1998     

A novel strategy for genetic dissection of complex traits: the population of specific chromosome substitution strains from laboratory and wild mice

The mouse is an irreplaceable model for understanding the precise genetic mechanisms of mammalian physiological pathways. Thousands of quantitative trait loci (QTLs) have been mapped onto the mouse genome during the last two decades. However, only a few genes’ underlying complex traits have been successfully identified, and rapid fine mapping of QTL genes still remains a challenge for mouse geneticists. Currently, the Collaborative Cross (CC) has proceeded to the goal of establishing more than 1,000 recombinant inbred strains for the sub-centimorgan mapping resolution of QTL loci. In this article, a novel complementary strategy, designated as population of specific chromosome substitution strains or PSCSS, is proposed for rapid fine mapping of QTLs on the substituted chromosome. One specific chromosome (Chr 1) of recipient mouse strain C57BL/6 J has been substituted by homologous counterparts from five different inbred strains (C3H/He, FVB/N, AKR, NOD/LtJ, NZW/LacJ), an outbred line Kunmin mouse in China, and 23 wild mice captured in different localities. The primary genetic studies on the structure of these wild donor chromosomes (Chr 1) show that these donor chromosomes harbor extensive genetic polymorphisms, with a high density of SNP distribution, abundant variations of STR alleles, and a high level of historical recombination accumulation. These specific chromosome substitution strains eventually form a special population that has the identical genetic background of the recipient strain and differs only in the donor chromosomes. With simple association studies, known QTLs on the donor chromosome can be rapidly mapped in high resolution without requirement of further crosses. This approach, taking advantage of the extensive genetic polymorphisms of wild resources and chromosome substitution strategy, brings a new outlook for genetic dissection of complex traits.     

Identification of genetic determinants of IGF‐1 levels and longevity among mouse inbred strains

The IGF‐1 signaling pathway plays an important role in regulating longevity. To identify the genetic loci and genes that regulate plasma IGF‐1 levels, we intercrossed MRL/MpJ and SM/J, inbred mouse strains that differ in IGF‐1 levels. Quantitative trait loci (QTL) analysis of IGF‐1 levels of these F2 mice detected four QTL on chromosomes (Chrs) 9 (48 Mb), 10 (86 Mb), 15 (18 Mb), and 17 (85 Mb). Haplotype association mapping of IGF‐1 levels in 28 domesticated inbred strains identified three suggestive loci in females on Chrs 2 (13 Mb), 10 (88 Mb), and 17 (28 Mb) and in four males on Chrs 1 (159 Mb), 3 (52 and 58 Mb), and 16 (74 Mb). Except for the QTL on Chr 9 and 16, all loci co‐localized with IGF‐1 QTL previously identified in other mouse crosses. The most significant locus was the QTL on Chr 10, which contains the Igf1 gene and which had a LOD score of 31.8. Haplotype analysis among 28 domesticated inbred strains revealed a major QTL on Chr 10 overlapping with the QTL identified in the F2 mice. This locus showed three major haplotypes; strains with haplotype 1 had significantly lower plasma IGF‐1 and extended longevity (P < 0.05) than strains with haplotype 2 or 3. Bioinformatic analysis, combined with sequencing and expression studies, showed that Igf1 is the most likely QTL gene, but that other genes may also play a role in this strong QTL.     

Genetic analysis of barrel field size in the first somatosensory area (SI) in inbred and recombinant inbred strains of mice

We measured the combined area of posterior medial barrel subfield (PMBSF) and anterior lateral barrel subfield (ALBSF) areas in four common inbred strains (C3H/HeJ, A?/J, C57BL?/6J, DBA/2J), B6D2F1, and ten recombinant inbred (RI) strains generated from C57BL/6J and DBA/2J progenitors (BXD) as an initial attempt to examine the genetic influences underlying natural variation in barrel field size in adult mice. These two subfields are associated with the representation of the whisker pad and sinus hairs on the contralateral face. Using cytochrome oxidase labeling to visualize the barrel field, we measured the size of the combined subfields in each mouse strain. We also measured body weight and brain weight in each strain. We report that DBA/2J mice have a larger combined PMBSF/ALBSF area (6.15?±?0.10?mm²,?n?=?7) than C57BL?/6J (5.48?±?0.13?mm²,?n?=?10), C3H/HeJ (5.37?±?0.16?mm²,?n?=?10), and A/J mice (5.04?±?0.09?mm²,?n?=?15), despite the fact that DBA/2J mice have smaller average brain and body sizes. This finding may reflect dissociation between systems that control brain size with those that regulate barrel field area. In addition, BXD strains (average n?=?4) and parental strains showed considerable and continuous variation in PMBSF/ALBSF area, suggesting that this trait is polygenic. Furthermore, brain, body, and cortex weights have heritable differences between inbred strains and among BXD strains. PMBSF/ALBSF pattern appears similar among inbred and BXD strains, suggesting that somatosensory patterning reflects a common plan of organization. This data is an important first step in the quantitative genetic analysis of the parcellation of neocortex into diverse cytoarchitectonic zones that vary widely within and between species, and in identifying the genetic factors underlying barrel field size using quantitative trait locus (QTL) analyses.     

Integrating QTL and high-density SNP analyses in mice to identify Insig2 as a susceptibility gene for plasma cholesterol levels

The use of inbred strains of mice to dissect the genetic complexity of common diseases offers a viable alternative to human studies, given the control over experimental parameters that can be exercised. Central to efforts to map susceptibility loci for common diseases in mice is a comprehensive map of DNA variation among the common inbred strains of mice. Here we present one of the most comprehensive high-density, single nucleotide polymorphism (SNP) maps of mice constructed to date. This map consists of 10,350 SNPs genotyped in 62 strains of inbred mice. We demonstrate the utility of these data via a novel integrative genomics approach to mapping susceptibility loci for complex traits. By integrating in silico quantitative trait locus (QTL) mapping with progressive QTL mapping strategies in segregating mouse populations that leverage large-scale mapping of the genetic determinants of gene expression traits, we not only facilitate identification of candidate quantitative trait genes, but also protect against spurious associations that can arise in genetic association studies due to allelic association among unlinked markers. Application of this approach to our high-density SNP map and two previously described F2 crosses between strains C57BL/6J (B6) and DBA/2J and between B6 ApoE(-/-) and C3H/HeJ ApoE(-/-) results in the identification of Insig2 as a strong candidate susceptibility gene for total plasma cholesterol levels.     

An integrative approach for the identification of quantitative trait loci

The genetic dissection of complex traits is one of the most difficult and most important challenges facing science today. We discuss here an integrative approach to quantitative trait loci (QTL) mapping in mice. This approach makes use of the wealth of genetic tools available in mice, as well as the recent advances in genome sequence data already available for a number of inbred mouse strains. We have developed mapping strategies that allow a stepwise narrowing of a QTL mapping interval, prioritizing candidate genes for further analysis with the potential of identifying the most probable candidate gene for the given trait. This approach integrates traditional mapping tools, fine mapping tools, sequence-based analysis, bioinformatics and gene expression.     

A quantitative trait locus on chromosome 1 modulates intermale aggression in mice

Aggression between male conspecifics is a complex social behavior that is likely modulated by multiple gene variants. In this study, the BXD recombinant inbred mouse strains (RIS) were used to map quantitative trait loci (QTLs) underlying behaviors associated with intermale aggression. Four hundred and fifty‐seven males from 55 strains (including the parentals) were observed at an age of 13 ± 1 week in a resident‐intruder test following 10 days of isolation. Attack latency was measured directly within a 10‐minute time period and the test was repeated 24 hours later. The variables we analyzed were the proportion of attacking males in a given strain as well as the attack latency (on days 1 and 2, and both days combined). On day 1, 29% of males attacked, and this increased to 37% on day 2. Large strain differences were obtained for all measures of aggression, indicating substantial heritability (intraclass correlations 0.10‐0.18). We identified a significant QTL on chromosome (Chr) 1 and suggestive QTLs on mouse Chrs 1 and 12 for both attack and latency variables. The significant Chr 1 locus maps to a gene‐sparse region between 82 and 88.5 Mb with the C57BL/6J allele increasing aggression and explaining about 18% of the variance. The most likely candidate gene modulating this trait is Htr2b which encodes the serotonin 2B receptor and has been implicated in aggressive and impulsive behavior in mice, humans and other species.     

Behavioural and physiological characterization of inbred mouse strains: prospects for elucidating the molecular mechanisms of mammalian learning and memory

With the advent of recombinant DNA methodology, it has become possible to dissect the molecular mechanisms of complex traits, including brain function and behaviour. The increasing amount of available information on the genomes of mammalian organisms, including our own, has facilitated this research. The present review focuses on a somewhat neglected area of genetics, one that involves the study of inbred mouse strains. It is argued that the use of inbred mice is complementary to transgenic approaches in the analysis of molecular mechanisms of complex traits. Whereas transgenic technology allows one to manipulate a single gene and investigate the in vivo effects of highly specific, artificially induced mutations, the study of inbred mouse strains should shed light on the roles of naturally occurring allelic variants in brain function and behaviour. Systematic characterization of the behavioural, electrophysiological, neurochemical, and neuroanatomical properties of a large number of inbred strains is required to elucidate mechanisms of mammalian brain function and behaviour. In essence, a 'mouse phenome' project is needed, entailing the construction of databases to investigate possible causal relationships amongst the phenotypical characteristics. This review focuses on electrophysiological and behavioural characterization of mouse strains. Nevertheless, it is emphasized that the full potential of the analysis of inbred mouse strains may be attained if techniques of numerous disciplines, including gene expression profiling, biochemical analysis, and quantitative trait loci (QTL) mapping, to name but a few, are also included.     

Identification of quantitative trait loci for prolificacy and growth in mice

Marker–quantitative trait locus (QTL) linkage was evaluated in F₂ intercross and backcross mouse populations derived from stocks differing dramatically in prolificacy and mature weight. A highly prolific outbred Quackenbush-Swiss mouse line, or an inbred line derived from it (16.62 ± 0.22 and 14.64 ± 0.27 pups per litter, respectively) were used as one of the grandparents in these populations. The less prolific C57BL/6J inbred mouse line (6.67 ± 0.37 pups per litter) was used as the other grandparent. Linkage was evaluated in a three-step process that involved selective genotyping of F₂ intercross progeny representing extremes for prolificacy, genotyping of the full F₂ for chromosomal regions potentially associated with prolificacy, and genotyping of the backcross for genomic regions significantly associated with prolificacy in the F₂. Segments of Chromosomes (Chrs) 2 and 4 were significantly (P < 0.05, experiment-wise error rate) associated with prolificacy, and LOD scores suggestive of linkage were observed for litter size on Chr 9 and growth on Chrs 4 and 11. Existence of growth QTL was also supported by marker effects that were significant (P < 0.05) or approaching significance (P < 0.10) in the backcross. Additive litter size QTL effects ranged from 0.56 to 0.79 pups per litter, and dominance deviations ranged from −0.56 to 1.19 pups per litter, suggesting overdominance as a possible mode of gene action in some cases. The observation of pleiotropic or linked QTL for growth and prolificacy corresponds well with results from many selection experiments identifying positively correlated responses to selection for these two traits. Received: 9 August 1997 / Accepted: 30 September 1997     

Identification of quantitative trait loci for susceptibility to mouse adenovirus type 1

Adult SJL/J mice are highly susceptible to mouse adenovirus type 1 (MAV-1) infections, whereas other inbred strains, including BALB/cJ, are resistant (K. R. Spindler, L. Fang, M. L. Moore, C. C. Brown, G. N. Hirsch, and A. K. Kajon, J. Virol. 75:12039-12046, 2001). Using congenic mouse strains, we showed that the H-2(s) haplotype of SJL/J mice is not associated with susceptibility to MAV-1. Susceptibility of MAV-1-infected (BALB/cJ x SJL/J)F(1) mice was intermediate between that of SJL/J mice and that of BALB/cJ mice, indicating that susceptibility is a genetically controlled quantitative trait. We mapped genetic loci involved in mouse susceptibility to MAV-1 by analysis of 192 backcross progeny in a genome scan with 65 simple sequence length polymorphic markers. A major quantitative trait locus (QTL) was detected on chromosome 15 (Chr 15) with a highly significant logarithm of odds score of 21. The locus on Chr 15 alone accounts for 40% of the total trait variance between susceptible and resistant strains. QTL modeling of the data indicated that there are a number of other QTLs with small effects that together with the major QTL on Chr 15 account for 54% of the trait variance. Identification of the major QTL is the first step in characterizing host genes involved in susceptibility to MAV-1.     

Ribosomal genes in inbred mouse strains: Interstrain and intrastrain variation of copy number and extent of methylation

Quantitative dot hybridization was used to estimate the rDNA copy number in brain tissues of five inbred mouse strains (AKR/JY, NZB/B1OrlY, CBA/CaLacY, 101/HY, and 129/JY), which were obtained from the collection of the Research Center of Biomedical Technologies (Y). In each strain, 9–12 mice aged 1–2 months were examined. The rDNA copy number per diploid genome in strains AKR (range 105–181, mean ± SD 136 ± 27) and NZB (129–169, 148 ± 12) was significantly lower than in strains CBA (172–267, 209 ± 31), 101 (179–270, 217 ± 30), and 129 (215–310, 264 ± 33). Mice of strain NZB were relatively homogeneous in this trait (CV = 8.1%). Strains AKR, CBA, 101, and 129 displayed significant between-group differences, CV varying from 12.5 to 19.9%. The same DNA specimens were digested with MspI or HpaII and used to estimate the extent of methylation of the 28S rDNA region. Regardless of the strain, all mice could be classed into two groups. One group (20 mice) had a methylated fraction accounting for less than 8% of rDNA and included all nine mice of strain NZB, seven out of nine mice of strain 101, and three out of ten mice of strain 129. In the other group (29 mice of strains AKR, CBA, 101, and 109), the methylated fraction varied from 18 to 38%. A possible role of methylation and the genome dosage of ribosomal genes in phenotypic variation (quantitative trait variation) of inbred mouse strains is discussed.