Evaluation of heritable determinants of blood and brain serotonin homeostasis using recombinant inbred mice

The biogenic amine serotonin (5‐HT, 5‐hydroxytryptamine) exerts powerful, modulatory control over multiple physiological functions in the brain and periphery, ranging from mood and appetite to vasoconstriction and gastrointestinal motility. In order to gain insight into shared and distinct molecular and phenotypic networks linked to variations in 5‐HT homeostasis, we capitalized on the stable genetic variation present in recombinant inbred mouse strains. This family of strains, all derived from crosses between C57BL/6J and DBA/2J (BXD) parents, represents a unique, community resource with approximately 40 years of assembled phenotype data that can be exploited to explore and test causal relationships in silico. We determined levels of 5‐HT and 5‐hydroxyindoleacetic acid from whole blood, midbrain and thalamus/hypothalamus (diencephalon) of 38 BXD lines and both sexes. All 5‐HT measures proved highly heritable in each region, although both gender and region significantly impacted between‐strain correlations. Our studies identified both expected and novel biochemical, anatomical and behavioral phenotypes linked to 5‐HT traits, as well as distinct quantitative trait loci. Analyses of these loci nominate a group of genes likely to contribute to gender‐ and region‐specific capacities for 5‐HT signaling. Analysis of midbrain mRNA variations across strains revealed overlapping gene expression networks linked to 5‐HT synthesis and metabolism. Altogether, our studies provide a rich profile of genomic, molecular and phenotypic networks that can be queried for novel relationships contributing risk for disorders linked to perturbed 5‐HT signaling .     

Brain Serotonin Transporter Binding of [123I]ADAM: Within‐Subject Variation between Summer and Winter Data

The neurotransmitter serotonin (5‐HT) controls several physiological functions, and a disturbance of the 5‐HT system is implicated in many psychiatric conditions. Seasonal variation has been suggested in the 5‐HT system. We investigated within‐subject seasonal variation in brain serotonin transporter (SERT) binding with the SERT‐ligand [¹²³I]ADAM and single photon emission computed tomography (SPECT) in 12 healthy individuals. No systematic variation was found in the midbrain or thalamus areas between scans done in summer and winter. Our results suggest that factors other than season are more important in causing within‐subject variation of brain SERT binding between summer and winter. (Author correspondence: anu.koskela@helsinki.fi)     

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.     

A nonsynonymous SNP within PCDH15 is associated with lipid traits in familial combined hyperlipidemia

Familial combined hyperlipidemia (FCHL) is a common lipid disorder characterized by the presence of multiple lipoprotein phenotypes that increase the risk of premature coronary heart disease. In a previous study, we identified an intragenic microsatellite marker within the protocadherin 15 (PCDH15) gene to be associated with high triglycerides (TGs) in Finnish dyslipidemic families. In this study we analyzed all four known nonsynonymous SNPs within PCDH15 in 1,268 individuals from Finnish and Dutch multigenerational families with FCHL. Association analyses of quantitative traits for SNPs were performed using the QTDT test. The nonsynonymous SNP rs10825269 resulted in a P = 0.0006 for the quantitative TG trait. Additional evidence for association was observed with the same SNP for apolipoprotein B levels (apo-B) (P = 0.0001) and total cholesterol (TC) levels (P = 0.001). None of the other three SNPs tested showed a significant association with any lipid-related trait. We investigated the expression of PCDH15 in different human tissues and observed that PCDH15 is expressed in several tissues including liver and pancreas. In addition, we measured the plasma lipid levels in mice with loss-of-function mutations in Pcdh15 (Pcdh15^av-Tg and Pcdh15^av-3J) to investigate possible abnormalities in their lipid profile. We observed a significant difference in plasma TG and TC concentrations for the Pcdh15^av-3J carriers when compared with the wild type (P = 0.013 and P = 0.044, respectively). Our study suggests that PCDH15 is associated with lipid abnormalities.     

QTL analysis of white blood cell, platelet and red blood cell-related traits in an F2 intercross between Landrace and Korean native pigs

Haematological traits play important roles in disease resistance and defence functions. The objective of this study was to locate quantitative trait loci (QTL) and the associated positional candidate genes influencing haematological traits in an F₂ intercross between Landrace and Korean native pigs. Eight blood‐related traits (six erythrocyte traits, one leucocyte trait and one platelet trait) were measured in 816 F₂ progeny. All experimental animals were genotyped with 173 informative microsatellite markers located throughout the pig genome. We report that nine chromosomes harboured QTL for the baseline blood parameters: genomic regions on SSC 1, 4, 5, 6, 8, 9, 11, 13 and 17. Eight of twenty identified QTL reached genome‐wide significance. In addition, we evaluated the KIT locus, an obvious candidate gene locus affecting variation in blood‐related traits. Using dense single nucleotide polymorphism marker data on SSC 8 and the marker‐assisted association test, the strong association of the KIT locus with blood phenotypes was confirmed. In conclusion, our study identified both previously reported and novel QTL affecting baseline haematological parameters in pigs. Additionally, the positional candidate genes identified here could play an important role in elucidating the genetic architecture of haematological phenotype variation in swine and in humans.     

Interval mapping of quantitative trait loci for reproductive,morphological, and seed traits of soybean (Glycine max L.)

Quantitative trait loci (QTL) were mapped in segregating progeny from a cross between two soybean (Glycine max (L.) Merr.) cultivars: Minsoy (PI 27.890) and Noir 1 (PI 290.136). The 15 traits analyzed included reproductive, morphological, and seed traits, seed yield and carbon isotope discrimination ratios (¹³C/¹²C). Genetic variation was detected for all of the traits, and transgressive segregation was a common phenomenon. One hundred and thirty-two linked genetic markers and 24 additional unlinked markers were used to locate QTL by interval mapping and one-way analysis of variance, respectively. Quantitative trait loci controlling 11 of the 15 traits studied were localized to intervals in 6 linkage groups. Quantitative trait loci for developmental and morphological traits (R1, R5, R8, plant height, canopy height, leaf area, etc.) tended to be clustered in three intervals, two of which were also associated with seed yield. Quantitative trait loci for seed oil were separated from all the other QTL. Major QTL for maturity and plant height were linked to RFLP markers R79 (31% variation) and G173 (53% variation). Quantitative trait loci associated with unlinked markers included possible loci for seed protein and weight. Linkage between QTL is discussed in relation to the heritability and genetic correlation of the traits.     

Identification of quantitative trait loci and candidate genes for an anxiolytic‐like response to ethanol in BXD recombinant inbred strains

Genetic differences in acute behavioral responses to ethanol contribute to the susceptibility to alcohol use disorder and the reduction of anxiety is a commonly reported motive underlying ethanol consumption among alcoholics. Therefore, we studied the genetic variance in anxiolytic‐like responses to ethanol across the BXD recombinant inbred (RI) mouse panel using the light–dark transition model of anxiety. Strain‐mean genetic mapping and a mixed‐model quantitative trait loci (QTL) analysis replicated several previously published QTL for locomotor activity and identified several novel anxiety‐related loci. Significant loci included a chromosome 11 saline anxiety‐like QTL (Salanq1) and a chromosome 12 locus (Etanq1) influencing the anxiolytic‐like response to ethanol. Etanq1 was successfully validated by studies with BXD advanced intercross strains and fine‐mapped to a region comprising less than 3.5 Mb. Through integration of genome‐wide mRNA expression profiles of the mesocorticolimbic reward circuit (prefrontal cortex, nucleus accumbens and ventral midbrain) across the BXD RI panel, we identified high priority candidate genes within Etanq1, the strongest of which was Ninein (Nin), a Gsk3β‐interacting protein that is highly expressed in the brain.     

From QTLs for enzyme activity to candidate genes in maize

In order to facilitate the search for genes underlying QTLs (Quantitative Trait Loci), the activities of key enzymes of the carbohydrate metabolism in maize, and the concentration of their substrates or products were used as quantitative traits. For each of the chosen enzyme, i.e. ADPglucose pyrophosphorylase, sucrose-phosphate-synthase and invertases, the corresponding cDNA was available. Since biochemical traits are more closely related to gene expression than agronomic traits, co-locations could be expected between an enzyme structural gene and a QTL for its enzyme activity, and/or the corresponding product or substrate content. This approach was applied using recombinant inbred lines on leaves at 3- or 4-leaf stage, under control and water stress conditions and on grain, at maturity. Several QTLs were detected for each trait, particularly for two enzyme activities measured in mature leaves. Apparent co-locations between QTL for activity and structural locus were observed for sucrose-phosphate-synthase (chromosome 8) and acid-soluble invertase (chromosome 2 and 5). Leaf acid-soluble (vacuolar) invertase provided an interesting case since QTL, on chromosome 5, explaining 17% of variability was apparently co-located with the Ivr2 gene encoding a vacuolar invertase protein which was strongly water-stress inducible. Similarly, in grain, an amylose QTL co-located with the Sh2 gene of ADPglucose pyrophosphorylase. The reliability of this candidate was further tested through the examination of Sh2 DNA polymorphism in 46 genetically unrelated lines. A correlation was obtained between this polymorphism and kernel starch content, which further validated Sh2 as a candidate. Some improvements or alternatives to this strategy are briefly discussed.      

Deciphering the genomic architecture of the stickleback brain with a novel multilocus gene‐mapping approach

Quantitative traits important to organismal function and fitness, such as brain size, are presumably controlled by many small‐effect loci. Deciphering the genetic architecture of such traits with traditional quantitative trait locus (QTL) mapping methods is challenging. Here, we investigated the genetic architecture of brain size (and the size of five different brain parts) in nine‐spined sticklebacks (Pungitius pungitius) with the aid of novel multilocus QTL‐mapping approaches based on a de‐biased LASSO method. Apart from having more statistical power to detect QTL and reduced rate of false positives than conventional QTL‐mapping approaches, the developed methods can handle large marker panels and provide estimates of genomic heritability. Single‐locus analyses of an F₂ interpopulation cross with 239 individuals and 15 198, fully informative single nucleotide polymorphisms (SNPs) uncovered 79 QTL associated with variation in stickleback brain size traits. Many of these loci were in strong linkage disequilibrium (LD) with each other, and consequently, a multilocus mapping of individual SNPs, accounting for LD structure in the data, recovered only four significant QTL. However, a multilocus mapping of SNPs grouped by linkage group (LG) identified 14 LGs (1–6 depending on the trait) that influence variation in brain traits. For instance, 17.6% of the variation in relative brain size was explainable by cumulative effects of SNPs distributed over six LGs, whereas 42% of the variation was accounted for by all 21 LGs. Hence, the results suggest that variation in stickleback brain traits is influenced by many small‐effect loci. Apart from suggesting moderately heritable (h² ≈ 0.15–0.42) multifactorial genetic architecture of brain traits, the results highlight the challenges in identifying the loci contributing to variation in quantitative traits. Nevertheless, the results demonstrate that the novel QTL‐mapping approach developed here has distinctive advantages over the traditional QTL‐mapping methods in analyses of dense marker panels.     

Genetic variation in the β, β‐carotene‐9′, 10′‐dioxygenase gene and association with fat colour in bovine adipose tissue and milk

β, β‐carotene‐9′, 10′‐dioxygenase (BCO2) plays a role in cleaving β‐carotene eccentrically, and may be involved in the control of adipose and milk colour in cattle. The bovine BCO2 gene was sequenced as a potential candidate gene for a beef fat colour QTL on chromosome (BTA) 15. A single nucleotide base change located in exon 3 causes the substitution of a stop codon (encoded by the A allele) for tryptophan⁸⁰ (encoded by the G allele) (c. 240G>A, p.Trp80stop, referred to herein as SNP W80X). Association analysis showed significant differences in subcutaneous fat colour and beta‐carotene concentration amongst cattle with different BCO2 genotypes. Animals with the BCO2 AA genotype had more yellow beef fat and a higher beta‐carotene concentration in adipose tissues than those with the GA or GG genotype. QTL mapping analysis with the BCO2 SNP W80X fitted as a fixed effect confirmed that this SNP is likely to represent the quantitative trait nucleotide (QTN) for the fat colour‐related traits on BTA 15. Moreover, animals with the AA genotype had yellower milk colour and a higher concentration of beta‐carotene in the milk.     

Two-trait selection response with marker-based assortative mating

 Marker-based assortative mating (MAM) – the mating of individuals that have similar genotypes at random marker loci – can increase selection response for a single trait by 3–8% over random mating (RM). Genetic gain is usually desired for multiple traits rather than for a single trait. My objectives in this study were to (1) compare MAM, phenotypic assortative mating (PAM), and RM of selected individuals for improving two traits and (2) determine when MAM will be most useful for improving two traits. I simulated 20 generations of selecting 32 out of 200 individuals in an F₂ population. The individuals were selected based on an index (SI) of two traits and were intermated by MAM, PAM, or RM. I studied eight genetic models that differed in three contrasts: (1) weight, number of quantitative trait loci (QTL), and heritability (h ²) for each trait; (2) linkage of QTL for each trait; and (3) trait means of the inbred parents of the F₂. For SI and the two component traits, MAM increased short-term selection response by 5–8% in six out of the eight genetic models. The MAM procedure was least effective in two genetic models, wherein the QTL for one trait were unlinked to the QTL for the other trait and the parents of the F₂ had divergent means for each trait. The loss of QTL heterozygosity was much greater with MAM than with PAM or RM. Consequently, the advantage of MAM over RM dissipated after 5–7 generations. Differences were small between selection responses with PAM and RM. The MAM procedure can enhance short-term selection response for two traits when selection is not stringent, h ² is low, and the means of the parents of the F₂ are equal for each trait. Received: 10 June 1998 / Accepted: 5 August 1998     

Systems genetics analysis of iron regulation in the brain

Iron imbalances in the brain, including excess accumulation and deficiency, are associated with neurological disease and dysfunction; yet, their origins are poorly understood. Using systems genetics analysis, we have learned that large individual differences exist in brain iron concentrations, even in the absence of neurological disease. Much of the individual differences can be tied to the genetic makeup of the individual. This genetic-based differential regulation can be modeled in genetic reference populations of rodents. The work in our laboratory centers on iron regulation in the brain and our animal model consists of 25 BXD/Ty recombinant inbred mouse strains. By studying naturally occurring variation in iron phenotypes, such as tissue iron concentration, we can tie that variability to one or more genes by way of quantitative trait loci (QTL) analysis. Moreover, we can conduct genetic correlation analyses between our phenotypes and others previously measured in the BXD/Ty strains. We have observed several suggestive QTL related to ventral midbrain iron content, including one on chromosome 17 that contains btbd9, a gene that in humans has been associated with restless legs syndrome and serum ferritin. We have also observed gene expression correlations with ventral midbrain iron, including btbd9 expression and dopamine receptor expression. In addition, we have observed significant correlations between ventral midbrain iron content and dopamine-related phenotypes. The following is a discussion of iron regulation in the brain and the contributions a systems genetics approach can make toward understanding the genetic underpinnings and relation to neurological disease.     

QTL consistency and meta-analysis for grain yield components in three generations in maize

Grain yield is the most important and complex trait in maize. In this study, a total of 258 F₉ recombinant inbred lines (RIL), derived from a cross between dent corn inbred Dan232 and popcorn inbred N04, were evaluated for eight grain yield components under four environments. Quantitative trait loci (QTL) and their epistatic interactions were detected for all traits under each environment and in combined analysis. Meta-analysis was used to integrate genetic maps and detected QTL across three generations (RIL, F_2:3 and BC₂F₂) derived from the same cross. In total, 103 QTL, 42 pairs of epistatic interactions and 16 meta-QTL (mQTL) were detected. Twelve out of 13 QTL with contributions (R ²) over 15% were consistently detected in 3–4 environments (or in combined analysis) and integrated in mQTL. Only q100GW-7-1 was detected in all four environments and in combined analysis. 100qGW-1-1 had the largest R ² (19.3–24.6%) in three environments and in combined analysis. In contrast, 35 QTL for 6 grain yield components were detected in the BC₂F₂ and F_2:3 generations, no common QTL across three generations were located in the same marker intervals. Only 100 grain weight (100GW) QTL on chromosome 5 were located in adjacent marker intervals. Four common QTL were detected across the RIL and F_2:3 generations, and two between the RIL and BC₂F₂ generations. Each of five important mQTL (mQTL7-1, mQTL10-2, mQTL4-1, mQTL5-1 and mQTL1-3) included 7–12 QTL associated with 2–6 traits. In conclusion, we found evidence of strong influence of genetic structure and environment on QTL detection, high consistency of major QTL across environments and generations, and remarkable QTL co-location for grain yield components. Fine mapping for five major QTL (q100GW-1-1, q100GW-7-1, qGWP-4-1, qERN-4-1 and qKR-4-1) and construction of single chromosome segment lines for genetic regions of five mQTL merit further studies and could be put into use in marker-assisted breeding.     

Relation among plant growth,carbohydrates and flowering time in the Arabidopsis Landsberg erecta × Kondara recombinant inbred line population

Arabidopsis thaliana natural variation was used to study plant performance viewed as the accumulation of photo‐assimilates, their allocation and storage, in relation to other growth‐related features and flowering‐related traits. Quantitative trait locus (QTL) analysis using recombinant inbred lines derived from the cross between Landsberg erecta (originating from Poland) and Kondara (originating from Tajikistan) grown on hydroponics, revealed QTLs for the different aspects of plant growth‐related traits, sugar and starch contents and flowering‐related traits. Co‐locations of QTLs for these different aspects were detected at different regions, mainly at the ER locus; the top of chromosomes 3, 4 and 5; and the bottom of chromosome 5. Increased plant growth was associated with early flowering and leaf transitory starch, and correlated negatively with the levels of soluble sugar at early phases of development. From the significant correlations and the co‐locations of the QTLs for these aspects, we conclude that there is a complex relationship between plant growth‐related traits, carbohydrate content and flowering‐related traits.     

Genome‐wide SNP analysis identifies major QTL for Salmonella colonization in the chicken

Salmonella‐infected poultry products are a major source of human Salmonella infection. The prophylactic use of antimicrobials in poultry production was recently banned in the EU, increasing the need for alternative methods to control Salmonella infections in poultry flocks. Genetic selection of chickens more resistant to Salmonella colonization provides an attractive means of sustainably controlling the pathogen in commercial poultry flocks and its subsequent entry into the food chain. Analysis of different inbred chickens has shown that individual lines are consistently either susceptible or resistant to the many serovars of Salmonella that have been tested. In this study, two inbred chicken lines with differential susceptibility to Salmonella colonization (6₁^(R) and N^(S)) were used in a backcross experimental design. Unlike previous studies that used a candidate gene approach or low‐density genome‐wide screens, we have exploited a high‐density marker set of 1255 SNPs covering the whole genome to identify quantitative trait loci (QTL). Analysis of log‐transformed caecal bacterial levels between the parental lines revealed a significant difference at 1, 2, 3 and 4 days post‐infection (P < 0.05). Analysis of the genotypes of the backcross (F₁ × N) population (n = 288) revealed four QTL on chromosomes 2, 3, 12 and 25 for the two traits examined in this study: log‐transformed bacterial counts in the caeca and presence of a hardened caseous caecal core. These included one genome‐wide significant QTL on chromosome 2 at 20 Mb and three additional QTL, on chromosomes 3, 12 and 25 at 96, 15 and 1 Mb, respectively, which were significant at the chromosome‐wide level (P < 0.05). The results generated in this study will inform future breeding strategies to control these pathogens in commercial poultry flocks.     

QTL mapping of <Emphasis Type="Italic">Sclerotinia</Emphasis> midstalk-rot resistance in sunflower

In many sunflower-growing regions of the world, Sclerotinia sclerotiorum (Lib.) de Bary is the major disease of sunflower (Helianthus annuus L.). In this study, we mapped and characterized quantitative trait loci (QTL) involved in resistance to S. sclerotiorum midstalk rot and two morphological traits. A total of 351 F₃ families developed from a cross between a resistant inbred line from the germplasm pool NDBLOS and the susceptible line CM625 were assayed for their parental F₂ genotype at 117 codominant simple sequence repeat markers. Disease resistance of the F₃ families was screened under artificial infection in field experiments across two sowing times in 1999. For the three resistance traits (leaf lesion, stem lesion, and speed of fungal growth) and the two morphological traits, genotypic variances were highly significant. Heritabilities were moderate to high (h²=0.55–0.89). Genotypic correlations between resistance traits were highly significant (P<0.01) but moderate. QTL were detected for all three resistance traits, but estimated effects at most QTL were small. Simultaneously, they explained between 24.4% and 33.7% of the genotypic variance for resistance against S. sclerotiorum. Five of the 15 genomic regions carrying a QTL for either of the three resistance traits also carried a QTL for one of the two morphological traits. The prospects of marker-assisted selection (MAS) for resistance to S. sclerotiorum are limited due to the complex genetic architecture of the trait. MAS can be superior to classical phenotypic selection only with low marker costs and fast selection cycles.     

Genome‐wide expression quantitative trait locus studies facilitate isolation of causal genes controlling panicle structure

The morphology of rice (Oryza sativa L.) panicles is an important determinant of grain yield, and elucidation of the genetic control of panicle structure is very important for fulfilling the demand for high yield in breeding programs. In a quantitative trait locus (QTL) study using 82 backcross inbred lines (BILs) derived from Koshihikari and Habataki, 68 QTLs for 25 panicle morphological traits were identified. Gene expression profiling from inflorescence meristems of BILs was obtained. A combination of phenotypic QTL (pQTL) and expression QTL (eQTL) analysis revealed co‐localization between pQTLs and eQTLs, consistent with significant correlations between phenotypic traits and gene expression levels. By combining pQTL and eQTL data, two genes were identified as controlling panicle structure: OsMADS18 modulates the average length of the primary rachis and OsFTL1 has pleiotropic effects on the total number of secondary rachides, number of grains per panicle, plant height and the length of flag leaves. Phenotypes were confirmed in RNA interference knocked‐down plants and overexpressor lines. The combination of pQTL and eQTL analysis could facilitate identification of genes involved in rice panicle formation.     

np2QTL: networking phenotypic plasticity quantitative trait loci across heterogeneous environments

Despite its critical importance to our understanding of plant growth and adaptation, the question of how environment‐induced plastic response is affected genetically remains elusive. Previous studies have shown that the reaction norm of an organism across environmental index obeys the allometrical scaling law of part‐whole relationships. The implementation of this phenomenon into functional mapping can characterize how quantitative trait loci (QTLs) modulate the phenotypic plasticity of complex traits to heterogeneous environments. Here, we assemble functional mapping and allometry theory through Lokta?Volterra ordinary differential equations (LVODE) into an R‐based computing platform, np²QTL, aimed to map and visualize phenotypic plasticity QTLs. Based on LVODE parameters, np²QTL constructs a bidirectional, signed and weighted network of QTL?QTL epistasis, whose emergent properties reflect the ecological mechanisms for genotype?environment interactions over any range of environmental change. The utility of np²QTL was validated by comprehending the genetic architecture of phenotypic plasticity via the reanalysis of published plant height data involving 3502 recombinant inbred lines of maize planted in multiple discrete environments. np²QTL also provides a tool for constructing a predictive model of phenotypic responses in extreme environments relative to the median environment.     

How replicable are mRNA expression QTL?

Applying quantitative trait analysis methods to genome-wide microarray-derived mRNA expression phenotypes in segregating populations is a valuable tool in the attempt to link high-level traits to their molecular causes. The massive multiple-testing issues involved in analyzing these data make the correct level of confidence to place in mRNA abundance quantitative trait loci (QTL) a difficult problem. We use a unique resource to directly test mRNA abundance QTL replicability in mice: paired recombinant inbred (RI) and F₂ data sets derived from C57BL/6J (B6) and DBA/2J (D2) inbred strains and phenotyped using the same Affymetrix arrays. We have one forebrain and one striatum data set pair. We describe QTL replication at varying stringencies in these data. For instance, 78% of mRNA expression QTL (eQTL) with genome-wide adjusted p ≤ 0.0001 in RI data replicate at a genome-wide adjusted p < 0.05 or better. Replicated QTL are disproportionately putatively cis-acting, and approximately 75% have higher apparent expression levels associated with B6 genotypes, which may be partly due to probe set generation using B6 sequence. Finally, we note that while trans-acting QTL do not replicate well between data sets in general, at least one cluster of trans-acting QTL on distal Chr 1 is notably preserved between data sets.