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Extensive Additivity of Gene Expression Differentiates

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Extensive Additivity of Gene Expression Differentiates Genetics: Published Articles Ahead of Print, published on October 18, 2007 as 10.1534/genetics.107.076190 Extensive additivity of gene expression differentiates subspecies of the house mouse Ruth Rottscheidt & Bettina Harr Institute for Genetics, University of Cologne, Zülpicher Strasse 47, 50674 Cologne, Germany Address for correspondence: Dr. Bettina Harr, Institute for Genetics, University of Cologne, Zülpicher Strasse 47, 50674 Cologne, Germany Email: [email protected] Tel: ++49 221 470 6617 Fax: ++49 221 470 5975 Keywords: house mouse, gene expression, F1 hybrid, speciation Running title: Additivity of gene expression Abstract We have studied different subspecies of the house mouse and their reciprocal F1 hybrids to estimate the within-locus mode of inheritance for subspecies differences in gene expression in three tissues (brain, liver, testis) of male mice. This study investigates mode of inheritance in crosses at a larger taxonomic distance than have been previously systematically investigated. We found the vast majority of transcripts to be additively expressed with only a few transcripts showing dominance or overdominance in expression, except for one direction of one cross, which showed large mis-expression in the testis. We suggest that as time passes, more genes come to influence expression, and if there is no directional dominance, additivity becomes increasingly more likely, up to a threshold beyond which there is F1 hybrid breakdown. Some previous studies on different organisms have found a large degree of dominance, commonly at shorter taxonomic differences. We surveyed these findings and show that the most consistent association exists between the amount of additivity detected in a study and expression analysis method (in particular microarray platform), suggesting that at least some of the differences among studies might be methodological. Most studies agree with ours in that within-locus additivity seems to be general mode of inheritance for transcript expression. Differentially expressed transcripts identified in our screen among subspecies of house mice are candidate genes that could be involved in reproductive isolation between these subspecies. Introduction The methods of quantitative genetics are now being applied to transcript abundance, as measured using microarrays. “Expression Quantitative Trait Locus” mapping (eQTL) identifies the genetic basis of expression differences between organisms (ROCKMAN and KRUGLYAK 2006). Such mapping studies are being used to ask how many loci contribute to a quantitative trait, what is the size of the effect of the loci, and how individual loci interact to generate a quantitative trait (MACKAY 2001). Treating gene expression levels as measured by microarrays as quantitative traits enables the simultaneous assessment of thousands of traits in parallel. eQTL studies can potentially also be used to ask whether regulatory variants, especially those that are important in evolution, are located in cis (i.e. directly linked to the gene that shows the differential expression) or in trans (i.e. somewhere else in the genome) (HOEKSTRA and COYNE 2007; WRAY 2007). Two approaches have been used to study the genetics of expression traits. In the first, DNA sequence polymorphisms are correlated with expression differences (BREM et al. 2002; DOSS et al. 2005; SCHADT et al. 2003; STOREY et al. 2005). A key finding from these studies is that expression traits are often affected by multiple underlying loci and interactions among them. The second approach makes use of F1 hybrids generated from a cross between divergent taxa to ask if a transcript’s expression is intermediate (“additive”) to that of the two parents. These studies have produced varying results. GIBSON et al. (2004) crossed two lines of Drosophila melanogaster and found most transcripts to be “nonadditivly” (i.e. the hybrids showed expression levels that were more closely to either on of the parents) expressed in F1 hybrids. Widespread nonadditivity was also identified in the Pacific Oyster (HEDGECOCK et al. 2007) and to a lesser extend in Arabidopsis (VUYLSTEKE et al. 2005). However, later studies on Drosophila (HUGHES et al. 2006), maize (STUPAR and SPRINGER 2006; SWANSON-WAGNER et al. 2006), and laboratory strains of the house mouse (CUI et al. 2006) were consistent with mostly additivity of expression. HUGHES et al. (2006) suggested the discrepancy between the different Drosophila studies might be explained in two ways. First, inbreeding might affect the results. Much within-locus additivity was observed using natural populations of D. melanogaster (HUGHES et al. 2006) while nonadditivity was observed with strongly inbred lines (GIBSON et al. 2004). It is well known that crosses between inbred strains produce offspring that exhibit greater biomass, speed of development, and fertility than both parents (heterosis) (COMINGS and MACMURRAY 2000). Heterosis is attributed to overdominance (superiority of heterozygotes at genes affecting fitness) or dominance (masking of recessive deleterious mutations) and plausibly could result in overdominant or dominant expression at the transcript level. However the inbreeding explanation seems to be an unlikely general explanation because additional recent studies have found strong evidence for additivity despite the use of inbred parental lines (CUI et al. 2006; STUPAR and SPRINGER 2006; SWANSON-WAGNER et al. 2006). A second explanation for the Drosophila differences is that genetic architecture of an expression trait might depend critically on the taxonomic level at which the variation is investigated (i.e., between populations as in the GIBSON et al. (2004) study as opposed to within populations as in the HUGHES et al. (2006) study). These authors assume that the more highly diverged the parents are the greater the nonadditivity in gene expression that will be observed. However, we might expect additivity of expression to become more likely as taxa diverge and the trait becomes influenced by more and more genes, provided that they do not show directional dominance. This would apply up to some certain threshold, beyond which incompatible genes lead to massive mis-expression in F1 hybrids. Here we investigate patterns of expression in the house mouse subspecies complex of Mus musculus. We used parental mouse strains that were collected in the wild and inbred in the laboratory for several generations. The strains belong to the three different subspecies of house mice, M. m. musculus, M. m. domesticus and M. m. castaneus, with estimated divergence times of between 300,000 to 1 Million years (BOURSOT et al. 1993). Previous systematic studies focused on comparisons within a single species or used house mouse laboratory strains. In contrast, our study employs natural-derived lines that are rather highly diverged. We found predominantly additive gene expression differences between these subspecies. Materials and Methods Mouse strains Wild-derived strains of domesticus (JPC 2705, from Germany), musculus (JPC 2821, from the Czech Republic) and castaneus (CIM, from India) were used for the microarray experiment. The domesticus and musculus strains were provided by J. Pialek. These strains were collected in the wild and inbred by brother-sister matings for ~13 generations in the laboratory of J. Pialek in the Department of Population Biology in Studenec, Czech Republic. The castaneus strain was provided by A. Orth and F. Bonhomme. This strain has been kept in the Laboratory Génome, Populations, Interactions, Adaptation, Montpellier, France for more than 30 generations in a closed colony. We set up reciprocal crosses between domesticus and musculus and between musculus and castaneus to obtain F1 hybrids. For each parental strain and each reciprocal cross two male individuals were analyzed. Altogether, we performed 42 microarray experiments, 14 in each of three tissues (brain, liver and testis). An overview of the samples used in this study is given in Table 1. All mice were raised under identical standard laboratory conditions and were sacrificed at the age of 8-10 weeks. RNA extraction We extracted RNA from three different tissues (brain, liver and testis) using Trizol® (Invitrogen, Carlsbad, CA) following the manufacturer’s protocol. Quality and integrity of the total RNA was controlled by using the Agilent Technologies 2100 Bioanalyzer and the RNA 6000 Nano LabChip® Kit (Agilent Technologies; Waldbronn, Germany). Microarray Expression profiles were determined for over 39,000 mouse transcripts using the Mouse Genome 430 2.0 Affymetrix® GeneChip ®. For biotin-labeled target synthesis starting from 3 µg of total RNA we used standard protocols supplied by the manufacturer (Affymetrix; Santa Clara, CA). After hybridization the GeneChips ® were washed, stained with SA-PE and read using an Affymetrix ® GeneChip ® fluidic station and scanner. Data analysis All data processing and statistical analyses were performed using the statistical language R. Raw signal intensities were normalized and summarized according to the standard Affymetrix MA Suite 5.0 algorithm using the program Bioconductor (http://www.bioconductor.org/). Signal intensities were ln-transformed prior to statistical analyses. MA Suite 5.0 expression values have been submitted to the Gene Expression Omnibus (accession number XX). We define a “group” as one of domesticus, musculus, castaneus, F1 hybrids from one direction of the cross, or F1 hybrids from the other direction of the cross. We called a transcript “expressed” in this
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