Dimension reduction for mapping mRNA abundance as quantitative traits

The advent of sophisticated genomic techniques for gene mapping and microarray analysis has provided opportunities to map mRNA abundance to quantitative trait loci (QTL) throughout the genome. Unfortunately, simple mapping of each individual mRNA trait on the scale of a typical microarray experiment is computationally intensive, subject to high sample variance, and therefore underpowered. However, this problem can be addressed by capitalizing on correlation among the large number of mRNA traits. We present a method to reduce the dimensionality for mapping gene expression data as quantitative traits. We used a blind method, principal components, and a sighted method, hierarchical clustering seeded by disease relevant traits, to define new traits composed of a small collection of promising mRNAs. We validated the principle of our approach by mapping the expression levels of metabolism genes in a population of F(2)-ob/ob mice derived from the BTBR and C57BL/6J strains. We found that lipogenic and gluconeogenic mRNAs, which are known targets of insulin action, were closely associated with the insulin trait. Multiple interval mapping and Bayesian interval mapping of this new trait revealed significant linkages to chromosome regions that were contained in loci associated with type 2 diabetes in this same mouse sample. As a further statistical refinement, we show that principal component analysis also effectively reduced dimensions for mapping phenotypes composed of mRNA abundances.     

Covariation of larval gene expression and adult body size in natural populations of Drosophila melanogaster

Understanding adaptive phenotypic variation is one of the most fundamental problems in evolutionary biology. Genes involved in adaptation are most likely those that affect traits most intimately connected to fitness: life-history traits. The genetics of quantitative trait variation (including life histories) is still poorly understood, but several studies suggest that (1) quantitative variation might be the result of variation in gene expression, rather than protein evolution, and (2) natural variation in gene expression underlies adaptation. The next step in studying the genetics of adaptive phenotypic variation is therefore an analysis of naturally occuring covariation of global gene expression and a life-history trait. Here, we report a microarray study addressing the covariation in larval gene expression and adult body weight, a life-history trait involved in adaptation. Natural populations of Drosophila melanogaster show adaptive geographic variation in adult body size, with larger animals at higher latitudes. Conditions during larval development also affect adult size with larger flies emerging at lower temperatures. We found statistically significant differences in normalized larval gene expression between geographic populations at one temperature (genetic variation) and within geographic populations between temperatures (developmental plasticity). Moreover, larval gene expression correlated highly with adult weight, explaining 81% of its natural variation. Of the genes that show a correlation of gene expression with adult weight, most are involved in cell growth or cell maintenance or are associated with growth pathways.     

A single origin for nymphalid butterfly eyespots followed by widespread loss of associated gene expression

Understanding how novel complex traits originate involves investigating the time of origin of the trait, as well as the origin of its underlying gene regulatory network in a broad comparative phylogenetic framework. The eyespot of nymphalid butterflies has served as an example of a novel complex trait, as multiple genes are expressed during eyespot development. Yet the origins of eyespots remain unknown. Using a dataset of more than 400 images of butterflies with a known phylogeny and gene expression data for five eyespot-associated genes from over twenty species, we tested origin hypotheses for both eyespots and eyespot-associated genes. We show that eyespots evolved once within the family Nymphalidae, approximately 90 million years ago, concurrent with expression of at least three genes associated with early eyespot development. We also show multiple losses of expression of most genes from this early three-gene cluster, without corresponding losses of eyespots. We propose that complex traits, such as eyespots, may have originated via co-option of a large pre-existing complex gene regulatory network that was subsequently streamlined of genes not required to fulfill its novel developmental function.     

Correlated changes in male plumage coloration and female mate choice in cardueline finches

The coevolution of extravagant male traits and female mate preferences is a central tenet of sexual selection theory. In lineages in which males have developed more elaborate sexual characters, females favour the most extreme expression of the trait. In some taxa, however, ornamental displays have evolved from more to less exaggerated states. Under these circumstances, it is unclear whether females show preferences for an ancestral male condition or for the current, less elaborate display. Here, we tested female mate preferences relative to male ornamental coloration in two species of cardueline finch (the American goldfinch, Carduelis tristis, and pine siskin, Carduelis pinus) that have evolved less elaborate carotenoid-based colour displays from more elaborately coloured ancestral states. We presented females of each species with a choice of males having either large patches of red colour (the elaborate, ancestral condition) or with species-typical patches of yellow colour (the less elaborate, derived state). Female goldfinches and siskins showed consistent preferences for the natural colour displays of males, and not for the more elaborate, ancestral colour pattern. Previous research on another cardueline finch taxon (a subspecies of the house finch, Carpodacus mexicanus griscomi), however, showed that females prefer more elaborate, ancestral coloration to the current form of reduced colour expression. The lack of congruence between male trait expression and female trait preference in the lineage with the most recently derived reduction in trait expression suggests that there may be evolutionary lags in the correspondence between male traits and female preferences. A shift in the expression of male coloration appears to be the first step towards the evolution of reduced colour displays in these finches.     

Why are rare traits unilaterally expressed?: Trait frequency and unilateral expression for cranial nonmetric traits in humans

Based on an analysis of nonmetric trait databases from several large skeletal series in Northern Europe and South America, representing 27 bilateral traits, we report a predictable relationship between the frequency of nonmetric traits and the probability that they are expressed bilaterally. In a wider sampling of traits and populations, this study thus confirms the findings of an earlier study by Ossenberg ([1981] Am. J. Phys. Anthropol. 54:471-479), which reported the same relationship for two mandibular traits. This trend was previously explained by extending the multifactorial threshold model for discontinuous traits to incorporate either separate thresholds for unilateral or bilateral expression, or by a fuzzy threshold in which the probability of bilateral expression increases away from the median threshold value. We show that the trend is produced under the standard multifactorial threshold model for discontinuous traits simply if the within-individual or developmental instability variance remains relatively constant across the range of liability. Under this assumption, the number of individuals in which one side but not the other is pushed over the threshold for trait formation will be a larger proportion of the number of individuals expressing the trait when the trait frequency is low. As trait frequency increases, the significance of within-individual variance as a determinant of trait formation decreases relative to the genetic and among-individual environmental variance. These results have implications for interpreting nonmetric trait data as well as for understanding the prevalence of unilateral vs. bilateral expression of a wide variety of discontinuous traits, including dysmorphologies in humans.     

Do large effect QTL fractionate? A case study at the maize domestication QTL teosinte branched1

Quantitative trait loci (QTL) mapping is a valuable tool for studying the genetic architecture of trait variation. Despite the large number of QTL studies reported in the literature, the identified QTL are rarely mapped to the underlying genes and it is usually unclear whether a QTL corresponds to one or multiple linked genes. Similarly, when QTL for several traits colocalize, it is usually unclear whether this is due to the pleiotropic action of a single gene or multiple linked genes, each affecting one trait. The domestication gene teosinte branched1 (tb1) was previously identified as a major domestication QTL with large effects on the differences in plant and ear architecture between maize and teosinte. Here we present the results of two experiments that were performed to determine whether the single gene tb1 explains all trait variation for its genomic region or whether the domestication QTL at tb1 fractionates into multiple linked QTL. For traits measuring plant architecture, we detected only one QTL per trait and these QTL all mapped to tb1. These results indicate that tb1 is the sole gene for plant architecture traits that segregates in our QTL mapping populations. For most traits related to ear morphology, we detected multiple QTL per trait in the tb1 genomic region, including a large effect QTL at tb1 itself plus one or two additional linked QTL. tb1 is epistatic to two of these additional QTL for ear traits. Overall, these results provide examples for both a major QTL that maps to a single gene, as well as a case in which a QTL fractionates into multiple linked QTL.     

A study of CNVs as trait-associated polymorphisms and as expression quantitative trait loci

We conducted a comprehensive study of copy number variants (CNVs) well-tagged by SNPs (r(2)≥ 0.8) by analyzing their effect on gene expression and their association with disease susceptibility and other complex human traits. We tested whether these CNVs were more likely to be functional than frequency-matched SNPs as trait-associated loci or as expression quantitative trait loci (eQTLs) influencing phenotype by altering gene regulation. Our study found that CNV-tagging SNPs are significantly enriched for cis eQTLs; furthermore, we observed that trait associations from the NHGRI catalog show an overrepresentation of SNPs tagging CNVs relative to frequency-matched SNPs. We found that these SNPs tagging CNVs are more likely to affect multiple expression traits than frequency-matched variants. Given these findings on the functional relevance of CNVs, we created an online resource of expression-associated CNVs (eCNVs) using the most comprehensive population-based map of CNVs to inform future studies of complex traits. Although previous studies of common CNVs that can be typed on existing platforms and/or interrogated by SNPs in genome-wide association studies concluded that such CNVs appear unlikely to have a major role in the genetic basis of several complex diseases examined, our findings indicate that it would be premature to dismiss the possibility that even common CNVs may contribute to complex phenotypes and at least some common diseases.     

A stochastic expectation and maximization algorithm for detecting quantitative trait-associated genes

MOTIVATION: Most biological traits may be correlated with the underlying gene expression patterns that are partially determined by DNA sequence variation. The correlations between gene expressions and quantitative traits are essential for understanding the functions of genes and dissecting gene regulatory networks. RESULTS: In the present study, we adopted a novel statistical method, called the stochastic expectation and maximization (SEM) algorithm, to analyze the associations between gene expression levels and quantitative trait values and identify genetic loci controlling the gene expression variations. In the first step, gene expression levels measured from microarray experiments were assigned to two different clusters based on the strengths of their association with the phenotypes of a quantitative trait under investigation. In the second step, genes associated with the trait were mapped to genetic loci of the genome. Because gene expressions are quantitative, the genetic loci controlling the expression traits are called expression quantitative trait loci. We applied the same SEM algorithm to a real dataset collected from a barley genetic experiment with both quantitative traits and gene expression traits. For the first time, we identified genes associated with eight agronomy traits of barley. These genes were then mapped to seven chromosomes of the barley genome. The SEM algorithm and the result of the barley data analysis are useful to scientists in the areas of bioinformatics and plant breeding. Availability and implementation: The R program for the SEM algorithm can be downloaded from our website: http://www.statgen.ucr.edu.     

Interspecific competition alters leaf stoichiometry in 20 grassland species

The extensive use of traits in ecological studies over the last few decades to predict community functions has revealed that plant traits are plastic and respond to various environmental factors. These plant traits are assumed to predict how plants compete and capture resources. Variation in stoichiometric ratios both within and across species reflects resource capture dynamics under competition. However, the impact of local plant diversity on species‐specific stoichiometry remains poorly studied. Here, we analyze how spatial and temporal diversity in resource‐acquisition traits affects leaf elemental stoichiometry of plants (i.e. the result of resource capture) and how flexible this stoichiometry is depending on the functional composition of the surrounding community. Therefore, we assessed inter‐ and intraspecific variations of leaf carbon (C), nitrogen (N), and phosphorus (P) (and their ratios) of 20 grassland species in a large trait‐based plant diversity experiment located in Jena (Germany) by measuring leaf elemental concentrations at the species‐level along a gradient in plant trait dissimilarity. Our results show that plants showed large intra‐ and interspecific variation in leaf stoichiometry, which was only partly explained by the functional group identity (grass or herb) of the species. Elemental concentrations (N, P, but not C) decreased with plant species richness, and species tended to become more deviant from their monoculture stoichiometry with increasing trait dissimilarity in the community. These responses differed among species, some consistently increased or decreased in P and N concentrations; for other species, the negative or positive change in P and N concentrations increased with increasing trait difference between the target species and the remaining community. The strength of this relationship was significantly associated to the relative position of the species along trait gradients related to resource acquisition. Trait‐difference and trait‐diversity thus were important predictors of how species’ resource capture changed in competitive neighbourhoods.     

The Genetic Architecture of Quantitative Traits Cannot Be Inferred from Variance Component Analysis

Classical quantitative genetic analyses estimate additive and non-additive genetic and environmental components of variance from phenotypes of related individuals without knowing the identities of quantitative trait loci (QTLs). Many studies have found a large proportion of quantitative trait variation can be attributed to the additive genetic variance (V_A), providing the basis for claims that non-additive gene actions are unimportant. In this study, we show that arbitrarily defined parameterizations of genetic effects seemingly consistent with non-additive gene actions can also capture the majority of genetic variation. This reveals a logical flaw in using the relative magnitudes of variance components to indicate the relative importance of additive and non-additive gene actions. We discuss the implications and propose that variance component analyses should not be used to infer the genetic architecture of quantitative traits.     

Cross-generational effects of climate change on expression of a sexually selected trait

Sexually selected traits and early breeding are often correlated with quality in birds: individuals that breed earlier in the season have more elaborate traits and raise more surviving offspring [1, 2]. As global climate warms, breeding date for many temperate birds is advancing [3, 4], but we lack corresponding information on climate-induced variation in sexual selection. Here, we investigated influences of climate on a sexually selected plumage trait in a Himalayan warbler (Phylloscopus humei). We found that when spring is warm, birds breed early. Subsequent to an early-breeding year, adults express relatively large sexually selected traits and rear offspring that also develop large traits. The positive effects of early breeding, plus the across-year correlation between parent and offspring cohorts, predict that warmer climates should lead to increases in trait size. However, trait size has not increased over the past 25 years, even though mean breeding date has advanced. We show that whereas warm springs have positive effects on trait size, warm summers have negative effects due to increased feather wear. Apparent stasis in the size of a sexually selected trait thus masks large, conflicting influences of climate change. Continued climate warming has the potential to affect the honesty of sexual signals, as trait expression and condition become increasingly disassociated.     

Evidence for the effect of serotonin receptor 1A gene (HTR1A) polymorphism on tractability in Thoroughbred horses

Tractability, or how easily animals can be trained and controlled, is an important behavioural trait for the management and training of domestic animals, but its genetic basis remains unclear. Polymorphisms in the serotonin receptor 1A gene (HTR1A) have been associated with individual variability in anxiety‐related traits in several species. In this study, we examined the association between HTR1A polymorphisms and tractability in Thoroughbred horses. We assessed the tractability of 167 one‐year‐old horses reared at a training centre for racehorses using a questionnaire consisting of 17 items. A principal components analysis of answers contracted the data to five principal component (PC) scores. We genotyped two non‐synonymous single nucleotide polymorphisms (SNPs) in the horse HTR1A coding region. We found that one of the two SNPs, c.709G>A, which causes an amino acid change at the intracellular region of the receptor, was significantly associated with scores of four of five PCs in fillies (all Ps < 0.05) and one PC in colts (P < 0.01). Horses carrying an A allele at c.709G>A showed lower tractability. This result provides the first evidence that a polymorphism in a serotonin‐related gene may affect tractability in horses with the effect partially different depending on sex.     

Genetic Regulation of Bone Metabolism in the Chicken: Similarities and Differences to Mammalian Systems

Birds have a unique bone physiology, due to the demands placed on them through egg production. In particular their medullary bone serves as a source of calcium for eggshell production during lay and undergoes continuous and rapid remodelling. We take advantage of the fact that bone traits have diverged massively during chicken domestication to map the genetic basis of bone metabolism in the chicken. We performed a quantitative trait locus (QTL) and expression QTL (eQTL) mapping study in an advanced intercross based on Red Junglefowl (the wild progenitor of the modern domestic chicken) and White Leghorn chickens. We measured femoral bone traits in 456 chickens by peripheral computerised tomography and femoral gene expression in a subset of 125 females from the cross with microarrays. This resulted in 25 loci for female bone traits, 26 loci for male bone traits and 6318 local eQTL loci. We then overlapped bone and gene expression loci, before checking for an association between gene expression and trait values to identify candidate quantitative trait genes for bone traits. A handful of our candidates have been previously associated with bone traits in mice, but our results also implicate unexpected and largely unknown genes in bone metabolism. In summary, by utilising the unique bone metabolism of an avian species, we have identified a number of candidate genes affecting bone allocation and metabolism. These findings can have ramifications not only for the understanding of bone metabolism genetics in general, but could also be used as a potential model for osteoporosis as well as revealing new aspects of vertebrate bone regulation or features that distinguish avian and mammalian bone.     

Physical linkage and mate preference generate linkage disequilibrium for behavioral isolation in two parapatric crickets

Behavioral isolation is a potent barrier to gene flow and a source of striking diversity in the animal kingdom. However, it remains unclear if the linkage disequilibrium (LD) between sex‐specific traits required for behavioral isolation results mostly from physical linkage between signal and preference loci or from directional mate preferences. Here, we test this in the field crickets Gryllus rubens and G. texensis. These closely related species diverged with gene flow and have strongly differentiated songs and preference functions for the mate calling song rhythm. We map quantitative trait loci for signal and preference traits (pQTL) as well as for gene expression associated with these traits (eQTL). We find strong, positive genetic covariance between song traits and between song and preference. Our results show that this is in part explained by incomplete physical linkage: although both linked pQTL and eQTL couple male and female traits, major effect loci for different traits were never on the same chromosome. We suggest that the finely tuned, highly divergent preference functions are likely an additional source of LD between male and female traits in this system. Furthermore, pleiotropy of gene expression presents an underappreciated mechanism to link sexually dimorphic phenotypes.     

Age‐ and quality‐dependent DNA methylation correlate with melanin‐based coloration in a wild bird

Secondary sexual trait expression can be influenced by fixed individual factors (such as genetic quality) as well as by dynamic factors (such as age and environmentally induced gene expression) that may be associated with variation in condition or quality. In particular, melanin‐based traits are known to relate to condition and there is a well‐characterized genetic pathway underpinning their expression. However, the mechanisms linking variable trait expression to genetic quality remain unclear. One plausible mechanism is that genetic quality could influence trait expression via differential methylation and differential gene expression. We therefore conducted a pilot study examining DNA methylation at a candidate gene (agouti‐related neuropeptide: AgRP) in the black grouse Lyrurus tetrix. We specifically tested whether CpG methylation covaries with age and multilocus heterozygosity (a proxy of genetic quality) and from there whether the expression of a melanin‐based ornament (ultraviolet‐blue chroma) correlates with DNA methylation. Consistent with expectations, we found clear evidence for age‐ and heterozygosity‐specific patterns of DNA methylation, with two CpG sites showing the greatest DNA methylation in highly heterozygous males at their peak age of reproduction. Furthermore, DNA methylation at three CpG sites was significantly positively correlated with ultraviolet‐blue chroma. Ours is the first study to our knowledge to document age‐ and quality‐dependent variation in DNA methylation and to show that dynamic sexual trait expression across the lifespan of an organism is associated with patterns of DNA methylation. Although we cannot demonstrate causality, our work provides empirical support for a mechanism that could potentially link key individual factors to variation in sexual trait expression in a wild vertebrate.