Person:

Hartl, Daniel

Selfish genes, such as meiotic drive elements, propagate themselves through a population without increasing the fitness of host organisms. X-linked (or Y-linked) meiotic drive elements reduce the transmission of the Y (X) chromosome and skew progeny and population sex ratios, leading to intense conflict among genomic compartments. Drosophila simulans is unusual in having a least three distinct systems of X chromosome meiotic drive. Here, we characterize naturally occurring genetic variation at the Winters sex-ratio driver (Distorter on the X or Dox), its progenitor gene (Mother of Dox or MDox), and its suppressor gene (Not Much Yang or Nmy), which have been previously mapped and characterized. We survey three North American populations as well as 13 globally distributed strains and present molecular polymorphism data at the three loci. We find that all three genes show signatures of selection in North America, judging from levels of polymorphism and skews in the site-frequency spectrum. These signatures likely result from the biased transmission of the driver and selection on the suppressor for the maintenance of equal sex ratios. Coalescent modeling indicates that the timing of selection is more recent than the age of the alleles, suggesting that the driver and suppressor are coevolving under an evolutionary “arms race.” None of the Winters sex-ratio genes are fixed in D. simulans, and at all loci we find ancestral alleles, which lack the gene insertions and exhibit high levels of nucleotide polymorphism compared to the derived alleles. In addition, we find several “null” alleles that have mutations on the derived Dox background, which result in loss of drive function. We discuss the possible causes of the maintenance of presence–absence polymorphism in the Winters sex-ratio genes.

Background: Patterns of emerging drug resistance reflect the underlying adaptive landscapes for specific drugs. In Plasmodium falciparum, the parasite that causes the most serious form of malaria, antifolate drugs inhibit the function of essential enzymes in the folate pathway. However, a handful of mutations in the gene coding for one such enzyme, dihydrofolate reductase, confer drug resistance. Understanding how evolution proceeds from drug susceptibility to drug resistance is critical if new antifolate treatments are to have sustained usefulness. Methodology/Principal Findings: We use a transgenic yeast expression system to build on previous studies that described the adaptive landscape for the antifolate drug pyrimethamine, and we describe the most likely evolutionary trajectories for the evolution of drug resistance to the antifolate chlorcycloguanil. We find that the adaptive landscape for chlorcycloguanil is multi-peaked, not all highly resistant alleles are equally accessible by evolution, and there are both commonalities and differences in adaptive landscapes for chlorcycloguanil and pyrimethamine. Conclusions/Significance: Our findings suggest that cross-resistance between drugs targeting the same enzyme reflect the fitness landscapes associated with each particular drug and the position of the genotype on both landscapes. The possible public health implications of these findings are discussed.

The ribosomal rDNA gene array is an epigenetically-regulated repeated gene locus. While rDNA copy number varies widely between and within species, the functional consequences of subtle copy number polymorphisms have been largely unknown. Deletions in the Drosophila Y-linked rDNA modifies heterochromatin-induced position effect variegation (PEV), but it has been unknown if the euchromatic component of the genome is affected by rDNA copy number. Polymorphisms of naturally occurring Y chromosomes affect both euchromatin and heterochromatin, although the elements responsible for these effects are unknown. Here we show that copy number of the Y-linked rDNA array is a source of genome-wide variation in gene expression. Induced deletions in the rDNA affect the expression of hundreds to thousands of euchromatic genes throughout the genome of males and females. Although the affected genes are not physically clustered, we observed functional enrichments for genes whose protein products are located in the mitochondria and are involved in electron transport. The affected genes significantly overlap with genes affected by natural polymorphisms on Y chromosomes, suggesting that polymorphic rDNA copy number is an important determinant of gene expression diversity in natural populations. Altogether, our results indicate that subtle changes to rDNA copy number between individuals may contribute to biologically relevant phenotypic variation.

The study of the evolution of novel genes generally focuses on the formation of new coding sequences. However, equally important in the evolution of novel functional genes are the formation of regulatory regions that allow the expression of the genes and the effects of the new genes in the organism as well. Herein, we discuss the current knowledge on the evolution of novel functional genes, and we examine in more detail the youngest genes discovered. We examine the existing data on a very recent and rapidly evolving cluster of duplicated genes, the Sdic gene cluster. This cluster of genes is an excellent model for the evolution of novel genes, as it is very recent and may still be in the process of evolving.

The Plasmodium falciparum parasite's ability to adapt to environmental pressures, such as the human immune system and antimalarial drugs, makes malaria an enduring burden to public health. Understanding the genetic basis of these adaptations is critical to intervening successfully against malaria. To that end, we created a high-density genotyping array that assays over 17,000 single nucleotide polymorphisms (~1 SNP/kb), and applied it to 57 culture-adapted parasites from three continents. We characterized genome-wide genetic diversity within and between populations and identified numerous loci with signals of natural selection, suggesting their role in recent adaptation. In addition, we performed a genome-wide association study (GWAS), searching for loci correlated with resistance to thirteen antimalarials; we detected both known and novel resistance loci, including a new halofantrine resistance locus, PF10_0355. Through functional testing we demonstrated that PF10_0355 overexpression decreases sensitivity to halofantrine, mefloquine, and lumefantrine, but not to structurally unrelated antimalarials, and that increased gene copy number mediates resistance. Our GWAS and follow-on functional validation demonstrate the potential of genome-wide studies to elucidate functionally important loci in the malaria parasite genome.

Understanding the molecular details of the sequence of events in multistep evolutionary pathways can reveal the extent to which natural selection exploits regulatory mutations affecting expression, amino acid replacements affecting the active site, amino acid replacements affecting protein folding or stability, or variations affecting gene copy number. In experimentally exploring the adaptive landscape of the evolution of resistance to β-lactam antibiotics in enteric bacteria, we noted that a regulatory mutation that increases β-lactamase expression by about 2-fold has a very strong tendency to be fixed at or near the end of the evolutionary pathway. This pattern contrasts with previous experiments selecting for the utilization of novel substrates, in which regulatory mutations that increase expression are often fixed early in the process. To understand the basis of the difference, we carried out experiments in which the expression of β-lactamase was under the control of a tunable arabinose promoter. We find that the fitness effect of an increase in gene expression is highly dependent on the catalytic activity of the coding sequence. An increase in expression of an inefficient enzyme has a negligible effect on drug resistance; however, the effect of an increase in expression of an efficient enzyme is very large. The contrast in the temporal incorporation of regulatory mutants between antibiotic resistance and the utilization of novel substrates is related to the nature of the function that relates enzyme activity to fitness. A mathematical model of β-lactam resistance is examined in detail and shown to be consistent with the observed results.

Background: At a time when genomes are being sequenced by the hundreds, much attention has shifted from identifying genes and phenotypes to understanding the networks of interactions among genes. We developed a gene network developmental model expanding on previous models of transcription regulatory networks. In our model, each network is described by a matrix representing the interactions between transcription factors, and a vector of continuous values representing the transcription factor expression in an individual. Results: In this work we used the gene network model to look at the impact of mating as well as insertions and deletions of genes in the evolution of complexity of these networks. We found that the natural process of diploid mating increases the likelihood of maintaining complexity, especially in higher order networks (more than 10 genes). We also show that gene insertion is a very efficient way to add more genes to a network as it provides a much higher chance of developmental stability. Conclusions: The continuous model affords a more complete view of the evolution of interacting genes. The notion of a continuous output vector also incorporates the reality of gene networks and graded concentrations of gene products.

Differences in gene expression are thought to be an important source of phenotypic diversity, so dissecting the genetic components of natural variation in gene expression is important for understanding the evolutionary mechanisms that lead to adaptation. Gene expression is a complex trait that, in diploid organisms, results from transcription of both maternal and paternal alleles. Directly measuring allelic expression rather than total gene expression offers greater insight into regulatory variation. The recent emergence of high-throughput sequencing offers an unprecedented opportunity to study allelic transcription at a genomic scale for virtually any species. By sequencing transcript pools derived from heterozygous individuals, estimates of allelic expression can be directly obtained. The statistical power of this approach is influenced by the number of transcripts sequenced and the ability to unambiguously assign individual sequence fragments to specific alleles on the basis of transcribed nucleotide polymorphisms. Here, using mathematical modelling and computer simulations, we determine the minimum sequencing depth required to accurately measure relative allelic expression and detect allelic imbalance via high-throughput sequencing under a variety of conditions. We conclude that, within a species, a minimum of 500–1000 sequencing reads per gene are needed to test for allelic imbalance, and consequently, at least five to 10 millions reads are required for studying a genome expressing 10 000 genes. Finally, using 454 sequencing, we illustrate an application of allelic expression by testing for cis-regulatory divergence between closely related Drosophila species.

A major challenge in evolutionary biology today is understanding the genetic and molecular mechanisms that give rise to phenotypic differences within and between species. Such differences can arise from mutations affecting the function of gene products (i.e. proteins or RNAs) or mutations that affect expression of these genes. Historically, researchers have looked almost exclusively for (and often found) changes in protein coding regions that appeared to contribute to phenotypic evolution; however, during the last decade, there has been a dramatic increase in the number of studies showing that changes affecting gene regulation can also bring about diversity in ecologically relevant traits that affect behaviour, physiology and morphology (e.g. Duda & Remigio 2008; Giger et al. 2008; Voelckel et al. 2008; see also for reviews Wray 2007; Hoekstra & Coyne 2007; Stern & Orgogozo 2008; Pennisi 2008; Wolf et al. 2010).

Studies of gene expression have become routine with the development of techniques that quantify transcript abundance in a high-throughput way. Microarray studies, in particular, have produced valuable catalogues of differences in transcript levels between individuals (Oleksiak et al. 2002; Whitehead & Crawford 2006), between species in diverse taxa (Rifkin et al. 2003) and between ecological conditions (Reymond et al. 2000; Carsten et al. 2005; Derome et al. 2006). Such studies also show that inter-individual differences in gene expression are often highly heritable (Wayne et al. 2004; Gibson & Weir 2005; Hughes et al. 2006; Lemos et al. 2008; Ayroles et al. 2009).

Because of this heritability, quantitative trait locus (QTL) mapping can be combined with microarray analysis to investigate the genetic basis of variable gene expression (Vasemagi & Primmer 2005). When a QTL affecting a gene’s transcription maps close to the affected gene it can be classified as cis-acting, while a QTL that maps further away on the same chromosome, or to another chromosome, can be classified as trans-acting (Brem et al. 2002). However, strictly speaking, ‘cis’ describes mutations that affect expression of only the allele on the same chromosome as the mutation, whereas ‘trans’ describes mutations that affect allelic expression on both homologous chromosomes. Examples of cis-acting sequences include promoters and enhancers, which are typically located close to the gene that they regulate, while examples of trans-acting regulators include genes that encode transcription factors, which may be located anywhere in the genome. Classifications of expression QTLs as cis- or trans-acting based solely on their proximity to the affected gene are therefore only an approximation – and one that comes with many caveats (Rockman & Kruglyak 2006).

Nevertheless, studies mapping expression QTLs suggest that both cis- and trans-regulatory mutations contribute to transcriptional variation, with a preponderance of expression QTLs appearing to be cis-acting (Wayne et al. 2004; Hughes et al. 2006; Osada et al. 2006; Bergen et al. 2007; Genissel et al. 2008; Gilad et al. 2008; Price et al. 2008; Lemos et al. 2008; but see Morley et al. 2004), although this methodology generally has less statistical power to detect trans-acting than cis-acting variants (Cookson et al. 2009). In addition, QTL mapping studies of variable gene expression require microarrays suitable for studying the species of interest, molecular markers that cover its complete genome, and resources for genotyping these markers in a segregating population. The lack of any one of these things can be a significant impediment for mapping expression QTLs outside well-established genetic model systems.

An alternative strategy for studying regulatory variation uses allelic transcript abundance and the fact that cis-regulatory mutations have allele-specific effects on gene expression while trans-regulatory mutations affect expression of both alleles in a diploid cell (Cowles et al. 2002; Wittkopp et al. 2004). One or more transcribed differences in nucleotide sequence are used to discriminate between transcripts produced by each allele. Asymmetric expression of two alleles, also known as allelic imbalance (AI) that is observed between alleles present in the same cell (i.e. exposed to the same trans-regulatory environment) provides direct evidence of cis-regulatory differences. Expression differences observed between individuals homozygous for two different alleles that are not also observed between these same alleles in heterozygotes are attributed to trans-regulatory differences (Wittkopp et al. 2004).

This allele-specific approach has now been used to decompose variable gene expression into its cis- and trans-regulatory component parts for flies (e.g. Wittkopp et al. 2008a,b), humans (e.g. Pant et al. 2006; Serre et al. 2008), plants (e.g. de Meaux et al. 2005; Guo et al. 2008) and yeast (Tirosh et al. 2009). With the exception of Tirosh et al. (2009), who developed custom microarrays, the methods used to measure allelic expression in these studies are not readily scalable to an entire genome. Furthermore, methods used in these studies, including Tirosh et al. (2009), require polymorphic sites that differentiate alleles to be known a priori. For these reasons, studying allelic expression genome wide has been impractical for nonmodel (as well as most model) species.

Next generation sequencing technologies have the potential to revolutionize studies of allelic expression. Because they obviate the need for a priori sequence information, molecular markers, and locus-specific genotyping assays, next generation sequencing methods can measure allelic abundance at a genomic level in virtually any species. Only transcribed nucleotide differences between alleles and sufficient sequencing depth for detecting AI are required. For these reasons, we expect measurements of allelic expression based on next generation sequencing will soon be acquired by many researchers, not only to disentangle cis- and trans-regulatory variation, but also to quantify the heritability of gene expression, examine dominance among regulatory alleles, evaluate their contribution to morphological, physiological, or behavioural changes, and reveal patterns of allelic variation within and between species.

Not surprisingly, the benefits of next generation sequencing come with a price – and often a high one. A single ‘run’ of high-throughput sequencing can provide up to hundreds of millions of sequences, but currently costs thousands of dollars. The precise cost per base differs among technologies, as does the length of each sequenced fragment and the total number of sequences collected. Because of this cost, careful experimental design that maximizes the data per dollar for allelic expression studies using next generation sequencing is critical. Optimal experimental design is particularly paramount for studies in molecular ecology that seek to examine allelic expression in multiple individuals, species or environmental conditions.

In this study, we use mathematical modelling and computer simulations to identify critical parameters affecting measurements of allelic expression and the detection of AI with high-throughput sequencing. We show that the statistical power of this method depends upon four crucial parameters (Fig. 1): sequence divergence between alleles, the relative transcript abundance, the average read length (i.e. amount of transcript sequenced) and sequencing depth (i.e. average number of reads per gene). The latter two parameters determine the number of sequencing reads expected to map to each gene. The former two parameters determine the proportion of sequence reads per gene that are informative for allelic expression [i.e. contain one or more single nucleotide polymorphisms (SNPs) that allow reads to be unambiguously assigned to an allele]. We show that this probability is strongly affected by the location of SNPs within an mRNA as well as by the way in which the cDNA library is prepared for sequencing. Here, we derive a mathematical model that determines the minimum number of reads required to test for significant AI given various levels of sequence divergence, read lengths, and distributions of relative transcript abundance, and we compare these results with simulations. Finally, to illustrate the potential of this approach, we describe an empirical study using measurements of allelic expression in F1 hybrids between Drosophila melanogaster and Drosophila simulans obtained using 454 sequencing (Roche 454 Life Sciences).

The Y chromosome, inherited without meiotic recombination from father to son, carries relatively few genes in most species. This is consistent with predictions from evolutionary theory that nonrecombining chromosomes lack variation and degenerate rapidly. However, recent work has suggested a dynamic role for the Y chromosome in gene regulation, a finding with important implications for spermatogenesis and male fitness. We studied Y chromosomes from two populations of Drosophila melanogaster that had previously been shown to have major effects on the thermal tolerance of spermatogenesis. We show that these Y chromosomes differentially modify the expression of hundreds of autosomal and X-linked genes. Genes showing Y-linked regulatory variation (YRV) also show an association with immune response and pheromone detection. Indeed, genes located proximal to the euchromatin–heterochromatin boundary of the X chromosome appear particularly responsive to Y-linked variation, including a substantial number of odorant-binding genes. Furthermore, the data show significant regulatory interactions between the Y chromosome and the genetic background of autosomes and X chromosome. Altogether, our findings support the view that interpopulation, Y-linked regulatory polymorphisms can differentially modulate the expression of many genes important to male fitness, and they also point to complex interactions between the Y chromosome and genetic background affecting global gene expression.

The spread of high-level pyrimethamine resistance in Africa threatens to curtail the therapeutic lifetime of antifolate antimalarials. We studied the possible evolutionary pathways in the evolution of pyrimethamine resistance using an approach in which all possible mutational intermediates were created by site-directed mutagenesis and assayed for their level of drug resistance. The coding sequence for dihydrofolate reductase (DHFR) from the malaria parasite Plasmodium falciparum was mutagenized, and tests were carried out in Escherichia coli under conditions in which the endogenous bacterial enzyme was selectively inhibited. We studied 4 key amino acid replacements implicated in pyrimethamine resistance: N51I, C59R, S108N, and I164L. Using empirical estimates of the mutational spectrum in P. falciparum and probabilities of fixation based on the relative levels of resistance, we found that the predicted favored pathways of drug resistance are consistent with those reported in previous kinetic studies, as well as DHFR polymorphisms observed in natural populations. We found that 3 pathways account for nearly 90% of the simulated realizations of the evolution of pyrimethamine resistance. The most frequent pathway (S108N and then C59R, N51I, and I164L) accounts for more than half of the simulated realizations. Our results also suggest an explanation for why I164L is detected in Southeast Asia and South America, but not at significant frequencies in Africa.