Polyploid and Hybrid Genomics

By James A. Birchler

Polyploidy plays an important role in biological diversity, trait improvement, and plant species survival. Understanding the evolutionary phenomenon of polyploidy is a key challenge for plant and crop scientists. This book is made up of contributions from leading researchers in the field from around the world, providing a truly global review of the subject. Providing broad-ranging coverage, and up-to-date information from some of the world’s leading researchers, this book is an invaluable resource for geneticists, plant and crop scientists, and evolutionary biologists.

• Language: English
• Publisher: Wiley
• Release date: Apr 5, 2013
• ISBN: 9781118552841

Book preview

Preface

The contributions to this volume center around the consequences that occur when different genomes come together. This seemingly simple process nevertheless transects several outstanding problems in biology, for example, the genetic and molecular mechanisms of hybrid vigor and speciation, as well as the contribution of polyploidy formation to evolution and agriculture.

Hybrid vigor or heterosis plays an important role in evolution and population biology as evidenced by the fact that most groups of eukaryotic organisms have evolved mechanisms to insure outcrossing. The increase in biomass and fertility as a result of heterozygosity in most plant species provides an evolutionary advantage, but this phenomenon has also found widespread use in breeding and agriculture with the use of hybrid production in many crops, vegetables, and some farm animals. Despite this widespread use in practical applications and a central role in evolutionary processes, both the genetic and molecular bases of heterosis have defied elucidation. Several authors have summarized the evidence from diverse species and from several different perspectives that can be brought to bear on this important topic.

The basis of speciation is likewise enigmatic. It has been recognized for decades that there are genetic incompatibilities that exist between species that can lead to hybrid sterility or lethality, postzygotically. Within a species, this usually does not occur. However, with divergence, the differences that accumulate can prevent gene flow between related species because of the detrimental consequences of hybridization. The nature of these genetic and molecular differences is only beginning to be discovered. Several authors describe experiments that address the molecular consequences that arise in hybrids between species. The bases of these incompatibilities may be many, but they lie at the heart of speciation mechanisms. The differences in specific genes and noncoding RNAs that evolve in different evolutionary lineages to condition incompatibilities will ultimately define how speciation operates, which will shed light on this critical evolutionary and biological issue.

Crosses between different species can also result in the formation of polyploidy if the hybrid doubles its chromosome number. While newly formed polyploids often exhibit detrimental qualities, polyploidy has clearly played an important role in evolution as revealed by the repeated histories of chromosome doubling in most eukaryotic lineages including fungi, protozoa, plants, and vertebrates. It is thus an important research question to address the qualities of polyploidy that lead to this central position in evolution. Moreover, the production of allopolyploids intersects with heterosis because it basically fixes the hybrid vigor for subsequent generations without the possibility of inbreeding reducing the diversity of gene copies between the two genomes contributing to the allopolyploid.

By bringing together a wide spectrum of information about polyploidy and hybrids in one volume, our hope is that it will serve as a valuable resource on this topic. But more importantly, it can serve as an inspiration to address critical biological problems that have defied solutions but that play a central role in evolution and agriculture.

James A. Birchler, Columbia, Missouri

Z. Jeffrey Chen, Austin, Texas

Section I

Genomics of Hybrids

1

Yeast Hybrids and Polyploids as Models in Evolutionary Studies

Avraham A. Levy¹, Itay Tirosh², Sharon Reikhav¹,², Yasmin Bloch¹,² and Naama Barkai²

¹Department of Plant Sciences, The Weizmann Institute of Science, Rehovot, Israel

²Department of Molecular Genetics, The Weizmann Institute of Science, Rehovot, Israel

Introduction

A major challenge in evolutionary biology is to understand if and how hybridization and polyploidization contribute to species fitness. Answering these questions in higher organisms, such as plants or animals, is difficult due to the required timescale to measure fitness and evolvability of a species and because of the complexity of multicellular organisms. The budding yeast, Saccharomyces cerevisiae, is the most advanced eukaryotic model system ideally suited to address basic principles in hybrid and polyploid speciation processes because it is amenable to evolutionary studies. Moreover, the mechanisms involved in the response of the genome to hybridity and polyploidy can be best addressed because of the extensive amount of genomic tools available. Here, we describe the yeast experimental system, focusing on S. cerevisiae and its close relatives, in the context of its contribution to the understanding of the genomic response to hybridity and polyploidy. We describe how hybrid genomics provides insight into the molecular mechanisms responsible for parental divergence during speciation. In addition, we present the lessons from the yeast system on the cost/benefit of polyploidy in evolution.

Experimental Advantages of Budding Yeasts

The Saccharomyces sensu stricto complex includes S. cerevisiae together with S. paradoxus and five more related species whose genome are fully sequenced and annotated (Naumov et al., 2000a; Kellis et al., 2003; Liti et al., 2006). These species, members of the sensu stricto subfamily, have diverged approximately 5–20 million years ago and display 80–90% and 62–80% sequence identity in coding and noncoding DNA respectively (Kellis et al., 2003). Budding yeasts are cheap and easy to maintain and have the ability to proliferate clonally, indefinitely both as haploids and as diploids, and their ploidy levels can readily be changed (Dilorio et al., 1987). Further, all species are able to hybridize to each other creating viable but near-sterile progeny.

Budding yeasts have a compact genome coding for 5000–6000 genes. Having such small genomes and being single-cell organisms, with a rapid generation time (∼1.5–3.0 hours per cell division), render yeast cells ideal models for research of highly complex biological processes. Short generation time enables us to perform evolution experiments (Dujon, 2010), and being unicellular makes yeast available to simple cell sorting-based types of analyses. These tools allow for sensitive and well-controlled fitness comparisons in the form of competition assays directly measuring the relative frequency of different varieties growing in the same environment over time (Breslow et al., 2008). Targeted mutagenesis by homologous recombination is routine in yeast and knockout mutants for 95% of all S. cerevisiae ORF are available in stock centers (Winzeler et al., 1999; Giaever et al., 2002). Also available are libraries of conditional knockouts, overexpression, fluorescent-tagged proteins, and other variants—all suitable for high-throughput, genome-wide work (Costanzo et al., 2006).

Another major advantage of the budding yeast is the extensive work already done and published and the publicly available large data sets produced using it as a model. These data sets, to name a few, consist of expression profiles, mutant phenotype information, genetic and functional linkage maps, and various large-scale screens for genes affecting several traits (Hohmann, 2005). Proper use of these experimental tools and data makes budding yeast a very good model for exploring the mechanisms involved in response to hybridity and polyploidy.

Yeast Hybrids

Several studies showed that species from the Saccharomyces genus are prone to interspecific hybridization, either naturally or through domestication in breweries and wineries and in laboratories (see review, Albertin & Marullo, 2012). We describe below only a few selected examples of naturally occurring hybrids. An interesting work showed a high occurrence of natural hybrids on grapevines alongside their parental species (Le Jeune et al., 2007). These hybridization events are recent since these hybrids still cannot produce viable spores, are asexual, and yet they prevail by mitotic divisions (Le Jeune et al., 2007). Another report shows remarkable fermentative qualities of a natural hybrid between S. cerevisiae and S. kudriavzevii (Gangl et al., 2009). In fact, one of the most famous fermenting yeast species, S. pastorianus (commonly named S. carlsbergenis) was shown to be an ancient hybrid between S. cerevisiae and S. bayanus (Hansen & Kielland-Brandt, 1994; Tamai et al., 1998). Another example is a strain used for cider production whose genome is composed of contributions from three species, namely of S. cerevisiae, S. kudriavzevii, and S. bayanus genomes (Masneuf et al., 1998). Note that S. bayanus itself is considered to contain a complex genome with chromosomal segments from S. uvarum, S. eubayanus, and to a less extent S. cerevisiae suggesting that it speciated through a series of ancient hybridization events (Libkind et al., 2011). Hybridization events in fermenting yeasts have been found to be so frequent up to a point where it is often debated whether some known varieties can be regarded as a unique species or a hybrid (Nguyen & Gaillardin, 2005).

Several explanations for this ubiquitous hybridity have been proposed, such as the potential phenotypic advantages of the hybrids (e.g., heterosis), their utilization in breeding yeast strains (Timberlake et al., 2011), their ability to survive following speciation, due to asexual reproduction, and to become, in the long-term, stabilized as distinct species through genomic rearrangements (Antunovics et al., 2005), or through genome doubling (Naumov et al., 2000b). All these show that most hybrid-specific phenomena reported in higher eukaryotes are also present in the yeast system. Hence, this system is highly suitable to model hybridity and polyploidy also in higher plants and other organisms.

Interestingly, the speciation process that gives rise to new yeast species is not well understood. Hybrid incompatibility genes, also called speciation genes as originally described in the 1930s (Dobzhansky, 1936), were isolated in several species (Johnson, 2010; Presgraves, 2010). However, the search for such genes in budding yeasts has been unsuccessful despite the significant efforts invested (Greig, 2007, 2009). The lack of incompatibility genes explains why closely related species of budding yeast mate readily and usually with no major deleterious interactions, except for the hybrid's sterility (Hunter et al., 1996; Marinoni et al., 1999). This sterility is probably caused by defective pairing of divergent chromosomes at meiosis rather than by the role of specific speciation genes. It does not prevent the vegetative propagation of the sterile hybrid; however, it may limit its long-term prospects for survival. Speciation may thus have occurred through physical rather than genetic isolation, although this possibility is not supported by the frequent occurrence of hybrids alongside their parental species (Le Jeune et al., 2007). Note that the sterility of diploid hybrids (homoploids) can be overcome upon genome duplication, giving rise to allopolyploids (also known as amphiploids) that are fertile, with most of the spores being viable (Greig et al., 2002).

Not surprisingly, considering their success in nature and under domestication, yeast interspecific hybrids were reported to show heterosis (Tirosh et al., 2009). The genetic and molecular basis of heterosis in yeast has received very little attention so far despite its importance for the yeast industry and its potential utility as a model for understanding heterosis in plants and animal breeding. Among the few reports, quantitative trait locus (QTL) mapping of genes involved in yeast growth under high temperatures uncovered a complex locus of three genes, which when heterozygous contributed to heterosis (Steinmetz et al., 2002).

Yeast Polyploids

Yeasts also provide a model for the study of polyploidy and aneuploidy. Mating usually starts by the fusion of haploid cells, followed by karyogamy, thus giving rise to a diploid cell. Diploid cells may also fuse with diploid or haploid cells, giving rise upon karyogamy to triploids or tetraploids. Autopolyploids exhibit phenotypic differences despite the identity of the duplicated genomes. This includes obvious traits, such as the increase in cell size along the increase in ploidy (Galitski et al., 1999), or more subtle traits, such as metabolic changes. For example, early studies comparing ploidy series with regard to their ability to produce ethanol reported that the efficiency of ethanol production per unit cell mass is greater in cells of higher ploidy (Dilorio et al., 1987). Nevertheless, most strains in wineries and breweries are diploids while in the bakery industry most strains are autotetraploids (Albertin et al., 2009).

Paleopolyploidy and Duplicated Genes Retention

Whole genome analysis of budding yeast species and of yeasts from different lineages has led to the conclusion that budding yeasts are paleopolyploid (Wolfe, 2001), meaning that they underwent an ancient whole genome duplication (WGD), approximately 100 million years ago (Wolfe & Shields, 1997; Dietrich et al., 2004; Kellis et al., 2004). The analysis of budding yeast genomes indicates that duplicated genes decay rapidly, as expected for redundant genes; nevertheless, approximately 550 pairs of orthologs have persisted out of a total of approximately 5500 protein-coding genes over 16 chromosomes (Byrne & Wolfe, 2005). The nature of the evolutionary forces that lead to the retention of the duplicated genes, which were expected to undergo diploidization after approximately 100 million years of evolution, has been the subject of extensive studies, models, and speculations. Early on, Ohno proposed that gene duplication can lead to novelty in evolution (Ohno, 1970). Yeast, with its well-annotated genome, transcriptome, proteome, and interactome, offers excellent insight into the postpolyploidization processes that affect the fate of duplicated genes. Yeast provides several examples on how WGD has contributed to the acquisition of new (neofunctionalization) or modified (subfunctionalization) functions. Remarkably, genes duplicated by WGD often show asymmetric rates of evolution, with one copy remaining similar to the original gene and the orthologous copy rapidly evolving, suggesting neofunctionalization (Kim and Yi, 2006; Byrne & Wolfe, 2007). The two S. cerevisiae serine kinases orthologs, NPR1 and PRR2, illustrate such neofunctionalization, with the slow-evolving copy, NPR1, and the fast-evolving copy, PRR2, diverging in function (Byrne & Wolfe, 2007). Interestingly, the fast-evolving ortholog is generally less essential than the slow-evolving copy (Byrne & Wolfe, 2007). Cases of subfunctionalization frequently involve a divergence in the expression of orthologs, manifested as tissue-specific or condition-dependent expression, which is often caused by differences in cis-regulatory elements (Papp et al., 2003b; Wapinski et al., 2007). Another manifestation of subfunctionalization of homologues is through differential subcellular protein localization (Marques et al., 2008). An additional interesting feature of ohnologues is that they do retain some degree of redundancy even though they have diverged in expression or function (Dean et al., 2008). In some cases, this might be explained by the ability of duplicated genes to reprogram their expression upon loss of one of the copies and to back up the missing copy (Kafri et al., 2005, 2006).

The preferential retention of genes has led to formulate the gene balance hypothesis (see review, Birchler & Veitia, 2010). According to this hypothesis, an imbalance in the stoichiometry in the concentration of proteins that are partners in a multisubunits complex can be deleterious to the organism. The analysis performed in yeast on the identity of genes retained following WGD has so far provided support for the balance hypothesis: over- or underexpression of one of the retained partners has deleterious effects (Papp et al., 2003a); S. cerevisiae genes showing haplo-insufficiency are enriched among retained orthologs that duplicated through WGD (Wapinski et al., 2007). An implication of these findings is that the duplication of whole genomes is the most likely way whereby whole modules of multiproteins complexes can be duplicated. This was indeed shown for essential machineries, such as ribosomes (Wapinski et al., 2007), further supporting the gene balance hypothesis. We thus learn from yeast that WGD is quite unique in enabling evolutionary innovation for whole modules, in a way that is not possible via gene-by-gene duplication.

Ploidy and Evolution—Theory and Experiments

Theoretical Consideration

How does ploidy affect fitness and the capacity to evolve? This basic question has intrigued evolutionary biologists for almost a century (for history of polyploidy, see review, Ramsey & Schemske, 1998). Yeast offers a unique experimental system to study the impact of ploidy on evolvability. Indeed, it would not be practical to carry evolution experiments in plants due to the long generation time. Opposite views have been frequently expressed on the virtue of polyploidy as a means to evolve rapidly. It has been considered that polyploidy promotes evolutionary innovation because it facilitates neo- and subfunctionalization, it generates a wide range of gene dosage, it buffers deleterious mutations, and it enables us to fix heterotic effects (in allopolyploids). Conversely, polyploidy was considered to be an evolutionary dead end (Stebbins, 1950, 1971) and to reduce the rate of speciation (Mayrose et al., 2011). Greig and Travisano have reviewed experimental works comparing haploids and diploids and present the case for haploid superiority (Greig & Travisano, 2003). In short, haploidy enables rapid purging of deleterious recessive mutations from the population; moreover, not all recessive mutations are fully compensated by the wild-type allele and maintaining a defective allele in diploids can be deleterious in the long term through increasing the load of deleterious mutations in the population (Haldane, 1924). In addition, beneficial recessive mutations are masked by the wild-type allele in diploids, suggesting that eventually, asexually growing diploids may adapt more slowly than haploids (the effect of dominant mutations being similar in diploids and haploids). Finally, the population size is also an important theoretical aspect of the question on ploidy and fitness because rare beneficial mutations will have a low chance to occur in a small population.

Experimental Data

In line with these theoretical considerations, Zeyl and coworkers have shown that, in the absence of sexual reproduction, haploids grown for approximately 2000 generations evolve more rapidly than diploids (as measured by growth rate before and after evolution) (Zeyl et al., 2003). However, when experiments were carried with small population sizes, there was no difference between haploids and diploids (Zeyl et al., 2003).

Additional experiments, many of which were reviewed by Gerstein and Otto (2009), emphasize the complexity of the effect of polyploidy on fitness. The emerging picture, as is often the case in evolution, is that it depends on the conditions. For example, in experiments on the resistance of yeast to antifungal drug, under low drug concentration, the diploid populations were more efficient at developing resistance (Anderson et al., 2004). The resistance mutations fixed in diploids were all dominant, while the mutations in haploids were either recessive (16 populations) or dominant (13 populations). However, under high drug concentration, haploids consistently achieved resistance much sooner than diploids through recessive mutations in the ERG3 gene that alters sterol synthesis. In addition, the spectrum of mutations identified at the sequence level was different between haploids and diploids (Anderson et al., 2004). Similarly, Gresham et al. (2008) found differential stress responses, in haploids and diploids, with respect to the spectrum of mutations, with a higher chance for large deletions and duplications in the diploid.

Another important aspect of evolution at different ploidy levels is the rate of mutations. Murray and coworkers (Thompson et al., 2006) have conducted an experiment with haploid and diploid yeasts, which were wild-type or mutator strains. These strains were let to evolve on different media and their relative fitness was measured along evolution, with respect to each other and with respect to their ancestors. The results show that wild-type haploids are the fittest, probably due to a quick disposal of deleterious recessive mutations; conversely, haploid mutators are the least fit due to the great cost accompanied to multiple deleterious mutations. In between these two extremes, diploid mutators have higher fitness than wild-type diploids, suggesting that diploids can deal with the excess of mutations better than haploids. These experiments are consistent with earlier results showing that fitness of diploids that carried a heavy mutation load was much less affected than that of haploids (Korona, 1999; Mable & Otto, 2001).

Higher ploidy levels, as in tetraploids, have been associated with reduced fitness compared to diploids under normal growth conditions (Andalis et al., 2004). The reduced fitness of tetraploids was correlated with chromosome loss, which might explain the convergence of evolving S. cerevisiae tetraploids toward the genome size of a diploid cell through chromosome loss, under two different environmental growth conditions when grown for approximately 1800 generations (Gerstein et al., 2006). However, more surprisingly, haploid strains also tend to converge to diploids, even though there is no obvious advantage of the diploids in growth rate compared to the haploids (Mable & Otto, 2001; Gerstein et al., 2006; Dickinson, 2008). The causes for diploid's superiority remain unclear: several possibilities have been considered, such as nutrients absorption, survival in stationary phase, resuming growth following stationary phase, but actual experiments remain inconclusive.

Karyotypic Instability in Polyploids

One of the advantages of yeast is that it is amenable to genome-wide functional genomic screens. To address the reasons for reduced fitness of the tetraploids, a search was designed for mutations, which are not essential in haploids and diploids but affect viability of triploids and tetraploids (Storchova et al., 2006). Thirty-nine out of 3740 mutations screened exhibited ploidy-specific lethality. Almost all these mutations affected genomic stability by impairing homologous recombination, sister chromatid cohesion, or mitotic spindle function. It was suggested that these findings reflect the inability of polyploid cells to scale up the mechanical and geometrical constraints of cell division (Storchova et al., 2006).

Allopolyploids can also be unstable and lose chromosomes, giving rise to aneuploid strains with unbalanced chromosome numbers (Gonzalez et al., 2006). Aneuploid yeast for either one of the yeast chromosomes exhibits a shared phenotype of defects in cell-cycle progression, increased glucose uptake, and high dependence on protein synthesis, folding, and degradation (Torres et al., 2007). The proliferation of aneuploids is usually hampered compared to euploids; however, under some perturbed environment they can outperform euploids (Pavelka et al., 2010). Similarly, aneuploid yeast growth rate can increase in certain mutants. For example, a mutation in the deubiquitinating enzyme Ubp6 was shown to provide aneuploids with improved proliferation rates (Torres et al., 2010). In addition, some mutants were found in the yeast deletion library, harboring an extra chromosome containing a homologous gene for the mutated one, and exhibiting an improved growth rate (Hughes et al., 2000), suggesting compensation of haplo-insufficiency through aneuploidy. A thorough genomic analysis of aneuploidy is needed to better evaluate the scope and underlying mechanisms of these phenomena.

Genomic Response to Polyploidy and Hybridity

A pioneering work used microarrays for determining ploidy-dependent regulation of gene expression from haploid to tetraploid (Galitski et al., 1999). The main findings of this work were that at high ploidy levels, G1 cyclins were repressed, a response that is likely correlated with the enlarged cell size. Since then, the genomics of polyploidy has not been analyzed despite the remarkable advances in the resolution of genomic tools.

By contrast, hybrids, and in particular interspecific yeast hybrids, have been subjected to several genomic analyses (see review, Tirosh & Barkai, 2011). The hybrid yeast model has enabled a better understanding of the mechanisms of rewiring of gene expression in hybrids, namely the novel features that are not additive compared to the parental species, such as overdominance or epistatic effects (Tirosh et al., 2009). In particular, the determination of cis- and trans-contributions to interspecies expression differences has shown that overdominance in gene expression (increased or decreased levels of gene expression in the hybrid compared to both parents) was associated with two distinct scenarios. In the first scenario, the same gene was influenced by a cis- and a trans-factor that diverged between the two species, and their interaction led to overdominance in the hybrid. In the second scenario, the trans-regulators of certain genes appeared to have a different activity in the hybrid compared to both parents (for unknown reasons) and thus led to increased or decreased expression of their target genes in the hybrid.

Yeast Hybrids as a Tool for Studying Genomic Regulation

Within a hybrid, two alleles of the same gene are in fact orthologous genes from the two parental species. These alleles differ by mutations in their coding and regulatory sequences, which give rise to allele-specific expression (ASE), but since they reside within the same nucleus these alleles are regulated by the same trans-factors. Thus, hybrid ASE reflects the effects of mutations in cis, while interspecies differences between the orthologous genes reflect the effects of mutations both in cis and in trans. Comparison of interspecies expression differences with hybrid ASE therefore enables a dissection of the interspecies differences to the independent contributions of cis- and trans-mutations as well as their interactions. This approach is made possible by the ability to measure, with custom microarrays or high-throughput sequencing, the differences in gene expression between two alleles that differ by a small number of mutations. This approach has been used in yeast (Tirosh et al., 2009; Bullard et al., 2010; Emerson et al., 2010) and flies (Wittkopp et al., 2004, 2008; McManus et al., 2010), and a similar approach has been used in mammals (Wilson et al., 2008).

Notably, hybrid-based dissection of cis- and trans-contributions is possible not only for gene expression levels but in fact for any genomic measurements that can distinguish orthologous regions within the hybrid. Indeed, this approach has so far been used to assess cis- and trans-contributions to buffering of gene expression variations (Tirosh et al., 2010a), to nucleosome positioning and occupancy (Tirosh et al., 2010b), to mRNA degradation rates (Dori-Bachash et al., 2011), and to DNA replication timing (Muller & Nieduszynski, 2012).

In the first example, yeast hybrid was used to examine the mechanisms defining the positioning of nucleosomes along the yeast genome. In this case, the approach provided a fresh insight into one of the major debates in the field: the relative importance of local DNA (cis-effects) and DNA-binding proteins such as chromatin remodelers (trans-effects) to the overall pattern of nucleosome positioning and occupancy (Kaplan et al., 2009; Zhang et al., 2009). Measuring nucleosome positioning of two yeast species and their hybrid and identifying cis-dependent and trans-dependent differences in nucleosome positioning and occupancy (Tirosh et al., 2010b) allowed us to estimate the relative contributions of cis- (∼70%) and trans-effects (∼30%) to the interspecies differences in nucleosome positioning. Further analysis of the cis-dependent sequence changes demonstrated that differences in nucleosome positioning and occupancy were driven primarily by mutations that increased or decreased the percentage of cytosine or guanine nucleotides (%GC), consistent with a simple model, whereby nucleosome positioning is determined largely by the single factor of %GC (Tillo & Hughes, 2009). This analysis also showed that the direct effect of mutations on positioning of a single nucleosome often propagates to adjacent nucleosomes, hence causing concomitant changes in an array of nucleosomes, consistent with the statistical positioning hypothesis (Kornberg & Stryer, 1988; Mavrich et al., 2008).

A second example where the use of hybrids to dissect regulatory mechanisms proved highly useful concerns mRNA degradation. While studies of mRNA expression levels have focused almost exclusively on transcription regulation, mRNAs are also regulated posttranscriptionally, most notably by cytoplasmic mRNA degradation. mRNA degradation rates can be determined by measuring the rate by which mRNA levels decrease following transcriptional arrest (Wang et al., 2002; Grigull et al., 2004). Applying the hybrid approach for measuring mRNA degradation rates (Dori-Bachash et al., 2011) demonstrated that evolutionary changes in mRNA degradation are highly correlated with evolutionary changes in transcription, such that increased rates of mRNA degradation are typically associated also with increased rates of transcription and hence paradoxically with increased mRNA levels. Such association between transcription and degradation evolutionary changes could reflect either the co-evolution of independent mutations affecting transcription and mRNA degradation or a direct mechanistic coupling, whereby individual mutations often affect both transcription and degradation. The latter possibility is strongly supported by two results that rely on our ability to distinguish cis- and trans-effects. First, trans-effects were significantly enriched among targets of the Rpb4/7 and Ccr4-Not complexes, both of which are known to regulate both transcription and mRNA degradation, and in some cases to directly couple the two processes (Collart, 2003; Goler-Baron et al., 2008). Second, transcription and degradation effects that influenced the same gene were almost always due to the same type of mutation (i.e., both cis-dependent and trans-dependent). In other words, if mRNA degradation rate of a certain gene has diverged through mutations in cis, then the transcription rate of that gene has typically also diverged through mutations in cis, suggesting that the same mutations affected transcription and mRNA degradation. Notably, this proposed global coupling between transcription and mRNA degradation was further supported by additional recent studies (Collart, 2003; Goler-Baron et al., 2008; Bregman et al., 2011; Shalem et al., 2011; Trcek et al., 2011; Sun et al., 2012). These results demonstrate how evolutionary changes, and the ability to classify them into cis- and trans-contributions, can serve as a valuable tool to study basic mechanisms of gene regulation. In the last example, replication profiles were determined for an S. cerevisiae × S. bayanus hybrid. This analysis indicates that there are both cis- and trans-regulators of origin of replication function (Muller & Nieduszynski, 2012).

Conclusions

The yeast model has provided much insight into the effect of hybridity and polyploidy in evolutionary processes. For example, hybrids of yeast serve as powerful tools to probe the molecular mechanisms that lead to the divergence between species. They enable the first genome-wide studies on interspecific divergence in cis- and trans-regulatory factors that affect gene expression, nucleosome occupancy, RNA stability (Tirosh & Barkai, 2011), and DNA replication (Muller & Nieduszynski, 2012).

In addition, the extensive yeast data on gene networks and protein complexes enable the detection of unique aspects of WGD followed by diploidization: we have learned from duplicate gene retention that WGD facilitates duplication of whole network modules in a manner that could not be achieved through gene-by-gene duplication due to stoichiometry constraints, thus enabling neofunctionalization, not only at the gene level but also at the network level (Wapinski et al., 2007).

Yeasts are the only organisms where experiments in evolution could actually be performed to address the question on how ploidy levels affect evolutionary processes. Evolution experiments in yeast have provided the only direct evidence showing that there is no clear advantage of increasing or decreasing ploidy in the evolutionary race. Each ploidy level seems to have advantages or limitations of its own, depending on the growth conditions (Gerstein & Otto, 2009).

Another important lesson from looking at natural and domesticated strains is that genome hybridity is very common (Albertin & Marullo, 2012). We can hypothesize that this is due to heterosis, even though there has not been a systematic study of heterosis in yeast. Polyploidy is also common in nature and industry (Albertin & Marullo, 2012). For example, most strains in the bread-making industry are tetraploid. This contrasts with several laboratory experiments that did not point to a clear advantage of polyploidy (Gerstein & Otto, 2009). How relevant, therefore, are laboratory studies to natural or domestic environments? Most laboratory studies that performed evolution experiments did so in homozygous strains under asexual conditions. Maybe some of the discrepancies between the natural and the laboratory environment are due to the fact that the combination of mutations, recombination, and segregation in evolving populations has not been addressed yet in yeast or other organisms. Studies on allopolyploids are missing, and modeling of the evolution of strains of different ploidy could also add to our understanding of ploidy-related evolution. In summary, research on yeast hybrids and polyploids has enriched our knowledge so far and promises to deliver many more insights.

Acknowledgments

The Levy and Barkai groups thank the ICORE (grant no. 152/11) and AERI alternative energy programs for funding their research on yeast hybrids and polyploids.

References

Albertin, W., & Marullo, P. (2012) Polyploidy in fungi: evolution after whole-genome duplication. Proc Biol Sci 279 (1738), 2497–2509.

Albertin, W., Marullo, P., Aigle, M., et al. (2009) Evidence for autotetraploidy associated with reproductive isolation in Saccharomyces cerevisiae: towards a new domesticated species. J Evol Biol 22 (11), 2157–2170.

Andalis, A.A., Storchova, Z., Styles, C., et al. (2004) Defects arising from whole-genome duplications in Saccharomyces cerevisiae. Genetics 167 (3), 1109–1121.

Anderson, J.B., Sirjusingh, C., & Ricker, N. (2004) Haploidy, diploidy and evolution of antifungal drug resistance in Saccharomyces cerevisiae. Genetics 168(4), 1915--1923.

Antunovics, Z., Nguyen, H.V., Gaillardin, C., & Sipiczki, M. (2005) Gradual genome stabilisation by progressive reduction of the Saccharomyces uvarum genome in an interspecific hybrid with Saccharomyces cerevisiae. FEMS Yeast Res 5 (12), 1141–1150.

Birchler, J.A., & Veitia, R.A. (2010) The gene balance hypothesis: implications for gene regulation, quantitative traits and evolution. New Phytologist 186 (1), 54–62.

Bregman, A., Avraham-Kelbert, M., Barkai, O., Duek, L., Guterman, A., & Choder, M. (2011) Promoter elements regulate cytoplasmic mRNA decay. Cell 147 (7), 1473–1483.

Breslow, D.K., Cameron, D.M., Collins, S.R., et al. (2008) A comprehensive strategy enabling high-resolution functional analysis of the yeast genome. Nat Methods 5 (8), 711–718.

Bullard, J.H., Mostovoy, Y., Dudoit, S., & Brem, R.B. (2010) Polygenic and directional regulatory evolution across pathways in Saccharomyces. Proc Natl Acad Sci USA 107 (11), 5058–5063.

Byrne, K.P., & Wolfe, K.H. (2005) The yeast gene order browser: combining curated homology and syntenic context reveals gene fate in polyploid species. Genome Res 15(10), 1456–1461.

Byrne, K.P., & Wolfe, K.H. (2007) Consistent patterns of rate asymmetry and gene loss indicate widespread neofunctionalization of yeast genes after whole-genome duplication. Genetics 175 (3), 1341–1350.

Collart, M.A. (2003) Global control of gene expression in yeast by the Ccr4-Not complex. Gene 313, 1–16.

Costanzo, M., Giaever, G., Nislow, C., & Andrews, B. (2006) Experimental approaches to identify genetic networks. Curr Opin Biotechnol 17 (5), 472–480.

Dean, E.J., Davis, J.C., Davis, R.W., & Petrov, D.A. (2008) Pervasive and persistent redundancy among duplicated genes in yeast. PLoS Genet 4 (7), e1000113.

Dickinson, W.J. (2008) Synergistic fitness interactions and a high frequency of beneficial changes among mutations accumulated under relaxed selection in Saccharomyces cerevisiae. Genetics 178 (3), 1571–1578.

Dietrich, F.S., Voegeli, S., Brachat, S., et al. (2004) The Ashbya gossypii genome as a tool for mapping the ancient Saccharomyces cerevisiae genome. Science 304 (5668), 304–307.

Dilorio, A.A., Weathers, P.J., & Campbele, D.A. (1987) Comparative enzyme and ethanol production in an isogenic yeast ploidy series. Curr Genet 12, 9–14.

Dobzhansky, T. (1936) Studies on hybrid sterility. II. Localization of sterility factors in Drosophila pseudoobscura hybrids. Genetics 21 (2), 113–135.

Dori-Bachash, M., Shema, E., & Tirosh, I. (2011) Coupled evolution of transcription and mRNA degradation. PLoS Biol 9 (7), e1001106.

Dujon, B. (2010) Yeast evolutionary genomics. Nat Rev Genet 11 (7), 512–524.

Emerson, J.J., Hsieh, L.C., Sung, H.M., et al. (2010) Natural selection on cis and trans regulation in yeasts. Genome Res 20 (6), 826–836.

Galitski, T., Saldanha, A.J., Styles, C.A., Lander, E.S., & Fink, G.R. (1999) Ploidy regulation of gene expression. Science 285 (5425), 251–254.

Gangl, H., Batusic, M., Tscheik, G., Tiefenbrunner, W., Hack, C., & Lopandic, K. (2009) Exceptional fermentation characteristics of natural hybrids from Saccharomyces cerevisiae and S. kudriavzevii. N Biotechnol 25 (4), 244–251.

Gerstein, A.C., Chun, H.J., Grant, A., & Otto, S.P. (2006) Genomic convergence toward diploidy in Saccharomyces cerevisiae. PLoS Genet 2 (9), e145.

Gerstein, A.C., & Otto, S.P. (2009) Ploidy and the causes of genomic evolution. J Hered 100 (5), 571–581.

Giaever, G., Chu, A.M., Ni, L., et al. (2002) Functional profiling of the Saccharomyces cerevisiae genome. Nature 418 (6896), 387–391.

Goler-Baron, V., Selitrennik, M., Barkai, O., Haimovich, G., Lotan, R., & Choder, M. (2008) Transcription in the nucleus and mRNA decay in the cytoplasm are coupled processes. Genes Dev 22 (15), 2022–2027.

Gonzalez, S.S., Barrio, E., Gafner, J., & Querol, A. (2006) Natural hybrids from Saccharomyces cerevisiae, Saccharomyces bayanus and Saccharomyces kudriavzevii in wine fermentations. FEMS Yeast Res 6 (8), 1221–1234.

Greig, D. (2007) A screen for recessive speciation genes expressed in the gametes of F1 hybrid yeast. PLoS Genet 3 (2), e21.

Greig, D. (2009) Reproductive isolation in Saccharomyces. Heredity (Edinb) 102 (1), 39–44.

Greig, D., Louis, E.J., Borts, R.H., & Travisano, M. (2002) Hybrid speciation in experimental populations of yeast. Science 298 (5599), 1773–1775.

Greig, D., & Travisano, M. (2003) Evolution. Haploid superiority. Science 299 (5606), 524–525.

Gresham, D., Desai, M.M., Tucker, C.M., et al. (2008) The repertoire and dynamics of evolutionary adaptations to controlled nutrient-limited environments in yeast. PLoS Genet 4 (12), e1000303.

Grigull, J., Mnaimneh, S., Pootoolal, J., Robinson, M.D., & Hughes, T.R. (2004) Genome-wide analysis of mRNA stability using transcription inhibitors and microarrays reveals posttranscriptional control of ribosome biogenesis factors. Mol Cell Biol 24 (12), 5534–5547.

Haldane, J.B.S. (1924) A mathematical theory of natural and artificial selection. Trans Cambridge Philos Soc 23, 19–41.

Hansen, J., & Kielland-Brandt, M.C. (1994) Saccharomyces carlsbergensis contains two functional MET2 alleles similar to homologues from S. cerevisiae and S. monacensis. Gene 140 (1), 33–40.

Hohmann, S. (2005) The yeast systems biology network: mating communities. Curr Opin Biotechnol 16 (3), 356–360.

Hughes, T.R., Roberts, C.J., Dai, H., et al. (2000) Widespread aneuploidy revealed by DNA microarray expression profiling. Nat Genet 25 (3), 333–337.

Hunter, N., Chambers, S.R., Louis, E.J., & Borts, R.H. (1996) The mismatch repair system contributes to meiotic sterility in an interspecific yeast hybrid. Embo J 15 (7), 1726–1733.

Johnson, N.A. (2010) Hybrid incompatibility genes: remnants of a genomic battlefield? Trends Genet 26 (7), 317–325.

Kafri, R., Bar-Even, A., & Pilpel, Y. (2005) Transcription control reprogramming in genetic backup circuits. Nat Genet 37 (3), 295–299.

Kafri, R., Levy, M., & Pilpel, Y. (2006) The regulatory utilization of genetic redundancy through responsive backup circuits. Proc Natl Acad Sci USA 103 (31), 11653–11658.

Kaplan, N., Moore, I.K., Fondufe-Mittendorf, Y., et al. (2009) The DNA-encoded nucleosome organization of a eukaryotic genome. Nature 458 (7236), 362–366.

Kellis, M., Birren, B.W., & Lander, E.S. (2004) Proof and evolutionary analysis of ancient genome duplication in the yeast Saccharomyces cerevisiae. Nature 428 (6983), 617–624.

Kellis, M., Patterson, N., Endrizzi, M., Birren, B., & Lander, E. (2003) Sequencing and comparison of yeast species to identify genes and regulatory elements. Nature 423 (6937), 241–254.

46. Kim, S.H., & S.V. Yi. (2006) Correlated asymmetry of sequence and functional divergence between duplicate proteins of Saccharomyces cerevisiae. Mol Biol Evol 23(5),1068--1075.

Kornberg, R.D., & Stryer, L. (1988) Statistical distributions of nucleosomes: nonrandom locations by a stochastic mechanism. Nucleic Acids Res 16 (14A), 6677–6690.

Korona, R. (1999) Unpredictable fitness transitions between haploid and diploid strains of the genetically loaded yeast Saccharomyces cerevisiae. Genetics 151 (1), 77–85.

Le Jeune, C., Lollier, M., Demuyter, C., et al. (2007) Characterization of natural hybrids of Saccharomyces cerevisiae and Saccharomyces bayanus var. uvarum. FEMS Yeast Res 7 (4), 540–549.

Libkind, D., Hittinger, C.T., Valério, E., et al. (2011) Microbe domestication and the identification of the wild genetic stock of lager-brewing yeast. Proc Natl Acad Sci USA 108 (35), 14539–14544.

Liti, G., Barton, D.B., & Louis, E.J. (2006) Sequence diversity, reproductive isolation and species concepts in Saccharomyces. Genetics 174 (2), 839–850.

Mable, B.K., & Otto, S.P. (2001) Masking and purging mutations following EMS treatment in haploid, diploid and tetraploid yeast (Saccharomyces cerevisiae). Genet Res 77 (1), 9–26.

Marinoni, G., Manuel, M., Petersen, R.F., Hvidtfeldt, J., Sulo, P., & Piskur, J. (1999) Horizontal transfer of genetic material among Saccharomyces yeasts. J Bacteriol 181 (20), 6488–6496.

Marques, A.C., Vinckenbosch, N., Brawand, D., & Kaessmann, H. (2008) Functional diversification of duplicate genes through subcellular adaptation of encoded proteins. Genome Biol 9 (3), R54.

Masneuf, I., Hansen, J., Groth, C., Piskur, J., & Dubourdieu, D. (1998) New hybrids between Saccharomyces sensu stricto yeast species found among wine and cider production strains. Appl Environ Microbiol 64 (10), 3887–3892.

Mavrich, T.N., Ioshikhes, I.P., Venters, B.J., et al. (2008) A barrier nucleosome model for statistical positioning of nucleosomes throughout the yeast genome. Genome Res 18 (7), 1073–1083.

Mayrose, I., Zhan, S.H., Rothfels, C.J., et al. (2011) Recently formed polyploid plants diversify at lower rates. Science 333 (6047), 1257.

McManus, C.J., Coolon, J.D., Duff, M.O., Eipper-Mains, J., Graveley, B.R., & Wittkopp, P.J. (2010) Regulatory divergence in Drosophila revealed by mRNA-seq. Genome Res 20 (6), 816–825.

Muller, C.A., & Nieduszynski, C.A. (2012) Conservation of replication timing reveals global and local regulation of replication origin activity. Genome Res 22 (10), 1953–1962.

Naumov, G.I., James, S.A., Naumova, E.S., Louis, E.J., & Roberts, I.N. (2000a) Three new species in the Saccharomyces sensu stricto complex: Saccharomyces cariocanus, Saccharomyces kudriavzevii and Saccharomyces mikatae. Int J Syst Evol Microbiol 50 (Pt 5), 1931–1942.

Naumov, G.I., Naumova, E.S., Masneuf, I., Aigle, M., Kondratieva, V.I., & Dubourdieu, D. (2000b) Natural polyploidization of some cultured yeast Saccharomyces sensu stricto: auto- and allotetraploidy. Syst Appl Microbiol 23 (3), 442–449.

Nguyen, H.V., & Gaillardin, C. (2005) Evolutionary relationships between the former species Saccharomyces uvarum and the hybrids Saccharomyces bayanus and Saccharomyces pastorianus; reinstatement of Saccharomyces uvarum (Beijerinck) as a distinct species. FEMS Yeast Res 5 (4–5), 471–483.

Ohno, S. (1970). Evolution by Gene Duplication. Springer, New York.

Papp, B., Pal, C., & Hurst, L.D. (2003a) Dosage sensitivity and the evolution of gene families in yeast. Nature 424 (6945), 194–197.

Papp, B., Pal, C., & Hurst, L.D. (2003b) Evolution of cis-regulatory elements in duplicated genes of yeast. Trends Genet 19 (8), 417–422.

Pavelka, N., Rancati, G., Zhu, J., et al. (2010) Aneuploidy confers quantitative proteome changes and phenotypic variation in budding yeast. Nature 468 (7321), 321–325.

Presgraves, D.C. (2010) The molecular evolutionary basis of species formation. Nat Rev Genet 11 (3), 175–180.

Ramsey, J., & Schemske, D.W. (1998) Pathways, mechanisms, and rates of polyploid formation in flowering plants. Ann Rev Ecol Sys 29, 467–501.

Shalem, O., Groisman, B., Choder, M., Dahan, O., & Pilpel, Y. (2011) Transcriptome kinetics is governed by a genome-wide coupling of mRNA production and degradation: a role for RNA PolII. PLoS Genet 7 (9), e1002273.

Stebbins, G.L. (1950). Variation and Evolution in Plants. Columbia University Press, New York.

Stebbins, G.L. (1971). Chromosomal Evolution in Higher Plants. Edward Arnold Publishers Ltd, London.

Steinmetz, L.M., Sinha, H., Richards, D.R., et al. (2002) Dissecting the architecture of a quantitative trait locus in yeast. Nature 416 (6878), 326–330.

Storchova, Z., Breneman, A., Cande, J., et al. (2006) Genome-wide genetic analysis of polyploidy in yeast. Nature 443 (7111), 541–547.

Sun, M., Schwalb, B., Schulz, D., et al. (2012) Comparative dynamic transcriptome analysis (cDTA) reveals mutual feedback between mRNA synthesis and degradation. Genome Res 22 (7), 1350–1359.

Tamai, Y., Momma, T., Yoshimoto, H., & Kaneko, Y. (1998) Co-existence of two types of chromosome in the bottom fermenting yeast, Saccharomyces pastorianus. Yeast 14 (10), 923–933.

Thompson, D.A., Desai, M.M., & Murray, A.W. (2006) Ploidy controls the success of mutators and nature of mutations during budding yeast evolution. Curr Biol 16 (16), 1581–1590.

Tillo, D., & Hughes, T.R. (2009) G+C content dominates intrinsic nucleosome occupancy. BMC Bioinformatics 10, 442.

Timberlake, W.E., Frizzell, M.A., Richards, K.D., & Gardner, R.C. (2011) A new yeast genetic resource for analysis and breeding. Yeast 28 (1), 63–80.

Tirosh, I., & Barkai, N. (2011) Inferring regulatory mechanisms from patterns of evolutionary divergence. Mol Syst Biol 7, 530.

Tirosh, I., Reikhav, S., Levy, A.A., & Barkai, N. (2009) A yeast hybrid provides insight into the evolution of gene expression regulation. Science 324 (5927), 659–662.

Tirosh, I., Reikhav, S., Sigal, N., Assia, Y., & Barkai, N. (2010a) Chromatin regulators as capacitors of interspecies variations in gene expression. Mol Syst Biol 6, 435.

Tirosh, I., Sigal, N., & Barkai, N. (2010b) Divergence of nucleosome positioning between two closely related yeast species: genetic basis and functional consequences. Mol Syst Biol 6, 365.

Torres, E.M., Dephoure, N., Panneerselvam, A., et al. (2010) Identification of aneuploidy-tolerating mutations. Cell 143 (1), 71–83.

Torres, E.M., Sokolsky, T., Tucker, C.M., et al. (2007) Effects of aneuploidy on cellular physiology and cell division in haploid yeast. Science 317 (5840), 916–924.

Trcek, T., Larson, D.R., Moldón, A., Query, C.C., & Singer, R.H. (2011) Single-molecule mRNA decay measurements reveal promoter- regulated mRNA stability in yeast. Cell 147 (7), 1484–1497.

Wang, Y., Liu, C.L., Storey, J.D., Tibshirani, R.J., Herschlag, D., & Brown, P.O. (2002) Precision and functional specificity in mRNA decay. Proc Natl Acad Sci USA 99 (9), 5860–5865.

Wapinski, I., Pfeffer, A., Friedman, N., & Regev, A. (2007) Natural history and evolutionary principles of gene duplication in fungi. Nature 449 (7158), 54–61.

Wilson, M.D., Barbosa-Morais, N.L., Schmidt, D., et al. (2008) Species-specific transcription in mice carrying human chromosome 21. Science 322 (5900), 434–438.

Winzeler, E.A., Shoemaker, D.D., Astromoff, A., et al. (1999) Functional characterization of the S. cerevisiae genome by gene deletion and parallel analysis. Science 285 (5429), 901–906.

Wittkopp, P.J., Haerum, B.K., & Clark, A.G. (2004) Evolutionary changes in cis and trans gene regulation. Nature 430 (6995), 85–88.

Wittkopp, P.J., Haerum, B.K., & Clark A.G. (2008) Regulatory changes underlying expression differences within and between Drosophila species. Nat Genet 40 (3), 346–350.

Wolfe, K.H. (2001) Yesterday's polyploids and the mystery of diploidization. Nat Rev Genet 2 (5), 333–341.

Wolfe, K.H., & Shields, D.C. (1997) Molecular evidence for an ancient duplication of the entire yeast genome. Nature 387 (6634), 708–713.

Zeyl, C., Vanderford, T., & Carter, M. (2003) An evolutionary advantage of haploidy in large yeast populations. Science 299 (5606), 555–558.

Zhang, Y., Moqtaderi, Z., Rattner, B.P., et al. (2009) Intrinsic histone-DNA interactions are not the major determinant of nucleosome positions in vivo. Nat Struct Mol Biol 16 (8), 847.

2

Transcriptome Profiling of Drosophila Interspecific Hybrids: Insights into Mechanisms of Regulatory Divergence and Hybrid Dysfunction

José M. Ranz¹, Shu-Dan Yeh¹, Kevin G. Nyberg² and Carlos A. Machado²

¹Department of Ecology and Evolutionary Biology, University of California, Irvine, California, USA

²Department of Biology, University of Maryland, College Park, Maryland, USA

Introduction

Sturtevant pioneered the use of interspecific hybrids to study the genetic basis of speciation using crosses between Drosophila melanogaster and Drosophila simulans (Sturtevant, 1920). In those early studies, he realized that one of the sexes was inviable while the other sex, that of the D. melanogaster parent, was viable but sterile. In interspecific hybrids, inviability and sterility result from the malfunction of interacting genes in a hybrid genetic background (i.e., due to genetic incompatibilities). For example, the dominant mutations lethal hybrid rescue (Lhr) and hybrid male rescue (Hmr), which enable the generation of D. melanogaster/D. simulans hybrid individuals that otherwise would die, have been shown to correspond to loss-of-function alleles. Therefore, it is the wild-type expression of the affected loci that prevents the proper development of the hybrid zygote into an adult (Barbash et al., 2003; Brideau et al., 2006). Those examples illustrate that genetic incompatibilities between evolutionary divergent genomes will be uncovered in hybrids, and, importantly, that they are often associated with improper gene expression. This anomalous expression in hybrids reflects regulatory divergence, which is considered the primary substrate for phenotypic evolution (Wray, 2007).

The advent of molecular approaches such as in situ hybridization and microarray technology have enabled us to monitor the outcome of loci malfunction since aberrant expression phenotypes (e.g., the abundance and spatial distribution of transcripts) are one of the closest proxies to genetic incompatibilities in hybrids. In this chapter, we explore what both case studies and genome-wide analyses using Drosophila hybrids have uncovered about the evolution of the transcriptome. First, we review the main factors that affect gene expression and briefly describe some of the most common methodologies to study gene expression. Next, we examine the different theories that try to explain the sterility and inviability of interspecific hybrids underscoring its regulatory nature. Last, we provide an extensive review of transcriptional studies on Drosophila hybrids emphasizing how they are helping us understand transcriptome evolution in the context of different aspects of organismal biology.

Gene Expression

Factors that Affect Gene Expression

Gene expression is an exquisitely regulated multistep process influenced by multiple factors that can be broadly classified as cis- and trans-acting regulatory elements. These regulatory elements determine the different attributes of gene expression (spatial distribution, timing, and abundance) of the molecules that actually perform most of the cell functions (Lewin et al., 2011). cis-Regulatory factors refer to DNA sequences located within or nearby the gene being regulated. These include DNA sequences involved in the initiation and fine-tuning of transcription, such as promoters, enhancers, and silencers, and motifs present in the 5′- and 3′-untranslated regions (UTRs) of the transcript itself, which are usually involved in its processing, stability, and intracellular localization. trans-Acting factors include proteins and RNAs derived from genomic regions distant to the regulated gene, such as transcription factors, RNA-binding proteins, and microRNAs; some of them act pretranscriptionally while others do so posttranscriptionally. Based on their mode of inheritance, cis-regulatory elements co-segregate with the gene being regulated, whereas trans-acting factors segregate independently from the target gene they regulate. cis-Regulatory element function is almost exclusively dependent on its primary nucleotide sequence, and thus only changes in that sequence will affect cis-function. trans-Acting factor function, however, is dependent on a larger number of features, from the structural conformation of proteins or RNAs to concentrations and interactions with other trans-acting factors. Changes in any of these can alter trans-function.

Initiation of gene transcription has been the most studied step in regulation of gene expression, and it will not be discussed here (Levine & Tjian, 2003). Other factors, such as those acting posttranscriptionally or epigenetic modifications, have become increasingly relevant more recently (Mata et al., 2005), and their impact in the expression profiles of interspecific hybrids remains largely uncharacterized. Posttranscriptional regulatory mechanisms include all basic steps of the processing of the nascent transcript including premature termination, the addition of a methylguanosine cap and a poly(A) tail to the 5′- and 3′-ends of the transcript, respectively, and the splicing of introns. End modification of transcripts is essential for proper export from the nucleus and for regulation of the half-life of the mature transcript as it affects degradation. Additional mechanisms impact the fate and the coding properties of the mature transcript. In the 5′- and 3′-UTRs there are motifs that play critical roles from determining the intracellular fate of the transcript to their efficient translation by ribosomes (Mignone et al., 2002; Kuersten & Goodwin, 2003). Further, the coding sequence of the transcript can be modified (i.e., edited) either by chemically altering individual nucleotides or by inserting or deleting nucleotides with the aid of guide RNA molecules. In one of its more common forms, mRNA editing involves the modification of adenosine to inosine. Because inosine is an analog of guanosine, the ultimate effect of this deamination is the alteration of the amino acid sequence of the encoded protein contributing as well to protein diversity (Stapleton et al., 2006).

The final fate of the mature transcript is also subject to extensive regulation (Houseley & Tollervey, 2009; Alonso, 2011). Common degradation pathways involve different kinds of RNA-binding proteins, and the process itself is influenced by secondary structures adopted by the transcript and by particular sequence motifs commonly located in the 3′-UTR region. Further, a suite of 19–25 nt long RNAs named microRNAs interacts via Watson–Crick complementarity with sequence motifs located, for the most part, in the 3′-UTR region of the transcript. Binding by microRNAs eventually results in mRNA degradation or in repressing protein translation, affecting protein levels (Ambros, 2004; Bartel, 2004).

Proper chromatin conformation is essential for the access of the transcriptional machinery. Environmental cues have an enormous potential to induce adaptive heritable modifications that do not alter the nucleotide sequence itself but that chemically alter chromatin conformation by affecting particular nucleotides and the histone proteins that constitute the nucleosomes. This epigenetic tagging impacts the potential for expression embedded in the DNA sequence, which seems to be essential in the context of cell fate decisions. This epigenetic tagging includes DNA methylation and several posttranslational histone modifications and is stable throughout meiosis and mitosis. DNA methylation in Drosophila has been documented at low levels during early stages of embryonic development affecting, for example, 0.4% of all cytosines, usually in the form of CpT and CpA dinucleotides (Lyko et al., 2000; Kunert et al., 2003; Lyko & Maleszka, 2011). Further, histone tails are accessible to different kinds of specialized enzymes, which modify particular amino acids by adding, for example, acetyl, methyl, or phosphate groups. Chromatin enriched in acetyl tags is usually found near active genes, whereas methyl tags tend to mark silenced genes. This histone code is usually reset during early embryogenesis, although a few genes escape this epigenetic reprogramming. These exceptions can explain transgenerational epigenetic inheritance (Xing et al., 2007).

Common Approaches to Conduct Gene Expression Profiling

Precise characterization of expression profiles is important for understanding phenotypic divergence of species and phenotypic dysfunction in hybrids. Multiple technical developments have been devised or adapted to quantify the level of expression of a single gene, multiple genes, or the entire transcriptome. Although this quantification can be performed at the transcript or protein levels, the most common methodological approaches focus on measuring transcript levels. The most widely used methods can be divided into two major groups: candidate gene approach methods (e.g., RT-qPCR or pyrosequencing) and exploratory approach methods (e.g., microarrays, RNA-seq). Microarrays have been the most useful approach for studying gene expression in Drosophila hybrids due to an excellent trade-off between cost, scope, and availability. Nevertheless, the recent development of RNA-seq methods allows assessing genome-wide patterns of allele-specific expression (ASE), an important but not widely studied aspect of gene expression in interspecific hybrids. A brief description follows on the most common methodologies currently applied to the study of gene expression in hybrids.

RT-qPCR

Reverse-transcription quantitative polymerase chain reaction (RT-qPCR), also known as quantitative real-time PCR, uses a fluorescent probe specific to a target sequence (a gene transcript) to monitor its relative abundance during PCR cycles of cDNAs that are reversely transcribed from mRNAs. How the fluorescent signal is generated depends on the fluorophore technology used in the RT-qPCR experiment (VanGuilder et al., 2008). The relative quantity of mRNAs is then calculated under the assumption that the exponential increase of PCR products during cycles of reactions is tightly associated with the initial quantity of cDNA templates. This approach can be used for validating the results of large-scale transcriptome experiments or for examining ASE in hybrids using allele-specific probes.

Pyrosequencing

This approach is essentially a DNA-sequencing technique that combines primer extension and fluorescence production (from luciferin/luciferase reaction) in each nucleotide-adding cycle. It is primarily a cost-effective method for genotyping single-nucleotide polymorphisms (SNPs) but has been adapted to quantify ASE in hybrid individuals (Wittkopp et al., 2004; Wittkopp, 2011). The coding sequences of the investigated genes and SNPs between parental alleles have to be identified prior to the experiments. The quantitative read-out of the fluorescent signal in a SNP site is then used to infer the relative abundance of biallelic copies and thus to estimate the expression level of each parental allele in F1 hybrids.

Microarrays

This technology uses the complementarity of DNA duplexes to assess transcript abundance and copy number variation. Thousands of DNA molecules are deposited on a glass slide with different technologies, enabling surveying all the transcribed fraction of the genome (protein coding and noncoding). The length of these DNA molecules can range from an entire cDNA, to PCR amplicons, to 60–70 mers, and to short 25 mers. These DNA molecules serve as probes that hybridize, via Watson–Crick duplex formation, with the experimental DNAs or cDNAs, which are labeled with fluorescent dyes. After hybridization, the intensity of fluorescent signals from each spot representing a particular DNA sequence is measured and these measures are used to infer the quantity of starting experimental transcript. For a more comprehensive description of the steps involved see Ranz and Machado (2006). The key underlying assumption is that the signal intensity is proportional to mRNA abundance.

The design of probes on a microarray is based on sequence information from a genome assembly or from a transcriptome database. Since the microarray platform to be used is usually designed with sequence information from a single species, expression profiling between species or that of F1 hybrids faces the limitation of the impact of sequence mismatches in the estimation of levels of mRNA abundance (Ranz et al., 2003; Gilad et al., 2005). Thus, diminished hybridization efficiency can be confounded with low mRNA abundance, especially in the case of microarray platforms with short probes and when one of the parental species is closer phylogenetically to the species used as a reference to design the probes. The latter situation usually results in a larger number of nucleotide differences between the probes on the array and the transcriptome of the most distantly related species, which exacerbates poor hybridization kinetics. Recent work has shown that in fact nucleotide mismatches usually inflate the variance of the estimates (Mezey et al., 2008), reducing the power to detect statistically significant differences in mRNA abundance.

Solutions to the impact of nucleotide mismatches include the use of probes on the array with no nucleotide mismatches when genome sequences for the target species are known (Jiang & Machado, 2009), or, if this is not possible because of absence of sequence information from one of the species, validation with another technique. Alternatively, the effects of nucleotide mismatches between probes and experimental mRNAs can be alleviated by using multispecies microarray platforms (Gilad et al., 2006). Despite the legitimate concern on the impact of nucleotide mismatches, carefully designed microarray experiments have allowed obtaining accurate estimates of interspecific gene expression differences. This is illustrated by the expression-profiling study of D. simulans and D. sechellia using cDNA and Affymetrix oligonucleotide arrays of D. melanogaster (Dworkin & Jones, 2009). Coding sequence divergence between D. simulans and D. sechellia has been estimated to be 1.9% on average (minimum 0%, maximum 18%), showing a similar degree of differentiation relative to D. melanogaster (6.8% on average). Based on the expression data