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1.  Towards a gene regulatory network perspective on phenotypic plasticity, genetic accommodation and genetic assimilation 
Molecular ecology  2014;23(18):4438-4440.
Many organisms can produce alternative phenotypes in direct response to different environmental conditions, a phenomenon known as phenotypic plasticity. The environmentally sensitive gene regulatory networks (GRNs) that mediate such developmental flexibility are largely unknown. Yet, characterizing these GRNs is important not only for elucidating plasticity’s molecular basis, but also for shedding light onto whether and how plasticity might impact evolution. In this issue of Molecular Ecology, Schneider et al.) describe one of the first efforts to determine the GRN underlying a plastic trait. They focus on diet-induced plasticity in the cichlid fish, Astatoreochromis alluaudi. Depending on whether soft food (e.g. insects) or hard food (e.g. molluscs) is consumed, this species forms a lower pharyngeal jaw (LPJ) with many fine teeth or with fewer molar-like teeth, respectively (Fig. 1). The authors previously identified genes that are differentially expressed between LPJ morphs during early development. In the present study, they examine the expression of 19 of these genes across development and diet. By analysing these transcriptional data in combination with information on putative transcription factor binding sites, they construct a GRN that explains observed gene expression patterns and is likely to control LPJ morphology. This work advances our understanding of how plasticity can arise as a consequence of environmentally sensitive GRNs and promises to help illuminate how changes in such GRNs could facilitate evolution.
PMCID: PMC4180264  PMID: 25208504
adaptation; fish; gene regulatory networks; macroevolution; molecular evolution; phenotypic plasticity
2.  MicroRNAs in plants 
Plant Signaling & Behavior  2008;3(10):829-830.
MicroRNAs (miRNAs) are important posttranscriptional regulators of gene expression in eukaryotes. In plants, most miRNAs exist in multiple copies throughout the genome and many of these miRNAs target multiple messenger RNA (mRNA) transcripts. Mutations at miRNAs in natural populations could facilitate evolutionary changes within and between species because of their positions at critical positions in gene regulatory networks. Dissecting the contribution of miRNAs to plant evolution requires the identification of potentially functional mutations at miRNAs within and between species. Recently, we and others have published papers focused on this topic, laying the foundation for studying the contributions of miRNAs to the phenotypic diversification of plants.
PMCID: PMC2634387  PMID: 19704512
microRNAs; precursor microRNAs; nonconserved miRNAs; plant phenotypic diversity
3.  Genetic Interactions Involving Five or More Genes Contribute to a Complex Trait in Yeast 
PLoS Genetics  2014;10(5):e1004324.
Recent research suggests that genetic interactions involving more than two loci may influence a number of complex traits. How these ‘higher-order’ interactions arise at the genetic and molecular levels remains an open question. To provide insights into this problem, we dissected a colony morphology phenotype that segregates in a yeast cross and results from synthetic higher-order interactions. Using backcrossing and selective sequencing of progeny, we found five loci that collectively produce the trait. We fine-mapped these loci to 22 genes in total and identified a single gene at each locus that caused loss of the phenotype when deleted. Complementation tests or allele replacements provided support for functional variation in these genes, and revealed that pre-existing genetic variants and a spontaneous mutation interact to cause the trait. The causal genes have diverse functions in endocytosis (END3), oxidative stress response (TRR1), RAS-cAMP signalling (IRA2), and transcriptional regulation of multicellular growth (FLO8 and MSS11), and for the most part have not previously been shown to exhibit functional relationships. Further efforts uncovered two additional loci that together can complement the non-causal allele of END3, suggesting that multiple genotypes in the cross can specify the same phenotype. Our work sheds light on the complex genetic and molecular architecture of higher-order interactions, and raises questions about the broader contribution of such interactions to heritable trait variation.
Author Summary
Although it is well known that interactions among genetic variants contribute to many complex traits, the forms of these interactions have not been fully characterized. Most work on this problem to date has focused on relatively simple cases involving two or three loci. However, higher-order interactions involving larger numbers of loci can also occur, and may have significant effects on the relationship between genotype and phenotype. In this paper, we dissect a colony morphology trait that segregates in a cross of two yeast strains and is caused by genetic interactions among five or more loci. Our work demonstrates that higher-order interactions can have major phenotypic effects, and provides novel insights into the genetic and molecular basis of these interactions.
PMCID: PMC4006734  PMID: 24784154
4.  Finding the sources of missing heritability in a yeast cross 
Nature  2013;494(7436):234-237.
For many traits, including susceptibility to common diseases in humans, causal loci uncovered by genetic mapping studies explain only a minority of the heritable contribution to trait variation. Multiple explanations for this “missing heritability” have been proposed1. Here we use a large cross between two yeast strains to accurately estimate different sources of heritable variation for 46 quantitative traits and to detect underlying loci with high statistical power. We find that the detected loci explain nearly the entire additive contribution to heritable variation for the traits studied. We also show that the contribution to heritability of gene-gene interactions varies among traits, from near zero to approximately 50%. Detected two-locus interactions explain only a minority of this contribution. These results substantially advance our understanding of the missing heritability problem and have important implications for future studies of complex and quantitative traits.
PMCID: PMC4001867  PMID: 23376951
5.  Genome-Wide Characterization of Genetic Variation in the Unicellular, Green Alga Chlamydomonas reinhardtii 
PLoS ONE  2012;7(7):e41307.
Chlamydomonas reinhardtii is a model system for studying cilia, photosynthesis, and other core features of eukaryotes, and is also an emerging source of biofuels. Despite its importance to basic and applied biological research, the level and pattern of genetic variation in this haploid green alga has yet to be characterized on a genome-wide scale. To improve understanding of C. reinhardtii's genetic variability, we generated low coverage whole genome resequencing data for nearly all of the available isolates of this species, which were sampled from a number of sites in North America over the past ∼70 years. Based on the analysis of more than 62,000 single nucleotide polymorphisms, we identified two groups of isolates that represent geographical subpopulations of the species. We also found that measurements of genetic diversity were highly variable throughout the genome, in part due to technical factors. We studied the level and pattern of linkage disequilibrium (LD), and observed one chromosome that exhibits elevated LD. Furthermore, we detected widespread evidence of recombination across the genome, which implies that outcrossing occurs in natural populations of this species. In summary, our study provides multiple insights into the sequence diversity of C. reinhardtii that will be useful to future studies of natural genetic variation in this organism.
PMCID: PMC3405113  PMID: 22848460
6.  Genetic Architecture of Highly Complex Chemical Resistance Traits across Four Yeast Strains 
PLoS Genetics  2012;8(3):e1002570.
Many questions about the genetic basis of complex traits remain unanswered. This is in part due to the low statistical power of traditional genetic mapping studies. We used a statistically powerful approach, extreme QTL mapping (X-QTL), to identify the genetic basis of resistance to 13 chemicals in all 6 pairwise crosses of four ecologically and genetically diverse yeast strains, and we detected a total of more than 800 loci. We found that the number of loci detected in each experiment was primarily a function of the trait (explaining 46% of the variance) rather than the cross (11%), suggesting that the level of genetic complexity is a consistent property of a trait across different genetic backgrounds. Further, we observed that most loci had trait-specific effects, although a small number of loci with effects in many conditions were identified. We used the patterns of resistance and susceptibility alleles in the four parent strains to make inferences about the allele frequency spectrum of functional variants. We also observed evidence of more complex allelic series at a number of loci, as well as strain-specific signatures of selection. These results improve our understanding of complex traits in yeast and have implications for study design in other organisms.
Author Summary
Most heritable traits of agricultural, evolutionary, and medical significance are specified by multiple genetic loci. Despite decades of research, we have only a limited understanding of the genetic basis of such complex traits. Studies in model organisms have the potential to provide fundamental insights into this research area, but most genetic mapping studies in these species have had low statistical power to detect multiple loci with small effects. Using a technique in which we employed millions of cross progeny in genetic mapping, we previously showed that resistance to chemicals has a highly complex genetic basis in a cross of a lab strain and a wine strain of the budding yeast Saccharomyces cerevisiae. Because we only examined a single cross, it was unclear how general our findings were. Here, we expand our work to all six possible crosses of four strains—the two isolates we used in our last study, as well as an isolate from an immunocompromised human being and an isolate from the sap of an oak tree. Our results based on these four ecologically and genetically distinct S. cerevisiae strains suggest that resistance to chemicals commonly exhibits a highly complex genetic basis among yeast isolates.
PMCID: PMC3305394  PMID: 22438822
7.  Dissection of genetically complex traits with extremely large pools of yeast segregants 
Nature  2010;464(7291):1039-1042.
Most heritable traits, including many human diseases 1, are caused by multiple loci. Studies in both humans and model organisms, such as yeast, have failed to detect a large fraction of the loci that underlie such complex traits 2,3. A lack of statistical power to identify multiple loci with small effects is undoubtedly one of the primary reasons for this problem. We have developed a method in yeast that allows the use of dramatically larger sample sizes than previously possible and hence permits the detection of multiple loci with small effects. The method involves generating very large numbers of progeny from a cross between two strains and then phenotyping and genotyping pools of these offspring. We applied the method to 17 chemical resistance traits and mitochondrial function, and identified loci for each of these phenotypes. We show that the range of genetic complexity underlying these quantitative traits is highly variable, with some traits influenced by one major locus and others due to at least 20 loci. Our results provide an empirical demonstration of the genetic complexity of many traits and show that it is possible to identify many of the underlying factors using straightforward techniques. Our method should have broad applications in yeast and can be extended to other organisms.
PMCID: PMC2862354  PMID: 20393561
8.  A Multiparent Advanced Generation Inter-Cross to Fine-Map Quantitative Traits in Arabidopsis thaliana 
PLoS Genetics  2009;5(7):e1000551.
Identifying natural allelic variation that underlies quantitative trait variation remains a fundamental problem in genetics. Most studies have employed either simple synthetic populations with restricted allelic variation or performed association mapping on a sample of naturally occurring haplotypes. Both of these approaches have some limitations, therefore alternative resources for the genetic dissection of complex traits continue to be sought. Here we describe one such alternative, the Multiparent Advanced Generation Inter-Cross (MAGIC). This approach is expected to improve the precision with which QTL can be mapped, improving the outlook for QTL cloning. Here, we present the first panel of MAGIC lines developed: a set of 527 recombinant inbred lines (RILs) descended from a heterogeneous stock of 19 intermated accessions of the plant Arabidopsis thaliana. These lines and the 19 founders were genotyped with 1,260 single nucleotide polymorphisms and phenotyped for development-related traits. Analytical methods were developed to fine-map quantitative trait loci (QTL) in the MAGIC lines by reconstructing the genome of each line as a mosaic of the founders. We show by simulation that QTL explaining 10% of the phenotypic variance will be detected in most situations with an average mapping error of about 300 kb, and that if the number of lines were doubled the mapping error would be under 200 kb. We also show how the power to detect a QTL and the mapping accuracy vary, depending on QTL location. We demonstrate the utility of this new mapping population by mapping several known QTL with high precision and by finding novel QTL for germination data and bolting time. Our results provide strong support for similar ongoing efforts to produce MAGIC lines in other organisms.
Author Summary
Most traits of economic and evolutionary interest vary quantitatively and have multiple genes affecting their expression. Dissecting the genetic basis of such traits is crucial for the improvement of crops and management of diseases. Here, we develop a new resource to identify genes underlying such quantitative traits in Arabidopsis thaliana, a genetic model organism in plants. We show that using a large population of inbred lines derived from intercrossing 19 parents, we can localize the genes underlying quantitative traits better than with existing methods. Using these lines, we were able to replicate the identification of previously known genes that affect developmental traits in A. thaliana and identify some new ones. This paper also presents all the necessary biological and computational material necessary for the scientific community to use these lines in their own research. Our results suggest that the use of lines derived from a multiparent advanced generation inter-cross (MAGIC lines) should be very useful in other organisms.
PMCID: PMC2700969  PMID: 19593375
9.  Distribution and Diversity of Natural Product Genes in Marine and Freshwater Cyanobacterial Cultures and Genomes 
Applied and Environmental Microbiology  2005;71(11):7401-7413.
Natural products are a functionally diverse class of biochemically synthesized compounds, which include antibiotics, toxins, and siderophores. In this paper, we describe both the detection of natural product activities and the sequence identification of gene fragments from two molecular systems that have previously been implicated in natural product production, i.e., nonribosomal peptide synthetases (NRPSs) and modular polyketide synthases (PKSs), in diverse marine and freshwater cyanobacterial cultures. Using degenerate PCR and the sequencing of cloned products, we show that NRPSs and PKSs are common among the cyanobacteria tested. Our molecular data, when combined with genomic searches of finished and progressing cyanobacterial genomes, demonstrate that not all cyanobacteria contain NRPS and PKS genes and that the filamentous and heterocystous cyanobacteria are the richest sources of these genes and the most likely sources of novel natural products within the phylum. In addition to validating the use of degenerate primers for the identification of PKS and NRPS genes in cyanobacteria, this study also defines numerous gene fragments that will be useful as probes for future studies of the synthesis of natural products in cyanobacteria. Phylogenetic analyses of the cyanobacterial NRPS and PKS fragments sequenced in this study, as well as those from the cyanobacterial genome projects, demonstrate that there is remarkable diversity and likely novelty of these genes within the cyanobacteria. These results underscore the potential variety of novel products being produced by these ubiquitous organisms.
PMCID: PMC1287672  PMID: 16269782

Results 1-9 (9)