Ian M. Ehrenreich

A multiparent advanced generation inter-cross to fine-map quantitative traits in Arabidopsis thaliana

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.

Dissection of genetically complex traits with extremely large pools of yeast segregants

Most heritable traits, including many human diseases, 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. 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 much 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 Saccharomyces cerevisiae 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 level of genetic complexity underlying these quantitative traits is highly variable, with some traits influenced by one major locus and others by at least 20 loci. Our results provide an empirical demonstration of the genetic complexity of a number of 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.

Finding the sources of missing heritability in a yeast cross

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 proposed. 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 per cent. 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.

Candidate Gene Association Mapping of Arabidopsis Flowering Time

The pathways responsible for flowering time in Arabidopsis thaliana comprise one of the best characterized genetic networks in plants. We harness this extensive molecular genetic knowledge to identify potential flowering time quantitative trait genes (QTGs) through candidate gene association mapping using 51 flowering time loci. We genotyped common single nucleotide polymorphisms (SNPs) at these genes in 275 A. thaliana accessions that were also phenotyped for flowering time and rosette leaf number in long and short days. Using structured association techniques, we find that haplotype-tagging SNPs in 27 flowering time genes show significant associations in various trait/environment combinations. After correction for multiple testing, between 2 and 10 genes remain significantly associated with flowering time, with CO arguably possessing the most promising associations. We also genotyped a subset of these flowering time gene SNPs in an independent recombinant inbred line population derived from the intercrossing of 19 accessions. Approximately one-third of significant polymorphisms that were associated with flowering time in the accessions and genotyped in the outbred population were replicated in both mapping populations, including SNPs at the CO, FLC, VIN3, PHYD, and GA1 loci, and coding region deletions at the FRI gene. We conservatively estimate that ∼4–14% of known flowering time genes may harbor common alleles that contribute to natural variation in this life history trait.

Distribution and Diversity of Natural Product Genes in Marine and Freshwater Cyanobacterial Cultures and Genomes

ABSTRACT 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.

Sequence Variation of MicroRNAs and Their Binding Sites in Arabidopsis

Major differences exist between plants and animals both in the extent of microRNA (miRNA)-based gene regulation and the sequence complementarity requirements for miRNA-messenger RNA pairing. Whether these differences affect how these sites evolve at the molecular level is unknown. To determine the extent of sequence variation at miRNAs and their targets in a plant species, we resequenced 16 miRNA families (66 miRNAs in total) and all 52 of the characterized binding sites for these miRNAs in the plant model Arabidopsis (Arabidopsis thaliana), accounting for around 50% of the known miRNAs and binding sites in this species. As has been shown previously in humans, we find that both miRNAs and their target binding sites have very low nucleotide variation and divergence compared to their flanking sequences in Arabidopsis, indicating strong purifying selection on these sites in this species. Sequence data flanking the mature miRNAs, however, exhibit normal levels of polymorphism for the accessions in this study and, in some cases, nonneutral evolution or subtle effects on predicted pre-miRNA secondary structure, suggesting that there is raw material for the differential function of miRNA alleles. Overall, our results show that despite differences in the architecture of miRNA-based regulation, miRNAs and their targets are similarly constrained in both plants and animals.

Phenotypic and genotypic characterization of multiple strains of the diazotrophic cyanobacterium, Crocosphaera watsonii, isolated from the open ocean

Diazotrophic cyanobacteria have long been recognized as important sources of reduced nitrogen (N) and therefore are important ecosystem components. Until recently, species of the filamentous cyanobacterium Trichodesmium were thought to be the primary sources of fixed N to the open ocean euphotic zone. It is now recognized that unicellular cyanobacteria are also important contributors, with members of the oligotrophic genus Crocosphaera being the only cultured examples. Herein we genetically and phenotypically characterize 10 strains isolated from the tropical Atlantic and North Pacific Oceans, and show that although all of the strains are highly similar at the genetic level, with the internal transcribed sequence (ITS) region sequence varying by approximately 2 bp on average, there are many unexpected phenotypic differences between the isolates (e.g. cell size, temperature optima and range, extracellular material excretion and variability in rates of nitrogen fixation). However based on the observed sequence similarity, we propose that all of these isolates are members of the genus Crocosphaera (type strain Crocosphaera watsonii WH8501), and that the phenotypic diversity we see may reflect ecologically important variation relevant for modelling N(2) fixation in the oligotrophic ocean.

Genetic Architecture of Highly Complex Chemical Resistance Traits across Four Yeast Strains

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.

The Genetic Architecture of Shoot Branching in Arabidopsis thaliana: A Comparative Assessment of Candidate Gene Associations vs. Quantitative Trait Locus Mapping

Association mapping focused on 36 genes involved in branch development was used to identify candidate genes for variation in shoot branching in Arabidopsis thaliana. The associations between four branching traits and moderate-frequency haplogroups at the studied genes were tested in a panel of 96 accessions from a restricted geographic range in Central Europe. Using a mixed-model association-mapping method, we identified three loci—MORE AXILLARY GROWTH 2 (MAX2), MORE AXILLARY GROWTH 3 (MAX3), and SUPERSHOOT 1 (SPS1)—that were significantly associated with branching variation. On the basis of a more extensive examination of the MAX2 and MAX3 genomic regions, we find that linkage disequilibrium in these regions decays within ∼10 kb and trait associations localize to the candidate genes in these regions. When the significant associations are compared to relevant quantitative trait loci (QTL) from previous Ler × Col and Cvi × Ler recombinant inbred line (RIL) mapping studies, no additive QTL overlapping these candidate genes are observed, although epistatic QTL for branching, including one that spans the SPS1, are found. These results suggest that epistasis is prevalent in determining branching variation in A. thaliana and may need to be considered in linkage disequilibrium mapping studies of genetically diverse accessions.

Higher-order genetic interactions and their contribution to complex traits

The contribution of genetic interactions involving three or more loci to complex traits is poorly understood. These higher-order genetic interactions (HGIs) are difficult to detect in genetic mapping studies, therefore, few examples of them have been described. However, the lack of data on HGIs should not be misconstrued as proof that this class of genetic effect is unimportant. To the contrary, evidence from model organisms suggests that HGIs frequently influence genetic studies and contribute to many complex traits. Here, we review the growing literature on HGIs and discuss the future of research on this topic.