Virulence Patterns of Oat Crown Rust in Australia - Season 2022.

Puccinia coronata f. sp. avenae (Pca) is an important foliar pathogen of oat which causes crown rust disease. The virulence profile of 48 Pca isolates derived from different locations in Australia was characterized using a collection of oat lines often utilized in rust surveys in the United States and Australia. This analysis indicates that Pca populations in Eastern Australia are broadly virulent, which contrasts with the population in Western Australia (WA). Several oat lines/Pc genes are effective against all rust samples collected from WA, suggesting they may provide useful resistance in this region if deployed in combination. We identified 19 lines from the United States oat differential set that display disease resistance to Pca in WA, with some in agreement with previous rust survey reports. We adopted the 10-letter nomenclature system to define oat crown rust races in Australia and compare the frequency of those virulence traits to published data from the United States. Based on this nomenclature, 42 unique races were detected among the 48 isolates, reflecting the high diversity of virulence phenotypes for Pca in Australia. Nevertheless, the Pca population in the United States is substantially more broadly virulent than that of Australia. Close examination of resistance profiles for the oat differential set lines after infection with Pca supports hypotheses of allelism or redundancy among Pc genes or the presence of several resistance genes in some oat differential lines. These findings illustrate the need to deconvolute the oat differential set using molecular tools.[Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

The stem rust fungus Puccinia graminis f. sp. tritici induces centromeric small RNAs during late infection that are associated with genome-wide DNA methylation.

BACKGROUND: Silencing of transposable elements (TEs) is essential for maintaining genome stability. Plants use small RNAs (sRNAs) to direct DNA methylation to TEs (RNA-directed DNA methylation; RdDM). Similar mechanisms of epigenetic silencing in the fungal kingdom have remained elusive. RESULTS: We use sRNA sequencing and methylation data to gain insight into epigenetics in the dikaryotic fungus Puccinia graminis f. sp. tritici (Pgt), which causes the devastating stem rust disease on wheat. We use Hi-C data to define the Pgt centromeres and show that they are repeat-rich regions (~250 kb) that are highly diverse in sequence between haplotypes and, like in plants, are enriched for young TEs. DNA cytosine methylation is particularly active at centromeres but also associated with genome-wide control of young TE insertions. Strikingly, over 90% of Pgt sRNAs and several RNAi genes are differentially expressed during infection. Pgt induces waves of functionally diversified sRNAs during infection. The early wave sRNAs are predominantly 21 nts with a 5' uracil derived from genes. In contrast, the late wave sRNAs are mainly 22-nt sRNAs with a 5' adenine and are strongly induced from centromeric regions. TEs that overlap with late wave sRNAs are more likely to be methylated, both inside and outside the centromeres, and methylated TEs exhibit a silencing effect on nearby genes. CONCLUSIONS: We conclude that rust fungi use an epigenetic silencing pathway that might have similarity with RdDM in plants. The Pgt RNAi machinery and sRNAs are under tight temporal control throughout infection and might ensure genome stability during sporulation.

Long-read sequencing based clinical metagenomics for the detection and confirmation of Pneumocystis jirovecii directly from clinical specimens: A paradigm shift in mycological diagnostics.

The advent of next generation sequencing technologies has enabled the characterization of the genetic content of entire communities of organisms, including those in clinical specimens, without prior culturing. The MinION from Oxford Nanopore Technologies offers real-time, direct sequencing of long DNA fragments directly from clinical samples. The aim of this study was to assess the ability of unbiased, genome-wide, long-read, shotgun sequencing using MinION to identify Pneumocystis jirovecii directly from respiratory tract specimens and to characterize the associated mycobiome. Pneumocystis pneumonia (PCP) is a life-threatening fungal disease caused by P. jirovecii. Currently, the diagnosis of PCP relies on direct microscopic or real-time quantitative polymerase chain reaction (PCR) examination of respiratory tract specimens, as P. jirovecii cannot be cultured readily in vitro. P. jirovecii DNA was detected in bronchoalveolar lavage (BAL) and induced sputum (IS) samples from three patients with confirmed PCP. Other fungi present in the associated mycobiome included known human pathogens (Aspergillus, Cryptococcus, Pichia) as well as commensal species (Candida, Malassezia, Bipolaris). We have established optimized sample preparation conditions for the generation of high-quality data, curated databases, and data analysis tools, which are key to the application of long-read MinION sequencing leading to a fundamental new approach in fungal diagnostics.

Probability Size Matters: The Effect of Foreground-Only versus Foreground+Background Graphs on Risk Aversion Diminishes with Larger Probabilities.

Graphs are increasingly recommended for improving decision-making and promoting risk-avoidant behaviors. Graphs that depict only the number of people affected by a risk ("foreground-only" displays) tend to increase perceived risk and risk aversion (e.g., willingness to get vaccinated), as compared to graphs that also depict the number of people at risk for harm ("foreground+background" displays). However, previous research examining these "foreground-only effects" has focused on relatively low-probability risks (<10%), limiting generalizability to communications about larger risks. In two experiments, we systematically investigated the moderating role of probability size on foreground-only effects, using a wide range of probability sizes (from 0.1% to 40%). Additionally, we examined the moderating role of the size of the risk reduction, that is, the extent to which a protective behavior reduces the risk. Across both experiments, foreground-only effects on perceived risk and risk aversion were weaker for larger probabilities. Experiment 2 also revealed that foreground-only effects were weaker for smaller risk reductions, while foreground-only displays decreased understanding of absolute risk magnitudes independently of probability size. These findings suggest that the greater effectiveness of foreground-only versus foreground+background displays for increasing perceived risk and risk aversion diminishes with larger probability sizes and smaller risk reductions. Moreover, if the goal is to promote understanding of absolute risk magnitudes, foreground+background displays should be used rather than foreground-only displays regardless of probability size. Our findings also help to refine and extend existing theoretical accounts of foreground-only effects to situations involving a wide range of probability sizes.

Cognitive but Not Affective Theory of Mind Deficits in Progressive MS.

OBJECTIVE: Social cognitive deficits are an important consequence of multiple sclerosis (MS), yet our understanding of how these deficits manifest in progressive MS is currently limited. To this end, we examined theory of mind (ToM) ability in a sample of individuals with progressive MS using an ecologically valid virtual assessment tool that allows for delineation of cognitive ToM (inferring thoughts and intentions of others) from affective ToM (inferring emotions of others). METHODS & RESULTS: We compared 15 individuals with progressive MS and 15 healthy controls on their ToM ability using the Virtual Assessment of Mentalising Ability. We found that, relative to healthy controls, participants with progressive MS were impaired in cognitive ToM, but not in affective ToM. Furthermore, we found that the MS participants' deficits in cognitive ToM were mediated by their general cognitive ability such that poor cognitive ToM ability in MS was explained by poor performance on tests of memory and processing speed. CONCLUSIONS: Our findings demonstrate that ToM deficits in progressive MS may be limited to cognitive ToM, while affective ToM is conserved. This could be attributable to the MS-related deficits in general cognitive ability, which appear to negatively affect only the cognitive component of ToM.

The 100-genomes strains, an S. cerevisiae resource that illuminates its natural phenotypic and genotypic variation and emergence as an opportunistic pathogen.

Saccharomyces cerevisiae, a well-established model for species as diverse as humans and pathogenic fungi, is more recently a model for population and quantitative genetics. S. cerevisiae is found in multiple environments-one of which is the human body-as an opportunistic pathogen. To aid in the understanding of the S. cerevisiae population and quantitative genetics, as well as its emergence as an opportunistic pathogen, we sequenced, de novo assembled, and extensively manually edited and annotated the genomes of 93 S. cerevisiae strains from multiple geographic and environmental origins, including many clinical origin strains. These 93 S. cerevisiae strains, the genomes of which are near-reference quality, together with seven previously sequenced strains, constitute a novel genetic resource, the "100-genomes" strains. Our sequencing coverage, high-quality assemblies, and annotation provide unprecedented opportunities for detailed interrogation of complex genomic loci, examples of which we demonstrate. We found most phenotypic variation to be quantitative and identified population, genotype, and phenotype associations. Importantly, we identified clinical origin associations. For example, we found that an introgressed PDR5 was present exclusively in clinical origin mosaic group strains; that the mosaic group was significantly enriched for clinical origin strains; and that clinical origin strains were much more copper resistant, suggesting that copper resistance contributes to fitness in the human host. The 100-genomes strains are a novel, multipurpose resource to advance the study of S. cerevisiae population genetics, quantitative genetics, and the emergence of an opportunistic pathogen.

The Drosophila melanogaster Genetic Reference Panel.

A major challenge of biology is understanding the relationship between molecular genetic variation and variation in quantitative traits, including fitness. This relationship determines our ability to predict phenotypes from genotypes and to understand how evolutionary forces shape variation within and between species. Previous efforts to dissect the genotype-phenotype map were based on incomplete genotypic information. Here, we describe the Drosophila melanogaster Genetic Reference Panel (DGRP), a community resource for analysis of population genomics and quantitative traits. The DGRP consists of fully sequenced inbred lines derived from a natural population. Population genomic analyses reveal reduced polymorphism in centromeric autosomal regions and the X chromosome, evidence for positive and negative selection, and rapid evolution of the X chromosome. Many variants in novel genes, most at low frequency, are associated with quantitative traits and explain a large fraction of the phenotypic variance. The DGRP facilitates genotype-phenotype mapping using the power of Drosophila genetics.

Genetic basis of transcriptome diversity in Drosophila melanogaster.

Understanding how DNA sequence variation is translated into variation for complex phenotypes has remained elusive but is essential for predicting adaptive evolution, for selecting agriculturally important animals and crops, and for personalized medicine. Gene expression may provide a link between variation in DNA sequence and organismal phenotypes, and its abundance can be measured efficiently and accurately. Here we quantified genome-wide variation in gene expression in the sequenced inbred lines of the Drosophila melanogaster Genetic Reference Panel (DGRP), increasing the annotated Drosophila transcriptome by 11%, including thousands of novel transcribed regions (NTRs). We found that 42% of the Drosophila transcriptome is genetically variable in males and females, including the NTRs, and is organized into modules of genetically correlated transcripts. We found that NTRs often were negatively correlated with the expression of protein-coding genes, which we exploited to annotate NTRs functionally. We identified regulatory variants for the mean and variance of gene expression, which have largely independent genetic control. Expression quantitative trait loci (eQTLs) for the mean, but not for the variance, of gene expression were concentrated near genes. Notably, the variance eQTLs often interacted epistatically with local variants in these genes to regulate gene expression. This comprehensive characterization of population-scale diversity of transcriptomes and its genetic basis in the DGRP is critically important for a systems understanding of quantitative trait variation.

Designing Graphs that Promote Both Risk Understanding and Behavior Change.

Graphs show promise for improving communications about different types of risks, including health risks, financial risks, and climate risks. However, graph designs that are effective at meeting one important risk communication goal (promoting risk-avoidant behaviors) can at the same time compromise another key goal (improving risk understanding). We developed and tested simple bar graphs aimed at accomplishing these two goals simultaneously. We manipulated two design features in graphs, namely, whether graphs depicted the number of people affected by a risk and those at risk of harm ("foreground+background") versus only those affected ("foreground-only"), and the presence versus absence of simple numerical labels above bars. Foreground-only displays were associated with larger risk perceptions and risk-avoidant behavior (i.e., willingness to take a drug for heart attack prevention) than foreground+background displays, regardless of the presence of labels. Foreground-only graphs also hindered risk understanding when labels were not present. However, the presence of labels significantly improved understanding, eliminating the detrimental effect of foreground-only displays. Labels also led to more positive user evaluations of the graphs, but did not affect risk-avoidant behavior. Using process modeling we identified mediators (risk perceptions, understanding, user evaluations) that explained the effect of display type on risk-avoidant behavior. Our findings contribute new evidence to the graph design literature: unlike what was previously feared, we demonstrate that it is possible to design foreground-only graphs that promote intentions for behavior change without a detrimental effect on risk understanding. Implications for the design of graphical risk communications and decision support are discussed.

Natural variation in genome architecture among 205 Drosophila melanogaster Genetic Reference Panel lines.

The Drosophila melanogaster Genetic Reference Panel (DGRP) is a community resource of 205 sequenced inbred lines, derived to improve our understanding of the effects of naturally occurring genetic variation on molecular and organismal phenotypes. We used an integrated genotyping strategy to identify 4,853,802 single nucleotide polymorphisms (SNPs) and 1,296,080 non-SNP variants. Our molecular population genomic analyses show higher deletion than insertion mutation rates and stronger purifying selection on deletions. Weaker selection on insertions than deletions is consistent with our observed distribution of genome size determined by flow cytometry, which is skewed toward larger genomes. Insertion/deletion and single nucleotide polymorphisms are positively correlated with each other and with local recombination, suggesting that their nonrandom distributions are due to hitchhiking and background selection. Our cytogenetic analysis identified 16 polymorphic inversions in the DGRP. Common inverted and standard karyotypes are genetically divergent and account for most of the variation in relatedness among the DGRP lines. Intriguingly, variation in genome size and many quantitative traits are significantly associated with inversions. Approximately 50% of the DGRP lines are infected with Wolbachia, and four lines have germline insertions of Wolbachia sequences, but effects of Wolbachia infection on quantitative traits are rarely significant. The DGRP complements ongoing efforts to functionally annotate the Drosophila genome. Indeed, 15% of all D. melanogaster genes segregate for potentially damaged proteins in the DGRP, and genome-wide analyses of quantitative traits identify novel candidate genes. The DGRP lines, sequence data, genotypes, quality scores, phenotypes, and analysis and visualization tools are publicly available.

Designing Graphs to Communicate Risks: Understanding How the Choice of Graphical Format Influences Decision Making.

Previous research suggests that the choice of graphical format for communicating risk information affects both understanding of the risk magnitude and the likelihood of acting to decrease risk. However, the mechanisms through which these effects work are poorly understood. To explore these mechanisms using a real-world scenario, we examined the relative impact of two graphical displays for depicting the risk of exposure to unexploded ammunition during potential land redevelopment. One display depicted only the foreground information graphically (a bar graph of the number of people harmed), and a second depicted the foreground and background graphically (a stacked bar graph representing both the number harmed and at risk). We presented 296 participants with either the foreground-only or the foreground and background graphical display and measured a broad set of outcome variables, examining (1) the graphical display effect on each of the outcome measures and (2) the pathways by which any display effects work to influence decision making. We found that the foreground-only graphical display increased perceived likelihood and experienced fear, which produced greater worry, which in turn increased risk aversion. In addition, a positive evaluation of the communication materials increased support for policies related to land redevelopment, whether those policies were risk taking or risk mitigating. Finally, the foreground-only graphical display decreased understanding of the risk magnitude, showing that approaches to accomplish one risk communication goal (promoting risk-averse decisions) may do so at the expense of another goal (increasing understanding).

Population genomic analysis reveals no evidence for GC-biased gene conversion in Drosophila melanogaster.

Gene conversion is the nonreciprocal exchange of genetic material between homologous chromosomes. Multiple lines of evidence from a variety of taxa strongly suggest that gene conversion events are biased toward GC-bearing alleles. However, in Drosophila, the data have largely been indirect and unclear, with some studies supporting the predictions of a GC-biased gene conversion model and other data showing contradictory findings. Here, we test whether gene conversion events are GC-biased in Drosophila melanogaster using whole-genome polymorphism and divergence data. Our results provide no support for GC-biased gene conversion and thus suggest that this process is unlikely to significantly contribute to patterns of polymorphism and divergence in this system.

Joint genotyping on the fly: identifying variation among a sequenced panel of inbred lines.

High-throughput sequencing is enabling remarkably deep surveys of genomic variation. It is now possible to completely sequence multiple individuals from a single species, yet the identification of variation among them remains an evolving computational challenge. This challenge is compounded for experimental organisms when strains are studied instead of individuals. In response, we present the Joint Genotyper for Inbred Lines (JGIL) as a method for obtaining genotypes and identifying variation among a large panel of inbred strains or lines. JGIL inputs the sequence reads from each line after their alignment to a common reference. Its probabilistic model includes site-specific parameters common to all lines that describe the frequency of nucleotides segregating in the population from which the inbred panel was derived. The distribution of line genotypes is conditional on these parameters and reflects the experimental design. Site-specific error probabilities, also common to all lines, parameterize the distribution of reads conditional on line genotype and realized coverage. Both sets of parameters are estimated per site from the aggregate read data, and posterior probabilities are calculated to decode the genotype of each line. We present an application of JGIL to 162 inbred Drosophila melanogaster lines from the Drosophila Genetic Reference Panel. We explore by simulation the effect of varying coverage, sequencing error, mapping error, and the number of lines. In doing so, we illustrate how JGIL is robust to moderate levels of error. Supported by these analyses, we advocate the importance of modeling the data and the experimental design when possible.

Sexuality generates diversity in the aflatoxin gene cluster: evidence on a global scale.

Aflatoxins are produced by Aspergillus flavus and A. parasiticus in oil-rich seed and grain crops and are a serious problem in agriculture, with aflatoxin B1 being the most carcinogenic natural compound known. Sexual reproduction in these species occurs between individuals belonging to different vegetative compatibility groups (VCGs). We examined natural genetic variation in 758 isolates of A. flavus, A. parasiticus and A. minisclerotigenes sampled from single peanut fields in the United States (Georgia), Africa (Benin), Argentina (Córdoba), Australia (Queensland) and India (Karnataka). Analysis of DNA sequence variation across multiple intergenic regions in the aflatoxin gene clusters of A. flavus, A. parasiticus and A. minisclerotigenes revealed significant linkage disequilibrium (LD) organized into distinct blocks that are conserved across different localities, suggesting that genetic recombination is nonrandom and a global occurrence. To assess the contributions of asexual and sexual reproduction to fixation and maintenance of toxin chemotype diversity in populations from each locality/species, we tested the null hypothesis of an equal number of MAT1-1 and MAT1-2 mating-type individuals, which is indicative of a sexually recombining population. All samples were clone-corrected using multi-locus sequence typing which associates closely with VCG. For both A. flavus and A. parasiticus, when the proportions of MAT1-1 and MAT1-2 were significantly different, there was more extensive LD in the aflatoxin cluster and populations were fixed for specific toxin chemotype classes, either the non-aflatoxigenic class in A. flavus or the B1-dominant and G1-dominant classes in A. parasiticus. A mating type ratio close to 1∶1 in A. flavus, A. parasiticus and A. minisclerotigenes was associated with higher recombination rates in the aflatoxin cluster and less pronounced chemotype differences in populations. This work shows that the reproductive nature of the population (more sexual versus more asexual) is predictive of aflatoxin chemotype diversity in these agriculturally important fungi.

Enhanced diversity and aflatoxigenicity in interspecific hybrids of Aspergillus flavus and Aspergillus parasiticus.

Aspergillus flavus and A. parasiticus are the two most important aflatoxin-producing fungi responsible for the contamination of agricultural commodities worldwide. Both species are heterothallic and undergo sexual reproduction in laboratory crosses. Here we examine the possibility of interspecific matings between A. flavus and A. parasiticus. These species can be distinguished morphologically and genetically, as well as by their mycotoxin profiles. Aspergillus flavus produces both B aflatoxins and cyclopiazonic acid (CPA), B aflatoxins or CPA alone, or neither mycotoxin; Aspergillus parasiticus produces B and G aflatoxins or the aflatoxin precursor O-methylsterigmatocystin, but not CPA. Only four of forty-five attempted interspecific crosses between opposite mating types of A. flavus and A. parasiticus were fertile and produced viable ascospores. Single ascospore strains from each cross were shown to be recombinant hybrids using multilocus genotyping and array comparative genome hybridization. Conidia of parents and their hybrid progeny were haploid and predominantly monokaryons and dikaryons based on flow cytometry. Multilocus phylogenetic inference showed that experimental hybrid progeny were grouped with naturally occurring A. flavus L strain and A. parasiticus. Higher total aflatoxin concentrations in some F1 progeny strains compared to midpoint parent aflatoxin levels indicate synergism in aflatoxin production; moreover, three progeny strains synthesized G aflatoxins that were not produced by the parents, and there was evidence of allopolyploidization in one strain. These results suggest that hybridization is an important diversifying force resulting in the genesis of novel toxin profiles in these agriculturally important fungi.

The genetics of quantitative traits: challenges and prospects.

A major challenge in current biology is to understand the genetic basis of variation for quantitative traits. We review the principles of quantitative trait locus mapping and summarize insights about the genetic architecture of quantitative traits that have been obtained over the past decades. We are currently in the midst of a genomic revolution, which enables us to incorporate genetic variation in transcript abundance and other intermediate molecular phenotypes into a quantitative trait locus mapping framework. This systems genetics approach enables us to understand the biology inside the 'black box' that lies between genotype and phenotype in terms of causal networks of interacting genes.

Effects of Numerical Versus Foreground-Only Icon Displays on Understanding of Risk Magnitudes.

The aim of this work is to advance knowledge of how to measure gist and verbatim understanding of risk magnitude information and to apply this knowledge to address whether graphics that focus on the number of people affected (the numerator of the risk ratio, i.e., the foreground) are effective displays for increasing (a) understanding of absolute and relative risk magnitudes and (b) risk avoidance. In 2 experiments, the authors examined the effects of a graphical display that used icons to represent the foreground information on measures of understanding (Experiments 1 and 2) and on perceived risk, affect, and risk aversion (Experiment 2). Consistent with prior findings, this foreground-only graphical display increased perceived risk and risk aversion; however, it also led to decreased understanding of absolute (although not relative) risk magnitudes. Methodologically, this work shows the importance of distinguishing understanding of absolute risk from understanding of relative risk magnitudes, and the need to assess gist knowledge of both types of risk. Substantively, this work shows that although using foreground-only graphical displays is an appealing risk communication strategy to increase risk aversion, doing so comes at the cost of decreased understanding of absolute risk magnitudes.

Phenotypic plasticity of the Drosophila transcriptome.

Phenotypic plasticity is the ability of a single genotype to produce different phenotypes in response to changing environments. We assessed variation in genome-wide gene expression and four fitness-related phenotypes of an outbred Drosophila melanogaster population under 20 different physiological, social, nutritional, chemical, and physical environments; and we compared the phenotypically plastic transcripts to genetically variable transcripts in a single environment. The environmentally sensitive transcriptome consists of two transcript categories, which comprise ∼15% of expressed transcripts. Class I transcripts are genetically variable and associated with detoxification, metabolism, proteolysis, heat shock proteins, and transcriptional regulation. Class II transcripts have low genetic variance and show sexually dimorphic expression enriched for reproductive functions. Clustering analysis of Class I transcripts reveals a fragmented modular organization and distinct environmentally responsive transcriptional signatures for the four fitness-related traits. Our analysis suggests that a restricted environmentally responsive segment of the transcriptome preserves the balance between phenotypic plasticity and environmental canalization.

Genomic variation and its impact on gene expression in Drosophila melanogaster.

Understanding the relationship between genetic and phenotypic variation is one of the great outstanding challenges in biology. To meet this challenge, comprehensive genomic variation maps of human as well as of model organism populations are required. Here, we present a nucleotide resolution catalog of single-nucleotide, multi-nucleotide, and structural variants in 39 Drosophila melanogaster Genetic Reference Panel inbred lines. Using an integrative, local assembly-based approach for variant discovery, we identify more than 3.6 million distinct variants, among which were more than 800,000 unique insertions, deletions (indels), and complex variants (1 to 6,000 bp). While the SNP density is higher near other variants, we find that variants themselves are not mutagenic, nor are regions with high variant density particularly mutation-prone. Rather, our data suggest that the elevated SNP density around variants is mainly due to population-level processes. We also provide insights into the regulatory architecture of gene expression variation in adult flies by mapping cis-expression quantitative trait loci (cis-eQTLs) for more than 2,000 genes. Indels comprise around 10% of all cis-eQTLs and show larger effects than SNP cis-eQTLs. In addition, we identified two-fold more gene associations in males as compared to females and found that most cis-eQTLs are sex-specific, revealing a partial decoupling of the genomic architecture between the sexes as well as the importance of genetic factors in mediating sex-biased gene expression. Finally, we performed RNA-seq-based allelic expression imbalance analyses in the offspring of crosses between sequenced lines, which revealed that the majority of strong cis-eQTLs can be validated in heterozygous individuals.

Using whole-genome sequence data to predict quantitative trait phenotypes in Drosophila melanogaster.

Predicting organismal phenotypes from genotype data is important for plant and animal breeding, medicine, and evolutionary biology. Genomic-based phenotype prediction has been applied for single-nucleotide polymorphism (SNP) genotyping platforms, but not using complete genome sequences. Here, we report genomic prediction for starvation stress resistance and startle response in Drosophila melanogaster, using ∼2.5 million SNPs determined by sequencing the Drosophila Genetic Reference Panel population of inbred lines. We constructed a genomic relationship matrix from the SNP data and used it in a genomic best linear unbiased prediction (GBLUP) model. We assessed predictive ability as the correlation between predicted genetic values and observed phenotypes by cross-validation, and found a predictive ability of 0.239±0.008 (0.230±0.012) for starvation resistance (startle response). The predictive ability of BayesB, a Bayesian method with internal SNP selection, was not greater than GBLUP. Selection of the 5% SNPs with either the highest absolute effect or variance explained did not improve predictive ability. Predictive ability decreased only when fewer than 150,000 SNPs were used to construct the genomic relationship matrix. We hypothesize that predictive power in this population stems from the SNP-based modeling of the subtle relationship structure caused by long-range linkage disequilibrium and not from population structure or SNPs in linkage disequilibrium with causal variants. We discuss the implications of these results for genomic prediction in other organisms.