Genomic Selection and Association Mapping in Rice (Oryza sativa): Effect of Trait Genetic Architecture,Training Population Composition,Marker Number and Statistical Model on Accuracy of Rice Genomic Selection in Elite,Tropical Rice Breeding Lines

Genomic Selection (GS) is a new breeding method in which genome-wide markers are used to predict the breeding value of individuals in a breeding population. GS has been shown to improve breeding efficiency in dairy cattle and several crop plant species, and here we evaluate for the first time its efficacy for breeding inbred lines of rice. We performed a genome-wide association study (GWAS) in conjunction with five-fold GS cross-validation on a population of 363 elite breeding lines from the International Rice Research Institute''s (IRRI) irrigated rice breeding program and herein report the GS results. The population was genotyped with 73,147 markers using genotyping-by-sequencing. The training population, statistical method used to build the GS model, number of markers, and trait were varied to determine their effect on prediction accuracy. For all three traits, genomic prediction models outperformed prediction based on pedigree records alone. Prediction accuracies ranged from 0.31 and 0.34 for grain yield and plant height to 0.63 for flowering time. Analyses using subsets of the full marker set suggest that using one marker every 0.2 cM is sufficient for genomic selection in this collection of rice breeding materials. RR-BLUP was the best performing statistical method for grain yield where no large effect QTL were detected by GWAS, while for flowering time, where a single very large effect QTL was detected, the non-GS multiple linear regression method outperformed GS models. For plant height, in which four mid-sized QTL were identified by GWAS, random forest produced the most consistently accurate GS models. Our results suggest that GS, informed by GWAS interpretations of genetic architecture and population structure, could become an effective tool for increasing the efficiency of rice breeding as the costs of genotyping continue to decline.     

Synthesizing and Salvaging NAD+: Lessons Learned from Chlamydomonas reinhardtii

The essential coenzyme nicotinamide adenine dinucleotide (NAD⁺) plays important roles in metabolic reactions and cell regulation in all organisms. Bacteria, fungi, plants, and animals use different pathways to synthesize NAD⁺. Our molecular and genetic data demonstrate that in the unicellular green alga Chlamydomonas NAD⁺ is synthesized from aspartate (de novo synthesis), as in plants, or nicotinamide, as in mammals (salvage synthesis). The de novo pathway requires five different enzymes: L-aspartate oxidase (ASO), quinolinate synthetase (QS), quinolate phosphoribosyltransferase (QPT), nicotinate/nicotinamide mononucleotide adenylyltransferase (NMNAT), and NAD⁺ synthetase (NS). Sequence similarity searches, gene isolation and sequencing of mutant loci indicate that mutations in each enzyme result in a nicotinamide-requiring mutant phenotype in the previously isolated nic mutants. We rescued the mutant phenotype by the introduction of BAC DNA (nic2-1 and nic13-1) or plasmids with cloned genes (nic1-1 and nic15-1) into the mutants. NMNAT, which is also in the de novo pathway, and nicotinamide phosphoribosyltransferase (NAMPT) constitute the nicotinamide-dependent salvage pathway. A mutation in NAMPT (npt1-1) has no obvious growth defect and is not nicotinamide-dependent. However, double mutant strains with the npt1-1 mutation and any of the nic mutations are inviable. When the de novo pathway is inactive, the salvage pathway is essential to Chlamydomonas for the synthesis of NAD⁺. A homolog of the human SIRT6-like gene, SRT2, is upregulated in the NS mutant, which shows a longer vegetative life span than wild-type cells. Our results suggest that Chlamydomonas is an excellent model system to study NAD⁺ metabolism and cell longevity.     

DNMT3L Modulates Significant and Distinct Flanking Sequence Preference for DNA Methylation by DNMT3A and DNMT3B In Vivo

The DNTM3A and DNMT3B de novo DNA methyltransferases (DNMTs) are responsible for setting genomic DNA methylation patterns, a key layer of epigenetic information. Here, using an in vivo episomal methylation assay and extensive bisulfite methylation sequencing, we show that human DNMT3A and DNMT3B possess significant and distinct flanking sequence preferences for target CpG sites. Selection for high or low efficiency sites is mediated by the base composition at the −2 and +2 positions flanking the CpG site for DNMT3A, and at the −1 and +1 positions for DNMT3B. This intrinsic preference reproducibly leads to the formation of specific de novo methylation patterns characterized by up to 34-fold variations in the efficiency of DNA methylation at individual sites. Furthermore, analysis of the distribution of signature methylation hotspot and coldspot motifs suggests that DNMT flanking sequence preference has contributed to shaping the composition of CpG islands in the human genome. Our results also show that the DNMT3L stimulatory factor modulates the formation of de novo methylation patterns in two ways. First, DNMT3L selectively focuses the DNA methylation machinery on properly chromatinized DNA templates. Second, DNMT3L attenuates the impact of the intrinsic DNMT flanking sequence preference by providing a much greater boost to the methylation of poorly methylated sites, thus promoting the formation of broader and more uniform methylation patterns. This study offers insights into the manner by which DNA methylation patterns are deposited and reveals a new level of interplay between members of the de novo DNMT family.     

Island-Model Genomic Selection for Long-Term Genetic Improvement of Autogamous Crops

Acceleration of genetic improvement of autogamous crops such as wheat and rice is necessary to increase cereal production in response to the global food crisis. Population and pedigree methods of breeding, which are based on inbred line selection, are used commonly in the genetic improvement of autogamous crops. These methods, however, produce a few novel combinations of genes in a breeding population. Recurrent selection promotes recombination among genes and produces novel combinations of genes in a breeding population, but it requires inaccurate single-plant evaluation for selection. Genomic selection (GS), which can predict genetic potential of individuals based on their marker genotype, might have high reliability of single-plant evaluation and might be effective in recurrent selection. To evaluate the efficiency of recurrent selection with GS, we conducted simulations using real marker genotype data of rice cultivars. Additionally, we introduced the concept of an “island model” inspired by evolutionary algorithms that might be useful to maintain genetic variation through the breeding process. We conducted GS simulations using real marker genotype data of rice cultivars to evaluate the efficiency of recurrent selection and the island model in an autogamous species. Results demonstrated the importance of producing novel combinations of genes through recurrent selection. An initial population derived from admixture of multiple bi-parental crosses showed larger genetic gains than a population derived from a single bi-parental cross in whole cycles, suggesting the importance of genetic variation in an initial population. The island-model GS better maintained genetic improvement in later generations than the other GS methods, suggesting that the island-model GS can utilize genetic variation in breeding and can retain alleles with small effects in the breeding population. The island-model GS will become a new breeding method that enhances the potential of genomic selection in autogamous crops, especially bringing long-term improvement.     

High Fat Feeding Induces Hepatic Fatty Acid Elongation in Mice

Background

High-fat diets promote hepatic lipid accumulation. Paradoxically, these diets also induce lipogenic gene expression in rodent liver. Whether high expression of these genes actually results in an increased flux through the de novo lipogenic pathway in vivo has not been demonstrated.

Methodology/Principal Findings

To interrogate this apparent paradox, we have quantified de novo lipogenesis in C57Bl/6J mice fed either chow, a high-fat or a n-3 polyunsaturated fatty acid (PUFA)-enriched high-fat diet. A novel approach based on mass isotopomer distribution analysis (MIDA) following 1-¹³C acetate infusion was applied to simultaneously determine de novo lipogenesis, fatty acid elongation as well as cholesterol synthesis. Furthermore, we measured very low density lipoprotein-triglyceride (VLDL-TG) production rates. High-fat feeding promoted hepatic lipid accumulation and induced the expression of lipogenic and cholesterogenic genes compared to chow-fed mice: induction of gene expression was found to translate into increased oleate synthesis. Interestingly, this higher lipogenic flux (+74 µg/g/h for oleic acid) in mice fed the high-fat diet was mainly due to an increased hepatic elongation of unlabeled palmitate (+66 µg/g/h) rather than to elongation of de novo synthesized palmitate. In addition, fractional cholesterol synthesis was increased, i.e. 5.8±0.4% vs. 8.1±0.6% for control and high fat-fed animals, respectively. Hepatic VLDL-TG production was not affected by high-fat feeding. Partial replacement of saturated fat by fish oil completely reversed the lipogenic effects of high-fat feeding: hepatic lipogenic and cholesterogenic gene expression levels as well as fatty acid and cholesterol synthesis rates were normalized.

Conclusions/Significance

High-fat feeding induces hepatic fatty acid synthesis in mice, by chain elongation and subsequent desaturation rather than de novo synthesis, while VLDL-TG output remains unaffected. Suppression of lipogenic fluxes by fish oil prevents from high fat diet-induced hepatic steatosis in mice.     

Genomic growth curves of an outbred pig population

In the current post-genomic era, the genetic basis of pig growth can be understood by assessing SNP marker effects and genomic breeding values (GEBV) based on estimates of these growth curve parameters as phenotypes. Although various statistical methods, such as random regression (RR-BLUP) and Bayesian LASSO (BL), have been applied to genomic selection (GS), none of these has yet been used in a growth curve approach. In this work, we compared the accuracies of RR-BLUP and BL using empirical weight-age data from an outbred F2 (Brazilian Piau X commercial) population. The phenotypes were determined by parameter estimates using a nonlinear logistic regression model and the halothane gene was considered as a marker for evaluating the assumptions of the GS methods in relation to the genetic variation explained by each locus. BL yielded more accurate values for all of the phenotypes evaluated and was used to estimate SNP effects and GEBV vectors. The latter allowed the construction of genomic growth curves, which showed substantial genetic discrimination among animals in the final growth phase. The SNP effect estimates allowed identification of the most relevant markers for each phenotype, the positions of which were coincident with reported QTL regions for growth traits.     

Comparisons of single-stage and two-stage approaches to genomic selection

Genomic selection (GS) is a method for predicting breeding values of plants or animals using many molecular markers that is commonly implemented in two stages. In plant breeding the first stage usually involves computation of adjusted means for genotypes which are then used to predict genomic breeding values in the second stage. We compared two classical stage-wise approaches, which either ignore or approximate correlations among the means by a diagonal matrix, and a new method, to a single-stage analysis for GS using ridge regression best linear unbiased prediction (RR-BLUP). The new stage-wise method rotates (orthogonalizes) the adjusted means from the first stage before submitting them to the second stage. This makes the errors approximately independently and identically normally distributed, which is a prerequisite for many procedures that are potentially useful for GS such as machine learning methods (e.g. boosting) and regularized regression methods (e.g. lasso). This is illustrated in this paper using componentwise boosting. The componentwise boosting method minimizes squared error loss using least squares and iteratively and automatically selects markers that are most predictive of genomic breeding values. Results are compared with those of RR-BLUP using fivefold cross-validation. The new stage-wise approach with rotated means was slightly more similar to the single-stage analysis than the classical two-stage approaches based on non-rotated means for two unbalanced datasets. This suggests that rotation is a worthwhile pre-processing step in GS for the two-stage approaches for unbalanced datasets. Moreover, the predictive accuracy of stage-wise RR-BLUP was higher (5.0–6.1 %) than that of componentwise boosting.     

Octarellin VI: Using Rosetta to Design a Putative Artificial (β/α)8 Protein

The computational protein design protocol Rosetta has been applied successfully to a wide variety of protein engineering problems. Here the aim was to test its ability to design de novo a protein adopting the TIM-barrel fold, whose formation requires about twice as many residues as in the largest proteins successfully designed de novo to date. The designed protein, Octarellin VI, contains 216 residues. Its amino acid composition is similar to that of natural TIM-barrel proteins. When produced and purified, it showed a far-UV circular dichroism spectrum characteristic of folded proteins, with α-helical and β-sheet secondary structure. Its stable tertiary structure was confirmed by both tryptophan fluorescence and circular dichroism in the near UV. It proved heat stable up to 70°C. Dynamic light scattering experiments revealed a unique population of particles averaging 4 nm in diameter, in good agreement with our model. Although these data suggest the successful creation of an artificial α/β protein of more than 200 amino acids, Octarellin VI shows an apparent noncooperative chemical unfolding and low solubility.     

Replication of the 4p16 Susceptibility Locus in Congenital Heart Disease in Han Chinese Populations

Congenital heart disease (CHD) is the most common form of congenital human birth anomalies and a leading cause of perinatal and infant mortality. Some studies including our published genome-wide association study (GWAS) of CHD have indicated that genetic variants may contribute to the risk of CHD. Recently, Cordell et al. published a GWAS of multiple CHD phenotypes in European Caucasians and identified 3 susceptibility loci (rs870142, rs16835979 and rs6824295) for ostium secundum atrial septal defect (ASD) at chromosome 4p16. However, whether these loci at 4p16 confer the predisposition to CHD in Chinese population is unclear. In the current study, we first analyzed the associations between these 3 single nucleotide polymorphisms (SNPs) at 4p16 and CHD risk by using our existing genome-wide scan data and found all of the 3 SNPs showed significant associations with ASD in the same direction as that observed in Cordell’s study, but not with other subtypes- ventricular septal defect (VSD) and ASD combined VSD. As these 3 SNPs were in high linkage disequilibrium (LD) in Chinese population, we selected one SNP with the lowest P value in our GWAS scan (rs16835979) to perform a replication study with additional 1,709 CHD cases with multiple phenotypes and 1,962 controls. The significant association was also observed only within the ASD subgroup, which was heterogeneous from other disease groups. In combined GWAS and replication samples, the minor allele of rs16835979 remained significant association with the risk of ASD (OR = 1.22, 95% CI = 1.08–1.38, P = 0.001). Our findings suggest that susceptibility loci of ASD identified from Cordell’s European GWAS are generalizable to Chinese population, and such investigation may provide new insights into the roles of genetic variants in the etiology of different CHD phenotypes.     

Genetic Variation for Life History Sensitivity to Seasonal Warming in Arabidopsis thaliana

Climate change has altered life history events in many plant species; however, little is known about genetic variation underlying seasonal thermal response. In this study, we simulated current and three future warming climates and measured flowering time across a globally diverse set of Arabidopsis thaliana accessions. We found that increased diurnal and seasonal temperature (1°–3°) decreased flowering time in two fall cohorts. The early fall cohort was unique in that both rapid cycling and overwintering life history strategies were revealed; the proportion of rapid cycling plants increased by 3–7% for each 1° temperature increase. We performed genome-wide association studies (GWAS) to identify the underlying genetic basis of thermal sensitivity. GWAS identified five main-effect quantitative trait loci (QTL) controlling flowering time and another five QTL with thermal sensitivity. Candidate genes include known flowering loci; a cochaperone that interacts with heat-shock protein 90; and a flowering hormone, gibberellic acid, a biosynthetic enzyme. The identified genetic architecture allowed accurate prediction of flowering phenotypes (R² > 0.95) that has application for genomic selection of adaptive genotypes for future environments. This work may serve as a reference for breeding and conservation genetic studies under changing environments.     

The Tandem Repeats Enabling Reversible Switching between the Two Phases of β-Lactamase Substrate Spectrum

Expansion or shrinkage of existing tandem repeats (TRs) associated with various biological processes has been actively studied in both prokaryotic and eukaryotic genomes, while their origin and biological implications remain mostly unknown. Here we describe various duplications (de novo TRs) that occurred in the coding region of a β-lactamase gene, where a conserved structure called the omega loop is encoded. These duplications that occurred under selection using ceftazidime conferred substrate spectrum extension to include the antibiotic. Under selective pressure with one of the original substrates (amoxicillin), a high level of reversion occurred in the mutant β-lactamase genes completing a cycle back to the original substrate spectrum. The de novo TRs coupled with reversion makes a genetic toggling mechanism enabling reversible switching between the two phases of the substrate spectrum of β-lactamases. This toggle exemplifies the effective adaptation of de novo TRs for enhanced bacterial survival. We found pairs of direct repeats that mediated the DNA duplication (TR formation). In addition, we found different duos of sequences that mediated the DNA duplication. These novel elements—that we named SCSs (same-strand complementary sequences)—were also found associated with β-lactamase TR mutations from clinical isolates. Both direct repeats and SCSs had a high correlation with TRs in diverse bacterial genomes throughout the major phylogenetic lineages, suggesting that they comprise a fundamental mechanism shaping the bacterial evolution.     

Identification and characterization of PDGFRα+ mesenchymal progenitors in human skeletal muscle

Fatty and fibrous connective tissue formation is a hallmark of diseased skeletal muscle and deteriorates muscle function. We previously identified non-myogenic mesenchymal progenitors that contribute to adipogenesis and fibrogenesis in mouse skeletal muscle. In this study, we report the identification and characterization of a human counterpart to these progenitors. By using PDGFRα as a specific marker, mesenchymal progenitors can be identified in the interstitium and isolated from human skeletal muscle. PDGFRα⁺ cells represent a cell population distinct from CD56⁺ myogenic cells, and adipogenic and fibrogenic potentials were highly enriched in the PDGFRα⁺ population. Activation of PDGFRα stimulates proliferation of PDGFRα⁺ cells through PI3K-Akt and MEK2-MAPK signaling pathways, and aberrant accumulation of PDGFRα⁺ cells was conspicuous in muscles of patients with both genetic and non-genetic muscle diseases. Our results revealed the pathological relevance of PDGFRα⁺ mesenchymal progenitors to human muscle diseases and provide a basis for developing therapeutic strategy to treat muscle diseases.     

Self-Organized Criticality Theory of Autoimmunity

Background

The cause of autoimmunity, which is unknown, is investigated from a different angle, i.e., the defect in immune ‘system’, to explain the cause of autoimmunity.

Methodology/Principal Findings

Repeated immunization with antigen causes systemic autoimmunity in mice otherwise not prone to spontaneous autoimmune diseases. Overstimulation of CD4⁺ T cells led to the development of autoantibody-inducing CD4⁺ T (aiCD4⁺ T) cell which had undergone T cell receptor (TCR) revision and was capable of inducing autoantibodies. The aiCD4⁺ T cell was induced by de novo TCR revision but not by cross-reaction, and subsequently overstimulated CD8⁺ T cells, driving them to become antigen-specific cytotoxic T lymphocytes (CTL). These CTLs could be further matured by antigen cross-presentation, after which they caused autoimmune tissue injury akin to systemic lupus erythematosus (SLE).

Conclusions/Significance

Systemic autoimmunity appears to be the inevitable consequence of over-stimulating the host''s immune ‘system’ by repeated immunization with antigen, to the levels that surpass system''s self-organized criticality.     

Unisexual and Heterosexual Meiotic Reproduction Generate Aneuploidy and Phenotypic Diversity De Novo in the Yeast Cryptococcus neoformans

Aneuploidy is known to be deleterious and underlies several common human diseases, including cancer and genetic disorders such as trisomy 21 in Down''s syndrome. In contrast, aneuploidy can also be advantageous and in fungi confers antifungal drug resistance and enables rapid adaptive evolution. We report here that sexual reproduction generates phenotypic and genotypic diversity in the human pathogenic yeast Cryptococcus neoformans, which is globally distributed and commonly infects individuals with compromised immunity, such as HIV/AIDS patients, causing life-threatening meningoencephalitis. C. neoformans has a defined a-α opposite sexual cycle; however, >99% of isolates are of the α mating type. Interestingly, α cells can undergo α-α unisexual reproduction, even involving genotypically identical cells. A central question is: Why would cells mate with themselves given that sex is costly and typically serves to admix preexisting genetic diversity from genetically divergent parents? In this study, we demonstrate that α-α unisexual reproduction frequently generates phenotypic diversity, and the majority of these variant progeny are aneuploid. Aneuploidy is responsible for the observed phenotypic changes, as chromosome loss restoring euploidy results in a wild-type phenotype. Other genetic changes, including diploidization, chromosome length polymorphisms, SNPs, and indels, were also generated. Phenotypic/genotypic changes were not observed following asexual mitotic reproduction. Aneuploidy was also detected in progeny from a-α opposite-sex congenic mating; thus, both homothallic and heterothallic sexual reproduction can generate phenotypic diversity de novo. Our study suggests that the ability to undergo unisexual reproduction may be an evolutionary strategy for eukaryotic microbial pathogens, enabling de novo genotypic and phenotypic plasticity and facilitating rapid adaptation to novel environments.     

Rare Copy Number Variants Are a Common Cause of Short Stature

Human growth has an estimated heritability of about 80%–90%. Nevertheless, the underlying cause of shortness of stature remains unknown in the majority of individuals. Genome-wide association studies (GWAS) showed that both common single nucleotide polymorphisms and copy number variants (CNVs) contribute to height variation under a polygenic model, although explaining only a small fraction of overall genetic variability in the general population. Under the hypothesis that severe forms of growth retardation might also be caused by major gene effects, we searched for rare CNVs in 200 families, 92 sporadic and 108 familial, with idiopathic short stature compared to 820 control individuals. Although similar in number, patients had overall significantly larger CNVs (p-value<1×10⁻⁷). In a gene-based analysis of all non-polymorphic CNVs>50 kb for gene function, tissue expression, and murine knock-out phenotypes, we identified 10 duplications and 10 deletions ranging in size from 109 kb to 14 Mb, of which 7 were de novo (p<0.03) and 13 inherited from the likewise affected parent but absent in controls. Patients with these likely disease causing 20 CNVs were smaller than the remaining group (p<0.01). Eleven (55%) of these CNVs either overlapped with known microaberration syndromes associated with short stature or contained GWAS loci for height. Haploinsufficiency (HI) score and further expression profiling suggested dosage sensitivity of major growth-related genes at these loci. Overall 10% of patients carried a disease-causing CNV indicating that, like in neurodevelopmental disorders, rare CNVs are a frequent cause of severe growth retardation.     

Blood cis-eQTL Analysis Fails to Identify Novel Association Signals among Sub-Threshold Candidates from Genome-Wide Association Studies in Restless Legs Syndrome

Restless legs syndrome (RLS) is a common neurologic disorder characterized by nightly dysesthesias affecting the legs primarily during periods of rest and relieved by movement. RLS is a complex genetic disease and susceptibility factors in six genomic regions have been identified by means of genome-wide association studies (GWAS). For some complex genetic traits, expression quantitative trait loci (eQTLs) are enriched among trait-associated single nucleotide polymorphisms (SNPs). With the aim of identifying new genetic susceptibility factors for RLS, we assessed the 332 best-associated SNPs from the genome-wide phase of the to date largest RLS GWAS for cis-eQTL effects in peripheral blood from individuals of European descent. In 740 individuals belonging to the KORA general population cohort, 52 cis-eQTLs with p_nominal<10⁻³ were identified, while in 976 individuals belonging to the SHIP-TREND general population study 53 cis-eQTLs with p_nominal<10⁻³ were present. 23 of these cis-eQTLs overlapped between the two cohorts. Subsequently, the twelve of the 23 cis-eQTL SNPs, which were not located at an already published RLS-associated locus, were tested for association in 2449 RLS cases and 1462 controls. The top SNP, located in the DET1 gene, was nominally significant (p<0.05) but did not withstand correction for multiple testing (p = 0.42). Although a similar approach has been used successfully with regard to other complex diseases, we were unable to identify new genetic susceptibility factor for RLS by adding this novel level of functional assessment to RLS GWAS data.     

Genome Wide Association Studies Using a New Nonparametric Model Reveal the Genetic Architecture of 17 Agronomic Traits in an Enlarged Maize Association Panel

Association mapping is a powerful approach for dissecting the genetic architecture of complex quantitative traits using high-density SNP markers in maize. Here, we expanded our association panel size from 368 to 513 inbred lines with 0.5 million high quality SNPs using a two-step data-imputation method which combines identity by descent (IBD) based projection and k-nearest neighbor (KNN) algorithm. Genome-wide association studies (GWAS) were carried out for 17 agronomic traits with a panel of 513 inbred lines applying both mixed linear model (MLM) and a new method, the Anderson-Darling (A-D) test. Ten loci for five traits were identified using the MLM method at the Bonferroni-corrected threshold −log₁₀ (P) >5.74 (α = 1). Many loci ranging from one to 34 loci (107 loci for plant height) were identified for 17 traits using the A-D test at the Bonferroni-corrected threshold −log₁₀ (P) >7.05 (α = 0.05) using 556809 SNPs. Many known loci and new candidate loci were only observed by the A-D test, a few of which were also detected in independent linkage analysis. This study indicates that combining IBD based projection and KNN algorithm is an efficient imputation method for inferring large missing genotype segments. In addition, we showed that the A-D test is a useful complement for GWAS analysis of complex quantitative traits. Especially for traits with abnormal phenotype distribution, controlled by moderate effect loci or rare variations, the A-D test balances false positives and statistical power. The candidate SNPs and associated genes also provide a rich resource for maize genetics and breeding.     

Prion Switching in Response to Environmental Stress

Evolution depends on the manner in which genetic variation is translated into new phenotypes. There has been much debate about whether organisms might have specific mechanisms for “evolvability,” which would generate heritable phenotypic variation with adaptive value and could act to enhance the rate of evolution. Capacitor systems, which allow the accumulation of cryptic genetic variation and release it under stressful conditions, might provide such a mechanism. In yeast, the prion [PSI⁺] exposes a large array of previously hidden genetic variation, and the phenotypes it thereby produces are advantageous roughly 25% of the time. The notion that [PSI⁺] is a mechanism for evolvability would be strengthened if the frequency of its appearance increased with stress. That is, a system that mediates even the haphazard appearance of new phenotypes, which have a reasonable chance of adaptive value would be beneficial if it were deployed at times when the organism is not well adapted to its environment. In an unbiased, high-throughput, genome-wide screen for factors that modify the frequency of [PSI⁺] induction, signal transducers and stress response genes were particularly prominent. Furthermore, prion induction increased by as much as 60-fold when cells were exposed to various stressful conditions, such as oxidative stress (H₂O₂) or high salt concentrations. The severity of stress and the frequency of [PSI⁺] induction were highly correlated. These findings support the hypothesis that [PSI⁺] is a mechanism to increase survival in fluctuating environments and might function as a capacitor to promote evolvability.     

How Genome-Wide SNP-SNP Interactions Relate to Nasopharyngeal Carcinoma Susceptibility

This study is the first to use genome-wide association study (GWAS) data to evaluate the multidimensional genetic architecture underlying nasopharyngeal cancer. Since analysis of data from GWAS confirms a close and consistent association between elevated risk for nasopharyngeal carcinoma (NPC) and major histocompatibility complex class 1 genes, our goal here was to explore lesser effects of gene-gene interactions. We conducted an exhaustive genome-wide analysis of GWAS data of NPC, revealing two-locus interactions occurring between single nucleotide polymorphisms (SNPs), and identified a number of suggestive interaction loci which were missed by traditional GWAS analyses. Although none of the interaction pairs we identified passed the genome-wide Bonferroni-adjusted threshold for significance, using independent GWAS data from the same population (Stage 2), we selected 66 SNP pairs in 39 clusters with P<0.01. We identified that in several chromosome regions, multiple suggestive interactions group to form a block-like signal, effectively reducing the rate of false discovery. The strongest cluster of interactions involved the CREB5 gene and a SNP rs1607979 on chromosome 17q22 (P = 9.86×10⁻¹¹) which also show trans-expression quantitative loci (eQTL) association in Chinese population. We then detected a complicated cis-interaction pattern around the NPC-associated HLA-B locus, which is immediately adjacent to copy-number variations implicated in male susceptibility for NPC. While it remains to be seen exactly how and to what degree SNP-SNP interactions such as these affect susceptibility for nasopharyngeal cancer, future research on these questions holds great promise for increasing our understanding of this disease’s genetic etiology, and possibly also that of other gene-related cancers.