SEEI: spherical evolution with feedback mechanism for identifying epistatic interactions.

BACKGROUND: Detecting epistatic interactions (EIs) involves the exploration of associations among single nucleotide polymorphisms (SNPs) and complex diseases, which is an important task in genome-wide association studies. The EI detection problem is dependent on epistasis models and corresponding optimization methods. Although various models and methods have been proposed to detect EIs, identifying EIs efficiently and accurately is still a challenge. RESULTS: Here, we propose a linear mixed statistical epistasis model (LMSE) and a spherical evolution approach with a feedback mechanism (named SEEI). The LMSE model expands the existing single epistasis models such as LR-Score, K2-Score, Mutual information, and Gini index. The SEEI includes an adaptive spherical search strategy and population updating strategy, which ensures that the algorithm is not easily trapped in local optima. We analyzed the performances of 8 random disease models, 12 disease models with marginal effects, 30 disease models without marginal effects, and 10 high-order disease models. The 60 simulated disease models and a real breast cancer dataset were used to evaluate eight algorithms (SEEI, EACO, EpiACO, FDHEIW, MP-HS-DHSI, NHSA-DHSC, SNPHarvester, CSE). Three evaluation criteria (pow1, pow2, pow3), a T-test, and a Friedman test were used to compare the performances of these algorithms. The results show that the SEEI algorithm (order 1, averages ranks = 13.125) outperformed the other algorithms in detecting EIs. CONCLUSIONS: Here, we propose an LMSE model and an evolutionary computing method (SEEI) to solve the optimization problem of the LMSE model. The proposed method performed better than the other seven algorithms tested in its ability to identify EIs in genome-wide association datasets. We identified new SNP-SNP combinations in the real breast cancer dataset and verified the results. Our findings provide new insights for the diagnosis and treatment of breast cancer. AVAILABILITY AND IMPLEMENTATION: https://github.com/scutdy/SSO/blob/master/SEEI.zip .

Genome instability drives epistatic adaptation in the human pathogen Leishmania.

How genome instability is harnessed for fitness gain despite its potential deleterious effects is largely elusive. An ideal system to address this important open question is provided by the protozoan pathogen Leishmania, which exploits frequent variations in chromosome and gene copy number to regulate expression levels. Using ecological genomics and experimental evolution approaches, we provide evidence that Leishmania adaptation relies on epistatic interactions between functionally associated gene copy number variations in pathways driving fitness gain in a given environment. We further uncover posttranscriptional regulation as a key mechanism that compensates for deleterious gene dosage effects and provides phenotypic robustness to genetically heterogenous parasite populations. Finally, we correlate dynamic variations in small nucleolar RNA (snoRNA) gene dosage with changes in ribosomal RNA 2'-O-methylation and pseudouridylation, suggesting translational control as an additional layer of parasite adaptation. Leishmania genome instability is thus harnessed for fitness gain by genome-dependent variations in gene expression and genome-independent compensatory mechanisms. This allows for polyclonal adaptation and maintenance of genetic heterogeneity despite strong selective pressure. The epistatic adaptation described here needs to be considered in Leishmania epidemiology and biomarker discovery and may be relevant to other fast-evolving eukaryotic cells that exploit genome instability for adaptation, such as fungal pathogens or cancer.

Mapping of QTLs and meta-QTLs for Heterodera avenae Woll. resistance in common wheat (Triticum aestivum L.).

BACKGROUND: In hexaploid wheat, quantitative trait loci (QTL) and meta-QTL (MQTL) analyses were conducted to identify genomic regions controlling resistance to cereal cyst nematode (CCN), Heterodera avenae. A mapping population comprising 149 RILs derived from the cross HUW 468 × C 306 was used for composite interval mapping (CIM) and inclusive composite interval mapping (ICIM). RESULTS: Eight main effect QTLs on three chromosomes (1B, 2A and 3A) were identified using two repeat experiments. One of these QTLs was co-localized with a previously reported wheat gene Cre5 for resistance to CCN. Seven important digenic epistatic interactions (PVE = 5% or more) were also identified, each involving one main effect QTL and another novel E-QTL. Using QTLs earlier reported in literature, two meta-QTLs were also identified, which were also used for identification of 57 candidate genes (CGs). Out of these, 29 CGs have high expression in roots and encoded the following proteins having a role in resistance to plant parasitic nematodes (PPNs): (i) NB-ARC,P-loop containing NTP hydrolase, (ii) Protein Kinase, (iii) serine-threonine/tyrosine-PK, (iv) protein with leucine-rich repeat, (v) virus X resistance protein-like, (vi) zinc finger protein, (vii) RING/FYVE/PHD-type, (viii) glycosyl transferase, family 8 (GT8), (ix) rubisco protein with small subunit domain, (x) protein with SANT/Myb domain and (xi) a protein with a homeobox. CONCLUSION: Identification and selection of resistance loci with additive and epistatic effect along with two MQTL and associated CGs, identified in the present study may prove useful for understanding the molecular basis of resistance against H. avenae in wheat and for marker-assisted selection (MAS) for breeding CCN resistant wheat cultivars.

Development and marker-trait relationships of functional markers for glutamine synthetase GS1 and GS2 homoeogenes in bread wheat.

GS1 and GS2 genes encode, respectively, the main cytosolic and the plastidic isoforms of glutamine synthetase (GS). In the present study, the wheat GS1 and GS2 homoeogenes located in the A, B and D genome chromosomes have been sequenced in a group of 15 bread wheat varieties including landraces, old commercial varieties and modern cultivars. Phenotypic characterization by multi-environment field trials detected significant effects of specific GS homoeogenes on three of the seven agronomic and grain quality traits analyzed. Based on the gene sequence polymorphisms found, biallelic molecular markers that could facilitate marker-assisted breeding were developed for genes GS1A, GS2A and GS2D. The remaining genes encoding main wheat GS were excluded because of being monomorphic (GS1D) or too polymorphic (GS1B and GS2B) in the sequencing panel varieties. A collection of 187 Spanish bread wheat landraces was genotyped for these gene-based molecular markers. Data analyses conducted with phenotypic records reported for this germplasm collection in López-Fernández et al. (Plants-Basel 10: 620, 2021) have revealed the beneficial influence of some individual alleles on thousand-kernel weight (TKW), kernels per spike (KS) and grain protein content. Furthermore, genetic interactions between GS1A, a cytosolic GS isoform coding gene, and GS2A or GS2D, plastidic GS enzyme coding genes, were found to affect TKW and KS. The finding that some alleles at one locus may mask the effect of positive alleles at hypostatic GS loci should be kept in mind if gene pyramiding strategies are attempted for the improvement of N-use efficiency-related traits. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-022-01354-0.

Genome-Wide Association Study Reveals Candidate Genes for Root-Related Traits in Rice.

Root architecture is a determinant factor of drought resistance in rice and plays essential roles in the absorption of water and nutrients for the survival of rice plants. Dissection of the genetic basis for root structure can help to improve stress-resistance and grain yield in rice breeding. In this study, a total of 391 rice (Oryz asativa L.) accessions were used to perform a genome-wide association study (GWAS) on three root-related traits in rice, including main root length (MRL), average root length (ARL), and total root number (TRN). As a result, 13 quantitative trait loci (QTLs) (qMRL1.1, qMRL1.2, qMRL3.1, qMRL3.2, qMRL3.3, qMRL4.1, qMRL7.1, qMRL8.1, qARL1.1, qARL9.1, qTRN9.1, qTRN9.2, and qTRN11.1) significantly associated with the three traits were identified, among which three (qMRL3.2, qMRL4.1 and qMRL8.1) were overlapped with OsGNOM1, OsARF12 and qRL8.1, respectively, and ten were novel QTLs. Moreover, we also detected epistatic interactions affecting root-related traits and identified 19 related genetic interactions. These results lay a foundation for cloning the corresponding genes for rice root structure, as well as provide important genomic resources for breeding high yield rice varieties.

GEP-EpiSeeker: a gene expression programming-based method for epistatic interaction detection in genome-wide association studies.

BACKGROUND: Identification of epistatic interactions provides a systematic way for exploring associations among different single nucleotide polymorphism (SNP) and complex diseases. Although considerable progress has been made in epistasis detection, efficiently and accurately identifying epistatic interactions remains a challenge due to the intensive growth of measuring SNP combinations. RESULTS: In this work, we formulate the detection of epistatic interactions by a combinational optimization problem, and propose a novel evolutionary-based framework, called GEP-EpiSeeker, to detect epistatic interactions using Gene Expression Programming. In GEP-EpiSeeker, we propose several tailor-made chromosome rules to describe SNP combinations, and incorporate Bayesian network-based fitness evaluation into the evolution of tailor-made chromosomes to find suspected SNP combinations, and adopt the Chi-square test to identify optimal solutions from suspected SNP combinations. Moreover, to improve the convergence and accuracy of the algorithm, we design two genetic operators with multiple and adjacent mutations and an adaptive genetic manipulation method with fuzzy control to efficiently manipulate the evolution of tailor-made chromosomes. We compared GEP-EpiSeeker with state-of-the-art methods including BEAM, BOOST, AntEpiSeeker, MACOED, and EACO in terms of power, recall, precision and F1-score on the GWAS datasets of 12 DME disease models and 10 DNME disease models. Our experimental results show that GEP-EpiSeeker outperforms comparative methods. CONCLUSIONS: Here we presented a novel method named GEP-EpiSeeker, based on the Gene Expression Programming algorithm, to identify epistatic interactions in Genome-wide Association Studies. The results indicate that GEP-EpiSeeker could be a promising alternative to the existing methods in epistasis detection and will provide a new way for accurately identifying epistasis.

Gene-Gene Interactions Dictate Ciprofloxacin Resistance in Pseudomonas aeruginosa and Facilitate Prediction of Resistance Phenotype from Genome Sequence Data.

Ciprofloxacin is one of the most widely used antibiotics for treating Pseudomonas aeruginosa infections. However, P. aeruginosa acquires mutations that confer ciprofloxacin resistance, making treatment more difficult. Resistance is multifactorial, with mutations in multiple genes influencing the resistance phenotype. However, the contributions of individual mutations and mutation combinations to the amounts of ciprofloxacin that P. aeruginosa can tolerate are not well understood. Engineering P. aeruginosa strain PAO1 to contain mutations in any one of the resistance-associated genes gyrA, nfxB, rnfC, parC, and parE showed that only gyrA mutations increased the MIC for ciprofloxacin. Mutations in parC and parE increased the MIC of a gyrA mutant, making the bacteria ciprofloxacin resistant. Mutations in nfxB and rnfC increased the MIC, conferring resistance, only if both were mutated in a gyrA background. Mutations in all of gyrA, nfxB, rnfC, and parC/E further increased the MIC. These findings reveal an epistatic network of gene-gene interactions in ciprofloxacin resistance. We used this information to predict ciprofloxacin resistance/susceptibility for 274 isolates of P. aeruginosa from their genome sequences. Antibiotic susceptibility profiles were predicted correctly for 84% of the isolates. The majority of isolates for which prediction was unsuccessful were ciprofloxacin resistant, demonstrating the involvement of additional as yet unidentified genes and mutations in resistance. Our data show that gene-gene interactions can play an important role in antibiotic resistance and can be successfully incorporated into models predicting resistance phenotype.

Genome-wide association coupled gene to gene interaction studies unveil novel epistatic targets among major effect loci impacting rice grain chalkiness.

Rice varieties whose quality is graded as excellent have a lower percent grain chalkiness (PGC) of two per cent and below with higher whole grain yields upon milling, leading to higher economic returns for farmers. We have conducted a genome-wide association study (GWAS) using a combined population panel of indica and japonica rice varieties, and identified a total of 746 single nucleotide polymorphisms (SNPs) that were strongly associated with the chalk phenotype, covered 78 Quantitative Trait Loci (QTL) regions. Among them, 21 were high-value QTLs, as they explained at least 10 % of the phenotypic variance for PGC. A combined epistasis and GWAS was applied to dissect the genetics of the complex chalkiness trait, and its regulatory cascades were validated using gene regulatory networks. Promising novel epistatic interactions were found between the loci of chromosomes 6 (PGC6.1) and 7 (PGC7.8) that contributed to lower PGC. Based on haplotype mining only a few modern rice varieties confounded with a lower chalkiness, and they possess several PGC QTLs. The importance of PGC6.1 was validated through multi-parent advanced generation intercrosses and several low-chalk lines possessing superior haplotypes were identified. The results of this investigation have deciphered the underlying genetic networks that can reduce PGC to 2%, and will thus support future breeding programs to improve the grain quality of elite genetic material with high-yielding potentials.

Phenotypic expression of floral traits in hybrid zones provides insights into their genetic architecture.

Information on the genetic architecture of phenotypic traits is helpful for constructing and testing models of the ecoevolutionary dynamics of natural populations. For plant groups with long life cycles there is a lack of line cross experiments that can unravel the genetic architecture of loci underlying quantitative traits. To fill this gap, we propose the use of variation for phenotypic traits expressed in natural hybrid zones as an alternative approach. We used data from orchid hybrid zones and compared expected and observed patterns of phenotypic trait expression in different early-generation hybrid classes identified by molecular genetic markers. We found evidence of additivity, dominance, and epistatic interactions for different phenotypic traits. We discuss the potential of this approach along with its limitations and suggest that it may represent a realistic way to gain an initial insight into the heritability and genomic architecture of traits in organismal groups with complex life history, such as orchids and many others.

High-Resolution Mapping in Two RIL Populations Refines Major "QTL Hotspot" Regions for Seed Size and Shape in Soybean (Glycine max L.).

Seed size and shape are important traits determining yield and quality in soybean. However, the genetic mechanism and genes underlying these traits remain largely unexplored. In this regard, this study used two related recombinant inbred line (RIL) populations (ZY and K3N) evaluated in multiple environments to identify main and epistatic-effect quantitative trait loci (QTLs) for six seed size and shape traits in soybean. A total of 88 and 48 QTLs were detected through composite interval mapping (CIM) and mixed-model-based composite interval mapping (MCIM), respectively, and 15 QTLs were common among both methods; two of them were major (R2 > 10%) and novel QTLs (viz., qSW-1-1ZN and qSLT-20-1K3N). Additionally, 51 and 27 QTLs were identified for the first time through CIM and MCIM methods, respectively. Colocalization of QTLs occurred in four major QTL hotspots/clusters, viz., "QTL Hotspot A", "QTL Hotspot B", "QTL Hotspot C", and "QTL Hotspot D" located on Chr06, Chr10, Chr13, and Chr20, respectively. Based on gene annotation, gene ontology (GO) enrichment, and RNA-Seq analysis, 23 genes within four "QTL Hotspots" were predicted as possible candidates, regulating soybean seed size and shape. Network analyses demonstrated that 15 QTLs showed significant additive x environment (AE) effects, and 16 pairs of QTLs showing epistatic effects were also detected. However, except three epistatic QTLs, viz., qSL-13-3ZY, qSL-13-4ZY, and qSW-13-4ZY, all the remaining QTLs depicted no main effects. Hence, the present study is a detailed and comprehensive investigation uncovering the genetic basis of seed size and shape in soybeans. The use of a high-density map identified new genomic regions providing valuable information and could be the primary target for further fine mapping, candidate gene identification, and marker-assisted breeding (MAB).

mtProtEvol: the resource presenting molecular evolution analysis of proteins involved in the function of Vertebrate mitochondria.

BACKGROUND: Heterotachy is the variation in the evolutionary rate of aligned sites in different parts of the phylogenetic tree. It occurs mainly due to epistatic interactions among the substitutions, which are highly complex and make it difficult to study protein evolution. The vast majority of computational evolutionary approaches for studying these epistatic interactions or their evolutionary consequences in proteins require high computational time. However, recently, it has been shown that the evolution of residue solvent accessibility (RSA) is tightly linked with changes in protein fitness and intra-protein epistatic interactions. This provides a computationally fast alternative, based on comparison of evolutionary rates of amino acid replacements with the rates of RSA evolutionary changes in order to recognize any shifts in epistatic interaction. RESULTS: Based on RSA information, data randomization and phylogenetic approaches, we constructed a software pipeline, which can be used to analyze the evolutionary consequences of intra-protein epistatic interactions with relatively low computational time. We analyzed the evolution of 512 protein families tightly linked to mitochondrial function in Vertebrates and created "mtProtEvol", the web resource with data on protein evolution. In strict agreement with lifespan and metabolic rate data, we demonstrated that different functional categories of mitochondria-related proteins subjected to selection on accelerated and decelerated RSA rates in rodents and primates. For example, accelerated RSA evolution in rodents has been shown for Krebs cycle enzymes, respiratory chain and reactive oxygen species metabolism, while in primates these functions are stress-response, translation and mtDNA integrity. Decelerated RSA evolution in rodents has been demonstrated for translational machinery and oxidative stress response components. CONCLUSIONS: mtProtEvol is an interactive resource focused on evolutionary analysis of epistatic interactions in protein families involved in Vertebrata mitochondria function and available at http://bioinfodbs.kantiana.ru/mtProtEvol /. This resource and the devised software pipeline may be useful tool for researchers in area of protein evolution.

Genetic factors affecting Fusarium head blight resistance improvement from introgression of exotic Sumai 3 alleles (including Fhb1, Fhb2, and Fhb5) in hard red spring wheat.

BACKGROUND: Fusarium head blight resistance genes, Fhb1 (for Type-II resistance), Fhb2 (Type-II), and Fhb5 (Type-I plus some Type-II), which originate from Sumai 3, are among the most important that confer resistance in hexaploid wheat. Near-isogenic lines (NILs), in the CDC Alsask (susceptible; n = 32) and CDC Go (moderately susceptible; n = 38) backgrounds, carrying these genes in all possible combinations were developed using flanking microsatellite markers and evaluated for their response to FHB and deoxynivalenol (DON) accumulation in eight environments. NILs were haplotyped with wheat 90 K iSelect assay to elucidate the genomic composition and confirm alleles' presence. Other than evaluating the effects of three major genes in common genetic background, the study elucidated the epistatic gene interactions as they influence FHB measurements; identified loci other than Fhb1, Fhb2, and Fhb5, in both recurrent and donor parents and examined annotated proteins in gene intervals. RESULTS: Genotyping using 81,857 single nucleotide polymorphism (SNP) markers revealed polymorphism on all chromosomes and that the NILs carried < 3% of alleles from the resistant donor. Significant improvement in field resistance (Type-I + Type-II) resulted only among the CDC Alsask NILs, not the CDC Go NILs. The phenotypic response of NILs carrying combinations of Sumai 3 derived genes suggested non-additive responses and Fhb5 was as good as Fhb1 in conferring field resistance in both populations. In addition to Fhb1, Fhb2, and Fhb5, four to five resistance improving alleles in both populations were identified and three of five in CDC Go were contributed by the susceptible parent. The introgressed chromosome regions carried genes encoding disease resistance proteins, protein kinases, nucleotide-binding and leucine rich repeats' domains. Complex epistatic gene-gene interactions among marker loci (including Fhb1, Fhb2, Fhb5) explained > 20% of the phenotypic variation in FHB measurements. CONCLUSIONS: Immediate Sumai 3 derivatives carry a number of resistance improving minor effect alleles, other than Fhb1, Fhb2, Fhb5. Results verified that marker-assisted selection is possible for the introgression of exotic FHB resistance genes, however, the genetic background of the recipient line and epistatic interactions can have a strong influence on expression and penetrance of any given gene.

Mitochondria, sex and variation in routine metabolic rate.

Variation in the metabolic costs associated with organismal maintenance may play a key role in determining fitness, and thus these differences among individuals are likely to be subject to natural selection. Although the evolvability of maintenance metabolism depends on its underlying genetic architecture, relatively little is known about the nature of genetic variation that underlies this trait. To address this, we measured variation in routine metabolic rate (MO2routine ), an index of maintenance metabolism, within and among three populations of Atlantic killifish, Fundulus heteroclitus, including a population from a region of genetic admixture between two subspecies. Polygenic association tests among individuals from the admixed population identified 54 single nucleotide polymorphisms (SNPs) that were associated with MO2routine , and these SNPs accounted for 43% of interindividual variation in this trait. However, genetic associations with MO2routine involved different SNPs if females and males were analysed separately, and there was a sex-dependent effect of mitochondrial genotype on variation in routine metabolism. These results imply that there are sex-specific genetic mechanisms, and potential mitonuclear interactions, that underlie variation in MO2routine . Additionally, there was evidence for epistatic interactions between 17% of the possible pairs of trait-associated SNPs, suggesting that epistatic effects on MO2routine are common. These data demonstrate not only that phenotypic variation in this ecologically important trait has a polygenic basis with considerable epistasis among loci, but also that these underlying genetic mechanisms, and particularly the role of mitochondrial genotype, may be sex-specific.

Heterozygous CTNNB1 and TBX4 variants in a patient with abnormal lung growth, pulmonary hypertension, microcephaly, and spasticity.

The canonical wingless (Wnt) and fibroblast growth factor (FGF) signaling pathways involving CTNNB1 and TBX4, respectively, are crucial for the regulation of human development. Perturbations of these pathways and disruptions from biological homeostasis have been associated with abnormal morphogenesis of multiple organs, including the lung. The aim of this study was to identify the underlying genetic cause of abnormal lung growth, pulmonary hypertension (PAH), severe microcephaly, and muscle spasticity in a full-term newborn, who died at 4 months of age due to progressively worsening PAH and respiratory failure. Family trio exome sequencing showed a de novo heterozygous nonsense c.1603C>T (p.Arg535*) variant in CTNNB1 and a paternally inherited heterozygous missense c.1198G>A (p.Glu400Lys) variant in TBX4, both predicted to be likely deleterious. We expand the phenotypic spectrum associated with CTNNB1 and TBX4 variants and indicate that they could act synergistically to produce a distinct more severe phenotype. Our findings further support a recently proposed complex compound inheritance model in lethal lung developmental diseases and the contention that dual molecular diagnoses can parsimoniously explain blended phenotypes.

ENHO, RXRA, and LXRA polymorphisms and dyslipidaemia, related comorbidities and survival in haemodialysis patients.

BACKGROUND: The energy homeostasis-associated gene (ENHO), retinoid X receptor alpha gene (RXRA), and liver X receptor alpha gene (LXRA) are involved in adipogenic/lipogenic regulation. We investigated whether single-nucleotide polymorphisms in these genes (ENHO rs2281997, rs72735260; RXRA rs749759, rs10776909, rs10881578; LXRA rs2279238, rs7120118, rs11039155) are associated with dyslipidaemia, related comorbidities and survival of haemodialysis (HD) patients also tested for T-helper (Th) cell interleukin genes (IL). METHODS: The study was carried out in 873 HD patients. Dyslipidaemia was diagnosed by the recommendations of the Kidney Disease Outcomes Quality Initiative (K/DOQI) guidelines (2003); atherogenic dyslipidaemia was referred to if the TG/HDL cholesterol ratio was equal to or higher than 3.8. Genotyping of ENHO SNPs, LXRA SNPs, and IL12A rs568408 was carried out using HRM analysis. RXRA SNPs, IL12B rs3212227, and IL18 rs360719 were genotyped using PCR-RFLP analysis. The circulating adropin concentration was determined in 126 patients by enzyme-linked immunosorbent assay. Survival probability was analysed using the Kaplan-Meier method in 440 patients followed through 7.5 years. RESULTS: Dyslipidaemia by K/DOQI was diagnosed in 459 patients (91% revealed hyper-LDL- cholesterolaemia), atherogenic dyslipidaemia was diagnosed in 454 patients, and 231 patients were free of dyslipidaemia by both criteria. The variant allele (T) of ENHO rs2281997 was associated with the hyper-LDL cholesterolaemic pattern of dyslipidaemia by K/DOQI. The frequency of atherogenic dyslipidaemia was lower in T-allele bearers than in CC-genotype patients. The rs2281997 T allele was associated with lower cardiovascular mortality in HD patients showing atherogenic dyslipidaemia. ENHO, RXRA, and LXRA showed epistatic interactions in dyslipidaemia. Circulating adropin was lower in atherogenic dyslipidaemia than in non-atherogenic conditions. RXRA rs10776909 was associated with myocardial infarction. Bearers of LXRA rs2279238, rs7120118 or rs11039155 minor alleles showed higher mortality. ENHO SNP positions fell within the same DNase 1 hypersensitivity site expressed in the Th1 cell line. Epistatic interactions occurred between rs2281997 and Th1 IL SNPs (rs360719, rs568408). CONCLUSIONS: Atherogenic dyslipidaemia occurs in HD patients in whom ENHO encodes less adropin. ENHO, RXRA, and LXRA SNPs, separately or jointly, are associated with dyslipidaemia, myocardial infarction, and survival in HD patients. Differences in the availability of transcription binding sites may contribute to these associations.

Genetic Variations of Oxidative Stress Related Genes ALOX5, ALOX5AP and MPO Modulate Ischemic Stroke Susceptibility Through Main Effects and Epistatic Interactions in a Chinese Population.

BACKGROUND/AIMS: To investigate the roles of the oxidative stress related-genes ALOX5, ALOX5AP and MPO in ischemic stroke susceptibility in the Han Chinese population. METHODS: A total of 351 ischemic stroke patients and 417 controls were recruited. The ALOX5 rs10900213, ALOX5AP rs4293222 and MPO rs2107545 gene polymorphisms were genotyped. RESULTS: We identified that rs2107545 of MPO gene was significantly associated with ischemic stroke susceptibility after adjusting for covariates. Furthermore, we also considered the likely complexity of oxidative stress and inflammatory process in stroke by assessing the combined effects of multiple genes. Generalized multifactor dimensionality reduction (GMDR) analysis revealed that the combination of ALOX5 rs10900213, ALOX5AP rs4293222 and MPO rs2107545 was significantly associated with increased risk of ischemic stroke (P=0.0040, OR (95% CI) =1.991 (1.241 to 3.195)). Additionally, the MPO rs2107545 genotype was significantly associated with clinical outcomes at 6 months after discharge from the hospital. CONCLUSION: Our study revealed that epistatic interaction among the ALOX5, ALOX5AP and MPO genes played a significant role in vulnerability to ischemic stroke. Furthermore, these results also suggest that the rs2107545 of MPO gene can be used as a biomarker for the susceptibility and prognosis of ischemic stroke patients.

CINOEDV: a co-information based method for detecting and visualizing n-order epistatic interactions.

BACKGROUND: Detecting and visualizing nonlinear interaction effects of single nucleotide polymorphisms (SNPs) or epistatic interactions are important topics in bioinformatics since they play an important role in unraveling the mystery of "missing heritability". However, related studies are almost limited to pairwise epistatic interactions due to their methodological and computational challenges. RESULTS: We develop CINOEDV (Co-Information based N-Order Epistasis Detector and Visualizer) for the detection and visualization of epistatic interactions of their orders from 1 to n (n ≥ 2). CINOEDV is composed of two stages, namely, detecting stage and visualizing stage. In detecting stage, co-information based measures are employed to quantify association effects of n-order SNP combinations to the phenotype, and two types of search strategies are introduced to identify n-order epistatic interactions: an exhaustive search and a particle swarm optimization based search. In visualizing stage, all detected n-order epistatic interactions are used to construct a hypergraph, where a real vertex represents the main effect of a SNP and a virtual vertex denotes the interaction effect of an n-order epistatic interaction. By deeply analyzing the constructed hypergraph, some hidden clues for better understanding the underlying genetic architecture of complex diseases could be revealed. CONCLUSIONS: Experiments of CINOEDV and its comparison with existing state-of-the-art methods are performed on both simulation data sets and a real data set of age-related macular degeneration. Results demonstrate that CINOEDV is promising in detecting and visualizing n-order epistatic interactions. CINOEDV is implemented in R and is freely available from R CRAN: http://cran.r-project.org and https://sourceforge.net/projects/cinoedv/files/ .

Nonadaptive Amino Acid Convergence Rates Decrease over Time.

Convergence is a central concept in evolutionary studies because it provides strong evidence for adaptation. It also provides information about the nature of the fitness landscape and the repeatability of evolution, and can mislead phylogenetic inference. To understand the role of adaptive convergence, we need to understand the patterns of nonadaptive convergence. Here, we consider the relationship between nonadaptive convergence and divergence in mitochondrial and model proteins. Surprisingly, nonadaptive convergence is much more common than expected in closely related organisms, falling off as organisms diverge. The extent of the convergent drop-off in mitochondrial proteins is well predicted by epistatic or coevolutionary effects in our "evolutionary Stokes shift" models and poorly predicted by conventional evolutionary models. Convergence probabilities decrease dramatically if the ancestral amino acids of branches being compared have diverged, but also drop slowly over evolutionary time even if the ancestral amino acids have not substituted. Convergence probabilities drop-off rapidly for quickly evolving sites, but much more slowly for slowly evolving sites. Furthermore, once sites have diverged their convergence probabilities are extremely low and indistinguishable from convergence levels at randomized sites. These results indicate that we cannot assume that excessive convergence early on is necessarily adaptive. This new understanding should help us to better discriminate adaptive from nonadaptive convergence and develop more relevant evolutionary models with improved validity for phylogenetic inference.

Natural variation involving deletion alleles of FRIGIDA modulate temperature-sensitive flowering responses in Arabidopsis thaliana.

Ambient temperature is one of the major environmental factors that modulate plant growth and development. There is extensive natural genetic variation in thermal responses of plants exemplified by the variation exhibited by the accessions of Arabidopsis thaliana. In this work we have studied the enhanced temperature response in hypocotyl elongation and flowering shown by the Tsu-0 accession in long days. Genetic mapping in the Col-0 × Tsu-0 recombinant inbred line (RIL) population identified several QTLs for thermal response including three major effect loci encompassing candidate genes FRIGIDA (FRI), FLOWERING LOCUS C (FLC) and FLOWERING LOCUS T (FT). We confirm and validate these QTLs. We show that the Tsu-0 FRI allele, which is the same as FRI-Ler is associated with late flowering but only at lower temperatures in long days. Using transgenic lines and accessions, we show that the FRI-Ler allele confers temperature-sensitive late flowering confirming a role for FRI in photoperiod-dependent thermal response. Through quantitative complementation with heterogeneous inbred families, we further show that cis-regulatory variation at FT contributes to the observed hypersensitivity of Tsu-0 to ambient temperature. Overall our results suggest that multiple loci that interact epistatically govern photoperiod-dependent thermal responses of A. thaliana.

Association genetics and transcriptome analysis reveal a gibberellin-responsive pathway involved in regulating photosynthesis.

Gibberellins (GAs) regulate a wide range of important processes in plant growth and development, including photosynthesis. However, the mechanism by which GAs regulate photosynthesis remains to be understood. Here, we used multi-gene association to investigate the effect of genes in the GA-responsive pathway, as constructed by RNA sequencing, on photosynthesis, growth, and wood property traits, in a population of 435 Populus tomentosa By analyzing changes in the transcriptome following GA treatment, we identified many key photosynthetic genes, in agreement with the observed increase in measurements of photosynthesis. Regulatory motif enrichment analysis revealed that 37 differentially expressed genes related to photosynthesis shared two essential GA-related cis-regulatory elements, the GA response element and the pyrimidine box. Thus, we constructed a GA-responsive pathway consisting of 47 genes involved in regulating photosynthesis, including GID1, RGA, GID2, MYBGa, and 37 photosynthetic differentially expressed genes. Single nucleotide polymorphism (SNP)-based association analysis showed that 142 SNPs, representing 40 candidate genes in this pathway, were significantly associated with photosynthesis, growth, and wood property traits. Epistasis analysis uncovered interactions between 310 SNP-SNP pairs from 37 genes in this pathway, revealing possible genetic interactions. Moreover, a structural gene-gene matrix based on a time-course of transcript abundances provided a better understanding of the multi-gene pathway affecting photosynthesis. The results imply a functional role for these genes in mediating photosynthesis, growth, and wood properties, demonstrating the potential of combining transcriptome-based regulatory pathway construction and genetic association approaches to detect the complex genetic networks underlying quantitative traits.