Towards genomic selection in apple (Malus ×domestica Borkh.) breeding programmes: Prospects, challenges and strategies

The apple genome sequence and the availability of high-throughput genotyping technologies have initiated a new era where SNP markers are abundant across the whole genome. Genomic selection (GS) is a statistical approach that utilizes all available genome-wide markers simultaneously to estimate breeding values or total genetic values. For breeding programmes, GS is a promising alternative to the traditional marker-assisted selection for manipulating complex polygenic traits often controlled by many small-effect genes. Various factors, such as genetic architecture of selection traits, population size and structure, genetic evaluation systems, density of SNP markers and extent of linkage disequilibrium, have been shown to be the key drivers of the accuracy of GS. In this paper, we provide an overview of the status of these aspects in current apple-breeding programmes. Strategies for GS for fruit quality and disease resistance are discussed, and an update on an empirical genomic selection study in a New Zealand apple-breeding programme is provided, along with a foresight of expected accuracy from such selection.     

Association of genetic variants rs641153 (CFB), rs2230199 (C3), and rs1410996 (CFH) with age-related macular degeneration in a Brazilian population

This study aimed to investigate the association among genetic variants of the complement pathway CFB R32Q (rs641153), C3 R102G (rs2230199), and CFH (rs1410996) with age-related macular degeneration (AMD) in a sample of the Brazilian population. In a case-control study, 484 AMD patients were classified according to the clinical age-related maculopathy grading system (CARMS) and compared to 479 unrelated controls. The genetic variants rs1410996 of complement H (CFH), rs641153 of complement factor B (CFB), and rs2230199 of complement 3 (C3) were evaluated through polymerase chain reaction (PCR) and direct sequencing. The associations between single nucleotide polymorphisms (SNPs) and AMD, adjusted by age, were assessed by using logistic regression models. A statistically significant association was observed between AMD risk and rs2230199 variant with an OR of 2.01 (P  = 0.0002) for CG individuals compared to CC individuals. Regarding the comparison of advanced AMD versus the control group, the OR was 2.12 (P = 0.0036) for GG versus AA genotypes for rs1410996 variant. Similarly, the OR for rs2230199 polymorphism was 2.3034 (P  = 5.47^e-05) when comparing CG individuals to CC carriers. In contrast, the rs641153 variant showed a significant protective effect against advanced AMD for GA versus GG genotype (OR = 0.4406; P  = 0.0019). When comparing wet AMD versus controls, a significant association was detected for rs1410996 variant (OR = 2.16; P  = 0.0039) comparing carriers of the homozygous GG versus AA genotype, as well as in the comparisons of GG (OR = 3.0713; P  = 0.0046) and CG genotypes (OR = 2.2249; P  = 0.0002) versus CC genotype for rs2230199 variant, respectively. The rs641153 variant granted a significant protective effect against wet AMD for GA versus GG genotypes (OR = 0.4601; P  = 0.0044). Our study confirmed the risk association between rs2230199 and rs1410996 variants and AMD, and the protective role against AMD for rs641153 variant.     

Comparison of marker-based pairwise relatedness estimators on a pedigreed plant population

Several estimators have been proposed that use molecular marker data to infer the degree of relatedness for pairs of individuals. The objective of this study was to evaluate the performance of seven estimators when applied to marker data of a set of 33 key individuals from a large complex apple pedigree. The evaluation considered different scenarios of allele frequencies and different numbers of marker loci. The method of moments estimators were Similarity, Queller-Goodknight, Lynch-Ritland and Wang. The maximum likelihood estimators were Thompson, Anderson-Weir and Jacquard. The pedigree-based coancestry coefficients were taken as the point of reference in calculating correlations and root mean square error (RMSE). The marker data comprised 86 multi-allelic SSR markers on 17 linkage groups, covering 11 Morgans. Additionally, we simulated 10 datasets conditional on the real pedigree to support the results on the real dataset. None of the estimators outperformed the others. Knowledge of allele frequencies appeared to be the most influential, i.e., the highest correlations and lowest RMSE were found when frequencies from the founder population were available. When equal allele frequencies were used, all estimators resulted in very similar, but on average lower, correlations. The use of allele frequencies estimated from the set of 33 individuals gave, on average, the poorest results. The maximum likelihood estimators and the Lynch-Ritland estimator were the most sensitive to allele frequencies. The results from the simulation study fully supported the trends in results of the real dataset. This study indicated that high correlations (up to 0.90) and small RMSE (below 0.03), may be obtained when population allelic frequencies are available. In this scenario, the performances of the various estimators were similar, but seemed to favor the maximum likelihood estimators. In the absence of reliable allele frequencies the method of moments estimators were shown to be more robust. The number of marker loci influenced the average performance of the estimators; however, the ranking was not affected. Correlations up to 0.80 were obtained when two markers per chromosome and appropriate allele frequencies were available. Adding more markers to the current dataset may lead to marginal improvements.     

Bayesian Markov Random Field Analysis for Protein Function Prediction Based on Network Data

Inference of protein functions is one of the most important aims of modern biology. To fully exploit the large volumes of genomic data typically produced in modern-day genomic experiments, automated computational methods for protein function prediction are urgently needed. Established methods use sequence or structure similarity to infer functions but those types of data do not suffice to determine the biological context in which proteins act. Current high-throughput biological experiments produce large amounts of data on the interactions between proteins. Such data can be used to infer interaction networks and to predict the biological process that the protein is involved in. Here, we develop a probabilistic approach for protein function prediction using network data, such as protein-protein interaction measurements. We take a Bayesian approach to an existing Markov Random Field method by performing simultaneous estimation of the model parameters and prediction of protein functions. We use an adaptive Markov Chain Monte Carlo algorithm that leads to more accurate parameter estimates and consequently to improved prediction performance compared to the standard Markov Random Fields method. We tested our method using a high quality S.cereviciae validation network with 1622 proteins against 90 Gene Ontology terms of different levels of abstraction. Compared to three other protein function prediction methods, our approach shows very good prediction performance. Our method can be directly applied to protein-protein interaction or coexpression networks, but also can be extended to use multiple data sources. We apply our method to physical protein interaction data from S. cerevisiae and provide novel predictions, using 340 Gene Ontology terms, for 1170 unannotated proteins and we evaluate the predictions using the available literature.     

Evaluation of c-erbB-2 overexpression and Her-2/neu gene copy number heterogeneity in Barrett's adenocarcinoma.

Amplification of the Her-2/neu gene is accompanied by overexpression of its cell surface receptor product, c-erbB-2 protein. To investigate the degree of intratumoural heterogeneity we applied immunohistochemistry in primary Barrett's adenocarcinoma (BCA) (n = 6) and dysplasia adjacent to the carcinoma (n = 4). In addition, fluorescence in situ hybridisation (FISH) was performed in primary BCA (n = 5) and dysplastic areas (n = 4). For an objective evaluation digital image analysis and laser scanning microscopy were used. Five of six BCA showed a marked intratumoral heterogeneous staining pattern ranging from areas in which the tumour cells were negative or faintly positive to tumour areas with a strong staining of the entire membrane. Among the two dysplastic areas also a heterogeneous staining pattern was observed. FISH analysis revealed marked heterogeneity of intratumoral gene copy number changes in all BCA showing populations with different fractions of cells with polysomy, low level amplification and high level amplification. One dysplasia showed a minor population with Her-2/neu signal clusters. In conclusion, we observed marked intratumoural heterogeneity of c-erbB-2 protein overexpression and Her-2/neu gene copy number in the majority of the primary BCA analyzed. Digital image analysis and laser scanning microscopy were helpful in quantifying the variations in protein expression and DNA copy number in individual tumour cells. The observed heterogeneity could hamper the exact diagnostic determination of the c-erbB-2 status in small biopsies and possibly influence the effectiveness of a potential c-erbB-2 targeting therapy. Figures on http://www.esacp.org/acp/2000/20-1/walch.htm+ ++.     

Membrane Rafts Are Involved in Intracellular Miconazole Accumulation in Yeast Cells

Azoles inhibit ergosterol biosynthesis, resulting in ergosterol depletion and accumulation of toxic 14α-methylated sterols in membranes of susceptible yeast. We demonstrated previously that miconazole induces actin cytoskeleton stabilization in Saccharomyces cerevisiae prior to induction of reactive oxygen species, pointing to an ancillary mode of action. Using a genome-wide agar-based screening, we demonstrate in this study that S. cerevisiae mutants affected in sphingolipid and ergosterol biosynthesis, namely ipt1, sur1, skn1, and erg3 deletion mutants, are miconazole-resistant, suggesting an involvement of membrane rafts in its mode of action. This is supported by the antagonizing effect of membrane raft-disturbing compounds on miconazole antifungal activity as well as on miconazole-induced actin cytoskeleton stabilization and reactive oxygen species accumulation. These antagonizing effects point to a primary role for membrane rafts in miconazole antifungal activity. We further show that this primary role of membrane rafts in miconazole action consists of mediating intracellular accumulation of miconazole in yeast cells.     

Linkage and Association Mapping for Two Major Traits Used in the Maritime Pine Breeding Program: Height Growth and Stem Straightness

BackgroundIncreasing our understanding of the genetic architecture of complex traits, through analyses of genotype-phenotype associations and of the genes/polymorphisms accounting for trait variation, is crucial, to improve the integration of molecular markers into forest tree breeding. In this study, two full-sib families and one breeding population of maritime pine were used to identify quantitative trait loci (QTLs) for height growth and stem straightness, through linkage analysis (LA) and linkage disequilibrium (LD) mapping approaches.ResultsThe populations used for LA consisted of two unrelated three-generation full-sib families (n = 197 and n = 477). These populations were assessed for height growth or stem straightness and genotyped for 248 and 217 markers, respectively. The population used for LD mapping consisted of 661 founders of the first and second generations of the breeding program. This population was phenotyped for the same traits and genotyped for 2,498 single-nucleotide polymorphism (SNP) markers corresponding to 1,652 gene loci. The gene-based reference genetic map of maritime pine was used to localize and compare the QTLs detected by the two approaches, for both traits. LA identified three QTLs for stem straightness and two QTLs for height growth. The LD study yielded seven significant associations (P ≤ 0.001): four for stem straightness and three for height growth. No colocalisation was found between QTLs identified by LA and SNPs detected by LD mapping for the same trait.ConclusionsThis study provides the first comparison of LA and LD mapping approaches in maritime pine, highlighting the complementary nature of these two approaches for deciphering the genetic architecture of two mandatory traits of the breeding program.