Identification of the sex-determining region in flathead grey mullet (Mugil cephalus).

Elucidation of the sex-determination mechanism in flathead grey mullet (Mugil cephalus) is required to exploit its economic potential by production of genetically determined monosex populations and application of hormonal treatment to parents rather than to the marketed progeny. Our objective was to construct a first-generation linkage map of the M. cephalus in order to identify the sex-determining region and sex-determination system. Deep-sequencing data of a single male was assembled and aligned to the genome of Nile tilapia (Oreochromis niloticus). A total 245 M. cephalus microsatellite markers were designed, spanning the syntenic tilapia genome assembly at intervals of 10 Mb. In the mapping family of full-sib progeny, 156 segregating markers were used to construct a first-generation linkage map of 24 linkage groups (LGs), corresponding to the number of chromosomes. The linkage map spanned approximately 1200 cM with an average inter-marker distance of 10.6 cM. Markers segregating on LG9 in two independent mapping families showed nearly complete concordance with gender (R2  = 0.95). The sex determining locus was fine mapped within an interval of 8.6 cM on LG9. The sex of offspring was determined only by the alleles transmitted from the father, thus indicating an XY sex-determination system.

Genome-wide analysis of DNA turnover and gene expression in stationary-phase Saccharomyces cerevisiae.

Exponential-phase yeast cells readily enter stationary phase when transferred to fresh, carbon-deficient medium, and can remain fully viable for up to several months. It is known that stationary-phase prokaryotic cells may still synthesize substantial amounts of DNA. Although the basis of this phenomenon remains unclear, this DNA synthesis may be the result of DNA maintenance and repair, recombination, and stress-induced transposition of mobile elements, which may occur in the absence of DNA replication. To the best of our knowledge, the existence of DNA turnover in stationary-phase unicellular eukaryotes remains largely unstudied. By performing cDNA-spotted (i.e. ORF) microarray analysis of stationary cultures of a haploid Saccharomyces cerevisiae strain, we demonstrated on a genomic scale the localization of a DNA-turnover marker [5-bromo-2'-deoxyuridine (BrdU); an analogue of thymidine], indicative of DNA synthesis in discrete, multiple sites across the genome. Exponential-phase cells on the other hand, exhibited a uniform, total genomic DNA synthesis pattern, possibly the result of DNA replication. Interestingly, BrdU-labelled sites exhibited a significant overlap with highly expressed features. We also found that the distribution among chromosomes of BrdU-labelled and expressed features deviates from random distribution; this was also observed for the overlapping set. Ty1 retrotransposon genes were also found to be labelled with BrdU, evidence for transposition during stationary phase; however, they were not significantly expressed. We discuss the relevance and possible connection of these results to DNA repair, mutation and related phenomena in higher eukaryotes.

Fine mapping and association analysis of a quantitative trait locus for milk production traits on Bos taurus autosome 4.

To fine map a quantitative trait locus (QTL) affecting milk production traits previously associated with microsatellite RM188, we implemented an interval mapping analysis by using microsatellite markers in a large Israeli Holstein half-sib sire family, and linkage disequilibrium (LD) mapping in a large set of US Holstein bulls. Interval mapping located the target QTL to the near vicinity of RM188. For the LD mapping, we identified 42 single nucleotide polymorphisms (SNP) in 15 genes in a 12-Mb region on bovine chromosome 4. A total of 24 tag SNP were genotyped in 882 bulls belonging to the University of California Davis archival collection of Holstein bull DNA samples with predicted transmitted ability phenotypes. Marker-to-marker LD analysis revealed 2 LD blocks, with intrablock r(2) values of 0.10 and 0.46, respectively; outside the blocks, r(2) values ranged from 0.002 to 0.23. A standard additive/dominance model using the generalized linear model procedure of SAS and the regression module of HelixTree software were used to test marker-trait associations. Single nucleotide polymorphism 9 on ARL4A, SNP10 on XR_027435.1, SNP12 on ETV1, SNP21 on SNX13, and SNP24 were significantly associated with milk production traits. We propose the interval encompassing ARL4A and SNX13 genes as a candidate region in bovine chromosome 4 for a concordant QTL related to milk protein traits in dairy cattle. Functional studies are needed to confirm this result.

Multilocus consensus genetic maps (MCGM): formulation, algorithms, and results.

In process of creating genetic maps different labs/research groups obtain overlapping parts of the map. Merging these parts into one integrative map is based on looking for maximum shared marker orders among the maps. Really, not all shared markers of such maps have consensus order that obstructs building of the integrative maps. In this paper we propose a new approach to build verified multilocus consensus genetic maps in which shared markers always are integrated in stable consensus order. The approach is based on combined analysis of initial mapping data rather than manipulating with previously constructed maps. We show that more effective and reliable solutions may be obtained based on "synchronized ordering" facilitated by cycles of "re-sampling-->ordering-->removing unstable markers". The proposed formulation of consensus genetic mapping can be considered as a version of traveling salesperson problem (TSP) that we refer to as synchronized-TSP. From the viewpoint of optimization, synchronized-TSP belongs to discrete constrained optimization problems. Earlier we developed new powerful and fast guided evolution strategy algorithms for some types of discrete constrained optimization. These algorithms were used here as a basis for solving more challenging problems of consensual marker ordering.

Approximate analysis of QTL-environment interaction with no limits on the number of environments.

An approach is presented here for quantitative trait loci (QTL) mapping analysis that allows for QTL x environment (E) interaction across multiple environments, without necessarily increasing the number of parameters. The main distinction of the proposed model is in the chosen way of approximation of the dependence of putative QTL effects on environmental states. We hypothesize that environmental dependence of a putative QTL effect can be represented as a function of environmental mean value of the trait. Such a description can be applied to take into account the effects of any cosegregating QTLs from other genomic regions that also may vary across environments. The conducted Monte-Carlo simulations and the example of barley multiple environments experiment demonstrate a high potential of the proposed approach for analyzing QTL x E interaction, although the results are only approximated by definition. However, this drawback is compensated by the possibility to utilize information from a potentially unlimited number of environments with a remarkable reduction in the number of parameters, as compared to previously proposed mapping models with QTL x E interactions.

Single- and multiple-trait mapping analysis of linked quantitative trait loci. Some asymptotic analytical approximations.

Estimating the resolution power of mapping analysis of linked quantitative trait loci (QTL) remains a difficult problem, which has been previously addressed mainly by Monte Carlo simulations. The analytical method of evaluation of the expected LOD developed in this article spreads the "deterministic sampling" approach for the case of two linked QTL for single- and two-trait analysis. Several complicated questions are addressed through this evaluation: the dependence of QTL detection power on the QTL effects, residual correlation between the traits, and the effect of epistatic interaction between the QTL for one or both traits on expected LOD (ELOD), etc. Although this method gives only an asymptotic estimation of ELOD, it allows one to get an approximate assessment of a broad spectrum of mapping situations. A good correspondence was found between the ELODs predicted by the model and LOD values averaged over Monte Carlo simulations.

Constructing large-scale genetic maps using an evolutionary strategy algorithm.

This article is devoted to the problem of ordering in linkage groups with many dozens or even hundreds of markers. The ordering problem belongs to the field of discrete optimization on a set of all possible orders, amounting to n!/2 for n loci; hence it is considered an NP-hard problem. Several authors attempted to employ the methods developed in the well-known traveling salesman problem (TSP) for multilocus ordering, using the assumption that for a set of linked loci the true order will be the one that minimizes the total length of the linkage group. A novel, fast, and reliable algorithm developed for the TSP and based on evolution-strategy discrete optimization was applied in this study for multilocus ordering on the basis of pairwise recombination frequencies. The quality of derived maps under various complications (dominant vs. codominant markers, marker misclassification, negative and positive interference, and missing data) was analyzed using simulated data with approximately 50-400 markers. High performance of the employed algorithm allows systematic treatment of the problem of verification of the obtained multilocus orders on the basis of computing-intensive bootstrap and/or jackknife approaches for detecting and removing questionable marker scores, thereby stabilizing the resulting maps. Parallel calculation technology can easily be adopted for further acceleration of the proposed algorithm. Real data analysis (on maize chromosome 1 with 230 markers) is provided to illustrate the proposed methodology.

Interval mapping of quantitative trait loci employing correlated trait complexes.

An approach to increase the resolution power of interval mapping of quantitative trait (QT) loci is proposed, based on analysis of correlated trait complexes. For a given set of QTs, the broad sense heritability attributed to a QT locus (QTL) (say, A/a) is an increasing function of the number of traits. Thus, for some traits x and y, H(xy)2(A/a) > or = H(x)2(A/a). The last inequality holds even if y does not depend on A/a at all, but x and y are correlated within the groups AA, Aa and aa due to nongenetic factors and segregation of genes from other chromosomes. A simple relationship connects H2 (both in single trait and two-trait analysis) with the expected LOD value, ELOD = -1/2N log(1-H2). Thus, situations could exist that from the inequality H(xy)2(A/a) > or = H(x)2(A/a) a higher resolution is provided by the two-trait analysis as compared to the single-trait analysis, in spite of the increased number of parameters. Employing LOD-score procedure to simulated backcross data, we showed that the resolution power of the QTL mapping model can be elevated if correlation between QTs is taken into account. The method allows us to test numerous biologically important hypotheses concerning manifold effects of genomic segments on the defined trait complex (means, variances and correlations).

High-resolution mapping of quantitative trait loci by selective recombinant genotyping.

Selective recombinant genotyping (SRG) is a three-stage procedure for high-resolution mapping of a QTL that has previously been mapped to a known confidence interval (target C.I.). In stage 1, a large mapping population is accessed and phenotyped, and a proportion, P, of the high and low tails is selected. In stage 2, the selected individuals are genotyped for a pair of markers flanking the target C.I., and a group of R individuals carrying recombinant chromosomes in the target interval are identified. In stage 3, the recombinant individuals are genotyped for a set of M markers spanning the target C.I. Extensive simulations showed that: (1) Standard error of QTL location (SEQTL) decreased when QTL effect (d) or population size (N) increased, but was constant for given "power factor" (PF = d(2)N); (2) increasing the proportion selected in the tails beyond 0.25 had only a negligible effect on SEQTL; and (3) marker spacing in the target interval had a remarkably powerful effect on SEQTL, yielding a reduction of up to 10-fold in going from highest (24 cM) to lowest (0.29 cM) spacing at given population size and QTL effect. At the densest marker spacing, SEQTL of 1.0-0.06 cM were obtained at PF = 500-16,000. Two new genotyping procedures, the half-section algorithm and the golden section/half-section algorithm, allow the equivalent of complete haplotyping of the target C.I. in the recombinant individuals to be achieved with many fewer data points than would be required by complete individual genotyping.

Enhanced efficiency of quantitative trait loci mapping analysis based on multivariate complexes of quantitative traits.

An approach to increase the efficiency of mapping quantitative trait loci (QTL) was proposed earlier by the authors on the basis of bivariate analysis of correlated traits. The power of QTL detection using the log-likelihood ratio (LOD scores) grows proportionally to the broad sense heritability. We found that this relationship holds also for correlated traits, so that an increased bivariate heritability implicates a higher LOD score, higher detection power, and better mapping resolution. However, the increased number of parameters to be estimated complicates the application of this approach when a large number of traits are considered simultaneously. Here we present a multivariate generalization of our previous two-trait QTL analysis. The proposed multivariate analogue of QTL contribution to the broad-sense heritability based on interval-specific calculation of eigenvalues and eigenvectors of the residual covariance matrix allows prediction of the expected QTL detection power and mapping resolution for any subset of the initial multivariate trait complex. Permutation technique allows chromosome-wise testing of significance for the whole trait complex and the significance of the contribution of individual traits owing to: (a) their correlation with other traits, (b) dependence on the chromosome in question, and (c) both a and b. An example of application of the proposed method on a real data set of 11 traits from an experiment performed on an F(2)/F(3) mapping population of tetraploid wheat (Triticum durum x T. dicoccoides) is provided.

Fast and high precision algorithms for optimization in large-scale genomic problems.

There are several very difficult problems related to genetic or genomic analysis that belong to the field of discrete optimization in a set of all possible orders. With n elements (points, markers, clones, sequences, etc.), the number of all possible orders is n!/2 and only one of these is considered to be the true order. A classical formulation of a similar mathematical problem is the well-known traveling salesperson problem model (TSP). Genetic analogues of this problem include: ordering in multilocus genetic mapping, evolutionary tree reconstruction, building physical maps (contig assembling for overlapping clones and radiation hybrid mapping), and others. A novel, fast and reliable hybrid algorithm based on evolution strategy and guided local search discrete optimization was developed for TSP formulation of the multilocus mapping problems. High performance and high precision of the employed algorithm named guided evolution strategy (GES) allows verification of the obtained multilocus orders based on different computing-intensive approaches (e.g., bootstrap or jackknife) for detection and removing unreliable marker loci, hence, stabilizing the resulting paths. The efficiency of the proposed algorithm is demonstrated on standard TSP problems and on simulated data of multilocus genetic maps up to 1000 points per linkage group.

Two-phase analysis in consensus genetic mapping.

Numerous mapping projects conducted on different species have generated an abundance of mapping data. Consequently, many multilocus maps have been constructed using diverse mapping populations and marker sets for the same organism. The quality of maps varies broadly among populations, marker sets, and software used, necessitating efforts to integrate the mapping information and generate consensus maps. The problem of consensus genetic mapping (MCGM) is by far more challenging compared with genetic mapping based on a single dataset, which by itself is also cumbersome. The additional complications introduced by consensus analysis include inter-population differences in recombination rate and exchange distribution along chromosomes; variations in dominance of the employed markers; and use of different subsets of markers in different labs. Hence, it is necessary to handle arbitrary patterns of shared sets of markers and different level of mapping data quality. In this article, we introduce a two-phase approach for solving MCGM. In phase 1, for each dataset, multilocus ordering is performed combined with iterative jackknife resampling to evaluate the stability of marker orders. In this phase, the ordering problem is reduced to the well-known traveling salesperson problem (TSP). Namely, for each dataset, we look for order that gives minimum sum of recombination distances between adjacent markers. In phase 2, the optimal consensus order of shared markers is selected from the set of allowed orders and gives the minimal sum of total lengths of nonconflicting maps of the chromosome. This criterion may be used in different modifications to take into account the variation in quality of the original data (population size, marker quality, etc.). In the foregoing formulation, consensus mapping is considered as a specific version of TSP that can be referred to as "synchronized TSP." The conflicts detected after phase 1 are resolved using either a heuristic algorithm over the entire chromosome or an exact/heuristic algorithm applied subsequently to the revealed small non-overlapping regions with conflicts separated by non-conflicting regions. The proposed approach was tested on a wide range of simulated data and real datasets from maize.

The dynamics of the rec-system in variable environments: haploid selection in a cyclical two-state environment.

The dynamics of a 3-locus infinite population with non-overlapping generations and panmixia was studied. Loci are di-allelic: two loci affect fitness under cyclical symmetric haploid selection while the third one is a modifier of recombination (rec-modifier). Selection favors alternatively haplotypes AB and ab or Ab and aB. It has been proven that under alternating selection (when period of selection consists of two generations) a dominant suppressor of recombination is displaced and the allele for non-zero recombination becomes fixed within the population. For populations with inversion heterozygosity within the selective system (i.e. with zero recombination in heterozygote for rec-modifier and non-zero for homozygotes) fixation of one of the alleles (depending on the initial point) at the rec-modifier locus is predicted. For other values of recombination parameters, the behavior of the system was studied numerically. A full bifurcation picture of parameters was obtained. Many of the results related to the case of a two-generation period hold also in the case of longer period lengths.

QTLs associated with growth traits and abdominal fat weight and their interactions with gender and hatch in commercial meat-type chickens.

Associations between microsatellite markers and traits related to growth and fatness were investigated using resource broiler population. A sire-line x dam-line F1 male was backcrossed to 12 dam-line females to produce 24 sires and 47 dams of the backcross 1 (BC1) generation. These 71 parents were genotyped with 76 microsatellite markers. Following full-sib mating among the parents, 234 BC1-F2 progeny were phenotyped for five growth traits (body weight at 49 days from hatch, wog weight, front half weight, breast weight and tender weight) and abdominal fat weight. Maximum likelihood analysis was used to estimate the marker effects and to evaluate their statistical significance. Individual marker-trait analysis revealed 44 significant associations out of the 456 marker-trait combinations. Correction for multiple comparisons by controlling the false discovery rate (FDR) resulted in 12 significant associations at FDR = 10% with markers on chromosomes 1, 2, 5 and 13. Seventy-five percent of the 44 significant associations displayed no dependence on either hatch or gender; half of the remaining associations displayed dependence of the quantitative trait loci (QTL) effect on hatch x gender interaction. Thus, the analysed traits in this study may be dependent on external factors.

Linkage between quantitative trait loci and marker loci: resolution power of three statistical approaches in single marker analysis.

This paper presents a comparison of three methods of parameter estimation in analysis of linkage between a quantitative trait locus (QTL) and a marker locus: maximum likelihood, mean square for trait cumulative distribution function, and method of moments, employing simulated backcross data. The sensitivity of estimates to violation of assumptions of normality and equal variances were also studied. Some measures of discrepancy between the trait distributions in the QTL groups are considered to evaluate the potential dependence of the resolution capacity of the QTL substitution effect with respect to trait mean value and variance.

Linkage between loci of quantitative traits and marker loci: multi-trait analysis with a single marker.

An efficient approach to increase the resolution power of linkage analysis between a quantitative trait locus (QTL) and a marker is described in this paper. It is based on a counting of the correlations between the QTs of interest. Such correlations may be caused by the segregation of other genes, environmental effects and physiological limitations. Let a QT locus A/a affect two correlated traits, x and y. Then, within the framework of mixture models, the accuracy of the parameter estimates may be seriously increased, if bivariate densities f aa(x, y), f Aa(x, y) and f AA(x, y) rather than the marginals are considered as the basis for mixture decomposition. The efficiency of the proposed method was demonstrated employing Monte-Carlo simulations. Several types of progeny were considered, including backcross, F2 and recombinant inbred lines. It was shown that provided the correlation between the traits involved was high enough, a good resolution to the problem is possible even if the QTL groups are strongly overlapping for their marginal densities.

Sequential estimation of linkage between PCR-generated markers and a target gene employing stepwise bulked analysis.

PCR-based markers are used for targeting plant genes. However, mapping these markers requires laborious and expensive analysis of individual genotypes. We propose here a sequential procedure for fine mapping of PCR markers relative to a target gene. Stepwise bulked analysis is employed to get a censored estimation of the recombination rate. The sequential estimation is compared to fixed sample size design. In both cases, the proposed procedure can achieve a substantial reduction in the number of PCR runs (up to 90-97% for close linkage) as compared to the standard individual-by-individual analysis.

Cyclical behavior of genotype frequencies in a two-locus population under fluctuating haploid selection.

Numerical iterations have shown that periodic haploid two-locus selection with nonoverlapping generations can produce large-scale cyclical behavior with a period differing significantly from the environmental period. Among other types, we observed slowly damping oscillations with very long periods, stable T-cycles with a length containing several environmental periods, and chaotic-like dynamics. Possible biological implications are discussed.

Genetic supercycles caused by cyclical selection.

Typical behavior of a two-locus genetic system experiencing cyclical selection, includes fixation (in one or both loci) or a stable polymorphic cycle with a period equal to that of environmental changes. By considering the time scale in terms of environmental periods, the last case could be trivially classified as a polymorphic stable point. Here we report on some results showing the complex limiting behavior of diploid population trajectories resulting from selection in a cyclically changing environment. We found that simple cyclical selection could produce genetic supercycles composed of many hundreds of environmental periods.

Nonrandom mating in Drosophila melanogaster laboratory populations derived from closely adjacent ecologically contrasting slopes at "Evolution Canyon".

Ecological differentiation of natural populations of Drosophila melanogaster, Drosophila simulans, and another drosophilid, Zaprionus tuberculatus, in "Evolution Canyon," Mount Carmel, Israel, is well established. The fitness complex of D. melanogaster includes oviposition temperature preferences, tolerance to high temperature, drought stress and starvation, and different longevity patterns. This remarkable differentiation has evolved despite small interslope distances (only 100-400 m), within easy dispersal distance. The differences between populations are those expected from genetic adaptation to local microclimates. How such differentiation could evolve and be maintained despite the likelihood of genetic exchange between populations is a challenging question. We hypothesized that interslope microclimatic differences caused strong differential selection for stress tolerance, accompanied by behavioral differentiation (habitat choice and reduced migration rate), reinforced by sexual isolation. Here we report highly significant mate choice by flies from different slopes of the canyon, with preference for sexual partners originating from the same slope. No preferences were found when the sexual partners belonged to different isofemale lines from the same slope.