Look before you reach!

This issue of Neuron contains an elegant neuroimaging study by Prado and colleagues, who report that the network of brain areas involved in visually guided reaching is modulated by whether targets are presented in central or peripheral vision. These results clarify prior inconsistencies in the literature regarding reach-related activation in the human brain, and they are valuable in interpreting neuropsychological cases of patients who demonstrate misreaching.     

Making inferences about speciation using sophisticated statistical genetics methods: look before you leap

Understanding speciation is a fundamental aim of evolutionary biology and a very challenging one. Speciation can be viewed as the dynamics of genetic differentiation between populations resulting in substantial reproductive isolation (Gavrilets 2003). It was generally accepted that very small levels of migration prevent genetic differentiation among populations and, therefore, speciation. However, recent theoretical work showed that sympatric speciation is possible (Gavrilets 2003). Nevertheless, providing empirical evidence that gene flow occurred during speciation is challenging because several gene flow scenarios can explain observed patterns of genetic differentiation. Positive migration rate estimates alone do not prove ongoing gene flow during divergence. We also need to know whether migration took place before, during or after speciation. There is no statistical method specifically aimed at estimating gene flow timing, but several studies used the isolation with migration model (Hey & Nielsen 2004, 2007; Hey 2010b) to estimate this parameter and make inferences about speciation scenarios. It is tempting to use statistical methods to estimate important evolutionary parameters even if they do not appear explicitly in the inference model. Nevertheless, before doing so, we need to determine whether they can provide reliable results. In this issue of Molecular Ecology, Strasburg and Rieseberg (2011) present a simulation study that examines the degree to which gene flow timing estimates obtained from IMa2 (Hey 2010b) can be used to make inferences about speciation mode. Their results are sobering; gene flow timing estimates obtained in this way are not reliable and cannot be used to unequivocally establish if gene flow was ongoing during speciation.     

Genomics and genome-wide association studies: an integrative approach to expression QTL mapping

Expression QTL mapping by integrating genome-wide gene expression and genotype data is a promising approach to identifying functional genetic variation, but is hampered by the large number of multiple comparisons inherent in such studies. A novel approach to addressing multiple testing problems in genome-wide family-based association studies is screening candidate markers using heritability or conditional power. We apply these methods in settings in which microarray gene expression data are used as phenotypes, screening for SNPs near the expressed genes. We perform association analyses for phenotypes using a univariate approach. We also perform simulations on trios with large numbers of causal SNPs to determine the optimal number of markers to use in a screen. We demonstrate that our family-based screening approach performs well in the analysis of integrative genomic datasets and that screening using either heritability or conditional power produces similar, though not identical, results.     

Multiple QTL mapping in related plant populations via a pedigree-analysis approach

QTL mapping experiments in plant breeding may involve multiple populations or pedigrees that are related through their ancestors. These known relationships have often been ignored for the sake of statistical analysis, despite their potential increase in power of mapping. We describe here a Bayesian method for QTL mapping in complex plant populations and reported the results from its application to a (previously analysed) potato data set. This Bayesian method was originally developed for human genetics data, and we have proved that it is useful for complex plant populations as well, based on a sensitivity analysis that was performed here. The method accommodates robustness to complex structures in pedigree data, full flexibility in the estimation of the number of QTL across multiple chromosomes, thereby accounting for uncertainties in the transmission of QTL and marker alleles due to incomplete marker information, and the simultaneous inclusion of non-genetic factors affecting the quantitative trait.     

A genetical genomics approach to genome scans increases power for QTL mapping

We describe a method for integrating gene expression information into genome scans and show that this can substantially increase the statistical power of QTL mapping. The method has three stages. First, standard clustering methods identify small (size 5-20) groups of genes with similar expression patterns. Second, each gene group is tested for a causative genetic locus shared with the clinical trait of interest. This is done using an EM algorithm approach that treats genotype at the putative causative locus as an unobserved variable and combines expression information from all of the genes in the group to infer genotype information at the locus. Finally, expression QTL (eQTL) are mapped for each gene group that shares a causative locus with the clinical trait. Such eQTL are candidates for the causative locus. Simulation results show that this method has far superior power to standard QTL mapping techniques in many circumstances. We applied this method to existing data on mouse obesity. Our method identified 27 putative body weight QTL, whereas standard QTL mapping produced only one. Furthermore, most gene groups with body weight QTL included cis genes, so candidate genes could be immediately identified. Eleven body weight QTL produced 16 candidate genes that have been previously associated with body weight or body weight-related traits, thus validating our method. In addition, 15 of the 16 other loci produced 32 candidate genes that have not been associated with body weight. Thus, this method shows great promise for finding new causative loci for complex traits.     

Look before you treat: increasing the cost effectiveness of eradication programs with aerial surveillance

Most successful invasive species eradication programs were applied to invasions confined to a small area. Invasions occupying large areas at a low density can potentially be eradicated if individual infestations can be found at affordable cost. The development of low cost aerial surveillance methods allows for larger areas to be monitored but such methods often have lower sensitivity than conventional surveillance methods, making their cost-effectiveness uncertain. Here, we consider the cost-effectiveness of including a new aerial monitoring method in Australia’s largest eradication program, the campaign to eradicate red imported fire ants (Solenopsis invicta). The program previously relied on higher sensitivity ground surveillance and broadcast treatment. The high cost of those methods restricted the total area that could be managed with available resources below the level required to prevent ongoing expansion of the invasion. By increasing the area that can be monitored and thereby improving the targeting of treatment and ground surveillance, we estimate that remote sensing could substantially reduce eradication costs despite the method’s low sensitivity. The development of low cost monitoring methods could potentially lead to substantially improved management of invasive species.     

MetaQTL: a package of new computational methods for the meta-analysis of QTL mapping experiments

Background  

Integration of multiple results from Quantitative Trait Loci (QTL) studies is a key point to understand the genetic determinism of complex traits. Up to now many efforts have been made by public database developers to facilitate the storage, compilation and visualization of multiple QTL mapping experiment results. However, studying the congruency between these results still remains a complex task. Presently, the few computational and statistical frameworks to do so are mainly based on empirical methods (e.g. consensus genetic maps are generally built by iterative projection).     

A new approach to genome mapping and sequencing: slalom libraries

We describe here an efficient strategy for simultaneous genome mapping and sequencing. The approach is based on physically oriented, overlapping restriction fragment libraries called slalom libraries. Slalom libraries combine features of general genomic, jumping and linking libraries. Slalom libraries can be adapted to different applications and two main types of slalom libraries are described in detail. This approach was used to map and sequence (with ~46% coverage) two human P1-derived artificial chromosome (PAC) clones, each of ~100 kb. This model experiment demonstrates the feasibility of the approach and shows that the efficiency (cost-effectiveness and speed) of existing mapping/sequencing methods could be improved at least 5–10-fold. Furthermore, since the efficiency of contig assembly in the slalom approach is virtually independent of length of sequence reads, even short sequences produced by rapid, high throughput sequencing techniques would suffice to complete a physical map and a sequence scan of a small genome.     

Some ways to improve QTL mapping accuracy

In this paper, we review some approaches for QTL mapping developed by our research group in collaboration with, following the recommendation of, or under inspiration of Moshe Soller. Specifically, we explain at a simple intuitive level the main principles and ideas of: (a) QTL mapping by fractioned DNA pooling, (b) increasing the detection power of QTL mapping (in the case of individual genotyping) by multiple-trait analysis, and (c) the role of variance-covariance effects in QTL mapping. On each of these themes we had long and deep discussions with Soller on the statistical aspects of the proposed procedures. We hope that together we made important contributions towards making QTL mapping procedures easier and more effective.     

A mixture model approach to the mapping of QTL controlling endosperm traits with bulked samples

Endosperm traits are of triploid inheritance and have become a focus of breeding effort for their close relations with the grain quality. Current methods for mapping quantitative trait loci (QTL) underlying endosperm traits are restricted to the use of the phenotypes of single grain samples as input data set, which are often not available in practice due to the small size of the cereal seeds. This paper proposed a statistical model for one specially tailored mapping strategy, where the marker genotypes are obtained from the maternal plants in the segregation population and the phenotypic responses are replaced by the trait means of composite endosperm samples pooled from each plant. It should therefore be more practical and have wide applicability in mapping endosperm traits. The method was implemented by fitting the phenotypic means of endosperms into a Gaussian mixture model. Both the exact and approximate Expectation-Maximization algorithms were proposed to estimate the model parameters. The presence of the QTL was determined by likelihood ratio test statistics. Statistical power and other properties of the new method were investigated and compared to the current single-seed method under a variety of scenarios through simulation studies. The simulations suggest a reasonable sample size should be used to ensure reliable results. The proposed method was also applied to a simulated genome data for further evaluation. As an illustration, a real data of maize was analyzed to find the loci responsible for the popping expansion volume.     

Biomass Cost Index: mapping biomass-to-biohydrogen feedstock costs by a new approach

Making decisions and developing policy in the field of biofuel and bioenergy is complex because of the large number and potential arrangements of feedstocks, technologies and supply chain options. Although, the technical optimisation and sustainability of any biomass to biofuel production chain is of major importance, the overall chain cost is still considered as the key for their market deployment. A significant percentage of this cost is attributed to primary generation, transportation/handling and pretreatment of the biomass. The separation of the system into smaller semi-independent sub-systems and dealing with their interfaces, provides the pathway to map this complex landscape. The main scope of this work is to present a tool, which was developed for the comparison of diverse biomass-to-biofuel systems, in order to facilitate the cost-wise decision making on this field.     

Three-dimensional endocardial impedance mapping: a new approach for myocardial infarction assessment

Precise identification of infarcted myocardial tissue is of importance in diagnostic and interventional cardiology. A three-dimensional, catheter-based endocardial electromechanical mapping technique was used to assess the ability of local endocardial impedance in delineating the exact location, size, and border of canine myocardial infarction. Electromechanical mapping of the left ventricle was performed in a control group (n = 10) and 4 wk after left anterior descending coronary artery ligation (n = 10). Impedance, bipolar electrogram amplitude, and endocardial local shortening (LS) were quantified. The infarcted area was compared with the corresponding regions in controls, revealing a significant reduction in impedance values [infarcted vs. controls: 168.8 +/- 11. 7 and 240.7 +/- 22.3 Omega, respectively (means +/- SE), P < 0.05] bipolar electrogram amplitude (1.8 +/- 0.2 mV, 4.4 +/- 0.7 mV, P < 0. 05), and LS (-2.36 +/- 1.6%, 11.9 +/- 0.9%, P < 0.05). The accuracy of the impedance maps in delineating the location and extent of the infarcted region was demonstrated by the high correlation with the infarct area (Pearson's correlation coefficient = 0.942) and the accurate identification of the infarct borders in pathology. By accurately defining myocardial infarction and its borders, endocardial impedance mapping may become a clinically useful tool in differentiating healthy from necrotic myocardial tissue.     

Application of a new IBD-based QTL mapping method to common wheat breeding population: analysis of kernel hardness and dough strength

Mapping quantitative trait loci (QTL) in plants is usually conducted using a population derived from a cross between two inbred lines. The power of such QTL detection and the estimation of the effects highly depend on the choice of the two parental lines. Thus, the QTL found represent only a small part of the genetic architecture and can be of limited economical interest in marker-assisted selection. On the other hand, applied breeding programmes evaluate large numbers of progeny derived from multiple-related crosses for a wide range of agronomic traits. It is assumed that the development of statistical techniques to deal with pedigrees in existing plant populations would increase the relevance and cost effectiveness of QTL mapping in a breeding context. In this study, we applied a two-step IBD-based-variance component method to a real wheat breeding population, composed of 374 F₆ lines derived from 80 different parents. Two bread wheat quality related traits were analysed by the method. Results obtained show very close agreement with major genes and QTL already known for those two traits. With this new QTL mapping strategy, inferences about QTL can be drawn across the breeding programme rather than being limited to the sample of progeny from a single cross and thus the use of the detected QTL in assisting breeding would be facilitated.