Data distributions in magnetic resonance images: A review

Many image processing methods applied to magnetic resonance (MR) images directly or indirectly rely on prior knowledge of the statistical data distribution that characterizes the MR data. Also, data distributions are key in many parameter estimation problems and strongly relate to the accuracy and precision with which parameters can be estimated. This review paper provides an overview of the various distributions that occur when dealing with MR data, considering both single-coil and multiple-coil acquisition systems. The paper also summarizes how knowledge of the MR data distributions can be used to construct optimal parameter estimators and answers the question as to what precision may be achieved ultimately from a particular MR image.     

Use of a large multiparent wheat mapping population in genomic dissection of coleoptile and seedling growth

Identification of alleles towards the selection for improved seedling vigour is a key objective of many wheat breeding programmes. A multiparent advanced generation intercross (MAGIC) population developed from four commercial spring wheat cultivars (cvv. Baxter, Chara, Westonia and Yitpi) and containing ca. 1000 F₂‐derived, F_6:7 RILs was assessed at two contrasting soil temperatures (12 and 20 °C) for shoot length and coleoptile characteristics length and thickness. Narrow‐sense heritabilities were high for coleoptile and shoot length (h² = 0.68–0.70), indicating a strong genetic basis for the differences among progeny. Genotypic variation was large, and distributions of genotype means were approximately Gaussian with evidence for transgressive segregation for all traits. A number of significant QTL were identified for all early growth traits, and these were commonly repeatable across the different soil temperatures. The largest negative effects on coleoptile lengths were associated with Rht‐B1b (?8.2%) and Rht‐D1b (?10.9%) dwarfing genes varying in the population. Reduction in coleoptile length with either gene was particularly large at the warmer soil temperature. Other large QTL for coleoptile length were identified on chromosomes 1A, 2B, 4A, 5A and 6B, but these were relatively smaller than allelic effects at the Rht‐B1 and Rht‐D1 loci. A large coleoptile length effect allele (a = 5.3 mm at 12 °C) was identified on chromosome 1AS despite the relatively shorter coleoptile length of the donor Yitpi. Strong, positive genetic correlations for coleoptile and shoot lengths (r_g = 0.85–0.90) support the co‐location of QTL for these traits and suggest a common physiological basis for both. The multiparent population has enabled the identification of promising shoot and coleoptile QTL despite the potential for the confounding of large effect dwarfing gene alleles present in the commercial parents. The incidence of these alleles in commercial wheat breeding programmes should facilitate their ready implementation in selection of varieties with improved establishment and early growth.     

Invasion Genetics of New World Medflies: Testing Alternative Colonization Scenarios

The Mediterranean fruit fly (Ceratitis capitata) is an invasive agricultural pest with a wide host range and a nearly global distribution. Efforts to forgo the medfly's spread into the United States are dependent on an understanding of population dynamics in newly established populations elsewhere. To explore the potential influence of demographic and historical parameters in six medfly populations distributed from Mexico to Peru, we created population genetic null models using Monte Carlo simulations. Null expectations for genetic differentiation (F _ST) were compared with actual sequence variation from four highly polymorphic nuclear loci. Four colonization scenarios that were modeled led to unique genetic signatures that could be used to interpret empirical data. Unless current gene flow across Latin America was assumed to be very high, we could reject colonizations consisting of multiple introductions, each of low genetic diversity. Further, if simulated populations were small (N _e = 5 × 10² individuals per population), small invasions from a single source consistently produced F _ST values comparable to those currently observed in Latin America. In contrast, only large invasions from diverse sources were compatible with the observed data for large populations (N _e 5 × 10³). This study demonstrates that alternative population genetic hypotheses can be tested empirically even when departures from equilibrium are extreme, and that population genetic theory can be used to explore the processes that underlie biological invasions.     

Assessing health risk using regional mappings based on local perceptions: A comparative study of three different hazards

Usually risk assessment falls within the competence of “hard sciences” through environmental and epidemiological measurements, evaluations, and modeling. Even if these approaches bring accurate assessment and evaluation of environmental processes, the perception of local inhabitants is often excluded or at least relegated to second place. Evaluation of human vulnerabilities and capacities to face such hazards requires us to understand the perceptions of the population exposed. Three case studies (Lao, Tunisia, and Ecuador) are presented where we applied a perception-based regional mapping, a mapping tool based on local perceptions, for assessing the connection between land uses and health issues. A selection of the results collected on these three study areas show that the perception of local inhabitants provides a good spatial representation of the different contaminations observed locally, with a good consistency with external data. It also indicates for a certain number of cases that the contamination extends far beyond the simulated radius and impacts peripheral areas. Beyond the analysis of such a method (methodological bias, spatial representation bias, etc.), the objective is to combine our results with epidemiological measurement.     

Are predators negative or positive predictors of farmland bird species community on a large geographical scale?

Species distribution models (SDMs) are numerical tools that combine species occurrence/density or species richness with environmental data in order to predict particular species’ distribution. In most cases only abiotic environmental parameters are used as predictors, while biotic interactions which control distribution of species and influence the goodness of fit of the SDM, such as predator–prey systems, have been broadly neglected. For this reason, we tested the usefulness of easy to detect predators, such as the Common Buzzard and the Common Raven, as positive and negative predictors, respectively, of farmland bird species richness. We analyzed factors affecting the density of both predators and farmland bird species using data from 958 1 × 1 km² study plots in Poland and a set of 22 environmental variables. Next, we also included these predators’ densities as additional predictors of farmland bird species. Habitat and climatological predictors were aggregated using the Principal Components Analysis and then related to the Common Raven's and the Common Buzzard's densities as well as farmland bird species richness using General Additive Models. Finally, completed models were assessed according to information – theoretic criteria. Our results showed that all the analyzed groups occurred in open areas; the Common Buzzard and passerine bird species preferred traditional farmland, while the Common Raven reached its highest density in modern intensive farmland. Importantly, we documented a significant increase in the goodness of fit of SDMs for farmland bird species, having added the density of predators as negative (Common Raven) and positive (Common Buzzard) predictors. Consequently, our findings suggest that species’ specific models can improve the predictive power of SDMs and can be used as an effective tool for predicting bird diversity with higher accuracy.     

Mapping complementary genes in maize: positioning the rf1 and rf2 nuclear-fertility restorer loci of Texas (T) cytoplasm relative to RFLP and visible markers

There are three major groups of cytoplasmic male-sterile cytoplasms in maize; C (Charrua), S (USDA), and T (Texas). These cytoplasms can be classified by the unique nuclear genes that suppress the male-sterility effects of these cytoplasms and restore pollen fertility. Typically, plants that carry Texas (T) cytoplasm are male fertile only if they carry dominant alleles at two unlinked nuclear restorer loci,rf1 andrf2. To facilitate analysis of T-cytoplasm-mediated male sterility and fertility restoration, we have mappedrf1 andrf2 relative to closely-linked RFLP markers using five populations. Therf1 locus and/or linked visible markers were mapped in four populations; therf2 locus was mapped in two of the populations. Data from the individual populations were joined with the aid of JoinMap software. The resulting consensus maps placerf1 between umc97 and umc92 on chromosome 3 andrf2 between umc153 andsus1 on chromosome 9. Markers that flank therf1 andrf2 loci have been used to identify alleles atrf1 andrf2 in segregating populations. These analyses demonstrate the possibility of tracking separate fertility restorer loci that contribute to a single phenotype.R. P. Wise and P. S. Schnable should both be considered first authors as they contributed equally to this workJoint contribution of the Field Crops Research Unit, USDA-Agricultural Research Service and the Iowa Agriculture and Home Economics Experiment Station. Journal Paper No. 15416 of the Iowa Agriculture and Home Economics Experiment Station, Ames, Iowa. Project Nos. 2447 and 3152     

Radiomics software for breast imaging optimization and simulation studies

Background and ObjectiveThe development, control and optimisation of new x-ray breast imaging modalities could benefit from a quantitative assessment of the resulting image textures. The aim of this work was to develop a software tool for routine radiomics applications in breast imaging, which will also be available upon request.MethodsThe tool (developed in MATLAB) allows image reading, selection of Regions of Interest (ROI), analysis and comparison. Requirements towards the tool also included convenient handling of common medical and simulated images, building and providing a library of commonly applied algorithms and a friendly graphical user interface. Initial set of features and analyses have been selected after a literature search. Being open, the tool can be extended, if necessary.ResultsThe tool allows semi-automatic extracting of ROIs, calculating and processing a total of 23 different metrics or features in 2D images and/or in 3D image volumes. Computations of the features were verified against computations with other software packages performed with test images. Two case studies illustrate the applicability of the tool – (i) features on a series of 2D ‘left’ and ‘right’ CC mammograms acquired on a Siemens Inspiration system were computed and compared, and (ii) evaluation of the suitability of newly proposed and developed breast phantoms for x-ray-based imaging based on reference values from clinical mammography images. Obtained results could steer the further development of the physical breast phantoms.ConclusionsA new image analysis toolbox was realized and can now be used in a multitude of radiomics applications, on both clinical and test images.     

Fine mapping of the <Emphasis Type="Italic">qCTS4</Emphasis> locus associated with seedling cold tolerance in rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.)

Rice seedlings are sensitive to low temperatures (≤15°C) and under prolonged or repeated exposure, yellowing and stunting are commonly observed. Damage to seedlings results in poor stand establishment and delayed maturation, which can cause significant reductions in yield. In general, japonica rice varieties exhibit more cold tolerance than indica varieties. Earlier genetic analysis of the California rice variety M202 revealed several quantitative trait loci (QTL) that contribute to its tolerance to low temperatures in comparison to the indica rice variety IR50. Among these QTL, qCTS4 is associated with tolerance to yellowing and stunting of rice seedlings and accounts for 40% of the phenotypic variation. Here we report on the fine mapping of qCTS4 to a 128 kb region of chromosome 4, which is highly suppressed for recombination in our mapping populations. Our results provide the necessary foundation for identifying the gene(s) underlying qCTS4 and the markers developed here may be used to introgress this region into indica varieties to improve seedling tolerance to low temperatures. The mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture.     

远交群体动态性状基因定位的似然分析Ⅱ.模拟研究

以远交设计群体为例,在推导出动态性状基因定位的似然法分析过程的基础上,选择3阶Legendre多项式为子模型,采用Monte-Carlo方法模拟研究了不同个体数、测定日频数、标记密度和QTL遗传贡献率对两种分析方法检测QTL效率的影响。每个因素都取高、中和低3个水平,利用正交设计安排模拟因素试验组合。模拟试验结果表明：高QTL遗传贡献率要比低QTL遗传贡献率的QTL在检测时需要较少个体数和测定日抽样;但不论QTL遗传贡献率多大,300以上的群体大小和5％以上的测定日频数都可以保证足够高的检测效率。个体数和测定日频数对动态性状QTL的分析和检测具有几乎相同的作用,而且相同样本含量条件下两者呈现互补的关系。就某个动态点的QTL检测而言,模拟试验也同时证明：提出的这种以整个动态过程为定位目标的动态性状基因定位方法明显优于传统的逐个动态点的定位分析方法。