Children's understanding of graphic representations of quantitative data

Children are encountering more and more graphic representations of data in their learning and everyday life. Much of this data occurs in quantitative forms as different forms of measurement are incorporated into the graphics during their construction. In their formal education, children are required to learn to use a range of these quantitative representations in subjects across the school curriculum. Previous research that focuses on the use of information processing and traditional approaches to cognitive psychology concludes that the development of an understanding of such representations of data is a complex process. An alternative approach is to investigate the experiences of children as they interact with graphic representations of quantitative data in their own life-worlds. This paper demonstrates how a phenomenographic approach may be used to reveal the qualitatively different ways in which children in Australian primary and secondary education understand the phenomenon of graphic representations of quantitative data. Seven variations of the children’s understanding were revealed. These have been described interpretively in the article and confirmed through the words of the children. A detailed outcome space demonstrates how these seven variations are structurally related.

Role of the apolipoprotein E and catechol-O-methyltransferase genes in prospective and retrospective memory traits

Human memory is a complex neurocognitive process. By combining psychological and molecular genetics expertise, we examined the APOE ε4 allele, a known risk factor for Alzheimer's disease, and the COMT Val 158 polymorphism, previously implicated in schizophrenia, for association with lowered memory functioning in healthy adults. To assess memory type we used a range of memory tests of both retrospective and prospective memory. Genotypes were determined using RFLP analysis and compared with mean memory scores using univariate ANOVAs. Despite a modest sample size (n=197), our study found a significant effect of the APOE ε4 polymorphism in prospective memory. Supporting our hypothesis, a significant difference was demonstrated between genotype groups for means of the Comprehensive Assessment of Prospective Memory total score (p=0.036; ε4 alleles=1.99; all other alleles=1.86). In addition, we demonstrate a significant interactive effect between the APOE ε4 and COMT polymorphisms in semantic memory. This is the first study to investigate both APOE and COMT genotypes in relation to memory in non-pathological adults and provides important information regarding the effect of genetic determinants on human memory.

Linkage mapping of CVD risk traits in the isolated Norfolk Island population

To understand the underlying genetic architecture of cardiovascular disease (CVD) risk traits, we undertook a genome-wide linkage scan to identify CVD quantitative trait loci (QTLs) in 377 individuals from the Norfolk Island population. The central aim of this research focused on the utilization of a genetically and geographically isolated population of individuals from Norfolk Island for the purposes of variance component linkage analysis to identify QTLs involved in CVD risk traits. Substantial evidence supports the involvement of traits such as systolic and diastolic blood pressures, high-density lipoprotein-cholesterol, low-density lipoprotein-cholesterol, body mass index and triglycerides as important risk factors for CVD pathogenesis. In addition to the environmental inXuences of poor diet, reduced physical activity, increasing age, cigarette smoking and alcohol consumption, many studies have illustrated a strong involvement of genetic components in the CVD phenotype through family and twin studies. We undertook a genome scan using 400 markers spaced approximately 10 cM in 600 individuals from Norfolk Island. Genotype data was analyzed using the variance components methods of SOLAR. Our results gave a peak LOD score of 2.01 localizing to chromosome 1p36 for systolic blood pressure and replicated previously implicated loci for other CVD relevant QTLs.

Quantitative and qualitative changes in gene expression patterns characterize the activity of plaques in multiple sclerosis

Multiple sclerosis (MS) is a complex autoimmune disorder of the CNS with both genetic and environmental contributing factors. Clinical symptoms are broadly characterized by initial onset, and progressive debilitating neurological impairment. In this study, RNA from MS chronic active and MS acute lesions was extracted, and compared with patient matched normal white matter by fluorescent cDNA microarray hybridization analysis. This resulted in the identification of 139 genes that were differentially regulated in MS plaque tissue compared to normal tissue. Of these, 69 genes showed a common pattern of expression in the chronic active and acute plaque tissues investigated (Pvalue<0.0001, ρ=0.73, by Spearman's ρ analysis); while 70 transcripts were uniquely differentially expressed (≥1.5-fold) in either acute or chronic active tissues. These results included known markers of MS such as the myelin basic protein (MBP) and glutathione S-transferase (GST) M1, nerve growth factors, such as nerve injury-induced protein 1 (NINJ1), X-ray and excision DNA repair factors (XRCC9 and ERCC5) and X-linked genes such as the ribosomal protein, RPS4X. Primers were then designed for seven array-selected genes, including transferrin (TF), superoxide dismutase 1 (SOD1), glutathione peroxidase 1 (GPX1), GSTP1, crystallin, alpha-B (CRYAB), phosphomannomutase 1 (PMM1) and tubulin β-5 (TBB5), and real time quantitative (Q)-PCR analysis was performed. The results of comparative Q-PCR analysis correlated significantly with those obtained by array analysis (r=0.75, Pvalue<0.01, by Pearson's bivariate correlation). Both chronic active and acute plaques shared the majority of factors identified suggesting that quantitative, rather than gross qualitative differences in gene expression pattern may define the progression from acute to chronic active plaques in MS.

Design, implementation and multisite evaluation of a system suitability protocol for the quantitative assessment of instrument performance in liquid chromatography-multiple reaction monitoring-MS (LC-MRM-MS)

Multiple reaction monitoring (MRM) mass spectrometry coupled with stable isotope dilution (SID) and liquid chromatography (LC) is increasingly used in biological and clinical studies for precise and reproducible quantification of peptides and proteins in complex sample matrices. Robust LC-SID-MRM-MS-based assays that can be replicated across laboratories and ultimately in clinical laboratory settings require standardized protocols to demonstrate that the analysis platforms are performing adequately. We developed a system suitability protocol (SSP), which employs a predigested mixture of six proteins, to facilitate performance evaluation of LC-SID-MRM-MS instrument platforms, configured with nanoflow-LC systems interfaced to triple quadrupole mass spectrometers. The SSP was designed for use with low multiplex analyses as well as high multiplex approaches when software-driven scheduling of data acquisition is required. Performance was assessed by monitoring of a range of chromatographic and mass spectrometric metrics including peak width, chromatographic resolution, peak capacity, and the variability in peak area and analyte retention time (RT) stability. The SSP, which was evaluated in 11 laboratories on a total of 15 different instruments, enabled early diagnoses of LC and MS anomalies that indicated suboptimal LC-MRM-MS performance. The observed range in variation of each of the metrics scrutinized serves to define the criteria for optimized LC-SID-MRM-MS platforms for routine use, with pass/fail criteria for system suitability performance measures defined as peak area coefficient of variation <0.15, peak width coefficient of variation <0.15, standard deviation of RT <0.15 min (9 s), and the RT drift <0.5min (30 s). The deleterious effect of a marginally performing LC-SID-MRM-MS system on the limit of quantification (LOQ) in targeted quantitative assays illustrates the use and need for a SSP to establish robust and reliable system performance. Use of a SSP helps to ensure that analyte quantification measurements can be replicated with good precision within and across multiple laboratories and should facilitate more widespread use of MRM-MS technology by the basic biomedical and clinical laboratory research communities.

Quantitative estimation of bioturbation based on digital image analysis

Quantitative determination of modification of primary sediment features, by the activity of organisms (i.e., bioturbation) is essential in geosciences. Some methods proposed since the 1960s are mainly based on visual or subjective determinations. The first semiquantitative evaluations of the Bioturbation Index, Ichnofabric Index, or the amount of bioturbation were attempted, in the best cases using a series of flashcards designed in different situations. Recently, more effective methods involve the use of analytical and computational methods such as X-rays, magnetic resonance imaging or computed tomography; these methods are complex and often expensive. This paper presents a compilation of different methods, using Adobe® Photoshop® software CS6, for digital estimation that are a part of the IDIAP (Ichnological Digital Analysis Images Package), which is an inexpensive alternative to recently proposed methods, easy to use, and especially recommended for core samples. The different methods — “Similar Pixel Selection Method (SPSM)”, “Magic Wand Method (MWM)” and the “Color Range Selection Method (CRSM)” — entail advantages and disadvantages depending on the sediment (e.g., composition, color, texture, porosity, etc.) and ichnological features (size of traces, infilling material, burrow wall, etc.). The IDIAP provides an estimation of the amount of trace fossils produced by a particular ichnotaxon, by a whole ichnocoenosis or even for a complete ichnofabric. We recommend the application of the complete IDIAP to a given case study, followed by selection of the most appropriate method. The IDIAP was applied to core material recovered from the IODP Expedition 339, enabling us, for the first time, to arrive at a quantitative estimation of the discrete trace fossil assemblage in core samples.

Mapping eQTLs in the Norfolk Island genetic isolate identifies candidate genes for CVD risk traits

Cardiovascular disease (CVD) affects millions of people worldwide and is influenced by numerous factors, including lifestyle and genetics. Expression quantitative trait loci (eQTLs) influence gene expression and are good candidates for CVD risk. Founder-effect pedigrees can provide additional power to map genes associated with disease risk. Therefore, we identified eQTLs in the genetic isolate of Norfolk Island (NI) and tested for associations between these and CVD risk factors. We measured genome-wide transcript levels of blood lymphocytes in 330 individuals and used pedigree-based heritability analysis to identify heritable transcripts. eQTLs were identified by genome-wide association testing of these transcripts. Testing for association between CVD risk factors (i.e., blood lipids, blood pressure, and body fat indices) and eQTLs revealed 1,712 heritable transcripts (p < 0.05) with heritability values ranging from 0.18 to 0.84. From these, we identified 200 cis-acting and 70 trans-acting eQTLs (p < 1.84 × 10(-7)) An eQTL-centric analysis of CVD risk traits revealed multiple associations, including 12 previously associated with CVD-related traits. Trait versus eQTL regression modeling identified four CVD risk candidates (NAAA, PAPSS1, NME1, and PRDX1), all of which have known biological roles in disease. In addition, we implicated several genes previously associated with CVD risk traits, including MTHFR and FN3KRP. We have successfully identified a panel of eQTLs in the NI pedigree and used this to implicate several genes in CVD risk. Future studies are required for further assessing the functional importance of these eQTLs and whether the findings here also relate to outbred populations.

Coordination and plasticity in leaf anatomical traits of invasive and native vine species

Premise of the study: Plant invasiveness can be promoted by higher values of adaptive traits (e.g., photosynthetic capacity, biomass accumulation), greater plasticity and coordination of these traits, and by higher and positive relative influence of these functionalities on fitness, such as increasing reproductive output. However, the dataset for this premise rarely include linkages between epidermal-stomatal traits, leaf internal anatomy, and physiological performance. Methods: Three ecological pairs of invasive vs non-invasive (native) woody vine species of South-East Queensland, Australia were investigated for trait differences in leaf morphology and anatomy under varying light intensity. The linkages of these traits with physiological performance (e.g. water use efficiency, photosynthesis, and leaf construction cost) and plant adaptive traits of specific leaf area, biomass, and relative growth rates were also explored. Key results: Mean leaf anatomical trait differed significantly between the two groups, except for stomatal size. Plasticity of traits, and to a very limited extent, their phenotypic integration were higher in the invasive relative to the native species. ANOVA, ordination, and analysis of similarity suggest that for leaf morphology and anatomy, the three functional strategies contribute to the differences between the two groups in the order phenotypic plasticity > trait means > phenotypic integration. Conclusions: The linkages demonstrated in the study between stomatal complex/gross anatomy and physiology are scarce in the ecological literature of plant invasiveness, but the findings suggest that leaf anatomical traits need to be considered routinely as part of weed species assessment and in the worldwide leaf economic spectrum.

Large-scale interlaboratory study to develop, analytically validate and apply highly multiplexed, quantitative peptide assays to measure cancer-relevant proteins in plasma

There is an increasing need in biology and clinical medicine to robustly and reliably measure tens-to-hundreds of peptides and proteins in clinical and biological samples with high sensitivity, specificity, reproducibility and repeatability. Previously, we demonstrated that LC-MRM-MS with isotope dilution has suitable performance for quantitative measurements of small numbers of relatively abundant proteins in human plasma, and that the resulting assays can be transferred across laboratories while maintaining high reproducibility and quantitative precision. Here we significantly extend that earlier work, demonstrating that 11 laboratories using 14 LC-MS systems can develop, determine analytical figures of merit, and apply highly multiplexed MRM-MS assays targeting 125 peptides derived from 27 cancer-relevant proteins and 7 control proteins to precisely and reproducibly measure the analytes in human plasma. To ensure consistent generation of high quality data we incorporated a system suitability protocol (SSP) into our experimental design. The SSP enabled real-time monitoring of LC-MRM-MS performance during assay development and implementation, facilitating early detection and correction of chromatographic and instrumental problems. Low to sub-nanogram/mL sensitivity for proteins in plasma was achieved by one-step immunoaffinity depletion of 14 abundant plasma proteins prior to analysis. Median intra- and inter-laboratory reproducibility was <20%, sufficient for most biological studies and candidate protein biomarker verification. Digestion recovery of peptides was assessed and quantitative accuracy improved using heavy isotope labeled versions of the proteins as internal standards. Using the highly multiplexed assay, participating laboratories were able to precisely and reproducibly determine the levels of a series of analytes in blinded samples used to simulate an inter-laboratory clinical study of patient samples. Our study further establishes that LC-MRM-MS using stable isotope dilution, with appropriate attention to analytical validation and appropriate quality c`ontrol measures, enables sensitive, specific, reproducible and quantitative measurements of proteins and peptides in complex biological matrices such as plasma.

Genomic architecture of ecologically divergent body shape in a pair of sympatric crater lake cichlid fishes

Determining the genetic bases of adaptations and their roles in speciation is a prominent issue in evolutionary biology. Cichlid fish species flocks are a prime example of recent rapid radiations, often associated with adaptive phenotypic divergence from a common ancestor within a short period of time. In several radiations of freshwater fishes, divergence in ecomorphological traits - including body shape, colour, lips and jaws - is thought to underlie their ecological differentiation, specialization and, ultimately, speciation. The Midas cichlid species complex (Amphilophus spp.) of Nicaragua provides one of the few known examples of sympatric speciation where species have rapidly evolved different but parallel morphologies in young crater lakes. This study identified significant QTL for body shape using SNPs generated via ddRAD sequencing and geometric morphometric analyses of a cross between two ecologically and morphologically divergent, sympatric cichlid species endemic to crater Lake Apoyo: an elongated limnetic species (Amphilophus zaliosus) and a high-bodied benthic species (Amphilophus astorquii). A total of 453 genome-wide informative SNPs were identified in 240 F-2 hybrids. These markers were used to construct a genetic map in which 25 linkage groups were resolved. Seventy-two segregating SNPs were linked to 11 QTL. By annotating the two most highly supported QTL-linked genomic regions, genes that might contribute to divergence in body shape along the benthic-limnetic axis in Midas cichlid sympatric adaptive radiations were identified. These results suggest that few genomic regions of large effect contribute to early stage divergence in Midas cichlids.

Identification of major loci controlling clinical manifestations of ankylosing spondylitis

Objective. To identify genomic regions linked with determinants of age at symptom onset, disease activity, and functional impairment in ankylosing spondylitis (AS). Methods. A whole genome linkage scan was performed in 188 affected sibling pair families with 454 affected individuals. Traits assessed were age at symptom onset, disease activity assessed by the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), and functional impairment assessed by the Bath Ankylosing Spondylitis Functional Index (BASFI). Parametric and nonparametric quantitative linkage analysis was performed using parameters defined in a previous segregation study. Results. Heritabilities of the traits studied in this data set were as follows: BASDAI 0.49 (P = 0.0001, 95% confidence interval [95% CI] 0.23-0.75), BASFI 0.76 (P = 10-7, 95% CI 0.49-1.0), and age at symptom onset 0.33 (P = 0.005, 95% CI 0.04-0.62). No linkage was observed between the major histocompatibility complex (MHC) and any of the traits studied (logarithm of odds [LOD] score <1.0). "Significant" linkage (LOD score 4.0) was observed between a region on chromosome 18p and the BASDAI. Age at symptom onset showed "suggestive" linkage to chromosome 11p (LOD score 3.3). Maximum linkage with the BASFI was seen at chromosome 2q (LOD score 2.9). Conclusion. In contrast to the genetic determinants of susceptibility to AS, clinical manifestations of the disease measured by the BASDAI, BASFI, and age at symptom onset are largely determined by a small number of genes not encoded within the MHC.

Genome-wide association study for radiographic vertebral fractures: A potential role for the 16q24 BMD locus

Vertebral fracture risk is a heritable complex trait. The aim of this study was to identify genetic susceptibility factors for osteoporotic vertebral fractures applying a genome-wide association study (GWAS) approach. The GWAS discovery was based on the Rotterdam Study, a population-based study of elderly Dutch individuals aged >55years; and comprising 329 cases and 2666 controls with radiographic scoring (McCloskey-Kanis) and genetic data. Replication of one top-associated SNP was pursued by de-novo genotyping of 15 independent studies across Europe, the United States, and Australia and one Asian study. Radiographic vertebral fracture assessment was performed using McCloskey-Kanis or Genant semi-quantitative definitions. SNPs were analyzed in relation to vertebral fracture using logistic regression models corrected for age and sex. Fixed effects inverse variance and Han-Eskin alternative random effects meta-analyses were applied. Genome-wide significance was set at p<5×10-8. In the discovery, a SNP (rs11645938) on chromosome 16q24 was associated with the risk for vertebral fractures at p=4.6×10-8. However, the association was not significant across 5720 cases and 21,791 controls from 14 studies. Fixed-effects meta-analysis summary estimate was 1.06 (95% CI: 0.98-1.14; p=0.17), displaying high degree of heterogeneity (I2=57%; Qhet p=0.0006). Under Han-Eskin alternative random effects model the summary effect was significant (p=0.0005). The SNP maps to a region previously found associated with lumbar spine bone mineral density (LS-BMD) in two large meta-analyses from the GEFOS consortium. A false positive association in the GWAS discovery cannot be excluded, yet, the low-powered setting of the discovery and replication settings (appropriate to identify risk effect size >1.25) may still be consistent with an effect size <1.10, more of the type expected in complex traits. Larger effort in studies with standardized phenotype definitions is needed to confirm or reject the involvement of this locus on the risk for vertebral fractures.

Genetics of rheumatoid arthritis contributes to biology and drug discovery

A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological data sets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA)1. Here we performed a genome-wide association study meta-analysis in a total of >100,000 subjects of European and Asian ancestries (29,880 RA cases and 73,758 controls), by evaluating ~10 million single-nucleotide polymorphisms. We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 101 (refs 2, 3, 4). We devised an in silico pipeline using established bioinformatics methods based on functional annotation5, cis-acting expression quantitative trait loci6 and pathway analyses7, 8, 9—as well as novel methods based on genetic overlap with human primary immunodeficiency, haematological cancer somatic mutations and knockout mouse phenotypes—to identify 98 biological candidate genes at these 101 risk loci. We demonstrate that these genes are the targets of approved therapies for RA, and further suggest that drugs approved for other indications may be repurposed for the treatment of RA. Together, this comprehensive genetic study sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis, and provides empirical evidence that the genetics of RA can provide important information for drug discovery.

Genetic insights into common pathways and complex relationships among iImmune-mediated diseases

Shared aetiopathogenic factors among immune-mediated diseases have long been suggested by their co-familiality and co-occurrence, and molecular support has been provided by analysis of human leukocyte antigen (HLA) haplotypes and genome-wide association studies. The interrelationships can now be better appreciated following the genotyping of large immune disease sample sets on a shared SNP array: the 'Immunochip'. Here, we systematically analyse loci shared among major immune-mediated diseases. This reveals that several diseases share multiple susceptibility loci, but there are many nuances. The most associated variant at a given locus frequently differs and, even when shared, the same allele often has opposite associations. Interestingly, risk alleles conferring the largest effect sizes are usually disease-specific. These factors help to explain why early evidence of extensive 'sharing' is not always reflected in epidemiological overlap. © 2013 Macmillan Publishers Limited. All rights reserved.

Domestication to crop improvement: Genetic resources for Sorghum and Saccharum (Andropogoneae).

Background: Both sorghum (Sorghum bicolor) and sugarcane (Saccharum officinarum) are members of the Andropogoneae tribe in the Poaceae and are each other's closest relatives amongst cultivated plants. Both are relatively recent domesticates and comparatively little of the genetic potential of these taxa and their wild relatives has been captured by breeding programmes to date. This review assesses the genetic gains made by plant breeders since domestication and the progress in the characterization of genetic resources and their utilization in crop improvement for these two related species. Genetic Resources: The genome of sorghum has recently been sequenced providing a great boost to our knowledge of the evolution of grass genomes and the wealth of diversity within S. bicolor taxa. Molecular analysis of the Sorghum genus has identified close relatives of S. bicolor with novel traits, endosperm structure and composition that may be used to expand the cultivated gene pool. Mutant populations (including TILLING populations) provide a useful addition to genetic resources for this species. Sugarcane is a complex polyploid with a large and variable number of copies of each gene. The wild relatives of sugarcane represent a reservoir of genetic diversity for use in sugarcane improvement. Techniques for quantitative molecular analysis of gene or allele copy number in this genetically complex crop have been developed. SNP discovery and mapping in sugarcane has been advanced by the development of high-throughput techniques for ecoTILLING in sugarcane. Genetic linkage maps of the sugarcane genome are being improved for use in breeding selection. The improvement of both sorghum and sugarcane will be accelerated by the incorporation of more diverse germplasm into the domesticated gene pools using molecular tools and the improved knowledge of these genomes.