Linkage and heritability analysis of migraine symptom groupings: A comparison of three different clustering methods on twin data

Migraine is a painful disorder for which the etiology remains obscure. Diagnosis is largely based on International Headache Society criteria. However, no feature occurs in all patients who meet these criteria, and no single symptom is required for diagnosis. Consequently, this definition may not accurately reflect the phenotypic heterogeneity or genetic basis of the disorder. Such phenotypic uncertainty is typical for complex genetic disorders and has encouraged interest in multivariate statistical methods for classifying disease phenotypes. We applied three popular statistical phenotyping methods—latent class analysis, grade of membership and grade of membership “fuzzy” clustering (Fanny)—to migraine symptom data, and compared heritability and genome-wide linkage results obtained using each approach. Our results demonstrate that different methodologies produce different clustering structures and non-negligible differences in subsequent analyses. We therefore urge caution in the use of any single approach and suggest that multiple phenotyping methods be used.

High-throughput Phenotyping of Wheat Seminal Root Traits in a Breeding Context

Water availability is a major limiting factor for wheat (Triticum aestivum L.) in rain-fed agricultural systems worldwide. Root architecture has important functional implications for the timing and extent of soil water extraction, yet selection for root traits in wheat breeding programs has been largely limited due to the lack of suitable phenotyping methods. The aim of this research was to develop a low-cost high-throughput phenotyping method to facilitate selection for desirable root traits. We developed a method to assess ‘seminal root angle’ and ‘seminal root number’ in seedlings – two proxy traits associated to root architecture of mature wheat plants (1). The method involves measuring the angle between the first pair of seminal roots and the number of roots of wheat seedlings grown in transparent pots (Figure 1). Images captured at 5 to 10 days after sowing are analyzed to calculate seminal root angle and number. Performing this technique under “speed breeding” conditions (plants grown at a density of 600 plants / m2, under controlled temperature and constant light) allows the selection based on the desired root traits of up to 5 consecutive generations within 12 months. Alternatively, when focusing only on germplasm screening, up to 52 successive phenotypic assays can be conducted within 12 months. This approach has been shown to be highly reproducible, it requires little resource (time, space, and labour) and can be used to rapidly enrich breeding populations with desirable alleles for narrow root angle and a high number of seminal roots to indirectly target the selection of deeper root system with higher branching at depth. Such root characteristics are highly desirable in wheat to cope with the climate model projections, especially in summer rainfall dominant regions including some Australian, Indian, South American and African cropping regions, where winter crops mainly rely on deep stored water.

High-throughput root phenotyping screens identify genetic loci associated with root architectural traits in Brassica napus under contrasting phosphate availabilities

Background and Aims: Phosphate (Pi) deficiency in soils is a major limiting factor for crop growth worldwide. Plant growth under low Pi conditions correlates with root architectural traits and it may therefore be possible to select these traits for crop improvement. The aim of this study was to characterize root architectural traits, and to test quantitative trait loci (QTL) associated with these traits, under low Pi (LP) and high Pi (HP) availability in Brassica napus. Methods: Root architectural traits were characterized in seedlings of a double haploid (DH) mapping population (n = 190) of B. napus 'Tapidor' x 'Ningyou 7' (TNDH) using high-throughput phenotyping methods. Primary root length (PRL), lateral root length (LRL), lateral root number (LRN), lateral root density (LRD) and biomass traits were measured 12 d post-germination in agar at LP and HP. Key Results: In general, root and biomass traits were highly correlated under LP and HP conditions. 'Ningyou 7' had greater LRL, LRN and LRD than 'Tapidor', at both LP and HP availability, but smaller PRL. A cluster of highly significant QTL for LRN, LRD and biomass traits at LP availability were identified on chromosome A03; QTL for PRL were identified on chromosomes A07 and C06. Conclusions: High-throughput phenotyping of Brassica can be used to identify root architectural traits which correlate with shoot biomass. It is feasible that these traits could be used in crop improvement strategies. The identification of QTL linked to root traits under LP and HP conditions provides further insights on the genetic basis of plant tolerance to P deficiency, and these QTL warrant further dissection.

Identification of molecular genetic factors that influence migraine

Migraine is a common neurological disorder with a strong genetic basis. However, the complex nature of the disorder has meant that few genes or susceptibility loci have been identified and replicated consistently to confirm their involvement in migraine. Approaches to genetic studies of the disorder have included analysis of the rare migraine subtype, familial hemiplegic migraine with several causal genes identified for this severe subtype. However, the exact genetic contributors to the more common migraine subtypes are still to be deciphered. Genome-wide studies such as genome-wide association studies and linkage analysis as well as candidate genes studies have been employed to investigate genes involved in common migraine. Neurological, hormonal and vascular genes are all considered key factors in the pathophysiology of migraine and are a focus of many of these studies. It is clear that the influence of individual genes on the expression of this disorder will vary. Furthermore, the disorder may be dependent on gene–gene and gene–environment interactions that have not yet been considered. In addition, identifying susceptibility genes may require phenotyping methods outside of the International Classification of Headache Disorders II criteria, such as trait component analysis and latent class analysis to better define the ambit of migraine expression.

Consistently replicating locus linked to migraine on 10q22-q23

Here, we present the results of two genome-wide scans in two diverse populations in which a consistent use of recently introduced migraine-phenotyping methods detects and replicates a locus on 10q22-q23, with an additional independent replication. No genetic variants have been convincingly established in migraine, and although several loci have been reported, none of them has been consistently replicated. We employed the three known migraine-phenotyping methods (clinical end diagnosis, latent-class analysis, and trait-component analysis) with robust multiple testing correction in a large sample set of 1675 individuals from 210 migraine families from Finland and Australia. Genome-wide multipoint linkage analysis that used the Kong and Cox exponential model in Finns detected a locus on 10q22-q23 with highly significant evidence of linkage (LOD 7.68 at 103 cM in female-specific analysis). The Australian sample showed a LOD score of 3.50 at the same locus (100 cM), as did the independent Finnish replication study (LOD score 2.41, at 102 cM). In addition, four previously reported loci on 8q21, 14q21, 18q12, and Xp21 were also replicated. A shared-segment analysis of 10q22-q23 linked Finnish families identified a 1.6-9.5 cM segment, centered on 101 cM, which shows in-family homology in 95% of affected Finns. This region was further studied with 1323 SNPs. Although no significant association was observed, four regions warranting follow-up studies were identified. These results support the use of symptomology-based phenotyping in migraine and suggest that the 10q22-q23 locus probably contains one or more migraine susceptibility variants.

Molecular Breeding for Complex Adaptive Traits: How Integrating Crop Ecophysiology and Modelling Can Enhance Efficiency

Progress in crop improvement is limited by the ability to identify favourable combinations of genotypes (G) and management practices (M) in relevant target environments (E) given the resources available to search among the myriad of possible combinations. To underpin yield advance we require prediction of phenotype based on genotype. In plant breeding, traditional phenotypic selection methods have involved measuring phenotypic performance of large segregating populations in multi-environment trials and applying rigorous statistical procedures based on quantitative genetic theory to identify superior individuals. Recent developments in the ability to inexpensively and densely map/sequence genomes have facilitated a shift from the level of the individual (genotype) to the level of the genomic region. Molecular breeding strategies using genome wide prediction and genomic selection approaches have developed rapidly. However, their applicability to complex traits remains constrained by gene-gene and gene-environment interactions, which restrict the predictive power of associations of genomic regions with phenotypic responses. Here it is argued that crop ecophysiology and functional whole plant modelling can provide an effective link between molecular and organism scales and enhance molecular breeding by adding value to genetic prediction approaches. A physiological framework that facilitates dissection and modelling of complex traits can inform phenotyping methods for marker/gene detection and underpin prediction of likely phenotypic consequences of trait and genetic variation in target environments. This approach holds considerable promise for more effectively linking genotype to phenotype for complex adaptive traits. Specific examples focused on drought adaptation are presented to highlight the concepts.

Polimorfismos del gen Butirilcolinesterasa responsables de reacciones adversas en pacientes consumidores de “cocaína”

La butirilcolinesterasa humana (BChE; EC 3.1.1.8) es una enzima polimórfica sintetizada en el hígado y en el tejido adiposo, ampliamente distribuida en el organismo y encargada de hidrolizar algunos ésteres de colina como la procaína, ésteres alifáticos como el ácido acetilsalicílico, fármacos como la metilprednisolona, el mivacurium y la succinilcolina y drogas de uso y/o abuso como la heroína y la cocaína. Es codificada por el gen BCHE (OMIM 177400), habiéndose identificado más de 100 variantes, algunas no estudiadas plenamente, además de la forma más frecuente, llamada usual o silvestre. Diferentes polimorfismos del gen BCHE se han relacionado con la síntesis de enzimas con niveles variados de actividad catalítica. Las bases moleculares de algunas de esas variantes genéticas han sido reportadas, entre las que se encuentra las variantes Atípica (A), fluoruro-resistente del tipo 1 y 2 (F-1 y F-2), silente (S), Kalow (K), James (J) y Hammersmith (H). En este estudio, en un grupo de pacientes se aplicó el instrumento validado Lifetime Severity Index for Cocaine Use Disorder (LSI-C) para evaluar la gravedad del consumo de “cocaína” a lo largo de la vida. Además, se determinaron Polimorfismos de Nucleótido Simple (SNPs) en el gen BCHE conocidos como responsables de reacciones adversas en pacientes consumidores de “cocaína” mediante secuenciación del gen y se predijo el efecto delos SNPs sobre la función y la estructura de la proteína, mediante el uso de herramientas bio-informáticas. El instrumento LSI-C ofreció resultados en cuatro dimensiones: consumo a lo largo de la vida, consumo reciente, dependencia psicológica e intento de abandono del consumo. Los estudios de análisis molecular permitieron observar dos SNPs codificantes (cSNPs) no sinónimos en el 27.3% de la muestra, c.293A>G (p.Asp98Gly) y c.1699G>A (p.Ala567Thr), localizados en los exones 2 y 4, que corresponden, desde el punto de vista funcional, a la variante Atípica (A) [dbSNP: rs1799807] y a la variante Kalow (K) [dbSNP: rs1803274] de la enzima BChE, respectivamente. Los estudios de predicción In silico establecieron para el SNP p.Asp98Gly un carácter patogénico, mientras que para el SNP p.Ala567Thr, mostraron un comportamiento neutro. El análisis de los resultados permite proponer la existencia de una relación entre polimorfismos o variantes genéticas responsables de una baja actividad catalítica y/o baja concentración plasmática de la enzima BChE y algunas de las reacciones adversas ocurridas en pacientes consumidores de cocaína.

Fenotipagem para estudos de estudos de tolerância à deficiência hídrica em eucalipto

Pós-graduação em Agronomia (Genética e Melhoramento de Plantas) - FCAV

Risk factors for infection with coagulase-negative staphylococci in newborns from the neonatal unit of a brazilian university hospital

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Image Analysis Methods for Sugar Beet Phenotyping

In un mondo che richiede sempre maggiormente un'automazione delle attività della catena produttiva industriale, la computer vision rappresenta uno strumento fondamentale perciò che viene già riconosciuta internazionalmente come la Quarta Rivoluzione Industriale o Industry 4.0. Avvalendomi di questo strumento ho intrapreso presso l'azienda Syngenta lo studio della problematica della conta automatica del numero di foglie di una pianta. Il problema è stato affrontato utilizzando due differenti approcci, ispirandosi alla letteratura. All'interno dell'elaborato è presente anche la descrizione progettuale di un ulteriore metodo, ad oggi non presente in letteratura. Le metodologie saranno spiegate in dettaglio ed i risultati ottenuti saranno confrontati utilizzando i primi due approcci. Nel capitolo finale si trarranno le conclusioni sulle basi dei risultati ottenuti e dall'analisi degli stessi.

Phenotyping cotton ovule fibre initiation with spatial statistics

Yield in cultivated cotton (Gossypium spp.) is affected by the number and distribution of fibres initiated on the seed surface but, apart from simple statistical summaries, little has been done to assess this phenotype quantitatively. Here we use two types of spatial statistics to describe and quantify differences in patterning of cotton ovule fibre initials (FI). The following five different species of Gossypium were analysed: G. hirsutum L., G. barbadense L., G. arboreum, G. raimondii Ulbrich. and G. trilobum (DC.) Skovsted. Scanning electron micrographs of FIs were taken on the day of anthesis. Cell centres for fibre and epidermal cells were digitised and analysed by spatial statistics methods appropriate for marked point processes and tessellations. Results were consistent with previously published reports of fibre number and spacing. However, it was shown that the spatial distributions of FIs in all of species examined exhibit regularity, and are not completely random as previously implied. The regular arrangement indicates FIs do not appear independently of each other and we surmise there may be some form of mutual inhibition specifying fibre-initial development. It is concluded that genetic control of FIs differs from that of stomata, another well studied plant idioblast. Since spatial statistics show clear species differences in the distribution of FIs within this genus, they provide a useful method for phenotyping cotton. © CSIRO 2007.

A multisite managed environment facility for targeted trait and germplasm phenotyping

Field evaluation of germplasm for performance under water and heat stress is challenging. Field environments are variable and unpredictable, and genotype x environment interactions are difficult to interpret if environments are not well characterised. Numerous traits, genes and quantitative trait loci have been proposed for improving performance but few have been used in variety development. This reflects the limited capacity of commercial breeding companies to screen for these traits and the absence of validation in field environments relevant to breeding companies, and because little is known about the economic benefit of selecting one particular trait over another. The value of the proposed traits or genes is commonly not demonstrated in genetic backgrounds of value to breeding companies. To overcome this disconnection between physiological trait breeding and uptake by breeding companies, three field sites representing the main environment types encountered across the Australian wheatbelt were selected to form a set of managed environment facilities (MEFs). Each MEF manages soil moisture stress through irrigation, and the effects of heat stress through variable sowing dates. Field trials are monitored continuously for weather variables and changes in soil water and canopy temperature in selected probe genotypes, which aids in decisions guiding irrigation scheduling and sampling times. Protocols have been standardised for an essential core set of measurements so that phenotyping yield and other traits are consistent across sites and seasons. MEFs enable assessment of a large number of traits across multiple genetic backgrounds in relevant environments, determine relative trait value, and facilitate delivery of promising germplasm and high value traits into commercial breeding programs.

Integrating Rapid Phenotyping and Speed Breeding to Improve Stay-Green and Root Adaptation of Wheat in Changing, Water-Limited, Australian Environments

Temperatures have increased and in-crop rainfall decreased over recent decades in many parts of the Australian wheat cropping region. With these trends set to continue or intensify, improving crop adaptation in the face of climate change is particularly urgent in this, already drought-prone, cropping region. Importantly, improved performance under water-limitation must be achieved while retaining yield potential during more favourable seasons. A multi-trait-based approach to improve wheat yield and yield stability in the face of water-limitation and heat has been instigated in northern Australia using novel phenotyping techniques and a nested association mapping (NAM) approach. An innovative laboratory technique allows rapid root trait screening of hundreds of lines. Using soil grown seedlings, the method offers significant advantages over many other lab-based techniques. Another recently developed method allows novel stay-green traits to be quantified objectively for hundreds of genotypes in standard field trial plots. Field trials in multiple locations and seasons allow evaluation of targeted trait values and identification of superior germplasm. Traits, including yield and yield components are measured for hundreds of NAM lines in rain fed environments under various levels of water-limitation. To rapidly generate lines of interest, the University of Queensland “speed breeding” method is being employed, allowing up to 7 plant generations per annum. A NAM population of over 1000 wheat recombinant inbred lines has been progressed to the F5 generation within 18 months. Genotyping the NAM lines with the genome-wide DArTseq molecular marker system provides up to 40,000 markers. They are now being used for association mapping to validate QTL previously identified in bi-parental populations and to identify novel QTL for stay-green and root traits. We believe that combining the latest techniques in physiology, phenotyping, genetics and breeding will increase genetic progress toward improved adaptation to water-limited environments.

Evaluation of methods and applications for behavioural profiling of transgenic mice

During the last 10-15 years interest in mouse behavioural analysis has evolved considerably. The driving force is development in molecular biological techniques that allow manipulation of the mouse genome by changing the expression of genes. Therefore, with some limitations it is possible to study how genes participate in regulation of physiological functions and to create models explaining genetic contribution to various pathological conditions. The first aim of our study was to establish a framework for behavioural phenotyping of genetically modified mice. We established comprehensive battery of tests for the initial screening of mutant mice. These included tests for exploratory and locomotor activity, emotional behaviour, sensory functions, and cognitive performance. Our interest was in the behavioural patterns of common background strains used for genetic manipulations in mice. Additionally we studied the behavioural effect of sex differences, test history, and individual housing. Our findings highlight the importance of careful consideration of genetic background for analysis of mutant mice. It was evident that some backgrounds may mask or modify the behavioural phenotype of mutants and thereby lead to false positive or negative findings. Moreover, there is no universal strain that is equally suitable for all tests, and using different backgrounds allows one to address possible phenotype modifying factors. We discovered that previous experience affected performance in several tasks. The most sensitive traits were the exploratory and emotional behaviour, as well as motor and nociceptive functions. Therefore, it may be essential to repeat some of the tests in naïve animals for assuring the phenotype. Social isolation for a long time period had strong effects on exploratory behaviour, but also on learning and memory. All experiments revealed significant interactions between strain and environmental factors (test history or housing condition) indicating genotype-dependent effects of environmental manipulations. Several mutant line analyses utilize this information. For example, we studied mice overexpressing as well as those lacking extracellular matrix protein heparin-binding growth-associated molecule (HB-GAM), and mice lacking N-syndecan (a receptor for HB-GAM). All mutant mice appeared to be fertile and healthy, without any apparent neurological or sensory defects. The lack of HB-GAM and N-syndecan, however, significantly reduced the learning capacity of the mice. On the other hand, overexpression of HB-GAM resulted in facilitated learning. Moreover, HB-GAM knockout mice displayed higher anxiety-like behaviour, whereas anxiety was reduced in HB-GAM overexpressing mice. Changes in hippocampal plasticity accompanied the behavioural phenotypes. We conclude that HB-GAM and N-syndecan are involved in the modulation of synaptic plasticity in hippocampus and play a role in regulation of anxiety- and learning-related behaviour.