Mutations causing premature termination codons discriminate and generate cellular and clinical variability in HHT.

ABSTRACT: For monogenic diseases caused by pathogenic loss-of-function DNA variants, attention focuses on dysregulated gene-specific pathways, usually considering molecular subtypes together within causal genes. To better understand phenotypic variability in hereditary hemorrhagic telangiectasia (HHT), we subcategorized pathogenic DNA variants in ENG/endoglin, ACVRL1/ALK1, and SMAD4 if they generated premature termination codons (PTCs) subject to nonsense-mediated decay. In 3 patient cohorts, a PTC-based classification system explained some previously puzzling hemorrhage variability. In blood outgrowth endothelial cells (BOECs) derived from patients with ACVRL1+/PTC, ENG+/PTC, and SMAD4+/PTC genotypes, PTC-containing RNA transcripts persisted at low levels (8%-23% expected, varying between replicate cultures); genes differentially expressed to Bonferroni P < .05 in HHT+/PTC BOECs clustered significantly only to generic protein terms (isopeptide-bond/ubiquitin-like conjugation) and pulse-chase experiments detected subtle protein maturation differences but no evidence for PTC-truncated protein. BOECs displaying highest PTC persistence were discriminated in unsupervised hierarchical clustering of near-invariant housekeeper genes, with patterns compatible with higher cellular stress in BOECs with >11% PTC persistence. To test directionality, we used a HeLa reporter system to detect induction of activating transcription factor 4 (ATF4), which controls expression of stress-adaptive genes, and showed that ENG Q436X but not ENG R93X directly induced ATF4. AlphaFold accurately modeled relevant ENG domains, with AlphaMissense suggesting that readthrough substitutions would be benign for ENG R93X and other less rare ENG nonsense variants but more damaging for Q436X. We conclude that PTCs should be distinguished from other loss-of-function variants, PTC transcript levels increase in stressed cells, and readthrough proteins and mechanisms provide promising research avenues.

Investigating the genetic control of plant development in spring barley under speed breeding conditions.

KEY MESSAGE: This study found that the genes, PPD-H1 and ELF3, control the acceleration of plant development under speed breeding, with important implications for optimizing the delivery of climate-resilient crops. Speed breeding is a tool to accelerate breeding and research programmes. Despite its success and growing popularity with breeders, the genetic basis of plant development under speed breeding remains unknown. This study explored the developmental advancements of barley genotypes under different photoperiod regimes. A subset of the HEB-25 Nested Association Mapping population was evaluated for days to heading and maturity under two contrasting photoperiod conditions: (1) Speed breeding (SB) consisting of 22 h of light and 2 h of darkness, and (2) normal breeding (NB) consisting of 16 h of light and 8 h of darkness. GWAS revealed that developmental responses under both conditions were largely controlled by two loci: PPDH-1 and ELF3. Allelic variants at these genes determine whether plants display early flowering and maturity under both conditions. At key QTL regions, domesticated alleles were associated with late flowering and maturity in NB and early flowering and maturity in SB, whereas wild alleles were associated with early flowering under both conditions. We hypothesize that this is related to the dark-dependent repression of PPD-H1 by ELF3 which might be more prominent in NB conditions. Furthermore, by comparing development under two photoperiod regimes, we derived an estimate of plasticity for the two traits. Interestingly, plasticity in development was largely attributed to allelic variation at ELF3. Our results have important implications for our understanding and optimization of speed breeding protocols particularly for introgression breeding and the design of breeding programmes to support the delivery of climate-resilient crops.

Medical Emergency Team call within 24 h of medical admission with a focus on sepsis: a retrospective review.

BACKGROUND AND AIMS: Clinical deterioration within the first 24 h of patient admission triggering a Medical Emergency Team (MET) call is a common occurrence. A greater understanding of these events, with a focus on the recognition and management of sepsis, could lead to quality improvement interventions. METHODS: A retrospective observational review of general and subspecialty medical admissions triggering a MET call within 24 h of admission at a quaternary Australian hospital. RESULTS: 2648 MET calls occurred (47.9/1000 admissions), 527 (20% of total MET events, 9.5/1000 admissions) within 24 h of admission, with the trigger more likely to be hypotension (odds ratio: 1.5, P = 0.0013). There were 263 MET calls to 217 individual medical patients within 24 h of admission, of which 84 (38.7%) were admitted with suspected infection, 69% of which fulfilled sepsis criteria. Of these, 36.2% received antimicrobial therapy within the recommended timeframe and 39.6% received antibiotics in line with hospital guidelines. Sepsis was initially missed in 11% of patients. Afferent limb failure occurred in 29% of patients with 40.5% experiencing a failure of the ward-based response to deterioration prior to MET call. Median hospital length of stay was increased in patients admitted with suspected infection (7 vs 5 days, P = 0.015) and in those with sepsis not receiving antimicrobial therapy within guideline timeframes (9 vs 4 days, P = 0.017). CONCLUSION: There is a significant opportunity to improve care for patients who trigger a MET within 24 h of admission. This study supports the implementation of a hospital sepsis management guideline.

Evaluating the impact of a national geriatric mental health ECHO educational program on healthcare providers' practice.

Project Extension for Community Healthcare Outcomes (ECHO) enables healthcare providers to share knowledge and best practices via telementoring. The ECHO model builds provider capacity and improves care for patients with a variety of health conditions. This study describes a Canada-wide National ECHO pilot project in the area of geriatric mental health and reports on the program's impact on providers' care practices. A mixed-methods approach was used to analyze surveys completed by participating healthcare providers. Program evaluation measured satisfaction, achievement of learning objectives, awareness of issues related to geriatric mental health, and comfort and self-efficacy working with older adults. The program led to a statistically significant increase in participants' awareness of issues related to support for older adults with mental illness and comfort and self-efficacy in managing these patients in their own practice. The National ECHO pilot project was successful in building healthcare providers' capacity to care for older adults with mental health issues and positively impacting their practice. These findings support using the ECHO model to provide ongoing geriatric mental health education for clinicians from across Canada and beyond.

Analysis of historical selection in winter wheat.

KEY MESSAGE: Modeling of the distribution of allele frequency over year of variety release identifies major loci involved in historical breeding of winter wheat. Winter wheat is a major crop with a rich selection history in the modern era of crop breeding. Genetic gains across economically important traits like yield have been well characterized and are the major force driving its production. Winter wheat is also an excellent model for analyzing historical genetic selection. As a proof of concept, we analyze two major collections of winter wheat varieties that were bred in Western Europe from 1916 to 2010, namely the Triticeae Genome (TG) and WAGTAIL panels, which include 333 and 403 varieties, respectively. We develop and apply a selection mapping approach, Regression of Alleles on Years (RALLY), in these panels, as well as in simulated populations. RALLY maps loci under sustained historical selection by using a simple logistic model to regress allele counts on years of variety release. To control for drift-induced allele frequency change, we develop a hybrid approach of genomic control and delta control. Within the TG panel, we identify 22 significant RALLY quantitative selection loci (QSLs) and estimate the local heritabilities for 12 traits across these QSLs. By correlating predicted marker effects with RALLY regression estimates, we show that alleles whose frequencies have increased over time are heavily biased toward conferring positive yield effect, but negative effects in flowering time, lodging, plant height and grain protein content. Altogether, our results (1) demonstrate the use of RALLY to identify selected genomic regions while controlling for drift, and (2) reveal key patterns in the historical selection in winter wheat and guide its future breeding.

The evolving battle between yellow rust and wheat: implications for global food security.

Wheat (Triticum aestivum L.) is a global commodity, and its production is a key component underpinning worldwide food security. Yellow rust, also known as stripe rust, is a wheat disease caused by the fungus Puccinia striiformis Westend f. sp. tritici (Pst), and results in yield losses in most wheat growing areas. Recently, the rapid global spread of genetically diverse sexually derived Pst races, which have now largely replaced the previous clonally propagated slowly evolving endemic populations, has resulted in further challenges for the protection of global wheat yields. However, advances in the application of genomics approaches, in both the host and pathogen, combined with classical genetic approaches, pathogen and disease monitoring, provide resources to help increase the rate of genetic gain for yellow rust resistance via wheat breeding while reducing the carbon footprint of the crop. Here we review key elements in the evolving battle between the pathogen and host, with a focus on solutions to help protect future wheat production from this globally important disease.

Wheat genetic loci conferring resistance to stripe rust in the face of genetically diverse races of the fungus Puccinia striiformis f. sp. tritici.

KEY MESSAGE: Analysis of a wheat multi-founder population identified 14 yellow rust resistance QTL. For three of the four most significant QTL, haplotype analysis indicated resistance alleles were rare in European wheat. Stripe rust, or yellow rust (YR), is a major fungal disease of wheat (Triticum aestivum) caused by Puccinia striiformis Westend f. sp. tritici (Pst). Since 2011, the historically clonal European Pst races have been superseded by the rapid incursion of genetically diverse lineages, reducing the resistance of varieties previously showing durable resistance. Identification of sources of genetic resistance to such races is a high priority for wheat breeding. Here we use a wheat eight-founder multi-parent population genotyped with a 90,000 feature single nucleotide polymorphism array to genetically map YR resistance to such new Pst races. Genetic analysis of five field trials at three UK sites identified 14 quantitative trait loci (QTL) conferring resistance. Of these, four highly significant loci were consistently identified across all test environments, located on chromosomes 1A (QYr.niab-1A.1), 2A (QYr.niab-2A.1), 2B (QYr.niab-2B.1) and 2D (QYr.niab-2D.1), together explaining ~ 50% of the phenotypic variation. Analysis of these four QTL in two-way and three-way combinations showed combinations conferred greater resistance than single QTL, and genetic markers were developed that distinguished resistant and susceptible alleles. Haplotype analysis in a collection of wheat varieties found that the haplotypes associated with YR resistance at three of these four major loci were rare (≤ 7%) in European wheat, highlighting their potential utility for future targeted improvement of disease resistance. Notably, the physical interval for QTL QYr.niab-2B.1 contained five nucleotide-binding leucine-rich repeat candidate genes with integrated BED domains, of which two corresponded to the cloned resistance genes Yr7 and Yr5/YrSp.

Trends of genetic changes uncovered by Env- and Eigen-GWAS in wheat and barley.

KEY MESSAGE: Variety age and population structure detect novel QTL for yield and adaptation in wheat and barley without the need to phenotype. The process of crop breeding over the last century has delivered new varieties with increased genetic gains, resulting in higher crop performance and yield. However, in many cases, the alleles and genomic regions underpinning this success remain unknown. This is partly due to the difficulty of generating sufficient phenotypic data on large numbers of historical varieties to enable such analyses. Here we demonstrate the ability to circumvent such bottlenecks by identifying genomic regions selected over 100 years of crop breeding using age of a variety as a surrogate for yield. Rather than collecting phenotype data, we deployed 'environmental genome-wide association scans' (EnvGWAS) based on variety age in two of the world's most important crops, wheat and barley, and detected strong signals of selection across both genomes. EnvGWAS identified 16 genomic regions in barley and 10 in wheat with contrasting patterns between spring and winter types of the two crops. To further examine changes in genome structure, we used the genomic relationship matrix of the genotypic data to derive eigenvectors for analysis in EigenGWAS. This detected seven major chromosomal introgressions that contributed to adaptation in wheat. EigenGWAS and EnvGWAS based on variety age avoid costly phenotyping and facilitate the identification of genomic tracts that have been under selection during breeding. Our results demonstrate the potential of using historical cultivar collections coupled with genomic data to identify chromosomal regions under selection and may help guide future plant breeding strategies to maximise the rate of genetic gain and adaptation.

A large-scale pedigree resource of wheat reveals evidence for adaptation and selection by breeders.

Information on crop pedigrees can be used to help maximise genetic gain in crop breeding and allow efficient management of genetic resources. We present a pedigree resource of 2,657 wheat (Triticum aestivum L.) genotypes originating from 38 countries, representing more than a century of breeding and variety development. Visualisation of the pedigree enables illustration of the key developments in United Kingdom wheat breeding, highlights the wide genetic background of the UK wheat gene pool, and facilitates tracing the origin of beneficial alleles. A relatively high correlation between pedigree- and marker-based kinship coefficients was found, which validated the pedigree and enabled identification of errors in the pedigree or marker data. Using simulations with a combination of pedigree and genotype data, we found evidence for significant effects of selection by breeders. Within crosses, genotypes are often more closely related than expected by simulations to one of the parents, which indicates selection for favourable alleles during the breeding process. Selection across the pedigree was demonstrated on a subset of the pedigree in which 110 genotyped varieties released before the year 2000 were used to simulate the distribution of marker alleles of 45 genotyped varieties released after the year 2000, in the absence of selection. Allelic diversity in the 45 varieties was found to deviate significantly from the simulated distributions at a number of loci, indicating regions under selection over this period. The identification of one of these regions as coinciding with a strong yield component quantitative trait locus (QTL) highlights both the potential of the remaining loci as wheat breeding targets for further investigation, as well as the utility of this pedigree-based methodology to identify important breeding targets in other crops. Further evidence for selection was found as greater linkage disequilibrium (LD) for observed versus simulated genotypes within all chromosomes. This difference was greater at shorter genetic distances, indicating that breeder selections have conserved beneficial linkage blocks. Collectively, this work highlights the benefits of generating detailed pedigree resources for crop species. The wheat pedigree database developed here represents a valuable community resource and will be updated as new varieties are released at https://www.niab.com/pages/id/501/UK_Wheat_varieties_Pedigree.

Risk taking propensity: Nurse, surgeon and patient preferences for diverting ileostomy.

AIM: The decision-making process to defunction a pelvic colorectal anastomosis involves complex heuristics and is framed by surgeon personality factors. Risk taking propensity may be an important factor in these decisions and patient preferences have not been evaluated alongside surgeons and nurses. METHODS: A prospective cross-sectional study involving a one-off interview and questionnaire assessing how risk taking propensity affects nurse, surgeon and patient preferences for a temporary defunctioning ileostomy (TDI) was performed. The risk taking index (RTI) was employed to evaluate risk taking propensity and the validated prospective measures of preference instruments to evaluate preferences for stoma avoidance in several scenarios by asking the individual to consider trading or gambling years of remaining life expectancy. RESULTS: One hundred and fifty participants met the inclusion criteria, which included 30 (20.0%) surgical nurses, 20 (13.3%) colorectal surgeons and 100 (66.7%) patients. Surgeons had a significantly higher RTI (mean ± SD: 26.8 ± 6.7) than patients (mean ± SD: 20.0 ± 9.8) and nurses (mean ± SD: 23.0 ± 6.6) p = 0.002. Surgeons would consider that it would be in a patient's best interest to have a TDI at an AL rate of 15% or greater, whereas nurses and patients would do so at 28% and 25%, respectively (p = 0.007). CONCLUSION: Surgeons were shown to have a higher risk taking propensity than patients and nurses but a significantly lower threshold of AL where they would consider a TDI is in the best interest of the patient.

Understanding the classics: the unifying concepts of transgressive segregation, inbreeding depression and heterosis and their central relevance for crop breeding.

Transgressive segregation and heterosis are the reasons that plant breeding works. Molecular explanations for both phenomena have been suggested and play a contributing role. However, it is often overlooked by molecular genetic researchers that transgressive segregation and heterosis are most simply explained by dispersion of favorable alleles. Therefore, advances in molecular biology will deliver the most impact on plant breeding when integrated with sources of heritable trait variation - and this will be best achieved within a quantitative genetics framework. An example of the power of quantitative approaches is the implementation of genomic selection, which has recently revolutionized animal breeding. Genomic selection is now being applied to both hybrid and inbred crops and is likely to be the major source of improvement in plant breeding practice over the next decade. Breeders' ability to efficiently apply genomic selection methodologies is due to recent technology advances in genotyping and sequencing. Furthermore, targeted integration of additional molecular data (such as gene expression, gene copy number and methylation status) into genomic prediction models may increase their performance. In this review, we discuss and contextualize a suite of established quantitative genetics themes relating to hybrid vigour, transgressive segregation and their central relevance to plant breeding, with the aim of informing crop researchers outside of the quantitative genetics discipline of their relevance and importance to crop improvement. Better understanding between molecular and quantitative disciplines will increase the potential for further improvements in plant breeding methodologies and so help underpin future food security.

Multi-parent populations in crops: a toolbox integrating genomics and genetic mapping with breeding.

Crop populations derived from experimental crosses enable the genetic dissection of complex traits and support modern plant breeding. Among these, multi-parent populations now play a central role. By mixing and recombining the genomes of multiple founders, multi-parent populations combine many commonly sought beneficial properties of genetic mapping populations. For example, they have high power and resolution for mapping quantitative trait loci, high genetic diversity and minimal population structure. Many multi-parent populations have been constructed in crop species, and their inbred germplasm and associated phenotypic and genotypic data serve as enduring resources. Their utility has grown from being a tool for mapping quantitative trait loci to a means of providing germplasm for breeding programmes. Genomics approaches, including de novo genome assemblies and gene annotations for the population founders, have allowed the imputation of rich sequence information into the descendent population, expanding the breadth of research and breeding applications of multi-parent populations. Here, we report recent successes from crop multi-parent populations in crops. We also propose an ideal genotypic, phenotypic and germplasm 'package' that multi-parent populations should feature to optimise their use as powerful community resources for crop research, development and breeding.

The effects of training population design on genomic prediction accuracy in wheat.

Genomic selection offers several routes for increasing the genetic gain or efficiency of plant breeding programmes. In various species of livestock, there is empirical evidence of increased rates of genetic gain from the use of genomic selection to target different aspects of the breeder's equation. Accurate predictions of genomic breeding value are central to this, and the design of training sets is in turn central to achieving sufficient levels of accuracy. In summary, small numbers of close relatives and very large numbers of distant relatives are expected to enable predictions with higher accuracy. To quantify the effect of some of the properties of training sets on the accuracy of genomic selection in crops, we performed an extensive field-based winter wheat trial. In summary, this trial involved the construction of 44 F2:4 bi- and tri-parental populations, from which 2992 lines were grown on four field locations and yield was measured. For each line, genotype data were generated for 25 K segregating SNP markers. The overall heritability of yield was estimated to 0.65, and estimates within individual families ranged between 0.10 and 0.85. Genomic prediction accuracies of yield BLUEs were 0.125-0.127 using two different cross-validation approaches and generally increased with training set size. Using related crosses in training and validation sets generally resulted in higher prediction accuracies than using unrelated crosses. The results of this study emphasise the importance of the training panel design in relation to the genetic material to which the resulting prediction model is to be applied.

Genomic index selection provides a pragmatic framework for setting and refining multi-objective breeding targets in Miscanthus.

BACKGROUND: Miscanthus has potential as a biomass crop but the development of varieties that are consistently superior to the natural hybrid M. × giganteus has been challenging, presumably because of strong G × E interactions and poor knowledge of the complex genetic architectures of traits underlying biomass productivity and climatic adaptation. While linkage and association mapping studies are starting to generate long lists of candidate regions and even individual genes, it seems unlikely that this information can be translated into effective marker-assisted selection for the needs of breeding programmes. Genomic selection has emerged as a viable alternative, and prediction accuracies are moderate across a range of phenological and morphometric traits in Miscanthus, though relatively low for biomass yield per se. METHODS: We have previously proposed a combination of index selection and genomic prediction as a way of overcoming the limitations imposed by the inherent complexity of biomass yield. Here we extend this approach and illustrate its potential to achieve multiple breeding targets simultaneously, in the absence of a priori knowledge about their relative economic importance, while also monitoring correlated selection responses for non-target traits. We evaluate two hypothetical scenarios of increasing biomass yield by 20 % within a single round of selection. In the first scenario, this is achieved in combination with delaying flowering by 44 d (roughly 20 %), whereas, in the second, increased yield is targeted jointly with reduced lignin (-5 %) and increased cellulose (+5 %) content, relative to current average levels in the breeding population. KEY RESULTS: In both scenarios, the objectives were achieved efficiently (selection intensities corresponding to keeping the best 20 and 4 % of genotypes, respectively). However, the outcomes were strikingly different in terms of correlated responses, and the relative economic values (i.e. value per unit of change in each trait compared with that for biomass yield) of secondary traits included in selection indices varied considerably. CONCLUSIONS: Although these calculations rely on multiple assumptions, they highlight the need to evaluate breeding objectives and explicitly consider correlated responses in silico, prior to committing extensive resources. The proposed approach is broadly applicable for this purpose and can readily incorporate high-throughput phenotyping data as part of integrated breeding platforms.

Using Genetic Distance to Infer the Accuracy of Genomic Prediction.

The prediction of phenotypic traits using high-density genomic data has many applications such as the selection of plants and animals of commercial interest; and it is expected to play an increasing role in medical diagnostics. Statistical models used for this task are usually tested using cross-validation, which implicitly assumes that new individuals (whose phenotypes we would like to predict) originate from the same population the genomic prediction model is trained on. In this paper we propose an approach based on clustering and resampling to investigate the effect of increasing genetic distance between training and target populations when predicting quantitative traits. This is important for plant and animal genetics, where genomic selection programs rely on the precision of predictions in future rounds of breeding. Therefore, estimating how quickly predictive accuracy decays is important in deciding which training population to use and how often the model has to be recalibrated. We find that the correlation between true and predicted values decays approximately linearly with respect to either FST or mean kinship between the training and the target populations. We illustrate this relationship using simulations and a collection of data sets from mice, wheat and human genetics.

Bacteria and viruses in the nasopharynx immediately prior to onset of acute lower respiratory infections in Indigenous Australian children.

Acute lower respiratory infection (ALRI) is a major cause of hospitalization for Indigenous children in remote regions of Australia. The associated microbiology remains unclear. Our aim was to determine whether the microbes present in the nasopharynx before an ALRI were associated with its onset. A retrospective case-control/crossover study among Indigenous children aged up to 2 years. ALRI cases identified by medical note review were eligible where nasopharyngeal swabs were available: (1) 0-21 days before ALRI onset (case); (2) 90-180 days before ALRI onset (same child controls); and (3) from time and age-matched children without ALRI (different child controls). PCR assays determined the presence and/or load of selected respiratory pathogens. Among 104 children (182 recorded ALRI episodes), 120 case-same child control and 170 case-different child control swab pairs were identified. Human adenoviruses (HAdV) were more prevalent in cases compared to same child controls (18 vs 7%; OR = 3.08, 95% CI 1.22-7.76, p = 0.017), but this association was not significant in cases versus different child controls (15 vs 10%; OR = 1.93, 95% CI 0.97-3.87 (p = 0.063). No other microbes were more prevalent in cases compared to controls. Streptococcus pneumoniae (74%), Haemophilus influenzae (75%) and Moraxella catarrhalis (88%) were commonly identified across all swabs. In a pediatric population with a high detection rate of nasopharyngeal microbes, HAdV was the only pathogen detected in the period before illness presentation that was significantly associated with ALRI onset. Detection of other potential ALRI pathogens was similar between cases and controls.

Detection of Toscana virus from an adult traveler returning to Australia with encephalitis.

Toscana virus (TOSV) is identified in sandflies, animals, and humans around the Mediterranean Sea. TOSV has not been reported in Australia. During investigations of cerebrospinal fluid samples from patients with encephalitis, TOSV genetic sequences were identified in a traveler returning to Australia from Europe. TOSV should be considered, especially during May to October, in travelers to Australia who embarked in countries in and around the Mediterranean Sea and who subsequently present for medical care because of neurological symptoms.

Cofactor-dependent conformational heterogeneity of GAD65 and its role in autoimmunity and neurotransmitter homeostasis.

The human neuroendocrine enzyme glutamate decarboxylase (GAD) catalyses the synthesis of the inhibitory neurotransmitter gamma-aminobutyric acid (GABA) using pyridoxal 5'-phosphate as a cofactor. GAD exists as two isoforms named according to their respective molecular weights: GAD65 and GAD67. Although cytosolic GAD67 is typically saturated with the cofactor (holoGAD67) and constitutively active to produce basal levels of GABA, the membrane-associated GAD65 exists mainly as the inactive apo form. GAD65, but not GAD67, is a prevalent autoantigen, with autoantibodies to GAD65 being detected at high frequency in patients with autoimmune (type 1) diabetes and certain other autoimmune disorders. The significance of GAD65 autoinactivation into the apo form for regulation of neurotransmitter levels and autoantibody reactivity is not understood. We have used computational and experimental approaches to decipher the nature of the holo → apo conversion in GAD65 and thus, its mechanism of autoinactivation. Molecular dynamics simulations of GAD65 reveal coupling between the C-terminal domain, catalytic loop, and pyridoxal 5'-phosphate-binding domain that drives structural rearrangement, dimer opening, and autoinactivation, consistent with limited proteolysis fragmentation patterns. Together with small-angle X-ray scattering and fluorescence spectroscopy data, our findings are consistent with apoGAD65 existing as an ensemble of conformations. Antibody-binding kinetics suggest a mechanism of mutually induced conformational changes, implicating the flexibility of apoGAD65 in its autoantigenicity. Although conformational diversity may provide a mechanism for cofactor-controlled regulation of neurotransmitter biosynthesis, it may also come at a cost of insufficient development of immune self-tolerance that favors the production of GAD65 autoantibodies.

Heterogeneous and Dynamic Prevalence of Asymptomatic Influenza Virus Infections.

Influenza infection manifests in a wide spectrum of severity, including symptomless pathogen carriers. We conducted a systematic review and meta-analysis of 55 studies to elucidate the proportional representation of these asymptomatic infected persons. We observed extensive heterogeneity among these studies. The prevalence of asymptomatic carriage (total absence of symptoms) ranged from 5.2% to 35.5% and subclinical cases (illness that did not meet the criteria for acute respiratory or influenza-like illness) from 25.4% to 61.8%. Statistical analysis showed that the heterogeneity could not be explained by the type of influenza, the laboratory tests used to detect the virus, the year of the study, or the location of the study. Projections of infection spread and strategies for disease control require that we identify the proportional representation of these insidious spreaders early on in the emergence of new influenza subtypes or strains and track how this rate evolves over time and space.

A highly recombined, high-density, eight-founder wheat MAGIC map reveals extensive segregation distortion and genomic locations of introgression segments.

Multiparent Advanced Generation Intercross (MAGIC) mapping populations offer unique opportunities and challenges for marker and QTL mapping in crop species. We have constructed the first eight-parent MAGIC genetic map for wheat, comprising 18 601 SNP markers. We validated the accuracy of our map against the wheat genome sequence and found an improvement in accuracy compared to published genetic maps. Our map shows a notable increase in precision resulting from the three generations of intercrossing required to create the population. This is most pronounced in the pericentromeric regions of the chromosomes. Sixteen percent of mapped markers exhibited segregation distortion (SD) with many occurring in long (>20 cM) blocks. Some of the longest and most distorted blocks were collinear with noncentromeric high-marker-density regions of the genome, suggesting they were candidates for introgression fragments introduced into the bread wheat gene pool from other grass species. We investigated two of these linkage blocks in detail and found strong evidence that one on chromosome 4AL, showing SD against the founder Robigus, is an interspecific introgression fragment. The completed map is available from http://www.niab.com/pages/id/326/Resources.