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Abstract Background Fabry disease (FD) is a rare genetic disorder characterized by glycosphingolipid accumulation and progressive damage across multiple organ systems. Due to its heterogeneous presentation, the condition is likely significantly underdiagnosed. Several approaches, including provider education efforts and newborn screening, have attempted to address underdiagnosis of FD across the age spectrum, with limited success. Artificial intelligence (AI) methods present another option for improving diagnosis. These methods isolate common health history patterns among patients using longitudinal real-world data, and can be particularly useful when patients experience nonspecific, heterogeneous symptoms over time. In this study, the performance of an AI tool in identifying patients with FD was analyzed. The tool was calibrated using de-identified health record data from a large cohort of nearly 5000 FD patients, and extracted phenotypic patterns from these records. The tool then used this FD pattern information to make individual-level estimates of FD in a testing dataset. Patterns were reviewed and confirmed with medical experts. Results The AI tool demonstrated strong analytic performance in identifying FD patients. In out-of-sample testing, it achieved an area under the receiver operating characteristic curve (AUROC) of 0.82. Strong performance was maintained when testing on male-only and female-only cohorts, with AUROCs of 0.83 and 0.82 respectively. The tool identified small segments of the population with greatly increased prevalence of FD: in the 1% of the population identified by the tool as at highest risk, FD was 23.9 times more prevalent than in the population overall. The AI algorithm used hundreds of phenotypic signals to make predictions and included both familiar symptoms associated with FD (e.g. renal manifestations) as well as less well-studied characteristics. Conclusions The AI tool analyzed in this study performed very well in identifying Fabry disease patients using structured medical history data. Performance was maintained in all-male and all-female cohorts, and the phenotypic manifestations of FD highlighted by the tool were reviewed and confirmed by clinical experts in the condition. The platform’s analytic performance, transparency, and ability to generate predictions based on existing real-world health data may allow it to contribute to reducing persistent underdiagnosis of Fabry disease.

Abstract Sleep and wakefulness are fundamental behavioral states of which the underlying molecular principles are becoming slowly elucidated. Transitions between these states require the coordination of multiple neurochemical and modulatory systems. In Caenorhabditis elegans sleep occurs during a larval transition stage called lethargus and is induced by somnogenic neuropeptides. Here, we identify two opposing neuropeptide/receptor signaling pathways: NLP-22 promotes behavioral quiescence, whereas NLP-2 promotes movement during lethargus, by signaling through gonadotropin-releasing hormone (GnRH) related receptors. Both NLP-2 and NLP-22 belong to the RPamide neuropeptide family and share sequence similarities with neuropeptides of the bilaterian GnRH, adipokinetic hormone (AKH) and corazonin family. RPamide neuropeptides dose-dependently activate the GnRH/AKH-like receptors GNRR-3 and GNRR-6 in a cellular receptor activation assay. In addition, nlp-22-induced locomotion quiescence requires the receptor gnrr-6. By contrast, wakefulness induced by nlp-2 overexpression is diminished by deletion of either gnrr-3 or gnrr-6. nlp-2 is expressed in a pair of olfactory AWA neurons and cycles with larval periodicity, as reported for nlp-22, which is expressed in RIA. Our data suggest that the somnogenic NLP-22 neuropeptide signals through GNRR-6, and that both GNRR-3 and GNRR-6 are required for the wake-promoting action of NLP-2 neuropeptides.

Abstract Background Yellow lupin (Lupinus luteus L.) is a promising grain legume for productive and sustainable crop rotations. It has the advantages of high tolerance to soil acidity and excellent seed quality, but its current yield potential is poor, especially in low rainfall environments. Key adaptation traits such as phenology and enhanced stress tolerance are often complex and controlled by several genes. Genomic-enabled technologies may help to improve our basic understanding of these traits and to provide selective markers in breeding. However, in yellow lupin there are very limited genomic resources to support research and no published information is available on the genetic control of adaptation traits. Results We aimed to address these deficiencies by developing the first linkage map for yellow lupin and conducting quantitative trait locus (QTL) analysis of yield under well-watered (WW) and water-deficit (WT) conditions. Two next-generation sequencing marker approaches - genotyping-by-sequencing (GBS) and Diversity Array Technology (DArT) sequencing - were employed to genotype a recombinant inbred line (RIL) population developed from a bi-parental cross between wild and domesticated parents. A total of 2,458 filtered single nucleotide polymorphism (SNP) and presence / absence variation (PAV) markers were used to develop a genetic map comprising 40 linkage groups, the first reported for this species. A number of significant QTLs controlling total biomass and 100-seed weight under two water (WW and WD) regimes were found on linkage groups YL-03, YL-09 and YL-26 that together explained 9 and 28% of total phenotypic variability. QTLs associated with length of the reproductive phase and time to flower were found on YL-01, YL-21, YL-35 and YL-40 that together explained a total of 12 and 44% of total phenotypic variation. Conclusion These genomic resources and the QTL information offer significant potential for use in marker-assisted selection in yellow lupin.

Abstract Background Narrow-leafed lupin is an emerging crop of significance in agriculture, livestock feed and human health food. However, its susceptibility to various diseases is a major obstacle towards increased adoption. Sclerotinia sclerotiorum and Botrytis cinerea – both necrotrophs with broad host-ranges - are reported among the top 10 lupin pathogens. Whole-genome sequencing and comparative genomics are useful tools to discover genes responsible for interactions between pathogens and their hosts. Results Genomes were assembled for one isolate of B. cinerea and two isolates of S. sclerotiorum, which were isolated from either narrow-leafed or pearl lupin species. Comparative genomics analysis between lupin-derived isolates and others isolated from alternate hosts was used to predict between 94 to 98 effector gene candidates from among their respective non-conserved gene contents. Conclusions Detection of minor differences between relatively recently-diverged isolates, originating from distinct regions and with hosts, may highlight novel or recent gene mutations and losses resulting from host adaptation in broad host-range fungal pathogens.

Abstract Background Determining which target to pursue is a challenging and error-prone first step in developing a therapeutic treatment for a disease, where missteps are potentially very costly given the long-time frames and high expenses of drug development. With current informatics technology and machine learning algorithms, it is now possible to computationally discover therapeutic hypotheses by predicting clinically promising drug targets based on the evidence associating drug targets with disease indications. We have collected this evidence from Open Targets and additional databases that covers 17 sources of evidence for target-indication association and represented the data as a tensor of 21,437 × 2211 × 17. Results As a proof-of-concept, we identified examples of successes and failures of target-indication pairs in clinical trials across 875 targets and 574 disease indications to build a gold-standard data set of 6140 known clinical outcomes. We designed and executed three benchmarking strategies to examine the performance of multiple machine learning models: Logistic Regression, LASSO, Random Forest, Tensor Factorization and Gradient Boosting Machine. With 10-fold cross-validation, tensor factorization achieved AUROC = 0.82 ± 0.02 and AUPRC = 0.71 ± 0.03. Across multiple validation schemes, this was comparable or better than other methods. Conclusion In this work, we benchmarked a machine learning technique called tensor factorization for the problem of predicting clinical outcomes of therapeutic hypotheses. Results have shown that this method can achieve equal or better prediction performance compared with a variety of baseline models. We demonstrate one application of the method to predict outcomes of trials on novel indications of approved drug targets. This work can be expanded to targets and indications that have never been clinically tested and proposing novel target-indication hypotheses. Our proposed biologically-motivated cross-validation schemes provide insight into the robustness of the prediction performance. This has significant implications for all future methods that try to address this seminal problem in drug discovery.

The Collaborative Approach to Reach Everyone with Familial Hypercholesterolemia (CARE-FH) study aims to improve diagnostic evaluation rates for FH at Geisinger, an integrated health delivery system. This clinical trial relies upon implementation science to transition the initial evaluation for FH into primary care, attempting to identify individuals prior to the onset of atherosclerotic cardiovascular disease events. The protocol for the CARE-FH study of this paper is available online. The first phase of the project focuses on trial design, including the development of implementation strategies to deploy evidence-based guidelines. The second phase will study the intervention, rolled out regionally to internal medicine, community medicine, and pediatric care clinicians using a stepped-wedge design, and analyzing data on diagnostic evaluation rates, and implementation, service, and health outcomes.

Complex extracellular structures exist throughout phylogeny, but the dynamics of their formation and dissolution are often opaque. One example is the pharyngeal grinder of the nematode Caenorhabditis elegans, an extracellular structure that ruptures bacteria during feeding. During each larval transition stage, called lethargus, the grinder is replaced with one of a larger size. Here, we characterize at the ultrastructural level the deconstruction of the larval grinder and the construction of the adult grinder during the fourth larval stage (L4)-to-adult transition. Early in L4 lethargus, pharyngeal muscle cells trans-differentiate from contractile to secretory cells, as evidenced by the appearance of clear and dense core vesicles and disruptions in sarcomere organization. This is followed, within minutes, by the dissolution of the L4 grinder and the formation and maturation of the adult grinder. Components of the nascent adult grinder are deposited basally, and are separated from the dissolving larval grinder by a visible apical layer. The complete grinder is a lamellated extracellular matrix comprised of five layers. Following grinder formation, pharyngeal muscle cells regain ultrastructural contractile properties, and muscle contractions resume. Our findings add to our understanding of how complex extracellular structures assemble and dissemble.

In this study, we investigated genetic elements of the type IV secretion system (T4SS) found in Sinorhizobium spp. and the role they play in symbiosis. Sinorhizobium meliloti and S. medicae each contain a putative T4SS similar to that used by Agrobacterium tumefaciens during pathogenesis. The Cre reporter assay for translocation system was used to validate potential effector proteins. Both S. meliloti and S. medicae contained the effector protein TfeA, which was translocated into the host plant. Sequence analysis revealed the presence of a nod box involved in transcriptional activation of symbiosis-related genes, upstream of the transcriptional regulator (virG) in the Sinorhizobium T4SS. Replicate quantitative reverse transcription-polymerase chain reaction analyses indicated that luteolin, released by roots and seeds of Medicago truncatula, upregulated transcription of tfeA and virG. Mutations in the T4SS apparatus or tfeA alone resulted in reduced numbers of nodules formed on M. truncatula genotypes. In addition, S. meliloti KH46c, which contains a deletion in the T4SS, was less competitive for nodule formation when coinoculated with an equal number of cells of the wild-type strain. To our knowledge, TfeA is the first T4SS effector protein identified in Sinorhizobium spp. Our results indicate that Sinorhizobium i) uses a T4SS during initiation of symbiosis with Medicago spp., and ii) alters Medicago cells in planta during symbiosis. This study also offers additional bioinformatic evidence that several different rhizobial species may use the T4SS in symbiosis with other legumes.

Oilseed Brassica species are vulnerable to heat and drought stress, especially in the early reproductive stage. We evaluated plant imaging of whole plant and flower tissue, leaf stomatal conductance, leaf and bud temperature, photochemical reflectance index, quantum yield of photosynthesis, and leaf gas exchange for their suitability to detect tolerance to heat (H) and/or drought (D) stress treatments in 12 Brassica genotypes (G). A replicated factorial experiment was set up with 7 d of stress treatment from the beginning of anthesis with various levels of three factors H, D, and G. Most phenomics tools detected plant stress as indicated by significant main effects of H, D, and H×D. Whole plant volume was highly correlated with fresh weight changes, suggesting that whole plant imaging may be a useful surrogate for fresh weight in future studies. Vcmax, the maximum carboxylation rate of photosynthesis, increased rapidly on day 1 in H and H+D treatments, and there were significant interactions of G×H and G×D. Vcmax of genotypes on day 1 in H and H+D treatments was positively correlated with their harvested seed yield. Vcmax on day 1 and day 3 were clustered with seed yield in H and H+D treatments as shown in the heatmaps of genotypic correlations. TPU, the rate of triose phosphate use, also showed significant positive genotypic correlations with seed yield in H+D treatments. Flower volume showed significant interactions of G×H and G×D on day 7, and flower volume of genotypes on day 7 in H was positively correlated with their harvested seed yield. There were few interactions of G×H or G×D for leaf stomatal conductance, leaf and bud temperature, photochemical reflectance index, and quantum yield of photosynthesis. Vcmax, TPU, and volume of flowers are potential nondestructive phenomic traits for heat or combined heat and drought stress tolerance screening in Brassica germplasm.

Low temperature inhibits rapid germination and successful seedling establishment of rapeseed (Brassica napus L.), leading to significant productivity losses. Little is known about the genetic diversity for seed vigor under low-temperature conditions in rapeseed, which motivated our investigation of 13 seed germination- and emergence-related traits under normal and low-temperature conditions for 442 diverse rapeseed accessions. The stress tolerance index was calculated for each trait based on performance under non-stress and low-temperature stress conditions. Principal component analysis of the low-temperature stress tolerance indices identified five principal components that captured 100% of the seedling response to low temperature. A genome-wide association study using ~8 million SNP (single-nucleotide polymorphism) markers identified from genome resequencing was undertaken to uncover the genetic basis of seed vigor related traits in rapeseed. We detected 22 quantitative trait loci (QTLs) significantly associated with stress tolerance indices regarding seed vigor under low-temperature stress. Scrutiny of the genes in these QTL regions identified 62 candidate genes related to specific stress tolerance indices of seed vigor, and the majority were involved in DNA repair, RNA translation, mitochondrial activation and energy generation, ubiquitination and degradation of protein reserve, antioxidant system, and plant hormone and signal transduction. The high effect variation and haplotype-based effect of these candidate genes were evaluated, and high priority could be given to the candidate genes BnaA03g40290D, BnaA06g07530D, BnaA09g06240D, BnaA09g06250D, and BnaC02g10720D in further study. These findings should be useful for marker-assisted breeding and genomic selection of rapeseed to increase seed vigor under low-temperature stress.

We present the first genetic map of tedera (Bituminaria bituminosa (L.) C.H. Stirton), a drought-tolerant forage legume from the Canary Islands with useful pharmaceutical properties. It is also the first genetic map for any species in the tribe Psoraleeae (Fabaceae). The map comprises 2042 genotyping-by-sequencing (GBS) markers distributed across 10 linkage groups, consistent with the haploid chromosome count for this species (n = 10). Sequence tags from the markers were used to find homologous matches in the genome sequences of the closely related species in the Phaseoleae tribe: soybean, common bean, and cowpea. No tedera linkage groups align in their entirety to chromosomes in any of these phaseoloid species, but there are long stretches of collinearity that could be used in tedera research for gene discovery purposes using the better-resourced phaseoloid species. Using Ks analysis of a tedera transcriptome against five legume genomes provides an estimated divergence time of 17.4 million years between tedera and soybean. Genomic information and resources developed here will be invaluable for breeding tedera varieties for forage and pharmaceutical purposes.

A phenome-wide association study of variants in genes in the Th17 and IL-17 pathway was performed using self-reported phenotypes and genetic data from 521,000 research participants of 23andMe. Results replicated known associations with similar effect sizes for autoimmune traits illustrating self-reported traits can be a surrogate for clinically assessed conditions. Novel associations controlling for a false discovery rate of 5% included the association of the variant encoding p.Ile684Ser in TYK2 with increased risk of tonsillectomy, strep throat occurrences and teen acne, the variant encoding p.Arg381Gln in IL23R with a decrease in dandruff frequency, the variant encoding p.Asp10Asn in TRAF3IP2 with risk of male-pattern balding, and the RORC regulatory variant (rs4845604) with protection from allergies. This approach enabled rapid assessment of association with a wide variety of traits and investigation of traits with limited reported associations to overlay meaningful phenotypic context on the range of conditions being considered for drugs targeting this pathway.

In response to environments that cause cellular stress, animals engage in sleep behavior that facilitates recovery from the stress. In Caenorhabditis elegans, stress-induced sleep(SIS) is regulated by cytokine activation of the ALA neuron, which releases FLP-13 neuropeptides characterized by an amidated arginine-phenylalanine (RFamide) C-terminus motif. By performing an unbiased genetic screen for mutants that impair the somnogenic effects of FLP-13 neuropeptides, we identified the gene dmsr-1, which encodes a G-protein coupled receptor similar to an insect RFamide receptor. DMSR-1 is activated by FLP-13 peptides in cell culture, is required for SIS in vivo, is expressed non-synaptically in several wake-promoting neurons, and likely couples to a Gi/o heterotrimeric G-protein. Our data expand our understanding of how a single neuroendocrine cell coordinates an organism-wide behavioral response, and suggest that similar signaling principles may function in other organisms to regulate sleep during sickness.

Quantitative Reverse Transcription PCR (qRT-PCR) is currently one of the most popular, high-throughput and sensitive technologies available for quantifying gene expression. Its accurate application depends heavily upon normalisation of gene-of-interest data with reference genes that are uniformly expressed under experimental conditions. The aim of this study was to provide the first validation of reference genes for Lupinus angustifolius (narrow-leafed lupin, a significant grain legume crop) using a selection of seven genes previously trialed as reference genes for the model legume, Medicago truncatula. In a preliminary evaluation, the seven candidate reference genes were assessed on the basis of primer specificity for their respective targeted region, PCR amplification efficiency, and ability to discriminate between cDNA and gDNA. Following this assessment, expression of the three most promising candidates [Ubiquitin C (UBC), Helicase (HEL), and Polypyrimidine tract-binding protein (PTB)] was evaluated using the NormFinder and RefFinder statistical algorithms in two narrow-leafed lupin lines, both with and without vernalisation treatment, and across seven organ types (cotyledons, stem, leaves, shoot apical meristem, flowers, pods and roots) encompassing three developmental stages. UBC was consistently identified as the most stable candidate and has sufficiently uniform expression that it may be used as a sole reference gene under the experimental conditions tested here. However, as organ type and developmental stage were associated with greater variability in relative expression, it is recommended using UBC and HEL as a pair to achieve optimal normalisation. These results highlight the importance of rigorously assessing candidate reference genes for each species across a diverse range of organs and developmental stages. With emerging technologies, such as RNAseq, and the completion of valuable transcriptome data sets, it is possible that other potentially more suitable reference genes will be identified for this species in future.

Humans have domesticated hundreds of plant and animal species as sources of food, fiber, forage, and tools over the past 12,000 years, with manifold effects on both human society and the genetic structure of the domesticated species. The outcomes of crop domestication were shaped by selection driven by human preferences, cultivation practices, and agricultural environments, as well as other population genetic processes flowing from the ensuing reduction in effective population size. It is obvious that any selection imposes a reduction of diversity, favoring preferred genotypes, such as nonshattering seeds or increased palatability. Furthermore, agricultural practices greatly reduced effective population sizes of crops, allowing genetic drift to alter genotype frequencies. Current advances in molecular technologies, particularly of genome sequencing, provide evidence of human selection acting on numerous loci during and after crop domestication. Population-level molecular analyses also enable us to clarify the demographic histories of the domestication process itself, which, together with expanded archaeological studies, can illuminate the origins of crops. Domesticated plant species are found in 160 taxonomic families. Approximately 2500 species have undergone some degree of domestication, and 250 species are considered to be fully domesticated. The evolutionary trajectory from wild to crop species is a complex process. Archaeological records suggest that there was a period of predomestication cultivation while humans first began the deliberate planting of wild stands that had favorable traits. Later, crops likely diversified as they were grown in new areas, sometimes beyond the climatic niche of their wild relatives. However, the speed and level of human intentionality during domestication remains a topic of active discussion. These processes led to the so-called domestication syndrome, that is, a group of traits that can arise through human preferences for ease of harvest and growth advantages under human propagation. These traits included reduced dispersal ability of seeds and fruits, changes to plant structure, and changes to plant defensive characteristics and palatability. Domestication implies the action of selective sweeps on standing genetic variation, as well as new genetic variation introduced via mutation or introgression. Furthermore, genetic bottlenecks during domestication or during founding events as crops moved away from their centers of origin may have further altered gene pools. To date, a few hundred genes and loci have been identified by classical genetic and association mapping as targets of domestication and postdomestication divergence. However, only a few of these have been characterized, and for even fewer is the role of the wild-type allele in natural populations understood. After domestication, only favorable haplotypes are retained around selected genes, which creates a genetic valley with extremely low genetic diversity. These “selective sweeps” can allow mildly deleterious alleles to come to fixation and may create a genetic load in the cultivated gene pool. Although the population-wide genomic consequences of domestication offer several predictions for levels of the genetic diversity in crops, our understanding of how this diversity corresponds to nutritional aspects of crops is not well understood. Many studies have found that modern cultivars have lower levels of key micronutrients and vitamins. We suspect that selection for palatability and increased yield at domestication and during postdomestication divergence exacerbated the low nutrient levels of many crops, although relatively little work has examined this question. Lack of diversity in modern germplasm may further limit our capacity to breed for higher nutrient levels, although little effort has gone into this beyond a handful of staple crops. This is an area where an understanding of domestication across many crop taxa may provide the necessary insight for breeding more nutritious crops in a rapidly changing world.

The formation of symbiotic nitrogen-fixing nodules on the roots and/or stem of leguminous plants involves a complex signal exchange between both partners. Since many microorganisms are present in the soil, legumes and rhizobia must recognize and initiate communication with each other to establish symbioses. This results in the formation of nodules. Rhizobia within nodules exchange fixed nitrogen for carbon from the legume. Symbiotic relationships can become non-beneficial if one partner ceases to provide support to the other. As a result, complex signal exchange mechanisms have evolved to ensure continued, beneficial symbioses. Proper recognition and signal exchange is also the basis for host specificity. Nodule formation always provides a fitness benefit to rhizobia, but does not always provide a fitness benefit to legumes. Therefore, legumes have evolved a mechanism to regulate the number of nodules that are formed, this is called autoregulation of nodulation. Sequencing of many different rhizobia have revealed the presence of several secretion systems - and the Type III, Type IV and Type VI secretion systems are known to be used by pathogens to transport effector proteins. These secretion systems are also known to have an effect on host specificity and are a determinant of overall nodule number on legumes. This review focuses on signal exchange between rhizobia and legumes, particularly focusing on the role of secretion systems involved in nodule formation and host specificity.

The Quick Urban and Industrial Complex (QUIC) plume modeling system is used to explore how the transport and dispersion of vehicle emissions in cities are impacted by the presence of buildings. Using downtown Philadelphia as a test case, notional vehicle emissions of gases and particles are specified as line source releases on a subset of the east–west and north–south streets. Cases were run in flat terrain and with 3D buildings present in order to show the differences in the model-computed outdoor concentration fields with and without buildings present. The QUIC calculations show that buildings result in regions with much higher concentrations and other areas with much lower concentrations when compared to the flat-earth case. On the roads with vehicle emissions, street-level concentrations were up to a factor of 10 higher when buildings were on either side of the street as compared to the flat-earth case due to trapping of pollutants between buildings. However, on roads without vehicle emissions and in other open areas, the concentrations were up to a factor of 100 times smaller as compared to the flat earth case because of vertical mixing of the vehicle emissions to building height in the cavity circulation that develops on the downwind side of unsheltered buildings. QUIC was also used to calculate infiltration of the contaminant into the buildings. Indoor concentration levels were found to be much lower than outdoor concentrations because of deposition onto indoor surfaces and particulate capture for buildings with filtration systems. Large differences in indoor concentrations from building to building resulted from differences in leakiness, air handling unit volume exchange rates, and filter type and for naturally ventilated buildings, whether or not the building was sheltered from the prevailing wind by a building immediately upwind.

Neuropeptides signal through G-protein coupled receptors (GPCRs) to regulate a broad array of animal behaviors and physiological processes. The Caenorhabditis elegans genome encodes approximately 100 predicted neuropeptide receptor GPCRs, but in vivo roles for only a few have been identified. We describe here a role for the GPCR FRPR-4 in the regulation of behavioral quiescence and locomotive posture. FRPR-4 is activated in cell culture by several neuropeptides with an amidated isoleucine-arginine-phenylalanine (IRF) motif or an amidated valine-arginine-phenylalanine (VRF) motif at their carboxy termini, including those encoded by the gene flp-13. Loss of frpr-4 function results in a minor feeding quiescence defect after heat-induced cellular stress. Overexpression of frpr-4 induces quiescence of locomotion and feeding as well as an exaggerated body bend posture. The exaggerated body bend posture requires the gene flp-13. While frpr-4 is expressed broadly, selective overexpression of frpr-4 in the proprioceptive DVA neurons results in exaggerated body bends that require flp-13 in the ALA neuron. Our results suggest that FLP-13 and other neuropeptides signal through FRPR-4 and other receptors to regulate locomotion posture and behavioral quiescence.

Time of flowering is a key adaptive trait in plants and is conditioned by the interaction of genes and environmental cues including length of photoperiod, ambient temperature and vernalisation. Here we investigated the photoperiod responsiveness of summer annual-types of Brassica napus (rapeseed, canola). A population of 131 doubled haploid lines derived from a cross between European and Australian parents was evaluated for days to flowering, thermal time to flowering (measured in degree-days) and the number of leaf nodes at flowering in a compact and efficient glasshouse-based experiment with replicated short and long day treatments. All three traits were under strong genetic control with heritability estimates ranging from 0.85-0.93. There was a very strong photoperiod effect with flowering in the population accelerated by 765 degree-days in the long day versus short day treatments. However, there was a strong genetic correlation of line effects (0.91) between the long and short day treatments and relatively low genotype x treatment interaction indicating that photoperiod had a similar effect across the population. Bivariate analysis of thermal time to flowering in short and long days revealed three main effect quantitative trait loci (QTLs) that accounted for 57.7% of the variation in the population and no significant interaction QTLs. These results provided insight into the contrasting adaptations of Australian and European varieties. Both parents responded to photoperiod and their alleles shifted the population to earlier flowering under long days. In addition, segregation of QTLs in the population caused wide transgressive segregation in thermal time to flowering. Potential candidate flowering time homologues located near QTLs were identified with the aid of the Brassica rapa reference genome sequence. We discuss how these results will help to guide the breeding of summer annual types of B. napus adapted to new and changing environments.

Statistical imputation of classical HLA alleles in case-control studies has become established as a valuable tool for identifying and fine-mapping signals of disease association in the MHC. Imputation into diverse populations has, however, remained challenging, mainly because of the additional haplotypic heterogeneity introduced by combining reference panels of different sources. We present an HLA type imputation model, HLA*IMP:02, designed to operate on a multi-population reference panel. HLA*IMP:02 is based on a graphical representation of haplotype structure. We present a probabilistic algorithm to build such models for the HLA region, accommodating genotyping error, haplotypic heterogeneity and the need for maximum accuracy at the HLA loci, generalizing the work of Browning and Browning (2007) and Ron et al. (1998). HLA*IMP:02 achieves an average 4-digit imputation accuracy on diverse European panels of 97% (call rate 97%). On non-European samples, 2-digit performance is over 90% for most loci and ethnicities where data available. HLA*IMP:02 supports imputation of HLA-DPB1 and HLA-DRB3-5, is highly tolerant of missing data in the imputation panel and works on standard genotype data from popular genotyping chips. It is publicly available in source code and as a user-friendly web service framework.

Mucopolysaccharidosis type I (MPS-I; Hurler syndrome) is an inborn error of metabolism caused by lack of the functional lysosomal glycosaminoglycan (GAG)-degrading enzyme α-l-iduronidase (IDUA). Without treatment, the resulting GAG accumulation causes multisystem dysfunction and death within the first decade. Current treatments include allogeneic hematopoietic stem cell transplantation (HSCT) and enzyme replacement therapy. HSCT ameliorates clinical features and extends life but is not available to all patients, and inadequately corrects the most devastating features of the disease including mental retardation and skeletal deformities. Recent developments suggest that stem cells can be used to deliver needed enzymes to the central nervous system. To test this concept, we transplanted bone marrow-derived normal adult human MultiStem® cells into the cerebral lateral ventricles of immunodeficient MPS-I neonatal mice. Transplanted cells and human-specific DNA were detected in the hippocampal formation, striatum, and other areas of the central nervous system. Brain tissue assays revealed significant long-term decrease in GAG levels in the hippocampus and striatum. Sensorimotor testing 6 months after transplantation demonstrated significantly improved rotarod performance of transplanted mice in comparison to nontransplanted and sham-transplanted control animals. These results suggest that a single injection of MultiStem cells into the cerebral ventricles of neonatal MPS-I mice induces sustained reduction in GAG accumulation within the brain, and modest long-term improvement in sensorimotor function.

Genome-wide association studies have found thousands of common genetic variants associated with a wide variety of diseases and other complex traits. However, a large portion of the predicted genetic contribution to many traits remains unknown. One plausible explanation is that some of the missing variation is due to the effects of rare variants. Nonetheless, the statistical analysis of rare variants is challenging. A commonly used method is to contrast, within the same region (gene), the frequency of minor alleles at rare variants between cases and controls. However, this strategy is most useful under the assumption that the tested variants have similar effects. We previously proposed a method that can accommodate heterogeneous effects in the analysis of quantitative traits. Here we extend this method to include binary traits that can accommodate covariates. We use simulations for a variety of causal and covariate impact scenarios to compare the performance of the proposed method to standard logistic regression, C-alpha, SKAT, and EREC. We found that i) logistic regression methods perform well when the heterogeneity of the effects is not extreme and ii) SKAT and EREC have good performance under all tested scenarios but they can be computationally intensive. Consequently, it would be more computationally desirable to use a two-step strategy by (i) selecting promising genes by faster methods and ii) analyzing selected genes using SKAT/EREC. To select promising genes one can use (1) regression methods when effect heterogeneity is assumed to be low and the covariates explain a non-negligible part of trait variability, (2) C-alpha when heterogeneity is assumed to be large and covariates explain a small fraction of trait's variability and (3) the proposed trend and heterogeneity test when the heterogeneity is assumed to be non-trivial and the covariates explain a large fraction of trait variability.

During animal development, cellular morphogenesis plays a fundamental role in determining the shape and function of tissues and organs. Identifying the components that regulate and drive morphogenesis is thus a major goal of developmental biology. The four-celled tip of the Caenorhabditis elegans male tail is a simple but powerful model for studying the mechanism of morphogenesis and its spatiotemporal regulation. Here, through a genome-wide post-embryonic RNAi-feeding screen, we identified 212 components that regulate or participate in male tail tip morphogenesis. We constructed a working hypothesis for a gene regulatory network of tail tip morphogenesis. We found regulatory roles for the posterior Hox genes nob-1 and php-3, the TGF-β pathway, nuclear hormone receptors (e.g. nhr-25), the heterochronic gene blmp-1, and the GATA transcription factors egl-18 and elt-6. The majority of the pathways converge at dmd-3 and mab-3. In addition, nhr-25 and dmd-3/mab-3 regulate each others' expression, thus placing these three genes at the center of a complex regulatory network. We also show that dmd-3 and mab-3 negatively regulate other signaling pathways and affect downstream cellular processes such as vesicular trafficking (e.g. arl-1, rme-8) and rearrangement of the cytoskeleton (e.g. cdc-42, nmy-1, and nmy-2). Based on these data, we suggest that male tail tip morphogenesis is governed by a gene regulatory network with a bow-tie architecture.

Genotype imputation has the potential to assess human genetic variation at a lower cost than assaying the variants using laboratory techniques. The performance of imputation for rare variants has not been comprehensively studied. We utilized 8865 human samples with high depth resequencing data for the exons and flanking regions of 202 genes and Genome-Wide Association Study (GWAS) data to characterize the performance of genotype imputation for rare variants. We evaluated reference sets ranging from 100 to 3713 subjects for imputing into samples typed for the Affymetrix (500K and 6.0) and Illumina 550K GWAS panels. The proportion of variants that could be well imputed (true r(2)>0.7) with a reference panel of 3713 individuals was: 31% (Illumina 550K) or 25% (Affymetrix 500K) with MAF (Minor Allele Frequency) less than or equal 0.001, 48% or 35% with 0.0010.05. The performance for common SNPs (MAF>0.05) within exons and flanking regions is comparable to imputation of more uniformly distributed SNPs. The performance for rare SNPs (0.01

The frontal eye field (FEF) contributes to directing visual attention and saccadic eye movement through intrinsic processing, interactions with extrastriate visual cortical areas (e.g. V4), and projections to subcortical structures (e.g. superior colliculus; SC). Several models have been proposed to describe the relationship between the allocation of visual attention and the production of saccades. We obtained anatomical information that might provide useful constraints on these models by evaluating two characteristics of FEF. First, we investigated the laminar distribution of efferent connections from FEF to visual areas V4 + TEO and to SC. Second, we examined the laminar distribution of different populations of GABAergic neurons in FEF. We found that the neurons in FEF that project to V4 + TEO are located predominantly in the supragranular layers, colocalized with the highest density of calbindin- and calretinin-immunoreactive inhibitory interneurons. In contrast, the cell bodies of neurons that project to SC are found only in layer 5 of FEF, colocalized primarily with parvalbumin inhibitory interneurons. None of the neurons in layer 5 that project to V4 + TEO also project to SC. These results provide useful constraints for cognitive models of visual attention and saccade production by indicating that different populations of neurons project to extrastriate visual cortical areas and to SC. This finding also suggests that FEF neurons projecting to visual cortex and superior colliculus are embedded in different patterns of intracortical circuitry.