An association test of the spatial distribution of rare missense variants within protein structures identifies Alzheimer's disease-related patterns.

More than 90% of genetic variants are rare in most modern sequencing studies, such as the Alzheimer's Disease Sequencing Project (ADSP) whole-exome sequencing (WES) data. Furthermore, 54% of the rare variants in ADSP WES are singletons. However, both single variant and unit-based tests are limited in their statistical power to detect an association between rare variants and phenotypes. To best use missense rare variants and investigate their biological effect, we examine their association with phenotypes in the context of protein structures. We developed a protein structure-based approach, protein optimized kernel evaluation of missense nucleotides (POKEMON), which evaluates rare missense variants based on their spatial distribution within a protein rather than their allele frequency. The hypothesis behind this test is that the three-dimensional spatial distribution of variants within a protein structure provides functional context to power an association test. POKEMON identified three candidate genes (TREM2, SORL1, and EXOC3L4) and another suggestive gene from the ADSP WES data. For TREM2 and SORL1, two known Alzheimer's disease (AD) genes, the signal from the spatial cluster is stable even if we exclude known AD risk variants, indicating the presence of additional low-frequency risk variants within these genes. EXOC3L4 is a novel AD risk gene that has a cluster of variants primarily shared by case subjects around the Sec6 domain. This cluster is also validated in an independent replication data set and a validation data set with a larger sample size.

Ponatinib Drives Cardiotoxicity by S100A8/A9-NLRP3-IL-1ß Mediated Inflammation.

BACKGROUND: The tyrosine kinase inhibitor ponatinib is the only treatment option for chronic myelogenous leukemia patients with T315I (gatekeeper) mutation. Pharmacovigilance analysis of Food and Drug Administration and World Health Organization datasets has revealed that ponatinib is the most cardiotoxic agent among all Food and Drug Administration-approved tyrosine kinase inhibitors in a real-world scenario. However, the mechanism of ponatinib-induced cardiotoxicity is unknown. METHODS: The lack of well-optimized mouse models has hampered the in vivo cardio-oncology studies. Here, we show that cardiovascular comorbidity mouse models evidence a robust cardiac pathological phenotype upon ponatinib treatment. A combination of multiple in vitro and in vivo models was employed to delineate the underlying molecular mechanisms. RESULTS: An unbiased RNA sequencing analysis identified the enrichment of dysregulated inflammatory genes, including a multifold upregulation of alarmins S100A8/A9, as a top hit in ponatinib-treated hearts. Mechanistically, we demonstrate that ponatinib activates the S100A8/A9-TLR4 (Toll-like receptor 4)-NLRP3 (NLR family pyrin domain-containing 3)-IL (interleukin)-1ß signaling pathway in cardiac and systemic myeloid cells, in vitro and in vivo, thereby leading to excessive myocardial and systemic inflammation. Excessive inflammation was central to the cardiac pathology because interventions with broad-spectrum immunosuppressive glucocorticoid dexamethasone or specific inhibitors of NLRP3 (CY-09) or S100A9 (paquinimod) nearly abolished the ponatinib-induced cardiac dysfunction. CONCLUSIONS: Taken together, these findings uncover a novel mechanism of ponatinib-induced cardiac inflammation leading to cardiac dysfunction. From a translational perspective, our results provide critical preclinical data and rationale for a clinical investigation into immunosuppressive interventions for managing ponatinib-induced cardiotoxicity.

NIAGADS Alzheimer's GenomicsDB: A resource for exploring Alzheimer's disease genetic and genomic knowledge.

INTRODUCTION: The National Institute on Aging Genetics of Alzheimer's Disease Data Storage Site Alzheimer's Genomics Database (GenomicsDB) is a public knowledge base of Alzheimer's disease (AD) genetic datasets and genomic annotations. METHODS: GenomicsDB uses a custom systems architecture to adopt and enforce rigorous standards that facilitate harmonization of AD-relevant genome-wide association study summary statistics datasets with functional annotations, including over 230 million annotated variants from the AD Sequencing Project. RESULTS: GenomicsDB generates interactive reports compiled from the harmonized datasets and annotations. These reports contextualize AD-risk associations in a broader functional genomic setting and summarize them in the context of functionally annotated genes and variants. DISCUSSION: Created to make AD-genetics knowledge more accessible to AD researchers, the GenomicsDB is designed to guide users unfamiliar with genetic data in not only exploring but also interpreting this ever-growing volume of data. Scalable and interoperable with other genomics resources using data technology standards, the GenomicsDB can serve as a central hub for research and data analysis on AD and related dementias. HIGHLIGHTS: The National Institute on Aging Genetics of Alzheimer's Disease Data Storage Site (NIAGADS) offers to the public a unique, disease-centric collection of AD-relevant GWAS summary statistics datasets. Interpreting these data is challenging and requires significant bioinformatics expertise to standardize datasets and harmonize them with functional annotations on genome-wide scales. The NIAGADS Alzheimer's GenomicsDB helps overcome these challenges by providing a user-friendly public knowledge base for AD-relevant genetics that shares harmonized, annotated summary statistics datasets from the NIAGADS repository in an interpretable, easily searchable format.

Human whole-exome genotype data for Alzheimer's disease.

The heterogeneity of the whole-exome sequencing (WES) data generation methods present a challenge to a joint analysis. Here we present a bioinformatics strategy for joint-calling 20,504 WES samples collected across nine studies and sequenced using ten capture kits in fourteen sequencing centers in the Alzheimer's Disease Sequencing Project. The joint-genotype called variant-called format (VCF) file contains only positions within the union of capture kits. The VCF was then processed specifically to account for the batch effects arising from the use of different capture kits from different studies. We identified 8.2 million autosomal variants. 96.82% of the variants are high-quality, and are located in 28,579 Ensembl transcripts. 41% of the variants are intronic and 1.8% of the variants are with CADD > 30, indicating they are of high predicted pathogenicity. Here we show our new strategy can generate high-quality data from processing these diversely generated WES samples. The improved ability to combine data sequenced in different batches benefits the whole genomics research community.

Late-stage Attentional Bias towards Food Cues Varies According to Weight Status.

The Current food environment has become increasingly obesogenic, with rates of obesity and related conditions continually rising. Advertisements for energy-dense foods are abundant and promote unhealthy eating behaviors by capitalizing on one's attentional bias towards food cues, a cognitive process resulting from the sensitization of highly reinforcing food. A heightened awareness towards food cues may promote overconsumption of energy-dense foods. The current study employed novel eye-tracking methodology to capture sustained, or late-stage, attentional bias towards food cues. Late-stage attentional bias is the aspect of attentional bias under conscious control and likely more prone to modification compared to initial/ early-stage attentional bias, which reflects automatic processes. The present study hypothesized late-stage attentional bias towards food cues is greater among individuals classified as overweight/obese than those classified as normal weight. Thirty (30) participants classified as overweight/obese (BMI ≥25) and 47 classified as normal weight (BMI <25) were assessed for late-stage attentional bias towards food cues, conceptualized as the percentage of time fixated on food cues when both food and neutral images were presented during a food-specific visual probe procedure task. Percentage of time fixated on food cues was 51.25 ± 1.27 (mean + SE) among individuals classified as overweight to obese while those classified as normal weight had a percent fixation of 47.26 ± 0.87 (P=0.03). In conclusion, individuals classified as overweight to obese have greater late-stage attentional bias towards food cues. This establishes an important factor influencing energy intake that may be modified in future clinical trials.

Multi-ancestry genome-wide meta-analysis of 56,241 individuals identifies LRRC4C, LHX5-AS1 and nominates ancestry-specific loci PTPRK , GRB14 , and KIAA0825 as novel risk loci for Alzheimer's disease: the Alzheimer's Disease Genetics Consortium.

Limited ancestral diversity has impaired our ability to detect risk variants more prevalent in non-European ancestry groups in genome-wide association studies (GWAS). We constructed and analyzed a multi-ancestry GWAS dataset in the Alzheimer's Disease (AD) Genetics Consortium (ADGC) to test for novel shared and ancestry-specific AD susceptibility loci and evaluate underlying genetic architecture in 37,382 non-Hispanic White (NHW), 6,728 African American, 8,899 Hispanic (HIS), and 3,232 East Asian individuals, performing within-ancestry fixed-effects meta-analysis followed by a cross-ancestry random-effects meta-analysis. We identified 13 loci with cross-ancestry associations including known loci at/near CR1 , BIN1 , TREM2 , CD2AP , PTK2B , CLU , SHARPIN , MS4A6A , PICALM , ABCA7 , APOE and two novel loci not previously reported at 11p12 ( LRRC4C ) and 12q24.13 ( LHX5-AS1 ). Reflecting the power of diverse ancestry in GWAS, we observed the SHARPIN locus using 7.1% the sample size of the original discovering single-ancestry GWAS (n=788,989). We additionally identified three GWS ancestry-specific loci at/near ( PTPRK ( P =2.4×10 -8 ) and GRB14 ( P =1.7×10 -8 ) in HIS), and KIAA0825 ( P =2.9×10 -8 in NHW). Pathway analysis implicated multiple amyloid regulation pathways (strongest with P adjusted =1.6×10 -4 ) and the classical complement pathway ( P adjusted =1.3×10 -3 ). Genes at/near our novel loci have known roles in neuronal development ( LRRC4C, LHX5-AS1 , and PTPRK ) and insulin receptor activity regulation ( GRB14 ). These findings provide compelling support for using traditionally-underrepresented populations for gene discovery, even with smaller sample sizes.

Chestnut resistance to the blight disease: insights from transcriptome analysis.

BACKGROUND: A century ago, Chestnut Blight Disease (CBD) devastated the American chestnut. Backcross breeding has been underway to introgress resistance from Chinese chestnut into surviving American chestnut genotypes. Development of genomic resources for the family Fagaceae, has focused in this project on Castanea mollissima Blume (Chinese chestnut) and Castanea dentata (Marsh.) Borkh (American chestnut) to aid in the backcross breeding effort and in the eventual identification of blight resistance genes through genomic sequencing and map based cloning. A previous study reported partial characterization of the transcriptomes from these two species. Here, further analyses of a larger dataset and assemblies including both 454 and capillary sequences were performed and defense related genes with differential transcript abundance (GDTA) in canker versus healthy stem tissues were identified. RESULTS: Over one and a half million cDNA reads were assembled into 34,800 transcript contigs from American chestnut and 48,335 transcript contigs from Chinese chestnut. Chestnut cDNA showed higher coding sequence similarity to genes in other woody plants than in herbaceous species. The number of genes tagged, the length of coding sequences, and the numbers of tagged members within gene families showed that the cDNA dataset provides a good resource for studying the American and Chinese chestnut transcriptomes. In silico analysis of transcript abundance identified hundreds of GDTA in canker versus healthy stem tissues. A significant number of additional DTA genes involved in the defense-response not reported in a previous study were identified here. These DTA genes belong to various pathways involving cell wall biosynthesis, reactive oxygen species (ROS), salicylic acid (SA), ethylene, jasmonic acid (JA), abscissic acid (ABA), and hormone signalling. DTA genes were also identified in the hypersensitive response and programmed cell death (PCD) pathways. These DTA genes are candidates for host resistance to the chestnut blight fungus, Cryphonectria parasitica. CONCLUSIONS: Our data allowed the identification of many genes and gene network candidates for host resistance to the chestnut blight fungus, Cryphonectria parasitica. The similar set of GDTAs in American chestnut and Chinese chestnut suggests that the variation in sensitivity to this pathogen between these species may be the result of different timing and amplitude of the response of the two to the pathogen infection. Resources developed in this study are useful for functional genomics, comparative genomics, resistance breeding and phylogenetics in the Fagaceae.

Packaging Biocomputing Software to Maximize Distribution and Reuse.

The majority of publications in computational biology and biocomputing develop or apply software approaches to relevant biological problems to some degree. While journals and conferences often prompt authors to make their source code available, these are often only basic requirements. Investigators often wish their software and tools were widely usable to the scientific community, but there are limited resources available to maximize the distribution and provide easy use of developed software. Even when authors adhere to standards of source code availability, the growing problem of system configuration issues, language and library version conflicts, and other implementation issues often impede the broad distribution, availability of software tools, and reproducibility of research. There are a variety of solutions to these implementation issues, but the learning curve for applying these solutions can be steep. This tutorial demonstrates tools and approaches for packaging and distribution of published code, and provides methodological practices for the broad and open sharing of new biocomputing software.

Contrasting effects of sleep fragmentation and angiotensin-II treatment upon pro-inflammatory responses of mice.

Disordered sleep promotes inflammation in brain and peripheral tissues, but the mechanisms that regulate these responses are poorly understood. One hypothesis is that activation of the sympathetic nervous system (SNS) from sleep loss elevates blood pressure to promote vascular sheer stress leading to inflammation. As catecholamines produced from SNS activation can directly regulate inflammation, we pharmacologically altered blood pressure using an alternative approach-manipulation of the renin-angiotensin system (RAS). Male C57BL6/J mice were treated with angiotensin or captopril to elevate and reduce blood pressure, respectively and then exposed to 24-h of sleep fragmentation (SF) or allowed to sleep (control). Pro- and anti-inflammatory cytokine gene expression and as endothelial adhesion gene expression as well as serum glucocorticoids (corticosterone) were measured. RAS manipulation elevated cytokines and endothelial adhesion expression in heart and aorta while SF increased cytokine expression in peripheral tissues, but not brain. However, there were interactive effects of angiotensin-II and SF upon cytokine gene expression in hippocampus and hypothalamus, but not prefrontal cortex. SF, but not RAS manipulation, elevated serum corticosterone concentration. These findings highlight the contrasting effects of RAS manipulation and SF, implying that inflammation from SF is acting on different pathways that are largely independent of RAS manipulation.

Alpha- and beta- adrenergic receptors regulate inflammatory responses to acute and chronic sleep fragmentation in mice.

Sleep is a recuperative process, and its dysregulation has cognitive, metabolic, and immunological effects that are largely deleterious to human health. Epidemiological and empirical studies have suggested that sleep fragmentation (SF) as result of obstructive sleep apnea (OSA) and other sleep abnormalities leads to pronounced inflammatory responses, which are influenced by the sympathetic nervous system (SNS). However, the underlying molecular mechanisms contributing to SNS regulation of SF-induced inflammation are not fully understood. To assess the effects of the SNS upon inflammatory responses to SF, C57BL/6j female mice were placed in automated SF chambers with horizontally moving bars across the bottom of each cage at specified intervals to disrupt sleep. Mice were first subjected to either control (no bar movement), acute sleep fragmentation (ASF), or chronic sleep fragmentation (CSF) on a 12:12-h light/dark schedule. ASF involved a bar sweep every 120 s for 24 h, whereas CSF involved a bar sweep every 120 s for 12 h (during 12 L; resting period) over a period of 4 weeks. After exposure to these conditions, mice received an intraperitoneal injection of either phentolamine (5 mg/kg BW; an α-adrenergic receptor blocker), propranolol (5 mg/kg BW; a ß-adrenergic receptor blocker), or vehicle (saline). Serum corticosterone concentration, brain and peripheral cytokine (IL1ß, TNFα, and TGFß) mRNA expression, and body mass were assessed. ASF and CSF significantly elevated serum corticosterone concentrations as well as cytokine mRNA expression levels compared with controls, and mice subjected to CSF had decreased body mass relative to controls. Mice subjected to CSF and treated with phentolamine or propranolol had a greater propensity for a decrease in cytokine gene expression compared with ASF, but effects were tissue-specific. Taken together, these results suggest that both α- and ß-adrenergic receptors contribute to the SNS mediation of inflammatory responses, and adrenergic antagonists may effectively mitigate tissue-specific SF-mediated inflammation.

Safety profile of D-penicillamine: a comprehensive pharmacovigilance analysis by FDA adverse event reporting system.

BACKGROUND: D-penicillamine (D-pen) is a copper-chelating drug and has immune-modulatory properties. D-pen is used to treat rheumatoid arthritis, Wilson's disease, and kidney stones (cystinuria). However, associated adverse events (AEs) of D-pen treatment are frequent and often serious. Therefore, a comprehensive assessment of the safety profile of D-pen is urgently needed. RESEARCH DESIGN AND METHODS: We identified and analyzed AEs associated with D-pen between April-1970 to July-2020 from the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS) databases and calculated the reported odds ratio (ROR) with 95% confidence intervals (CI) using the disproportionality analysis. RESULTS: A total of 9,150,234 AEs related to drugs were reported in the FAERS database, of which 542 were related to D-Pen. We report that D-pen was associated with dystonia (ROR: 20.52; 95%CI: 12.46-33.80), drug hypersensitivity (ROR: 5.42; 95%CI: 3.72-7.90), pancytopenia (ROR: 10.20; 95%CI: 5.61-18.56), joint swelling (ROR: 9.07; 95%CI: 5.51-14.94), renal-impairment (ROR: 6.68; 95%CI: 3.67-12.15), dysphagia (ROR: 5.05; 95%CI: 2.76-8.89), aggravation of condition (ROR: 4.16; 95%CI: 2.60-6.67), congestive cardiac failure (ROR: 4.04; 95%CI: 2.22-7.35), peripheral edema (ROR: 3.77; 95%CI: 2.17-6.55), tremor (ROR: 3.46; 95%CI: 2.00-6.01), pyrexia (ROR: 3.46; 95%CI: 2.00-6.01), and gait disturbance (ROR: 2.41; 95%CI: 1.29-4.52). CONCLUSIONS: Patients taking D-pen require close monitoring of renal function, blood counts, immunity, liver, cardiac function, and neurological function. D-pen suppresses immune system which maximizes the risk of infection.

Packaging Biocomputing Software to Maximize Distribution and Reuse.

The majority of accepted papers in computational biology and biocomputing describe new software approaches to relevant biological problems. While journals and conferences often require the availability of software and source code, there are limited resources available to maximize the distribution and use of developed software within the scientific community. The accepted standard is to make source code available for new approaches in published work, the growing problem of system configuration issues, language, library version conflicts, and other implementation issues often impede the broad distribution, availability of software tools, and reproducibility of research. There are a variety of solutions to these implementation issues, but the learning curve for applying these solutions is steep. This tutorial demonstrates tools and approaches for packaging and distribution of published code, and provides methodological practices for the broad and open sharing of new biocomputing software.

Hadoop and PySpark for reproducibility and scalability of genomic sequencing studies.

Modern genomic studies are rapidly growing in scale, and the analytical approaches used to analyze genomic data are increasing in complexity. Genomic data management poses logistic and computational challenges, and analyses are increasingly reliant on genomic annotation resources that create their own data management and versioning issues. As a result, genomic datasets are increasingly handled in ways that limit the rigor and reproducibility of many analyses. In this work, we examine the use of the Spark infrastructure for the management, access, and analysis of genomic data in comparison to traditional genomic workflows on typical cluster environments. We validate the framework by reproducing previously published results from the Alzheimer's Disease Sequencing Project. Using the framework and analyses designed using Jupyter notebooks, Spark provides improved workflows, reduces user-driven data partitioning, and enhances the portability and reproducibility of distributed analyses required for large-scale genomic studies.

Comparison of the transcriptomes of American chestnut (Castanea dentata) and Chinese chestnut (Castanea mollissima) in response to the chestnut blight infection.

UNLABELLED: BACKGROUND1471-2229-9-51: American chestnut (Castanea dentata) was devastated by an exotic pathogen in the beginning of the twentieth century. This chestnut blight is caused by Cryphonectria parasitica, a fungus that infects stem tissues and kills the trees by girdling them. Because of the great economic and ecological value of this species, significant efforts have been made over the century to combat this disease, but it wasn't until recently that a focused genomics approach was initiated. Prior to the Genomic Tool Development for the Fagaceae project, genomic resources available in public databases for this species were limited to a few hundred ESTs. To identify genes involved in resistance to C. parasitica, we have sequenced the transcriptome from fungal infected and healthy stem tissues collected from blight-sensitive American chestnut and blight-resistant Chinese chestnut (Castanea mollissima) trees using ultra high throughput pyrosequencing. RESULTS: We produced over a million 454 reads, totaling over 250 million bp, from which we generated 40,039 and 28,890 unigenes in total from C. mollissima and C. dentata respectively. The functions of the unigenes, from GO annotation, cover a diverse set of molecular functions and biological processes, among which we identified a large number of genes associated with resistance to stresses and response to biotic stimuli. In silico expression analyses showed that many of the stress response unigenes were expressed more in canker tissues versus healthy stem tissues in both American and Chinese chestnut. Comparative analysis also identified genes belonging to different pathways of plant defense against biotic stresses that are differentially expressed in either American or Chinese chestnut canker tissues. CONCLUSION: Our study resulted in the identification of a large set of cDNA unigenes from American chestnut and Chinese chestnut. The ESTs and unigenes from this study constitute an important resource to the scientific community interested in the discovery of genes involved in various biological processes in Chestnut and other species. The identification of many defense-related genes differentially expressed in canker vs. healthy stem in chestnuts provides many new candidate genes for developing resistance to the chestnut blight and for studying pathways involved in responses of trees to necrotrophic pathogens. We also identified several candidate genes that may underline the difference in resistance to Cryphonectria parasitica between American chestnut and Chinese chestnut.

Association genetics in Pinus taeda L. I. Wood property traits.

Genetic association is a powerful method for dissecting complex adaptive traits due to (i) fine-scale mapping resulting from historical recombination, (ii) wide coverage of phenotypic and genotypic variation within a single experiment, and (iii) the simultaneous discovery of loci and alleles. In this article, genetic association among single nucleotide polymorphisms (58 SNPs) from 20 wood- and drought-related candidate genes and an array of wood property traits with evolutionary and commercial importance, namely, earlywood and latewood specific gravity, percentage of latewood, earlywood microfibril angle, and wood chemistry (lignin and cellulose content), was tested using mixed linear models (MLMs) that account for relatedness among individuals by using a pairwise kinship matrix. Population structure, a common systematic bias in association studies, was assessed using 22 nuclear microsatellites. Different phenotype:genotype associations were found, some of them confirming previous evidence from collocation of QTL and genes in linkage maps (for example, 4cl and percentage of latewood) and two that involve nonsynonymous polymorphisms (cad SNP M28 with earlywood specific gravity and 4cl SNP M7 with percentage of latewood). The strongest genetic association found in this study was between allelic variation in alpha-tubulin, a gene involved in the formation of cortical microtubules, and earlywood microfibril angle. Intragenic LD decays rapidly in conifers; thus SNPs showing genetic association are likely to be located in close proximity to the causative polymorphisms. This first multigene association genetic study in forest trees has shown the feasibility of candidate gene strategies for dissecting complex adaptive traits, provided that genes belonging to key pathways and appropriate statistical tools are used. This approach is of particular utility in species such as conifers, where genomewide strategies are limited by their large genomes.

Hi-MC: a novel method for high-throughput mitochondrial haplogroup classification.

Effective approaches for assessing mitochondrial DNA (mtDNA) variation are important to multiple scientific disciplines. Mitochondrial haplogroups characterize branch points in the phylogeny of mtDNA. Several tools exist for mitochondrial haplogroup classification. However, most require full or partial mtDNA sequence which is often cost prohibitive for studies with large sample sizes. The purpose of this study was to develop Hi-MC, a high-throughput method for mitochondrial haplogroup classification that is cost effective and applicable to large sample sizes making mitochondrial analysis more accessible in genetic studies. Using rigorous selection criteria, we defined and validated a custom panel of mtDNA single nucleotide polymorphisms that allows for accurate classification of European, African, and Native American mitochondrial haplogroups at broad resolution with minimal genotyping and cost. We demonstrate that Hi-MC performs well in samples of European, African, and Native American ancestries, and that Hi-MC performs comparably to a commonly used classifier. Implementation as a software package in R enables users to download and run the program locally, grants greater flexibility in the number of samples that can be run, and allows for easy expansion in future revisions. Hi-MC is available in the CRAN repository and the source code is freely available at https://github.com/vserch/himc.

DNA sequence variation and selection of tag single-nucleotide polymorphisms at candidate genes for drought-stress response in Pinus taeda L.

Genetic association studies are rapidly becoming the experimental approach of choice to dissect complex traits, including tolerance to drought stress, which is the most common cause of mortality and yield losses in forest trees. Optimization of association mapping requires knowledge of the patterns of nucleotide diversity and linkage disequilibrium and the selection of suitable polymorphisms for genotyping. Moreover, standard neutrality tests applied to DNA sequence variation data can be used to select candidate genes or amino acid sites that are putatively under selection for association mapping. In this article, we study the pattern of polymorphism of 18 candidate genes for drought-stress response in Pinus taeda L., an important tree crop. Data analyses based on a set of 21 putatively neutral nuclear microsatellites did not show population genetic structure or genomewide departures from neutrality. Candidate genes had moderate average nucleotide diversity at silent sites (pi(sil) = 0.00853), varying 100-fold among single genes. The level of within-gene LD was low, with an average pairwise r2 of 0.30, decaying rapidly from approximately 0.50 to approximately 0.20 at 800 bp. No apparent LD among genes was found. A selective sweep may have occurred at the early-response-to-drought-3 (erd3) gene, although population expansion can also explain our results and evidence for selection was not conclusive. One other gene, ccoaomt-1, a methylating enzyme involved in lignification, showed dimorphism (i.e., two highly divergent haplotype lineages at equal frequency), which is commonly associated with the long-term action of balancing selection. Finally, a set of haplotype-tagging SNPs (htSNPs) was selected. Using htSNPs, a reduction of genotyping effort of approximately 30-40%, while sampling most common allelic variants, can be gained in our ongoing association studies for drought tolerance in pine.

The Douglas-Fir Genome Sequence Reveals Specialization of the Photosynthetic Apparatus in Pinaceae.

A reference genome sequence for Pseudotsuga menziesii var. menziesii (Mirb.) Franco (Coastal Douglas-fir) is reported, thus providing a reference sequence for a third genus of the family Pinaceae. The contiguity and quality of the genome assembly far exceeds that of other conifer reference genome sequences (contig N50 = 44,136 bp and scaffold N50 = 340,704 bp). Incremental improvements in sequencing and assembly technologies are in part responsible for the higher quality reference genome, but it may also be due to a slightly lower exact repeat content in Douglas-fir vs. pine and spruce. Comparative genome annotation with angiosperm species reveals gene-family expansion and contraction in Douglas-fir and other conifers which may account for some of the major morphological and physiological differences between the two major plant groups. Notable differences in the size of the NDH-complex gene family and genes underlying the functional basis of shade tolerance/intolerance were observed. This reference genome sequence not only provides an important resource for Douglas-fir breeders and geneticists but also sheds additional light on the evolutionary processes that have led to the divergence of modern angiosperms from the more ancient gymnosperms.

Democratizing an electroluminescence imaging apparatus and analytics project for widespread data acquisition in photovoltaic materials.

We present a description of an electroluminescence (EL) apparatus, easily sourced from commercially available components, with a quantitative image processing platform that demonstrates feasibility for the widespread utility of EL imaging as a characterization tool. We validated our system using a Gage R&R analysis to find a variance contribution by the measurement system of 80.56%, which is typically unacceptable, but through quantitative image processing and development of correction factors a variance contribution by the measurement system of 2.41% was obtained. We further validated the system by quantifying the signal-to-noise ratio (SNR) and found values consistent with other systems published in the literature, at SNR values of 10-100, albeit at exposure times of greater than 1 s compared to 10 ms for other systems. This SNR value range is acceptable for image feature recognition, providing the opportunity for widespread data acquisition and large scale data analytics of photovoltaics.

Mapping of quantitative trait loci controlling adaptive traits in coastal Douglas fir. III. Quantitative trait loci-by-environment interactions.

Quantitative trait loci (QTL) were mapped in the woody perennial Douglas fir (Pseudotsuga menziesii var. menziesii [Mirb.] Franco) for complex traits controlling the timing of growth initiation and growth cessation. QTL were estimated under controlled environmental conditions to identify QTL interactions with photoperiod, moisture stress, winter chilling, and spring temperatures. A three-generation mapping population of 460 cloned progeny was used for genetic mapping and phenotypic evaluations. An all-marker interval mapping method was used for scanning the genome for the presence of QTL and single-factor ANOVA was used for estimating QTL-by-environment interactions. A modest number of QTL were detected per trait, with individual QTL explaining up to 9.5% of the phenotypic variation. Two QTL-by-treatment interactions were found for growth initiation, whereas several QTL-by-treatment interactions were detected among growth cessation traits. This is the first report of QTL interactions with specific environmental signals in forest trees and will assist in the identification of candidate genes controlling these important adaptive traits in perennial plants.