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Objectives: This report provides information about the public release of the 2018-2019 Maize G X E project of the Genomes to Fields (G2F) Initiative datasets. G2F is an umbrella initiative that evaluates maize hybrids and inbred lines across multiple environments and makes available phenotypic, genotypic, environmental, and metadata information. The initiative understands the necessity to characterize and deploy public sources of genetic diversity to face the challenges for more sustainable agriculture in the context of variable environmental conditions., Data Description: Datasets include phenotypic, climatic, and soil measurements, metadata information, and inbred genotypic information for each combination of location and year. Collaborators in the G2F initiative collected data for each location and year; members of the group responsible for coordination and data processing combined all the collected information and removed obvious erroneous data. The collaborators received the data before the DOI release to verify and declare that the data generated in their own locations was accurate. ReadMe and description files are available for each dataset. Previous years of evaluation are already publicly available, with common hybrids present to connect across all locations and years evaluated since this project's inception., (© 2023. The Author(s).)

Background: The initial management of acute aortic dissection centers around rapid control of blood pressure and heart rate, commonly requiring initiation of continuous intravenous (IV) antihypertensive agents and intensive care unit (ICU) admission. However, there is limited guidance for when and how to transition off IV infusions to enteral agents, potentially extending ICU length of stay (LOS) in stable patients who are otherwise ready for floor transfer. The objective of this study is to compare the impact of rapid vs. slow transition from IV to enteral vasoactive medications on ICU LOS., Methods: In this retrospective cohort study of 56 adult patients admitted with aortic dissection requiring IV vasoactive infusions for >6 hours, patients were grouped by time required to fully transition from IV to enteral vasoactive agents. Patients who transitioned in ≤72 hours were considered the "rapid" group, and the "slow" group required >72 hours to fully convert. The primary endpoint was ICU LOS., Results: For the primary endpoint, the median ICU LOS was 3.6 days for the "rapid" group, compared to 7.7 days in the "slow" group (P<0.001). The "slow" group required a significantly longer duration of IV vasoactive infusions (115.7 vs. 36.0 hours, P<0.001) and also trended towards longer median hospital LOS. The two cohorts had similar incidences of hypotension., Conclusions: In this study, rapid transition to enteral antihypertensives within 72 hours was associated with a shorter ICU LOS without an increase in hypotension., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-22-1274/coif). The authors have no conflicts of interest to declare., (2023 Journal of Thoracic Disease. All rights reserved.)

Accurate prediction of the phenotypic outcomes produced by different combinations of genotypes, environments, and management interventions remains a key goal in biology with direct applications to agriculture, research, and conservation. The past decades have seen an expansion of new methods applied toward this goal. Here we predict maize yield using deep neural networks, compare the efficacy of 2 model development methods, and contextualize model performance using conventional linear and machine learning models. We examine the usefulness of incorporating interactions between disparate data types. We find deep learning and best linear unbiased predictor (BLUP) models with interactions had the best overall performance. BLUP models achieved the lowest average error, but deep learning models performed more consistently with similar average error. Optimizing deep neural network submodules for each data type improved model performance relative to optimizing the whole model for all data types at once. Examining the effect of interactions in the best-performing model revealed that including interactions altered the model's sensitivity to weather and management features, including a reduction of the importance scores for timepoints expected to have a limited physiological basis for influencing yield-those at the extreme end of the season, nearly 200 days post planting. Based on these results, deep learning provides a promising avenue for the phenotypic prediction of complex traits in complex environments and a potential mechanism to better understand the influence of environmental and genetic factors., Competing Interests: Conflicts of interest None declared., (Published by Oxford University Press on behalf of the Genetics Society of America 2023.)

Crop genetic diversity for climate adaptations is globally partitioned. We performed experimental evolution in maize to understand the response to selection and how plant germplasm can be moved across geographical zones. Initialized with a common population of tropical origin, artificial selection on flowering time was performed for two generations at eight field sites spanning 25° latitude, a 2800 km transect. We then jointly tested all selection lineages across the original sites of selection, for the target trait and 23 other traits. Modeling intergenerational shifts in a physiological reaction norm revealed separate components for flowering-time plasticity. Generalized and local modes of selection altered the plasticity of each lineage, leading to a latitudinal pattern in the responses to selection that were strongly driven by photoperiod. This transformation led to widespread changes in developmental, architectural, and yield traits, expressed collectively in an environment-dependent manner. Furthermore, selection for flowering time alone alleviated a maladaptive syndrome and improved yields for tropical maize in the temperate zone. Our findings show how phenotypic selection can rapidly shift the flowering phenology and plasticity of maize. They also demonstrate that selecting crops to local conditions can accelerate adaptation to climate change., (© 2023 The Authors. New Phytologist © 2023 New Phytologist Foundation.)

Prenatal and postnatal treatment modalities for congenital diaphragmatic hernia (CDH) continue to improve, however patients still face high rates of morbidity and mortality caused by severe underlying persistent pulmonary hypertension and pulmonary hypoplasia. Though the majority of CDH cases are idiopathic, it is believed that CDH is a polygenic developmental defect caused by interactions between candidate genes, as well as environmental and epigenetic factors. However, the origin and pathogenesis of these developmental insults are poorly understood. Further, connections between disrupted lung development and the failure of diaphragmatic closure during embryogenesis have not been fully elucidated. Though several animal models have been useful in identifying candidate genes and disrupted signalling pathways, more studies are required to understand the pathogenesis and to develop effective preventative care. In this article, we summarize the most recent litterature on disrupted embryological lung and diaphragmatic development associated with CDH., Competing Interests: Declaration of Competing Interest The authors declare no conflict of interest., (Copyright © 2022. Published by Elsevier Inc.)

Large-scale investigations of maize kernel traits important to researchers, breeders, and processors require high throughput methods, which are presently lacking. To address this bottleneck, we developed a novel flatbed platform that automatically acquires and analyzes multiwavelength near-infrared (NIR hyperspectral) images of maize kernels precisely enough to support robust predictions of protein content, density, and endosperm vitreousness. The upward facing-camera design and the automated ability to analyze the embryo or abgerminal sides of each individual kernel in a sample with the appropriate side-specific model helped to produce a superior combination of throughput and prediction accuracy compared to other single-kernel platforms. Protein was predicted to within 0.85% (root mean square error of prediction), density to within 0.038 g/cm 3 , and endosperm vitreousness percentage to within 6.3%. Kernel length and width were also accurately measured so that each kernel in a rapidly scanned sample was comprehensively characterized., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The Stiff Stalk heterotic pool is a foundation of US maize seed parent germplasm and has been heavily utilized by both public and private maize breeders since its inception in the 1930s. Flowering time and plant height are critical characteristics for both inbred parents and their test crossed hybrid progeny. To study these traits, a 6-parent multiparent advanced generation intercross population was developed including maize inbred lines B73, B84, PHB47 (B37 type), LH145 (B14 type), PHJ40 (novel early Stiff Stalk), and NKH8431 (B73/B14 type). A set of 779 doubled haploid lines were evaluated for flowering time and plant height in 2 field replicates in 2016 and 2017, and a subset of 689 and 561 doubled haploid lines were crossed to 2 testers, respectively, and evaluated as hybrids in 2 locations in 2018 and 2019 using an incomplete block design. Markers were derived from a practical haplotype graph built from the founder whole genome assemblies and genotype-by-sequencing and exome capture-based sequencing of the population. Genetic mapping utilizing an update to R/qtl2 revealed differing profiles of significant loci for both traits between 635 of the DH lines and 2 sets of 570 and 471 derived hybrids. Genomic prediction was used to test the feasibility of predicting hybrid phenotypes based on the per se data. Predictive abilities were highest on direct models trained using the data they would predict (0.55-0.63), and indirect models trained using per se data to predict hybrid traits had slightly lower predictive abilities (0.49-0.55). Overall, this finding is consistent with the overlapping and nonoverlapping significant quantitative trait loci found within the per se and hybrid populations and suggests that selections for phenology traits can be made effectively on doubled haploid lines before hybrid data is available., (© The Author(s) 2022. Published by Oxford University Press on behalf of Genetics Society of America. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

In biological research domains, liquid chromatography-mass spectroscopy (LC-MS) has prevailed as the preferred technique for generating high quality metabolomic data. However, even with advanced instrumentation and established data acquisition protocols, technical errors are still routinely encountered and can pose a significant challenge to unveiling biologically relevant information. In large-scale studies, signal drift and batch effects are how technical errors are most commonly manifested. We developed pseudoDrift, an R package with capabilities for data simulation and outlier detection, and a new training and testing approach that is implemented to capture and to optionally correct for technical errors in LC-MS metabolomic data. Using data simulation, we demonstrate here that our approach performs equally as well as existing methods and offers increased flexibility to the researcher. As part of our study, we generated a targeted LC-MS dataset that profiled 33 phenolic compounds from seedling stem tissue in 602 genetically diverse non-transgenic maize inbred lines. This dataset provides a unique opportunity to investigate the dynamics of specialized metabolism in plants.

The stiff-stalk heterotic group in Maize (Zea mays L.) is an important source of inbreds used in U.S. commercial hybrid production. Founder inbreds B14, B37, B73, and, to a lesser extent, B84, are found in the pedigrees of a majority of commercial seed parent inbred lines. We created high-quality genome assemblies of B84 and four expired Plant Variety Protection (ex-PVP) lines LH145 representing B14, NKH8431 of mixed descent, PHB47 representing B37, and PHJ40, which is a Pioneer Hi-Bred International (PHI) early stiff-stalk type. Sequence was generated using long-read sequencing achieving highly contiguous assemblies of 2.13-2.18 Gbp with N50 scaffold lengths >200 Mbp. Inbred-specific gene annotations were generated using a core five-tissue gene expression atlas, whereas transposable element (TE) annotation was conducted using de novo and homology-directed methodologies. Compared with the reference inbred B73, synteny analyses revealed extensive collinearity across the five stiff-stalk genomes, although unique components of the maize pangenome were detected. Comparison of this set of stiff-stalk inbreds with the original Iowa Stiff Stalk Synthetic breeding population revealed that these inbreds represent only a proportion of variation in the original stiff-stalk pool and there are highly conserved haplotypes in released public and ex-Plant Variety Protection inbreds. Despite the reduction in variation from the original stiff-stalk population, substantial genetic and genomic variation was identified supporting the potential for continued breeding success in this pool. The assemblies described here represent stiff-stalk inbreds that have historical and commercial relevance and provide further insight into the emerging maize pangenome., (© 2021 The Authors. The Plant Genome published by Wiley Periodicals LLC on behalf of Crop Science Society of America.)

Somatic and germline mutations in the proofreading domain of the replicative DNA polymerase ε (POLE-exonuclease domain mutations, POLE-EDMs) are frequently found in colorectal and endometrial cancers and, occasionally, in other tumours. POLE-associated cancers typically display hypermutation, and a unique mutational signature, with a predominance of C > A transversions in the context TCT and C > T transitions in the context TCG. To understand better the contribution of hypermutagenesis to tumour development, we have modelled the most recurrent POLE-EDM (POLE-P286R) in Schizosaccharomyces pombe. Whole-genome sequencing analysis revealed that the corresponding pol2-P287R allele also has a strong mutator effect in vivo, with a high frequency of base substitutions and relatively few indel mutations. The mutations are equally distributed across different genomic regions, but in the immediate vicinity there is an asymmetry in AT frequency. The most abundant base-pair changes are TCT > TAT transversions and, in contrast to human mutations, TCG > TTG transitions are not elevated, likely due to the absence of cytosine methylation in fission yeast. The pol2-P287R variant has an increased sensitivity to elevated dNTP levels and DNA damaging agents, and shows reduced viability on depletion of the Pfh1 helicase. In addition, S phase is aberrant and RPA foci are elevated, suggestive of ssDNA or DNA damage, and the pol2-P287R mutation is synthetically lethal with rad3 inactivation, indicative of checkpoint activation. Significantly, deletion of genes encoding some translesion synthesis polymerases, most notably Pol κ, partially suppresses pol2-P287R hypermutation, indicating that polymerase switching contributes to this phenotype., Competing Interests: The authors have declared that no competing interests exist.

Traditional phenotyping methods, coupled with genetic mapping in segregating populations, have identified loci governing complex traits in many crops. Unoccupied aerial systems (UAS)-based phenotyping has helped to reveal a more novel and dynamic relationship between time-specific associated loci with complex traits previously unable to be evaluated. Over 1,500 maize (Zea mays L.) hybrid row plots containing 280 different replicated maize hybrids from the Genomes to Fields (G2F) project were evaluated agronomically and using UAS in 2017. Weekly UAS flights captured variation in plant heights during the growing season under three different management conditions each year: optimal planting with irrigation (G2FI), optimal dryland planting without irrigation (G2FD), and a stressed late planting (G2LA). Plant height of different flights were ranked based on importance for yield using a random forest (RF) algorithm. Plant heights captured by early flights in G2FI trials had higher importance (based on Gini scores) for predicting maize grain yield (GY) but also higher accuracies in genomic predictions which fluctuated for G2FD (-0.06∼0.73), G2FI (0.33∼0.76), and G2LA (0.26∼0.78) trials. A genome-wide association analysis discovered 52 significant single nucleotide polymorphisms (SNPs), seven were found consistently in more than one flights or trial; 45 were flight or trial specific. Total cumulative marker effects for each chromosome's contributions to plant height also changed depending on flight. Using UAS phenotyping, this study showed that many candidate genes putatively play a role in the regulation of plant architecture even in relatively early stages of maize growth and development., (© 2021 The Authors. The Plant Genome published by Wiley Periodicals LLC on behalf of Crop Science Society of America.)

Genomic prediction provides an efficient alternative to conventional phenotypic selection for developing improved cultivars with desirable characteristics. New and improved methods to genomic prediction are continually being developed that attempt to deal with the integration of data types beyond genomic information. Modern automated weather systems offer the opportunity to capture continuous data on a range of environmental parameters at specific field locations. In principle, this information could characterize training and target environments and enhance predictive ability by incorporating weather characteristics as part of the genotype-by-environment (G×E) interaction component in prediction models. We assessed the usefulness of including weather data variables in genomic prediction models using a naïve environmental kinship model across 30 environments comprising the Genomes to Fields (G2F) initiative in 2014 and 2015. Specifically four different prediction scenarios were evaluated (i) tested genotypes in observed environments; (ii) untested genotypes in observed environments; (iii) tested genotypes in unobserved environments; and (iv) untested genotypes in unobserved environments. A set of 1,481 unique hybrids were evaluated for grain yield. Evaluations were conducted using five different models including main effect of environments; general combining ability (GCA) effects of the maternal and paternal parents modeled using the genomic relationship matrix; specific combining ability (SCA) effects between maternal and paternal parents; interactions between genetic (GCA and SCA) effects and environmental effects; and finally interactions between the genetics effects and environmental covariates. Incorporation of the genotype-by-environment interaction term improved predictive ability across all scenarios. However, predictive ability was not improved through inclusion of naive environmental covariates in G×E models. More research should be conducted to link the observed weather conditions with important physiological aspects in plant development to improve predictive ability through the inclusion of weather data., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Jarquin, de Leon, Romay, Bohn, Buckler, Ciampitti, Edwards, Ertl, Flint-Garcia, Gore, Graham, Hirsch, Holland, Hooker, Kaeppler, Knoll, Lee, Lawrence-Dill, Lynch, Moose, Murray, Nelson, Rocheford, Schnable, Schnable, Smith, Springer, Thomison, Tuinstra, Wisser, Xu, Yu and Lorenz.)

High-dimensional and high-throughput genomic, field performance, and environmental data are becoming increasingly available to crop breeding programs, and their integration can facilitate genomic prediction within and across environments and provide insights into the genetic architecture of complex traits and the nature of genotype-by-environment interactions. To partition trait variation into additive and dominance (main effect) genetic and corresponding genetic-by-environment variances, and to identify specific environmental factors that influence genotype-by-environment interactions, we curated and analyzed genotypic and phenotypic data on 1918 maize (Zea mays L.) hybrids and environmental data from 65 testing environments. For grain yield, dominance variance was similar in magnitude to additive variance, and genetic-by-environment variances were more important than genetic main effect variances. Models involving both additive and dominance relationships best fit the data and modeling unique genetic covariances among all environments provided the best characterization of the genotype-by-environment interaction patterns. Similarity of relative hybrid performance among environments was modeled as a function of underlying weather variables, permitting identification of weather covariates driving correlations of genetic effects across environments. The resulting models can be used for genomic prediction of mean hybrid performance across populations of environments tested or for environment-specific predictions. These results can also guide efforts to incorporate high-throughput environmental data into genomic prediction models and predict values in new environments characterized with the same environmental characteristics., (Published by Oxford University Press on behalf of Genetics Society of America 2021. This work is written by US Government employees and is in the public domain in the US.)

Single-parent expression (SPE) is defined as gene expression in only one of the two parents. SPE can arise from differential expression between parental alleles, termed non-presence/absence (non-PAV) SPE, or from the physical absence of a gene in one parent, termed PAV SPE. We used transcriptome data of diverse Zea mays (maize) inbreds and hybrids, including 401 samples from five different tissues, to test for differences between these types of SPE genes. Although commonly observed, SPE is highly genotype and tissue specific. A positive correlation was observed between the genetic distance of the two inbred parents and the number of SPE genes identified. Regulatory analysis showed that PAV SPE and non-PAV SPE genes are mainly regulated by cis effects, with a small fraction under trans regulation. Polymorphic transposable element insertions in promoter sequences contributed to the high level of cis regulation for PAV SPE and non-PAV SPE genes. PAV SPE genes were more frequently expressed in hybrids than non-PAV SPE genes. The expression of parentally silent alleles in hybrids of non-PAV SPE genes was relatively rare but occurred in most hybrids. Non-PAV SPE genes with expression of the silent allele in hybrids are more likely to exhibit above high parent expression level than hybrids that do not express the silent allele, leading to non-additive expression. This study provides a comprehensive understanding of the nature of non-PAV SPE and PAV SPE genes and their roles in gene expression complementation in maize hybrids., (© 2020 Society for Experimental Biology and John Wiley & Sons Ltd.)

Key Message: Significant introgression-by-environment interactions are observed for traits throughout development from small introgressed segments of the genome. Relatively small genomic introgressions containing quantitative trait loci can have significant impacts on the phenotype of an individual plant. However, the magnitude of phenotypic effects for the same introgression can vary quite substantially in different environments due to introgression-by-environment interactions. To study potential patterns of introgression-by-environment interactions, fifteen near-isogenic lines (NILs) with > 90% B73 genetic background and multiple Mo17 introgressions were grown in 16 different environments. These environments included five geographical locations with multiple planting dates and multiple planting densities. The phenotypic impact of the introgressions was evaluated for up to 26 traits that span different growth stages in each environment to assess introgression-by-environment interactions. Results from this study showed that small portions of the genome can drive significant genotype-by-environment interaction across a wide range of vegetative and reproductive traits, and the magnitude of the introgression-by-environment interaction varies across traits. Some introgressed segments were more prone to introgression-by-environment interaction than others when evaluating the interaction on a whole plant basis throughout developmental time, indicating variation in phenotypic plasticity throughout the genome. Understanding the profile of introgression-by-environment interaction in NILs is useful in consideration of how small introgressions of QTL or transgene containing regions might be expected to impact traits in diverse environments.

The hydroxycinnamic acids p-coumaric acid (pCA) and ferulic acid (FA) add diversity to the portfolio of products produced by using grass-fed lignocellulosic biorefineries. The level of lignin-bound pCA in Zea mays was modified by the alteration of p-coumaroyl-CoA monolignol transferase expression. The biomass was processed in a lab-scale alkaline-pretreatment biorefinery process and the data were used for a baseline technoeconomic analysis to determine where to direct future research efforts to couple plant design to biomass utilization processes. It is concluded that future plant engineering efforts should focus on strategies that ramp up accumulation of one type of hydroxycinnamate (pCA or FA) predominantly and suppress that of the other. Technoeconomic analysis indicates that target extraction titers of one hydroxycinnamic acid need to be >50 g kg -1 biomass, at least five times higher than observed titers for the impure pCA/FA product mixture from wild-type maize. The technical challenge for process engineers is to develop a viable process that requires more than 80 % reduction of the isolation costs., (© 2020 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.)

Objectives: Advanced tools and resources are needed to efficiently and sustainably produce food for an increasing world population in the context of variable environmental conditions. The maize genomes to fields (G2F) initiative is a multi-institutional initiative effort that seeks to approach this challenge by developing a flexible and distributed infrastructure addressing emerging problems. G2F has generated large-scale phenotypic, genotypic, and environmental datasets using publicly available inbred lines and hybrids evaluated through a network of collaborators that are part of the G2F's genotype-by-environment (G × E) project. This report covers the public release of datasets for 2014-2017., Data Description: Datasets include inbred genotypic information; phenotypic, climatic, and soil measurements and metadata information for each testing location across years. For a subset of inbreds in 2014 and 2015, yield component phenotypes were quantified by image analysis. Data released are accompanied by README descriptions. For genotypic and phenotypic data, both raw data and a version without outliers are reported. For climatic data, a version calibrated to the nearest airport weather station and a version without outliers are reported. The 2014 and 2015 datasets are updated versions from the previously released files [1] while 2016 and 2017 datasets are newly available to the public.

Small RNAs (sRNAs) regulate gene expression, play important roles in epigenetic pathways, and are hypothesized to contribute to hybrid vigor in plants. Prior investigations have provided valuable insights into associations between sRNAs and heterosis, often using a single hybrid genotype or tissue, but our understanding of the role of sRNAs and their potential value to plant breeding are limited by an incomplete picture of sRNA variation between diverse genotypes and development stages. Here, we provide a deep exploration of sRNA variation and inheritance among a panel of 108 maize ( Zea mays ) samples spanning five tissues from eight inbred parents and 12 hybrid genotypes, covering a spectrum of heterotic groups, genetic variation, and levels of heterosis for various traits. We document substantial developmental and genotypic influences on sRNA expression, with varying patterns for 21-nucleotide (nt), 22-nt, and 24-nt sRNAs. We provide a detailed view of the distribution of sRNAs in the maize genome, revealing a complex makeup that also shows developmental plasticity, particularly for 22-nt sRNAs. sRNAs exhibited substantially more variation between inbreds as compared with observed variation for gene expression. In hybrids, we identify locus-specific examples of nonadditive inheritance, mostly characterized as partial or complete dominance, but rarely outside the parental range. However, the global abundance of 21-nt, 22-nt, and 24-nt sRNAs varies very little between inbreds and hybrids, suggesting that hybridization affects sRNA expression principally at specific loci rather than on a global scale. This study provides a valuable resource for understanding the potential role of sRNAs in hybrid vigor., (© 2020 American Society of Plant Biologists. All Rights Reserved.)

Understanding the evolutionary capacity of populations to adapt to novel environments is one of the major pursuits in genetics. Moreover, for plant breeding, maladaptation is the foremost barrier to capitalizing on intraspecific variation in order to develop new breeds for future climate scenarios in agriculture. Using a unique study design, we simultaneously dissected the population and quantitative genomic basis of short-term evolution in a tropical landrace of maize that was translocated to a temperate environment and phenotypically selected for adaptation in flowering time phenology. Underlying 10 generations of directional selection, which resulted in a 26-day mean decrease in female-flowering time, [Formula: see text] of the heritable variation mapped to [Formula: see text] of the genome, where, overall, alleles shifted in frequency beyond the boundaries of genetic drift in the expected direction given their flowering time effects. However, clustering these non-neutral alleles based on their profiles of frequency change revealed transient shifts underpinning a transition in genotype-phenotype relationships across generations. This was distinguished by initial reductions in the frequencies of few relatively large positive effect alleles and subsequent enrichment of many rare negative effect alleles, some of which appear to represent allelic series. With these genomic shifts, the population reached an adapted state while retaining [Formula: see text] of the standing molecular marker variation in the founding population. Robust selection and association mapping tests highlighted several key genes driving the phenotypic response to selection. Our results reveal the evolutionary dynamics of a finite polygenic architecture conditioning a capacity for rapid environmental adaptation in maize., (Copyright © 2019 by the Genetics Society of America.)

Image analysis methods for measuring crop phenotypes may replace traditional measurements if they more efficiently and reliably capture similar or superior information. This study used a recreational-grade unmanned aerial vehicle carrying a spectrally-modified consumer-grade camera to collect images in which each pixel value is a vegetation index based on the normalized difference between the blue and near infrared wavelength bands (BNDVI). The subjects of the study were Zea mays hybrids with good yield potential grown in 4-row plots. Flights were conducted at least once per week during three successive growing seasons in south-central Wisconsin. Average BNDVI for each plot (genotype) rose steadily through June, peaked in July, and then declined as plants matured. BNDVI histograms changed shape over the season as the canopy concealed soil, became more uniformly green, then senesced. Principal Components Analysis (PCA) captured the change in histogram shape. PC1 represented canopy closure. PC2 represented the mean of the BNDVI distribution. PC3 represented the spread of the distribution. Correlation analysis showed that flowering time correlated with PC2 and PC3 best (r ≈ 0.5) a few days before the event (day in which 50% of the plants exhibited tassels). Three ears were picked from each plot to quantify kernel dimensions by image analysis before each plot was mechanically harvested to determine grain weight per plot. Correlations between this measurement of yield and PC2 were low in June but exceeded 0.4 within 10 days after flowering. Kernel length correlated similarly with PC2. The correlation between PC2 and kernel thickness displayed a similar but inverted time course. These results indicate that greater mid-season BNDVI values correlate positively with yield comprised of tall, thin kernels. Partial least squares regression performed on the BNDVI time courses predicted flowering time (r = 0.54-0.79) and yield (r = 0.4-0.69). This three-year experiment demonstrated that readily available hardware and software can create a phenotyping platform capable of predicting maize flowering time, yield, and kernel dimensions to a useful degree., (Copyright © 2019 Wu, Miller, de Leon, Kaeppler and Spalding.)

Premature senescence in annual crops reduces yield, while delayed senescence, termed stay-green, imposes positive and negative impacts on yield and nutrition quality. Despite its importance, scant information is available on the genetic architecture of senescence in maize ( Zea mays ) and other cereals. We combined a systematic characterization of natural diversity for senescence in maize and coexpression networks derived from transcriptome analysis of normally senescing and stay-green lines. Sixty-four candidate genes were identified by genome-wide association study (GWAS), and 14 of these genes are supported by additional evidence for involvement in senescence-related processes including proteolysis, sugar transport and signaling, and sink activity. Eight of the GWAS candidates, independently supported by a coexpression network underlying stay-green, include a trehalose-6-phosphate synthase, a NAC transcription factor, and two xylan biosynthetic enzymes. Source-sink communication and the activity of cell walls as a secondary sink emerge as key determinants of stay-green. Mutant analysis supports the role of a candidate encoding Cys protease in stay-green in Arabidopsis ( Arabidopsis thaliana ), and analysis of natural alleles suggests a similar role in maize. This study provides a foundation for enhanced understanding and manipulation of senescence for increasing carbon yield, nutritional quality, and stress tolerance of maize and other cereals., (© 2019 American Society of Plant Biologists. All rights reserved.)

Use of a single reference genome for genome-wide association studies (GWAS) limits the gene space represented to that of a single accession. This limitation can complicate identification and characterization of genes located within presence-absence variations (PAVs). In this study, we present the draft de novo genome assembly of 'PHJ89', an 'Oh43'-type inbred line of maize ( L.). From three separate reference genome assemblies ('B73', 'PH207', and PHJ89) that represent the predominant germplasm groups of maize, we generated three separate whole-seedling gene expression profiles and single nucleotide polymorphism (SNP) matrices from a panel of 942 diverse inbred lines. We identified 34,447 (B73), 39,672 (PH207), and 37,436 (PHJ89) transcripts that are not present in the respective reference genome assemblies. Genome-wide association studies were conducted in the 942 inbred panel with both the SNP and expression data values to map (SCMV) resistance. Highlighting the impact of alternative reference genomes in gene discovery, the GWAS results for SCMV resistance with expression values as a surrogate measure of PAV resulted in robust detection of the physical location of a known resistance gene when the B73 reference that contains the gene was used, but not the PH207 reference. This study provides the valuable resource of the Oh43-type PHJ89 genome assembly as well as SNP and expression data for 942 individuals generated from three different reference genomes., (© 2019 The Author(s).)

Deconvolution of the genetic architecture underlying yield is critical for understanding bases of genetic gain in species of agronomic importance. To dissect the genetic components of yield in potato, we adopted a reference-based recombination map composed of four segregating alleles from an interspecific pseudotestcross F 1 potato population ( n = 90). Approximately 1.5 million short nucleotide variants were utilized during map construction, resulting in unprecedented resolution for an F 1 population, estimated by a median bin length of 146 kb and 11 genes per bin. Regression models uncovered 14 quantitative trait loci (QTL) underpinning yield, average tuber weight, and tubers produced per plant in a population exhibiting a striking 332% average midparent-value heterosis. Nearly 80% of yield-associated QTL were epistatic, and contained between 0 and 44 annotated genes. We found that approximately one-half of epistatic QTL overlap regions of residual heterozygosity identified in the inbred parental parent (M6). Genomic regions recalcitrant to inbreeding were associated with an increased density of genes, many of which demonstrated signatures of selection and floral tissue specificity. Dissection of the genome-wide additive and dominance values for yield and yield components indicated a widespread prevalence of dominance contributions in this population, enriched at QTL and regions of residual heterozygosity. Finally, the effects of short nucleotide variants and patterns of gene expression were determined for all genes underlying yield-associated QTL, exposing several promising candidate genes for future investigation., (Copyright © 2019 by the Genetics Society of America.)

During periods in which glucose absorption from the gastrointestinal (GI) tract is insufficient to meet body requirements, hepatic gluconeogenesis plays a key role to maintain normal blood glucose levels. The current studies investigated the role in this process played by vasodilatory-associated phosphoprotein (VASP), a protein that is phosphorylated in hepatocytes by cAMP/protein kinase A (PKA), a key mediator of the action of glucagon. We report that following stimulation of hepatocytes with 8Br-cAMP, phosphorylation of VASP preceded induction of genes encoding key gluconeogenic enzymes, glucose-6-phosphatase (G6p) and phosphoenolpyruvate carboxykinase (Pck1), and that VASP overexpression enhanced this gene induction. Conversely, hepatocytes from mice lacking VASP (Vasp-/-) displayed blunted induction of gluconeogenic enzymes in response to cAMP, and Vasp-/- mice exhibited both greater fasting hypoglycemia and blunted hepatic gluconeogenic enzyme gene expression in response to fasting in vivo. These effects of VASP deficiency were associated with reduced phosphorylation of both CREB (a key transcription factor for gluconeogenesis that lies downstream of PKA) and histone deacetylase 4 (HDAC4), a combination of effects that inhibit transcription of gluconeogenic genes. These data support a model in which VASP functions as a molecular bridge linking the two key signal transduction pathways governing hepatic gluconeogenic gene expression., Competing Interests: The authors have declared that no competing interests exist.

Background: Maize stover is an important source of crop residues and a promising sustainable energy source in the United States. Stalk is the main component of stover, representing about half of stover dry weight. Characterization of genetic determinants of stalk traits provide a foundation to optimize maize stover as a biofuel feedstock. We investigated maize natural genetic variation in genome-wide association studies (GWAS) to detect candidate genes associated with traits related to stalk biomass (stalk diameter and plant height) and stalk anatomy (rind thickness, vascular bundle density and area)., Results: Using a panel of 942 diverse inbred lines, 899,784 RNA-Seq derived single nucleotide polymorphism (SNP) markers were identified. Stalk traits were measured on 800 members of the panel in replicated field trials across years. GWAS revealed 16 candidate genes associated with four stalk traits. Most of the detected candidate genes were involved in fundamental cellular functions, such as regulation of gene expression and cell cycle progression. Two of the regulatory genes (Zmm22 and an ortholog of Fpa) that were associated with plant height were previously shown to be involved in regulating the vegetative to floral transition. The association of Zmm22 with plant height was confirmed using a transgenic approach. Transgenic lines with increased expression of Zmm22 showed a significant decrease in plant height as well as tassel branch number, indicating a pleiotropic effect of Zmm22., Conclusion: Substantial heritable variation was observed in the association panel for stalk traits, indicating a large potential for improving useful stalk traits in breeding programs. Genome-wide association analyses detected several candidate genes associated with multiple traits, suggesting common regulatory elements underlie various stalk traits. Results of this study provide insights into the genetic control of maize stalk anatomy and biomass.

Increasing popularity of high-throughput phenotyping technologies, such as image-based phenotyping, offer novel ways for quantifying plant growth and morphology. These new methods can be more or less accurate and precise than traditional, manual measurements. Many large-scale phenotyping efforts are conducted to enable genome-wide association studies (GWAS), but it is unclear exactly how alternative methods of phenotyping will affect GWAS results. In this study we simulate phenotypes that are controlled by the same set of causal loci but have differing heritability, similar to two different measurements of the same morphological character. We then perform GWAS with the simulated traits and create receiver operating characteristic (ROC) curves from the results. The areas under the ROC curves (AUCs) provide a metric that allows direct comparisons of GWAS results from different simulated traits. We use this framework to evaluate the effects of heritability and the number of causative loci on the AUCs of simulated traits; we also test the differences between AUCs of traits with differing heritability. We find that both increasing the number of causative loci and decreasing the heritability reduce a trait's AUC. We also find that when two traits are controlled by a greater number of causative loci, they are more likely to have significantly different AUCs as the difference between their heritabilities increases. When simulation results are applied to measures of tassel morphology, we find no significant difference between AUCs from GWAS using manual and image-based measurements of typical maize tassel characters. This finding indicates that both measurement methods have similar ability to identify genetic associations. These results provide a framework for deciding between competing phenotyping strategies when the ultimate goal is to generate and use phenotype-genotype associations from GWAS., (Copyright © 2018 Gage et al.)

Inflorescence capacity plays a crucial role in reproductive fitness in plants, and in production of hybrid crops. Maize is a monoecious species bearing separate male and female flowers (tassel and ear, respectively). The switch from open-pollinated populations of maize to hybrid-based breeding schemes in the early 20th century was accompanied by a dramatic reduction in tassel size, and the trend has continued with modern breeding over the recent decades. The goal of this study was to identify selection signatures in genes that may underlie this dramatic transformation. Using a population of 942 diverse inbred maize accessions and a nested association mapping population comprising three 200-line biparental populations, we measured 15 tassel morphological characteristics by manual and image-based methods. Genome-wide association studies identified 242 single nucleotide polymorphisms significantly associated with measured traits. We compared 41 unselected lines from the Iowa Stiff Stalk Synthetic (BSSS) population to 21 highly selected lines developed by modern commercial breeding programs, and found that tassel size and weight were reduced significantly. We assayed genetic differences between the two groups using three selection statistics: cross population extended haplotype homozogysity, cross-population composite likelihood ratio, and fixation index. All three statistics show evidence of selection at genomic regions associated with tassel morphology relative to genome-wide null distributions. These results support the tremendous effect, both phenotypic and genotypic, that selection has had on maize male inflorescence morphology., (Copyright © 2018 J. L. Gage et al.)

Plants can produce different phenotypes when exposed to different environments. Understanding the genetic basis of these plastic responses is crucial for crop breeding efforts. We discuss two recent studies that suggest that yield plasticity in maize has been under selection but is controlled by different genes than yield.

Objectives: Crop improvement relies on analysis of phenotypic, genotypic, and environmental data. Given large, well-integrated, multi-year datasets, diverse queries can be made: Which lines perform best in hot, dry environments? Which alleles of specific genes are required for optimal performance in each environment? Such datasets also can be leveraged to predict cultivar performance, even in uncharacterized environments. The maize Genomes to Fields (G2F) Initiative is a multi-institutional organization of scientists working to generate and analyze such datasets from existing, publicly available inbred lines and hybrids. G2F's genotype by environment project has released 2014 and 2015 datasets to the public, with 2016 and 2017 collected and soon to be made available., Data Description: Datasets include DNA sequences; traditional phenotype descriptions, as well as detailed ear, cob, and kernel phenotypes quantified by image analysis; weather station measurements; and soil characterizations by site. Data are released as comma separated value spreadsheets accompanied by extensive README text descriptions. For genotypic and phenotypic data, both raw data and a version with outliers removed are reported. For weather data, two versions are reported: a full dataset calibrated against nearby National Weather Service sites and a second calibrated set with outliers and apparent artifacts removed.

The environment can influence heterosis, the phenomena in which the offspring of two inbred parents exhibits phenotypic performance beyond the inbred parents for specific traits. In this study we measured 25 traits in a set of 47 maize hybrids and their inbred parents grown in 16 different environments with varying levels of average productivity. By quantifying 25 vegetative and reproductive traits across the life cycle we were able to analyze interactions between the environment and multiple distinct instances of heterosis. The magnitude and rank among hybrids for better-parent heterosis (BPH) varied for the different traits and environments. Across the traits, a higher within plot variance was observed for inbred lines compared to hybrids. However, for most traits, variance across environments was not significantly different for inbred lines compared to hybrids. Further, for many traits the correlations of BPH to hybrid performance and BPH to better parent performance were of comparable magnitude. These results indicate that inbred lines and hybrids show similar trends in environmental response and both are contributing to observed genotype-by-environment interactions for heterosis. This study highlights the degree of heterosis is not an inherent trait of a specific hybrid, but varies depending on the trait measured and the environment where that trait is measured. Studies that attempt to correlate molecular processes with heterosis are hindered by the fact that heterosis is not a consistent attribute of a specific hybrid.

Remarkable productivity has been achieved in crop species through artificial selection and adaptation to modern agronomic practices. Whether intensive selection has changed the ability of improved cultivars to maintain high productivity across variable environments is unknown. Understanding the genetic control of phenotypic plasticity and genotype by environment (G × E) interaction will enhance crop performance predictions across diverse environments. Here we use data generated from the Genomes to Fields (G2F) Maize G × E project to assess the effect of selection on G × E variation and characterize polymorphisms associated with plasticity. Genomic regions putatively selected during modern temperate maize breeding explain less variability for yield G × E than unselected regions, indicating that improvement by breeding may have reduced G × E of modern temperate cultivars. Trends in genomic position of variants associated with stability reveal fewer genic associations and enrichment of variants 0-5000 base pairs upstream of genes, hypothetically due to control of plasticity by short-range regulatory elements.

Key Message: Capitalizing upon the genomic characteristics of long-term random mating populations, sampling from pre-selected landraces is a promising approach for broadening the genetic base of elite germplasm for quantitative traits. Genome-enabled strategies for harnessing untapped allelic variation of landraces are currently evolving. The success of such approaches depends on the choice of source material. Thus, the analysis of different strategies for sampling allelic variation from landraces and their impact on population diversity and linkage disequilibrium (LD) is required to ensure the efficient utilization of diversity. We investigated the impact of different sampling strategies on diversity parameters and LD based on high-density genotypic data of 35 European maize landraces each represented by more than 20 individuals. On average, five landraces already captured ~95% of the molecular diversity of the entire dataset. Within landraces, absence of pronounced population structure, consistency of linkage phases and moderate to low LD levels were found. When combining data of up to 10 landraces, LD decay distances decreased to a few kilobases. Genotyping 24 individuals per landrace with 5k SNPs was sufficient for obtaining representative estimates of diversity and LD levels to allow an informed pre-selection of landraces. Integrating results from European with Central and South American landraces revealed that European landraces represent a unique and diverse spectrum of allelic variation. Sampling strategies for harnessing allelic variation from landraces depend on the study objectives. If the focus lies on the improvement of elite germplasm for quantitative traits, we recommend sampling from pre-selected landraces, as it yields a wide range of diversity, allows optimal marker imputation, control for population structure and avoids the confounding effects of strong adaptive alleles.

Background/objective: Direct-acting oral anticoagulants (DOACs) are increasingly used to prevent or treat thromboembolism. We conducted a study to compare how well initial DOAC prescribing for adult inpatients adhered to dosing recommendations approved by the US Food and Drug Administration (FDA)., Design: Retrospective analysis., Setting: Single academic medical center, July 1, 2014 to June 30, 2015., Patients: 508 adult inpatients., Measurements: DOAC prescriptions were evaluated to determine whether they met FDA-recommended dosing and administration according to patient age, weight, sex, race, kidney function, diagnoses, and concomitant medications., Results: DOACs were prescribed in 635 admissions (247 apixaban, 97 dabigatran, 291 rivaroxaban). The indication was atrial fibrillation/flutter in 465 admissions (8% with bioprostheses or valve repair), chronic deep vein thrombosis (DVT) in 67, acute DVT in 32, chronic pulmonary embolism in 23, acute pulmonary embolism in 19, DVT prevention after hip or knee surgery in 19, and non-FDA-approved indications in 10. Sixteen percent of orders for venous thromboembolic disease were for patients with active malignancy. Dosages not concordant with recommendations were prescribed for apixaban in 18% of admissions, for rivaroxaban in 14%, and for dabigatran in 7% (𝑃 = 0.04). Lower than recommended dosing was more common than higher than recommended dosing (𝑃 < 0.05). Half the deviations were continuations of outpatient dosing. Atrial fibrillation/flutter and post-hip or -knee surgery dosing deviations were more common than venous thromboembolic disease deviations (𝑃 < 0.001) but were not related to prescriber specialty., Conclusions: DOAC prescribing recommendation deviations that can affect clinical efficacy were identified. Education and point-of-care decision support tools for improving dosing are needed, as are outcome data for patients who receive DOACs at lower than recommended dosing or for off-label indications., (© 2017 Society of Hospital Medicine)

Background: The cell wall polymer lignin provides structural support and rigidity to plant cell walls, and therefore to the plant body. However, the recalcitrance associated with lignin impedes the extraction of polysaccharides from the cell wall to make plant-based biofuels and biomaterials. The cell wall digestibility can be improved by introducing labile ester bonds into the lignin backbone that can be easily broken under mild base treatment at room temperature. The FERULOYL-CoA MONOLIGNOL TRANSFERASE (FMT) enzyme, which may be naturally found in many plants, uses feruloyl-CoA and monolignols to synthesize the ester-linked monolignol ferulate conjugates. A mutation in the first lignin-specific biosynthetic enzyme, CINNAMOYL-CoA REDUCTASE (CCR), results in an increase in the intracellular pool of feruloyl-CoA., Results: Maize ( Zea mays ) has a native putative FMT enzyme, and its ccr mutants produce an increased pool of feruloyl-CoA that can be used for conversion to monolignol ferulate conjugates. The decreased lignin content and monomers did not, however, impact the plant growth or biomass. The increase in monolignol conjugates correlated with an improvement in the digestibility of maize stem rind tissue., Conclusions: Together, increased monolignol ferulates and improved digestibility in ccr1 mutant plants suggests that they may be superior biofuel crops.

Background: The maize male inflorescence (tassel) produces pollen necessary for reproduction and commercial grain production of maize. The size of the tassel has been linked to factors affecting grain yield, so understanding the genetic control of tassel architecture is an important goal. Tassels are fragile and deform easily after removal from the plant, necessitating rapid measurement of any shape characteristics that cannot be retained during storage. Some morphological characteristics of tassels such as curvature and compactness are difficult to quantify using traditional methods, but can be quantified by image-based phenotyping tools. These constraints necessitate the development of an efficient method for capturing natural-state tassel morphology and complementary automated analytical methods that can quickly and reproducibly quantify traits of interest such as height, spread, and branch number., Results: This paper presents the Tassel Image-based Phenotyping System (TIPS), which provides a platform for imaging tassels in the field immediately following removal from the plant. TIPS consists of custom methods that can quantify morphological traits from profile images of freshly harvested tassels acquired with a standard digital camera in a field-deployable light shelter. Correlations between manually measured traits (tassel weight, tassel length, spike length, and branch number) and image-based measurements ranged from 0.66 to 0.89. Additional tassel characteristics quantified by image analysis included some that cannot be quantified manually, such as curvature, compactness, fractal dimension, skeleton length, and perimeter. TIPS was used to measure tassel phenotypes of 3530 individual tassels from 749 diverse inbred lines that represent the diversity of tassel morphology found in modern breeding and academic research programs. Repeatability ranged from 0.85 to 0.92 for manually measured phenotypes, from 0.77 to 0.83 for the same traits measured by image-based methods, and from 0.49 to 0.81 for traits that can only be measured by image analysis., Conclusions: TIPS allows morphological features of maize tassels to be quantified automatically, with minimal disturbance, at a scale that supports population-level studies. TIPS is expected to accelerate the discovery of associations between genetic loci and tassel morphology characteristics, and can be applied to maize breeding programs to increase productivity with lower resource commitment.

Grain yield of the maize plant depends on the sizes, shapes, and numbers of ears and the kernels they bear. An automated pipeline that can measure these components of yield from easily-obtained digital images is needed to advance our understanding of this globally important crop. Here we present three custom algorithms designed to compute such yield components automatically from digital images acquired by a low-cost platform. One algorithm determines the average space each kernel occupies along the cob axis using a sliding-window Fourier transform analysis of image intensity features. A second counts individual kernels removed from ears, including those in clusters. A third measures each kernel's major and minor axis after a Bayesian analysis of contour points identifies the kernel tip. Dimensionless ear and kernel shape traits that may interrelate yield components are measured by principal components analysis of contour point sets. Increased objectivity and speed compared to typical manual methods are achieved without loss of accuracy as evidenced by high correlations with ground truth measurements and simulated data. Millimeter-scale differences among ear, cob, and kernel traits that ranged more than 2.5-fold across a diverse group of inbred maize lines were resolved. This system for measuring maize ear, cob, and kernel attributes is being used by multiple research groups as an automated Web service running on community high-throughput computing and distributed data storage infrastructure. Users may create their own workflow using the source code that is staged for download on a public repository., (© 2016 The Authors. The Plant Journal published by Society for Experimental Biology and John Wiley & Sons Ltd.)

Intense artificial selection over the last 100 years has produced elite maize (Zea mays) inbred lines that combine to produce high-yielding hybrids. To further our understanding of how genome and transcriptome variation contribute to the production of high-yielding hybrids, we generated a draft genome assembly of the inbred line PH207 to complement and compare with the existing B73 reference sequence. B73 is a founder of the Stiff Stalk germplasm pool, while PH207 is a founder of Iodent germplasm, both of which have contributed substantially to the production of temperate commercial maize and are combined to make heterotic hybrids. Comparison of these two assemblies revealed over 2500 genes present in only one of the two genotypes and 136 gene families that have undergone extensive expansion or contraction. Transcriptome profiling revealed extensive expression variation, with as many as 10,564 differentially expressed transcripts and 7128 transcripts expressed in only one of the two genotypes in a single tissue. Genotype-specific genes were more likely to have tissue/condition-specific expression and lower transcript abundance. The availability of a high-quality genome assembly for the elite maize inbred PH207 expands our knowledge of the breadth of natural genome and transcriptome variation in elite maize inbred lines across heterotic pools., (© 2016 American Society of Plant Biologists. All rights reserved.)

HfN specimens deformed via four-point bend tests at room temperature and at 2300 °C (~0.7 T m ) showed increased plasticity response with temperature. Dynamic diffraction via transmission electron microscopy (TEM) revealed ⟨110⟩{111} as the primary slip system in both temperature regimes and ⟨110⟩{110} to be a secondary slip system activated at elevated temperature. Dislocation line lengths changed from a primarily linear to a curved morphology with increasing temperature suggestive of increased dislocation mobility being responsible for the brittle to ductile temperature transition. First principle generalized stacking fault energy calculations revealed an intrinsic stacking fault (ISF) along ⟨112⟩{111}, which is the partial dislocation direction for slip on these close packed planes. Though B1 structures, such as NaCl and HfC predominately slip on ⟨110⟩{110}, the ISF here is believed to facilitate slip on the {111} planes for this B1 HfN phase.

Carbohydrates stored in vegetative organs, particularly stems, of grasses are a very important source of energy. We examined carbohydrate accumulation in adult sorghum and maize hybrids with distinct phenology and different end uses (grain, silage, sucrose or sweetness in stalk juice, and biomass). Remarkable variation was observed for non-structural carbohydrates and structural polysaccharides during three key developmental stages both between and within hybrids developed for distinct end use in both species. At the onset of the reproductive phase (average 65 days after planting, DAP), a wide range for accumulation of non-structural carbohydrates (free glucose and sucrose combined), was observed in internodes of maize (11-24%) and sorghum (7-36%) indicating substantial variation for transient storage of excess photosynthate during periods of low grain or vegetative sink strength. Remobilization of these reserves for supporting grain fill or vegetative growth was evident from lower amounts in maize (8-19%) and sorghum (9-27%) near the end of the reproductive period (average 95 DAP). At physiological maturity of grain hybrids (average 120 DAP), amounts of these carbohydrates were generally unchanged in maize (9-21%) and sorghum (16-27%) suggesting a loss of photosynthetic assimilation due to weakening sink demand. Nonetheless, high amounts of non-structural carbohydrates at maturity even in grain maize and sorghum (15-18%) highlight the potential for developing dual-purpose (grain/stover) crops. For both species, the amounts of structural polysaccharides in the cell wall, measured as monomeric components (glucose and pentose), decreased during grain fill but remained unchanged thereafter with maize biomass possessing slightly higher amounts than sorghum. Availability of carbohydrates in maize and sorghum highlights the potential for developing energy-rich dedicated biofuel or dual-purpose (grain/stover) crops.

Seed size is an important component of grain yield and a key determinant trait for crop domestication. The Krug Yellow Dent long-term selection experiment for large and small seed provides a valuable resource to dissect genetic and phenotypic changes affecting seed size within a common genetic background. In this study, inbred lines derived from Krug Large Seed (KLS) and Krug Small Seed (KSS) populations and reciprocal F1 crosses were used to investigate developmental and molecular mechanisms governing seed size. Seed morphological characteristics showed striking differences between KLS and KSS inbred lines, and the reciprocal cross experiment revealed a strong maternal influence on both seed weight and seed size. Quantification of endosperm area, starchy endosperm cell size, and kernel dry mass accumulation indicated a positive correlation between seed size, endosperm cell number, and grain filling rate, and patterns of grain filling in reciprocal crosses mirrored that of the maternal parent. Consistent with the maternal contribution to seed weight, transcriptome profiling of reciprocal F1 hybrids showed substantial similarities to the maternal parent. A set of differentially expressed genes between KLS and KSS inbreds were found, which fell into a broad number of functional categories including DNA methylation, nucleosome assembly, and heat stress response. In addition, gene co-expression network analysis of parental inbreds and reciprocal F1 hybrids identified co-expression modules enriched in ovule development and DNA methylation, implicating these two processes in seed size determination. These results expand our understanding of seed size regulation and help to uncover the developmental and molecular basis underlying maternal control of seed size in maize., (© The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology.)

Comprehensive and systematic transcriptome profiling provides valuable insight into biological and developmental processes that occur throughout the life cycle of a plant. We have enhanced our previously published microarray-based gene atlas of maize ( L.) inbred B73 to now include 79 distinct replicated samples that have been interrogated using RNA sequencing (RNA-seq). The current version of the atlas includes 50 original array-based gene atlas samples, a time-course of 12 stalk and leaf samples postflowering, and an additional set of 17 samples from the maize seedling and adult root system. The entire dataset contains 4.6 billion mapped reads, with an average of 20.5 million mapped reads per biological replicate, allowing for detection of genes with lower transcript abundance. As the new root samples represent key additions to the previously examined tissues, we highlight insights into the root transcriptome, which is represented by 28,894 (73.2%) annotated genes in maize. Additionally, we observed remarkable expression differences across both the longitudinal (four zones) and radial gradients (cortical parenchyma and stele) of the primary root supported by fourfold differential expression of 9353 and 4728 genes, respectively. Among the latter were 1110 genes that encode transcription factors, some of which are orthologs of previously characterized transcription factors known to regulate root development in (L.) Heynh., while most are novel, and represent attractive targets for reverse genetics approaches to determine their roles in this important organ. This comprehensive transcriptome dataset is a powerful tool toward understanding maize development, physiology, and phenotypic diversity., (Copyright © 2016 Crop Science Society of America.)

Nuclear magnetic resonance spectroscopy is a powerful tool for the structural analysis of organic compounds and biomolecules but typically requires macroscopic sample quantities. We use a sensor, which consists of two quantum bits corresponding to an electronic spin and an ancillary nuclear spin, to demonstrate room temperature magnetic resonance detection and spectroscopy of multiple nuclear species within individual ubiquitin proteins attached to the diamond surface. Using quantum logic to improve readout fidelity and a surface-treatment technique to extend the spin coherence time of shallow nitrogen-vacancy centers, we demonstrate magnetic field sensitivity sufficient to detect individual proton spins within 1 second of integration. This gain in sensitivity enables high-confidence detection of individual proteins and allows us to observe spectral features that reveal information about their chemical composition., (Copyright © 2016, American Association for the Advancement of Science.)

Fast pyrolysis has been identified as one of the biorenewable conversion platforms that could be a part of an alternative energy future, but it has not yet received the same attention as cellulosic ethanol in the analysis of genetic inheritance within potential feedstocks such as maize. Ten bio-oil compounds were measured via pyrolysis/gas chromatography-mass spectrometry (Py/GC-MS) in maize cobs. 184 recombinant inbred lines (RILs) of the intermated B73 x Mo17 (IBM) Syn4 population were analyzed in two environments, using 1339 markers, for quantitative trait locus (QTL) mapping. QTL mapping was performed using composite interval mapping with significance thresholds established by 1000 permutations at α = 0.05. 50 QTL were found in total across those ten traits with R2 values ranging from 1.7 to 5.8%, indicating a complex quantitative inheritance of these traits.

A maize (Zea mays L. subsp. mays) diversity panel consisting of 26 maize lines exhibiting a wide range of cell-wall properties and responses to hydrolysis by cellulolytic enzymes was employed to investigate the relationship between cell-wall properties, cell-wall responses to mild NaOH pre-treatment, and enzymatic hydrolysis yields. Enzymatic hydrolysis of the cellulose in the untreated maize was found to be positively correlated with the water retention value, which is a measure of cell-wall susceptibility to swelling. It was also positively correlated with the lignin syringyl/guaiacyl ratio and negatively correlated with the initial cell-wall lignin, xylan, acetate, and p-coumaric acid (pCA) content, as well as pCA released from the cell wall by pre-treatment. The hydrolysis yield following pre-treatment exhibited statistically significant negative correlations to the lignin content after pre-treatment and positive correlations to the solubilized ferulic acid and pCA. Several unanticipated results were observed, including a positive correlation between initial lignin and acetate content, lack of correlation between acetate content and initial xylan content, and negative correlation between each of these three variables to the hydrolysis yields for untreated maize. Another surprising result was that pCA release was negatively correlated with hydrolysis yields for untreated maize and, along with ferulic acid release, was positively correlated with the pre-treated maize hydrolysis yields. This indicates that these properties that may negatively contribute to the recalcitrance in untreated cell walls may positively contribute to their deconstruction by alkaline pre-treatment., (© The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology.)

Delayed transition from the vegetative stage to the reproductive stage of development and increased plant height have been shown to increase biomass productivity in grasses. The goal of this project was to detect quantitative trait loci using extremes from a large synthetic population, as well as a related recombinant inbred line mapping population for these two traits. Ten thousand individuals from a B73 × Mo17 noninbred population intermated for 14 generations (IBM Syn14) were grown at a density of approximately 16,500 plants ha(-1). Flowering time and plant height were measured within this population. DNA was pooled from the 46 most extreme individuals from each distributional tail for each of the traits measured and used in bulk segregant analysis (BSA) sequencing. Allelic divergence at each of the ∼1.1 million SNP loci was estimated as the difference in allele frequencies between the selected extremes. Additionally, 224 intermated B73 × Mo17 recombinant inbred lines were concomitantly grown at a similar density adjacent to the large synthetic population and were assessed for flowering time and plant height. Using the BSA sequencing method, 14 and 13 genomic regions were identified for flowering time and plant height, respectively. Linkage mapping with the RIL population identified eight and three regions for flowering time and plant height, respectively. Of the regions identified, three colocalized between the two populations for flowering time and two colocalized for plant height. This study demonstrates the utility of using BSA sequencing for the dissection of complex quantitative traits important for production of lignocellulosic ethanol., (Copyright © 2015 Haase et al.)

Differences in plasticity are usually attributed to significant changes in crystalline symmetry or the strength of the interatomic bonds. In the B1 monocarbides, differences in slip planes exist at low temperatures despite having the same structure and very similar bonding characteristics. Our experimental results demonstrate concretely that HfC slips on {110} planes while TaC slips on {111} planes. Density functional theory calculations rationalize this difference through the formation of an intrinsic stacking fault on the {111} planes, formation of Shockley partials, and enhanced metallic bonding because of the valence filling of electrons between these transitional metal carbides.

Background: High-density genomic data is often analyzed by combining information over windows of adjacent markers. Interpretation of data grouped in windows versus at individual locations may increase statistical power, simplify computation, reduce sampling noise, and reduce the total number of tests performed. However, use of adjacent marker information can result in over- or under-smoothing, undesirable window boundary specifications, or highly correlated test statistics. We introduce a method for defining windows based on statistically guided breakpoints in the data, as a foundation for the analysis of multiple adjacent data points. This method involves first fitting a cubic smoothing spline to the data and then identifying the inflection points of the fitted spline, which serve as the boundaries of adjacent windows. This technique does not require prior knowledge of linkage disequilibrium, and therefore can be applied to data collected from individual or pooled sequencing experiments. Moreover, in contrast to existing methods, an arbitrary choice of window size is not necessary, since these are determined empirically and allowed to vary along the genome., Results: Simulations applying this method were performed to identify selection signatures from pooled sequencing FST data, for which allele frequencies were estimated from a pool of individuals. The relative ratio of true to false positives was twice that generated by existing techniques. A comparison of the approach to a previous study that involved pooled sequencing FST data from maize suggested that outlying windows were more clearly separated from their neighbors than when using a standard sliding window approach., Conclusions: We have developed a novel technique to identify window boundaries for subsequent analysis protocols. When applied to selection studies based on F ST data, this method provides a high discovery rate and minimizes false positives. The method is implemented in the R package GenWin, which is publicly available from CRAN.