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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

maslov-group/FUN-PROSE

mRNA levels of all genes in a genome is a critical piece of information defining the overall state of the cell in a given environmental condition. Being able to reconstruct such condition-specific expression in fungal genomes is particularly important to metabolically engineer these organisms to produce desired chemicals in industrially scalable conditions. Most previous deep learning approaches focused on predicting the average expression levels of a gene based on its promoter sequence, ignoring its variation across different conditions. Here we present FUN-PROSE—a deep learning model trained to predict differential expression of individual genes across various conditions using their promoter sequences and expression levels of all transcription factors. We train and test our model on three fungal species and get the correlation between predicted and observed condition-specific gene expression as high as 0.85. We then interpret our model to extract promoter sequence motifs responsible for variable expression of individual genes. We also carried out input feature importance analysis to connect individual transcription factors to their gene targets. A sizeable fraction of both sequence motifs and TF-gene interactions learned by our model agree with previously known biological information, while the rest corresponds to either novel biological facts or indirect correlations.

Liu, Simon↗
DOE OSTI2015

Rapid response sensor for analyzing Special Nuclear Material

Rapid in-situ analytical techniques are attractive for characterizing Special Nuclear Material (SNM). Present techniques are time consuming, and require sample dissolution. Proof-of-principal studies are performed to demonstrate the utility of employing low energy neutrons from a portable pulsed neutron generator for non-destructive isotopic analysis of nuclear material. In particular, time-sequenced data acquisition, operating synchronously with the pulsing of a neutron generator, partitions the characteristic elemental prompt gamma-rays according to the type of the reaction; inelastic neutron scattering reactions during the ON state and thermal neutron capture reactions during the OFF state of the generator. Thus, the key challenge is isolating these signature gamma- rays from the prompt fission and β-delayed gamma-rays that are also produced during the neutron interrogation. A commercial digital multi-channel analyzer has been specially customized to enable time-resolved gamma-ray spectral data to be acquired in multiple user-defined time bins within each of the ON/OFF gate periods of the neutron generator. Preliminary results on new signatures from depleted uranium as well as modeling and benchmarking of the concept are presented, however this approach should should be applicable for virtually all forms of SNM.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Alignment of Short Reads: A Crucial Step for Application of Next-Generation Sequencing Data in Precision Medicine

Precision medicine or personalized medicine has been proposed as a modernized and promising medical strategy. Genetic variants of patients are the key information for implementation of precision medicine. Next-generation sequencing (NGS) is an emerging technology for deciphering genetic variants. Alignment of raw reads to a reference genome is one of the key steps in NGS data analysis. Many algorithms have been developed for alignment of short read sequences since 2008. Users have to make a decision on which alignment algorithm to use in their studies. Selection of the right alignment algorithm determines not only the alignment algorithm but also the set of suitable parameters to be used by the algorithm. Understanding these algorithms helps in selecting the appropriate alignment algorithm for different applications in precision medicine. Here, we review current available algorithms and their major strategies such as seed-and-extend and q-gram filter. We also discuss the challenges in current alignment algorithms, including alignment in multiple repeated regions, long reads alignment and alignment facilitated with known genetic variants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Environmental contaminants and microRNA regulation: Transcription factors as regulators of toxicant-altered microRNA expression

MicroRNAs (miRNAs) regulate gene expression by binding mRNA and inhibiting translation and/or inducing degradation of the associated transcripts. Expression levels of miRNAs have been shown to be altered in response to environmental toxicants, thus impacting cellular function and influencing disease risk. Transcription factors (TFs) are known to be altered in response to environmental toxicants and play a critical role in the regulation of miRNA expression. To date, environmentally-responsive TFs that are important for regulating miRNAs remain understudied. In a state-of-the-art analysis, we utilized an in silico bioinformatic approach to characterize potential transcriptional regulators of environmentally-responsive miRNAs. Using the miRStart database, genomic sequences of promoter regions for all available human miRNAs (n = 847) were identified and promoter regions were defined as − 1000/+500 base pairs from the transcription start site. Subsequently, the promoter region sequences of environmentally-responsive miRNAs (n = 128) were analyzed using enrichment analysis to determine overrepresented TF binding sites (TFBS). While most (56/73) TFs differed across environmental contaminants, a set of 17 TFs was enriched for promoter binding among miRNAs responsive to numerous environmental contaminants. Of these, one TF was common to miRNAs altered by the majority of environmental contaminants, namely SWI/SNF-related, matrix-associated, actin-dependent regulator of chromatin, subfamily A, member 3 (SMARCA3). These identified TFs represent candidate common transcriptional regulators of miRNAs perturbed by environmental toxicants. - Highlights: • Transcription factors that regulate environmentally-modulated miRNA expression are understudied • Transcription factor binding sites (TFBS) located within DNA promoter regions of miRNAs were identified. • Specific transcription factors may serve as master regulators of environmentally-mediated microRNA expression.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Diffusion tensor imaging of the kidney in healthy controls and in children and young adults with autosomal recessive polycystic kidney disease

Objective: To compare diffusion tensor imaging (DTI) of the kidneys and its derived parameters in children with autosomal recessive polycystic kidney disease (ARPKD) versus healthy controls. Methods: In a prospective IRB-approved study, we evaluated the use of DTI to compare kidney parenchyma FA values in healthy controls (age-matched children with no history of renal disease) versus patients with ARPKD. A 20-direction DTI with b-values of b = 0 s/mm{sup 2} and b = 400 s/mm{sup 2} was used to acquire data in coronal direction using a fat-suppressed spin-echo echo-planar sequence. Diffusion Toolkit and TrackVis were used for analysis and segmentation. TrackVis was used to draw regions of interest (ROIs) covering the entire volume of the renal parenchyma, excluding the collecting system. Fibers were reconstructed using a deterministic fiber tracking algorithm. The FA values based on the ROI data, mean length, and volume of the tracks based on the fiber tracking data were recorded. Results: Eight healthy controls (mean age = 12.9 years ± 4.0; 1/8 males) and six ARPKD participants (mean age = 13.8 years ± 8.5; 5/6 males) were included in the study. Compared to healthy controls, patients with ARPKD had significantly lower FA values (0.33 ± 0.03 vs. 0.25 ± 0.02, p = 0.002) and mean track length (16.73 ± 3.43 vs. 11.61 ± 1.29 mm, p = 0.005). Conclusion: DTI of the kidneys shows significantly lower FA values and mean track length in children and young adults with ARPKD compared to normal subjects. DTI of the kidney offers a novel approach for characterizing renal disease based on changes in diffusion anisotropy and kidney structure.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Rational development of transformation in Clostridium thermocellum ATCC 27405 via complete methylome analysis and evasion of native restriction–modification systems

A major barrier to both metabolic engineering and fundamental biological studies is the lack of genetic tools in most microorganisms. One example is Clostridium thermocellum ATCC 27405 T , where genetic tools are not available to help validate decades of hypotheses. A crucial barrier to DNA transformation is restriction–modification systems, which defend against foreign DNA methylated differently than the host. To determine the active restriction–modification systems in this strain, we performed complete methylome analysis via single-molecule, real-time sequencing to detect 6-methyladenine and 4-methylcytosine and the rarely used whole-genome bisulfite sequencing to detect 5-methylcytosine. Multiple active systems were identified, and corresponding DNA methyltransferases were expressed from the Escherichia coli chromosome to mimic the C. thermocellum methylome. Plasmid methylation was experimentally validated and successfully electroporated into C. thermocellum ATCC 27405. This combined method enabled genetic modification of the C. thermocellum -type strain and acts as a blueprint for transformation of other non-model microorganisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Effect of NaOH Concentration and Adding Sequences on Structural and Magnetic Properties of Ni{sub 0.4}Co{sub 0.6}Fe{sub 2}O{sub 4} Nanopowders Prepared Via Co-precipitation Route

Ni{sub 0.4}Co{sub 0.6}Fe{sub 2}O{sub 4} nanopowders were prepared via the co-precipitation route followed by annealing treatment. The structural and magnetic properties of the as-synthesized samples were determined by XRD, FT-IR, TG-DSC, and PPMS measurements, respectively. The XRD patterns indicated a single-phase cubic spinel structure for all the Ni-Co ferrite samples, regardless of adding sequences of the reactants or NaOH concentration. The analysis of the XRD patterns revealed that the enhancement in lattice constant with increasing NaOH concentration is related to the prevention of oxidization of Co{sup 2+} ions in the Ni-Co ferrite lattice. The FT-IR spectra indicated that samples prepared in the B process have fewer impurities than those prepared in the A process. The enhancement in saturation magnetization with the increase in sodium hydroxide concentration could be attributed to the strengthening of super-exchange interaction between A and B sublattices, due to replacements of Co{sup 3+} ions (magnetic moment of 0 μ{sub B}) by Co{sup 2+} ions (magnetic moment of 3 μ{sub B}) at B sublattices. The obvious increase in the coercivity field with the increase in concentration of NaOH solutions can be interpreted in terms of enhancement of magneto-crystalline anisotropy that originated from gradual substitutions of Co{sup 3+} ions with Co{sup 2+} ions at the octahedral sites.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

A clinically and genomically annotated nerve sheath tumor biospecimen repository

Nerve sheath tumors occur as a heterogeneous group of neoplasms in patients with neurofibromatosis type 1 (NF1). The malignant form represents the most common cause of death in people with NF1, and even when benign, these tumors can result in significant disfigurement, neurologic dysfunction, and a range of profound symptoms. Lack of human tissue across the peripheral nerve tumors common in NF1 has been a major limitation in the development of new therapies. To address this unmet need, we have created an annotated collection of patient tumor samples, patient-derived cell lines, and patient-derived xenografts, and carried out high-throughput genomic and transcriptomic characterization to serve as a resource for further biologic and preclinical therapeutic studies. In this work, we release genomic and transcriptomic datasets comprised of 55 tumor samples derived from 23 individuals, complete with clinical annotation. All data are publicly available through the NF Data Portal and at http://synapse.org/jhubiobank.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Viral afterlife: SARS-CoV-2 as a reservoir of immunomimetic peptides that reassemble into proinflammatory supramolecular complexes

It is unclear how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection leads to the strong but ineffective inflammatory response that characterizes severe Coronavirus disease 2019 (COVID-19), with amplified immune activation in diverse cell types, including cells without angiotensin-converting enzyme 2 receptors necessary for infection. Proteolytic degradation of SARS-CoV-2 virions is a milestone in host viral clearance, but the impact of remnant viral peptide fragments from high viral loads is not known. Here, we examine the inflammatory capacity of fragmented viral components from the perspective of supramolecular self-organization in the infected host environment. Interestingly, a machine learning analysis to SARS-CoV-2 proteome reveals sequence motifs that mimic host antimicrobial peptides (xenoAMPs), especially highly cationic human cathelicidin LL-37 capable of augmenting inflammation. Such xenoAMPs are strongly enriched in SARS-CoV-2 relative to low-pathogenicity coronaviruses. Moreover, xenoAMPs from SARS-CoV-2 but not low-pathogenicity homologs assemble double-stranded RNA (dsRNA) into nanocrystalline complexes with lattice constants commensurate with the steric size of Toll-like receptor (TLR)-3 and therefore capable of multivalent binding. Such complexes amplify cytokine secretion in diverse uninfected cell types in culture (epithelial cells, endothelial cells, keratinocytes, monocytes, and macrophages), similar to cathelicidin’s role in rheumatoid arthritis and lupus. The induced transcriptome matches well with the global gene expression pattern in COVID-19, despite using <0.3% of the viral proteome. Delivery of these complexes to uninfected mice boosts plasma interleukin-6 and CXCL1 levels as observed in COVID-19 patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Pseudomonas aeruginosa : One Health approach to deciphering hidden relationships in Northern Portugal

Abstract Aims Antimicrobial resistance in Pseudomonas aeruginosa represents a major global challenge in public and veterinary health, particularly from a One Health perspective. This study aimed to investigate antimicrobial resistance, the presence of virulence genes, and the genetic diversity of P. aeruginosa isolates from diverse sources. Methods and results The study utilized antimicrobial susceptibility testing, genomic analysis for resistance and virulence genes, and multilocus sequence typing to characterize a total of 737 P. aeruginosa isolates that were collected from humans, domestic animals, and aquatic environments in Northern Portugal. Antimicrobial resistance profiles were analyzed, and genomic approaches were employed to detect resistance and virulence genes. The study found a high prevalence of multidrug-resistant isolates, including high-risk clones such as ST244 and ST446, particularly in hospital sources and wastewater treatment plants. Key genes associated with resistance and virulence, including efflux pumps (e.g. MexA and MexB) and secretion systems (T3SS and T6SS), were identified. Conclusions This work highlights the intricate dynamics of multidrug-resistant P. aeruginosa across interconnected ecosystems in Northern Portugal. It underscores the importance of genomic studies in revealing the mechanisms of resistance and virulence, contributing to the broader understanding of resistance dynamics and informing future mitigation strategies.

de Sousa, Telma↗
DOE OSTI2020

Genomic Analysis Enlightens Agaricales Lifestyle Evolution and Increasing Peroxidase Diversity

Abstract As actors of global carbon cycle, Agaricomycetes (Basidiomycota) have developed complex enzymatic machineries that allow them to decompose all plant polymers, including lignin. Among them, saprotrophic Agaricales are characterized by an unparalleled diversity of habitats and lifestyles. Comparative analysis of 52 Agaricomycetes genomes (14 of them sequenced de novo) reveals that Agaricales possess a large diversity of hydrolytic and oxidative enzymes for lignocellulose decay. Based on the gene families with the predicted highest evolutionary rates—namely cellulose-binding CBM1, glycoside hydrolase GH43, lytic polysaccharide monooxygenase AA9, class-II peroxidases, glucose–methanol–choline oxidase/dehydrogenases, laccases, and unspecific peroxygenases—we reconstructed the lifestyles of the ancestors that led to the extant lignocellulose-decomposing Agaricomycetes. The changes in the enzymatic toolkit of ancestral Agaricales are correlated with the evolution of their ability to grow not only on wood but also on leaf litter and decayed wood, with grass-litter decomposers as the most recent eco-physiological group. In this context, the above families were analyzed in detail in connection with lifestyle diversity. Peroxidases appear as a central component of the enzymatic toolkit of saprotrophic Agaricomycetes, consistent with their essential role in lignin degradation and high evolutionary rates. This includes not only expansions/losses in peroxidase genes common to other basidiomycetes but also the widespread presence in Agaricales (and Russulales) of new peroxidases types not found in wood-rotting Polyporales, and other Agaricomycetes orders. Therefore, we analyzed the peroxidase evolution in Agaricomycetes by ancestral-sequence reconstruction revealing several major evolutionary pathways and mapped the appearance of the different enzyme types in a time-calibrated species tree.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Toward a Holistic Performance Evaluation of Large Language Models Across Diverse AI Accelerators

Artificial intelligence (AI) methods have become critical in scientific applications to help accelerate scientific discovery. Large language models (LLMs) are being considered a promising approach to address some challenging problems because of their superior generalization capabilities across domains. The effectiveness of the models and the accuracy of the applications are contingent upon their efficient execution on the underlying hardware infrastructure. Specialized Al accelerator hardware systems have recently become available for accelerating Al applications. However, the comparative performance of these AI accelerators on large language models has not been previously studied. In this paper, we systematically study LLMs on multiple AI accelerators and GPUs and evaluate their performance characteristics for these models. We evaluate these systems with (i) a micro-benchmark using a core transformer block, (ii) a GPT-2 model, and (iii) an 1,I,M-driven science use case, GenSLM. We present our findings and analyses of the models' performance to better understand the intrinsic capabilities of AI accelerators. Furthermore, our analysis takes into account key factors such as sequence lengths, scaling behavior, and sensitivity to gradient accumulation steps.

Emani, Murali↗
DOE OSTI2017

Processing and characteristics of transparent Gd 3 TaO 7 polycrystalline ceramics

Transparent polycrystalline Gd 3 TaO 7 ceramics were successfully developed. A sol-gel process was used to synthesize Gd 3 TaO 7 powder with a uniform composition and an estimated average particle size of 100 nm. Simultaneous thermal gravimetric analysis and differential thermal analysis (TGA/DTA) was used to identify the decomposition sequence as a function of temperature for the as-synthesized sol-gel powders. Crystallization was confirmed by X-ray diffraction (XRD) and a single phase was achieved by calcining at 1000°C. The calcined powders were hot-pressed at 1400°C to achieve >96% theoretical density with closed pore structure followed by a hot isostatic pressing at 1400°C at 207 MPa to achieve a fully dense structure. Microstructural characterization shows a uniform grain size distribution with an average grain size of about 7 μm. In-line transmission measurements revealed high transparency in the red and infrared. Thermal conductivity was measured to be >1.6 W/mK at room temperature, decreasing to ~1.3 W/mK by 500°C. Dielectric properties remain stable with relative permittivity values just above 200 and loss tangents <0.005 up to 350°C.

36 MATERIALS SCIENCE↗
DOE OSTI2016

In situ embryo rescue for generation of wide intra‐ and interspecific hybrids of Panicum virgatum L.

Summary Wide crosses have been used for decades as a method for transferring novel genetic material and traits in plant breeding. Historically, many products of wide crosses require tedious and inefficient surgical embryo rescue prior to embryo abortion to recover single plantlets. We have utilized transgenic switchgrass ( Panicum virgatum L. cv Alamo) as a pollen donor in conjunction with antibiotic or herbicide selection for recovery of intra‐and interspecific F 1 crosses by using developing ovules from the female parent and selecting for embryogenic cultures derived from the in situ immature embryo. Using this approach, several intravarietial crosses were generated between transgenic Alamo and the switchgrass varieties Kanlow, Blackwell and Cave ‐ in ‐ Rock as well as an interspecific cross with Atlantic coastal panicgrass. This procedure selected F 1 embryogenic callus produced from the developing embryo contained within isolated immature ovules. Several clonal plants were successfully regenerated from each cross. Southern blot, PCR , phenotypic analyses and genomic analysis confirmed F 1 hybrids. Using genotyping‐by‐sequencing shows the hybridization of the recovered plants by determining the ratio of transgressive markers to total compared markers between parents and their potential offspring. The ratio of transgressive markers to total compared markers was significantly lower between parents and their predicted offspring than between parents and offspring unrelated to them. This approach provides the possibility to move useful transgenes into varieties that are recalcitrant to direct transformation which can be optionally segregated thus useful to create new hybrids, as well as recovery of wide crosses that are either difficult or impossible using traditional techniques.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

SU-G-JeP1-07: Development of a Programmable Motion Testbed for the Validation of Ultrasound Tracking Algorithms

Purpose: To develop an advanced testbed that combines a 3D motion stage and ultrasound phantom to optimize and validate 2D and 3D tracking algorithms for real-time motion management during radiation therapy. Methods: A Siemens S2000 Ultrasound scanner utilizing a 9L4 transducer was coupled with the Washington University 4D Phantom to simulate patient motion. The transducer was securely fastened to the 3D stage and positioned to image three cylinders of varying contrast in a Gammex 404GS LE phantom. The transducer was placed within a water bath above the phantom in order to maintain sufficient coupling for the entire range of simulated motion. A programmed motion sequence was used to move the transducer during image acquisition and a cine video was acquired for one minute to allow for long sequence tracking. Images were analyzed using a normalized cross-correlation block matching tracking algorithm and compared to the known motion of the transducer relative to the phantom. Results: The setup produced stable ultrasound motion traces consistent with those programmed into the 3D motion stage. The acquired ultrasound images showed minimal artifacts and an image quality that was more than suitable for tracking algorithm verification. Comparisons of a block matching tracking algorithm with the known motion trace for the three features resulted in an average tracking error of 0.59 mm. Conclusion: The high accuracy and programmability of the 4D phantom allows for the acquisition of ultrasound motion sequences that are highly customizable; allowing for focused analysis of some common pitfalls of tracking algorithms such as partial feature occlusion or feature disappearance, among others. The design can easily be modified to adapt to any probe such that the process can be extended to 3D acquisition. Further development of an anatomy specific phantom better resembling true anatomical landmarks could lead to an even more robust validation. This work is partially funded by NIH grant R01CA190298.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Pathosphere.org: pathogen detection and characterization through a web-based, open source informatics platform

The detection of pathogens in complex sample backgrounds has been revolutionized by wide access to next-generation sequencing (NGS) platforms. However, analytical methods to support NGS platforms are not as uniformly available. Pathosphere (found at Pathosphere.org) is a cloud - based open - sourced community tool that allows for communication, collaboration and sharing of NGS analytical tools and data amongst scientists working in academia, industry and government. The architecture allows for users to upload data and run available bioinformatics pipelines without the need for onsite processing hardware or technical support. The pathogen detection capabilities hosted on Pathosphere were tested by analyzing pathogen-containing samples sequenced by NGS with both spiked human samples as well as human and zoonotic host backgrounds. Pathosphere analytical pipelines developed by Edgewood Chemical Biological Center (ECBC) identified spiked pathogens within a common sample analyzed by 454, Ion Torrent, and Illumina sequencing platforms. ECBC pipelines also correctly identified pathogens in human samples containing arenavirus in addition to animal samples containing flavivirus and coronavirus. These analytical methods were limited in the detection of sequences with limited homology to previous annotations within NCBI databases, such as parvovirus. Utilizing the pipeline-hosting adaptability of Pathosphere, the analytical suite was supplemented by analytical pipelines designed by the United States Army Medical Research Institute of Infectious Diseases and Walter Reed Army Institute of Research (USAMRIID-WRAIR). These pipelines were implemented and detected parvovirus sequence in the sample that the ECBC iterative analysis previously failed to identify. By accurately detecting pathogens in a variety of samples, this work demonstrates the utility of Pathosphere and provides a platform for utilizing, modifying and creating pipelines for a variety of NGS technologies developed to detect pathogens in complex sample backgrounds. These results serve as an exhibition for the existing pipelines and web-based interface of Pathosphere as well as the plug-in adaptability that allows for integration of newer NGS analytical software as it becomes available.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Feature selection and causal analysis for microbiome studies in the presence of confounding using standardization

Abstract Background Microbiome studies have uncovered associations between microbes and human, animal, and plant health outcomes. This has led to an interest in developing microbial interventions for treatment of disease and optimization of crop yields which requires identification of microbiome features that impact the outcome in the population of interest. That task is challenging because of the high dimensionality of microbiome data and the confounding that results from the complex and dynamic interactions among host, environment, and microbiome. In the presence of such confounding, variable selection and estimation procedures may have unsatisfactory performance in identifying microbial features with an effect on the outcome. Results In this manuscript, we aim to estimate population-level effects of individual microbiome features while controlling for confounding by a categorical variable. Due to the high dimensionality and confounding-induced correlation between features, we propose feature screening, selection, and estimation conditional on each stratum of the confounder followed by a standardization approach to estimation of population-level effects of individual features. Comprehensive simulation studies demonstrate the advantages of our approach in recovering relevant features. Utilizing a potential-outcomes framework, we outline assumptions required to ascribe causal, rather than associational, interpretations to the identified microbiome effects. We conducted an agricultural study of the rhizosphere microbiome of sorghum in which nitrogen fertilizer application is a confounding variable. In this study, the proposed approach identified microbial taxa that are consistent with biological understanding of potential plant-microbe interactions. Conclusions Standardization enables more accurate identification of individual microbiome features with an effect on the outcome of interest compared to other variable selection and estimation procedures when there is confounding by a categorical variable.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

COMPILE: a GWAS computational pipeline for gene discovery in complex genomes

Abstract Background Genome-Wide Association Studies (GWAS) are used to identify genes and alleles that contribute to quantitative traits in large and genetically diverse populations. However, traits with complex genetic architectures create an enormous computational load for discovery of candidate genes with acceptable statistical certainty. We developed a streamlined computational pipeline for GWAS (COMPILE) to accelerate identification and annotation of candidate maize genes associated with a quantitative trait, and then matches maize genes to their closest rice and Arabidopsis homologs by sequence similarity. Results COMPILE executed GWAS using a Mixed Linear Model that incorporated, without compression, recent advancements in population structure control, then linked significant Quantitative Trait Loci (QTL) to candidate genes and RNA regulatory elements contained in any genome. COMPILE was validated using published data to identify QTL associated with the traits of α-tocopherol biosynthesis and flowering time, and identified published candidate genes as well as additional genes and non-coding RNAs. We then applied COMPILE to 274 genotypes of the maize Goodman Association Panel to identify candidate loci contributing to resistance of maize stems to penetration by larvae of the European Corn Borer ( Ostrinia nubilalis ). Candidate genes included those that encode a gene of unknown function, WRKY and MYB-like transcriptional factors, receptor-kinase signaling, riboflavin synthesis, nucleotide-sugar interconversion, and prolyl hydroxylation. Expression of the gene of unknown function has been associated with pathogen stress in maize and in rice homologs closest in sequence identity. Conclusions The relative speed of data analysis using COMPILE allowed comparison of population size and compression. Limitations in population size and diversity are major constraints for a trait and are not overcome by increasing marker density. COMPILE is customizable and is readily adaptable for application to species with robust genomic and proteome databases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗