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DOE OSTI2023

Haplotype‐resolved genome assembly of Populus tremula × P. alba reveals aspen‐specific megabase satellite DNA

SUMMARY Populus species play a foundational role in diverse ecosystems and are important renewable feedstocks for bioenergy and bioproducts. Hybrid aspen Populus tremula × P. alba INRA 717‐1B4 is a widely used transformation model in tree functional genomics and biotechnology research. As an outcrossing interspecific hybrid, its genome is riddled with sequence polymorphisms which present a challenge for sequence‐sensitive analyses. Here we report a telomere‐to‐telomere genome for this hybrid aspen with two chromosome‐scale, haplotype‐resolved assemblies. We performed a comprehensive analysis of the repetitive landscape and identified both tandem repeat array‐based and array‐less centromeres. Unexpectedly, the most abundant satellite repeats in both haplotypes lie outside of the centromeres, consist of a 147 bp monomer PtaM147, frequently span >1 megabases, and form heterochromatic knobs. PtaM147 repeats are detected exclusively in aspens (section Populus ) but PtaM147‐like sequences occur in LTR‐retrotransposons of closely related species, suggesting their origin from the retrotransposons. The genomic resource generated for this transformation model genotype has greatly improved the design and analysis of genome editing experiments that are highly sensitive to sequence polymorphisms. The work should motivate future hypothesis‐driven research to probe into the function of the abundant and aspen‐specific PtaM147 satellite DNA.

Zhou, Ran↗

DOE OSTI2015

SUPER-FOCUS: A tool for agile functional analysis of shotgun metagenomic data

Analyzing the functional profile of a microbial community from unannotated shotgun sequencing reads is one of the important goals in metagenomics. Functional profiling has valuable applications in biological research because it identifies the abundances of the functional genes of the organisms present in the original sample, answering the question what they can do. Currently, available tools do not scale well with increasing data volumes, which is important because both the number and lengths of the reads produced by sequencing platforms keep increasing. Here, we introduce SUPER-FOCUS, SUbsystems Profile by databasE Reduction using FOCUS, an agile homology-based approach using a reduced reference database to report the subsystems present in metagenomic datasets and profile their abundances. We tested SUPER-FOCUS with over 70 real metagenomes, the results showing that it accurately predicts the subsystems present in the profiled microbial communities, and is up to 1000 times faster than other tools.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2013

STELLAR DIAMETERS AND TEMPERATURES. III. MAIN-SEQUENCE A, F, G, AND K STARS: ADDITIONAL HIGH-PRECISION MEASUREMENTS AND EMPIRICAL RELATIONS

Based on CHARA Array measurements, we present the angular diameters of 23 nearby, main-sequence stars, ranging from spectral types A7 to K0, 5 of which are exoplanet host stars. We derive linear radii, effective temperatures, and absolute luminosities of the stars using Hipparcos parallaxes and measured bolometric fluxes. The new data are combined with previously published values to create an Angular Diameter Anthology of measured angular diameters to main-sequence stars (luminosity classes V and IV). This compilation consists of 125 stars with diameter uncertainties of less than 5%, ranging in spectral types from A to M. The large quantity of empirical data is used to derive color-temperature relations to an assortment of color indices in the Johnson (BVR{sub J} I{sub J} JHK), Cousins (R{sub C} I{sub C}), Kron (R{sub K} I{sub K}), Sloan (griz), and WISE (W{sub 3} W{sub 4}) photometric systems. These relations have an average standard deviation of {approx}3% and are valid for stars with spectral types A0-M4. To derive even more accurate relations for Sun-like stars, we also determined these temperature relations omitting early-type stars (T{sub eff} > 6750 K) that may have biased luminosity estimates because of rapid rotation; for this subset the dispersion is only {approx}2.5%. We find effective temperatures in agreement within a couple of percent for the interferometrically characterized sample of main-sequence stars compared to those derived via the infrared flux method and spectroscopic analysis.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Analysis of genomic signatures associated with Variovorax endosphere colonization

This repository contains the analysis code and supporting datasets associated with the study “Genomic signatures in Variovorax enabling colonization of the Populus endosphere.” Beals DG, Carper DL, Hochanadel LH, Jawdy SS, Klingeman DM, Piatkowski BT, Weston DJ, Doktycz MJ, Pelletier DA. 2026. Genomic signatures in Variovorax enabling colonization of the Populus endosphere. mSystems 11:e01605-25. https://doi.org/10.1128/msystems.01605-25 The scripts are organized sequentially (01–07) and document the workflows used for: Sequence-read alignment and feature counting Orthogroup and KEGG Ortholog annotation Count normalization Statistical analysis and aggregation Generation of manuscript figures and tables Repository contents The uncompressed files are the finalized, formatted datasets used to generate the figures and tables reported in the study, including the supplemental CSV files referenced in the manuscript. The accompanying ZIP archive contains the complete codebase and example data_input/ and data_output/ directories illustrating the organization and execution of the analytical workflow. Individual scripts identify the corresponding manuscript analyses and figure panels. Raw sequencing data Raw sequencing reads are available through the NCBI Sequence Read Archive under BioProject accession PRJNA1322484.

Beals, Delaney [ORNL] (ORCID:0000000306274574)↗

DOE OSTI2016

Systematic identification and analysis of frequent gene fusion events in metabolic pathways

Here, gene fusions are the most powerful type of in silico -derived functional associations. However, many fusion compilations were made when <100 genomes were available, and algorithms for identifying fusions need updating to handle the current avalanche of sequenced genomes. The availability of a large fusion dataset would help probe functional associations and enable systematic analysis of where and why fusion events occur. As a result, here we present a systematic analysis of fusions in prokaryotes. We manually generated two training sets: (i) 121 fusions in the model organism Escherichia coli ; (ii) 131 fusions found in B vitamin metabolism. These sets were used to develop a fusion prediction algorithm that captured the training set fusions with only 7 % false negatives and 50 % false positives, a substantial improvement over existing approaches. This algorithm was then applied to identify 3.8 million potential fusions across 11,473 genomes. The results of the analysis are available in a searchable database. A functional analysis identified 3,000 reactions associated with frequent fusion events and revealed areas of metabolism where fusions are particularly prevalent. In conclusion, customary definitions of fusions were shown to be ambiguous, and a stricter one was proposed. Exploring the genes participating in fusion events showed that they most commonly encode transporters, regulators, and metabolic enzymes. The major rationales for fusions between metabolic genes appear to be overcoming pathway bottlenecks, avoiding toxicity, controlling competing pathways, and facilitating expression and assembly of protein complexes. Finally, our fusion dataset provides powerful clues to decipher the biological activities of domains of unknown function.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Formation of Al{sub 15}Mn{sub 3}Si{sub 2} Phase During Solidification of a Novel Al-12%Si-4%Cu-1.2%Mn Heat-Resistant Alloy and Its Thermal Stability

The formation of Al{sub 15}Mn{sub 3}Si{sub 2} phase in Al-12Si-4Cu-1.2Mn (wt.%) alloy during solidification was investigated by adopting CALPHAD method and microstructural observation by optical microscopy, SEM–EDS, TEM–EDS/SAD and XRD analysis; SEM fixed-point observation method was applied to evaluate its thermal stability. As-cast microstructural observation consistently demonstrates the solidification sequence of the studied alloy predicted by phase diagram calculation. Based on the phase diagram calculation, SEM–EDS, TEM–EDS/SAD and XRD analysis, as well as evidences on Al-Si-Mn-Fe compounds from the literature, the primary and eutectic Mn-rich phases with different morphologies in the studied alloy are identified to be Al{sub 15}Mn{sub 3}Si{sub 2} that has a body-centered cubic (BCC) structure with a lattice constant of a = 1.352 nm. SEM fixed-point observation and XRD analysis indicate that Al{sub 15}Mn{sub 3}Si{sub 2} phase has more excellent thermal stability at high temperature than that of CuAl{sub 2} phase and can serve as the major strengthening phase in heat-resistant aluminum alloy that has to face a high-temperature working environment. Results of tension test show that addition of Mn can improve the strength of Al-Si-Cu alloy, especially at elevated temperature.

36 MATERIALS SCIENCE↗

DOE OSTI2015

Metagenomic analysis of the microbiota in the highly compartmented hindguts of six wood- or soil-feeding higher termites

Termites are important contributors to carbon and nitrogen cycling in tropical ecosystems. Higher termites digest lignocellulose in various stages of humification with the help of an entirely prokaryotic microbiota housed in their compartmented intestinal tract. Previous studies revealed fundamental differences in community structure between compartments, but the functional roles of individual lineages in symbiotic digestion are mostly unknown. Furthermore, we conducted a highly resolved analysis of the gut microbiota in six species of higher termites that feed on plant material at different levels of humification. Combining amplicon sequencing and metagenomics, we assessed similarities in community structure and functional potential between the major hindgut compartments (P1, P3, and P4). Cluster analysis of the relative abundances of orthologous gene clusters (COGs) revealed high similarities among woodand litter-feeding termites and strong differences to humivorous species. However, abundance estimates of bacterial phyla based on 16S rRNA genes greatly differed from those based on protein-coding genes. In conclusion, the community structure and functional potential of the microbiota in individual gut compartments are clearly driven by the digestive strategy of the host. The metagenomics libraries obtained in this study provide the basis for future studies that elucidate the fundamental differences in the symbiont-mediated breakdown of lignocellulose and humus by termites of different feeding groups. Furthermore, the high proportion of uncultured bacterial lineages in all samples calls for a reference-independent approach for the correct taxonomic assignment of protein-coding genes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

ShadeLab/PAPER_Howe_2023_switchgrass_MetaT

The raw data (metagenomes and metatranscriptomes) for this study are available in the Joint Genomes Institute Genome Portal (https://genome.jgi.doe.gov/portal/ Project ID 503249) with projects designated by year and product type. The MAG genomes analyzed in this paper are available on NCBI, as bioproject PRJNA800073. Plants and microorganisms form beneficial associations. Understanding plant-microbe interactions will inform microbiome management to enhance crop productivity and resilience to stress. Here, we apply a genome-centric approach to identify ecologically important leaf microbiome members on field-grown switchgrass and miscanthus and to quantify their activities for switchgrass over two growing seasons. We integrate metagenome and metatranscriptome sequencing from 192 leaf samples collected over representative time points in crop phenology. We curated 40 medium- and high-quality metagenome-assembled-genomes (MAGs) and focused analysis on seasonal transcript recruitment to them. Classes represented by these focal MAGs (Actinomycetia, Alpha- and Gamma- Proteobacteria, and Bacteroidota) were active and had increases in transcripts for short-chain dehydrogenase, molybdopterin oxidoreductase, and polyketide cyclase in the late season. The majority of MAGs had activated stress-associated pathways, including trehalose metabolism, indole acetic acid degradation, betaine biosynthesis, and reactive oxygen species degradation, suggesting direct engagement with the host environment. We also detected seasonally activated biosynthetic pathways for terpenes (carotenoids and isoprenoids) and for various non-ribosomal peptide pathways that were poorly annotated. Overall, this study overcame laboratory and bioinformatic challenges associated with field-based leaf metatranscriptome analysis to inform both general and likely specialized activities of these phyllosphere populations. These activities collectively support that leaf-associated bacterial populations are seasonally dynamic, responsive to host cues, and interactively engage in feedback with the plant. This analysis represented quality filtering of metagenomes and metatranscriptomes (data-preparation folder), metagenome assemblies (metagenome-assembly folder) and metagenome-assembled genome binning, curation, refinement, annotation (mag-evaluation folder). Abundances of sequencing libraries were calculated based on reads mapped (mapping folder). Additionallly, analysis of our annotated results are also included (analysis folder).

Howe, Adina↗

DOE OSTI2012

Development of Thermoanaerobacterium saccharolyticum for the conversion of lignocellulose to ethanol (Final Technical Report)

This project addressed the need for economical technology for the conversion of lignocellulosic biomass to fuels, specifically the conversion of pretreated hardwood to ethanol. The technology developed is a set of strains of the bacterium Thermoanaerobacterium saccharolyticum and an associated fermentation process for pretreated hardwood. Tools for genetic engineering and analysis of the organism were developed, including a markerless mutation method, a complete genome sequence and a set of gene expression profiles that show the activity of its genes under a variety of conditions relevant to lignocellulose conversion. Improved strains were generated by selection and genetic engineering to be able to produce higher amounts of ethanol (up to 70 g/L) and to be able to better tolerate inhibitory compounds from pretreated hardwood. Analysis of these strains has generated useful insight into the genetic basis for desired properties of biofuel producing organisms. Fermentation conditions were tested and optimized to achieve ethanol production targets established in the original project proposal. The approach proposed was to add cellulase enzymes to the fermentation, a method called Simultaneous Saccharification and Fermentation (SSF). We had reason to think SSF would be an efficient approach because the optimal temperature and pH for the enzymes and bacterium are very close. Unfortunately, we discovered that commercially available cellulases are inactivated in thermophilic SSF by a combination of low redox potential and ethanol. Despite this, progress was made against the fermentation targets using bacterial cellulases. Thermoanaerobacterium saccharolyticum may still prove to be a commercially viable technology should cellulase enzyme issues be addressed. Moreover, the organism was demonstrated to produce ethanol at approximately theoretical yield from oligomeric hemicellulose extracts, an ability that may prove to be uniquely valuable in pretreatment configurations in which cellulose and hemicellulose are separated.

09 BIOMASS FUELS↗

DOE OSTI2014

The Genome Portal of the Department of Energy Joint Genome Institute

The JGI Genome Portal (http://genome.jgi.doe.gov) provides unified access to all JGI genomic databases and analytical tools. A user can search, download and explore multiple data sets available for all DOE JGI sequencing projects including their status, assemblies and annotations of sequenced genomes. Genome Portal in the past 2 years was significantly updated, with a specific emphasis on efficient handling of the rapidly growing amount of diverse genomic data accumulated in JGI. A critical aspect of handling big data in genomics is the development of visualization and analysis tools that allow scientists to derive meaning from what are otherwise terrabases of inert sequence. An interactive visualization tool developed in the group allows us to explore contigs resulting from a single metagenome assembly. Implemented with modern web technologies that take advantage of the power of the computer's graphical processing unit (gpu), the tool allows the user to easily navigate over a 100,000 data points in multiple dimensions, among many biologically meaningful parameters of a dataset such as relative abundance, contig length, and G+C content.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

Data Analysis Approaches for the Risk-Informed Safety Margins Characterization Toolkit

In the past decades, several numerical simulation codes have been employed to simulate accident dynamics (e.g., RELAP5-3D, RELAP-7, MELCOR, MAAP). In order to evaluate the impact of uncertainties into accident dynamics, several stochastic methodologies have been coupled with these codes. These stochastic methods range from classical Monte-Carlo and Latin Hypercube sampling to stochastic polynomial methods. Similar approaches have been introduced into the risk and safety community where stochastic methods (such as RAVEN, ADAPT, MCDET, ADS) have been coupled with safety analysis codes in order to evaluate the safety impact of timing and sequencing of events. These approaches are usually called Dynamic PRA or simulation-based PRA methods. These uncertainties and safety methods usually generate a large number of simulation runs (database storage may be on the order of gigabytes or higher). The scope of this paper is to present a broad overview of methods and algorithms that can be used to analyze and extract information from large data sets containing time dependent data. In this context, “extracting information” means constructing input-output correlations, finding commonalities, and identifying outliers. Some of the algorithms presented here have been developed or are under development within the RAVEN statistical framework.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Analysis of Time Dependent Data and PRA

In the past decades, several numerical simulation codes have been employed to simulate accident dynamics (e.g., RELAP5-3D, MELCOR, MAAP). In order to evaluate the impact of uncertainties into accident dynamics, several stochastic methodologies have been coupled with these codes. These stochastic methods range from classical Monte-Carlo and Latin Hypercube sampling to stochastic polynomial methods. Similar approaches have been introduced into the risk and safety community where stochastic methods (such as RAVEN, ADAPT, MCDET, ADS) have been coupled with safety analysis codes in order to evaluate the safety impact of timing and sequencing of events. These approaches are usually called Dynamic PRA or simulation-based PRA methods. These uncertainties and safety methods usually generate a large number of simulation runs (database storage may be on the order of gigabytes or higher). The scope of this paper is to present a broad overview of methods and algorithms that can be used to analyze and extract information from large data sets containing time dependent data. In this context, 'extracting information' means constructing input-output correlations, finding commonalities, and identifying outliers. Some of the algorithms presented here have been developed or are under development within the RAVEN statistical framework. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2013

Evolutionary analyses of non-family genes in plants

There are a large number of non-family (NF) genes that do not cluster into families with three or more members per genome. While gene families have been extensively studied, a systematic analysis of NF genes has not been reported. We performed comparative studies on NF genes in 14 plant species. Based on the clustering of protein sequences, we identified ~94,000 NF genes across these species that were divided into five evolutionary groups: Viridiplantae-wide, angiosperm-specific, monocot-specific, dicot-specific, and those that were species-specific. Our analysis revealed that the NF genes resulted largely from less frequent gene duplications and/or a higher rate of gene loss after segmental duplication relative to genes in both low-copy-number families (LF; 3 10 copies per genome) and high-copy-number families (HF; >10 copies). Furthermore, we identified functions enriched in the NF gene set as compared with the HF genes. We found that NF genes were involved in essential biological processes shared by all plant lineages (e.g., photosynthesis and translation), as well as gene regulation and stress responses associated with phylogenetic diversification. In particular, our analysis of an Arabidopsis protein-protein interaction network revealed that hub proteins with the top 10% most connections were over-represented in the NF set relative to the HF set. This research highlights the roles that NF genes may play in evolutionary and functional genomics research.

Ye, Chuyu↗

DOE OSTI2024

HAPPA: A Modular Platform for HPC Application Resilience Analysis with LLMs Embedded

High-performance computing (HPC) systems are increasingly vulnerable to soft errors, which pose significant challenges in maintaining computational accuracy and reliability. Predicting the resilience of HPC applications to these errors is crucial for robust code protection and detailed resilience analysis. In this study, we present HAppA, a modular platform designed for HPC Application Resilience Analysis. Embedding Large Language Models (LLMs), HAppA addresses understanding the context information of long code sequences typical in HPC applications. HAppA implements a novel code representation module that chunks the code into fixed-size segments and aggregates the embeddings of these segments. Three aggregation methods have been explored: MeanPooling, MaxPooling, and LSTM-based techniques. We built a DAtaset for REsilience analysis using Fault Injection (FI), named DARE. Using our DARE dataset, HAppA is trained for regression prediction tasks. Our evaluation results demonstrate the predictive accuracy of HAppA compared to other models, particularly noting that the LSTM-based aggregation method -- HAppA-LSTM -- achieves a mean squared error (MSE) of 0.078 for SDC prediction, surpassing the existing state-of-the-art PARIS model, which recorded an MSE of 0.1172. Additionally, HAppA with the KeyBERT model extracts a list of keywords representing the source code. A comprehensive importance analysis of these keywords further elucidates the code patterns contributing to the error rate. These findings highlight the effectiveness of HAppA in analyzing the resilience of HPC applications and establish a new benchmark for predictive accuracy in resilience.

Jiang, Hailong [Kent State University]↗

DOE OSTI2012

Genome Improvement at JGI-HAGSC

Since the completion of the sequencing of the human genome, the Joint Genome Institute (JGI) has rapidly expanded its scientific goals in several DOE mission-relevant areas. At the JGI-HAGSC, we have kept pace with this rapid expansion of projects with our focus on assessing, assembling, improving and finishing eukaryotic whole genome shotgun (WGS) projects for which the shotgun sequence is generated at the Production Genomic Facility (JGI-PGF). We follow this by combining the draft WGS with genomic resources generated at JGI-HAGSC or in collaborator laboratories (including BAC end sequences, genetic maps and FLcDNA sequences) to produce an improved draft sequence. For eukaryotic genomes important to the DOE mission, we then add further information from directed experiments to produce reference genomic sequences that are publicly available for any scientific researcher. Also, we have continued our program for producing BAC-based finished sequence, both for adding information to JGI genome projects and for small BAC-based sequencing projects proposed through any of the JGI sequencing programs. We have now built our computational expertise in WGS assembly and analysis and have moved eukaryotic genome assembly from the JGI-PGF to JGI-HAGSC. We have concentrated our assembly development work on large plant genomes and complex fungal and algal genomes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2014

An optimized method to identify RR Lyrae stars in the SDSS×Pan-STARRS1 overlapping area using a bayesian generative technique

We present a method for selecting RR Lyrae (RRL) stars (or other types of variable stars) in the absence of a large number of multi-epoch data and light curve analyses. Our method uses color and variability selection cuts that are defined by applying a Gaussian Mixture Bayesian Generative Method (GMM) on 636 pre-identified RRL stars instead of applying the commonly used rectangular cuts. Specifically, our method selects 8115 RRL candidates (heliocentric distances < 70 kpc) using GMM color cuts from the Sloan Digital Sky Survey (SDSS) and GMM variability cuts from the Panoramic Survey Telescope and Rapid Response System 1 3π survey (PS1). Comparing our method with the Stripe 82 catalog of RRL stars shows that the efficiency and completeness levels of our method are ∼77% and ∼52%, respectively. Most contaminants are either non-variable main-sequence stars or stars in eclipsing systems. The method described here efficiently recovers known stellar halo substructures. It is expected that the current completeness and efficiency levels will further improve with the additional PS1 epochs (∼3 epochs per filter) that will be observed before the conclusion of the survey. A comparison between our efficiency and completeness levels using the GMM method to the efficiency and completeness levels using rectangular cuts that are commonly used yielded a significant increase in the efficiency level from ∼13% to ∼77% and an insignificant change in the completeness levels. Hence, we favor using the GMM technique in future studies. Although we develop it over the SDSS×PS1 footprint, the technique presented here would work well on any multi-band, multi-epoch survey for which the number of epochs is limited.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

California condor microbiomes: Bacterial variety and functional properties in captive-bred individuals

Around the world, scavenging birds such as vultures and condors have been experiencing drastic population declines. Scavenging birds have a distinct digestive process to deal with higher amounts of bacteria in their primary diet of carcasses in varying levels of decay. These observations motivate us to present an analysis of captive and healthy California condor (Gymnogyps californianus) microbiomes to characterize a population raised together under similar conditions. Shotgun metagenomic DNA sequences were analyzed from fecal and cloacal samples of captive birds. Classification of shotgun DNA sequence data with peptide signatures using the Sequedex package provided both phylogenetic and functional profiles, as well as individually annotated reads for targeted confirmatory analysis. We observed bacterial species previously associated with birds and gut microbiomes, including both virulent and opportunistic pathogens such as Clostridium perfringens, Propionibacterium acnes, Shigella flexneri, and Fusobacterium mortiferum, common flora such as Lactobacillus johnsonii, Lactobacillus ruminus, and Bacteroides vulgatus, and mucosal microbes such as Delftia acidovorans, Stenotrophomonas maltophilia, and Corynebacterium falsnii. Classification using shotgun metagenomic reads from phylogenetic marker genes was consistent with, and more specific than, analysis based on 16S rDNA data. Classification of samples based on either phylogenetic or functional profiles of genomic fragments differentiated three types of samples: fecal, mature cloacal and immature cloacal, with immature birds having approximately 40% higher diversity of microbes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2012

Identification of a p-Coumarate Degradation Regulon in Rhodopseudomonas palustris by Xpression, an Integrated Tool for Prokaryotic RNA-Seq Data Processing

High-throughput sequencing of cDNA prepared from RNA, an approach known as RNA-seq, is coming into increasing use as a method for transcriptome analysis. Despite its many advantages, widespread adoption of the technique has been hampered by a lack of easy-to-use, integrated, open-source tools for analyzing the nucleotide sequence data that are generated. Here we describe Xpression, an integrated tool for processing prokaryotic RNA-seq data. The tool is easy to use and is fully automated. It performs all essential processing tasks, including nucleotide sequence extraction, alignment, quantification, normalization, and visualization. Importantly, Xpression processes multiplexed and strand-specific nucleotide sequence data. It extracts and trims specific sequences from files and separately quantifies sense and antisense reads in the final results. Outputs from the tool can also be conveniently used in downstream analysis. In this paper, we show the utility of Xpression to process strand-specific RNA-seq data to identify genes regulated by CouR, a transcription factor that controls p -coumarate degradation by the bacterium Rhodopseudomonas palustris.

59 BASIC BIOLOGICAL SCIENCES↗