Facilitating Multifunctional Green Infrastructure Planning in Washington, DC through a Tableau Interface

Multifunctional urban green infrastructure (UGI) can regulate stormwater, mitigate heat islands, conserve biodiversity and biocultural diversity, and produce food, among other functions. Equitable governance of UGI requires new tools for sharing pertinent information. Our goal was to develop a public-access geographic information system (GIS) that can be used for comprehensive UGI planning in Washington, DC (the District) and to create an e-tool for UGI in the form of Tableau dashboards. The dashboards allow stakeholders to identify (1) existing UGI and (2) potential areas for new UGI including urban agriculture (UA). They also allow users to manipulate the data and identify priority locations for equitable UGI development by applying population vulnerability indices and other filters. We demonstrate use of the dashboards through scenarios focusing on UA in the District, which currently has 150 ha of existing UGI in the form of documented projects and an additional 3012 ha potentially suitable for UGI development. A total of 2792 ha is potentially suitable for UA, with 58% of that area in Wards 5, 7, and 8, which are largely food deserts and whose residents are primarily Black and experience the greatest inequities. Our work can serve as a model for similar digital tools in other locales using Tableau and other platforms

Mapping plant metabolic pathways using PathVisio 2

The purpose of this presentation is to show the source, methods, and results of creating a computerized display of the metabolic pathways of model plants Oryza sativa (rice) and Arabidopsis thaliana (thale cress) using the computer program PathVisio2. The finished products may be viewed and modified for free on www.wikipathways.org by the registered community annotators

WikiPathways for plants: a community pathway curation portal and a case study in rice and arabidopsis seed development networks

Background: Next-generation sequencing and 'omics' platforms are used extensively in plant biology research to unravel new genomes and study their interactions with abiotic and biotic agents in the growth environment. Despite the availability of a large and growing number of genomic data sets, there are only limited resources providing highly-curated and up-to-date metabolic and regulatory networks for plant pathways. Results: Using PathVisio, a pathway editor tool associated with WikiPathways, we created a gene interaction network of 430 rice (Oryza sativa) genes involved in the seed development process by curating interactions reported in the published literature. We then applied an InParanoid-based homology search to these genes and used the resulting gene clusters to identify 351 Arabidopsis thaliana genes. Using this list of homologous genes, we constructed a seed development network in Arabidopsis by processing the gene list and the rice network through a Perl utility software called Pathway GeneSWAPPER developed by us. In order to demonstrate the utility of these networks in generating testable hypotheses and preliminary analysis prior to more in-depth downstream analysis, we used the expression viewer and statistical analysis features of PathVisio to analyze publicly-available and published microarray gene expression data sets on diurnal photoperiod response and the seed development time course to discover patterns of coexpressed genes found in the rice and Arabidopsis seed development networks. These seed development networks described herein, along with other plant pathways and networks, are freely available on the plant pathways portal at WikiPathways (http://plants.wikipathways.org). Conclusion: In collaboration with the WikiPathways project we present a community curation and analysis platform for plant biologists where registered users can freely create, edit, share and monitor pathways supported by published literature. We describe the curation and annotation of a seed development network in rice, and the projection of a similar, gene homology-based network in Arabidopsis. We also demonstrate the utility of the Pathway GeneSWAPPER (PGS) application in saving valuable time and labor when a reference network in one species compiled in GPML format is used to project a similar network in another species based on gene homology.Keywords: Metabolic pathways, Stress response, Oryza sativa L., Gene expression, Coordinated transcriptional regulation, Use efficiency, Flowering time, Database, Identification, Genom

Design and Evaluation of a Crowdsourcing Precision Agriculture Mobile Application for Lambsquarters, Mission LQ

Precision agriculture is highly dependent on the collection of high quality ground truth data to validate the algorithms used in prescription maps. However, the process of collecting ground truth data is labor-intensive and costly. One solution to increasing the collection of ground truth data is by recruiting citizen scientists through a crowdsourcing platform. In this study, a crowdsourcing platform application was built using a human-centered design process. The primary goals were to gauge users’ perceptions of the platform, evaluate how well the system satisfies their needs, and observe whether the classification rate of lambsquarters by the users would match that of an expert. Previous work demonstrated a need for ground truth data on lambsquarters in the D.C., Maryland, Virginia (DMV) area. Previous social interviews revealed users who would want a citizen science platform to expand their skills and give them access to educational resources. Using a human-centered design protocol, design iterations of a mobile application were created in Kinvey Studio. The application, Mission LQ, taught people how to classify certain characteristics of lambsquarters in the DMV and allowed them to submit ground truth data. The final design of Mission LQ received a median system usability scale (SUS) score of 80.13, which indicates a good design. The classification rate of lambsquarters was 72%, which is comparable to expert classification. This demonstrates that a crowdsourcing mobile application can be used to collect high quality ground truth data for use in precision agriculture

GenizaMatthewMolecularCellularBiologyDeNovoTranscriptome_SupportingInformation.zip

BACKGROUND: Triticum monococcum (2n) is a close ancestor of T. urartu, the A-genome progenitor of cultivated hexaploid wheat, and is therefore a useful model for the study of components regulating photomorphogenesis in diploid wheat. In order to develop genetic and genomic resources for such a study, we constructed genome-wide transcriptomes of two Triticum monococcum subspecies, the wild winter wheat T. monococcum ssp. aegilopoides (accession G3116) and the domesticated spring wheat T. monococcum ssp. monococcum (accession DV92) by generating de novo assemblies of RNA-Seq data derived from both etiolated and green seedlings. PRINCIPAL FINDINGS: The de novo transcriptome assemblies of DV92 and G3116 represent 120,911 and 117,969 transcripts, respectively. We successfully mapped ~90% of these transcripts from each accession to barley and ~95% of the transcripts to T. urartu genomes. However, only ~77% transcripts mapped to the annotated barley genes and ~85% transcripts mapped to the annotated T. urartu genes. Differential gene expression analyses revealed 22% more light up-regulated and 35% more light down-regulated transcripts in the G3116 transcriptome compared to DV92. The DV92 and G3116 mRNA sequence reads aligned against the reference barley genome led to the identification of ~500,000 single nucleotide polymorphism (SNP) and ,22,000 simple sequence repeat (SSR) sites. CONCLUSIONS: De novo transcriptome assemblies of two accessions of the diploid wheat T. monococcum provide new empirical transcriptome references for improving Triticeae genome annotations, and insights into transcriptional programming during photomorphogenesis. The SNP and SSR sites identified in our analysis provide additional resources for the development of molecular markers

GenizaMatthewMolecularCellularBiologyDeNovoTranscriptome.pdf

BACKGROUND: Triticum monococcum (2n) is a close ancestor of T. urartu, the A-genome progenitor of cultivated hexaploid wheat, and is therefore a useful model for the study of components regulating photomorphogenesis in diploid wheat. In order to develop genetic and genomic resources for such a study, we constructed genome-wide transcriptomes of two Triticum monococcum subspecies, the wild winter wheat T. monococcum ssp. aegilopoides (accession G3116) and the domesticated spring wheat T. monococcum ssp. monococcum (accession DV92) by generating de novo assemblies of RNA-Seq data derived from both etiolated and green seedlings. PRINCIPAL FINDINGS: The de novo transcriptome assemblies of DV92 and G3116 represent 120,911 and 117,969 transcripts, respectively. We successfully mapped ~90% of these transcripts from each accession to barley and ~95% of the transcripts to T. urartu genomes. However, only ~77% transcripts mapped to the annotated barley genes and ~85% transcripts mapped to the annotated T. urartu genes. Differential gene expression analyses revealed 22% more light up-regulated and 35% more light down-regulated transcripts in the G3116 transcriptome compared to DV92. The DV92 and G3116 mRNA sequence reads aligned against the reference barley genome led to the identification of ~500,000 single nucleotide polymorphism (SNP) and ,22,000 simple sequence repeat (SSR) sites. CONCLUSIONS: De novo transcriptome assemblies of two accessions of the diploid wheat T. monococcum provide new empirical transcriptome references for improving Triticeae genome annotations, and insights into transcriptional programming during photomorphogenesis. The SNP and SSR sites identified in our analysis provide additional resources for the development of molecular markers

De Novo Transcriptome Assembly and Analyses of Gene Expression during Photomorphogenesis in Diploid Wheat Triticum monococcum

Citation: Fox, S., Geniza, M., Hanumappa, M., . . . Jaiswal, P. (2014). De Novo Transcriptome Assembly and Analyses of Gene Expression during Photomorphogenesis in Diploid Wheat Triticum monococcum. PLoS One, 9(5), e96855. https://doi.org/10.1371/journal.pone.0096855Background: Triticum monococcum (2n) is a close ancestor of T. urartu, the A-genome progenitor of cultivated hexaploid wheat, and is therefore a useful model for the study of components regulating photomorphogenesis in diploid wheat. In order to develop genetic and genomic resources for such a study, we constructed genome-wide transcriptomes of two Triticum monococcum subspecies, the wild winter wheat T. monococcum ssp. aegilopoides (accession G3116) and the domesticated spring wheat T. monococcum ssp. monococcum (accession DV92) by generating de novo assemblies of RNA-Seq data derived from both etiolated and green seedlings. Principal Findings: The de novo transcriptome assemblies of DV92 and G3116 represent 120,911 and 117,969 transcripts, respectively. We successfully mapped ~90% of these transcripts from each accession to barley and ~95% of the transcripts to T. urartu genomes. However, only ~77% transcripts mapped to the annotated barley genes and ~85% transcripts mapped to the annotated T. urartu genes. Differential gene expression analyses revealed 22% more light up-regulated and 35% more light down-regulated transcripts in the G3116 transcriptome compared to DV92. The DV92 and G3116 mRNA sequence reads aligned against the reference barley genome led to the identification of ~500,000 single nucleotide polymorphism (SNP) and ~22,000 simple sequence repeat (SSR) sites. Conclusions: De novo transcriptome assemblies of two accessions of the diploid wheat T. monococcum provide new empirical transcriptome references for improving Triticeae genome annotations, and insights into transcriptional programming during photomorphogenesis. The SNP and SSR sites identified in our analysis provide additional resources for the development of molecular markers

Exonerate_Alignments.tar.gz

Background: Triticum monococcum (2n) is a close ancestor of T. urartu, the A-genome progenitor of cultivated hexaploid wheat, and is therefore a useful model for the study of components regulating photomorphogenesis in diploid wheat. In order to develop genetic and genomic resources for such a study, we constructed genome-wide transcriptomes of two Triticum monococcum subspecies, the wild winter wheat T. monococcum ssp. aegilopoides (accession G3116) and the domesticated spring wheat T. monococcum ssp. monococcum (accession DV92) by generating de novo assemblies of RNA-Seq data derived from both etiolated and green seedlings. Principal Findings: The de novo transcriptome assemblies of DV92 and G3116 represent 120,911 and 117,969 transcripts, respectively. We successfully mapped ~90% of these transcripts from each accession to barley and ~95% of the transcripts to T. urartu genomes. However, only ~77% transcripts mapped to the annotated barley genes and ~85% transcripts mapped to the annotated T. urartu genes. Differential gene expression analyses revealed 22% more light up-regulated and 35% more light down-regulated transcripts in the G3116 transcriptome compared to DV92. The DV92 and G3116 mRNA sequence reads aligned against the reference barley genome led to the identification of ~500,000 single nucleotide polymorphism (SNP) and ~22,000 simple sequence repeat (SSR) sites. Conclusions: De novo transcriptome assemblies of two accessions of the diploid wheat T. monococcum provide new empirical transcriptome references for improving Triticeae genome annotations, and insights into transcriptional programming during photomorphogenesis. The SNP and SSR sites identified in our analysis provide additional resources for the development of molecular markers. For more details on the Triticum monococcum transcriptome project data, visit: http://jaiswallab.cgrb.oregonstate.edu/genomics/whea