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Dive into the research topics where Matthew Geniza is active.

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Featured researches published by Matthew Geniza.


PLOS ONE | 2014

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

Samuel E. Fox; Matthew Geniza; Mamatha Hanumappa; Sushma Naithani; Christopher M. Sullivan; Justin Preece; Vijay K. Tiwari; Justin Elser; Jeffrey M. Leonard; Abigail Sage; Cathy Gresham; Arnaud Kerhornou; Dan Bolser; Fiona M. McCarthy; Paul J. Kersey; Gerard R. Lazo; Pankaj Jaiswal

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.


Nucleic Acids Research | 2018

Expression Atlas: gene and protein expression across multiple studies and organisms

Irene Papatheodorou; Nuno A. Fonseca; Maria Keays; Y. Amy Tang; Elisabet Barrera; Wojciech Bażant; Melissa Burke; Anja Füllgrabe; Alfonso Munoz-Pomer Fuentes; Nancy George; Laura Huerta; Satu Koskinen; Suhaib Mohammed; Matthew Geniza; Justin Preece; Pankaj Jaiswal; Andrew F. Jarnuczak; Wolfgang Huber; Oliver Stegle; Juan Antonio Vizcaíno; Alvis Brazma; Robert Petryszak

Abstract Expression Atlas (http://www.ebi.ac.uk/gxa) is an added value database that provides information about gene and protein expression in different species and contexts, such as tissue, developmental stage, disease or cell type. The available public and controlled access data sets from different sources are curated and re-analysed using standardized, open source pipelines and made available for queries, download and visualization. As of August 2017, Expression Atlas holds data from 3,126 studies across 33 different species, including 731 from plants. Data from large-scale RNA sequencing studies including Blueprint, PCAWG, ENCODE, GTEx and HipSci can be visualized next to each other. In Expression Atlas, users can query genes or gene-sets of interest and explore their expression across or within species, tissues, developmental stages in a constitutive or differential context, representing the effects of diseases, conditions or experimental interventions. All processed data matrices are available for direct download in tab-delimited format or as R-data. In addition to the web interface, data sets can now be searched and downloaded through the Expression Atlas R package. Novel features and visualizations include the on-the-fly analysis of gene set overlaps and the option to view gene co-expression in experiments investigating constitutive gene expression across tissues or other conditions.


Nucleic Acids Research | 2018

Gramene 2018: unifying comparative genomics and pathway resources for plant research

Marcela K. Tello-Ruiz; Sushma Naithani; Joshua C. Stein; Parul Gupta; Michael S. Campbell; Andrew Olson; Sharon Wei; Justin Preece; Matthew Geniza; Yinping Jiao; Young Koung Lee; Bo Wang; Joseph Mulvaney; Kapeel Chougule; Justin Elser; Noor Al-Bader; Sunita Kumari; James Thomason; Vivek Kumar; Daniel M. Bolser; Guy Naamati; Electra Tapanari; Nuno A. Fonseca; Laura Huerta; Haider Iqbal; Maria Keays; Alfonso Munoz-Pomer Fuentes; Amy Tang; Antonio Fabregat; Peter D’Eustachio

Abstract Gramene (http://www.gramene.org) is a knowledgebase for comparative functional analysis in major crops and model plant species. The current release, #54, includes over 1.7 million genes from 44 reference genomes, most of which were organized into 62,367 gene families through orthologous and paralogous gene classification, whole-genome alignments, and synteny. Additional gene annotations include ontology-based protein structure and function; genetic, epigenetic, and phenotypic diversity; and pathway associations. Gramenes Plant Reactome provides a knowledgebase of cellular-level plant pathway networks. Specifically, it uses curated rice reference pathways to derive pathway projections for an additional 66 species based on gene orthology, and facilitates display of gene expression, gene–gene interactions, and user-defined omics data in the context of these pathways. As a community portal, Gramene integrates best-of-class software and infrastructure components including the Ensembl genome browser, Reactome pathway browser, and Expression Atlas widgets, and undergoes periodic data and software upgrades. Via powerful, intuitive search interfaces, users can easily query across various portals and interactively analyze search results by clicking on diverse features such as genomic context, highly augmented gene trees, gene expression anatomograms, associated pathways, and external informatics resources. All data in Gramene are accessible through both visual and programmatic interfaces.


PLOS ONE | 2015

Quantitative Trait Loci Associated with the Tocochromanol (Vitamin E) Pathway in Barley

Ryan C. Graebner; Mitchell L. Wise; Alfonso Cuesta-Marcos; Matthew Geniza; Tom Blake; Victoria C. Blake; Joshua Butler; Shiaomen Chao; David J Hole; R. D. Horsley; Pankaj Jaiswal; Don E. Obert; Kevin P. Smith; S. E. Ullrich; Patrick M. Hayes

The Genome-Wide Association Studies approach was used to detect Quantitative Trait Loci associated with tocochromanol concentrations using a panel of 1,466 barley accessions. All major tocochromanol types- α-, β-, δ-, γ-tocopherol and tocotrienol- were assayed. We found 13 single nucleotide polymorphisms associated with the concentration of one or more of these tocochromanol forms in barley, seven of which were within 2 cM of sequences homologous to cloned genes associated with tocochromanol production in barley and/or other plants. These associations confirmed a prior report based on bi-parental QTL mapping. This knowledge will aid future efforts to better understand the role of tocochromanols in barley, with specific reference to abiotic stress resistance. It will also be useful in developing barley varieties with higher tocochromanol concentrations, although at current recommended daily consumption amounts, barley would not be an effective sole source of vitamin E. However, it could be an important contributor in the context of whole grains in a balanced diet.


Mutation Research | 2015

The effect of low dose ionizing radiation on homeostasis and functional integrity in an organotypic human skin model

Claere von Neubeck; Matthew Geniza; Paula M. Kauer; Joseph E. Robinson; William B. Chrisler; Marianne B. Sowa

Outside the protection of Earths atmosphere, astronauts are exposed to low doses of high linear energy transfer (LET) radiation. Future NASA plans for deep space missions or a permanent settlement on the moon are limited by the health risks associated with space radiation exposures. There is a paucity of direct epidemiological data for low dose exposures to space radiation-relevant high LET ions. Health risk models are used to estimate the risk for such exposures, though these models are based on high dose experiments. There is increasing evidence, however, that low and high dose exposures result in different signaling events at the molecular level, and may involve different response mechanisms. Further, despite their low abundance, high LET particles have been identified as the major contributor to health risk during manned space flight. The human skin is exposed in every external radiation scenario, making it an ideal epithelial tissue model in which to study radiation induced effects. Here, we exposed an in vitro three dimensional (3-D) human organotypic skin tissue model to low doses of high LET oxygen (O), silicon (Si) and iron (Fe) ions. We measured proliferation and differentiation profiles in the skin tissue and examined the integrity of the skins barrier function. We discuss the role of secondary particles in changing the proportion of cells receiving a radiation dose, emphasizing the possible impact on radiation-induced health issues in astronauts.


Methods of Molecular Biology | 2017

Variant Effect Prediction Analysis Using Resources Available at Gramene Database

Sushma Naithani; Matthew Geniza; Pankaj Jaiswal

The goal of Gramene database ( www.gramene.org ) is to empower the plant research community in conducting comparative genomics studies across model plants and crops by employing a phylogenetic framework and orthology-based projections. Gramene database (release #49) provides resources for comparative plant genomics including well-annotated plant genomes (39 complete reference genomes and six partial genomes), genetic or structural variation data for 14 plant species, pathways for 58 plant species, and gene expression data for 14 species including Arabidopsis, rice, maize, soybean, wheat, etc. (fetched from EBI-EMBL Gene Expression Atlas database). Gramene also facilitates visualization and analysis of user-defined data in the context of species-specific Genome Browsers or pathways. This chapter describes basic navigation for Gramene users and illustrates how they can use the genome section to analyze the gene expression and nucleotide variation data generated in their labs. This includes (1) upload and display of genomic data onto a Genome Browser track, (2) analysis of variation data using online Variant Effect Predictor (VEP) tool for smaller data sets, and (3) the use of the stand-alone Perl scripts and command line protocols for variant effect prediction on larger data sets.


Integrative Biology | 2013

Integrated Experimental and Computational Approach to Understand the Effects of Heavy Ion Radiation on Skin Homeostasis.

Claere von Neubeck; Harish Shankaran; Matthew Geniza; Paula M. Kauer; R. Joe Robinson; William B. Chrisler; Marianne B. Sowa


Current Plant Biology | 2017

Tools for building de novo transcriptome assembly

Matthew Geniza; Pankaj Jaiswal


Archive | 2017

Exonerate_Alignments.tar.gz

Matthew Geniza; Samuel E. Fox; Sushma Naithani; Christopher M. Sullivan; Arnaud Kerhornou; Mamatha Hanumappa; Dan Bolser; Pankaj Jaiswal; Justin Elser; Gerard R. Lazo; Abagail Sage; Justin Preece; Paul Kersey; Fiona M. McCarthy; Jeffery M. Leonard; Cathy Gresham; Vijay K. Tiwari


Archive | 2014

Constructing a gene expression atlas of Chia (Salvia hispanica)

Jeremy Levi Phillips; Matthew Geniza; Ebaad Haq; Pankaj Jaiswal

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Justin Elser

Oregon State University

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Dan Bolser

European Bioinformatics Institute

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Cathy Gresham

Mississippi State University

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Gerard R. Lazo

Agricultural Research Service

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