Life Sciences Commons^™

Promises And Challenges Of Eco-Physiological Genomics In The Field: Tests Of Drought Responses In Switchgrass. Plant Physiology, John T. Lovell, Eugene V. Shakirov, Scott Schwartz, David B. Lowry, Michael J. Aspinwall, Samuel H. Taylor, Jason Bonnette, Juan Diego Palacio-Mejia, Christine V. Hawkes, Philip A. Fay, Thomas E. Juenger

Yevgeniy (Eugene) Shakirov

Identifying the physiological and genetic basis of stress tolerance in plants has proven to be critical to understanding adaptation in both agricultural and natural systems. However, many discoveries were initially made in the controlled conditions of greenhouses or laboratories, not in the field. To test the comparability of drought responses across field and greenhouse environments, we undertook three independent experiments using the switchgrass reference genotype Alamo AP13. We analyzed physiological and gene expression variation across four locations, two sampling times, and three years. Relatively similar physiological responses and expression coefficients of variation across experiments masked highly dissimilar gene expression responses …

The Genomic Landscape Of Molecular Responses To Natural Drought Stress In Panicum Hallii., John T. Lovell, Jerry Jenkins, David B. Lowry, Sujan Mamidi, Avinash Sreedasyam, Xiaoyu Weng, Kerrie Barry, Jason Bonnette, Brandon Campitelli, Chris Daum, Sean P. Gordon, Billie A. Gould, Albina Khasanova, Anna Lipzen, Alice Macqueen, Juan Diego Palacio-Mejía, Christopher Plott, Eugene V. Shakirov, Shengqiang Shu, Yuko Yoshinaga, Matt Zane, Dave Kudrna, Jason D. Talag, Daniel Rokhsar, Jane Grimwood, Jeremy Schmutz, Thomas E. Juenger

Yevgeniy (Eugene) Shakirov

Environmental stress is a major driver of ecological community dynamics and agricultural productivity. This is especially true for soil water availability, because drought is the greatest abiotic inhibitor of worldwide crop yields. Here, we test the genetic basis of drought responses in the genetic model for C4 perennial grasses, Panicum hallii, through population genomics, field-scale gene-expression (eQTL) analysis, and comparison of two complete genomes. While gene expression networks are dominated by local cis-regulatory elements, we observe three genomic hotspots of unlinked trans-regulatory loci. These regulatory hubs are four times more drought responsive than the genome-wide average. Additionally, cis- and trans-regulatory …

Integrating Human Omics Data To Prioritize Candidate Genes., Yong Chen, Xuebing Wu, Rui Jiang

Yong Chen

BACKGROUND: The identification of genes involved in human complex diseases remains a great challenge in computational systems biology. Although methods have been developed to use disease phenotypic similarities with a protein-protein interaction network for the prioritization of candidate genes, other valuable omics data sources have been largely overlooked in these methods.

METHODS: With this understanding, we proposed a method called BRIDGE to prioritize candidate genes by integrating disease phenotypic similarities with such omics data as protein-protein interactions, gene sequence similarities, gene expression patterns, gene ontology annotations, and gene pathway memberships. BRIDGE utilizes a multiple regression model with lasso penalty to …

Genome-Wide Discovery Of Missing Genes In Biological Pathways Of Prokaryotes., Yong Chen, Fenglou Mao, Guojun Li, Ying Xu

Yong Chen

BACKGROUND: Reconstruction of biological pathways is typically done through mapping well-characterized pathways of model organisms to a target genome, through orthologous gene mapping. A limitation of such pathway-mapping approaches is that the mapped pathway models are constrained by the composition of the template pathways, e.g., some genes in a target pathway may not have corresponding genes in the template pathways, the so-called "missing gene" problem.

METHODS: We present a novel pathway-expansion method for identifying additional genes that are possibly involved in a target pathway after pathway mapping, to fill holes caused by missing genes as well as to expand the …

Tracing Evolutionary Footprints To Identify Novel Gene Functional Linkages., Yong Chen, Li Yang, Yunfeng Ding, Shuyan Zhang, Tong He, Fenglou Mao, Congyan Zhang, Huina Zhang, Chaoxing Huo, Pingsheng Liu

Yong Chen

Systematic determination of gene function is an essential step in fully understanding the precise contribution of each gene for the proper execution of molecular functions in the cell. Gene functional linkage is defined as to describe the relationship of a group of genes with similar functions. With thousands of genomes sequenced, there arises a great opportunity to utilize gene evolutionary information to identify gene functional linkages. To this end, we established a computational method (called TRACE) to trace gene footprints through a gene functional network constructed from 341 prokaryotic genomes. TRACE performance was validated and successfully tested to predict enzyme …

Integrated Omics Study Delineates The Dynamics Of Lipid Droplets In Rhodococcus Opacus Pd630., Yong Chen, Yunfeng Ding, Li Yang, Jinhai Yu, Guiming Liu, Xumin Wang, Shuyan Zhang, Dan Yu, Lai Song, Hangxiao Zhang, Congyan Zhang, Linhe Huo, Chaoxing Huo, Yang Wang, Yalan Du, Huina Zhang, Peng Zhang, Huimin Na, Shimeng Xu, Yaxin Zhu, Zhensheng Xie, Tong He, Yue Zhang, Guoliang Wang, Zhonghua Fan, Fuquan Yang, Honglei Liu, Xiaowo Wang, Xuegong Zhang, Michael Q Zhang, Yanda Li, Alexander Steinbüchel, Toyoshi Fujimoto, Simon Cichello, Jun Yu, Pingsheng Liu

Yong Chen

Rhodococcus opacus strain PD630 (R. opacus PD630), is an oleaginous bacterium, and also is one of few prokaryotic organisms that contain lipid droplets (LDs). LD is an important organelle for lipid storage but also intercellular communication regarding energy metabolism, and yet is a poorly understood cellular organelle. To understand the dynamics of LD using a simple model organism, we conducted a series of comprehensive omics studies of R. opacus PD630 including complete genome, transcriptome and proteome analysis. The genome of R. opacus PD630 encodes 8947 genes that are significantly enriched in the lipid transport, synthesis and metabolic, indicating a super …

The Efficacy Of Whole Human Genome Capture On Ancient Dental Calculus And Dentin, Kirsten A. Ziesemer, Jazmin Ramos-Madrigal, Allison E. Mann, Bernd W. Brandt, Krithivasan Sankaranarayanan, Andrew T. Ozga, Menno Hoogland, Courtney A. Hofman, Domingo C. Salazar-Garcia, Bruno Frohlich, George R. Miller, Anne C. Stone, Mark Aldenderfer, Cecil M. Lewis Jr., Corinne L. Hofman, Christina Warinner, Hannes Schroeder

Andrew Ozga

Objectives

Dental calculus is among the richest known sources of ancient DNA in the archaeological record. Although most DNA within calculus is microbial, it has been shown to contain sufficient human DNA for the targeted retrieval of whole mitochondrial genomes. Here, we explore whether calculus is also a viable substrate for whole human genome recovery using targeted enrichment techniques.

Materials and methods

Total DNA extracted from 24 paired archaeological human dentin and calculus samples was subjected to whole human genome enrichment using in‐solution hybridization capture and high‐throughput sequencing.

Results

Total DNA from calculus exceeded that of dentin in all cases, …

Saccharomyces Genome Database & Uniprot Bioinformatics Analysis, Ray A. Enke

Ray Enke Ph.D.

De-Identified Interviews For The Study: Data Challenges Of Biomedical Researchers In The Age Of Omics, Rolando Garcia-Milian, Denise Hersey, Milica Vukmirovic

Rolando Garcia-Milian

Genomic Approaches For Improvement Of Understudied Grasses, Keenan Amundsen, Gautam Sarath, Teresa Donze-Reiner

Teresa Donze-Reiner

No abstract provided.

Statistical Contributions To Bioinformatics: Design, Modeling, Structure Learning, And Integration, Jeffrey S. Morris, Veera Baladandayuthapani

Jeffrey S. Morris

Genomic Variants Associated With Cancer-Related Fatigue: A Systematic Review, Joseph D. Tariman Phd, Sadaf Dhorajiwala Msn

Joseph D Tariman PhD, RN, ANP-BC, FAAN

Making Sense Of Genomic Variation: Part 1 Snp Annotation, Rolando Garcia-Milian

Rolando Garcia-Milian

Functional Car Models For Spatially Correlated Functional Datasets, Lin Zhang, Veerabhadran Baladandayuthapani, Hongxiao Zhu, Keith A. Baggerly, Tadeusz Majewski, Bogdan Czerniak, Jeffrey S. Morris

Jeffrey S. Morris

We develop a functional conditional autoregressive (CAR) model for spatially correlated data for which functions are collected on areal units of a lattice. Our model performs functional response regression while accounting for spatial correlations with potentially nonseparable and nonstationary covariance structure, in both the space and functional domains. We show theoretically that our construction leads to a CAR model at each functional location, with spatial covariance parameters varying and borrowing strength across the functional domain. Using basis transformation strategies, the nonseparable spatial-functional model is computationally scalable to enormous functional datasets, generalizable to different basis functions, and can be used on …

Ordinal Probit Wavelet-Based Functional Models For Eqtl Analysis, Mark J. Meyer, Jeffrey S. Morris, Craig P. Hersh, Jarret D. Morrow, Christoph Lange, Brent A. Coull

Jeffrey S. Morris

Current methods for conducting expression Quantitative Trait Loci (eQTL) analysis are limited in scope to a pairwise association testing between a single nucleotide polymorphism (SNPs) and expression probe set in a region around a gene of interest, thus ignoring the inherent between-SNP correlation. To determine association, p-values are then typically adjusted using Plug-in False Discovery Rate. As many SNPs are interrogated in the region and multiple probe-sets taken, the current approach requires the fitting of a large number of models. We propose to remedy this by introducing a flexible function-on-scalar regression that models the genome as a functional outcome. The …

Open Consent, Biobanking And Data Protection Law: Can Open Consent Be ‘Informed’ Under The Forthcoming Data Protection Regulation?, Dara Hallinan, Michael Friedewald

Michael Friedewald

This article focuses on whether a certain form of consent used by biobanks – open consent – is compatible with the Proposed Data Protection Regulation. In an open consent procedure, the biobank requests consent once from the data subject for all future research uses of genetic material and data. However, as biobanks process personal data, they must comply with data protection law. Data protection law is currently undergoing reform. The Proposed Data Protection Regulation is the culmination of this reform and, if voted into law, will constitute a new legal framework for biobanking. The Regulation puts strict conditions on consent …

Bayesian Joint Selection Of Genes And Pathways: Applications In Multiple Myeloma Genomics, Lin Zhang, Jeffrey S. Morris, Jiexin Zhang, Robert Orlowski, Veerabhadran Baladandayuthapani

Jeffrey S. Morris

It is well-established that the development of a disease, especially cancer, is a complex process that results from the joint effects of multiple genes involved in various molecular signaling pathways. In this article, we propose methods to discover genes and molecular pathways significantly associ- ated with clinical outcomes in cancer samples. We exploit the natural hierarchal structure of genes related to a given pathway as a group of interacting genes to conduct selection of both pathways and genes. We posit the problem in a hierarchical structured variable selection (HSVS) framework to analyze the corresponding gene expression data. HSVS methods conduct …

Bayesian Methods For Expression-Based Integration, Elizabeth M. Jennings, Jeffrey S. Morris, Raymond J. Carroll, Ganiraju C. Manyam, Veera Baladandayuthapani

Jeffrey S. Morris

We propose methods to integrate data across several genomic platforms using a hierarchical Bayesian analysis framework that incorporates the biological relationships among the platforms to identify genes whose expression is related to clinical outcomes in cancer. This integrated approach combines information across all platforms, leading to increased statistical power in finding these predictive genes, and further provides mechanistic information about the manner in which the gene affects the outcome. We demonstrate the advantages of the shrinkage estimation used by this approach through a simulation, and finally, we apply our method to a Glioblastoma Multiforme dataset and identify several genes potentially …

Advanced Molecular Biologic Techniques In Toxicologic Disease, Jeanine Ward, Gyongyi Szabo, David Mcmanus, Edward Boyer

Gyongyi Szabo

The advancement of molecular biologic techniques and their capabilities to answer questions pertaining to mechanisms of pathophysiologic events have greatly expanded over the past few years. In particular, these opportunities have provided researchers and clinicians alike the framework from with which to answer clinical questions not amenable for elucidation using previous, more antiquated methods. Utilizing extremely small molecules, namely microRNA, DNA, protein, and nanoparticles, we discuss the background and utility of these approaches to the progressive, practicing physician. Finally, we consider the application of these tools employed as future bedside point of care tests, aiding in the ultimate goal of …

Using Comparative Genomics For Inquiry-Based Learning To Dissect Virulence Of Escherichia Coli O157:H7 And Yersinia Pestis, David J. Baumler, Lois M. Banta, Kai F. Hung, Jodi A. Schwarz, Eric L. Cabot, Jeremy D. Glasner, Nicole T. Perna

Kai F. Hung

Genomics and bioinformatics are topics of increasing interest in undergraduate biological science curricula. Many existing exercises focus on gene annotation and analysis of a single genome. In this paper, we present two educational modules designed to enable students to learn and apply fundamental concepts in comparative genomics using examples related to bacterial pathogenesis. Students first examine alignments of genomes of Escherichia coli O157:H7 strains isolated from three food-poisoning outbreaks using the multiple-genome alignment tool Mauve. Students investigate conservation of virulence factors using the Mauve viewer and by browsing annotations available at the A Systematic Annotation Package for Community Analysis of …

Integrative Bayesian Analysis Of High-Dimensional Multi-Platform Genomics Data, Wenting Wang, Veerabhadran Baladandayuthapani, Jeffrey S. Morris, Bradley M. Broom, Ganiraju C. Manyam, Kim-Anh Do

Jeffrey S. Morris

Motivation: Analyzing data from multi-platform genomics experiments combined with patients’ clinical outcomes helps us understand the complex biological processes that characterize a disease, as well as how these processes relate to the development of the disease. Current integration approaches that treat the data are limited in that they do not consider the fundamental biological relationships that exist among the data from platforms.

Statistical Model: We propose an integrative Bayesian analysis of genomics data (iBAG) framework for identifying important genes/biomarkers that are associated with clinical outcome. This framework uses a hierarchical modeling technique to combine the data obtained from multiple platforms …

Boesenbergia Rotunda: From Ethnomedicine To Drug Discovery, Norzulaani Khalid

Norzulaani Khalid

Boesenbergia rotunda is a herb from the Boesenbergia genera under the Zingiberaceae family. B. rotunda is widely found in Asian countries where it is commonly used as a food ingredient and in ethnomedicinal preparations. The popularity of its ethnomedicinal usage has drawn the attention of scientists worldwide to further investigate its medicinal properties. Advancement in drug design and discovery research has led to the development of synthetic drugs from B. rotunda metabolites via bioinformatics and medicinal chemistry studies. Furthermore, with the advent of genomics, transcriptomics, proteomics, and metabolomics, new insights on the biosynthetic pathways of B. rotunda metabolites can be …

Detecting Microrna Activity From Gene Expression Data, Stephen F. Madden, Susan B. Carpenter, Ian B. Jeffery, Harry Bjorkbacka, Katherine A. Fitzgerald, Luke A. J. O'Neill, Desmond G. Higgins

Katherine A. Fitzgerald

BACKGROUND: MicroRNAs (miRNAs) are non-coding RNAs that regulate gene expression by binding to the messenger RNA (mRNA) of protein coding genes. They control gene expression by either inhibiting translation or inducing mRNA degradation. A number of computational techniques have been developed to identify the targets of miRNAs. In this study we used predicted miRNA-gene interactions to analyse mRNA gene expression microarray data to predict miRNAs associated with particular diseases or conditions.

RESULTS: Here we combine correspondence analysis, between group analysis and co-inertia analysis (CIA) to determine which miRNAs are associated with differences in gene expression levels in microarray data sets. …

Niche Of Harmful Alga Aureococcus Anophagefferens Revealed Through Ecogenomics, Christopher Gobler, Dianna Berry, Sonya Dyhrman, Steven Wilhelm

Steven Wilhelm

Harmful algal blooms (HABs) cause significant economic and ecological damage worldwide. Despite considerable efforts, a comprehensive understanding of the factors that promote these blooms has been lacking, because the biochemical pathways that facilitate their dominance relative to other phytoplankton within specific environments have not been identified. Here, biogeochemical measurements showed that the harmful alga Aureococcus anophagefferens outcompeted co-occurring phytoplankton in estuaries with elevated levels of dissolved organic matter and turbidity and low levels of dissolved inorganic nitrogen. We subsequently sequenced the genome of A. anophagefferens and compared its gene complement with those of six competing phytoplankton species identified through metaproteomics. …

Nature 2011 Ngs Review, Elaine Mardis

Ray Enke Ph.D.

Members’ Discoveries: Fatal Flaws In Cancer Research, Jeffrey S. Morris

Jeffrey S. Morris

A recent article published in The Annals of Applied Statistics (AOAS) by two MD Anderson researchers—Keith Baggerly and Kevin Coombes—dissects results from a highly-influential series of medical papers involving genomics-driven personalized cancer therapy, and outlines a series of simple yet fatal flaws that raises serious questions about the veracity of the original results. Having immediate and strong impact, this paper, along with related work, is providing the impetus for new standards of reproducibility in scientific research.

Statistical Contributions To Proteomic Research, Jeffrey S. Morris, Keith A. Baggerly, Howard B. Gutstein, Kevin R. Coombes

Jeffrey S. Morris

Proteomic profiling has the potential to impact the diagnosis, prognosis, and treatment of various diseases. A number of different proteomic technologies are available that allow us to look at many proteins at once, and all of them yield complex data that raise significant quantitative challenges. Inadequate attention to these quantitative issues can prevent these studies from achieving their desired goals, and can even lead to invalid results. In this chapter, we describe various ways the involvement of statisticians or other quantitative scientists in the study team can contribute to the success of proteomic research, and we outline some of the …

Bayesian Random Segmentationmodels To Identify Shared Copy Number Aberrations For Array Cgh Data, Veerabhadran Baladandayuthapani, Yuan Ji, Rajesh Talluri, Luis E. Nieto-Barajas, Jeffrey S. Morris

Jeffrey S. Morris

Array-based comparative genomic hybridization (aCGH) is a high-resolution high-throughput technique for studying the genetic basis of cancer. The resulting data consists of log fluorescence ratios as a function of the genomic DNA location and provides a cytogenetic representation of the relative DNA copy number variation. Analysis of such data typically involves estimation of the underlying copy number state at each location and segmenting regions of DNA with similar copy number states. Most current methods proceed by modeling a single sample/array at a time, and thus fail to borrow strength across multiple samples to infer shared regions of copy number aberrations. …

Detecting Outlier Genes From High-Dimensional Data: A Fuzzy Approach, Debashis Ghosh

Debashis Ghosh

A recent nding in cancer research has been the characterization of previously undis- covered chromosomal abnormalities in several types of solid tumors. This was found based on analyses of high-throughput data from gene expression microarrays and motivated the development of so-called `outlier' tests for dierential expression. One statistical issue was the potential discreteness of the test statistics. Using ideas from fuzzy set theory, we develop fuzzy outlier detection algorithms that have links to ideas in multiple comparisons. Two- and K-sample extensions are considered. The methodology is illustrated by application to two microarray studies.

Data Sharing, Latency Variables And The Science Commons, Jorge L. Contreras

Jorge L Contreras

Over the past decade, the rapidly decreasing cost of computer storage and the increasing prevalence of high-speed Internet connections have fundamentally altered the way in which scientific research is conducted. Led by scientists in disciplines such as genomics, the rapid sharing of data sets and cross-institutional collaboration promise to increase scientific efficiency and output dramatically. As a result, an increasing number of public “commons” of scientific data are being created: aggregations intended to be used and accessed by researchers worldwide. Yet, the sharing of scientific data presents legal, ethical and practical challenges that must be overcome before such science commons …