The Edinburgh mouse atlas and gene-expression database: a spatio-temporal database for biological research

2003 ◽  
Author(s):  
A. Burger ◽  
R. Baldock ◽  
Yiya Yang ◽  
A. Waterhouse ◽  
D. Houghton ◽  
...  
Keyword(s):  
Gene Expression ◽  
Biological Research ◽  
Gene Expression Database ◽  
Temporal Database ◽  
Mouse Atlas ◽  
Spatio Temporal

The mouse atlas and graphical gene-expression database

1997 ◽  
Vol 8 (5) ◽  
pp. 509-517 ◽  
Author(s):  
D. Davidson ◽  
J. Bard ◽  
R. Brune ◽  
A. Burger ◽  
C. Dubreuil ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Database ◽  
Mouse Atlas

Establishing Standard Protocols for Bacterial Culture in Biological Research in Canisters (BRIC) Hardware

2020 ◽  
Vol 4 (2) ◽  
pp. 58-69 ◽  
Author(s):  
Patricia Fajardo-Cavazos ◽  
Wayne L. Nicholson
Keyword(s):  
Gene Expression ◽  
Bacterial Culture ◽  
Culture Conditions ◽  
Media Culture ◽  
Ground Control ◽  
Biological Research ◽  
Confounding Factors ◽  
Cross Experiment ◽  
Spaceflight Experiments ◽  
Control Samples

AbstractThe NASA GeneLab Data System (GLDS) was recently developed to facilitate cross-experiment comparisons in order to understand the response of microorganisms to the human spaceflight environment. However, prior spaceflight experiments have been conducted using a wide variety of different hardware, media, culture conditions, and procedures. Such confounding factors could potentially mask true differences in gene expression between spaceflight and ground control samples. In an attempt to mitigate such confounding factors, we describe here the development of a standardized set of hardware, media, and protocols for liquid cultivation of microbes in Biological Research in Canisters (BRIC) spaceflight hardware, using the model bacteria Bacillus subtilis strain 168 and Staphylococcus aureus strain UAMS-1 as examples.

scholarly journals Spatio-temporal selection of reference genes in the two congeneric species of Glycyrrhiza

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yuping Li ◽  
Xiaoju Liang ◽  
Xuguo Zhou ◽  
Yu An ◽  
Ming Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Developmental Stage ◽  
Reference Genes ◽  
Developmental Stages ◽  
Individual Factors ◽  
Congeneric Species ◽  
Spatio Temporal ◽  
The Stability ◽  
Different Tissues ◽  
Selection Of

AbstractGlycyrrhiza, a genus of perennial medicinal herbs, has been traditionally used to treat human diseases, including respiratory disorders. Functional analysis of genes involved in the synthesis, accumulation, and degradation of bioactive compounds in these medicinal plants requires accurate measurement of their expression profiles. Reverse transcription quantitative real-time PCR (RT-qPCR) is a primary tool, which requires stably expressed reference genes to serve as the internal references to normalize the target gene expression. In this study, the stability of 14 candidate reference genes from the two congeneric species G. uralensis and G. inflata, including ACT, CAC, CYP, DNAJ, DREB, EF1, RAN, TIF1, TUB, UBC2, ABCC2, COPS3, CS, R3HDM2, were evaluated across different tissues and throughout various developmental stages. More importantly, we investigated the impact of interactions between tissue and developmental stage on the performance of candidate reference genes. Four algorithms, including geNorm, NormFinder, BestKeeper, and Delta Ct, were used to analyze the expression stability and RefFinder, a comprehensive software, provided the final recommendation. Based on previous research and our preliminary data, we hypothesized that internal references for spatio-temporal gene expression are different from the reference genes suited for individual factors. In G. uralensis, the top three most stable reference genes across different tissues were R3HDM2, CAC and TUB, while CAC, CYP and ABCC2 were most suited for different developmental stages. CAC is the only candidate recommended for both biotic factors, which is reflected in the stability ranking for the spatio (tissue)-temporal (developmental stage) interactions (CAC, R3HDM2 and DNAJ). Similarly, in G. inflata, COPS3, R3HDM2 and DREB were selected for tissues, while RAN, COPS3 and CS were recommended for developmental stages. For the tissue-developmental stage interactions, COPS3, DREB and ABCC2 were the most suited reference genes. In both species, only one of the top three candidates was shared between the individual factors and their interactions, specifically, CAC in G. uralensis and COPS3 in G. inflata, which supports our overarching hypothesis. In summary, spatio-temporal selection of reference genes not only lays the foundation for functional genomics research in Glycyrrhiza, but also facilitates these traditional medicinal herbs to reach/maximize their pharmaceutical potential.

scholarly journals Genome Wide Analysis of the Transcriptional Profiles in Different Regions of the Developing Rice Grains

Rice ◽  
2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Ting-Ying Wu ◽  
Marlen Müller ◽  
Wilhelm Gruissem ◽  
Navreet K. Bhullar
Keyword(s):  
Gene Expression ◽  
Dna Sequence ◽  
Expression Patterns ◽  
Grain Filling ◽  
Aleurone Layer ◽  
Rice Grain ◽  
Sequence Motifs ◽  
Grain Development ◽  
Spatio Temporal ◽  
Dna Sequence Motifs

Abstract Background Rice is an important food source for humans worldwide. Because of its nutritional and agricultural significance, a number of studies addressed various aspects of rice grain development and grain filling. Nevertheless, the molecular processes underlying grain filling and development, and in particular the contributions of different grain tissues to these processes, are not understood. Main Text Using RNA-sequencing, we profiled gene expression activity in grain tissues comprised of cross cells (CC), the nucellar epidermis (NE), ovular vascular trace (OVT), endosperm (EN) and the aleurone layer (AL). These tissues were dissected using laser capture microdissection (LCM) at three distinct grain development stages. The mRNA expression datasets offer comprehensive and new insights into the gene expression patterns in different rice grain tissues and their contributions to grain development. Comparative analysis of the different tissues revealed their similar and/or unique functions, as well as the spatio-temporal regulation of common and tissue-specific genes. The expression patterns of genes encoding hormones and transporters indicate an important role of the OVT tissue in metabolite transport during grain development. Gene co-expression network prediction on OVT-specific genes identified several distinct and common development-specific transcription factors. Further analysis of enriched DNA sequence motifs proximal to OVT-specific genes revealed known and novel DNA sequence motifs relevant to rice grain development. Conclusion Together, the dataset of gene expression in rice grain tissues is a novel and useful resource for further work to dissect the molecular and metabolic processes during rice grain development.

Computational Strategies for Analyzing Data in Gene Expression Microarray Experiments

2003 ◽  
Vol 01 (03) ◽  
pp. 541-586 ◽  
Author(s):  
Tero Aittokallio ◽  
Markus Kurki ◽  
Olli Nevalainen ◽  
Tuomas Nikula ◽  
Anne West ◽  
...  
Keyword(s):  
Gene Expression ◽  
Data Analysis ◽  
Microarray Data ◽  
Microarray Data Analysis ◽  
Biological Research ◽  
Microarray Experiments ◽  
Dna Microarray Data ◽  
Open Questions ◽  
Analysis Technique ◽  
Wide Range

Microarray analysis has become a widely used method for generating gene expression data on a genomic scale. Microarrays have been enthusiastically applied in many fields of biological research, even though several open questions remain about the analysis of such data. A wide range of approaches are available for computational analysis, but no general consensus exists as to standard for microarray data analysis protocol. Consequently, the choice of data analysis technique is a crucial element depending both on the data and on the goals of the experiment. Therefore, basic understanding of bioinformatics is required for optimal experimental design and meaningful interpretation of the results. This review summarizes some of the common themes in DNA microarray data analysis, including data normalization and detection of differential expression. Algorithms are demonstrated by analyzing cDNA microarray data from an experiment monitoring gene expression in T helper cells. Several computational biology strategies, along with their relative merits, are overviewed and potential areas for additional research discussed. The goal of the review is to provide a computational framework for applying and evaluating such bioinformatics strategies. Solid knowledge of microarray informatics contributes to the implementation of more efficient computational protocols for the given data obtained through microarray experiments.

scholarly journals Genome expression dynamics reveals parasitism regulatory landscape of the root-knot nematode Meloidogyne incognita and a promoter motif associated with effector genes

2021 ◽  
Author(s):  
Martine Da Rocha ◽  
Caroline Bournaud ◽  
Julie Dazeniere ◽  
Peter Thorpe ◽  
Clement Pellegrin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Meloidogyne Incognita ◽  
Life Stage ◽  
Regulation Of Gene Expression ◽  
Root Knot Nematode ◽  
Root Knot Nematodes ◽  
Control Of Gene Expression ◽  
Precise Control ◽  
Effector Genes ◽  
Spatio Temporal

Root-knot nematodes are the major contributor to the crop losses caused by nematodes. Root-knot nematodes secrete effectors into the plant, derived from two sets of pharyngeal gland cells, to manipulate host physiology and immunity. Successful completion of the life cycle, involving successive molts from egg to adult, covers morphologically and functionally distinct stages and will require precise control of gene expression, including effectors. The details of how root-knot nematodes regulate transcription remain sparse. Here, we report a life stage-specific transcriptome of Meloidogyne incognita. Combined with an available annotated genome, we explore the spatio-temporal regulation of gene expression. We reveal gene expression clusters and predicted functions that accompany the major developmental transitions. Focusing on effectors, we identify a putative cis-regulatory motif associated with expression in the dorsal glands: providing an insight into effector regulation. We combine the presence of this motif with several other criteria to predict a novel set of putative dorsal gland effectors. Finally, we show this motif, and thereby its utility, is broadly conserved across the Meloidogyne genus and termed it Mel-DOG. Taken together, we provide the first genome-wide analysis of spatio-temporal gene expression in a root-knot nematode, and identify a new set of candidate effector genes that will guide future functional analyses.

scholarly journals Bioinformatics in otolaryngology research. Part one: concepts in DNA sequencing and gene expression analysis

2014 ◽  
Vol 128 (10) ◽  
pp. 848-858 ◽  
Author(s):  
T J Ow ◽  
K Upadhyay ◽  
T J Belbin ◽  
M B Prystowsky ◽  
H Ostrer ◽  
...  
Keyword(s):  
Gene Expression ◽  
Data Storage ◽  
Expression Analysis ◽  
High Throughput ◽  
Gene Expression Analysis ◽  
Biological Data ◽  
Biological Research ◽  
Nucleotide Sequencing ◽  
New Era ◽  
Crucial Component

AbstractBackground:Advances in high-throughput molecular biology, genomics and epigenetics, coupled with exponential increases in computing power and data storage, have led to a new era in biological research and information. Bioinformatics, the discipline devoted to storing, analysing and interpreting large volumes of biological data, has become a crucial component of modern biomedical research. Research in otolaryngology has evolved along with these advances.Objectives:This review highlights several modern high-throughput research methods, and focuses on the bioinformatics principles necessary to carry out such studies. Several examples from recent literature pertinent to otolaryngology are provided. The review is divided into two parts; this first part discusses the bioinformatics approaches applied in nucleotide sequencing and gene expression analysis.Conclusion:This paper demonstrates how high-throughput nucleotide sequencing and transcriptomics are changing biology and medicine, and describes how these changes are affecting otorhinolaryngology. Sound bioinformatics approaches are required to obtain useful information from the vast new sources of data.

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