Seed genomics: germinating opportunities

2002 ◽  
Vol 12 (3) ◽  
pp. 145-153 ◽  
Author(s):  
A. (Lonneke) ◽  
H.M. van der Geest
Keyword(s):  
High Throughput ◽  
Large Scale ◽  
Plant Biology ◽  
Sequence Information ◽  
Molecular Tools ◽  
Seed Biology ◽  
Physiological Processes ◽  
Large Scale Analysis ◽  
Quantum Leap ◽  
Mutant Phenotypes

With the sequencing of theArabidopsis thalianagenome, the field of plant biology has made a quantum leap. The sequence information available to the community has greatly facilitated the identification of genes responsible for mutant phenotypes and the large-scale analysis of gene expression inArabidopsis. High-throughput laboratory tools for DNA sequencing (genomics), mutant analysis (functional genomics), mRNA quantification (transcriptomics) and protein analysis (proteomics) are being used to scrutinize this model plant. For seed physiologists, the challenge lies in translating this information into physiological processes in seeds from other plant species. Combining more traditional seed biology with the new high-throughput molecular tools should yield breakthroughs in seed science.

scholarly journals Advances in Development of New Treatment for Leishmaniasis

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Juliana Perrone Bezerra de Menezes ◽  
Carlos Eduardo Sampaio Guedes ◽  
Antônio Luis de Oliveira Almeida Petersen ◽  
Deborah Bittencourt Mothé Fraga ◽  
Patrícia Sampaio Tavares Veras
Keyword(s):  
High Throughput ◽  
Drug Targets ◽  
Scientific Community ◽  
Large Scale ◽  
High Throughput Analysis ◽  
Large Scale Analysis ◽  
Parasite Biology ◽  
New Treatment ◽  
Novel Drug ◽  
Chemotherapeutic Interventions

Leishmaniasis is a neglected infectious disease caused by several different species of protozoan parasites of the genusLeishmania. Current strategies to control this disease are mainly based on chemotherapy. Despite being available for the last 70 years, leishmanial chemotherapy has lack of efficiency, since its route of administration is difficult and it can cause serious side effects, which results in the emergence of resistant cases. The medical-scientific community is facing difficulties to overcome these problems with new suitable and efficient drugs, as well as the identification of new drug targets. The availability of the complete genome sequence ofLeishmaniahas given the scientific community the possibility of large-scale analysis, which may lead to better understanding of parasite biology and consequent identification of novel drug targets. In this review we focus on how high-throughput analysis is helping us and other groups to identify novel targets for chemotherapeutic interventions. We further discuss recent data produced by our group regarding the use of the high-throughput techniques and how this helped us to identify and assess the potential of new identified targets.

Large‐Scale Analysis of 73 329 Physcomitrella Plants Transformed with Different Gene Disruption Libraries: Production Parameters and Mutant Phenotypes

Plant Biology ◽  
2005 ◽  
Vol 7 (3) ◽  
pp. 228-237 ◽  
Author(s):  
G. Schween ◽  
T. Egener ◽  
D. Fritzowsky ◽  
J. Granado ◽  
M.‐C. Guitton ◽  
...  
Keyword(s):  
Gene Disruption ◽  
Large Scale ◽  
Scale Analysis ◽  
Production Parameters ◽  
Large Scale Analysis ◽  
Mutant Phenotypes

scholarly journals Enabling Large-Scale Pharmacogenetic Studies by High-Throughput Mutation Detection and Genotyping Technologies

2001 ◽  
Vol 47 (2) ◽  
pp. 164-172 ◽  
Author(s):  
Michael M Shi
Keyword(s):  
Genetic Polymorphisms ◽  
High Throughput ◽  
Large Scale ◽  
Mutation Detection ◽  
Mutation Screening ◽  
Sequence Information ◽  
Polymorphism Analysis ◽  
Vast Number ◽  
Individual Variations ◽  
Oligonucleotide Ligation Assay

Abstract Background: Pharmacogenetics is a scientific discipline that examines the genetic basis for individual variations in response to therapeutics. Pharmacogenetics promises to develop individualized medicines tailored to patients’ genotypes. However, identifying and genotyping a vast number of genetic polymorphisms in large populations also pose a great challenge. Approach: This article reviews the recent technology development in mutation detection and genotyping with a focus on genotyping of single nucleotide polymorphisms (SNPs). Content: Novel mutations/polymorphisms are commonly identified by conformation-based mutation screening and direct high-throughput heterozygote sequencing. With a large amount of public sequence information available, in silico SNP mapping has also emerged as a cost-efficient way for new polymorphism identification. Gel electrophoresis-based genotyping methods for known polymorphisms include PCR coupled with restriction fragment length polymorphism analysis, multiplex PCR, oligonucleotide ligation assay, and minisequencing. Fluorescent dye-based genotyping technologies are emerging as high-throughput genotyping platforms, including oligonucleotide ligation assay, pyrosequencing, single-base extension with fluorescence detection, homogeneous solution hybridization such as TaqMan®, and molecular beacon genotyping. Rolling circle amplification and InvaderTM assays are able to genotype directly from genomic DNA without PCR amplification. DNA chip-based microarray and mass spectrometry genotyping technologies are the latest development in the genotyping arena. Summary: Large-scale genotyping is crucial to the identification of the genetic make-ups that underlie the onset of diseases and individual variations in drug responses. Enabling technologies to identify genetic polymorphisms rapidly, accurately, and cost effectively will dramatically impact future drug and development processes.

DNA microarrays: a bridge between genome sequence information and biological understanding

2002 ◽  
Vol 10 (3) ◽  
pp. 389-408 ◽  
Author(s):  
KEITH HARSHMAN ◽  
CARLOS MARTÍNEZ-A
Keyword(s):  
Large Scale ◽  
Dna Microarrays ◽  
Expression Patterns ◽  
Dna Polymorphisms ◽  
Model Organisms ◽  
Sequence Information ◽  
Single Experiment ◽  
Cellular Processes ◽  
Large Scale Analysis ◽  
Sequence Variations

The development, refinement and increasingly widespread use of DNA microarrays have been important responses to the explosion of sequence information produced by genome science. The high sample densities possible with DNA microarrays, coupled with the complete or nearly complete genome sequences available for humans and model organisms, provide a powerful analytical method to measure both qualitative and quantitative variations in RNA and DNA. Principal among the applications of microarrays is the large-scale analysis of RNA expression, often referred to as expression profiling. The power of this application lies in its ability to determine the expression patterns of tens of thousands of genes in a single experiment. Additionally, the ability to detect DNA polymorphisms makes microarrays useful in studies designed to correlate DNA sequence variations with variations in phenotype. The unprecedented scale on which microarrays allow both experimentation and generation of results should make possible a more complete and comprehensive understanding of cells and cellular processes.

scholarly journals Using the antibody-antigen binding interface to train image-based deep neural networks for antibody-epitope classification

2021 ◽  
Vol 17 (3) ◽  
pp. e1008864
Author(s):  
Daniel R. Ripoll ◽  
Sidhartha Chaudhury ◽  
Anders Wallqvist
Keyword(s):  
Neural Networks ◽  
B Cell ◽  
High Throughput ◽  
Large Scale ◽  
Deep Neural Networks ◽  
Viral Infections ◽  
Adaptive Immune Response ◽  
Sequence Information ◽  
Data Generation ◽  
Binding Interface

High-throughput B-cell sequencing has opened up new avenues for investigating complex mechanisms underlying our adaptive immune response. These technological advances drive data generation and the need to mine and analyze the information contained in these large datasets, in particular the identification of therapeutic antibodies (Abs) or those associated with disease exposure and protection. Here, we describe our efforts to use artificial intelligence (AI)-based image-analyses for prospective classification of Abs based solely on sequence information. We hypothesized that Abs recognizing the same part of an antigen share a limited set of features at the binding interface, and that the binding site regions of these Abs share share common structure and physicochemical property patterns that can serve as a “fingerprint” to recognize uncharacterized Abs. We combined large-scale sequence-based protein-structure predictions to generate ensembles of 3-D Ab models, reduced the Ab binding interface to a 2-D image (fingerprint), used pre-trained convolutional neural networks to extract features, and trained deep neural networks (DNNs) to classify Abs. We evaluated this approach using Ab sequences derived from human HIV and Ebola viral infections to differentiate between two Abs, Abs belonging to specific B-cell family lineages, and Abs with different epitope preferences. In addition, we explored a different type of DNN method to detect one class of Abs from a larger pool of Abs. Testing on Ab sets that had been kept aside during model training, we achieved average prediction accuracies ranging from 71–96% depending on the complexity of the classification task. The high level of accuracies reached during these classification tests suggests that the DNN models were able to learn a series of structural patterns shared by Abs belonging to the same class. The developed methodology provides a means to apply AI-based image recognition techniques to analyze high-throughput B-cell sequencing datasets (repertoires) for Ab classification.

scholarly journals TIMPs of parasitic helminths – a large-scale analysis of high-throughput sequence datasets

2013 ◽  
Vol 6 (1) ◽  
Author(s):  
Cinzia Cantacessi ◽  
Andreas Hofmann ◽  
Darren Pickering ◽  
Severine Navarro ◽  
Makedonka Mitreva ◽  
...  
Keyword(s):  
High Throughput ◽  
Large Scale ◽  
Scale Analysis ◽  
Parasitic Helminths ◽  
Large Scale Analysis
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