In recent years, single nucleotide polymorphisms have received increased and special attention in a rapidly developing field of personalized medicine and drug treatment. Comprising more than eighty percent of all known polymorphisms, single nucleotide polymorphisms (SNPs) are primarily responsible for phenotypic differences between individuals, and have been suggested to affect the development of diseases in humans and the response to drug treatment and environmental stress. In Single Nucleotide Polymorphisms: Methods and Protocols, Second Edition, expert researchers explore the latest advances in this area, highlighting the substantial progress that has been made in SNP genotyping, examining recent developments in high-throughput genotyping approaches, and exploring our new understanding of the impact of SNPs on gene function. Chapters address the impact of SNPs on phenotype, examine SNP databases, look at methods that have been applied for SNP bioinformatics discovery and analysis, and discuss advanced experimental approaches used for SNP detection. Composed in the highly successful Methods in Molecular BiologyTM series format, each chapter contains a brief introduction, step-by-step methods, a list of necessary materials, and a Notes section which shares tips on troubleshooting and avoiding known pitfalls. Current and innovative, Single Nucleotide Polymorphisms: Methods and Protocols, Second Edition is an essential guidebook for individual researchers as well as institutions and companies working in the field.

A comprehensive collection of readily reproducible techniques for the difficult process of single nucleotide polymorphisms (SNP) discovery and genotyping. These cutting-edge protocols for mutation/SNP detection utilize denaturing high-performance liquid chromatography (dHPLC), single-strand conformation polymorphism (SSCP), conformation-sensitive gel electrophoresis (CSGE), chemical cleavage, and direct sequencing. Equally powerful and up-to-date methods are given for genotyping SNPs, including molecular beacons, the Taqman assay, single-base extension approaches, pyrosequencing, ligation, the Invader assay, and primer extension with mass spectrometry detection.

For the past decade, there has been success in using conventional map-based strategies in identification and cloning of quantitative trait loci (QTL) in model plant species including tomato and Arabidopsis. These quantitative traits are generally the products of many loci with varying degrees of effect upon the observed phenotypes. Recently, a new approach to genetic mapping has emerged called association mapping. This new technique takes into account the thousands of genes to evaluate for QTL effect and is a more efficient approach that does not require generation of segregating populations/large numbers of progeny. As it can utilize all of the historic recombination events in a diverse population of individuals it can generate higher resolution genetic maps and, is needed to complement current map based cloning methods. Association Mapping in Plants provides both basic and advanced understanding of association mapping and an awareness of population genomics tools to facilitate mapping and identification of the underlying causes of quantitative trait variation in plants. It acts as a useful review of the marker technology, the statistical methodology, and the progress to date. It also offers guides to the use of single nucleotide polymorphisms (SNPs) in association studies. This book will appeal to all those with an interest in plant genetics, plant breeding, and plant genomics. About the Editors: Dr. Nnadozie C. Oraguzie is a Senior Scientist in Genetics at the Horticulture and Food Research Institute of New Zealand Ltd (HortResearch). Dr. Erik H. A. Rikkerink is a Science Leader at HortResearch, New Zealand. Dr. Susan E. Gardiner is a Principal Scientist and leader of the Gene Mapping research team at HortResearch, New Zealand. Dr. H. Nihal De Silva/STRONG is a Senior Scientist of Biometrics at HortResearch, New Zealand.

By any measure, the story of the Scottish National Party is an extraordinary one. Forced to endure decades of electoral irrelevance since its creation in the 1930s, during which it often found itself grappling with internal debate on strategy, and rebellion from within its own ranks, the SNP virtually swept the board in the 2015 general election, winning all but three of Scotland's fifty-nine seats in Westminster. What's more, under the current leadership of Nicola Sturgeon, the SNP has never been a more important force in the landscape of British politics. The leaders who have stood at its helm during this tumultuous eighty-year history - from Sir Alexander MacEwen to Nicola Sturgeon and Alex Salmond - have steered the SNP vessel with varying degrees of success, but there is no doubt that all have contributed to the shape, purpose and ultimate goal of the party of government we see today. The latest addition to the acclaimed British Political Leaders series, Scottish National Party Leaders examines each of these senior figures for the first time, and is essential reading for anyone curious about how this former fringe party evolved into a political phenomenon, changing not only the face of Scottish politics, but British politics as well.

Inhaltsangabe:Abstract: This work brings together two areas of science biology and informatics that have only recently been connected in the emerging (and vastly growing) research field of Bioinformatics. In order to achieve a common basis for Parts 2 and 3 of this work, Part 1 intends to introduce the computer scientist to the relevant biological background and terminology (Chapter 2), and to familiarize the biologist with the relevant topics from theoretical computer science (Chapter 3). Chapter 2 first introduces some terminology from the field of genetics, thereby defining SNPs. We then motivate the analysis of SNPs by two applications, i.e. the analysis of evolutionary development and the field of pharmacogenetics. Especially the field of pharmacogenetics is capable of having an enormous impact on medicine and the pharmaceutical industry in the near future by using SNP data to predict the efficacy of medication. Chapter 3 gives a brief introduction to the field of computational complexity. We will see and motivate how algorithms are analyzed in theoretical computer science. This will lead to the definition of complexity classes , introducing the class NP which includes computationally hard problems. Some of the hard problems in the class NP can be solved efficiently using the tool of fixed-parameter tractability, introduced at the end of this chapter. An important application of SNP data is in the analysis of the evolutionary history of species development (phylogenetic analysis part two chapters 4 and 5). As will be made plausible in Chapter 5 using SNP data is in many ways superior to previous approaches of phylogenetic analysis. In order to analyze the development of species using SNP data, an underlying model of evolution must be specified. A popular model is the so-called perfect phylogeny, but the construction of this phylogeny is a computationally hard problem when there are inconsistencies (such as read-errors or an imperfect .t to the model of perfect phylogeny) in the underlying data. Chapter 4 analyzes the problem of forbidden submatrix removal which is closely connected to constructing perfect phylogenies we will see in Chapter 5 that its computational complexity is directly related to that of constructing a perfect phylogeny from data which is partially erroneous. In this chapter, we analyze the algorithmic tractability of forbidden submatrix removal , characterizing cases where this problem is NP-complete (being [...]

Advances in Animal Genomics provides an outstanding collection of integrated strategies involving traditional and modern - omics (structural, functional, comparative and epigenomics) approaches and genomics-assisted breeding methods which animal biotechnologists can utilize to dissect and decode the molecular and gene regulatory networks involved in the complex quantitative yield and stress tolerance traits in livestock. Written by international experts on animal genomics, this book explores the recent advances in high-throughput, next-generation whole genome and transcriptome sequencing, array-based genotyping, and modern bioinformatics approaches which have enabled to produce huge genomic and transcriptomic resources globally on a genome-wide scale. This book is an important resource for researchers, students, educators and professionals in agriculture, veterinary and biotechnology sciences that enables them to solve problems regarding sustainable development with the help of current innovative biotechnologies. - Integrates basic and advanced concepts of animal biotechnology and presents future developments - Describes current high-throughput next-generation whole genome and transcriptome sequencing, array-based genotyping, and modern bioinformatics approaches for sustainable livestock production - Illustrates integrated strategies to dissect and decode the molecular and gene regulatory networks involved in complex quantitative yield and stress tolerance traits in livestock - Ensures readers will gain a strong grasp of biotechnology for sustainable livestock production with its well-illustrated discussion

Describes some of the developments in the field of Plant Genotyping, focusing on single nucleotide polymorphism (SNPs). This book covers the discovery, analysis and uses of SNPs, and examines other approaches to plant genotyping.