Statistical Genetics of Quantitative Traits

Statistical Genetics of Quantitative Traits

EnglishHardback
Wu Rongling
Springer-Verlag New York Inc.
EAN: 9780387203348
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Detailed information

Most traits in nature and of importance to agriculture are quantitatively inherited. These traits are di?cult to study due to the complex nature of their inheritance. However, recent developments of genomic technologies provide a revolutionary means for unraveling the secrets of genetic variation in quantitative traits. Genomic te- nologies allow the molecular characterization of polymorphic markers throughout the entire genome that are then used to identify and map the genes or quantitative trait loci (QTLs) underlying a quantitative trait based on linkage analysis. Statistical analysis is a crucial tool for analyzing genome data, which are now becoming increasingly available for a variety of species, and for giving precise exp- nations regarding genetic variation in quantitative traits occurring among species, populations, families, and individuals. In 1989, Lander and Botstein published a ha- mark methodological paper for interval mapping that enables geneticists to detect and estimate individual QTL that control the phenotype of a trait. Today, interval mappingisanimportantstatisticaltoolforstudyingthegeneticsofquantitativetraits at the molecular level, and has led to the discovery of thousands of QTLs responsible for a variety of traits in plants, animals, and humans. In a recent study published in Science, Li, Zhou, and Sang (2006, 311, 1936–1939) were able to characterize the molecular basis of the reduction of grain shattering – a fundamental selection process for rice domestication – at the detected QTL by interval mapping.
EAN 9780387203348
ISBN 0387203346
Binding Hardback
Publisher Springer-Verlag New York Inc.
Publication date July 31, 2007
Pages 368
Language English
Dimensions 235 x 155
Country United States
Readership Professional & Scholarly
Authors Casella George; Ma Changxing; Wu Rongling
Illustrations XVI, 368 p.
Edition 2007 ed.
Series Statistics for Biology and Health