Evolution and Selection of Quantitative Traits

Quantitative traits-be they morphological or physiological characters, aspects of behavior, or genome-level features such as the amount of RNA or protein expression for a specific gene-usually show considerable variation within and among populations. Quantitative genetics, also referred to as the genetics of complex traits, is the study of such characters and is based on mathematical models of evolution in which many genes influence the trait and in which non-genetic factors may also be important. Evolution and Selection of Quantitative Traits presents a holistic treatment of the subject, showing the interplay between theory and data with extensive discussions on statistical issues relating to the estimation of the biologically relevant parameters for these models. Quantitative genetics is viewed as the bridge between complex mathematical models of trait evolution and real-world data, and the authors have clearly framed their treatment as such. This is the second volume in a planned trilogy that summarizes the modern field of quantitative genetics, informed by empirical observations from wide-ranging fields (agriculture, evolution, ecology, and human biology) as well as population genetics, statistical theory, mathematical modeling, genetics, and genomics. Whilst volume 1 (1998) dealt with the genetics of such traits, the main focus of volume 2 is on their evolution, with a special emphasis on detecting selection (ranging from the use of genomic and historical data through to ecological field data) and examining its consequences.

Produktdetails

• Autoren: Michael Lynch, Lynch Michael, Bruce Walsh, Bruce (Professor Walsh, Walsh Bruce
• Verlag: Oxford University Press
• Sprache: Englisch
• Produktform: Fester Einband
• Erschienen: 12.07.2018
• EAN: 9780198830870
• ISBN: 978-0-19-883087-0
• Seiten: 1496
• Themen: Naturwissenschaften, Medizin, Informatik, Technik > Biologie > Allgemeines, Lexika; Evolution, SCIENCE / Life Sciences / Evolution, SCIENCE / Life Sciences / Biology, SCIENCE / Life Sciences / Genetics & Genomics, Biology, life sciences, Genetics (non-medical), Dna & Genome, Computational biology / bioinformatics