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Evolutionary quantitative genetics (EQG) provides a formal theoretical foundation for quantitatively linking natural selection and genetic variation to the rate and expanse of adaptive evolution. It has become the dominant conceptual framework for interpreting the evolution of quantitative traits in terms of elementary forces (mutation, inheritance, selection, and drift). Despite this success, the relevance of EQG to many biological scenarios remains relatively unappreciated, with numerous fields yet to fully embrace its approach. Part of the reason for this lag is that conceptual advances in EQG have not yet been fully synthesized and made accessible to a wider academic audience. A comprehensive, accessible overview is therefore now timely, and Evolutionary Quantitative Genetics provides this much-needed synthesis. The central argument of the book is that an adaptive landscape concept can be used to understand both evolutionary process within lineages and the pattern of adaptive radiations. In particular, it provides a convincing argument that models with a moving adaptive peak carry us further than any other conceptual approach yet devised. Although additive theory holds center stage, the book mentions and references departures from additivity including non-Gaussian distributions of allelic effects, dominance, epistasis, maternal effects and phenotypic plasticity. This accessible, advanced textbook is aimed principally at students (from senior undergraduate to postgraduate) as well as practising scientists in the fields of evolutionary biology, ecology, physiology, functional morphology, developmental biology, comparative biology, paleontology, and beyond who are interested in how adaptive radiations are produced by evolutionary and ecological processes.

Biometrics and statistics have become integral to the understanding of genetics and plant breeding experiments. It is important to gain knowledge of these aspects for expertise in practical applications of life sciences and to excel in competitive examinations. This book covers ARS (Agricultural and Research Scientist)and SRF (Senior Research Fellow) syllabus on statistical and biometrical concepts in genetics and plant breeding, prescribed by ICAR. It is written in simple question-answer pattern for easy and quick comprehension of the subject, followed by multiple choice section for self-evaluation. This book is envisaged to facilitate preparations for competitive examinations like ICAR NET/ARS, JRF, SRF, CSIR NET/JRF.

A Primer of Population Genetics and Genomics has been completely revised and updated to provide a concise but comprehensive introduction to the basic concepts of population genetics and genomics. Recent textbooks have tended to focus on such specialized topics as the coalescent, molecular evolution, human population genetics, or genomics. This primer bucks that trend by encouraging a broader familiarity with, and understanding of, population genetics and genomics as a whole. The overview ranges from mating systems through the causes of evolution, molecular population genetics, and the genomics of complex traits. Interwoven are discussions of ancient DNA, gene drive, landscape genetics, identifying risk factors for complex diseases, the genomics of adaptation and speciation, and other active areas of current research. The principles are illuminated by numerous examples from a wide variety of animals, plants, microbes, and human populations. The approach also emphasizes learning by doing, which in this case means solving numerical or conceptual problems. The rationale behind this is that the use of concepts in problem-solving lead to deeper understanding and longer knowledge retention. This accessible, introductory textbook is aimed principally at students of various levels and abilities (from senior undergraduate to postgraduate) as well as practising scientists in the fields of population genetics, ecology, evolutionary biology, computational biology, bioinformatics, biostatistics, physics, and mathematics.

Since the first edition of this book was published in 2002, the field of quantitative genetics, genomics and breeding has changed markedly. In response, only four chapters have been updated for this new edition, and the remaining 16 chapters are entirely new. This book presents state-of-the-art, authoritative chapters on contemporary issues in the broad areas of quantitative genetics, genomics and plant breeding. Section 1 (Chapters 2 to 12) emphasizes the application of genomics, and genome and epigenome editing techniques, in plant breeding; bioinformatics; quantitative trait loci mapping; and the latest approaches of examining and exploiting genotype-environment interactions. Section 2 (Chapters 13 to 20) represents the intersection of breeding, genetics and genomics. This section describes the use of cutting-edge molecular breeding and quantitative genetics techniques in wheat, rice, maize, root and tuber crops and pearl millet. Overall, the book focuses on using genomic information to help evaluate traits that can combat biotic/abiotic stresses, genome-wide association mapping, high-throughput genotyping/phenotyping, biofortification, use of big data, orphan crops, and gene editing techniques. The examples featured are taken from across crop science research and cover a wide geographical base. This book contains: chapters by expert authors from six continents; state-of-the-art information on topical areas relative to crop improvement; coverage of genome-editing techniques.

Although the field of quantitative genetics - the study of the genetic basis of variation in quantitative characteristics such as body size, or reproductive success - is almost 100 years old, its application to the study of evolutionary processes in wild populations has expanded greatly over the last few decades. During this time, the use of'wild quantitative genetics'has provided insights into a range of important questions in evolutionary ecology, ranging from studies conducting research in well-established fields such as life-history theory, behavioural ecology and sexual selection, to others addressing relatively new issues such as populations'responses to climate change or the process of senescence in natural environments. Across these fields, there is increasing appreciation of the need to quantify the genetic - rather than just the phenotypic - basis and diversity of key traits, the genetic basis of the associations between traits, and the interaction between these genetic effects and the environment. This research activity has been fuelled by methodological advances in both molecular genetics and statistics, as well as by exciting results emerging from laboratory studies of evolutionary quantitative genetics, and the increasing availability of suitable long-term datasets collected in natural populations, especially in animals. Quantitative Genetics in the Wild is the first book to synthesize the current level of knowledge in this exciting and rapidly-expanding area. This comprehensive volume also offers exciting perspectives for future studies in emerging areas, including the application of quantitative genetics to plants or arthropods, unraveling the molecular basis of variation in quantitative traits, or estimating non-additive genetic variance. Since this book deals with many fundamental questions in evolutionary ecology, it should be of interest to graduate, post-graduate students, and academics from a wide array of fields such as animal behaviour, ecology, evolution, and genetics.

The Animal Production International Seminar (APIS) is the first international conference held by the Faculty of Animal Science, Universitas Brawijaya. APIS was held for the first time in 2010 and was repeated every three years. In 2022, the 5th APIS was organized as an online meeting. The Faculty of Animal Science, Universitas Brawijaya, is optimistic that the results of the 5th APIS will just be as successful as the 4th APIS in 2019. The theme of 5th APIS was ""Developing Modern Livestock Production in Tropical Countries"". The 5th APIS discussed matters related to strategies for developing modern livestock production in several tropical countries. The participants of 5th APIS, including keynote speakers and invited speakers, are from various countries (tropical and sub-tropical). These proceedings present the selected papers from the 5th APIS conference.

In most breeding programs of plant and animal species, genetic data (such as data from field progeny tests) are used to rank parents and help choose candidates for selection. In general, all selection processes first rank the candidates using some function of the observed data and then choose as the selected portion those candidates with the largest (or smallest) values of that function. To make maximum progress from selection, it is necessary to use a function of the data that results in the candidates being ranked as closely as possible to the true (but always unknown) ranking. Very often the observed data on various candidates are messy and unbalanced and this complicates the process of developing precise and accurate rankings. For example, for any given candidate, there may be data on that candidate and its siblings growing in several field tests of different ages. Also, there may be performance data on siblings, ancestors or other relatives from greenhouse, laboratory or other field tests. In addition, data on different candidates may differ drastically in terms of quality and quantity available and may come from varied relatives. Genetic improvement programs which make most effective use of these varied, messy, unbalanced and ancestral data will maximize progress from all stages of selection. In this regard, there are two analytical techniques, best linear prediction (BLP) and best linear unbiased prediction (BLUP), which are quite well-suited to predicting genetic values from a wide variety of sources, ages, qualities and quantities of data.

The impetus for this book arose out of my previous book, The Evolution of Life Histories (Roff, 1992). In that book I presented a single chapter on quanti­ tative genetic theory. However, as the book was concerned with the evolution of life histories and traits connected to this, the presence of quantitative genetic variation was an underlying theme throughout. Much of the focus was placed on optimality theory, for it is this approach that has proven to be extremely successful in the analysis of life history variation. But quantitative genetics cannot be ig­ nored, because there are some questions for which optimality approaches are inappropriate; for example, although optimality modeling can address the ques­ tion of the maintenance of phenotypic variation, it cannot say anything about genetic variation, on which further evolution clearly depends. The present book is, thus, a natural extension of the first. I have approached the problem not from the point of view of an animal or plant breeder but from that of one interested in understanding the evolution of quantitative traits in wild populations. The subject is large with a considerable body of theory: I generally present the assumptions underlying the analysis and the results, giving the relevant references for those interested in the intervening mathematics. My interest is in what quantitative genetics tells me about evolutionary processes; therefore, I have concentrated on areas of research most relevant to field studies.

The present work is unique in that sense it gives formulae along with actual data (analyzed) for the easy understanding. This book is mainly meant for post graduate and research scholars in Quantitative Genetics. A careful perusal of the book will give clear cut idea about the interpretation of the data and formulation of breeding strategies.

Maize is used in an endless list of products that are directly or indirectly related to human nutrition and food security. Maize is grown in producer farms, farmers depend on genetically improved cultivars, and maize breeders develop improved maize cultivars for farmers. Nikolai I. Vavilov defined plant breeding as plant evolution directed by man. Among crops, maize is one of the most successful examples for breeder-directed evolution. Maize is a cross-pollinated species with unique and separate male and female organs allowing techniques from both self and cross-pollinated crops to be utilized. As a consequence, a diverse set of breeding methods can be utilized for the development of various maize cultivar types for all economic conditions (e.g., improved populations, inbred lines, and their hybrids for different types of markets). Maize breeding is the science of maize cultivar development. Public investment in maize breeding from 1865 to 1996 was $3 billion (Crosbie et al., 2004) and the return on investment was $260 billion as a consequence of applied maize breeding, even without full understanding of the genetic basis of heterosis. The principles of quantitative genetics have been successfully applied by maize breeders worldwide to adapt and improve germplasm sources of cultivars for very simple traits (e.g. maize flowering) and very complex ones (e.g., grain yield). For instance, genomic efforts have isolated early-maturing genes and QTL for potential MAS but very simple and low cost phenotypic efforts have caused significant and fast genetic progress across genotypes moving elite tropical and late temperate maize northward with minimal investment. Quantitative genetics has allowed the integration of pre-breeding with cultivar development by characterizing populations genetically, adapting them to places never thought of (e.g., tropical to short-seasons), improving them by all sorts of intra- and inter-population recurrent selection methods, extracting lines with more probability of success, and exploiting inbreeding and heterosis. Quantitative genetics in maize breeding has improved the odds of developing outstanding maize cultivars from genetically broad based improved populations such as B73. The inbred-hybrid concept in maize was a public sector invention 100 years ago and it is still considered one of the greatest achievements in plant breeding. Maize hybrids grown by farmers today are still produced following this methodology and there is still no limit to genetic improvement when most genes are targeted in the breeding process. Heterotic effects are unique for each hybrid and exotic genetic materials (e.g., tropical, early maturing) carry useful alleles for complex traits not present in the B73 genome just sequenced while increasing the genetic diversity of U.S. hybrids. Breeding programs based on classical quantitative genetics and selection methods will be the basis for proving theoretical approaches on breeding plans based on molecular markers. Mating designs still offer large sample sizes when compared to QTL approaches and there is still a need to successful integration of these methods. There is a need to increase the genetic diversity of maize hybrids available in the market (e.g., there is a need to increase the number of early maturing testers in the northern U.S.). Public programs can still develop new and genetically diverse products not available in industry. However, public U.S. maize breeding programs have either been discontinued or are eroding because of decreasing state and federal funding toward basic science. Future significant genetic gains in maize are dependent on the incorporation of useful and unique genetic diversity not available in industry (e.g., NDSU EarlyGEM lines). The integration of pre-breeding methods with cultivar development should enhance future breeding efforts to maintain active public breeding programs not only adapting and improving genetically broad-based germplasm but also

Quantitative Trait Loci (QTL) is a topic of major agricultural significance for efficient livestock production. This advanced-level textbook covers all the statistical methods that have been used or proposed for detection and analysis of QTL and marker- and gene- assisted selection in animal genetics and breeding, as well as new advances that have revolutionized the field since the first edition.

In this chapter, we provide a systematic review of the biological perspective in entrepreneurship. Specifically, we systematically review research linking the three biological strands of genetics, physiology, and neuroscience to entrepreneurship. We discuss the findings of this growing literature and how incorporating biology into the study of entrepreneurship can enhance our understanding of various entrepreneurial outcomes. We then discuss the mechanisms through which biology affects entrepreneurship. Finally, we conclude with directions for future research.

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Les notions de base permettant de comprendre la transmission héréditaire des caractères quantitatifs et leur évolution dans le temps : situation des populations satisfaisant aux conditions de l'équilibre de Hardy-Weinberg, principaux facteurs d'évolution (fractionnement en sous-populations d'effectif limité, sélection, mutation et migration). L'ouvrage intègre les principales avancées de ces dernières années : méthodes modernes d'évaluation génétique, principes d'utilisation, en amélioration génétique, de gènes de nature diverse ou de segments d'ADN balisant le génome. Un ouvrage de base pour étudiants, enseignants et chercheurs en génétique animale et végétale. Une référence pour agronomes et zootechniciens engagés dans des actions d'amélioration génétique ou pour tout généticien appelé à gérer des populations.

This book describes the theory and practice of methods for quantitative trait loci (QTL) detection and analysis, as well as marker assisted selection, in animal genetics and breeding. It is divided into 16 chapters: historical overview; principles of parameter estimation; random and fixed effects (the mixed model); experimental designs to detect QTL (generation of linkage disequilibrium); QTL parameter estimation for crosses between inbred lines; advanced statistical methods for QTL detection and parameter estimation; analysis of QTL as random effects; statistical power to detect QTL and parameter confidence interval; optimization of experimental designs; fine mapping of QTL; complete genome QTL scans (the problem of multiple comparisons); multiple trait QTL analysis; principles of selection index and traditional breeding programmes; marker-assisted selection (theory); marker-assisted selection (results of simulation studies); and marker-assisted introgression. The book is aimed at graduate students and research workers in quantitative genetics and animal breeding. There is an author index and a detailed subject index.

Quantitative Genetic Variation describes some of the experimental approaches to quantitative genetic variation, along with their potential applications and limitations. It considers one of the most widely applicable tools, i.e., biometrical analysis, as well as individual polygenic effects, specific components of a quantitative genetic trait, and artificial selection, and it shows how selection experiments can address specific developmental and genetic questions. Organized into four sections encompassing 17 chapters, this volume begins with a historical overview of the study of quantitative genetic variation, along with genetic variation in fungi and Drosophila. It then discusses the biometrical approach to quantitative variation, selection theory and analysis, uses and limitations of polygene mapping, and computer simulation of the breeding program for polygene location. The reader is also introduced to genes affecting quantitative aspects of physiology in rodents, as well as cytological markers and quantitative variation in wheat. This book will be extremely useful to students, researchers, and geneticists.