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The Effect Of Cycles Of Genomic Selection On Wheat Triticum Aestivum L Traits And On The Wheat Genome
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Book Synopsis The Effect of Cycles of Genomic Selection on Wheat (Triticum Aestivum L.) Traits and on the Wheat Genome by : Maria Nelly Arguello Blanco
Download or read book The Effect of Cycles of Genomic Selection on Wheat (Triticum Aestivum L.) Traits and on the Wheat Genome written by Maria Nelly Arguello Blanco and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Breeders use genomic selection (GS) for rapid cycling of parents for crop improvement. GS increases efficiency of breeding by shortening the duration of breeding cycles. The effect of rapid cycling on the wheat genome is unknown. The first objective of this dissertation was to assess the effect of five rapid cycles on the wheat genome. The OSU wheat breeding program began GS with a training population (YTP) phenotyped for yield, quality, and fusarium head blight (FHB) resistance traits. This YTP was genotyped with 3972 single nucleotide polymorphism (SNP) markers. The phenotypes and genotypes were used to build a GS model to obtain genomic estimated breeding values (GEBV). The GEBVs of F2 plants were then used to advance plants through five cycles of GS (YC1, YC2, YC3, YC4, YC5). We assessed the impact of GS on allele frequencies, the forces driving these changes, genetic distance (GD), population differentiation (FST), and linkage disequilibrium (LD). Relative to the YTP, we found that 27% of SNP had a significant change in allele frequency, 18% SNPs were under selection, 13% changed due to genetic drift, 9.3% were undiscernible for drift or selection, and 18.5% were fixed by YC5. Genetic distance narrowed within cycle while the GD between cycles increased at a 0.02 units per cycle. The cycles differentiated from the YTP at a rate of 0.046 FST units per cycle. The YC5 was highly differentiated from the YTP with an FST value of 0.224. We found the correlation between LD matrices decreasing at -0.057 units per cycle. Overall, we found reduction in genetic diversity, increased genetic differentiation of cycles from the YTP, and changes in LD patterns over cycles. The change in the genome is not desired when implementing GS because the changes will lower the prediction accuracy as the number of cycles increases. The second objective of this dissertation was to estimate the accuracy of GS at predicting the phenotypes of lines derived from cycles of GS. Prediction accuracy is the correlation between GEVBs and observed phenotypes. We compared the prediction accuracies using three training (YTP, TP1721 and TP21) and two prediction populations (GSELPP and GDERPP). We found moderate prediction accuracies (range of -0.25 to 0.25) that varied by trait, training population, and prediction population. While the accuracies were moderate to low, there were significant differences between the top and bottom groups of GSELPP for yield and FHB resistance when they were classified by their GEBVs. This is important as breeders select lines with the best values and discard those with the worst values. Classifying the GSELPP lines using GEBVs based on the TP1721 and TP21 produced significant positive differences for yield suggesting that GS impacts yield even when accuracies are modest. An important role for GS may lie in discarding the worst lines prior to expensive field testing, rather than its ability to identify the very best lines. Breeders should use the prediction accuracies to modify their program to maximize the benefits of GS. This would include the selection of parents, crossing schemes, and field testing so program resources are used to create TPs based on past data have the greatest potential to accurately predict the future.
Book Synopsis Physiological, Molecular, and Genetic Perspectives of Wheat Improvement by : Shabir H Wani
Download or read book Physiological, Molecular, and Genetic Perspectives of Wheat Improvement written by Shabir H Wani and published by Springer Nature. This book was released on 2020-12-17 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: World population is growing at an alarming rate and may exceed 9.7 billion by 2050, whereas agricultural productivity has been negatively affected due to yield limiting factors such as biotic and abiotic stresses as a result of global climate change. Wheat is a staple crop for ~20% of the world population and its yield needs be augmented correspondingly in order to satisfy the demands of our increasing world population. “Green revolution”, the introduction of semi-dwarf, high yielding wheat varieties along with improved agronomic management practices, gave rise to a substantial increase in wheat production and self-sufficiency in developing countries that include Mexico, India and other south Asian countries. Since the late 1980’s, however, wheat yield is at a standoff with little fluctuation. The current trend is thus insufficient to meet the demands of an increasing world population. Therefore, while conventional breeding has had a great impact on wheat yield, with climate change becoming a reality, newer molecular breeding and management tools are needed to meet the goal of improving wheat yield for the future. With the advance in our understanding of the wheat genome and more importantly, the role of environmental interactions on productivity, the idea of genomic selection has been proposed to select for multi-genic quantitative traits early in the breeding cycle. Accordingly genomic selection may remodel wheat breeding with gain that is predicted to be 3 to 5 times that of crossbreeding. Phenomics (high-throughput phenotyping) is another fairly recent advancement using contemporary sensors for wheat germplasm screening and as a selection tool. Lastly, CRISPR/Cas9 ribonucleoprotein mediated genome editing technology has been successfully utilized for efficient and specific genome editing of hexaploid bread wheat. In summary, there has been exciting progresses in the development of non-GM wheat plants resistant to biotic and abiotic stress and/or wheat with improved nutritional quality. We believe it is important to highlight these novel research accomplishments for a broader audience, with the hope that our readers will ultimately adopt these powerful technologies for crops improvement in order to meet the demands of an expanding world population.
Book Synopsis Accuracy of Genomic Selection in a Soft Winter Wheat (Triticum Aestivum L.) Breeding Program by : Mao Huang
Download or read book Accuracy of Genomic Selection in a Soft Winter Wheat (Triticum Aestivum L.) Breeding Program written by Mao Huang and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Genomic selection (GS) is a new marker assisted selection tool that utilizes data from lines in a training population (TP) to predict performance of other related lines by generating their genetic estimated breeding values. The selection process is complicated by genotype by environment interaction (GEI), as the performance of lines in one environment may not predict their performance in other environments. It is critical to evaluate and optimize GS accuracy with the existence of GEI. The GS accuracy can be evaluated by testing the GS model on different validation populations (VP). This study utilized subset of soft winter wheat lines from TP as the VP, and also utilized a VP composed of lines not included in, yet were genetically related to the TP. Our objectives were: 1) to assess GEI patterns and generate trait stability indices; 2) to evaluate GS accuracy for traits and trait stability indices for within and between-population predictions; 3) to assess the effects of optimization approaches on GS accuracy for between-environment predictions within population; 4) to assess GS accuracy from different optimization approaches for between-environment predictions across populations. An elite population (EP) of 273 lines and a yield population (YP) of 294 lines were phenotyped in independent sets of environments. A total of up to 24 different environments, representing four years across locations in five different states were assessed. The EP and YP were both phenotyped for yield (YLD), test weight (TW), plant height (HGT), and heading date (HD), and were genotyped with a common set of 3,537 single nucleotide polymorphism (SNP) markers. The EP was additionally phenotyped for seven quality traits. We produced useful GS prediction accuracy for within-population predictions for all traits (r ranging from 0.33 to 0.74) and most trait stability indices. We observed that ridge regression Best Linear Unbiased Prediction model was as predictive as other GS models, including the ones incorporating GEI term. The best approach to optimize the TP for between-environment accuracy was to subset markers that had the significant and stable effects coupled with eliminating least predictive lines in the TP. The between-population prediction for TW, HGT and HD were useful (r exceeded 0.29) though the between-population prediction for YLD was not within useful range (r ranged from -0.28 to 0.17). The EP and YP environments were separated in two distinct clusters based on the marker effects of YLD, and further supported the hypothesis that the low GS accuracy for YLD was mainly due to the marker effects by population interaction. This suggests that in order to obtain maximum GS accuracy for complex traits such as yield, the population to be predicted could consist of the same lines as in TP, but would be grown under different environments, or the new population to be predicted may be directly derived from TP. Our findings are directly applicable for wheat breeders in North-Eastern U.S. to best design GS schemes, and to implement GS in wheat breeding programs to achieve higher genetic gains with reduced costs and time than conventional breeding methods.
Download or read book The Wheat Genome written by Rudi Appels and published by Springer Nature. This book was released on 2023-12-15 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book provides the first comprehensive coverage of the wheat genome sequence since the publication of the draft and reference sequences for bread wheat and durum wheat. It presents an overview and all aspects of the gold standard sequence of the bread wheat genome, IWGSC RefSeq v1.0 and its subsequent improvements through 2022 (IWGSC RefSeq v2.1), as well as the sequencing of multiple elite wheat varieties, durum wheat, and ancient wheat. The book provides a broad and extensive review of the resources, tools, and methodologies available for exploiting the wheat genome sequence for crop improvement and studying fundamental questions related to the structure, function, and evolution of the wheat genome. Wheat (Tritcum aestivum L.) is the most widely grown crop in the world, contributing approximately 20 percent of total calories and more protein in human diets than any other single source. This book is useful to students, teachers, and scientists in academia and industry interested in gaining an understanding of the wheat genome and its application as well as plant scientists generally interested in polyploid plant species.
Book Synopsis Quantitative Genetics in Maize Breeding by : Arnel R. Hallauer
Download or read book Quantitative Genetics in Maize Breeding written by Arnel R. Hallauer and published by Springer Science & Business Media. This book was released on 2010-09-28 with total page 669 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 developing unique products and training the next generation of maize breeders producing research dissertations directly linked to breeding programs. This is especially important in areas where commercial hybrids are not locally bred. More than ever public and private institutions are encouraged to cooperate in order to share breeding rights, research goals, winter nurseries, managed stress environments, and latest technology for the benefit of producing the best possible hybrids for farmers with the least cost. We have the opportunity to link both classical and modern technology for the benefit of breeding in close cooperation with industry without the need for investing in academic labs and time (e.g., industry labs take a week vs months/years in academic labs for the same work). This volume, as part of the Handbook of Plant Breeding series, aims to increase awareness of the relative value and impact of maize breeding for food, feed, and fuel security. Without breeding programs continuously developing improved germplasm, no technology can develop improved cultivars. Quantitative Genetics in Maize Breeding presents principles and data that can be applied to maximize genetic improvement of germplasm and develop superior genotypes in different crops. The topics included should be of interest of graduate students and breeders conducting research not only on breeding and selection methods but also developing pure lines and hybrid cultivars in crop species. This volume is a unique and permanent contribution to breeders, geneticists, students, policy makers, and land-grant institutions still promoting quality research in applied plant breeding as opposed to promoting grant monies and indirect costs at any short-term cost. The book is dedicated to those who envision the development of the next generation of cultivars with less need of water and inputs, with better nutrition; and with higher percentages of exotic germplasm as well as those that pursue independent research goals before searching for funding. Scientists are encouraged to use all possible breeding methodologies available (e.g., transgenics, classical breeding, MAS, and all possible combinations could be used with specific sound long and short-term goals on mind) once germplasm is chosen making wise decisions with proven and scientifically sound technologies for assisting current breeding efforts depending on the particular trait under selection. Arnel R. Hallauer is C. F. Curtiss Distinguished Professor in Agriculture (Emeritus) at Iowa State University (ISU). Dr. Hallauer has led maize-breeding research for mid-season maturity at ISU since 1958. His work has had a worldwide impact on plant-breeding programs, industry, and students and was named a member of the National Academy of Sciences. Hallauer is a native of Kansas, USA. José B. Miranda Filho is full-professor in the Department of Genetics, Escola Superior de Agricultura Luiz de Queiroz - University of São Paulo located at Piracicaba, Brazil. His research interests have emphasized development of quantitative genetic theory and its application to maize breeding. Miranda Filho is native of Pirassununga, São Paulo, Brazil. M.J. Carena is professor of plant sciences at North Dakota State University (NDSU). Dr. Carena has led maize-breeding research for short-season maturity at NDSU since 1999. This program is currently one the of the few public U.S. programs left integrating pre-breeding with cultivar development and training in applied maize breeding. He teaches Quantitative Genetics and Crop Breeding Techniques at NDSU. Carena is a native of Buenos Aires, Argentina. http://www.ag.ndsu.nodak.edu/plantsci/faculty/Carena.htm
Book Synopsis Accelerating Genetic Gain for Key Traits Using Genome-Wide Association Studies and Genomic Selection: Promising Breeding Tools for Sustainable Agriculture by : Sundeep Kumar
Download or read book Accelerating Genetic Gain for Key Traits Using Genome-Wide Association Studies and Genomic Selection: Promising Breeding Tools for Sustainable Agriculture written by Sundeep Kumar and published by Frontiers Media SA. This book was released on 2024-01-08 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Genetics and Genomics of the Triticeae by : Catherine Feuillet
Download or read book Genetics and Genomics of the Triticeae written by Catherine Feuillet and published by Springer Science & Business Media. This book was released on 2009-06-10 with total page 774 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sequencing of the model plant genomes such as those of A. thaliana and rice has revolutionized our understanding of plant biology but it has yet to translate into the improvement of major crop species such as maize, wheat, or barley. Moreover, the comparative genomic studies in cereals that have been performed in the past decade have revealed the limits of conservation between rice and the other cereal genomes. This has necessitated the development of genomic resources and programs for maize, sorghum, wheat, and barley to serve as the foundation for future genome sequencing and the acceleration of genomic based improvement of these critically important crops. Cereals constitute over 50% of total crop production worldwide (http://www.fao.org/) and cereal seeds are one of the most important renewable resources for food, feed, and industrial raw materials. Crop species of the Triticeae tribe that comprise wheat, barley, and rye are essential components of human and domestic animal nutrition. With 17% of all crop area, wheat is the staple food for 40% of the world’s population, while barley ranks fifth in the world production. Their domestication in the Fertile Crescent 10,000 years ago ushered in the beginning of agriculture and signified an important breakthrough in the advancement of civilization. Rye is second after wheat among grains most commonly used in the production of bread and is also very important for mixed animal feeds. It can be cultivated in poor soils and climates that are generally not suitable for other cereals. Extensive genetics and cytogenetics studies performed in the Triticeae species over the last 50 years have led to the characterization of their chromosomal composition and origins and have supported intensive work to create new genetic resources. Cytogenetic studies in wheat have allowed the identification and characterization of the different homoeologous genomes and have demonstrated the utility of studying wheat genome evolution as a model for the analysis of polyploidization, a major force in the evolution of the eukaryotic genomes. Barley with its diploid genome shows high collinearity with the other Triticeae genomes and therefore serves as a good template for supporting genomic analyses in the wheat and rye genomes. The knowledge gained from genetic studies in the Triticeae has also been used to produce Triticale, the first human made hybrid crop that results from a cross between wheat and rye and combines the nutrition quality and productivity of wheat with the ruggedness of rye. Despite the economic importance of the Triticeae species and the need for accelerated crop improvement based on genomics studies, the size (1.7 Gb for the bread wheat genome, i.e., 5x the human genome and 40 times the rice genome), high repeat content (>80%), and complexity (polyploidy in wheat) of their genomes often have been considered too challenging for efficient molecular analysis and genetic improvement in these species. Consequently, Triticeae genomics has lagged behind the genomic advances of other cereal crops for many years. Recently, however, the situation has changed dramatically and robust genomic programs can be established in the Triticeae as a result of the convergence of several technology developments that have led to new, more efficient scientific capabilities and resources such as whole-genome and chromosome-specific BAC libraries, extensive EST collections, transformation systems, wild germplasm and mutant collections, as well as DNA chips. Currently, the Triticeae genomics "toolbox" is comprised of: - 9 publicly available BAC libraries from diploid (5), tetraploid (1) and hexaploid (3) wheat; 3 publicly available BAC libraries from barley and one BAC library from rye; - 3 wheat chromosome specific BAC libraries; - DNA chips including commercially available first generation chips from AFFYMETRIX containing 55’000 wheat and 22,000 barley genes; - A large number of wheat and barley genetic maps that are saturated by a significant number of markers; - The largest plant EST collection with 870’000 wheat ESTs, 440’000 barley ESTs and about 10’000 rye ESTs; - Established protocols for stable transformation by biolistic and agrobacterium as well as a transient expression system using VIGS in wheat and barley; and - Large collections of well characterized cultivated and wild genetic resources. International consortia, such as the International Triticeae Mapping Initiative (ITMI), have advanced synergies in the Triticeae genetics community in the development of additional mapping populations and markers that have led to a dramatic improvement in the resolution of the genetic maps and the amount of molecular markers in the three species resulting in the accelerated utilization of molecular markers in selection programs. Together, with the development of the genomic resources, the isolation of the first genes of agronomic interest by map-based cloning has been enabled and has proven the feasibility of forging the link between genotype and phenotype in the Triticeae species. Moreover, the first analyses of BAC sequences from wheat and barley have allowed preliminary characterizations of their genome organization and composition as well as the first inter- and intra-specific comparative genomic studies. These later have revealed important evolutionary mechanisms (e.g. unequal crossing over, illegitimate recombination) that have shaped the wheat and barley genomes during their evolution. These breakthroughs have demonstrated the feasibility of developing efficient genomic studies in the Triticeae and have led to the recent establishment of the International Wheat Genome Sequencing Consortium (IWGSC) (http//:www.wheatgenome.org) and the International Barley Sequencing Consortium (www.isbc.org) that aim to sequence, respectively, the hexaploid wheat and barley genomes to accelerate gene discovery and crop improvement in the next decade. Large projects aiming at the establishment of the physical maps as well as a better characterization of their composition and organization through large scale random sequencing projects have been initiated already. Concurrently, a number of projects have been launched to develop high throughput functional genomics in wheat and barley. Transcriptomics, proteomics, and metabolomics analyses of traits of agronomic importance, such as quality, disease resistance, drought, and salt tolerance, are underway in both species. Combined with the development of physical maps, efficient gene isolation will be enabled and improved sequencing technologies and reduced sequencing costs will permit ultimately genome sequencing and access to the entire wheat and barley gene regulatory elements repertoire. Because rye is closely related to wheat and barley in Triticeae evolution, the latest developments in wheat and barley genomics will be of great use for developing rye genomics and for providing tools for rye improvement. Finally, a new model for temperate grasses has emerged in the past year with the development of the genetics and genomics (including a 8x whole genome shotgun sequencing project) of Brachypodium, a member of the Poeae family that is more closely related to the Triticeae than rice and can provide valuable information for supporting Triticeae genomics in the near future. These recent breakthroughs have yet to be reviewed in a single source of literature and current handbooks on wheat, barley, or rye are dedicated mainly to progress in genetics. In "Genetics and Genomics of the Triticeae", we will aim to comprehensively review the recent progress in the development of structural and functional genomics tools in the Triticeae species and review the understanding of wheat, barley, and rye biology that has resulted from these new resources as well as to illuminate how this new found knowledge can be applied for the improvement of these essential species. The book will be the seventh volume in the ambitious series of books, Plant Genetics and Genomics (Richard A. Jorgensen, series editor) that will attempt to bring the field up-to-date on the genetics and genomics of important crop plants and genetic models. It is our hope that the publication will be a useful and timely tool for researchers and students alike working with the Triticeae.
Book Synopsis Genetic Data Analysis for Plant and Animal Breeding by : Fikret Isik
Download or read book Genetic Data Analysis for Plant and Animal Breeding written by Fikret Isik and published by Springer. This book was released on 2017-09-09 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book fills the gap between textbooks of quantitative genetic theory, and software manuals that provide details on analytical methods but little context or perspective on which methods may be most appropriate for a particular application. Accordingly this book is composed of two sections. The first section (Chapters 1 to 8) covers topics of classical phenotypic data analysis for prediction of breeding values in animal and plant breeding programs. In the second section (Chapters 9 to 13) we provide the concept and overall review of available tools for using DNA markers for predictions of genetic merits in breeding populations. With advances in DNA sequencing technologies, genomic data, especially single nucleotide polymorphism (SNP) markers, have become available for animal and plant breeding programs in recent years. Analysis of DNA markers for prediction of genetic merit is a relatively new and active research area. The algorithms and software to implement these algorithms are changing rapidly. This section represents state-of-the-art knowledge on the tools and technologies available for genetic analysis of plants and animals. However, readers should be aware that the methods or statistical packages covered here may not be available or they might be out of date in a few years. Ultimately the book is intended for professional breeders interested in utilizing these tools and approaches in their breeding programs. Lastly, we anticipate the usage of this volume for advanced level graduate courses in agricultural and breeding courses.
Book Synopsis Evolution and Selection of Quantitative Traits by : Bruce Walsh
Download or read book Evolution and Selection of Quantitative Traits written by Bruce Walsh and published by Oxford University Press. This book was released on 2018-06-21 with total page 1504 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Assessing Genome Wide Breeding Strategies for Economic Traits in Soft Winter Wheat and Their Impact on Genetic Architecture by : Amber L. Hoffstetter
Download or read book Assessing Genome Wide Breeding Strategies for Economic Traits in Soft Winter Wheat and Their Impact on Genetic Architecture written by Amber L. Hoffstetter and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: With next generation sequencing technology, such as genotyping-by-sequencing (GBS), breeders can now genotype large populations with thousands of markers. This technology can be coupled with statistical methods such as genome-wide association studies (GWAS) and genomic selection (GS) to identify marker-trait associations and estimate marker effects. Where GWAS studies estimate each marker separately and use a p-value to determine significance, GS ignores significant thresholds and uses a training population (TP) with phenotypic and genotypic data to estimate all markers simultaneously. These effects are then used to predict the genomic estimated breeding values (GEBV) of other individuals. We performed a GWAS analysis using an elite population of soft red winter wheat lines and identified 14 QTL for grain yield (GY), four for Fusarium Head Blight (FHB) index, four for flour yield (FY), and five for softness equivalence (SE) Across all traits the R2 values ranged from 1.8 to 3.5%. We also determined the prediction accuracy GS for these four traits. Using all markers and lines we found the prediction accuracies ranged from 0.35 (FHB) to 0.57 (GY, Wooster, Ohio). In general using only data from TP lines with low GEI or marker subsets increased the GS accuracy. When using the TP to predict the performance of the 23 parental lines, accuracies using weighted correlations based on the parent’s contribution to the TP produced the highest prediction accuracies (r = 0.08 to 0.85). The accuracy of the TP model for predicting the phenotypes of the validation population was low (r = -0.25 to 0.22), especially for GY, but improved when using a subset of VP lines more related to the TP (r = 0.01 to 0.71). When analyzing the impact of GS on diversity and linkage disequilibrium (LD) we found that there was a loss of diversity across the two cycles of GS and that the second cycle of GS (GC1) is more inbred than the TP. LD for most marker pairs remains low across all three populations. The correlation of R2 values across the three populations ranged from 0.46 to 0.65. As LD between markers in the TP increases, a similar or higher LD is found with the F2 individuals comprising the two cycles of GS (GC0 and GC1). The frequency of the 1 allele for majority (46%) of markers associated with GY in Wooster, Ohio decreases while the remaining markers have either the 1 allele increasing or remaining unchanged. The preferred allele for these two trends is increasing for 95% and 80% of the markers respectively. The frequency of the 1 allele for individuals in the top 10% (best) and bottom 10% (worst) of the GC0 and GC1 individuals relative to the TP indicates that in the first cycle the majority (53%) of markers show signs of genetic drift while in the second cycle the majority (60%) show signs of direction selection. The results of this work show that these two breeding strategies could be useful for the SRWW program here of Ohio State. And indicates that GS impacts genetic diversity, LD, and allele frequencies.
Book Synopsis Improving Breeding Program Efficiency and Genetic Gain Through the Implementation of Genomic Selection in Diverse Wheat Germplasm by : Dylan Larkin
Download or read book Improving Breeding Program Efficiency and Genetic Gain Through the Implementation of Genomic Selection in Diverse Wheat Germplasm written by Dylan Larkin and published by . This book was released on 2020 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genomic selection (GS) is an important tool for increasing genetic gain for economically important traits in breeding programs. Genomic selection uses molecular markers across the entire genome in order to predict the performance of breeding lines for a trait of interest prior to phenotyping. A training population (TP) of elite germplasm, representative of the University of Arkansas wheat breeding program, was developed in order to predict important agronomic and Fusarium head blight (FHB) resistance traits within the University of Arkansas wheat breeding program through cross-validation and forward prediction. A genome-wide association study (GWAS) was performed on the TP to identify novel FHB resistance loci for deoxynivalenol (DON) accumulation, Fusarium damaged kernels (FDK), incidence (INC), and severity (SEV). Significantly loci were used as fixed effects in a GS model (GS+GWAS) and compared to a naïve GS (NGS) model, where the NGS models had significantly higher prediction accuracies (PA) than the GS+GWAS models for all four FHB traits. The GWAS identified novel loci for all four FHB traits, most notably on chromosomes 3BL and 4BL. Multivariate GS (MVGS) models using correlated traits as covariates were also compared to NGS models and the MVGS models significantly outperformed the NGS models for all four traits. The same TP was also evaluated for five agronomic traits, including grain yield (GY), heading date (HD), maturity date (MD), plant height (PH), and test weight (TW), where MVGS models were compared to NGS models. Again, MVGS models significantly outperformed NGS models for all five agronomic traits, especially when there were strong genetic correlations between predicted traits and covariates. Additionally, MVGS models were tested using GY data for genotypes only grown in some environments to predict said genotypes in missing environments. This method significantly improved PA for GY between 6% and 21% for four of six tested environments. The abovementioned TP was then used for forward prediction to predict GY for untested F4:6 breeding lines and DON, FDK, and SEV for F4:7 breeding lines. The MVGS models were comparable to phenotypic selection and had higher selection accuracies for two of three breeding cycles for GY, both cycles for DON, and at least one cycle for FDK and SEV. The MVGS model also had higher PAs for all four traits compared with the NGS models. These results show that GS, and MVGS, can be successfully implemented in a wheat breeding program over multiple breeding cycles and can be effective alongside phenotypic selection for economically important traits. The MVGS models are particularly effective when predicted traits share strong genetic correlations with covariate traits, and covariate traits have a higher heritability than the predicted traits.
Book Synopsis Genomic Selection: Lessons Learned and Perspectives by : Johannes W. R. Martini
Download or read book Genomic Selection: Lessons Learned and Perspectives written by Johannes W. R. Martini and published by Frontiers Media SA. This book was released on 2022-09-15 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genomic selection (GS) has been the most prominent topic in breeding science in the last two decades. The continued interest is promoted by its huge potential impact on the efficiency of breeding. Predicting a breeding value based on molecular markers and phenotypic values of relatives may be used to manipulate three parameters of the breeder's equation. First, the accuracy of the selection may be improved by predicting the genetic value more reliably when considering the records of relatives and the realized genomic relationship. Secondly, genotyping and predicting may be more cost effective than comprehensive phenotyping. Resources can instead be allocated to increasing population sizes and selection intensity. The third, probably most important factor, is time. As shown in dairy cattle breeding, reducing cycle time by crossing selection candidates earlier may have the strongest impact on selection gain. Many different prediction models have been used, and different ways of using predicted values in a breeding program have been explored. We would like to address the questions: i. How did GS change breeding schemes of different crops in the last 20 years? ii. What was the impact on realized selection gain? iii. What would be the best structure of a crop-specific breeding scheme to exploit the full potential of GS? iv. What is the potential of hybrid prediction, epistasis effect models, deep learning methods and other extensions of the standard prediction of additive effects? v. What are the long-term effects of GS? vi. Can predictive breeding approaches also be used to harness genetic resources from germplasm banks in a more efficient way to adapt current germplasm to new environmental challenges? This Research Topic welcomes submissions of Original Research papers, Opinions, Perspectives, Reviews, and Mini-Reviews related to these themes: 1. Genomic selection: statistical methodology 2. The (optimal) use of GS in breeding schemes 3. Practical experiences with GS (selection gain, long-term effects, negative side effects) 4. Predictive approaches to harness genetic resources Concerning point 1): If an original research paper compares different methods empirically without theoretical considerations on when one or the other method should be better, the methods should be compared with at least five different data sets. The data sets should differ either in crop, genotyping method or its source, for instance from a breeding program or gene bank accessions. Concerning point 2): Manuscripts addressing the use of GS in breeding schemes should illustrate breeding schemes that are run in practice. General ideas about schemes that may be run in the future may be considered as 'Perspective' articles. Conflict of Interest statements: - Topic Editor Valentin Wimmer is affiliated to KWS SAAT SE & Co. KGaA, Germany. - Topic Editor Brian Gardunia is affiliated to Bayer Crop Sciences and has a collaboration with AbacusBio, and is an author on patents with Bayer Crop Sciences. The other Topic Editors did not disclose any conflicts of interest. Image credit: CIMMYT, reproduced under the CC BY-NC-SA 2.0 license
Book Synopsis Molecular Plant Breeding by : Yunbi Xu
Download or read book Molecular Plant Breeding written by Yunbi Xu and published by CABI. This book was released on 2010 with total page 756 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advances in plant genomics and molecular biology have revolutionized our understanding of plant genetics, providing new opportunities for more efficient and controllable plant breeding. Successful techniques require a solid understanding of the underlying molecular biology as well as experience in applied plant breeding. Bridging the gap between developments in biotechnology and its applications in plant improvement, Molecular Plant Breeding provides an integrative overview of issues from basic theories to their applications to crop improvement including molecular marker technology, gene mapping, genetic transformation, quantitative genetics, and breeding methodology.
Book Synopsis Advances in Wheat Genetics: From Genome to Field by : Yasunari Ogihara
Download or read book Advances in Wheat Genetics: From Genome to Field written by Yasunari Ogihara and published by Springer. This book was released on 2015-09-15 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: This proceedings is a collection of 46 selected papers that were presented at the 12th International Wheat Genetics Symposium (IWGS). Since the launch of the wheat genome sequencing project in 2005, the arrival of draft genome sequences has marked a new era in wheat genetics and genomics, catalyzing rapid advancement in the field. This book provides a comprehensive review of the forefront of wheat research, across various important topics such as germplasm and genetic diversity, cytogenetics and allopolyploid evolution, genome sequencing, structural and functional genomics, gene function and molecular biology, biotic stress, abiotic stress, grain quality, and classical and molecular breeding. Following an introduction, 9 parts of the book are dedicated to each of these topics. A final, 11th part entitled “Toward Sustainable Wheat Production” contains 7 excellent papers that were presented in the 12th IWGS Special Session supported by the OECD. With rapid population growth and radical climate changes, the world faces a global food crisis and is in need of another Green Revolution to boost yields of wheat and other widely grown staple crops. Although this book focuses on wheat, many of the newly developed techniques and results presented here can be applied to other plant species with large and complex genomes. As such, this volume is highly recommended for all students and researchers in wheat sciences and related plant sciences and for those who are interested in stable food production and food security.
Book Synopsis Association Mapping and Genomic Selection for Yield and Agronomic Traits in Soft Winter Wheat by : Dennis Nicuh Bulusan Lozada
Download or read book Association Mapping and Genomic Selection for Yield and Agronomic Traits in Soft Winter Wheat written by Dennis Nicuh Bulusan Lozada and published by . This book was released on 2018 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tools such as genome-wide association study (GWAS) and genomic selection (GS) have expedited the development of crops with improved genetic potential. While GWAS aims to identify significant markers associated with a trait of interest, the goal of GS is to utilize all marker effects to predict the performance of new breeding lines prior to testing. A GWAS for grain yield (GY), yield components, and agronomic traits was conducted using a diverse panel of 239 soft winter wheat (SWW) lines evaluated in eight site-years in Arkansas and Oklahoma. Broad sense heritability of GY (H2=0.48) was moderate compared to other traits including plant height (H2=0.81) and kernel weight (H2=0.77). Markers associated with multiple traits on chromosomes 1A, 2D, 3B, and 4B serve as potential targets for marker assisted breeding to select for GY improvement. Validation of GY-related loci using spring wheat from the International Maize and Wheat Improvement Center (CIMMYT) in Mexico confirmed the effects of three loci in chromosomes 3A, 4B, and 6B. Lines possessing the favorable allele at all three loci (A-C-G allele combination) had the highest mean GY of possible haplotypes. The same population of 239 lines was used in a GS study as a training population (TP) to determine factors that affect the predictability of GY. The TP size had the greatest effect on predictive ability across the measured traits. Adding covariates in the GS model was more advantageous in increasing prediction accuracies under single population cross validations than in forward predictions. Forward validation of the prediction models on two new populations resulted in a maximum accuracy of 0.43 for GY. Genomic selection was "superior" to marker-assisted selection in terms of response to selection and combining phenotypic selection with GS resulted in the highest response. Results from this study can be used to accelerate the process of GY improvement and increase genetic gains in wheat breeding programs.
Book Synopsis Genomic Prediction of Complex Traits by : Nourollah Ahmadi
Download or read book Genomic Prediction of Complex Traits written by Nourollah Ahmadi and published by Springer Nature. This book was released on 2022-04-22 with total page 651 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume explores the conceptual framework and the practical issues related to genomic prediction of complex traits in human medicine and in animal and plant breeding. The book is organized into five parts. Part One reminds molecular genetics approaches intending to predict phenotypic variations. Part Two presents the principles of genomic prediction of complex traits, and reviews factors that affect its reliability. Part Three describes genomic prediction methods, including machine-learning approaches, accounting for different degree of biological complexity, and reviews the associated computer-packages. Part Four reports on emerging trends such as phenomic prediction and incorporation into genomic prediction models of “omics” data and crop growth models. Part Five is dedicated to lessons learned from cases studies in the fields of human health and animal and plant breeding, and to methods for analysis of the economic effectiveness of genomic prediction. Written in the highly successful Methods in Molecular Biology series format, the book provides theoretical bases and practical guidelines for an informed decision making of practitioners and identifies pertinent routes for further methodological researches. Cutting-edge and thorough, Complex Trait Predictions: Methods and Protocols is a valuable resource for scientists and researchers who are interested in learning more about this important and developing field. Chapters 3, 9, 13, 14, and 21 are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Book Synopsis Genetic and Genomic Studies on Wheat Pre-harvest Sprouting Resistance by : Meng Lin
Download or read book Genetic and Genomic Studies on Wheat Pre-harvest Sprouting Resistance written by Meng Lin and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Wheat pre-harvest sprouting (PHS), germination of physiologically matured grains in a wheat spike before harvesting, can cause significant reduction in grain yield and end-use quality. Many quantitative trait loci (QTL) for PHS resistance have been reported in different sources. To determine the genetic architecture of PHS resistance and its relationship with grain color (GC) in US hard winter wheat, a genome-wide association study (GWAS) on both PHS resistance and GC was conducted using in a panel of 185 U.S. elite breeding lines and cultivars and 90K wheat SNP arrrays. PHS resistance was assessed by evaluating sprouting rates in wheat spikes harvested from both greenhouse and field experiments. Thirteen QTLs for PHS resistance were identified on 11 chromosomes in at least two experiments, and the effects of these QTLs varied among different environments. The common QTLs for PHS resistance and GC were identified on the long arms of the chromosome 3A and 3D, indicating pleiotropic effect of the two QTLs. Significant QTLs were also detected on chromosome arms 3AS and 4AL, which were not related to GC, suggesting that it is possible to improve PHS resistance in white wheat. To identify markers closely linked to the 4AL QTL, genotyping-by-sequencing (GBS) technology was used to analyze a population of recombinant inbred lines (RILs) developed from a cross between two parents, "Tutoumai A" and "Siyang 936", contrasting in 4AL QTL. Several closely linked GBS SNP markers to the 4AL QTL were identified and some of them were coverted to KASP for marker-assisted breeding. To investigate effects of the two non-GC related QTLs on 3AS and 4AL, both QTLs were transferered from "Tutoumai A" and "AUS1408" into a susceptible US hard winter wheat breeding line, NW97S186, through marker-assisted backcrossing using the gene marker TaPHS1 for 3AS QTL and a tightly linked KASP marker we developed for 4AL QTL. The 3AS QTL (TaPHS1) significantly interacted with environments and genetic backgrounds, whereas 4AL QTL (TaMKK3-A) interacted with environments only. The two QTLs showed additive effects on PHS resistance, indicating pyramiding these two QTLs can increase PHS resistance. To improve breeding selection efficiency, genomic prediction using genome-wide markers and marker-based prediction (MBP) using selected trait-linked markers were conducted in the association panel. Among the four genomic prediction methods evaluated, the ridge regression best linear unbiased prediction (rrBLUP) provides the best prediction among the tested methods (rrBLUP, BayesB, BayesC and BayesC0). However, MBP using 11 significant SNPs identified in the association study provides a better prediction than genomic prediction. Therefore, for traits that are controlled by a few major QTLs, MBP may be more effective than genomic selection.
