Genome-Wide Association Studies (GWAS) are widely used in the genetic dissection of complex traits. Most existing methods are based on single-marker association in genome-wide scans with population structure and polygenic background controls. To control the false positive rate, the Bonferroni correction for multiple tests is frequently adopted. This stringent correction results in the exclusion of important loci, especially for GWAS in crop genetics. To address this issue, multi-locus GWAS methodologies have been recommended, i.e., FASTmrEMMA, ISIS EM-BLASSO, mrMLM, FASTmrMLM, pLARmEB, pKWmEB and FarmCPU. In this Research Topic, our purpose is to clarify some important issues in the application of multi-locus GWAS methods. Here we discuss the following subjects: First, we discuss the advantages of new multi-locus GWAS methods over the widely-used single-locus GWAS methods in the genetic dissection of complex traits, metabolites and gene expression levels. Secondly, large experiment error in the field measurement of phenotypic values for complex traits in crop genetics results in relatively large P-values in GWAS, indicating the existence of small number of significantly associated SNPs. To solve this issue, a less stringent P-value critical value is often adopted, i.e., 0.001, 0.0001 and 1/m (m is the number of markers). Although lowering the stringency with which an association is made could identify more hits, confidence in these hits would significantly drop. In this Research Topic we propose a new threshold of significant QTN (LOD=3.0 or P-value=2.0e-4) in multi-locus GWAS to balance high power and low false positive rate. Thirdly, heritability missing in GWAS is a common phenomenon, and a series of scientists have explained the reasons why the heritability is missing. In this Research Topic, we also add one additional reason and propose the joint use of several GWAS methodologies to capture more QTNs. Thus, overall estimated heritability would be increased. Finally, we discuss how to select and use these multi-locus GWAS methods.

Genome-wide association studies (GWAS) have been widely used in the genetic dissection of complex traits. However, there are still limits in current GWAS statistics. For example, (1) almost all the existing methods do not estimate additive and dominance effects in quantitative trait nucleotide (QTN) detection; (2) the methods for detecting QTN-by-environment interaction (QEI) are not straightforward and do not estimate additive and dominance effects as well as additive-by-environment and dominance-by-environment interaction effects, leading to unreliable results; and (3) no or too simple polygenic background controls have been employed in QTN-by-QTN interaction (QQI) detection. As a result, few studies of QEI and QQI for complex traits have been reported based on multiple-environment experiments. Recently, new statistical tools, including 3VmrMLM, have been developed to address these needs in GWAS. In 3VmrMLM, all the trait-associated effects, including QTN, QEI and QQI related effects, are compressed into a single effect-related vector, while all the polygenic backgrounds are compressed into a single polygenic effect matrix. These compressed parameters can be accurately and efficiently estimated through a unified mixed model analysis. To further validate these new GWAS methods, particularly 3VmrMLM, they should be rigorously tested in real data of various plants and a wide range of other species.

Maize is one of the most economically important food crops worldwide. It is used for livestock feeds and human nutrition. Recent strategies have been adopted for improving maize crops. This book brings together recent advances, breeding strategies, and applications in the biological control, breeding, and genetic improvement of maize genetic resources. It also provides new insights and sheds light on new perspectives and future research work that have been carried out for further improvement of maize crops. This book is a useful resource for students, researchers, and scientists.

Biotic stresses cause yield loss of 31-42% in crops in addition to 6-20% during post-harvest stage. Understanding interaction of crop plants to the biotic stresses caused by insects, bacteria, fungi, viruses, and oomycetes, etc. is important to develop resistant crop varieties. Knowledge on the advanced genetic and genomic crop improvement strategies including molecular breeding, transgenics, genomic-assisted breeding and the recently emerging genome editing for developing resistant varieties in oilseed crops is imperative for addressing FPNEE (food, health, nutrition. energy and environment) security. Whole genome sequencing of these crops followed by genotyping-by-sequencing have facilitated precise information about the genes conferring resistance useful for gene discovery, allele mining and shuttle breeding which in turn opened up the scope for 'designing' crop genomes with resistance to biotic stresses. The eight chapters each dedicated to an oilseed crop in this volume elucidate on different types of biotic stress agents and their effects on and interaction with the crop plants; enumerate on the available genetic diversity with regard to biotic stress resistance among available cultivars; illuminate on the potential gene pools for utilization in interspecific gene transfer; present brief on the classical genetics of stress resistance and traditional breeding for transferring them to their cultivated counterparts; depict the success stories of genetic engineering for developing biotic stress resistant varieties; discuss on molecular mapping of genes and QTLs underlying biotic stress resistance and their marker-assisted introgression into elite varieties; enunciate on different emerging genomics-aided techniques including genomic selection, allele mining, gene discovery and gene pyramiding for developing resistant crop varieties with higher quantity and quality of yields; and also elaborate some case studies on genome editing focusing on specific genes for generating disease and insect resistant crops.

Concepts and Techniques in OMICS and Systems Biology provides a concise and lucid account on the technical aspects of omics, system biology and their application in fields of different life science. With a strong focus on the fundamental principles understanding of metabolomics, ionomics and system biology, the book also gives an updated account on technical aspects of omics and system biology. Since both omics and systems biology fields are fast advancing filed of biological sciences, its significance and applications need to be understood from the baseline. In 10 chapters Concepts and Techniques in OMICS and Systems Biology introduces the reader to both Proteomics, Metabolomics and Ionomics, and System Biology, the technical applications, describes both the software in for proteomics as metabolomic enumeration and preludes Omics technologies and their applications. The chapters are designed in a well-defined chronology such that readers will understand the concepts and techniques involved in omics and system biology. This compilation will be ideal reading material for students, researchers and people working in the industries related to biological sciences. Provides an in-depth explanation of fundamental principles regarding the understanding of metabolomics, ionomics and system biology. Gives updated account on technical aspects of omics and system biology. Includes unique content in its theoretical background, technical approaches and advancements made in omics and systems biology