This book is the first comprehensive compilation of deliberations on whole genome sequencing of the diploid and tetraploid alfalfa genomes including sequence assembly, gene annotation, and comparative genomics with the model legume genome, functional genomics, and genomics of important agronomic characters. Other chapters describe the genetic diversity and germplasm collections of alfalfa, as well as development of genetic markers and genome-wide association and genomic selection for economical important traits, genome editing, genomics, and breeding targets to address current and future needs. Altogether, the book contains about 300 pages over 16 chapters authored by globally reputed experts on the relevant field in this crop. This book is useful to the students, teachers, and scientists in the academia and relevant private companies interested in genetics, breeding, pathology, physiology, molecular genetics and breeding, biotechnology, and structural and functional genomics. The work is also useful to seed and forage industries.

The primary goal of the research presented in the following chapters was to assess the genomic basis of the adaptive trait of autumn dormancy in alfalfa using high resolution genetic mapping approaches in diverse germplasm. Previous work in the field has developed protocols to generate vast amounts of sequence based marker data for this species using GBS. However, opportunity remains to extract more information from such data than had been previously possible. In chapter 1, we review some concepts relevant to the rest of this work including basic biology and improvement of alfalfa, the trait of autumn dormancy, and opportunities for molecular markers in alfalfa research. In chapter 2, we employ a recent SNP calling methodology and develop a framework for estimating allele frequencies from pooled sequencing. We use that framework to screen the non-dormant cultivar CUF 101 and populations developed by three cycles of selection for taller and shorter plants in autumn. We validated the robustness of our GBS-derived, population-specific allele frequency estimates using an analytic approach. In chapter 3, we analyze pre- and post-selection populations from an additional five backgrounds together with CUF 101 to seek evidence for loci under selection in germplasm expressing a range of dormancy levels. In chapter 4, we build on recent scientific reports to propose a method for conducting genome-wide association scans from low-coverage autotetraploid sequencing data that is able to account for uncertainty regarding genotypes. We apply this method to a panel of semi-dormant individuals from a commercial breeding program. Using simulations, we show this method to be more powerful than an existing method.

The genetic structure of complex agronomic traits in alfalfa (Medicago sativa) is not well understood. By crossing the subspecies M. sativa subsp. falcata and M. sativa subsp. sativa, a fullsib F1 population was created from which a genetic linkage map of each parental genome was developed using RFLP and SSR markers. These maps include simplex, duplex, and simplex-simplex alleles along with a number of alleles exhibiting segregation distortion. The inclusion of these more complicated segregation ratios resulted in greater saturation of the genome, a better convergence to eight consensus linkage groups, and a more realistic view of regions of the genome that may not behave normally due to segregation distortion than would have been possible by only using simplex alleles as has been done previously. The population was clonally propagated and grown at three field locations with phenotypic data collected over three years for various agronomic traits, including biomass production, forage height, and forage regrowth. Combining the marker data with the phenotypic data, markers were identified from each parental genome that were associated with these traits, suggesting that both major germplasm sources of cultivated alfalfa contain alleles that may contribute to improved alfalfa cultivars. These results provide a much better understanding of the genomic regions underlying these traits and are an important start in efforts aimed at the use of marker-assisted selection for the improvement of alfalfa cultivars.