title: Emerging technologies advancing forage and turf grass genomics.
abstract: Grassland is of major importance for agricultural production and provides valuable ecosystem services. Its impact is likely to rise in changing socio-economic and climatic environments. High yielding forage grass species are major components of sustainable grassland production. Understanding the genome structure and function of grassland species provides opportunities to accelerate crop improvement and thus to mitigate the future challenges of increased feed and food demand, scarcity of natural resources such as water and nutrients, and high product qualities. In this review, we will discuss a selection of technological developments that served as main drivers to generate new insights into the structure and function of nuclear genomes. Many of these technologies were originally developed in human or animal science and are now increasingly applied in plant genomics. Our main goal is to highlight the benefits of using these technologies for forage and turf grass genome research, to discuss their potentials and limitations as well as their relevance for future applications.
authors.affiliation: Centre of the Region Haná for Biotechnological and Agricultural Research, Institute of Experimental Botany, Šlechtitelů 31, CZ-78371, Olomouc-Holice, Czech Republic.
authors.forename: David
authors.initials: D
authors.lastname: Kopecký
authors.affiliation: Forage Crop Genetics, Institute of Agricultural Sciences, ETH Zurich, Universitaetsstrasse 2, 8092 Zurich, Switzerland. Electronic address: bruno.studer@usys.ethz.ch.
authors.forename: Bruno
authors.initials: B
authors.lastname: Studer
mesh_terms: D000383:Agriculture; D001709:Biotechnology; D001947:Breeding; D018745:Genome, Plant / Q000235:genetics*; D023281:Genomics / Q000379:methods*; D006109:Poaceae / Q000145:classification / Q000235:genetics
keywords: Cytogenetics; Epigenetics; Flow cytometry; Forage and turf grasses; Genome zipper; Genome-wide association studies (GWAS); Genotyping by sequencing (GBS); Next generation sequencing (NGS); QTL analysis; Transcriptome sequencing