RADseq approaches and applications for forest tree genetics

• Published in: Tree genetics & genomes Vol. 14; no. 3; pp. 1 - 25
• Main Authors: Parchman, Thomas L., Jahner, Joshua P., Uckele, Kathryn A., Galland, Lanie M., Eckert, Andrew J.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2018; Springer Nature B.V
• Subjects: analytical methods; bioinformatics; Biomedical and Life Sciences; Biotechnology; chromosome mapping; Data processing; Deoxyribonucleic acid; DNA; DNA sequencing; Empirical analysis; experimental design; forest trees; Forestry; Gene mapping; Genetics; genome; Genomes; Genomics; Genotyping; Germplasm Diversity; Laboratories; Laboratory methods; Life Sciences; Linkage disequilibrium; Parameter estimation; Phylogeny; Plant Breeding/Biotechnology; plant genetics; Plant Genetics and Genomics; Plant species; Population genetics; Quantitative genetics; Resource development; Review; sequence analysis; Single-nucleotide polymorphism; Tree Biology; Trees; Phylogenetics; RADseq; Genome scan; Linkage mapping; Genotyping by sequencing; Population genomics
• ISSN: 1614-2942; 1614-2950
• DOI: 10.1007/s11295-018-1251-3

As tree species vary extensively in genome size, complexity, and resource development, reduced representation methods have been increasingly employed for the generation of population genomic data. By allowing rapid marker discovery and genotyping for thousands of genomic regions in many individuals without requiring genomic resources, restriction site-associated DNA sequencing (RADseq) methods have dramatically improved our ability to bring population genomic perspectives to non-model trees. The rapid recent increase in studies of trees utilizing RADseq suggests that it is likely to become among the most common approaches for generating genome-wide data for a variety of applications. Here we provide a practical review of RADseq and its application to research areas of tree genetics. We briefly review RADseq laboratory methods and consider analytical approaches for assembly, variant calling, and bioinformatic processing. To guide considerations for study design, we use in silico analyses of eight available tree genomes to illustrate how expected marker number and density vary across laboratory approaches and genome sizes, and to consider the ability of RADseq designs to query coding regions. We review the empirical use of RADseq for different research objectives, considering its strengths and limitations. Many studies have used RADseq data to perform genome scans for selection, although limited marker density and linkage disequilibrium will often compromise its utility for such analyses. Regardless of this limitation, RADseq offers a powerful and inexpensive technique for generating genome-wide SNP data that can greatly contribute to research spanning phylogenetic and population genetic inference, linkage mapping, and quantitative genetic parameter estimation for tree genetics.