Resolved phylogenetic relationships in the Ocotea complex (Supraocotea) facilitate phylogenetic classification and studies of character evolution.

PREMISE: The Ocotea complex contains the greatest diversity of Lauraceae in the Neotropics. However, the traditional taxonomy of the group has relied on only three main floral characters, and previous molecular analyses have used only a few markers and provided limited support for relationships among the major clades. This lack of useful data has hindered the development of a comprehensive classification, as well as studies of character evolution. METHODS: We used RAD-seq data to infer the phylogenetic relationships of 149 species in the Ocotea complex, generating a reference-based assembly using the Persea americana genome. The results provide the basis for a phylogenetic classification that reflects our current molecular knowledge and for analyses of the evolution of breeding system, stamen number, and number of anther locules. RESULTS: We recovered a well-supported tree that demonstrates the paraphyly of Licaria, Aniba, and Ocotea and clarifies the relationships of Umbellularia, Phyllostemonodaphne, and the Old World species. To begin the development of a new classification and to facilitate precise communication, we also provide phylogenetic definitions for seven major clades. Our ancestral reconstructions show multiple origins for the three floral characters that have routinely been used in Lauraceae systematics, suggesting that these be used with caution in the future. CONCLUSIONS: This study advances our understanding of phylogenetic relationships and character evolution in a taxonomically difficult group using RAD-seq data. Our new phylogenetic names will facilitate unambiguous communication as studies of the Ocotea complex progress.

Sequence coverage required for accurate genotyping by sequencing in polyploid species.

Polyploidy plays an important role in the evolution of eukaryotes, especially for flowering plants. Many of ecologically or agronomically important plant or crop species are polyploids, including sycamore maple (tetraploid), the world second and third largest food crops wheat (hexaploid) and potato (tetraploid) as well as economically important aquaculture animals such as Atlantic salmon and trout. The next generation sequencing data enables to allocate genotype at a sequence variant site, known as genotyping by sequencing (GBS). GBS has stimulated enormous interests in population based genomics studies in almost all diploid and many polyploid organisms. DNA sequence polymorphisms are codominant and thus fully informative about the underlying genotype at the polymorphic site, making GBS a straightforward task in diploids. However, sequence data may usually be uninformative in polyploid species, making GBS a far more challenging task in polyploids. This paper presents novel and rigorous statistical methods for predicting the number of sequence reads needed to ensure accurate GBS at a polymorphic site bared by the reads in polyploids and shows that a dozen of reads can ensure a probability of 95% to recover all constituent alleles of any tetraploid genotype but several hundreds of reads are needed to accurately uncover the genotype with probability confidence of 90%, subverting the proposition of GBS using low coverage sequence data in the literature. The theoretical prediction was tested by use of RAD-seq data from tetraploid potato cultivars. The paper provides polyploid experimentalists with theoretical guides and methods for designing and conducting their sequence-based studies.

Sampling Variation of RAD-Seq Data from Diploid and Tetraploid Potato (Solanum tuberosum L.).

The new sequencing technology enables identification of genome-wide sequence-based variants at a population level and a competitively low cost. The sequence variant-based molecular markers have motivated enormous interest in population and quantitative genetic analyses. Generation of the sequence data involves a sophisticated experimental process embedded with rich non-biological variation. Statistically, the sequencing process indeed involves sampling DNA fragments from an individual sequence. Adequate knowledge of sampling variation of the sequence data generation is one of the key statistical properties for any downstream analysis of the data and for implementing statistically appropriate methods. This paper reports a thorough investigation on modeling the sampling variation of the sequence data from the optimized RAD-seq (Restriction sit associated DNA sequencing) experiments with two parents and their offspring of diploid and autotetraploid potato (Solanum tuberosum L.). The analysis shows significant dispersion in sampling variation of the sequence data over that expected under multinomial distribution as widely assumed in the literature and provides statistical methods for modeling the variation and calculating the model parameters, which may be easily implemented in real sequence datasets. The optimized design of RAD-seq experiments enabled effective control of presentation of undesirable chloroplast DNA and RNA genes in the sequence data generated.