|MILLER, ALLISON - St Louis University|
|MATASCI, NAIM - University Of Arizona|
|Prins, Bernard - Bernie|
|SIMON, CHARLES - Former ARS Employee|
|Buckler, Edward - Ed|
|MYLES, SEAN - Dalhousie University|
Submitted to: PLOS ONE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/15/2013
Publication Date: 11/13/2013
Publication URL: http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0078680
Citation: Miller, A., Matasci, N., Schwaninger, H.R., Aradhya, M.K., Prins, B.H., Zhong, G., Simon, C., Buckler IV, E.S., Myles, S. 2013. Vitis phylogenomics: hybridization intensities from a SNP array outperform genotype calls. PLoS One. doi: 10.1371/journal.pone.0078680.
Interpretive Summary: Grapes have many wild relatives. These wild relatives are important sources of genes to be introduced into cultivated grapes for improving resistance to diseases and pests, tolerance to unfavorable growing conditions, fruit quality and productivity. Understanding relationships among cultivated and wild grape species can help accelerate the speed for introducing useful genes from wild grapes to cultivated ones. One approach to study the relationships among grape species is to compare profiles of various grape species using molecular markers such as single nucletodie polymorphisms or SNPs. To reduce costs in obtaining the profiles of SNPs across many different grape species and accessions, we usually first identify SNPs in a subset of individuals, and then to compile these SNPs on an array that can be used to obtain SNP profiles for additional samples at hundreds or thousands of different genomic sites simultaneously through the so-called ‘hybridization’ process. Grape samples which contain similar SNPs as the initial subset of individuals will show positive signals (presence of a hybridization signal) on an array after hybridation, suggesting that these grape samples are related to each other. Although powerful and efficient, this method is subject to ascertainment bias because applying variation discovered in a representative subset to a larger sample favors identification of SNPs with high minor allele frequencies and introduces bias against rare alleles. In this study, we demonstrate that the use of signal intensity data, rather than signal presence or absence, reduces the effects of ascertainment bias. We compared both methods, using the Vitis9kSNP array previously developed for grapes, to show the effects of ascertainment bias in reconstructing evolutionary relationships among grape species. We demonstrated that the relationships revealed among grape species by using SNP hybridization intensities suffer less from the distorting effects of ascertainment bias, and are thus more accurate, than the one based on presence or ansence of the hybridization signals.
Technical Abstract: Understanding relationships among species is a fundamental goal of evolutionary biology. Single nucleotide polymorphisms (SNPs) identified through next generation sequencing and related technologies enable phylogeny reconstruction by providing unprecedented numbers of characters for analysis. One approach to SNP-based phylogeny reconstruction is to identify SNPs in a subset of individuals, and then to compile SNPs on an array that can be used to genotype additional samples at hundreds or thousands of sites simultaneously. Although powerful and efficient, this method is subject to ascertainment bias because applying variation discovered in a representative subset to a larger sample favors identification of SNPs with high minor allele frequencies and introduces bias against rare alleles. Here, we demonstrate that the use of hybridization intensity data, rather than genotype calls, reduces the effects of ascertainment bias. Whereas traditional SNP calls assess known variants based on diversity housed in the discovery panel, hybridization intensity data survey variation in the broader sample pool, regardless of whether those variants are present in the initial SNP discovery process. We apply SNP genotype and hybridization intensity data derived from the Vitis9kSNP array developed for grape to show the effects of ascertainment bias and to reconstruct evolutionary relationships among Vitis species. We demonstrate that phylogenies constructed using hybridization intensities suffer less from the distorting effects of ascertainment bias, and are thus more accurate, than phylogenies based on genotype calls. Moreover, we reconstruct the phylogeny of the genus Vitis using hybridization data, show that North American subgenus Vitis species are indeed monophyletic, and resolve several previously unknown relationships among North American species. This study builds on previous work that applied the Vitis9kSNP array to evolutionary questions within Vitis and has general implications for addressing ascertainment bias in array-enabled phylogeny reconstruction.