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      Vitis Phylogenomics: Hybridization Intensities from a SNP Array Outperform Genotype Calls

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          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 monophyletic, and resolve several previously poorly known relationships among North American species. This study builds on earlier work that applied the Vitis9kSNP array to evolutionary questions within Vitis vinifera and has general implications for addressing ascertainment bias in array-enabled phylogeny reconstruction.

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          Development and Characterization of a High Density SNP Genotyping Assay for Cattle

          The success of genome-wide association (GWA) studies for the detection of sequence variation affecting complex traits in human has spurred interest in the use of large-scale high-density single nucleotide polymorphism (SNP) genotyping for the identification of quantitative trait loci (QTL) and for marker-assisted selection in model and agricultural species. A cost-effective and efficient approach for the development of a custom genotyping assay interrogating 54,001 SNP loci to support GWA applications in cattle is described. A novel algorithm for achieving a compressed inter-marker interval distribution proved remarkably successful, with median interval of 37 kb and maximum predicted gap of <350 kb. The assay was tested on a panel of 576 animals from 21 cattle breeds and six outgroup species and revealed that from 39,765 to 46,492 SNP are polymorphic within individual breeds (average minor allele frequency (MAF) ranging from 0.24 to 0.27). The assay also identified 79 putative copy number variants in cattle. Utility for GWA was demonstrated by localizing known variation for coat color and the presence/absence of horns to their correct genomic locations. The combination of SNP selection and the novel spacing algorithm allows an efficient approach for the development of high-density genotyping platforms in species having full or even moderate quality draft sequence. Aspects of the approach can be exploited in species which lack an available genome sequence. The BovineSNP50 assay described here is commercially available from Illumina and provides a robust platform for mapping disease genes and QTL in cattle.
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            Navigating the tip of the genomic iceberg: Next-generation sequencing for plant systematics.

            Just as Sanger sequencing did more than 20 years ago, next-generation sequencing (NGS) is poised to revolutionize plant systematics. By combining multiplexing approaches with NGS throughput, systematists may no longer need to choose between more taxa or more characters. Here we describe a genome skimming (shallow sequencing) approach for plant systematics. Through simulations, we evaluated optimal sequencing depth and performance of single-end and paired-end short read sequences for assembly of nuclear ribosomal DNA (rDNA) and plastomes and addressed the effect of divergence on reference-guided plastome assembly. We also used simulations to identify potential phylogenetic markers from low-copy nuclear loci at different sequencing depths. We demonstrated the utility of genome skimming through phylogenetic analysis of the Sonoran Desert clade (SDC) of Asclepias (Apocynaceae). Paired-end reads performed better than single-end reads. Minimum sequencing depths for high quality rDNA and plastome assemblies were 40× and 30×, respectively. Divergence from the reference significantly affected plastome assembly, but relatively similar references are available for most seed plants. Deeper rDNA sequencing is necessary to characterize intragenomic polymorphism. The low-copy fraction of the nuclear genome was readily surveyed, even at low sequencing depths. Nearly 160000 bp of sequence from three organelles provided evidence of phylogenetic incongruence in the SDC. Adoption of NGS will facilitate progress in plant systematics, as whole plastome and rDNA cistrons, partial mitochondrial genomes, and low-copy nuclear markers can now be efficiently obtained for molecular phylogenetics studies.
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              A Large Maize (Zea mays L.) SNP Genotyping Array: Development and Germplasm Genotyping, and Genetic Mapping to Compare with the B73 Reference Genome

              SNP genotyping arrays have been useful for many applications that require a large number of molecular markers such as high-density genetic mapping, genome-wide association studies (GWAS), and genomic selection. We report the establishment of a large maize SNP array and its use for diversity analysis and high density linkage mapping. The markers, taken from more than 800,000 SNPs, were selected to be preferentially located in genes and evenly distributed across the genome. The array was tested with a set of maize germplasm including North American and European inbred lines, parent/F1 combinations, and distantly related teosinte material. A total of 49,585 markers, including 33,417 within 17,520 different genes and 16,168 outside genes, were of good quality for genotyping, with an average failure rate of 4% and rates up to 8% in specific germplasm. To demonstrate this array's use in genetic mapping and for the independent validation of the B73 sequence assembly, two intermated maize recombinant inbred line populations – IBM (B73×Mo17) and LHRF (F2×F252) – were genotyped to establish two high density linkage maps with 20,913 and 14,524 markers respectively. 172 mapped markers were absent in the current B73 assembly and their placement can be used for future improvements of the B73 reference sequence. Colinearity of the genetic and physical maps was mostly conserved with some exceptions that suggest errors in the B73 assembly. Five major regions containing non-colinearities were identified on chromosomes 2, 3, 6, 7 and 9, and are supported by both independent genetic maps. Four additional non-colinear regions were found on the LHRF map only; they may be due to a lower density of IBM markers in those regions or to true structural rearrangements between lines. Given the array's high quality, it will be a valuable resource for maize genetics and many aspects of maize breeding.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2013
                13 November 2013
                : 8
                : 11
                : e78680
                Affiliations
                [1 ]Department of Biology, Saint Louis University, St. Louis, Missouri, United States of America
                [2 ]Department of Ecology and Evolutionary Biology and iPlant Collaborative, University of Arizona, Tucson, Arizona, United States of America
                [3 ]United States Department of Agriculture, Agricultural Research Service, Plant Genetic Resources Unit, New York State Agricultural Experiment Station, Cornell University, Geneva, New York, United States of America
                [4 ]United States Department of Agriculture, Agricultural Research Service, National Clonal Germplasm Repository, University of California Davis, Davis, California, United States of America
                [5 ]United States Department of Agriculture, Agricultural Research Service, Grape Genetic Research Unit, New York Agricultural Experiment Station, Cornell University, Geneva, New York, United States of America
                [6 ]Institute for Genomic Diversity, Cornell University, Ithaca, New York, United States of America
                [7 ]Faculty of Agriculture, Dalhousie University, Truro, Canada
                Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, China
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: GZ CS ESB MA SM. Performed the experiments: HS SM. Analyzed the data: NM AM SM. Contributed reagents/materials/analysis tools: GZ CS HS BP MA ESB. Wrote the paper: AM SM.

                Article
                PONE-D-13-26606
                10.1371/journal.pone.0078680
                3827278
                24236035
                96787b52-cb72-4420-bda3-a02ee6467ceb
                Copyright @ 2013

                This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

                History
                : 27 June 2013
                : 15 September 2013
                Page count
                Pages: 11
                Funding
                This article was written, in part, thanks to funding from the Canada Research Chairs program and the National Sciences and Engineering Research Council of Canada. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article

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