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      The Genomic Signature of Crop-Wild Introgression in Maize

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          Abstract

          The evolutionary significance of hybridization and subsequent introgression has long been appreciated, but evaluation of the genome-wide effects of these phenomena has only recently become possible. Crop-wild study systems represent ideal opportunities to examine evolution through hybridization. For example, maize and the conspecific wild teosinte Zea mays ssp. mexicana (hereafter, mexicana) are known to hybridize in the fields of highland Mexico. Despite widespread evidence of gene flow, maize and mexicana maintain distinct morphologies and have done so in sympatry for thousands of years. Neither the genomic extent nor the evolutionary importance of introgression between these taxa is understood. In this study we assessed patterns of genome-wide introgression based on 39,029 single nucleotide polymorphisms genotyped in 189 individuals from nine sympatric maize- mexicana populations and reference allopatric populations. While portions of the maize and mexicana genomes appeared resistant to introgression (notably near known cross-incompatibility and domestication loci), we detected widespread evidence for introgression in both directions of gene flow. Through further characterization of these genomic regions and preliminary growth chamber experiments, we found evidence suggestive of the incorporation of adaptive mexicana alleles into maize during its expansion to the highlands of central Mexico. In contrast, very little evidence was found for adaptive introgression from maize to mexicana. The methods we have applied here can be replicated widely, and such analyses have the potential to greatly inform our understanding of evolution through introgressive hybridization. Crop species, due to their exceptional genomic resources and frequent histories of spread into sympatry with relatives, should be particularly influential in these studies.

          Author Summary

          Hybridization and introgression have been shown to play a critical role in the evolution of species. These processes can generate the diversity necessary for novel adaptations and continued diversification of taxa. Previous research has suggested that not all regions of a genome are equally permeable to introgression. We have conducted one of the first genome-wide assessments of patterns of reciprocal introgression in plant populations. We found evidence that suggests domesticated maize received adaptation to highland conditions from a wild relative, teosinte, during its spread to the high elevations of central Mexico. Gene flow appeared asymmetric, favoring teosinte introgression into maize, and was widespread across populations at putatively adaptive loci. In contrast, genomic regions near known domestication and cross-incompatibility loci appeared particularly resistant to introgression in both directions of gene flow. Crop-wild study systems should play an important role in future studies of introgression due to their well-developed genomic resources and histories of reciprocal gene flow during crop expansion.

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          A fast and flexible statistical model for large-scale population genotype data: applications to inferring missing genotypes and haplotypic phase.

          We present a statistical model for patterns of genetic variation in samples of unrelated individuals from natural populations. This model is based on the idea that, over short regions, haplotypes in a population tend to cluster into groups of similar haplotypes. To capture the fact that, because of recombination, this clustering tends to be local in nature, our model allows cluster memberships to change continuously along the chromosome according to a hidden Markov model. This approach is flexible, allowing for both "block-like" patterns of linkage disequilibrium (LD) and gradual decline in LD with distance. The resulting model is also fast and, as a result, is practicable for large data sets (e.g., thousands of individuals typed at hundreds of thousands of markers). We illustrate the utility of the model by applying it to dense single-nucleotide-polymorphism genotype data for the tasks of imputing missing genotypes and estimating haplotypic phase. For imputing missing genotypes, methods based on this model are as accurate or more accurate than existing methods. For haplotype estimation, the point estimates are slightly less accurate than those from the best existing methods (e.g., for unrelated Centre d'Etude du Polymorphisme Humain individuals from the HapMap project, switch error was 0.055 for our method vs. 0.051 for PHASE) but require a small fraction of the computational cost. In addition, we demonstrate that the model accurately reflects uncertainty in its estimates, in that probabilities computed using the model are approximately well calibrated. The methods described in this article are implemented in a software package, fastPHASE, which is available from the Stephens Lab Web site.
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            Testing for ancient admixture between closely related populations.

            One enduring question in evolutionary biology is the extent of archaic admixture in the genomes of present-day populations. In this paper, we present a test for ancient admixture that exploits the asymmetry in the frequencies of the two nonconcordant gene trees in a three-population tree. This test was first applied to detect interbreeding between Neandertals and modern humans. We derive the analytic expectation of a test statistic, called the D statistic, which is sensitive to asymmetry under alternative demographic scenarios. We show that the D statistic is insensitive to some demographic assumptions such as ancestral population sizes and requires only the assumption that the ancestral populations were randomly mating. An important aspect of D statistics is that they can be used to detect archaic admixture even when no archaic sample is available. We explore the effect of sequencing error on the false-positive rate of the test for admixture, and we show how to estimate the proportion of archaic ancestry in the genomes of present-day populations. We also investigate a model of subdivision in ancestral populations that can result in D statistics that indicate recent admixture.
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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 Genet
                PLoS Genet
                plos
                plosgen
                PLoS Genetics
                Public Library of Science (San Francisco, USA )
                1553-7390
                1553-7404
                May 2013
                May 2013
                9 May 2013
                : 9
                : 5
                : e1003477
                Affiliations
                [1 ]Department of Plant Sciences, University of California Davis, Davis, California, United States of America
                [2 ]Foreign Agricultural Service, United States Department of Agriculture, Washington, D.C., United States of America
                [3 ]Department of Botany and Plant Sciences, University of California Riverside, Riverside, California, United States of America
                [4 ]Genome Center and Center for Population Biology, University of California Davis, Davis, California, United States of America
                University of Georgia, United States of America
                Author notes

                The authors have declared that no competing interests exist.

                Conceived and designed the experiments: MBH PL NCE JR-I. Performed the experiments: MBH PL MTD. Analyzed the data: MBH TP. Contributed reagents/materials/analysis tools: NCE JR-I. Wrote the paper: MBH JR-I.

                Article
                PGENETICS-D-12-02115
                10.1371/journal.pgen.1003477
                3649989
                23671421
                98d7df36-270f-4a84-ae90-fec6b12b6e3c
                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
                : 18 August 2012
                : 12 March 2013
                Page count
                Pages: 13
                Funding
                PL and NCE acknowledge support from UC MEXUS. TP received support from the Academy of Finland. This work was supported by US–NSF grant IOS-0922703 and USDA–National Institute of Food and Agriculture grant 2009-01864. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Computational Biology
                Genomics
                Genome Evolution
                Population Genetics
                Gene Flow
                Ecology
                Plant Ecology
                Evolutionary Biology
                Evolutionary Genetics
                Genetics
                Plant Genetics
                Crop Genetics

                Genetics
                Genetics

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