Patterns and Processes of Diploidization in Land Plants

Most land plants are now known to be ancient polyploids that have rediploidized. Diploidization involves many changes in genome organization that ultimately restore bivalent chromosome pairing and disomic inheritance, and resolve dosage and other issues caused by genome duplication. In this review, we discuss the nature of polyploidy and its impact on chromosome pairing behavior. We also provide an overview of two major and largely independent processes of diploidization: cytological diploidization and genic diploidization/fractionation. Finally, we compare variation in gene fractionation across land plants and highlight the differences in diploidization between plants and animals. Altogether, we demonstrate recent advancements in our understanding of variation in the patterns and processes of diploidization in land plants and provide a road map for future research to unlock the mysteries of diploidization and eukaryotic genome evolution.

AlloMap6: an R package for genetic linkage analysis in allohexaploids

Allopolyploids are a group of polyploids with more than two sets of chromosomes derived from different species. Previous linkage analysis of allopolyploids is based on the assumption that different chromosomes pair randomly during meiosis. A more sophisticated model to relax this assumption has been developed for allotetraploids by incorporating the preferential pairing behavior of homologous over homoeologous chromosomes. Here, we show that the basic principle of this model can be extended to perform linkage analysis of higher-ploidy allohexaploids, where multiple preferential pairing factors are used to characterize chromosomal-pairing meiotic features between different constituent species. We implemented the extended model into an R package, called AlloMap6, allowing the recombination fractions and preferential pairing factors to be estimated simultaneously. Allomap6 has two major functionalities, computer simulation and real-data analysis. By analyzing a real data from a full-sib family of allohexaploid persimmon, we tested and validated the usefulness and utility of this package. AlloMap6 lays a foundation for allohexaploid genetic mapping and provides a new horizon to explore the chromosomal kinship of allohexaploids.

Natural pathways to polyploidy in plants and consequences for genome reorganization

The last decade highlighted polyploidy as a rampant evolutionary process that triggers drastic genome reorganization, but much remains to be understood about their causes and consequences in both autopolyploids and allopolyploids. Here, we provide an overview of the current knowledge on the pathways leading to different types of polyploids and patterns of polyploidy-induced genome restructuring and functional changes in plants. Available evidence leads to a tentative 'diverge, merge and diverge' model supporting polyploid speciation and stressing patterns of divergence between diploid progenitors as a suitable predictor of polyploid genome reorganization. The merging of genomes at the origin of a polyploid lineage may indeed reveal different kinds of incompatibilities (chromosomal, genic and transposable elements) that have accumulated in diverging progenitors and reduce the fitness of nascent polyploids. Accordingly, successful polyploids have to overcome these incompatibilities through non-Mendelian mechanisms, fostering polyploid genome reorganization in association with the establishment of new lineages. See also sister article focusing on animals by Collares-Pereira et al., in this themed issue.

Statistical models for genetic mapping in polyploids: challenges and opportunities

Statistical methods for genetic mapping have well been developed for diploid species but are lagging in the more complex polyploids. The genetic mapping of polyploids, where genome number is higher than two, is complicated by uncertainty about the genotype-phenotype correspondence, inconsistent meiotic mechanisms, heterozygous genome structures, and increased allelic (action) and nonallelic (interaction) combinations. According to their meiotic configurations, polyploids can be classified as bivalent polyploids, in which only two chromosomes pair during meiosis at a time, and multivalent polyploids, where multiple chromosomes pair simultaneously. For some polyploids, these two types of pairing occur at the same time, leading to a mixed category. This chapter reviews several challenges due to the complexities of linkage analysis in polyploids and describes statistical models and algorithms that have been developed for linkage mapping based on their distinct meiotic characteristics. We discuss several issues that should be addressed to better understand the genome structure and organization of polyploids and the genetic architecture of complex traits for this unique group of plants.

A bivalent polyploid model for linkage analysis in outcrossing tetraploids

Polyploids can be classified as either allopolyploids or autopolyploids based on their presumed origins. From a perspective of linkage analysis, however, the nature of polyploids can be better described as bivalent polyploids, in which two chromosomes pair at meiosis, multivalent polyploids, in which more than two chromosomes pair, and general polyploids, in which bivalent and multivalent formations occur simultaneously. In this paper, we develop a statistical method for linkage analysis of polymorphic markers in bivalent polyploids. This method takes into account a unique cytological pairing mechanism for the formation of diploid gametes in tetraploids-preferential bivalent pairings at meiosis during which two homologous chromosomes pair with a higher probability than two homoeologous chromosomes. The higher frequency of homologous over homoeologous pairing, defined as the preferential pairing factor, affects the segregation patterns and linkage analysis of different genes on the same chromosome. A maximum likelihood method implemented with the EM algorithm is proposed to simultaneously estimate linkage and parental linkage phases over a pair of markers from any possible marker cross type between two outbred bivalent tetraploid parents demonstrating preferential bivalent pairings. Simulation studies display that the method can be well used to estimate the recombination fraction between different marker types and the preferential pairing factor typical of bivalent tetraploids. The implications of this method for current genome projects in polyploid species are discussed.

Were vertebrates octoploid?

It has long been suggested that gene and genome duplication play important roles in the evolution of organismal complexity. For example, work by Ohno proposed that two rounds of whole genome doubling (tetraploidy) occurred during the evolution of vertebrates: the extra genes permitting an increase in physiological and anatomical complexity. Several modifications of this 'two tetraploidies' hypothesis have been proposed, taking into account accumulating data, and there is wide acceptance of the basic scheme. In the past few years, however, several authors have raised doubts, citing lack of direct support or even evidence to the contrary. Here, we review the evidence for and against the occurrence of tetraploidies in early vertebrate evolution, and present a new compilation of molecular phylogenetic data for amphioxus. We argue that evidence in favour of tetraploidy, based primarily on genome and gene family analyses, is strong. Furthermore, we show that two observations used as evidence against genome duplication are in fact compatible with the hypothesis: but only if the genome doubling occurred by two closely spaced sequential rounds of autotetraploidy. We propose that early vertebrates passed through an autoautooctoploid phase in the evolution of their genomes.

A general polyploid model for analyzing gene segregation in outcrossing tetraploid species

Polyploidy has played an important role in higher plant evolution and applied plant breeding. Polyploids are commonly categorized as allopolyploids resulting from the increase of chromosome number through hybridization and subsequent chromosome doubling or autopolyploids due to chromosome doubling of the same genome. Allopolyploids undergo bivalent pairing at meiosis because only homologous chromosomes pair. For autopolyploids, however, all homologous chromosomes can pair at the same time so that multivalents and, therefore, double reductions are formed. In this article, we use a maximum-likelihood method to develop a general polyploid model for estimating gene segregation patterns from molecular markers in a full-sib family derived from an arbitrary polyploid combining meiotic behaviors of both bivalent and multivalent pairings. Two meiotic parameters, one describing the preference of homologous chromosome pairing (expressed as the preferential pairing factor) typical of allopolyploids and the other specifying the degree of double reduction of autopolyploids, are estimated. The type of molecular markers used can be fully informative vs. partially informative or dominant vs. codominant. Simulation studies show that our polyploid model is well suited to estimate the preferential pairing factor and the frequency of double reduction at meiosis, which should help to characterize gene segregation in the progeny of autopolyploids. The implications of this model for linkage mapping, population genetic studies, and polyploid classification are discussed.

MicroMeasure: A new computer program for the collection and analysis of cytogenetic data

The ability to identify individual chromosomes in cytological preparations is an essential component of many investigations. While several computer software applications have been used to facilitate such quantitative karyotype analysis, most of these programs are limited by design for specific types of analyses, or can be used only with specific hardware configurations. MicroMeasure is a new image analysis application that may be used to collect data for a wide variety of chromosomal parameters from electronically captured or scanned images. Unlike similar applications, MicroMeasure may be individually configured by the end user to suit a wide variety of research needs. This program can be used with most common personal computers, and requires no unusual or specific hardware. MicroMeasure is made available to the research community without cost by the Department of Biology at Colorado State University via the World Wide Web at http://www.biology.colostate.edu/MicroMeasure.Key words: MicroMeasure, computer program, chromosome measurement, cytogenetics.