What is the significance of chromosome number

However, in meiosis, the cycle occurs twice meiosis I and meiosis II before the four haploid daughter cells are produced. Another difference between the stages of mitosis and meiosis is that in meiosis, homologous chromosomes pair up during metaphase instead of chromatids.

In a homologous pair, one chromosome comes from the mother, and one chromosome comes from the father. Homologous chromosomes are very similar, but they are not identical. They carry the same genes eg, hair or eye color , but they may not code for the same trait eg, blonde hair or brown eyes.

Occurs before cell division. Consists of three stages: Gap 1 growth , S phase DNA replication and Gap 2 continues growth, prepares for cell division. Tell us what you think about Healio.

What is a Genome? Whole-Exome Sequencing vs. Visit Healio. Your Module Progress. Module 1. Module Content. A major reason for reproductive difficulty is having either an embryo or a pregnancy with an incorrect number of chromosomes. Why are chromosomes important? Chromosomes are located in the nucleus of each cell containing the DNA comprising genes. Genes are passed from parent to child making each of us unique. In other words, chromosomes make you, you.

Having the correct number of chromosomes is critically important to having a successful pregnancy. If your embryo does not have the correct number of chromosomes then your baby may fail to develop properly. Evolution of European ecosystems during Pleistocene - Holocene transition Rev Bras Genet. Baker RJ, Bickham : Speciation by monobrachial centric fusion.

Wolf KW: The structure of condensed chromosomes in mitosis and meiosis of insects. Int J Insect Morphol Embryol. Lukhtanov VA, Kuznetsova VG: Molecular and cytogenetic approaches to species diagnostics, systematics, and phylogenetics. Zh Obshch Biol. Lukhtanov VA, Kuznetsova VG: What genes and chromosomes say about the origin and evolution of insects and other arthropods. Rieseberg LH: Chromosomal rearrangements and speciation.

Trends Ecol Evol. Faria R, Navarro A: Chromosomal speciation revisited: rearranging theory with pieces of evidence. Lowry DB, Willis JH: A widespread chromosomal inversion polymorphism contributes to a najor life-history transition, local adaptation, and reproductive isolation. Nature Comm. Insect Syst Evol.

Comparative Cytogenetics. Molecular Biology and Genetics of the Lepidoptera. Butterflies of Europe. Edited by: Kudrna O. Mol Mar Biol Biotech. CAS Google Scholar. Ann Ent Soc Am. PCR Protocols: a guide to methods and applications. Biomatters Ltd. Posada D: Collapse: Describing haplotypes from sequence alignments.

Guindon S, Gascuel O: A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. J Mol Evol. Posada D: jModelTest: phylogenetic model averaging. Mol Biol Evol. Am J Human Gen. BMC Evol Biol. Download references. We thank L. Dapporto, A. Bakloushinskaya and V. Kuznetsova for suggestions on the manuscript.

Kaliszewska designed the primers for CAD. Petersburg, Russia. Department of Entomology, St. Petersburg State University, Universitetskaya nab. You can also search for this author in PubMed Google Scholar. All authors read and approved the final manuscript.

Additional file Karyotypes of Leptidea sinapis. Discriminant analysis classification results for chromosomal races of L. List of specimens included in this study. Results of morphometric analysis of the male genitalia.

List of the specimens included in the analysis of geographical longitude vs. PDF KB. This article is published under license to BioMed Central Ltd. Reprints and Permissions.

Lukhtanov, V. Unprecedented within-species chromosome number cline in the Wood White butterfly Leptidea sinapis and its significance for karyotype evolution and speciation. BMC Evol Biol 11, Download citation.

Received : 07 December Accepted : 20 April Published : 20 April Anyone you share the following link with will be able to read this content:. Sorry, a shareable link is not currently available for this article. Provided by the Springer Nature SharedIt content-sharing initiative. Skip to main content. Search all BMC articles Search. Download PDF. Abstract Background Species generally have a fixed number of chromosomes in the cell nuclei while between-species differences are common and often pronounced.

Results We present the discovery of exceptional intraspecific variability in the karyotype of the widespread Eurasian butterfly Leptidea sinapis. Conclusions The discovered system represents the first clearly documented case of explosive chromosome number evolution through intraspecific and intrapopulation accumulation of multiple chromosomal changes.

Background Despite the fundamental role of chromosomal change in eukaryotic evolution, the mechanisms related to this process are still poorly known. Results and Discussion We analyzed the karyotype, mitochondrial and nuclear genetic markers, and the morphology of the Wood White butterfly L. Figure 1. Full size image. Figure 2. Figure 3. Figure 4. Conclusions Given that a chromosomal races of L. A typical ROB combines long arms of two telo- or acrocentric chromosomes by recombination between their centric ends or short arms.

The first translocation product is the fusion chromosome containing two long arms and one or two centromeres monocentric or dicentric ROB. The second product is either an acentric fragment or centromere-containing mini-chromosome, whose elimination due to its small size and absence of essential genes can be tolerated by the translocation carrier.

Thus, ROBs reduce the number of short arms, while increasing the number of metacentric chromosomes, and hence the karyotype symmetry. End-to-end translocation EET; fig.

EETs were deduced from two ancestral chromosomes being tandemly arranged within a single evolutionary younger chromosome. As the head-to-tail collinearity of both ancestral chromosomes remains conserved within the fusion chromosome, recombination between uncapped terminal sequences of two nonhomologous chromosomes is the most plausible pathway of these chromosome fusions.

Except for instances where the two centromeres are in a tight spatial proximity i. The elimination process is not well characterized and epigenetic modifications together with recombination-dependent deletion of centromere-specific nucleosomes and DNA sequences are purported to instantly restore monocentricity of the fusion chromosome Lysak Nested chromosome insertion NCI; fig.

NCIs combine two ancestral nonhomologous chromosomes in a peculiar fashion, superficially appearing as an insertion of one chromosome into the peri centromere of another chromosome Luo et al. Thus, the centromere of the insertion chromosome serves as the functional centromere, whereas the centromere of the recipient chromosome loses its function.

In organisms with monocentric chromosomes, all chromosomal rearrangements increasing or reducing the number of chromosomes must comply with the persistence or elimination of a functional centromere.

In contrast, in organisms with holocentric or holokinetic chromosomes, that is, chromosomes with a kinetochore assembling along the entire chromosome length, dysploid changes are more easily fixed. The frequent fission and fusion events acting on holocentric chromosomes result in long dysploid series of chromosome numbers in some plant genera, such as Carex and Luzula Guerra and references therein , as well as in butterflies Lepidoptera; e. As all inferences of chromosome-number evolution are based on extant chromosome-number variation, all predictions essentially start on a laboratory workbench by establishing chromosome numbers for species in a group of interest.

However, chromosome number itself usually does not provide sufficient information on how the individual chromosomes and the whole karyotypes originated, and how they are related to chromosome complements of other species. Chromosome counting from floral e.

This is often a laborious, time-consuming, and occasionally unsatisfactory procedure e. Although flow-cytometric DNA content estimation cannot substitute chromosome counting Suda et al.

Although chromosome counting and ploidy estimation methods provide the information on the number of chromosomes, chromosome structure and rearrangements underlying chromosome number variation have to be determined through comparative analysis of individual chromosomal DNA molecules. Direct localization of DNA sequences on chromosomes provides an observable evidence of their physical position.

The development of cytogenetic methods used in comparative plant genomics was driven by three principal requirements.

Third, comparative analyses require cross-hybridization of chromosome-specific DNA probes among two or more genomes being compared. This means that intergenome sequence homeology must be sufficiently high to ensure that a probe originating from one genome will target a homeologous chromosomal region in other genomes. Thus, the level of phylogenetic relatedness among the compared genomes is a critical parameter. With the advent of DNA sequencing and DNA cloning technologies, methods of classical comparative cytogenetics have changed for a recent review, see Hu et al.

This conceptual shift transformed classical cytogenetics research into comparative cytogenomics—the discipline of chromosome research capitalizing on multiple whole-genome sequences. Some of these approaches are detailed below. Large-scale chromosome painting to identify entire chromosomes using BAC contigs was established only for crucifers Brassicaceae and grasses Poaceae.

Lysak et al. Later, Pecinka et al. The true power of BAC-based chromosome painting for plant comparative genomics was demonstrated by application of Arabidopsis chromosome-level BAC contigs to analyze karyotypes of other crucifer species fig.

This approach, exploiting low- and single-copy orthologous sequences ancestrally shared among genomes, allows for identification of homeologous chromosome regions and chromosomes. Although comparative cytogenomics in Brassicaceae essentially explored the collinearity between chromosomes of A. Complementary approaches of comparative plant genomics. Capital letters refer to ancestral genomic blocks.

C and D Oligo painting. E Chromosome-scale genome comparison among two strawberry Fragaria and one black raspberry Rubus species revealing the conserved versus corrupted intergenome chromosome collinearity.

All three genomes were sequenced and assembled using the PacBio single-molecule sequencing technique Edger et al. F High-throughput chromosome conformation capture Hi-C map of the Rubus occidentalis genome. Putative locations of centromeres are visible for some of the seven chromosomes. The abundance of dispersed repetitive sequences along plant chromosomes Schubert et al. The low repeat abundance decreases the probability that bona fide chromosome-specific BAC clones will cross-hybridize to nontarget chromosomes.

The ever-increasing number and quality of sequenced genomes opened up a new avenue for comparative cytogenomics. Although most plant genomes are dominated by repeat sequences, usually unsuitable for identification of specific chromosome regions, single- and low-copy coding sequences are chromosome-specific. The oligo painting approach Han et al. Such an oligo library is amplified, labeled by haptens or fluorochromes, and single-stranded labeled oligomers oligo probes are hybridized to the target chromosomes by FISH see Jiang [] for a recent review.

Compared with high-capacity BAC vectors, oligo painting does not require construction of chromosome-specific BAC libraries and subsequent screening to eliminate repeat-rich BAC clones. On the other hand, this methodology requires the availability of a chromosome-level genome sequence, synthesis of high-cost chromosome-specific oligo libraries, and entails several challenging preparatory steps Han et al.

In addition, oligo libraries offer less flexibility in targeting particular shorter chromosome regions compared with chromosome-specific BAC libraries. Oligo painting was successfully used to explore cross-species chromosome collinearity in several model and crop species, such as banana, cucumbers fig. Recently, Bi et al. Such double-stranded oligo probes also generate stronger fluorescent signals compared with single-stranded oligomere probes Han et al. MP-OP represents a cost- and time-effective approach to pinpoint complex collinearity-corrupting chromosomal rearrangements.

In the last two decades, the number and quality of sequenced plant genomes have increased sharply, from the first plant genome A. These sequencing projects have enlightened our view on complex patterns underlying chromosomal evolution. Already the pioneering Arabidopsis sequencing project has identified segmental duplications that pointed to a previously not recognized ancient WGD, followed by genome shuffling and descending dysploidy. The constantly improving quality of genome assemblies allows for unprecedentedly detailed comparisons of chromosome structures among closely related species and across phyla.

This was achieved particularly through single-molecule sequencing platforms producing longer sequence reads e. Aligning genome assemblies of two or more species enables to discover collinearity-corrupting rearrangements and to characterize the corresponding breakpoints with a single-nucleotide accuracy fig.

Thus, sequence-based comparative genomics provides detailed insights into the principles underlying chromosomal evolution. In comparison with comparative cytogenomics, genome sequencing and assembly manifest an increased capability of detecting near-complete spectrum of structural variations, including rearrangements, which were below the detection limit of microscopy-based methodologies, in a time-saving high-throughput manner.

As stated by Hu et al. This is a time-saving and cost-effective approach for identifying the most abundant repeats even from low-coverage whole-genome sequence data.

Conversely, comparative chromosome painting may guide genome assembly fig. Chromosome-specific probes may help to resolve ambiguities during anchoring sequence contigs and scaffolds to pseudochromosomes. Whole-chromosome comparative cytogenomic maps, such as these based on cross-species hybridization of Arabidopsis BAC contigs, guided genome assembly in several Brassicaceae species Dassanayake et al.

The extensive variation in plant chromosome numbers has been extensively exploited for inferring major genomic events, with particular interest toward determining which species are polyploids and which are diploids. Early work examined the distribution of chromosome numbers within a focal group of species and identified one or more denominators that are common to most chromosome counts.

This number, commonly termed x , was regarded as the base number and taken to represent the ancestral haploid genome. Consequently, multiplications of this number were treated as the inferred ploidy level of the species. Alternatively, others have designated a species as polyploid if its haploid number was a multiple of the lowest count found in the examined clade by a predefined factor Stebbins ; Wood et al.

Clearly, such threshold methods suffered from extrapolated ad hoc assumptions, disregarded the relative frequencies of polyploid and dysploid transitions, and frequently disregarded the phylogenetic relationships among the species. More recently, chromosome numbers were analyzed within a phylogenetic context following the maximum parsimony principle Schultheis ; Hansen et al. The use of parsimony allows the reconstruction of chromosome numbers at ancestral nodes and the identification of putative transition events along particular branches of the phylogeny.

However, as has been well discussed in the literature in the context of molecular sequences, the maximum parsimony approach suffers from several drawbacks Felenstein Parsimony does not make use of an explicit model of evolution and thus the same weight is assigned to all state changes: whether they indicate a dysploidy e.

Parsimony ignores branch length information, and thus changes along short branches would be treated similarly as those occurring along very long ones. Similarly, parsimony ignores the possibility of multiple and back transitions occurring along the same branch e. Additionally, the use of parsimony implicitly assumes that the chromosome numbers of extinct ancestral taxa must also be presented in the extant taxa—an assumption that is not necessarily sensible, particularly if rates of chromosome-number change within the group are high.

Over the last decade, methods based on probabilistic models of chromosome number evolution have emerged. These methods are more powerful, as they emulate the evolutionary process along the phylogeny as a stochastic process, while taking into account the mechanisms by which chromosome numbers change. Consequently, the use of such models allows researchers to form and test assumptions regarding the most plausible evolutionary pathways by which the evolution of chromosome numbers have proceeded, while relying on the well-developed machinery of probabilistic statistical inference.

For example, the likelihood ratio test can be used to compare the fit of alternative models, each containing a different set of parameters, to a specific data set at hand Huelsenbeck and Crandall Additionally, once the evolution of chromosome numbers was casted within a probabilistic framework, a generic modeling scheme was created, allowing modeling extensions to be easily implemented and compared.

Several studies have employed general models of character evolution to model the evolution of chromosome numbers in clades in which chromosome fusion and fission events are the main drivers of karyotype change. For example, Hipp had employed a series of Brownian Motion and Ornstein—Uhlenbeck processes to examine the evolution of chromosome numbers in the Cyperaceae sedges , a group characterized by holocentric chromosomes, in which chromosome fusion and fission events are thought to be common and polyploidizations rare see Dysploidy in Groups with Holocentric Chromosomes above.

Rockman and Rowell have examined the evolution of chromosome numbers in Planipapillus velvet worms , a group characterized by frequent centric fusion events, using the Poisson process. In both these groups, in which the dynamics of chromosomal evolution vary across subclades of the phylogeny, the evolutionary patterns of chromosome numbers better fitted a heterogeneous process. In these studies, chromosome numbers were modeled either as ordered categorical variables or as additive quantitative traits, and thus the possibility of integrating biological phenomena reflecting the mechanisms of chromosome-number change into the models was lacking.

A model with a specific focus on the evolution of chromosome numbers was first formulated by Mayrose et al. The chromEvol model is based on a continuous time Markov process, which is defined by a rate matrix that describes the instantaneous rate of change from a genome with i haploid chromosomes to a genome with j haploid chromosomes.

The entries in this matrix are determined based on several parameters that define the rate of change for different types of events fig. The rate matrix allows for the likelihood function to be computed, given a specified phylogeny and assignment of chromosome numbers to the tip taxa. The possible transitions allowed in the chromEvol model. The use of the above simple model already allows for several inference tasks: 1 To obtain the maximum likelihood ML estimates of the rate parameters, allowing the relative frequencies of the different types of events to be compared; 2 To compare the fit of different model variants, each with different constraints on the free parameters, to a particular data set.

Model selection criteria, such as the likelihood ratio test or the Akaike Information Criterion, can then be used to test whether there is a significant evidence for polyploidization in the examined data set; 3 To reconstruct the ancestral chromosome numbers at internal nodes of the tree, including that of the root node.

This can be done either using an ML approach Pupko et al. A tip taxon can be classified as either diploid or polyploid, with respect to the state at the root of the phylogeny, if the expected number of diploid-to-polyploid transitions from the root to the tip is above or below a certain threshold. In initial applications of chromEvol , these thresholds were arbitrarily set as fixed values e. A more sensitive alternative was developed in Glick and Mayrose , in which a simulation-based approach was used to compute the thresholds that are most suitable to the analyzed data.

We note that a probabilistic model of chromosome-number change was also developed by Hallinan and Lindberg This model is based on a background birth—death process allowing for dysploidy transitions that operates along branches of a species tree combined with the possibility of strict doubling events i. This model sums over all possible assignments to ancestral states and over all possible number of dysploidy events, while allowing for the possibility of a single polyploidy transition to occur per branch, and can be used to compute the posterior probability that a polyploidy event occurred on each branch of the phylogeny.

Extension of this model, to include polyploid transitions aside from exact duplications or multiple polyploidy events, is not trivial since the computation over all possible number of duplications and across all types of transitions per branch need to be explicitly formulated.

In the following sections, we thus describe modeling extensions that were developed in the context of the more general chromEvol probabilistic framework. The basic chromEvol model incorporates WGDs that involve exact duplications of the chromosome number.

However, polyploid transitions also involve the fusion of gametes with different ploidies. Two types of transitions were incorporated into model variants that allow for such possibilities. This allows, for example, the generation of a hexaploid from a tetraploid lineage via the fusion of reduced and unreduced gametes, or from a diploid lineage in a two-step process via a triploid bridge followed by genome duplication. Note that demi-polyploidy transitions are well defined only for even haploid numbers, whereas for odd numbers, the transition rate is split between the two alternative possibilities.

Furthermore, this modeling scheme is inadequate for some polyploid transitions that involve the combination of genomes with high ploidy levels. Notably, this modeling scheme also comes with some shortcomings of its own. For example, it assumes that a clade is defined by a single base number. However, it is possible that due to dysploidy transitions, each subclade in an analyzed phylogeny would be characterized by its own base number or that some subclades would exhibit multiple base numbers.

This is in contrast to demi-polyploidy transitions that explicitly account for the current chromosome number of a lineage. Thus, in clades where dysploidy transitions are common, it is conceivable that models that incorporate demi-polyploidy transitions would be better supported than those that include only transitions by an inferred base number. However, because the transitions allowed by the two modeling approaches do not entirely overlap, it is possible that in large clades, in which a large number of parameters could be supported, the inclusion of both transition types would be beneficial.

The basic chromEvol model assumes that dysploidy and polyploidy transitions occur at rates that are identical for all lineages. Although this possibility was not yet incorporated for modeling polyploidy transitions, several possibilities were suggested for dysploidy transitions. For example, as implemented in the model by Hallinan and Lindberg , dysploidy rates are forced to linearly depend on the current number of chromosomes i.

This result suggests that the probability of chromosome fission and fusion events is comparable across genomes with different number of chromosomes. It is thus possible that analyses with larger clades would support the additional model parameters and would allow to determine whether dysploidy rates are more likely to increase in genomes with higher number of chromosomes.

The chromEvol models detailed thus far assume that the transition pattern is identical throughout the phylogeny. This time-homogeneity assumption is rather unlikely, especially when large phylogenies that include several distinct subclades are analyzed.

In such cases, a more realistic approach would allow shifts in the transition pattern: either when different dynamics of chromosome number change are dictated by the presence of a certain organismal trait or when different transition patterns characterize different subclades of the phylogeny fig.

Heterogeneous models of chromosome-number evolution.