7.1: Linkage - Biology

7.1:  Linkage - Biology

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As we learned in Chapter 6, Mendel reported that the pairs of loci he observed behaved independently of each other; for example, the segregation of seed color alleles was independent from the segregation of alleles for seed shape. This observation was the basis for his Second Law (Independent Assortment), and contributed greatly to our understanding of heredity. However, further research showed that Mendel’s Second Law did not apply to every pair of genes that could be studied. In fact, we now know that alleles of loci that are located close together on the same chromosome tend to be inherited together. This phenomenon is called linkage, and is a major exception to Mendel’s Second Law of Independent Assortment. Researchers use linkage to determine the location of genes along chromosomes in a process called genetic mapping. The concept of gene linkage is important to the natural processes of heredity and evolution.


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Coupling and Repulsion Hypothesis of Gene

Bateson and Punnett in 1906, described a cross in sweat pea, where failure of gene pairs to assort independently was exhibited. Plants of a sweat pea variety having blue flower (BB) and long pollen (LL) were crossed with those of ano­ther variety having red flower (bb) and round pollen (II). F1 individuals (BbLl) had blue flower and long pollen.

These were test crossed with plants having red flower and round pollen (bbll).

In this case, the character for blue colour of flower is dominant over red colour, and long pollen character is dominant over round pollen. In case of independent assortment, one should expect 1:1:1:1 ratio in test cross. Instead 7:1:1:7 ratio was actually obtained, indicating that there was a tendency of dominant alleles to remain together.

The case was similar for reces­sive alleles also. This deviation was explained in terms of gametic coupling by Bateson.

It was also observed that when two such dominant alleles or recessive alleles come from different parents, they tend to remain separate. This was termed as gametic repulsion. In Bateson’s experiment, in repulsion phase, one parent would have blue flower and round pollen (BBII) and the other would have red flower and long pollen (bbLL).

The results of test cross in such a repulsion phase were similar to those obtained in coupling phase, giving 1:7:7:1 ratio instead of expected 1:1:1:1 (Fig. 8.1).

Bateson explained the lack of independent assortment by means of a hypothesis known as coupling and repulsion hypothesis. Later on, coupling and repulsion were discovered to be two different aspects of linkage.

Autosomal linkage (AQA A-level Biology)

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This clear and concise lesson explains how the inheritance of two or more genes that have loci on the same autosome demonstrates autosomal linkage. The engaging PowerPoint and associated resource have been designed to cover the part of point 7.1 of the AQA A-level Biology specification which states that students should be able to use fully-labelled genetic diagrams to interpret the results of crosses involving autosomal linkage.

This is a topic which can cause confusion for students so time was taken in the design to split the concept into small chunks. There is a clear focus on how the number of original phenotypes and recombinants can be used to determine linkage and suggest how the loci of the two genes compare. Important links to other topics such as crossing over in meiosis are made to enable students to understand how the random formation of the chiasma determines whether new phenotypes will be seen in the offspring or not. Linkage is an important cause of variation and the difference between observed and expected results and this is emphasised on a number of occasions. The main task of the lesson acts as an understanding check where students are challenged to analyse a set of results involving the inheritance of the ABO blood group gene and the nail-patella syndrome gene to determine whether they have loci on the same chromosome and if so, how close their loci would appear to be.

This lesson has been written to tie in with the other 6 lessons from topic 7.1 (Inheritance) and these have also been uploaded

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Topic 7.1: Inheritance (AQA A-level Biology)

This bundle contains 7 lessons which combine to cover the content of topic 7.1 (Inheritance) of the AQA A-level Biology specification. All 7 are fully-resourced and contain differentiated tasks which allow students of differing abilities to access the work whilst being challenged. They have been designed to include a wide range of activities that check the understanding of the current topic as well as making links between other parts of this topics and topics covered earlier in the course. The lessons on codominant and multiple alleles and epistasis are free so you can sample the quality of this bundle before deciding to make a purchase

AQA A-level Biology Topic 7: Genetics, populations, evolution and ecosystems

This bundle contains 14 fully-resourced and detailed lessons that have been designed to cover the content of topic 7 of the AQA A-level Biology specification which concerns genetics, populations, evolution and ecosystems. The wide range of activities included in each lesson will engage the students whilst the detailed content is covered and the understanding and previous knowledge checks allow them to assess their progress on the current topic as well as challenging them to make links to other related topics. Most of the tasks are differentiated to allow differing abilities to access the work and be challenged. The following sub-topics are covered in this bundle of lessons: * The use of genetic terminology * The inheritance of one or two genes in monohybrid and dihybrid crosses * Codominant and multiple alleles * The inheritance of sex-linked characteristics * Autosomal linkage * Epistasis as a gene interaction * The use of the chi-squared test * Calculating allele frequencies using the Hardy-Weinberg principle * Causes of phenotypic variation * Stabilising, directional and disruptive selection * Genetic drift * Allopatric and sympatric speciation * Estimating the size of a population using randomly placed quadrats, transects and the mark-release-recapture method * Conservation of habitats frequently involves the management of succession This is one of the 8 topics which have to be covered over the length of the 2 year course and therefore it is expected that the teaching time for this bundle will be in excess of 2 months If you want to see the quality of the lessons before purchasing then the lessons on codominant and multiple alleles, epistasis and phenotypic variation are free resources to download


Gregor Mendel's Law of Independent Assortment states that every trait is inherited independently of every other trait. But shortly after Mendel's work was rediscovered, exceptions to this rule were found. In 1905, the British geneticists William Bateson, Edith Rebecca Saunders and Reginald Punnett cross-bred pea plants in experiments similar to Mendel's. [1] [2] They were interested in trait inheritance in the sweet pea and were studying two genes—the gene for flower colour (P, purple, and p, red) and the gene affecting the shape of pollen grains (L, long, and l, round). They crossed the pure lines PPLL and ppll and then self-crossed the resulting PpLl lines.

According to Mendelian genetics, the expected phenotypes would occur in a 9:3:3:1 ratio of PL:Pl:pL:pl. To their surprise, they observed an increased frequency of PL and pl and a decreased frequency of Pl and pL:

Bateson, Saunders, and Punnett experiment
Phenotype and genotype Observed Expected from 9:3:3:1 ratio
Purple, long (P_L_) 284 216
Purple, round (P_ll) 21 72
Red, long (ppL_) 21 72
Red, round (ppll) 55 24

Their experiment revealed linkage between the P and L alleles and the p and l alleles. The frequency of P occurring together with L and p occurring together with l is greater than that of the recombinant Pl and pL. The recombination frequency is more difficult to compute in an F2 cross than a backcross, [3] but the lack of fit between observed and expected numbers of progeny in the above table indicate it is less than 50%. This indicated that two factors interacted in some way to create this difference by masking the appearance of the other two phenotypes. This led to the conclusion that some traits are related to each other because of their near proximity to each other on a chromosome.

The understanding of linkage was expanded by the work of Thomas Hunt Morgan. Morgan's observation that the amount of crossing over between linked genes differs led to the idea that crossover frequency might indicate the distance separating genes on the chromosome. The centimorgan, which expresses the frequency of crossing over, is named in his honour.

A linkage map (also known as a genetic map) is a table for a species or experimental population that shows the position of its known genes or genetic markers relative to each other in terms of recombination frequency, rather than a specific physical distance along each chromosome. Linkage maps were first developed by Alfred Sturtevant, a student of Thomas Hunt Morgan.

A linkage map is a map based on the frequencies of recombination between markers during crossover of homologous chromosomes. The greater the frequency of recombination (segregation) between two genetic markers, the further apart they are assumed to be. Conversely, the lower the frequency of recombination between the markers, the smaller the physical distance between them. Historically, the markers originally used were detectable phenotypes (enzyme production, eye colour) derived from coding DNA sequences eventually, confirmed or assumed noncoding DNA sequences such as microsatellites or those generating restriction fragment length polymorphisms (RFLPs) have been used.

Linkage maps help researchers to locate other markers, such as other genes by testing for genetic linkage of the already known markers. In the early stages of developing a linkage map, the data are used to assemble linkage groups, a set of genes which are known to be linked. As knowledge advances, more markers can be added to a group, until the group covers an entire chromosome. [5] For well-studied organisms the linkage groups correspond one-to-one with the chromosomes.

A linkage map is not a physical map (such as a radiation reduced hybrid map) or gene map.

Linkage analysis is a genetic method that searches for chromosomal segments that cosegregate with the ailment phenotype through families and is the analysis technique that has been used to determine the bulk of lipodystrophy genes. [6] [7] It can be used to map genes for both binary and quantitative traits. [7] Linkage analysis may be either parametric (if we know the relationship between phenotypic and genetic similarity) or non-parametric. Parametric linkage analysis is the traditional approach, whereby the probability that a gene important for a disease is linked to a genetic marker is studied through the LOD score, which assesses the probability that a given pedigree, where the disease and the marker are cosegregating, is due to the existence of linkage (with a given linkage value) or to chance. Non-parametric linkage analysis, in turn, studies the probability of an allele being identical by descent with itself.

Parametric linkage analysis Edit

The LOD score (logarithm (base 10) of odds), developed by Newton Morton, [8] is a statistical test often used for linkage analysis in human, animal, and plant populations. The LOD score compares the likelihood of obtaining the test data if the two loci are indeed linked, to the likelihood of observing the same data purely by chance. Positive LOD scores favour the presence of linkage, whereas negative LOD scores indicate that linkage is less likely. Computerised LOD score analysis is a simple way to analyse complex family pedigrees in order to determine the linkage between Mendelian traits (or between a trait and a marker, or two markers).

The method is described in greater detail by Strachan and Read.[1] Briefly, it works as follows:

  1. Establish a pedigree
  2. Make a number of estimates of recombination frequency
  3. Calculate a LOD score for each estimate
  4. The estimate with the highest LOD score will be considered the best estimate

The LOD score is calculated as follows:

NR denotes the number of non-recombinant offspring, and R denotes the number of recombinant offspring. The reason 0.5 is used in the denominator is that any alleles that are completely unlinked (e.g. alleles on separate chromosomes) have a 50% chance of recombination, due to independent assortment. θ is the recombinant fraction, i.e. the fraction of births in which recombination has happened between the studied genetic marker and the putative gene associated with the disease. Thus, it is equal to R / (NR + R) .

By convention, a LOD score greater than 3.0 is considered evidence for linkage, as it indicates 1000 to 1 odds that the linkage being observed did not occur by chance. On the other hand, a LOD score less than −2.0 is considered evidence to exclude linkage. Although it is very unlikely that a LOD score of 3 would be obtained from a single pedigree, the mathematical properties of the test allow data from a number of pedigrees to be combined by summing their LOD scores. A LOD score of 3 translates to a p-value of approximately 0.05, [9] and no multiple testing correction (e.g. Bonferroni correction) is required. [10]

Limitations Edit

Linkage analysis has a number of methodological and theoretical limitations that can significantly increase the type-1 error rate and reduce the power to map human quantitative trait loci (QTL). [11] While linkage analysis was successfully used to identify genetic variants that contribute to rare disorders such as Huntington disease, it did not perform that well when applied to more common disorders such as heart disease or different forms of cancer. [12] An explanation for this is that the genetic mechanisms affecting common disorders are different from those causing some rare disorders. [13]

Recombination frequency is a measure of genetic linkage and is used in the creation of a genetic linkage map. Recombination frequency (θ) is the frequency with which a single chromosomal crossover will take place between two genes during meiosis. A centimorgan (cM) is a unit that describes a recombination frequency of 1%. In this way we can measure the genetic distance between two loci, based upon their recombination frequency. This is a good estimate of the real distance. Double crossovers would turn into no recombination. In this case we cannot tell if crossovers took place. If the loci we're analysing are very close (less than 7 cM) a double crossover is very unlikely. When distances become higher, the likelihood of a double crossover increases. As the likelihood of a double crossover increases we systematically underestimate the genetic distance between two loci.

During meiosis, chromosomes assort randomly into gametes, such that the segregation of alleles of one gene is independent of alleles of another gene. This is stated in Mendel's Second Law and is known as the law of independent assortment. The law of independent assortment always holds true for genes that are located on different chromosomes, but for genes that are on the same chromosome, it does not always hold true.

As an example of independent assortment, consider the crossing of the pure-bred homozygote parental strain with genotype AABB with a different pure-bred strain with genotype aabb. A and a and B and b represent the alleles of genes A and B. Crossing these homozygous parental strains will result in F1 generation offspring that are double heterozygotes with genotype AaBb. The F1 offspring AaBb produces gametes that are AB, Ab, aB, and ab with equal frequencies (25%) because the alleles of gene A assort independently of the alleles for gene B during meiosis. Note that 2 of the 4 gametes (50%)—Ab and aB—were not present in the parental generation. These gametes represent recombinant gametes. Recombinant gametes are those gametes that differ from both of the haploid gametes that made up the original diploid cell. In this example, the recombination frequency is 50% since 2 of the 4 gametes were recombinant gametes.

The recombination frequency will be 50% when two genes are located on different chromosomes or when they are widely separated on the same chromosome. This is a consequence of independent assortment.

When two genes are close together on the same chromosome, they do not assort independently and are said to be linked. Whereas genes located on different chromosomes assort independently and have a recombination frequency of 50%, linked genes have a recombination frequency that is less than 50%.

As an example of linkage, consider the classic experiment by William Bateson and Reginald Punnett. [ citation needed ] They were interested in trait inheritance in the sweet pea and were studying two genes—the gene for flower colour (P, purple, and p, red) and the gene affecting the shape of pollen grains (L, long, and l, round). They crossed the pure lines PPLL and ppll and then self-crossed the resulting PpLl lines. According to Mendelian genetics, the expected phenotypes would occur in a 9:3:3:1 ratio of PL:Pl:pL:pl. To their surprise, they observed an increased frequency of PL and pl and a decreased frequency of Pl and pL (see table below).

Bateson and Punnett experiment
Phenotype and genotype Observed Expected from 9:3:3:1 ratio
Purple, long (P_L_) 284 216
Purple, round (P_ll) 21 72
Red, long (ppL_) 21 72
Red, round (ppll) 55 24

Their experiment revealed linkage between the P and L alleles and the p and l alleles. The frequency of P occurring together with L and with p occurring together with l is greater than that of the recombinant Pl and pL. The recombination frequency is more difficult to compute in an F2 cross than a backcross, [3] but the lack of fit between observed and expected numbers of progeny in the above table indicate it is less than 50%.

The progeny in this case received two dominant alleles linked on one chromosome (referred to as coupling or cis arrangement). However, after crossover, some progeny could have received one parental chromosome with a dominant allele for one trait (e.g. Purple) linked to a recessive allele for a second trait (e.g. round) with the opposite being true for the other parental chromosome (e.g. red and Long). This is referred to as repulsion or a trans arrangement. The phenotype here would still be purple and long but a test cross of this individual with the recessive parent would produce progeny with much greater proportion of the two crossover phenotypes. While such a problem may not seem likely from this example, unfavourable repulsion linkages do appear when breeding for disease resistance in some crops.

The two possible arrangements, cis and trans, of alleles in a double heterozygote are referred to as gametic phases, and phasing is the process of determining which of the two is present in a given individual.

When two genes are located on the same chromosome, the chance of a crossover producing recombination between the genes is related to the distance between the two genes. Thus, the use of recombination frequencies has been used to develop linkage maps or genetic maps.

However, it is important to note that recombination frequency tends to underestimate the distance between two linked genes. This is because as the two genes are located farther apart, the chance of double or even number of crossovers between them also increases. Double or even number of crossovers between the two genes results in them being cosegregated to the same gamete, yielding a parental progeny instead of the expected recombinant progeny. As mentioned above, the Kosambi and Haldane transformations attempt to correct for multiple crossovers. [14] [15]

Linkage of genetic sites within a gene Edit

In the early 1950s the prevailing view was that the genes in a chromosome are discrete entities, indivisible by genetic recombination and arranged like beads on a string. During 1955 to 1959, Benzer performed genetic recombination experiments using rII mutants of bacteriophage T4. He found that, on the basis of recombination tests, the sites of mutation could be mapped in a linear order. [16] [17] This result provided evidence for the key idea that the gene has a linear structure equivalent to a length of DNA with many sites that can independently mutate.

Edgar et al. [18] performed mapping experiments with r mutants of bacteriophage T4 showing that recombination frequencies between rII mutants are not strictly additive. The recombination frequency from a cross of two rII mutants (a x d) is usually less than the sum of recombination frequencies for adjacent internal sub-intervals (a x b) + (b x c) + (c x d). Although not strictly additive, a systematic relationship was observed [19] that likely reflects the underlying molecular mechanism of genetic recombination.

While recombination of chromosomes is an essential process during meiosis, there is a large range of frequency of cross overs across organisms and within species. Sexually dimorphic rates of recombination are termed heterochiasmy, and are observed more often than a common rate between male and females. In mammals, females often have a higher rate of recombination compared to males. It is theorised that there are unique selections acting or meiotic drivers which influence the difference in rates. The difference in rates may also reflect the vastly different environments and conditions of meiosis in oogenesis and spermatogenesis. [ citation needed ]

Genes affecting recombination frequency Edit

Mutations in genes that encode proteins involved in the processing of DNA often affect recombination frequency. In bacteriophage T4, mutations that reduce expression of the replicative DNA polymerase [gene product 43 (gp43)] increase recombination (decrease linkage) several fold. [20] [21] The increase in recombination may be due to replication errors by the defective DNA polymerase that are themselves recombination events such as template switches, i.e. copy choice recombination events. [22] Recombination is also increased by mutations that reduce the expression of DNA ligase (gp30) [23] [21] and dCMP hydroxymethylase (gp42), [20] [21] two enzymes employed in DNA synthesis.

Recombination is reduced (linkage increased) by mutations in genes that encode proteins with nuclease functions (gp46 and gp47) [23] [21] and a DNA-binding protein (gp32) [21] Mutation in the bacteriophage uvsX gene also substantially reduces recombination. [24] The uvsX gene is analogous to the well studied recA gene of Escherichia coli that plays a central role in recombination. [25]

With very large pedigrees or with very dense genetic marker data, such as from whole-genome sequencing, it is possible to precisely locate recombinations. With this type of genetic analysis, a meiosis indicator is assigned to each position of the genome for each meiosis in a pedigree. The indicator indicates which copy of the parental chromosome contributes to the transmitted gamete at that position. For example, if the allele from the 'first' copy of the parental chromosome is transmitted, a '0' might be assigned to that meiosis. If the allele from the 'second' copy of the parental chromosome is transmitted, a '1' would be assigned to that meiosis. The two alleles in the parent came, one each, from two grandparents. These indicators are then used to determine identical-by-descent (IBD) states or inheritance states, which are in turn used to identify genes responsible for diseases.

Gene Linkage 2.

Drosophila Experiments on Gene Linkage

Use an online fly lab to repeat some of the experiments which helped Thomas Hunt Morgan in the discovery of linked genes, and the recognition of the role of chromosomes. Students learn that sometimes alleles are not independently assorted. Drosophila eye colour is one example. The connection between parent phenotypes, F1 phenotypes and recombinant genotypes is illustrated using historical experiments. Linkage notation is also introduced.

Lesson Description

Guiding Questions

Explain this prediction, &ldquoThe association of chromosomes in pairs and their subsequent separation during [meiosis] may be the physical basis of the Mendelian law of heredity.&rdquo Sutton, W. S. 1902.

Why did it take Thomas Hunt Morgan eight years of fly crossing experiments before he could be confident that his evidence supported his idea that alleles can be linked on chromosomes?

Activity 1 - Simulated breeding experiments with Drosophila

These slides give a step by step guide to the first part of the activity on the Drosophila experiments of Thomas hunt Morgan.

Use the slides alongside the animation and the worksheet The discovery of linked genes - Morgan 1910 below.

Morgan fly lab - instructions slides:

Morgan fly lab - instructions slides:

Morgan fly lab - instructions slides:

Morgan fly lab - instructions slides:

Morgan fly lab - instructions slides:

Morgan fly lab - instructions slides:

Morgan fly lab - instructions slides:

Morgan fly lab - instructions slides:

Morgan fly lab - instructions slides:

Morgan fly lab - instructions slides:

Morgan fly lab - instructions slides:

Morgan fly lab - instructions slides:

Morgan fly lab - instructions slides:

Morgan fly lab - instructions slides:

Morgan fly lab - instructions slides:

Morgan fly lab - instructions slides:

Morgan fly lab - instructions slides:

Morgan fly lab - instructions slides:

Morgan fly lab - instructions slides:

Morgan fly lab - instructions slides:

Use this online simulation with the slides to carry out the experiments

Keep a record of the results of the simulation experiments on this worksheet The discovery of linked genes - Morgan 1910. Answer the questions on the worksheet.

Does the data collected support the idea that inheritance of sex and of other genetic traits depends on the chromosomes?

Activity 2 - Can female fruit flies have white eyes?

Continue using the online simulation with these extra slides to carry out some more advanced crosses with Drosophila.

Morgan fly lab further instructions:

Morgan fly lab further instructions:

Morgan fly lab further instructions:

Morgan fly lab further instructions:

Morgan fly lab further instructions:

Morgan fly lab further instructions:

Morgan fly lab further instructions:

Morgan fly lab further instructions:

Morgan fly lab further instructions:

Morgan fly lab further instructions:

Morgan fly lab further instructions:

Morgan fly lab further instructions:

Morgan fly lab further instructions:

Morgan fly lab further instructions:

Morgan fly lab further instructions:

Morgan fly lab further instructions:

Activity 3 - Extra reading about linkage notation.

If this is the first time students have seen this notation then the following slides will be some help:

These six slides explain clearly how the genes for some characteristics of Drosophila are linked to others

Activity 4 - Further online breeding experiments with Drosophila flies

This is a more advanced online Drosophila breeding lab. Use it to find out about Drosophila traits and other Drosophila experiments. The computer calculated chi squared values are nice too.

This is a video introduction.

This is the simulation itself. Click the link.

Teachers' notes

This activity is designed to help students develop the skill of using chi squared tests of goodness of fit to evaluate whether evidence from genetic experiments actually supports an hypothesis or not.

Students will also learn to predict phenotype ratios, recombinant phenotypes, parental phenotypes and to identify gene linkage when it appears in data from di-hybrid genetics experiments.

The introductory powerpoint is designed to be projected by the teacher while students follow the worksheet which explains how to make predictions and how to test the results. Details of using the simulations for the breeding experiments are outlined in the powerpoint.

The worksheet outlines the story of genetic experiments carried out on Drosophila flies over 17 years by Thomas hunt Morgan in the USA. He was the first to find conclusive experimental proof of gene linkage and later went on to map the positions of genes on chromosomes before winning the Nobel Prize. There are points worth making here about International Mindedness and the nature of scientific discovery.

The Drosophila simulations in activity 3 will give a useful extension for faster students.
There is a wide range of Drosophila activities possible in this animation.

I'm working on some model answers which can be seen on this page: Gene linkage 2 - model answers

3.7.1 Genetics 3 - Linkage, Gender and Sex Linkage

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Repetitive elements form a major fraction of eukaryotic genomes. Though once dismissed as mere junk DNA, they are now recognized as "drivers of genome evolution" [1] whose evolutionary role can be "symbiotic (rather than parasitic)" [2]. Examples of potentially beneficial evolutionary events in which repetitive elements have been implicated include genome rearrangements [1], gene-rich segmental duplications [3], random drift to new biological function [4, 5] and increased rate of evolution during times of stress [6, 7]. For these and other reasons, the study of repeat elements and their evolution is now emerging as a key area in evolutionary biology.

Individual repeat elements can be grouped into repeat families, each defined by the consensus sequence of its diverged copies. Repeat family libraries, such as Repbase Update libraries [8, 9] and RepeatMasker libraries [10], contain consensus sequences of known repeat families. Repeat families often contain shared subsequences, which we call repeat domains. Repeat domains can occur more than once within the same repeat family for example, the ubiquitous human Alu family is dimeric [11]. There are a number of cases of repeat families whose repeat domains are known to have different biological origins, for example, from repeat families with different modes of replication or from distinct retrovirus families. These repeat families and the domains they share are worthy of special attention, since they are assumed to result from interesting evolutionary events. We define a repeat family to be a composite repeat if it contains at least two repeat domains of different biological origin. Of course, discerning the biological origin of a repeat domain is a challenging endeavor. Nevertheless, human Repbase Update documents more than 10 repeat families as composite repeats, including the RICKSHA and Harlequin families. Many other composite repeats contain fragments from different retroviruses. Since composite repeats that contain only fragments of retroviral origin are probably products of retroviral recombinations, these are documented in Repbase Update as retroviral recombinations (see [12] for a review). Composite repeats are likely more than a mere curiosity: one composite repeat, SVA, is the third most active retrotransposon since the human/chimpanzee speciation [13]. An additional example is found in the eel where a composite SINE repeat family borrowed a repeat domain from a different LINE family this borrowed domain was experimentally shown to greatly enhance the retrotransposition rate of the SINE family [14].

Shared repeat domains yield important insights into repeat evolution, in the same way that multidomain protein organization yields insights into protein evolution [15, 16]. However, while the study of protein domains is a well-established research area, the study of repeat domains is still in its infancy. Indeed, RepeatGluer [17] is the only existing algorithm for repeat domain analysis. While RepeatGluer shows promise as a tool for repeat domain analysis, it is computationally intractable for large genomes. For large genomes, we propose that instead of identifying repeat domains de novo from genomic sequence, we identify repeat domains by analyzing repeat family libraries that are obtained via other means.

The main challenge in the analysis of repeat domains is that repeat family consensus sequences typically form a complex mosaic of shared subsequences. This mosaic structure is reminiscent of the mosaic structure of segmental duplications in mammalian genomes [18] (H Tang, Z Jiang, EE Eichler, submitted). Standard sequence comparison tools are unable to capture mosaic structure. These tools reveal local similarities between different repeat families, but do not reveal the structure of shared repeat domains between different families. For example, although a dot plot of the sequences of the 11 Caenorhabditis elegans and C. briggsae repeat families sharing repeat domains (Figure 1) contains essentially all the information about these repeat families, it is not well-organized and leaves one puzzled about what the repeat domains are. Thus, identifying repeat domains is an important and unsolved problem.

Dot plot of 11 concatenated repeat family sequences from C. elegans and C. briggsae shows the presence of shared repeat domains. Our repeat domain graph of the same set of sequences is shown in Figure 5.

In this paper, we propose a new framework for analyzing a library of repeat families to identify the mosaic structure of its shared repeat domains. Our main idea is to represent a repeat library by a repeat domain graph that reveals all repeat domains as edges (lines linking between nodes) of the graph, and indicates the order(s) in which those domains appear in the corresponding repeat famili(es). For example, Figure 2 illustrates the domain structure of a selected subset of repeat families sharing repeat domains with the RICKSHA family, and the corresponding repeat domain graph. We describe a method to construct the repeat domain graph from a set of repeat sequences, and we demonstrate methods for analyzing the topology of the repeat domain graph that lead to hypotheses about repeat biology. We apply our method to single-species analyses of human and C. elegans repeat family libraries. Our method recovers documented composite repeats in Repbase Update [8, 9] and suggests a number of additional putative shared repeat domains in human and C. elegans. In addition, we use our method to perform a cross-species comparative analysis of C. elegans and C. briggsae repeat libraries, and we find a putative ancient repeat domain shared between C. elegans and C. briggsae. We also demonstrate the application of our method in assisting annotation of repeat libraries that are generated de novo from genomic sequence. As numerous new genomes are sequenced and repeat family libraries are automatically constructed, the applications of our method will multiply.

Repeat domain structure and repeat domain graph. (a) Diagram of repeat domains shared between RICKSHA and other repeat families. RICKSHA and RICKSHA_0 have 79 bp inverted terminal repeats. In addition, RICKSHA shares some sequences from retroviral elements ERVL and MLT2B. (b) Repeat domain graph of the same set of sequences. Each sequence is represented by a path from a source to a sink vertex, where source and sinks are labeled with the ID number in (a). Negative signs refer to the reverse complement sequences (see Results section). Similar parts between sequences are glued into shared edges. Edge label: the number inside the parentheses is the multiplicity and the number outside the parentheses is the length, multiplicity one is omitted.


Department of Biopharmaceutical Sciences, University of California, 1700 4th Street, San Francisco, San Francisco, CA, 94143-2550, USA

Department of Biochemistry, University of Illinois, Roger Adams Laboratory, 600 S Mathews Avenue, Urbana, IL, 61801, USA

Department of Biochemistry, Molecular Biology, and Biophysics, Biological Process Technology Institute, and Center for Microbial and Plant Genomics, University of Minnesota, St Paul, MN, 55108, USA

Departments of Biopharmaceutical Sciences and Pharmaceutical Chemistry, University of California, 1700 4th Street, San Francisco, San Francisco, CA, 94143-2550, USA

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