Algebraic Distribution of Segmental Duplication Lengths in Whole-Genome Sequence Self-Alignments

Gao, Kun; Miller, Jonathan

doi:10.1371/journal.pone.0018464

Cited by 24 publications

(34 citation statements)

References 44 publications

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“…statistical signature; i.e., it is well described by a power law with exponent À3 (black curve in Fig. 1), which can also be found in other species and was first reported by Gao and Miller [14]. Given this empirical result and considering that it only holds over one order of magnitude, it is reasonable to question if a meaningful model can be developed that also explains this finding mathematically; see Ref.…”

supporting

confidence: 64%

Neutral Evolution of Duplicated DNA: An Evolutionary Stick-Breaking Process Causes Scale-Invariant Behavior

Massip

Arndt

2013

Phys. Rev. Lett.

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Recently, an enrichment of identical matching sequences has been found in many eukaryotic genomes. Their length distribution exhibits a power law tail raising the question of what evolutionary mechanism or functional constraints would be able to shape this distribution. Here we introduce a simple and evolutionarily neutral model, which involves only point mutations and segmental duplications, and produces the same statistical features as observed for genomic data. Further, we extend a mathematical model for random stick breaking to analytically show that the exponent of the power law tail is À3 and universal as it does not depend on the microscopic details of the model. DOI: 10.1103/PhysRevLett.110.148101 PACS numbers: 87.10.Vg, 87.10.Ca, 87.18.Wd, 87.23.Kg Ever since Susumu Ohno wrote his influential book to highlight the role of gene duplication in evolution [1], it has been well recognized that duplication and subsequent change of genetic material allow the exploration of evolutionary trajectories not accessible by point mutations only. Having completed the sequencing of the human genome, we know today that about 5% of primate genomes are composed of so-called segmental duplications often spanning tens of kbp [2,3]. The majority of those duplications are thought to have no direct function. In contrast to the very rich discussion about ''the evolutionary fate and consequences of duplicated genes' ' [4], the destiny of duplicated nonfunctional DNA segments is in the majority of cases clear: they will dissolve into the genomic background by random mutations. However, as we show in this Letter, this dispersion process generates interesting statistical properties of the length distribution of identical sequence segments in genomes, which exhibits scale invariance with an integer exponent. We argue that this distribution is the characteristic mark of processes that are continuous and perpetual on evolutionary time scales and generate segmental duplications of genetic material and disperse them by random mutations into the genomic background.Just after its duplication, a duplicated sequence segment will start out 100% identical to its original; subsequently random nucleotide substitutions and small scale insertions or deletions will break it into two and then more pieces, each being still identical to the corresponding segment in the original. This dispersion process can easily be observed in sequenced genomes when considering maximal segments of exactly matching nucleotides, i.e., copies of sequence segments that are equal over their entire length but differ on both ends. Such identical matches can easily be found using, for example, a gapless local alignment algorithm with infinite mismatch costs [5]. More advanced techniques employing suffix trees [6] or word counts are considerably faster for counting long and short segments, respectively. Independent of the algorithm, a selfalignment will include the global match along the diagonal of the alignment grid but will also show smaller (offdiagonal) matches repre...

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supporting

confidence: 64%

Neutral Evolution of Duplicated DNA: An Evolutionary Stick-Breaking Process Causes Scale-Invariant Behavior

Massip

Arndt

2013

Phys. Rev. Lett.

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“…A main evolutionary force of genome evolution that we have not considered so far is sequence duplication. Genomic duplication is a major source of genomic rearrangements and it is quite common across the whole phylogenetic tree [33,34].…”

Section: Genomic Duplication Is the Key Ingredient To Explain The mentioning

confidence: 99%

Genomic duplications shaped current retrotransposon position distribution in human

Riba

Fumagalli

Caselle³

et al. 2019

Preprint

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† These authors contributed equally to this work.Retrotransposons, DNA sequences capable of creating copies of themselves, compose about half of the human genome and played a central role in the evolution of mammals. Their current position in the host genome is the result of the retrotranscription process and of the following host genome evolution. We apply a model from statistical physics to show that the genomic distribution of the two most populated classes of retrotransposons in human deviates from random placement, and that this deviation increases with time. The time dependence suggests a major role of the host genome dynamics in shaping the current retrotransposon distributions. In fact, these distributions can be explained by a stochastic process of random placement due to retrotranscription followed by genome expansion and sequence duplications. Besides the inherent interest in understanding the origin of current retrotransposon distributions, this work sets a general analytical framework to analyze quantitatively the effects of genome evolutionary dynamics on the distribution of genomic elements.

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“…1 was¯rst obtained for a small number of chromosomes by self-alignment. 20 Sequence alignment is a heuristic process whose outcome depends on the method applied and parameters chosen. Only once the power-law behavior was reproduced as described here, wherein the distribution computed is de¯ned independently of any algorithm, could it be con¯dently asserted that the power-law behavior was not an artifact of the alignment method.…”

Section: Length Distributions Of Natural Genome Sequencesmentioning

confidence: 99%

“…For example, although the amplitudes of the curves often undergo multifold enhancement when bases are counted modulo the most frequent base substitution event, 38 C$T/ G$A, it turns out that the power-law behavior remains unchanged; this observation yields an important constraint on evolutionary dynamics. 20,39 Additionally, as much as half of each natural genome occurs as so-called \repetitive sequence a ;" length distributions of chromosomes from which these repetitive sequences have been excised (RM for repeat-masking) nevertheless exhibit a power-law. (see the plots for RM, 2b, and RM-2b in the supporting information.)…”

Section: Length Distributions Of Natural Genome Sequencesmentioning

confidence: 99%

“…Those inter-genomic computations were performed by hash-table based search 15 and whole-genome alignment 13,15 using the BLAST 16,17 alignment tool BLASTZ 18 (supplanted by LASTZ 19 ). Whole-genome alignment has recently demonstrated an intra-genome power-law regime in the length distribution of exactly duplicated sequence within a single genome 20 ; however, practical whole-genome alignment methods are heuristic and time-consuming; hashtable based intersection unwieldy and can make it di±cult to recover sequence features such as local maximality (see below) and copy number.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

EXHAUSTIVE COMPUTATION OF EXACT DUPLICATIONS VIA SUPER AND NON-NESTED LOCAL MAXIMAL REPEATS

Taillefer

Miller

2014

J. Bioinform. Comput. Biol.

Self Cite

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We propose and implement a method to obtain all duplicated sequences (repeats) from a chromosome or whole genome. Unlike existing approaches our method makes it possible to simultaneously identify and classify repeats into super, local, and non-nested local maximal repeats. Computation veri¯cation demonstrates that maximal repeats for a genome of several gigabases can be identi¯ed in a reasonable time, enabling us to identi¯ed these maximal repeats for any sequenced genome. The algorithm used for the identi¯cation relies on enhanced su±x array data structure to achieve practical space and time e±ciency, to identify and classify the maximal repeats, and to perform further post-processing on the identi¯ed duplicated sequences. The simplicity and e®ectiveness of the implementation makes the method readily extendible to more sophisticated computations. Maxmers can be exhaustively accounted for in few minutes for genome sequences of dozen megabases in length and in less than a day or two for genome sequences of few gigabases in length. One application of duplicated sequence identi¯cation is to the study of duplicated sequence length distributions, which our found to exhibit for large lengths a persistent power-law behavior. Variation of estimated exponents of this power law are studied among di®erent species and successive assembly release versions of the same species. This makes the characterization of the power-law regime of sequenced genomes via maximal repeats identi¯cation and classi¯cation, an important task for the derivation of models that would help us to elucidate sequence duplication and genome evolution.

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Algebraic Distribution of Segmental Duplication Lengths in Whole-Genome Sequence Self-Alignments

Cited by 24 publications

References 44 publications

Neutral Evolution of Duplicated DNA: An Evolutionary Stick-Breaking Process Causes Scale-Invariant Behavior

Neutral Evolution of Duplicated DNA: An Evolutionary Stick-Breaking Process Causes Scale-Invariant Behavior

Genomic duplications shaped current retrotransposon position distribution in human

EXHAUSTIVE COMPUTATION OF EXACT DUPLICATIONS VIA SUPER AND NON-NESTED LOCAL MAXIMAL REPEATS

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