5,467 research outputs found
A Computational Method for the Rate Estimation of Evolutionary Transpositions
Genome rearrangements are evolutionary events that shuffle genomic
architectures. Most frequent genome rearrangements are reversals,
translocations, fusions, and fissions. While there are some more complex genome
rearrangements such as transpositions, they are rarely observed and believed to
constitute only a small fraction of genome rearrangements happening in the
course of evolution. The analysis of transpositions is further obfuscated by
intractability of the underlying computational problems.
We propose a computational method for estimating the rate of transpositions
in evolutionary scenarios between genomes. We applied our method to a set of
mammalian genomes and estimated the transpositions rate in mammalian evolution
to be around 0.26.Comment: Proceedings of the 3rd International Work-Conference on
Bioinformatics and Biomedical Engineering (IWBBIO), 2015. (to appear
Analysis of top-swap shuffling for genome rearrangements
We study Markov chains which model genome rearrangements. These models are
useful for studying the equilibrium distribution of chromosomal lengths, and
are used in methods for estimating genomic distances. The primary Markov chain
studied in this paper is the top-swap Markov chain. The top-swap chain is a
card-shuffling process with cards divided over decks, where the cards
are ordered within each deck. A transition consists of choosing a random pair
of cards, and if the cards lie in different decks, we cut each deck at the
chosen card and exchange the tops of the two decks. We prove precise bounds on
the relaxation time (inverse spectral gap) of the top-swap chain. In
particular, we prove the relaxation time is . This resolves an
open question of Durrett.Comment: Published in at http://dx.doi.org/10.1214/105051607000000177 the
Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute
of Mathematical Statistics (http://www.imstat.org
A genetic network that suppresses genome rearrangements in Saccharomyces cerevisiae and contains defects in cancers.
Gross chromosomal rearrangements (GCRs) play an important role in human diseases, including cancer. The identity of all Genome Instability Suppressing (GIS) genes is not currently known. Here multiple Saccharomyces cerevisiae GCR assays and query mutations were crossed into arrays of mutants to identify progeny with increased GCR rates. One hundred eighty two GIS genes were identified that suppressed GCR formation. Another 438 cooperatively acting GIS genes were identified that were not GIS genes, but suppressed the increased genome instability caused by individual query mutations. Analysis of TCGA data using the human genes predicted to act in GIS pathways revealed that a minimum of 93% of ovarian and 66% of colorectal cancer cases had defects affecting one or more predicted GIS gene. These defects included loss-of-function mutations, copy-number changes associated with reduced expression, and silencing. In contrast, acute myeloid leukaemia cases did not appear to have defects affecting the predicted GIS genes
On pairwise distances and median score of three genomes under DCJ
In comparative genomics, the rearrangement distance between two genomes
(equal the minimal number of genome rearrangements required to transform them
into a single genome) is often used for measuring their evolutionary
remoteness. Generalization of this measure to three genomes is known as the
median score (while a resulting genome is called median genome). In contrast to
the rearrangement distance between two genomes which can be computed in linear
time, computing the median score for three genomes is NP-hard. This inspires a
quest for simpler and faster approximations for the median score, the most
natural of which appears to be the halved sum of pairwise distances which in
fact represents a lower bound for the median score.
In this work, we study relationship and interplay of pairwise distances
between three genomes and their median score under the model of
Double-Cut-and-Join (DCJ) rearrangements. Most remarkably we show that while a
rearrangement may change the sum of pairwise distances by at most 2 (and thus
change the lower bound by at most 1), even the most "powerful" rearrangements
in this respect that increase the lower bound by 1 (by moving one genome
farther away from each of the other two genomes), which we call strong, do not
necessarily affect the median score. This observation implies that the two
measures are not as well-correlated as one's intuition may suggest.
We further prove that the median score attains the lower bound exactly on the
triples of genomes that can be obtained from a single genome with strong
rearrangements. While the sum of pairwise distances with the factor 2/3
represents an upper bound for the median score, its tightness remains unclear.
Nonetheless, we show that the difference of the median score and its lower
bound is not bounded by a constant.Comment: Proceedings of the 10-th Annual RECOMB Satellite Workshop on
Comparative Genomics (RECOMB-CG), 2012. (to appear
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