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

Loss-of-function analysis of EphA receptors in retinotectal mapping

Peer reviewedPublisher PD

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

A Unifying Model of Genome Evolution Under Parsimony

We present a data structure called a history graph that offers a practical basis for the analysis of genome evolution. It conceptually simplifies the study of parsimonious evolutionary histories by representing both substitutions and double cut and join (DCJ) rearrangements in the presence of duplications. The problem of constructing parsimonious history graphs thus subsumes related maximum parsimony problems in the fields of phylogenetic reconstruction and genome rearrangement. We show that tractable functions can be used to define upper and lower bounds on the minimum number of substitutions and DCJ rearrangements needed to explain any history graph. These bounds become tight for a special type of unambiguous history graph called an ancestral variation graph (AVG), which constrains in its combinatorial structure the number of operations required. We finally demonstrate that for a given history graph $G$, a finite set of AVGs describe all parsimonious interpretations of $G$, and this set can be explored with a few sampling moves.Comment: 52 pages, 24 figure

Parking functions, labeled trees and DCJ sorting scenarios

In genome rearrangement theory, one of the elusive questions raised in recent years is the enumeration of rearrangement scenarios between two genomes. This problem is related to the uniform generation of rearrangement scenarios, and the derivation of tests of statistical significance of the properties of these scenarios. Here we give an exact formula for the number of double-cut-and-join (DCJ) rearrangement scenarios of co-tailed genomes. We also construct effective bijections between the set of scenarios that sort a cycle and well studied combinatorial objects such as parking functions and labeled trees.Comment: 12 pages, 3 figure

A new transcript in the TCRB locus unveils the human ortholog of the mouse pre-Dß1 promoter

Introduction: While most transcripts arising from the human T Cell Receptor locus reflect fully rearranged genes, several germline transcripts have been identified. We describe a new germline transcript arising from the human TCRB locus. Methods: cDNA sequencing, promoter, and gene expression analyses were used to characterize the new transcript. Results: The new germline transcript encoded by the human TCRB locus consists of a new exon of 103bp, which we named TRBX1 (X1), spliced with the first exon of gene segments C ss 1 or C ss 2. X1 is located upstream of gene segment D ss 1 and is therefore deleted from a V-DJ rearranged TCRB locus. The X1-C ss transcripts do not appear to code for a protein. We define their transcription start and minimal promoter. These transcripts are found in populations of mature T lymphocytes from blood or tissues and in T cell clones with a monoallelic TCRB rearrangement. In immature thymocytes, they are already detectable in CD1a(-)CD34(+)CD4(-)CD8(-) cells, therefore before completion of the TCRB rearrangements. Conclusions: The X1 promoter appears to be the ortholog of the mouse pre-D ss 1 promoter (PD ss 1). Like PD ss 1, its activation is regulated by E ss in T cells and might facilitate the TCRB rearrangement process by contributing to the accessibility of the D ss 1 locus

VEGF Trap In Combination With Radiotherapy Improves Tumor Control In U87 Glioblastoma

Purpose To determine the effect of vascular endothelial growth factor VEGF Trap (Regeneron Pharmaceuticals, Tarrytown, NY), a humanized soluble vascular endothelial growth factor (VEGF) receptor protein, and radiation (RT) on tumor growth in U87 glioblastoma xenografts in nude mice. Methods and Materials U87 cell suspensions were implanted subcutaneously into hind limbs of nude mice. VEGF Trap (2.5–25 mg/kg) was administered every 3 days for 3 weeks alone or in combination with a single dose of 10 Gy or fractionated RT (3 x 5 Gy). In addition, three scheduling protocols for VEGF Trap plus fractionated RT were examined. Results Improved tumor control was seen when RT (either single dose or fractionated doses) was combined with the lowest dose of VEGF Trap (2.5 mg/kg). Scheduling did not significantly affect the efficacy of combined therapy. Although high-dose VEGF Trap (10 mg/kg or 25 mg/kg) significantly reduced tumor growth over that of RT alone, there was no additional benefit to combining high-dose VEGF Trap with RT. Conclusions Vascular endothelial growth factor Trap plus radiation is clearly better than radiation alone in a U87 subcutaneous xenograft model. Although high doses of VEGF Trap alone are highly efficacious, it is unclear whether such high doses can be used clinically without incurring normal tissue toxicities. Thus, information on lower doses of VEGF Trap and ionizing radiation is of clinical relevance. Int. J. Radiation Oncol. Biol. Physics, Volume 67, Issue 5, pages 1526-1537, 2007