Biomedical subjects

Dannie Durand

Publications and source records attributed to Dannie Durand.

6 recordsLinked to original sources

PubMed2006

Diagnosing duplications--can it be done?

New genes arise through duplication and modification of DNA sequences on a range of scales: single gene duplication, duplication of large chromosomal fragments and whole-genome duplication. Each duplication mechanism has specific characteristics that influence the fate of the resulting duplicates, such as the size of the duplicated fragment, the potential for dosage imbalance, the preservation or disruption of regulatory control and genomic context. The ability to diagnose or identify the mechanism that produced a pair of paralogs has the potential to increase our ability to reconstruct evolutionary history, to understand the processes that govern genome evolution and to make functional predictions based on paralogy. The recent availability of large amounts of whole-genome sequence, often from several closely related species, has stimulated a wealth of new computational methods to diagnose gene duplications.

Animals↗

PubMed2006

A hybrid micro-macroevolutionary approach to gene tree reconstruction.

Gene family evolution is determined by microevolutionary processes (e.g., point mutations) and macroevolutionary processes (e.g., gene duplication and loss), yet macroevolutionary considerations are rarely incorporated into gene phylogeny reconstruction methods. We present a dynamic program to find the most parsimonious gene family tree with respect to a macroevolutionary optimization criterion, the weighted sum of the number of gene duplications and losses. The existence of a polynomial delay algorithm for duplication/loss phylogeny reconstruction stands in contrast to most formulations of phylogeny reconstruction, which are NP-complete. We next extend this result to obtain a two-phase method for gene tree reconstruction that takes both micro- and macroevolution into account. In the first phase, a gene tree is constructed from sequence data, using any of the previously known algorithms for gene phylogeny construction. In the second phase, the tree is refined by rearranging regions of the tree that do not have strong support in the sequence data to minimize the duplication/lost cost. Components of the tree with strong support are left intact. This hybrid approach incorporates both micro- and macroevolutionary considerations, yet its computational requirements are modest in practice because the two-phase approach constrains the search space. Our hybrid algorithm can also be used to resolve nonbinary nodes in a multifurcating gene tree. We have implemented these algorithms in a software tool, NOTUNG 2.0, that can be used as a unified framework for gene tree reconstruction or as an exploratory analysis tool that can be applied post hoc to any rooted tree with bootstrap values. The NOTUNG 2.0 graphical user interface can be used to visualize alternate duplication/loss histories, root trees according to duplication and loss parsimony, manipulate and annotate gene trees, and estimate gene duplication times. It also offers a command line option that enables high-throughput analysis of a large number of trees.

ATP-Binding Cassette Transporters↗

PubMed2006

Graph theoretical insights into evolution of multidomain proteins.

We study properties of multidomain proteins from a graph theoretical perspective. In particular, we demonstrate connections between properties of the domain overlap graph and certain variants of Dollo parsimony models. We apply our graph theoretical results to address several interrelated questions: do proteins acquire new domains infrequently, or often enough that the same combinations of domains will be created repeatedly through independent events? Once domain architectures are created do they persist? In other words, is the existence of ancestral proteins with domain compositions not observed in contemporary proteins unlikely? Our experimental results indicate that independent merges of domain pairs are not uncommon in large superfamilies.

Amino Acids↗

PubMed2005

The statistical analysis of spatially clustered genes under the maximum gap criterion.

Statistical validation of gene clusters is imperative for many important applications in comparative genomics which depend on the identification of genomic regions that are historically and/or functionally related. We develop the first rigorous statistical treatment of max-gap clusters, a cluster definition frequently used in empirical studies. We present exact expressions for the probability of observing an individual cluster of a set of marked genes in one genome, as well as upper and lower bounds on the probability of observing a cluster of h homologs in a pairwise whole-genome comparison. We demonstrate the utility of our approach by applying it to a whole-genome comparison of E. coli and B. subtilis. Code for statistical tests is available at.

Bacillus subtilis↗

PubMed2003

Vertebrate evolution: doubling and shuffling with a full deck.

The number and role of whole-genome duplications in vertebrate evolution has intrigued evolutionary biologists since Ohno first proposed genome duplication as the force driving the 'big leap' in vertebrate morphological innovation. Attempts to resolve these issues have been thwarted by small and noisy datasets, and by lack of computational accuracy and statistical rigor. Recently, Ken Wolfe and colleagues presented a genome-scale, statistically rigorous analysis of evidence based on the spatial organization of duplicated genes, as well as estimates of duplication times. Their results provide the strongest evidence to date of large-scale duplication throughout the vertebrate genome, consistent with at least one whole-genome duplication.

Animals↗

PubMed2003

Tests for gene clustering.

Comparing chromosomal gene order in two or more related species is an important approach to studying the forces that guide genome organization and evolution. Linked clusters of similar genes found in related genomes are often used to support arguments of evolutionary relatedness or functional selection. However, as the gene order and the gene complement of sister genomes diverge progressively due to large scale rearrangements, horizontal gene transfer, gene duplication and gene loss, it becomes increasingly difficult to determine whether observed similarities in local genomic structure are indeed remnants of common ancestral gene order, or are merely coincidences. A rigorous comparative genomics requires principled methods for distinguishing chance commonalities, within or between genomes, from genuine historical or functional relationships. In this paper, we construct tests for significant groupings against null hypotheses of random gene order, taking incomplete clusters, multiple genomes, and gene families into account. We consider both the significance of individual clusters of prespecified genes and the overall degree of clustering in whole genomes.

Algorithms↗