Statistical detection of chromosomal homology using shared-gene density alone

Hampson, Steven E.; Gaut, B. S.; Baldi, Pierre

doi:10.1093/bioinformatics/bti168

Cited by 30 publications

(31 citation statements)

References 19 publications

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“…Continuous stretches of duplicate genes can be computationally deduced through synteny, using some variants of clustering approaches (Vandepoele et al 2002;Hampson et al 2005) or more specifically using dynamic programming with a customized scoring scheme if conserved gene order (collinearity) is also considered (Haas et al 2004;Wang et al 2006). Traditional methods for deduction of synteny based on "best-in-genome" criteria (Miller et al 2007), uncovering one-to-one best matching regions during pairwise genome comparisons, are relatively straightforward in vertebrates yet difficult in angiosperms because of additional challenges that are more prominent in angiosperm genomes (Tang et al 2008).…”

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confidence: 99%

Unraveling ancient hexaploidy through multiply-aligned angiosperm gene maps

Tang¹,

Wang²,

Bowers³

et al. 2008

Genome Res.

568

542

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Large-scale (segmental or whole) genome duplication has been recurring in angiosperm evolution. Subsequent gene loss and rearrangements further affect gene copy numbers and fractionate ancestral gene linkages across multiple chromosomes. The fragmented "multiple-to-multiple" correspondences resulting from this distinguishing feature of angiosperm evolution complicates comparative genomic studies. Using a robust computational framework that combines information from multiple orthologous and duplicated regions to construct local syntenic networks, we show that a shared ancient hexaploidy event (or perhaps two roughly concurrent genome fusions) can be inferred based on the sequences from several divergent plant genomes. This "paleo-hexaploidy" clearly preceded the rosid-asterid split, but it remains equivocal whether it also affected monocots. The model resulting from our multi-alignments lays the foundation for approximating the number and arrangement of genes in the last universal common ancestor of angiosperms. Comparative analysis of inferred homologous genes derived from this model shows patterns of preferential gene retention or loss after polyploidy and reveals large variability of nucleotide substitution rates among plant nuclear genomes.

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mentioning

confidence: 99%

Unraveling ancient hexaploidy through multiply-aligned angiosperm gene maps

Tang¹,

Wang²,

Bowers³

et al. 2008

Genome Res.

568

542

View full text Add to dashboard Cite

show abstract

“…Such implicit constraints may be particularly problematic when the goal is to characterize the properties of homologous regions. For example, although the CloseUp algorithm was ostensibly designed to identify chromosomal homology using "shared-gene density alone" [33], the greedy nature of the search algorithm means that all clusters with a minimum gene density may not actually be detected. If such an approach was used to evaluate the extent to which order is conserved in homologous regions, incorrect inferences could be made.…”

Section: Discussionmentioning

confidence: 99%

“…Clusters have also been defined in terms of graph-theoretic structures (e.g., Figure 1(c)), such as connected components [27] or high-scoring paths [28,29]. Finally, a variety of heuristics have been proposed to search for gene clusters [30,25,31,32,33,34,29,11], the majority of which are specifically de-signed to find sets of genes in approximately collinear order (i.e., forming a rough diagonal on the dot-plot).…”

Section: Cluster Definitionsmentioning

confidence: 99%

“…However, if the processes that degrade a cluster are operating uniformly, then the length of the cluster in both genomes should be similar. This similarity of lengths is implicitly sought by the length constraint of r-windows, and explicitly sought in the clustering method of Hampson et al [33].…”

Section: Lengthmentioning

confidence: 99%

“…Greedy algorithms use a bottom-up approach: each homologous gene pair serves as a cluster seed, and a cluster is extended by looking in its chromosomal neighborhood for another homologous gene pair close to the cluster on both genomes [25,31,33,39]. It can be shown that any greedy search algorithm that constructs max-gap clusters iteratively, i.e., by constructing a cluster of size k by adding a gene to a cluster of size k − 1, will find exactly the set of all maximal nested maxgap clusters, as long as it considers each homologous gene pair as a seed for a potential cluster.…”

Section: Nestednessmentioning

confidence: 99%

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The Incompatible Desiderata of Gene Cluster Properties

Hoberman

Durand

2005

Comparative Genomics

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Abstract. There is widespread interest in comparative genomics in determining if historically and/or functionally related genes are spatially clustered in the genome, and whether the same sets of genes reappear in clusters in two or more genomes. We formalize and analyze the desirable properties of gene clusters and cluster definitions. Through detailed analysis of two commonly applied types of cluster, r-windows and maxgap, we investigate the extent to which a single definition can embody all of these properties simultaneously. We show that many of the most important properties are difficult to satisfy within the same definition. We also examine whether one commonly assumed property, which we call nestedness, is satisfied by the structures present in real genomic data.

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Comparative Genomics

Dicks

2007

Handbook of Statistical Genetics

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Over the last couple of decades, numerous genetic and physical maps have been developed for a wide range of species. These data have led to the development of the field of comparative genomics, in which we analyse characteristics of whole genomes, in contrast to the analysis of single genes in comparative genetics. By comparing homologous markers between species, we can get a feel for their relative distributions on the chromosomes of the respective species. Such information also enables us to deduce segments of chromosomes where the gene content, and sometimes also the order of the genes, is similar in two or more species. More recently, DNA sequences of whole genomes have become available, enabling us to compare genomes at both the sequence and the gene levels. Furthermore, these datasets have provided us with more detailed information with which to study the processes involved in genome dynamics. The promise of the post-genome era means that we will see many fully sequenced genomes within the next decade and we should develop analytical methods that are mature when significant quantities of data become available. However, not all species will be sequenced, at least in the near future, and so we should continue to develop methods of analysis that are appropriate for both types of data. In this chapter, we give a flavour of the types of comparative genome analysis that are currently possible. We highlight particular problems such as phylogenetic inference and the use of maps to compare genomes. Finally, we look at problems that should be tackled to enable us to make the most of the emerging genomic data.

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Statistical detection of chromosomal homology using shared-gene density alone

Abstract: pfbaldi@ics.uci.edu.

Cited by 30 publications

References 19 publications

Unraveling ancient hexaploidy through multiply-aligned angiosperm gene maps

Unraveling ancient hexaploidy through multiply-aligned angiosperm gene maps

The Incompatible Desiderata of Gene Cluster Properties

Comparative Genomics

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