Biomedical subjects

Lars Arvestad

Publications and source records attributed to Lars Arvestad.

6 recordsLinked to original sources

PubMed2007

Evolution after gene duplication: models, mechanisms, sequences, systems, and organisms.

Gene duplication is postulated to have played a major role in the evolution of biological novelty. Here, gene duplication is examined across levels of biological organization in an attempt to create a unified picture of the mechanistic process by which gene duplication can have played a role in generating biodiversity. Neofunctionalization and subfunctionalization have been proposed as important processes driving the retention of duplicate genes. These models have foundations in population genetic theory, which is now being refined by explicit consideration of the structural constraints placed upon genes encoding proteins through physical chemistry. Further, such models can be examined in the context of comparative genomics, where an integration of gene-level evolution and species-level evolution allows an assessment of the frequency of duplication and the fate of duplicate genes. This process, of course, is dependent upon the biochemical role that duplicated genes play in biological systems, which is in turn dependent upon the mechanism of duplication: whole genome duplication involving a co-duplication of interacting partners vs. single gene duplication. Lastly, the role that these processes may have played in driving speciation is examined.

Animals↗

PubMed2006

Genome-wide survey for biologically functional pseudogenes.

According to current estimates there exist about 20,000 pseudogenes in a mammalian genome. The vast majority of these are disabled and nonfunctional copies of protein-coding genes which, therefore, evolve neutrally. Recent findings that a Makorin1 pseudogene, residing on mouse Chromosome 5, is, indeed, in vivo vital and also evolutionarily preserved, encouraged us to conduct a genome-wide survey for other functional pseudogenes in human, mouse, and chimpanzee. We identify to our knowledge the first examples of conserved pseudogenes common to human and mouse, originating from one duplication predating the human-mouse species split and having evolved as pseudogenes since the species split. Functionality is one possible way to explain the apparently contradictory properties of such pseudogene pairs, i.e., high conservation and ancient origin. The hypothesis of functionality is tested by comparing expression evidence and synteny of the candidates with proper test sets. The tests suggest potential biological function. Our candidate set includes a small set of long-lived pseudogenes whose unknown potential function is retained since before the human-mouse species split, and also a larger group of primate-specific ones found from human-chimpanzee searches. Two processed sequences are notable, their conservation since the human-mouse split being as high as most protein-coding genes; one is derived from the protein Ataxin 7-like 3 (ATX7NL3), and one from the Spinocerebellar ataxia type 1 protein (ATX1). Our approach is comparative and can be applied to any pair of species. It is implemented by a semi-automated pipeline based on cross-species BLAST comparisons and maximum-likelihood phylogeny estimations. To separate pseudogenes from protein-coding genes, we use standard methods, utilizing in-frame disablements, as well as a probabilistic filter based on Ka/Ks ratios.

Animals↗

PubMed2006

Efficient methods for estimating amino acid replacement rates.

Replacement rate matrices describe the process of evolution at one position in a protein and are used in many applications where proteins are studied with an evolutionary perspective. Several general matrices have been suggested and have proved to be good approximations of the real process. However, there are data for which general matrices are inappropriate, for example, special protein families, certain lineages in the tree of life, or particular parts of proteins. Analysis of such data could benefit from adaption of a data-specific rate matrix. This paper suggests two new methods for estimating replacement rate matrices from independent pairwise protein sequence alignments and also carefully studies Müller-Vingron's resolvent method. Comprehensive tests on synthetic datasets show that both new methods perform better than the resolvent method in a variety of settings. The best method is furthermore demonstrated to be robust on small datasets as well as practical on very large datasets of real data. Neither short nor divergent sequence pairs have to be discarded, making the method economical with data. A generalization to multialignment data is suggested and used in a test on protein-domain family phylogenies, where it is shown that the method offers family-specific rate matrices that often have a significantly better likelihood than a general matrix.

Amino Acid Substitution↗

PubMed2005

Assessment of protein distance measures and tree-building methods for phylogenetic tree reconstruction.

Distance-based methods are popular for reconstructing evolutionary trees of protein sequences, mainly because of their speed and generality. A number of variants of the classical neighbor-joining (NJ) algorithm have been proposed, as well as a number of methods to estimate protein distances. We here present a large-scale assessment of performance in reconstructing the correct tree topology for the most popular algorithms. The programs BIONJ, FastME, Weighbor, and standard NJ were run using 12 distance estimators, producing 48 tree-building/distance estimation method combinations. These were evaluated on a test set based on real trees taken from 100 Pfam families. Each tree was used to generate multiple sequence alignments with the ROSE program using three evolutionary models. The accuracy of each method was analyzed as a function of both sequence divergence and location in the tree. We found that BIONJ produced the overall best results, although the average accuracy differed little between the tree-building methods (normally less than 1%). A noticeable trend was that FastME performed poorer than the rest on long branches. Weighbor was several orders of magnitude slower than the other programs. Larger differences were observed when using different distance estimators. Protein-adapted Jukes-Cantor and Kimura distance correction produced clearly poorer results than the other methods, even worse than uncorrected distances. We also assessed the recently developed Scoredist measure, which performed equally well as more complex methods.

Base Sequence↗

PubMed2005

The genome sequence of black cottonwood (Populus trichocarpa) reveals 18 conserved cellulose synthase (CesA) genes.

The genome sequence of Populus trichocarpa was screened for genes encoding cellulose synthases by using full-length cDNA sequences and ESTs previously identified in the tissue specific cDNA libraries of other poplars. The data obtained revealed 18 distinct CesA gene sequences in P. trichocarpa. The identified genes were grouped in seven gene pairs, one group of three sequences and one single gene. Evidence from gene expression studies of hybrid aspen suggests that both copies of at least one pair, CesA3-1 and CesA3-2, are actively transcribed. No sequences corresponding to the gene pair, CesA6-1 and CesA6-2, were found in Arabidopsis or hybrid aspen, while one homologous gene has been identified in the rice genome and an active transcript in Populus tremuloides. A phylogenetic analysis suggests that the CesA genes previously associated with secondary cell wall synthesis originate from a single ancestor gene and group in three distinct subgroups. The newly identified copies of CesA genes in P. trichocarpa give rise to a number of new questions concerning the mechanism of cellulose synthesis in trees.

Chromosome Mapping↗

PubMed2003

Bayesian gene/species tree reconciliation and orthology analysis using MCMC.

MOTIVATION: Comparative genomics in general and orthology analysis in particular are becoming increasingly important parts of gene function prediction. Previously, orthology analysis and reconciliation has been performed only with respect to the parsimony model. This discards many plausible solutions and sometimes precludes finding the correct one. In many other areas in bioinformatics probabilistic models have proven to be both more realistic and powerful than parsimony models. For instance, they allow for assessing solution reliability and consideration of alternative solutions in a uniform way. There is also an added benefit in making model assumptions explicit and therefore making model comparisons possible. For orthology analysis, uncertainty has recently been addressed using parsimonious reconciliation combined with bootstrap techniques. However, until now no probabilistic methods have been available. RESULTS: We introduce a probabilistic gene evolution model based on a birth-death process in which a gene tree evolves 'inside' a species tree. Based on this model, we develop a tool with the capacity to perform practical orthology analysis, based on Fitch's original definition, and more generally for reconciling pairs of gene and species trees. Our gene evolution model is biologically sound (Nei et al., 1997) and intuitively attractive. We develop a Bayesian analysis based on MCMC which facilitates approximation of an a posteriori distribution for reconciliations. That is, we can find the most probable reconciliations and estimate the probability of any reconciliation, given the observed gene tree. This also gives a way to estimate the probability that a pair of genes are orthologs. The main algorithmic contribution presented here consists of an algorithm for computing the likelihood of a given reconciliation. To the best of our knowledge, this is the first successful introduction of this type of probabilistic methods, which flourish in phylogeny analysis, into reconciliation and orthology analysis. The MCMC algorithm has been implemented and, although not yet being in its final form, tests show that it performs very well on synthetic as well as biological data. Using standard correspondences, our results carry over to allele trees as well as biogeography.

Algorithms↗