Biomedical subjects

Claude W dePamphilis

Publications and source records attributed to Claude W dePamphilis.

6 recordsLinked to original sources

PubMed2005

Rate variation in parasitic plants: correlated and uncorrelated patterns among plastid genes of different function.

BACKGROUND: The analysis of synonymous and nonsynonymous rates of DNA change can help in the choice among competing explanations for rate variation, such as differences in constraint, mutation rate, or the strength of genetic drift. Nonphotosynthetic plants of the Orobanchaceae have increased rates of DNA change. In this study 38 taxa of Orobanchaceae and relatives were used and 3 plastid genes were sequenced for each taxon. RESULTS: Phylogenetic reconstructions of relative rates of sequence evolution for three plastid genes (rbcL, matK and rps2) show significant rate heterogeneity among lineages and among genes. Many of the non-photosynthetic plants have increases in both synonymous and nonsynonymous rates, indicating that both (1) selection is relaxed, and (2) there has been a change in the rate at which mutations are entering the population in these species. However, rate increases are not always immediate upon loss of photosynthesis. Overall there is a poor correlation of synonymous and nonsynonymous rates. There is, however, a strong correlation of synonymous rates across the 3 genes studied and the lineage-speccific pattern for each gene is strikingly similar. This indicates that the causes of synonymous rate variation are affecting the whole plastid genome in a similar way. There is a weaker correlation across genes for nonsynonymous rates. Here the picture is more complex, as could be expected if there are many causes of variation, differing from taxon to taxon and gene to gene. CONCLUSIONS: The distinctive pattern of rate increases in Orobanchaceae has at least two causes. It is clear that there is a relaxation of constraint in many (though not all) non-photosynthetic lineages. However, there is also some force affecting synonymous sites as well. At this point, it is not possible to tell whether it is generation time, speciation rate, mutation rate, DNA repair efficiency or some combination of these factors.

Cell Nucleus↗

PubMed2004

EST clustering error evaluation and correction.

MOTIVATION: The gene expression intensity information conveyed by (EST) Expressed Sequence Tag data can be used to infer important cDNA library properties, such as gene number and expression patterns. However, EST clustering errors, which often lead to greatly inflated estimates of obtained unique genes, have become a major obstacle in the analyses. The EST clustering error structure, the relationship between clustering error and clustering criteria, and possible error correction methods need to be systematically investigated. RESULTS: We identify and quantify two types of EST clustering error, namely, Type I and II in EST clustering using CAP3 assembling program. A Type I error occurs when ESTs from the same gene do not form a cluster whereas a Type II error occurs when ESTs from distinct genes are falsely clustered together. While the Type II error rate is <1.5% for both 5' and 3' EST clustering, the Type I error in the 5' EST case is approximately 10 times higher than the 3' EST case (30% versus 3%). An over-stringent identity rule, e.g., P >/= 95%, may even inflate the Type I error in both cases. We demonstrate that approximately 80% of the Type I error is due to insufficient overlap among sibling ESTs (ISO error) in 5' EST clustering. A novel statistical approach is proposed to correct ISO error to provide more accurate estimates of the true gene cluster profile.

Algorithms↗

PubMed2003

Highly heterogeneous rates of evolution in the SKP1 gene family in plants and animals: functional and evolutionary implications.

Skp1 (S-phase kinase-associated protein 1) is a core component of SCF ubiquitin ligases and mediates protein degradation, thereby regulating eukaryotic fundamental processes such as cell cycle progression, transcriptional regulation, and signal transduction. Among the four components of the SCF complexes, Rbx1 and Cullin form a core catalytic complex, an F-box protein acts as a receptor for target proteins, and Skp1 is an adaptor between one of the variable F-box proteins and Cullin. Whereas protists, fungi, and some vertebrates have a single SKP1 gene, many animal and plant species possess multiple SKP1 homologs. It has been shown that the same Skp1 homolog can interact with two or more F-box proteins, and different Skp1 homologs from the same species sometimes can interact with the same F-box protein. In this paper, we demonstrate that multiple Skp1 homologs from the same species have evolved at highly heterogeneous rates. Parametric bootstrap analyses suggested that the differences in evolutionary rate are so large that true phylogenies were not recoverable from the full data set. Only when the original data set were partitioned into sets of genes with slow, medium, and rapid rates of evolution and analyzed separately, better-resolved relationships were observed. The slowly evolving Skp1 homologs, which are relatively highly conserved in sequence and expressed widely and/or at high levels, usually have very low d(N)/d(S) values, suggesting that they have evolved under functional constraint and serve the most fundamental function(s). On the other hand, the rapidly evolving members are structurally more diverse and usually have limited expression patterns and higher d(N)/d(S) values, suggesting that they may have evolved under relaxed or altered constraint, or even under positive selection. Some rapidly evolving members may have lost their original function(s) and/or acquired new function(s) or become pseudogenes, as suggested by their expression patterns, d(N)/d(S) values, and amino acid changes at key positions. In addition, our analyses revealed several monophyletic groups within the SKP1 gene family, one for each of protists, fungi, animals, and plants, as well as nematodes, arthropods, and angiosperms, suggesting that the extant SKP1 genes within each of these eukaryote groups shared only one common ancestor.

Amino Acid Sequence↗

PubMed2003

Antiquity and evolution of the MADS-box gene family controlling flower development in plants.

MADS-box genes in plants control various aspects of development and reproductive processes including flower formation. To obtain some insight into the roles of these genes in morphological evolution, we investigated the origin and diversification of floral MADS-box genes by conducting molecular evolutionary genetics analyses. Our results suggest that the most recent common ancestor of today's floral MADS-box genes evolved roughly 650 MYA, much earlier than the Cambrian explosion. They also suggest that the functional classes T (SVP), B (and Bs), C, F (AGL20 or TM3), A, and G (AGL6) of floral MADS-box genes diverged sequentially in this order from the class E gene lineage. The divergence between the class G and E genes apparently occurred around the time of the angiosperm/gymnosperm split. Furthermore, the ancestors of three classes of genes (class T genes, class B/Bs genes, and the common ancestor of the other classes of genes) might have existed at the time of the Cambrian explosion. We also conducted a phylogenetic analysis of MADS-domain sequences from various species of plants and animals and presented a hypothetical scenario of the evolution of MADS-box genes in plants and animals, taking into account paleontological information. Our study supports the idea that there are two main evolutionary lineages (type I and type II) of MADS-box genes in plants and animals.

Animals↗

PubMed2002

Missing links: the genetic architecture of flowers [correction of flower] and floral diversification.

To understand the genetic architecture of floral development, including the origin and subsequent diversification of the flower, data are needed not only for a few model organisms but also for gymnosperms, basal angiosperm lineages and early-diverging eudicots. We must link what is known about derived model plants such as Arabidopsis, snapdragon and maize with other angiosperms. To this end, we suggest a massive evolutionary genomics effort focused on the identification and expression patterns of floral genes and elucidation of their expression patterns in 'missing-link' taxa differing in the arrangement, number and organization of floral parts.

Cycadopsida↗

PubMed2002

The Chlamydomonas reinhardtii plastid chromosome: islands of genes in a sea of repeats.

Chlamydomonas reinhardtii is a unicellular eukaryotic alga possessing a single chloroplast that is widely used as a model system for the study of photosynthetic processes. This report analyzes the surprising structural and evolutionary features of the completely sequenced 203,395-bp plastid chromosome. The genome is divided by 21.2-kb inverted repeats into two single-copy regions of approximately 80 kb and contains only 99 genes, including a full complement of tRNAs and atypical genes encoding the RNA polymerase. A remarkable feature is that >20% of the genome is repetitive DNA: the majority of intergenic regions consist of numerous classes of short dispersed repeats (SDRs), which may have structural or evolutionary significance. Among other sequenced chlorophyte plastid genomes, only that of the green alga Chlorella vulgaris appears to share this feature. The program MultiPipMaker was used to compare the genic complement of Chlamydomonas with those of other chloroplast genomes and to scan the genomes for sequence similarities and repetitive DNAs. Among the results was evidence that the SDRs were not derived from extant coding sequences, although some SDRs may have arisen from other genomic fragments. Phylogenetic reconstruction of changes in plastid genome content revealed that an accelerated rate of gene loss also characterized the Chlamydomonas/Chlorella lineage, a phenomenon that might be independent of the proliferation of SDRs. Together, our results reveal a dynamic and unusual plastid genome whose existence in a model organism will allow its features to be tested functionally.

Amino Acid Sequence↗