Timing and Reconstruction of the Most Recent Common Ancestor of the Subtype C Clade of Human Immunodeficiency Virus Type 1

Human immunodeficiency virus type 1 (HIV-1) subtype C is responsible for more than 55% of HIV-1 infections worldwide. When this subtype first emerged is unknown. We have analyzed all available gag (p17 and p24) and env (C2-V3) subtype C sequences with known sampling dates, which ranged from 1983 to 2000. The majority of these sequences come from the Karonga District in Malawi and include some of the earliest known subtype C sequences. Linear regression analyses of sequence divergence estimates (with four different approaches)were plotted against sample year to estimate the year in which there was zero divergence from the reconstructed ancestral sequence. Here we suggest that the most recent common ancestor of subtype C appeared in the mid- to late 1960s. Sensitivity analyses, by which possible biases due to oversampling from one district were explored, gave very similar estimates

Identifying and Seeing beyond Multiple Sequence Alignment Errors Using Intra-Molecular Protein Covariation

BACKGROUND: There is currently no way to verify the quality of a multiple sequence alignment that is independent of the assumptions used to build it. Sequence alignments are typically evaluated by a number of established criteria: sequence conservation, the number of aligned residues, the frequency of gaps, and the probable correct gap placement. Covariation analysis is used to find putatively important residue pairs in a sequence alignment. Different alignments of the same protein family give different results demonstrating that covariation depends on the quality of the sequence alignment. We thus hypothesized that current criteria are insufficient to build alignments for use with covariation analyses. METHODOLOGY/PRINCIPAL FINDINGS: We show that current criteria are insufficient to build alignments for use with covariation analyses as systematic sequence alignment errors are present even in hand-curated structure-based alignment datasets like those from the Conserved Domain Database. We show that current non-parametric covariation statistics are sensitive to sequence misalignments and that this sensitivity can be used to identify systematic alignment errors. We demonstrate that removing alignment errors due to 1) improper structure alignment, 2) the presence of paralogous sequences, and 3) partial or otherwise erroneous sequences, improves contact prediction by covariation analysis. Finally we describe two non-parametric covariation statistics that are less sensitive to sequence alignment errors than those described previously in the literature. CONCLUSIONS/SIGNIFICANCE: Protein alignments with errors lead to false positive and false negative conclusions (incorrect assignment of covariation and conservation, respectively). Covariation analysis can provide a verification step, independent of traditional criteria, to identify systematic misalignments in protein alignments. Two non-parametric statistics are shown to be somewhat insensitive to misalignment errors, providing increased confidence in contact prediction when analyzing alignments with erroneous regions because of an emphasis on they emphasize pairwise covariation over group covariation

Conserved and variable correlated mutations in the plant MADS protein network

<p>Abstract</p> <p>Background</p> <p>Plant MADS domain proteins are involved in a variety of developmental processes for which their ability to form various interactions is a key requisite. However, not much is known about the structure of these proteins or their complexes, whereas such knowledge would be valuable for a better understanding of their function. Here, we analyze those proteins and the complexes they form using a correlated mutation approach in combination with available structural, bioinformatics and experimental data.</p> <p>Results</p> <p>Correlated mutations are affected by several types of noise, which is difficult to disentangle from the real signal. In our analysis of the MADS domain proteins, we apply for the first time a correlated mutation analysis to a family of interacting proteins. This provides a unique way to investigate the amount of signal that is present in correlated mutations because it allows direct comparison of mutations in various family members and assessing their conservation. We show that correlated mutations in general are conserved within the various family members, and if not, the variability at the respective positions is less in the proteins in which the correlated mutation does not occur. Also, intermolecular correlated mutation signals for interacting pairs of proteins display clear overlap with other bioinformatics data, which is not the case for non-interacting protein pairs, an observation which validates the intermolecular correlated mutations. Having validated the correlated mutation results, we apply them to infer the structural organization of the MADS domain proteins.</p> <p>Conclusion</p> <p>Our analysis enables understanding of the structural organization of the MADS domain proteins, including support for predicted helices based on correlated mutation patterns, and evidence for a specific interaction site in those proteins.</p

Non-random pre-transcriptional evolution in HIV-1. A refutation of the foundational conditions for neutral evolution

The complete base sequence of HIV-1 virus and GP120 ENV gene were analyzed to establish their distance to the expected neutral random sequence. An especial methodology was devised to achieve this aim. Analyses included: a) proportion of dinucleotides (signatures); b) homogeneity in the distribution of dinucleotides and bases (isochores) by dividing both segments in ten and three sub-segments, respectively; c) probability of runs of bases and No-bases according to the Bose-Einstein distribution. The analyses showed a huge deviation from the random distribution expected from neutral evolution and neutral-neighbor influence of nucleotide sites. The most significant result is the tremendous lack of CG dinucleotides (p < 10-50 ), a selective trait of eukaryote and not of single stranded RNA virus genomes. Results not only refute neutral evolution and neutral neighbor influence, but also strongly indicate that any base at any nucleotide site correlates with all the viral genome or sub-segments. These results suggest that evolution of HIV-1 is pan-selective rather than neutral or nearly neutral

Correlated Mutations: A Hallmark of Phenotypic Amino Acid Substitutions

Point mutations resulting in the substitution of a single amino acid can cause severe functional consequences, but can also be completely harmless. Understanding what determines the phenotypical impact is important both for planning targeted mutation experiments in the laboratory and for analyzing naturally occurring mutations found in patients. Common wisdom suggests using the extent of evolutionary conservation of a residue or a sequence motif as an indicator of its functional importance and thus vulnerability in case of mutation. In this work, we put forward the hypothesis that in addition to conservation, co-evolution of residues in a protein influences the likelihood of a residue to be functionally important and thus associated with disease. While the basic idea of a relation between co-evolution and functional sites has been explored before, we have conducted the first systematic and comprehensive analysis of point mutations causing disease in humans with respect to correlated mutations. We included 14,211 distinct positions with known disease-causing point mutations in 1,153 human proteins in our analysis. Our data show that (1) correlated positions are significantly more likely to be disease-associated than expected by chance, and that (2) this signal cannot be explained by conservation patterns of individual sequence positions. Although correlated residues have primarily been used to predict contact sites, our data are in agreement with previous observations that (3) many such correlations do not relate to physical contacts between amino acid residues. Access to our analysis results are provided at http://webclu.bio.wzw.tum.de/~pagel/supplements/correlated-positions/

Characterization of the avian trojan gene family reveals contrasting evolutionary constraints

"Trojan" is a leukocyte-specific, cell surface protein originally identified in the chicken. Its molecular function has been hypothesized to be related to anti-apoptosis and the proliferation of immune cells. The Trojan gene has been localized onto the Z sex chromosome. The adjacent two genes also show significant homology to Trojan, suggesting the existence of a novel gene/protein family. Here, we characterize this Trojan family, identify homologues in other species and predict evolutionary constraints on these genes. The two Trojan-related proteins in chicken were predicted as a receptor-type tyrosine phosphatase and a transmembrane protein, bearing a cytoplasmic immuno-receptor tyrosine-based activation motif. We identified the Trojan gene family in ten other bird species and found related genes in three reptiles and a fish species. The phylogenetic analysis of the homologues revealed a gradual diversification among the family members. Evolutionary analyzes of the avian genes predicted that the extracellular regions of the proteins have been subjected to positive selection. Such selection was possibly a response to evolving interacting partners or to pathogen challenges.We also observed an almost complete lack of intracellular positively selected sites, suggesting a conserved signaling mechanism of the molecules. Therefore, the contrasting patterns of selection likely correlate with the interaction and signaling potential of the molecules