Yumi Yamaguchi-Kabata

Reevaluation of Amino Acid Variability of the Human Immunodeficiency Virus Type 1 gp120 Envelope Glycoprotein and Prediction of New Discontinuous Epitopes

ABSTRACT To elucidate the evolutionary mechanisms of the human immunodeficiency virus type 1 gp120 envelope glycoprotein at the single-site level, the degree of amino acid variation and the numbers of synonymous and nonsynonymous substitutions were examined in 186 nucleotide sequences for gp120 (subtype B). Analyses of amino acid variabilities showed that the level of variability was very different from site to site in both conserved (C1 to C5) and variable (V1 to V5) regions previously assigned. To examine the relative importance of positive and negative selection for each amino acid position, the numbers of synonymous and nonsynonymous substitutions that occurred at each codon position were estimated by taking phylogenetic relationships into account. Among the 414 codon positions examined, we identified 33 positions where nonsynonymous substitutions were significantly predominant. These positions where positive selection may be operating, which we call putative positive selection (PS) sites, were found not only in the variable loops but also in the conserved regions (C1 to C4). In particular, we found seven PS sites at the surface positions of the α-helix (positions 335 to 347 in the C3 region) in the opposite face for CD4 binding. Furthermore, two PS sites in the C2 region and four PS sites in the C4 region were detected in the same face of the protein. The PS sites found in the C2, C3, and C4 regions were separated in the amino acid sequence but close together in the three-dimensional structure. This observation suggests the existence of discontinuous epitopes in the proteins surface including this α-helix, although the antigenicity of this area has not been reported yet.

Distribution and effects of nonsense polymorphisms in human genes.

Background A great amount of data has been accumulated on genetic variations in the human genome, but we still do not know much about how the genetic variations affect gene function. In particular, little is known about the distribution of nonsense polymorphisms in human genes despite their drastic effects on gene products. Methodology/Principal Findings To detect polymorphisms affecting gene function, we analyzed all publicly available polymorphisms in a database for single nucleotide polymorphisms (dbSNP build 125) located in the exons of 36,712 known and predicted protein-coding genes that were defined in an annotation project of all human genes and transcripts (H-InvDB ver3.8). We found a total of 252,555 single nucleotide polymorphisms (SNPs) and 8,479 insertion and deletions in the representative transcripts in these genes. The SNPs located in ORFs include 40,484 synonymous and 53,754 nonsynonymous SNPs, and 1,258 SNPs that were predicted to be nonsense SNPs or read-through SNPs. We estimated the density of nonsense SNPs to be 0.85×10−3 per site, which is lower than that of nonsynonymous SNPs (2.1×10−3 per site). On average, nonsense SNPs were located 250 codons upstream of the original termination codon, with the substitution occurring most frequently at the first codon position. Of the nonsense SNPs, 581 were predicted to cause nonsense-mediated decay (NMD) of transcripts that would prevent translation. We found that nonsense SNPs causing NMD were more common in genes involving kinase activity and transport. The remaining 602 nonsense SNPs are predicted to produce truncated polypeptides, with an average truncation of 75 amino acids. In addition, 110 read-through SNPs at termination codons were detected. Conclusion/Significance Our comprehensive exploration of nonsense polymorphisms showed that nonsense SNPs exist at a lower density than nonsynonymous SNPs, suggesting that nonsense mutations have more severe effects than amino acid changes. The correspondence of nonsense SNPs to known pathological variants suggests that phenotypic effects of nonsense SNPs have been reported for only a small fraction of nonsense SNPs, and that nonsense SNPs causing NMD are more likely to be involved in phenotypic variations. These nonsense SNPs may include pathological variants that have not yet been reported. These data are available from Transcript View of H-InvDB and VarySysDB (http://h-invitational.jp/varygene/).

VarySysDB: a human genetic polymorphism database based on all H-InvDB transcripts

Creation of a vast variety of proteins is accomplished by genetic variation and a variety of alternative splicing transcripts. Currently, however, the abundant available data on genetic variation and the transcriptome are stored independently and in a dispersed fashion. In order to provide a research resource regarding the effects of human genetic polymorphism on various transcripts, we developed VarySysDB, a genetic polymorphism database based on 187 156 extensively annotated matured mRNA transcripts from 36 073 loci provided by H-InvDB. VarySysDB offers information encompassing published human genetic polymorphisms for each of these transcripts separately. This allows comparisons of effects derived from a polymorphism on different transcripts. The published information we analyzed includes single nucleotide polymorphisms and deletion–insertion polymorphisms from dbSNP, copy number variations from Database of Genomic Variants, short tandem repeats and single amino acid repeats from H-InvDB and linkage disequilibrium regions from D-HaploDB. The information can be searched and retrieved by features, functions and effects of polymorphisms, as well as by keywords. VarySysDB combines two kinds of viewers, GBrowse and Sequence View, to facilitate understanding of the positional relationship among polymorphisms, genome, transcripts, loci and functional domains. We expect that VarySysDB will yield useful information on polymorphisms affecting gene expression and phenotypes. VarySysDB is available at http://h-invitational.jp/varygene/.

Linkage of Amino Acid Variation and Evolution of Human Immunodeficiency Virus Type 1 gp120 Envelope Glycoprotein (Subtype B) with Usage of the Second Receptor

To clarify the relationship between the amino acid variations of the gp120 of human immunodeficiency virus type 1 (HIV-1) and the chemokine receptors that are used as the second receptor for HIV, we evaluated amino acid site variation of gp120 between the X4 strains (use CXCR4) and the R5 strains (use CCR5) from 21 sequences of subtype B. Our analysis showed that residues 306 and 322 in the V3 loop and residue 440 in the C4 region were associated with usage of the second receptor. The polymorphism at residue 440 is clearly associated with the usage of the second receptor: The amino acid at position 440 was a basic amino acid in the R5 strains, and a nonbasic and smaller amino acid in the X4 strains, while the V3 loop of the X4 strains was more basic than that of the R5 strains. This suggests that residue 440 in the C4 region, which is close to the V3 loop in the three-dimensional structure, is critical in determining which second receptor is used. Analysis of codon frequency suggests that, in almost all cases, the difference at residue 440 between basic amino acids in the R5 strains and nonbasic amino acids in the X4 strains could be due to a single nucleotide change. These findings predict that the evolutionary changes in amino acid residue 440 may be correlated with evolutionary changes in the V3 loop. One possibility is that a change in electric charge at residue 440 compensates for a change in electric charge in the V3 loop. The amino acid polymorphism at position 440 can be useful to predict the cell tropism of a strain of HIV-1 subtype B.

A prioritization analysis of disease association by data-mining of functional annotation of human genes

Complex diseases result from contributions of multiple genes that act in concert through pathways. Here we present a method to prioritize novel candidates of disease-susceptibility genes depending on the biological similarities to the known disease-related genes. The extent of disease-susceptibility of a gene is prioritized by analyzing seven features of human genes captured in H-InvDB. Taking rheumatoid arthritis (RA) and prostate cancer (PC) as two examples, we evaluated the efficiency of our method. Highly scored genes obtained included TNFSF12 and OSM as candidate disease genes for RA and PC, respectively. Subsequent characterization of these genes based upon an extensive literature survey reinforced the validity of these highly scored genes as possible disease-susceptibility genes. Our approach, Prioritization ANalysis of Disease Association (PANDA), is an efficient and cost-effective method to narrow down a large set of genes into smaller subsets that are most likely to be involved in the disease pathogenesis.

Prediction of Protein-Destabilizing Polymorphisms by Manual Curation with Protein Structure

The relationship between sequence polymorphisms and human disease has been studied mostly in terms of effects of single nucleotide polymorphisms (SNPs) leading to single amino acid substitutions that change protein structure and function. However, less attention has been paid to more drastic sequence polymorphisms which cause premature termination of a protein’s sequence or large changes, insertions, or deletions in the sequence. We have analyzed a large set (n = 512) of insertions and deletions (indels) and single nucleotide polymorphisms causing premature termination of translation in disease-related genes. Prediction of protein-destabilization effects was performed by graphical presentation of the locations of polymorphisms in the protein structure, using the Genomes TO Protein (GTOP) database, and manual annotation with a set of specific criteria. Protein-destabilization was predicted for 44.4% of the nonsense SNPs, 32.4% of the frameshifting indels, and 9.1% of the non-frameshifting indels. A prediction of nonsense-mediated decay allowed to infer which truncated proteins would actually be translated as defective proteins. These cases included the proteins linked to diseases inherited dominantly, suggesting a relation between these diseases and toxic aggregation. Our approach would be useful in identifying potentially aggregation-inducing polymorphisms that may have pathological effects.