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Biomedical subjects

Andrew G Clark

Publications and source records attributed to Andrew G Clark.

At least 55 records · Page 3Linked to original sources

Genetic basis of natural variation in D. melanogaster antibacterial immunity.

Many genes involved in Drosophila melanogaster innate immune processes have been identified, but whether naturally occurring polymorphism in these genes leads to variation in immune competence among wild flies has not been tested. We report here substantial variability among wild-derived D. melanogaster in the ability to suppress infection by a Gram-negative entomopathogen, Serratia marcescens. Variability in immune competence was significantly associated with nucleotide polymorphism in 16 innate immunity genes, corresponding primarily to pathogen recognition and intracellular signaling loci, and substantial epistasis was detected between intracellular signaling and antimicrobial peptide genes. Variation in these genes, therefore, seems to drive variability in immunocompetence among wild Drosophila.

Alleles↗

Whole-genome shotgun assembly and comparison of human genome assemblies.

We report a whole-genome shotgun assembly (called WGSA) of the human genome generated at Celera in 2001. The Celera-generated shotgun data set consisted of 27 million sequencing reads organized in pairs by virtue of end-sequencing 2-kbp, 10-kbp, and 50-kbp inserts from shotgun clone libraries. The quality-trimmed reads covered the genome 5.3 times, and the inserts from which pairs of reads were obtained covered the genome 39 times. With the nearly complete human DNA sequence [National Center for Biotechnology Information (NCBI) Build 34] now available, it is possible to directly assess the quality, accuracy, and completeness of WGSA and of the first reconstructions of the human genome reported in two landmark papers in February 2001 [Venter, J. C., Adams, M. D., Myers, E. W., Li, P. W., Mural, R. J., Sutton, G. G., Smith, H. O., Yandell, M., Evans, C. A., Holt, R. A., et al. (2001) Science 291, 1304-1351; International Human Genome Sequencing Consortium (2001) Nature 409, 860-921]. The analysis of WGSA shows 97% order and orientation agreement with NCBI Build 34, where most of the 3% of sequence out of order is due to scaffold placement problems as opposed to assembly errors within the scaffolds themselves. In addition, WGSA fills some of the remaining gaps in NCBI Build 34. The early genome sequences all covered about the same amount of the genome, but they did so in different ways. The Celera results provide more order and orientation, and the consortium sequence provides better coverage of exact and nearly exact repeats.

Computational Biology↗

The role of haplotypes in candidate gene studies.

Human geneticists working on systems for which it is possible to make a strong case for a set of candidate genes face the problem of whether it is necessary to consider the variation in those genes as phased haplotypes, or whether the one-SNP-at-a-time approach might perform as well. There are three reasons why the phased haplotype route should be an improvement. First, the protein products of the candidate genes occur in polypeptide chains whose folding and other properties may depend on particular combinations of amino acids. Second, population genetic principles show us that variation in populations is inherently structured into haplotypes. Third, the statistical power of association tests with phased data is likely to be improved because of the reduction in dimension. However, in reality it takes a great deal of extra work to obtain valid haplotype phase information, and inferred phase information may simply compound the errors. In addition, if the causal connection between SNPs and a phenotype is truly driven by just a single SNP, then the haplotype-based approach may perform worse than the one-SNP-at-a-time approach. Here we examine some of the factors that affect haplotype patterns in genes, how haplotypes may be inferred, and how haplotypes have been useful in the context of testing association between candidate genes and complex traits.

Genetic Predisposition to Disease↗

Optimal haplotype block-free selection of tagging SNPs for genome-wide association studies.

It is widely hoped that the study of sequence variation in the human genome will provide a means of elucidating the genetic component of complex diseases and variable drug responses. A major stumbling block to the successful design and execution of genome-wide disease association studies using single-nucleotide polymorphisms (SNPs) and linkage disequilibrium is the enormous number of SNPs in the human genome. This results in unacceptably high costs for exhaustive genotyping and presents a challenging problem of statistical inference. Here, we present a new method for optimally selecting minimum informative subsets of SNPs, also known as "tagging" SNPs, that is efficient for genome-wide selection. We contrast this method to published methods including haplotype block tagging, that is, grouping SNPs into segments of low haplotype diversity and typing a subset of the SNPs that can discriminate all common haplotypes within the blocks. Because our method does not rely on a predefined haplotype block structure and makes use of the weaker correlations that occur across neighboring blocks, it can be effectively applied across chromosomal regions with both high and low local linkage disequilibrium. We show that the number of tagging SNPs selected is substantially smaller than previously reported using block-based approaches and that selecting tagging SNPs optimally can result in a two- to threefold savings over selecting random SNPs.

Algorithms↗

The effect of genetic conflict on genomic imprinting and modification of expression at a sex-linked locus.

We examine how genomic imprinting may have evolved at an X-linked locus, using six diallelic models of selection in which one allele is imprintable and the other is not. Selection pressures are generated by genetic conflict between mothers and their offspring. The various models describe cases of maternal and paternal inactivation, in which females may be monogamous or bigamous. When inactivation is maternal, we examine the situations in which only female offspring exhibit imprinting as well as when both sexes do. We compare our results to those previously obtained for an autosomal locus and to four models in which a dominant modifier of biallelic expression is subjected to the same selection pressures. We find that, in accord with verbal predictions, maternal inactivation of growth enhancers and paternal inactivation of growth inhibitors are more likely than imprinting in the respective opposite directions, although these latter outcomes are possible for certain parameter combinations. The expected outcomes are easier to evolve than the same outcomes for autosomal loci, contradicting the available evidence concerning the direction of imprinting on mammalian sex chromosomes. In most of our models stable polymorphism of imprinting status is possible, a behavior not predicted by verbal accounts.

Animals↗

Specificity determinants and diversification of the Brassica self-incompatibility pollen ligand.

Self-incompatibility in crucifers is effected by allele-specific interactions between the highly polymorphic stigmatic S locus receptor kinase (SRK) and its pollen ligand, the S locus cysteine-rich protein (SCR). Here we show that specificity in SCR function is determined by four contiguous amino acids in one variant, indicating that the minimum sequence requirement for gaining a new specificity can be low. We also provide evidence for an extraordinarily high degree of evolutionary flexibility in SCR, whereby SCR can tolerate extensive amino acid changes within the limits of maintaining the same predicted overall structure. This remarkable adaptability suggests a hypothesis for generation of new self-incompatibility specificities by gradual modification of SRK-SCR affinities and, more generally, for functional specialization within families of homologous ligands and receptors.

Amino Acid Sequence↗

Inferring nonneutral evolution from human-chimp-mouse orthologous gene trios.

Even though human and chimpanzee gene sequences are nearly 99% identical, sequence comparisons can nevertheless be highly informative in identifying biologically important changes that have occurred since our ancestral lineages diverged. We analyzed alignments of 7645 chimpanzee gene sequences to their human and mouse orthologs. These three-species sequence alignments allowed us to identify genes undergoing natural selection along the human and chimp lineage by fitting models that include parameters specifying rates of synonymous and nonsynonymous nucleotide substitution. This evolutionary approach revealed an informative set of genes with significantly different patterns of substitution on the human lineage compared with the chimpanzee and mouse lineages. Partitions of genes into inferred biological classes identified accelerated evolution in several functional classes, including olfaction and nuclear transport. In addition to suggesting adaptive physiological differences between chimps and humans, human-accelerated genes are significantly more likely to underlie major known Mendelian disorders.

Active Transport, Cell Nucleus↗

Genomewide distribution of high-frequency, completely mismatching SNP haplotype pairs observed to be common across human populations.

Knowledge of human haplotype structure has important implications for strategies of disease-gene mapping and for understanding human evolutionary history. Many attributes of SNPs and haplotypes appear to exhibit highly nonrandom behavior, suggesting past operation of selection or other nonneutral forces. We report the exceptional abundance of a particular haplotype pattern in which two high-frequency haplotypes have different alleles at every SNP site (hence the name "yin yang haplotypes"). Analysis of common haplotypes in 62 random genomic loci and 85 gene coding regions in humans shows that the proportion of the genome spanned by yin yang haplotypes is 75%-85%. Population data of 28 genomic loci in Drosophila melanogaster reveal a similar pattern. The high recurrence (>/=85%) of these haplotype patterns in four distinct human populations suggests that the yin yang haplotypes are likely to predate the African diaspora. The pattern initially appeared to suggest deep population splitting or maintenance of ancient lineages by selection; however, coalescent simulation reveals that the yin yang phenomenon can be explained by strictly neutral evolution in a well-mixed population.

Algorithms↗

A 3.9-centimorgan-resolution human single-nucleotide polymorphism linkage map and screening set.

Recent advances in technologies for high-throughout single-nucleotide polymorphism (SNP)-based genotyping have improved efficiency and cost so that it is now becoming reasonable to consider the use of SNPs for genomewide linkage analysis. However, a suitable screening set of SNPs and a corresponding linkage map have yet to be described. The SNP maps described here fill this void and provide a resource for fast genome scanning for disease genes. We have evaluated 6,297 SNPs in a diversity panel composed of European Americans, African Americans, and Asians. The markers were assessed for assay robustness, suitable allele frequencies, and informativeness of multi-SNP clusters. Individuals from 56 Centre d'Etude du Polymorphisme Humain pedigrees, with >770 potentially informative meioses altogether, were genotyped with a subset of 2,988 SNPs, for map construction. Extensive genotyping-error analysis was performed, and the resulting SNP linkage map has an average map resolution of 3.9 cM, with map positions containing either a single SNP or several tightly linked SNPs. The order of markers on this map compares favorably with several other linkage and physical maps. We compared map distances between the SNP linkage map and the interpolated SNP linkage map constructed by the deCode Genetics group. We also evaluated cM/Mb distance ratios in females and males, along each chromosome, showing broadly defined regions of increased and decreased rates of recombination. Evaluations indicate that this SNP screening set is more informative than the Marshfield Clinic's commonly used microsatellite-based screening set.

Alleles↗

Linkage disequilibrium and inference of ancestral recombination in 538 single-nucleotide polymorphism clusters across the human genome.

The prospect of using linkage disequilibrium (LD) for fine-scale mapping in humans has attracted considerable attention, and, during the validation of a set of single-nucleotide polymorphisms (SNPs) for linkage analysis, a set of data for 4,833 SNPs in 538 clusters was produced that provides a rich picture of local attributes of LD across the genome. LD estimates may be biased depending on the means by which SNPs are first identified, and a particular problem of ascertainment bias arises when SNPs identified in small heterogeneous panels are subsequently typed in larger population samples. Understanding and correcting ascertainment bias is essential for a useful quantitative assessment of the landscape of LD across the human genome. Heterogeneity in the population recombination rate, rho=4Nr, along the genome reflects how variable the density of markers will have to be for optimal coverage. We find that ascertainment-corrected rho varies along the genome by more than two orders of magnitude, implying great differences in the recombinational history of different portions of our genome. The distribution of rho is unimodal, and we show that this is compatible with a wide range of mixtures of hotspots in a background of variable recombination rate. Although rho is significantly correlated across the three population samples, some regions of the genome exhibit population-specific spikes or troughs in rho that are too large to be explained by sampling. This result is consistent with differences in the genealogical depth of local genomic regions, a finding that has direct bearing on the design and utility of LD mapping and on the National Institutes of Health HapMap project.

Alleles↗

Natural variation in human membrane transporter genes reveals evolutionary and functional constraints.

Membrane transporters maintain cellular and organismal homeostasis by importing nutrients and exporting toxic compounds. Transporters also play a crucial role in drug response, serving as drug targets and setting drug levels. As part of a pharmacogenetics project, we screened exons and flanking intronic regions for variation in a set of 24 membrane transporter genes (96 kb; 57% coding) in 247 DNA samples from ethnically diverse populations. We identified 680 single nucleotide polymorphisms (SNPs), of which 175 were synonymous and 155 caused amino acid changes, and 29 small insertions and deletions. Amino acid diversity (pi(NS)) in transmembrane domains (TMDs) was significantly lower than in loop domains, suggesting that TMDs have special functional constraints. This difference was especially striking in the ATP-binding cassette superfamily and did not parallel evolutionary conservation: there was little variation in the TMDs, even in evolutionarily unconserved residues. We used allele frequency distribution to evaluate different scoring systems (Grantham, blosum62, SIFT, and evolutionarily conservedevolutionarily unconserved) for their ability to predict which SNPs affect function. Our underlying assumption was that alleles that are functionally deleterious will be selected against and thus under represented at high frequencies and over represented at low frequencies. We found that evolutionary conservation of orthologous sequences, as assessed by evolutionarily conservedevolutionarily unconserved and SIFT, was the best predictor of allele frequency distribution and hence of function. European Americans had an excess of high frequency alleles in comparison to African Americans, consistent with a historic bottleneck. In addition, African Americans exhibited a much higher frequency of population specific medium-frequency alleles than did European Americans.

DNA↗

Molecular population genetics of inducible antibacterial peptide genes in Drosophila melanogaster.

Insects respond to septic infection in part by producing a suite of antimicrobial peptides that may be subject to host-pathogen coevolutionary dynamics. In order to infer population genetic forces acting on Drosophila antibacterial peptide genes, we examine global properties of polymorphism and divergence in the Drosophila melanogaster defensin, drosocin, metchnikowin, attacin C, diptericin A, and cecropin A, B, and C genes. As a functional class, antibacterial peptides exhibit low levels of interspecific amino acid divergence. There are multiple amino acid polymorphisms segregating within D. melanogaster, however, a high proportion of which change the charge or polarity of the variable residue. These polymorphisms are particularly prevalent in processed signal and propeptide domains. We find that models of coevolutionary "arms races" and selectively maintained hypervariability do not adequately describe the population dynamics of mature antibacterial peptides in D. melanogaster, but that a highly significant excess of high-frequency derived polymorphisms coupled with substantial intralocus linkage disequilibrium suggests that positive selection may act on antibacterial peptide genes. Some attributes of the data may be consistent with a simple demographic model of population founding followed by expansion, but departures from the equilibrium null tend to be more pronounced in the peptide genes than at other loci around the genome.

Amino Acid Sequence↗

Tracing the evolutionary history of Drosophila regulatory regions with models that identify transcription factor binding sites.

Much of evolutionary change is mediated at the level of gene expression, yet our understanding of regulatory evolution remains unsatisfying. In light of recent data indicating that transcription factor binding sites undergo substantial turnover between species, we attempt to quantify the process of binding site turnover in regulatory regions of well-studied genes controlling embryonic patterning in Drosophila. We examine polymorphism and divergence data in Drosophila melanogaster and four related species from regulatory regions of five early development genes for which functional binding sites have been identified. This analysis reveals that Drosophila regulatory regions exhibit patterns of variation consistent with functional constraint. We develop a novel approach to binding site prediction which we use to characterize the process of binding site divergence in regulatory regions. This method uses sets of known binding sites to construct a model that predicts transcription factor specificity and bootstrap sampling to derive significance levels. This approach allows appropriate significance levels to be determined even in the face of skewed base composition in the background sequence. Using this approach, we show that, although functional elements exhibit conservation of sequence, there is substantial potential to gain new functional elements within the regulatory regions. Our results show that application of models that predict transcription factor binding sites can yield insights into the process and dynamics of binding site evolution within regulatory regions.

Animals↗

Finding genes underlying risk of complex disease by linkage disequilibrium mapping.

Identification of genes that harbor variation associated with inter-individual differences in risk of complex diseases remains one of the most challenging and important problems in human genetics. For genetic variants that are sufficiently common and have sufficiently large effects, direct tests of association through linkage disequilibrium with anonymous SNPs may prove effective. But the two critical parameters - the frequency of risk-inflating alleles and the magnitudes of their effect on risk - remain largely unknown. In this review we consider the latest information regarding the likely efficacy of the linkage disequilibrium mapping approach.

Chromosome Mapping↗

Y chromosome and other heterochromatic sequences of the Drosophila melanogaster genome: how far can we go?

Whole genome shotgun assemblies have proven remarkably successful in reconstructing the bulk of euchromatic genes, with the only limit appearing to be determined by the sequencing depth. For genes imbedded in heterochromatin, however, the low cloning efficiency of repetitive sequences, combined with the computational challenges, demand that additional clues be used to annotate the sequences. One approach that has proven very successful in identifying protein coding genes in Y-linked heterochromatin of Drosophila melanogaster has been to make a BLASTable database of the small, unmapped contigs and fragments leftover at the end of a shotgun assembly, and to attempt to capture these by blasting with an appropriate query sequence. This approach often yields a staggered alignment of contigs from the unmapped set to the query sequence, as though the disjoint contigs represent small portions of the gene. Further inspection frequently shows that the contigs are broken by very large, heterochromatic introns. Methods of this sort are being expanded to make best use of all available clues to determine which unmapped contigs are associated with genes. These include use of EST libraries, and, in the case of the Y chromosome, testing of male specific genes and reduced shotgun depth of relevant contigs. It appears much more hopeful than anyone would have imagined that whole genome shotgun assemblies can recover the great bulk of even heterochromatic genes.

Animals↗

Robustness of inference of haplotype block structure.

In this report, we examine the validity of the haplotype block concept by comparing block decompositions derived from public data sets by variants of several leading methods of block detection. We first develop a statistical method for assessing the concordance of two block decompositions. We then assess the robustness of inferred haplotype blocks to the specific detection method chosen, to arbitrary choices made in the block-detection algorithms, and to the sample analyzed. Although the block decompositions show levels of concordance that are very unlikely by chance, the absolute magnitude of the concordance may be low enough to limit the utility of the inference. For purposes of SNP selection, it seems likely that methods that do not arbitrarily impose block boundaries among correlated SNPs might perform better than block-based methods.

Algorithms↗