Biomedical subjects

Melissa J Hubisz

Publications and source records attributed to Melissa J Hubisz.

9 recordsLinked to original sources

PubMed2026

Evolution of maize recombination landscape during domestication.

Despite the plethora of knowledge about the benefits of meiotic recombination and numerous theoretical studies examining how recombination rates evolve, there is a general lack of empirical support and consensus across species. To fill this knowledge gap, we characterized the evolution of recombination landscape in maize during its domestication from teosinte and related the observed changes to established theoretical frameworks. Through examining recombination in experimental populations of maize and teosinte and the population genomics approach of identifying historical recombination events using ancestral recombination graph inference to generate saturated maize and teosinte recombination maps, we found that during domestication, maize experienced a 12% increase in its genome-wide recombination rate. Furthermore, maize evolved higher recombination rates on the long arms of chromosomes in regions closer to centromeres, where recombination is generally very low. The repatterning of crossover events came from changes in global crossover positioning rather than alterations in cis-acting chromatin factors. Consequently, we found evidence of selection acting on trans-acting recombination modifiers affecting crossover interference and controlling the interference-dependent class I crossover pathway. We show that CO repatterning was likely beneficial for maize fitness, as significant recombination rate increases were predominantly in gene-rich regions, which harbor domestication-related variation. This work suggests genomic and mechanistic processes leading to the evolution of meiotic recombination landscape in response to directional selection pressure and provides evidence for the evolutionary advantage of recombination.

Zea mays↗

PubMed2006

Maximum likelihood estimation of ancestral codon usage bias parameters in Drosophila.

We present a likelihood method for estimating codon usage bias parameters along the lineages of a phylogeny. The method is an extension of the classical codon-based models used for estimating dN/dS ratios along the lineages of a phylogeny. However, we add one extra parameter for each lineage: the selection coefficient for optimal codon usage (S), allowing joint maximum likelihood estimation of S and the dN/dS ratio. We apply the method to previously published data from Drosophila melanogaster, Drosophila simulans, and Drosophila yakuba and show, in accordance with previous results, that the D. melanogaster lineage has experienced a reduction in the selection for optimal codon usage. However, the D. melanogaster lineage has also experienced a change in the biological mutation rates relative to D. simulans, in particular, a relative reduction in the mutation rate from A to G and an increase in the mutation rate from C to T. However, neither a reduction in the strength of selection nor a change in the mutational pattern can alone explain all of the data observed in the D. melanogaster lineage. For example, we also confirm previous results showing that the Notch locus has experienced positive selection for previously classified unpreferred mutations.

Animals↗

PubMed2005

A scan for positively selected genes in the genomes of humans and chimpanzees.

Since the divergence of humans and chimpanzees about 5 million years ago, these species have undergone a remarkable evolution with drastic divergence in anatomy and cognitive abilities. At the molecular level, despite the small overall magnitude of DNA sequence divergence, we might expect such evolutionary changes to leave a noticeable signature throughout the genome. We here compare 13,731 annotated genes from humans to their chimpanzee orthologs to identify genes that show evidence of positive selection. Many of the genes that present a signature of positive selection tend to be involved in sensory perception or immune defenses. However, the group of genes that show the strongest evidence for positive selection also includes a surprising number of genes involved in tumor suppression and apoptosis, and of genes involved in spermatogenesis. We hypothesize that positive selection in some of these genes may be driven by genomic conflict due to apoptosis during spermatogenesis. Genes with maximal expression in the brain show little or no evidence for positive selection, while genes with maximal expression in the testis tend to be enriched with positively selected genes. Genes on the X chromosome also tend to show an elevated tendency for positive selection. We also present polymorphism data from 20 Caucasian Americans and 19 African Americans for the 50 annotated genes showing the strongest evidence for positive selection. The polymorphism analysis further supports the presence of positive selection in these genes by showing an excess of high-frequency derived nonsynonymous mutations.

Animals↗

PubMed2005

Evolutionary genomics: detecting selection needs comparative data.

Positive selection at the molecular level is usually indicated by an increase in the ratio of non-synonymous to synonymous substitutions (dN/dS) in comparative data. However, Plotkin et al. describe a new method for detecting positive selection based on a single nucleotide sequence. We show here that this method is particularly sensitive to assumptions regarding the underlying mutational processes and does not provide a reliable way to identify positive selection.

Animals↗

PubMed2005

Detecting coevolving amino acid sites using Bayesian mutational mapping.

MOTIVATION: The evolution of protein sequences is constrained by complex interactions between amino acid residues. Because harmful substitutions may be compensated for by other substitutions at neighboring sites, residues can coevolve. We describe a Bayesian phylogenetic approach to the detection of coevolving residues in protein families. This method, Bayesian mutational mapping (BMM), assigns mutations to the branches of the evolutionary tree stochastically, and then test statistics are calculated to determine whether a coevolutionary signal exists in the mapping. Posterior predictive P-values provide an estimate of significance, and specificity is maintained by integrating over uncertainty in the estimation of the tree topology, branch lengths and substitution rates. A coevolutionary Markov model for codon substitution is also described, and this model is used as the basis of several test statistics. RESULTS: Results on simulated coevolutionary data indicate that the BMM method can successfully detect nearly all coevolving sites when the model has been correctly specified, and that non-parametric statistics such as mutual information are generally less powerful than parametric statistics. On a dataset of eukaryotic proteins from the phosphoglycerate kinase (PGK) family, interdomain site contacts yield a significantly greater coevolutionary signal than interdomain non-contacts, an indication that the method provides information about interacting sites. Failure to account for the heterogeneity in rates across sites in PGK resulted in a less discriminating test, yielding a marked increase in the number of reported positives at both contact and non-contact sites. SUPPLEMENTARY INFORMATION: http://www.dimmic.net/supplement/

Amino Acids↗

PubMed2005

Comparative genome sequencing of Drosophila pseudoobscura: chromosomal, gene, and cis-element evolution.

We have sequenced the genome of a second Drosophila species, Drosophila pseudoobscura, and compared this to the genome sequence of Drosophila melanogaster, a primary model organism. Throughout evolution the vast majority of Drosophila genes have remained on the same chromosome arm, but within each arm gene order has been extensively reshuffled, leading to a minimum of 921 syntenic blocks shared between the species. A repetitive sequence is found in the D. pseudoobscura genome at many junctions between adjacent syntenic blocks. Analysis of this novel repetitive element family suggests that recombination between offset elements may have given rise to many paracentric inversions, thereby contributing to the shuffling of gene order in the D. pseudoobscura lineage. Based on sequence similarity and synteny, 10,516 putative orthologs have been identified as a core gene set conserved over 25-55 million years (Myr) since the pseudoobscura/melanogaster divergence. Genes expressed in the testes had higher amino acid sequence divergence than the genome-wide average, consistent with the rapid evolution of sex-specific proteins. Cis-regulatory sequences are more conserved than random and nearby sequences between the species--but the difference is slight, suggesting that the evolution of cis-regulatory elements is flexible. Overall, a pattern of repeat-mediated chromosomal rearrangement, and high coadaptation of both male genes and cis-regulatory sequences emerges as important themes of genome divergence between these species of Drosophila.

Animals↗

PubMed2005

Ascertainment bias in studies of human genome-wide polymorphism.

Large-scale SNP genotyping studies rely on an initial assessment of nucleotide variation to identify sites in the DNA sequence that harbor variation among individuals. This "SNP discovery" sample may be quite variable in size and composition, and it has been well established that properties of the SNPs that are found are influenced by the discovery sampling effort. The International HapMap project relied on nearly any piece of information available to identify SNPs-including BAC end sequences, shotgun reads, and differences between public and private sequences-and even made use of chimpanzee data to confirm human sequence differences. In addition, the ascertainment criteria shifted from using only SNPs that had been validated in population samples, to double-hit SNPs, to finally accepting SNPs that were singletons in small discovery samples. In contrast, Perlegen's primary discovery was a resequencing-by-hybridization effort using the 24 people of diverse origin in the Polymorphism Discovery Resource. Here we take these two data sets and contrast two basic summary statistics, heterozygosity and F(ST), as well as the site frequency spectra, for 500-kb windows spanning the genome. The magnitude of disparity between these samples in these measures of variability indicates that population genetic analysis on the raw genotype data is ill advised. Given the knowledge of the discovery samples, we perform an ascertainment correction and show how the post-correction data are more consistent across these studies. However, discrepancies persist, suggesting that the heterogeneity in the SNP discovery process of the HapMap project resulted in a data set resistant to complete ascertainment correction. Ascertainment bias will likely erode the power of tests of association between SNPs and complex disorders, but the effect will likely be small, and perhaps more importantly, it is unlikely that the bias will introduce false-positive inferences.

Databases, Genetic↗

PubMed2005

Genomic scans for selective sweeps using SNP data.

Detecting selective sweeps from genomic SNP data is complicated by the intricate ascertainment schemes used to discover SNPs, and by the confounding influence of the underlying complex demographics and varying mutation and recombination rates. Current methods for detecting selective sweeps have little or no robustness to the demographic assumptions and varying recombination rates, and provide no method for correcting for ascertainment biases. Here, we present several new tests aimed at detecting selective sweeps from genomic SNP data. Using extensive simulations, we show that a new parametric test, based on composite likelihood, has a high power to detect selective sweeps and is surprisingly robust to assumptions regarding recombination rates and demography (i.e., has low Type I error). Our new test also provides estimates of the location of the selective sweep(s) and the magnitude of the selection coefficient. To illustrate the method, we apply our approach to data from the Seattle SNP project and to Chromosome 2 data from the HapMap project. In Chromosome 2, the most extreme signal is found in the lactase gene, which previously has been shown to be undergoing positive selection. Evidence for selective sweeps is also found in many other regions, including genes known to be associated with disease risk such as DPP10 and COL4A3.

Black or African American↗

PubMed2004

Reconstituting the frequency spectrum of ascertained single-nucleotide polymorphism data.

Most of the available SNP data have eluded valid population genetic analysis because most population genetical methods do not correctly accommodate the special discovery process used to identify SNPs. Most of the available SNP data have allele frequency distributions that are biased by the ascertainment protocol. We here show how this problem can be corrected by obtaining maximum-likelihood estimates of the true allele frequency distribution. In simple cases, the ML estimate of the true allele frequency distribution can be obtained analytically, but in other cases computational methods based on numerical optimization or the EM algorithm must be used. We illustrate the new correction method by analyzing some previously published SNP data from the SNP Consortium. Appropriate treatment of SNP ascertainment is vital to our ability to make correct inferences from the data of the International HapMap Project.

Alleles↗