Biomedical subjects

Maitreya J Dunham

Publications and source records attributed to Maitreya J Dunham.

6 recordsLinked to original sources

PubMed2006

Functional analysis of gene duplications in Saccharomyces cerevisiae.

Gene duplication can occur on two scales: whole-genome duplications (WGD) and smaller-scale duplications (SSD) involving individual genes or genomic segments. Duplication may result in functionally redundant genes or diverge in function through neofunctionalization or subfunctionalization. The effect of duplication scale on functional evolution has not yet been explored, probably due to the lack of global knowledge of protein function and different times of duplication events. To address this question, we used integrated Bayesian analysis of diverse functional genomic data to accurately evaluate the extent of functional similarity and divergence between paralogs on a global scale. We found that paralogs resulting from the whole-genome duplication are more likely to share interaction partners and biological functions than smaller-scale duplicates, independent of sequence similarity. In addition, WGD paralogs show lower frequency of essential genes and higher synthetic lethality rate, but instead diverge more in expression pattern and upstream regulatory region. Thus, our analysis demonstrates that WGD paralogs generally have similar compensatory functions but diverging expression patterns, suggesting a potential of distinct evolutionary scenarios for paralogs that arose through different duplication mechanisms. Furthermore, by identifying these functional disparities between the two types of duplicates, we reconcile previous disputes on the relationship between sequence divergence and expression divergence or essentiality.

Bayes Theorem↗

PubMed2006

Global mapping of transposon location.

Transposable genetic elements are ubiquitous, yet their presence or absence at any given position within a genome can vary between individual cells, tissues, or strains. Transposable elements have profound impacts on host genomes by altering gene expression, assisting in genomic rearrangements, causing insertional mutations, and serving as sources of phenotypic variation. Characterizing a genome's full complement of transposons requires whole genome sequencing, precluding simple studies of the impact of transposition on interindividual variation. Here, we describe a global mapping approach for identifying transposon locations in any genome, using a combination of transposon-specific DNA extraction and microarray-based comparative hybridization analysis. We use this approach to map the repertoire of endogenous transposons in different laboratory strains of Saccharomyces cerevisiae and demonstrate that transposons are a source of extensive genomic variation. We also apply this method to mapping bacterial transposon insertion sites in a yeast genomic library. This unique whole genome view of transposon location will facilitate our exploration of transposon dynamics, as well as defining bases for individual differences and adaptive potential.

Chromosome Mapping↗

PubMed2006

Mapping novel traits by array-assisted bulk segregant analysis in Saccharomyces cerevisiae.

We demonstrate a new method, microarray-assisted bulk segregant analysis, for mapping traits in yeast by genotyping pooled segregants. We apply a probabilistic model to the progeny of a single cross and as little as two microarray hybridizations to reliably map an auxotrophic marker, a Mendelian trait, and a major-effect quantitative trait locus.

Chromosome Mapping↗

PubMed2006

Genome-wide detection of polymorphisms at nucleotide resolution with a single DNA microarray.

A central challenge of genomics is to detect, simply and inexpensively, all differences in sequence among the genomes of individual members of a species. We devised a system to detect all single-nucleotide differences between genomes with the use of data from a single hybridization to a whole-genome DNA microarray. This allowed us to detect a variety of spontaneous single-base pair substitutions, insertions, and deletions, and most (>90%) of the approximately 30,000 known single-nucleotide polymorphisms between two Saccharomyces cerevisiae strains. We applied this approach to elucidate the genetic basis of phenotypic variants and to identify the small number of single-base pair changes accumulated during experimental evolution of yeast.

Directed Molecular Evolution↗

PubMed2004

Accurate detection of aneuploidies in array CGH and gene expression microarray data.

MOTIVATION: Chromosomal copy number changes (aneuploidies) are common in cell populations that undergo multiple cell divisions including yeast strains, cell lines and tumor cells. Identification of aneuploidies is critical in evolutionary studies, where changes in copy number serve an adaptive purpose, as well as in cancer studies, where amplifications and deletions of chromosomal regions have been identified as a major pathogenetic mechanism. Aneuploidies can be studied on whole-genome level using array CGH (a microarray-based method that measures the DNA content), but their presence also affects gene expression. In gene expression microarray analysis, identification of copy number changes is especially important in preventing aberrant biological conclusions based on spurious gene expression correlation or masked phenotypes that arise due to aneuploidies. Previously suggested approaches for aneuploidy detection from microarray data mostly focus on array CGH, address only whole-chromosome or whole-arm copy number changes, and rely on thresholds or other heuristics, making them unsuitable for fully automated general application to gene expression datasets. There is a need for a general and robust method for identification of aneuploidies of any size from both array CGH and gene expression microarray data. RESULTS: We present ChARM (Chromosomal Aberration Region Miner), a robust and accurate expectation-maximization based method for identification of segmental aneuploidies (partial chromosome changes) from gene expression and array CGH microarray data. Systematic evaluation of the algorithm on synthetic and biological data shows that the method is robust to noise, aneuploidal segment size and P-value cutoff. Using our approach, we identify known chromosomal changes and predict novel potential segmental aneuploidies in commonly used yeast deletion strains and in breast cancer. ChARM can be routinely used to identify aneuploidies in array CGH datasets and to screen gene expression data for aneuploidies or array biases. Our methodology is sensitive enough to detect statistically significant and biologically relevant aneuploidies even when expression or DNA content changes are subtle as in mixed populations of cells. AVAILABILITY: Code available by request from the authors and on Web supplement at http://function.cs.princeton.edu/ChARM/

Algorithms↗

PubMed2002

Characteristic genome rearrangements in experimental evolution of Saccharomyces cerevisiae.

Genome rearrangements, especially amplifications and deletions, have regularly been observed as responses to sustained application of the same strong selective pressure in microbial populations growing in continuous culture. We studied eight strains of budding yeast (Saccharomyces cerevisiae) isolated after 100-500 generations of growth in glucose-limited chemostats. Changes in DNA copy number were assessed at single-gene resolution by using DNA microarray-based comparative genomic hybridization. Six of these evolved strains were aneuploid as the result of gross chromosomal rearrangements. Most of the aneuploid regions were the result of translocations, including three instances of a shared breakpoint on chromosome 14 immediately adjacent to CIT1, which encodes the citrate synthase that performs a key regulated step in the tricarboxylic acid cycle. Three strains had amplifications in a region of chromosome 4 that includes the high-affinity hexose transporters; one of these also had the aforementioned chromosome 14 break. Three strains had extensive overlapping deletions of the right arm of chromosome 15. Further analysis showed that each of these genome rearrangements was bounded by transposon-related sequences at the breakpoints. The observation of repeated, independent, but nevertheless very similar, chromosomal rearrangements in response to persistent selection of growing cells parallels the genome rearrangements that characteristically accompany tumor progression.

Aneuploidy↗