16 research outputs found
Development and evaluation of new mask protocols for gene expression profiling in humans and chimpanzees
Abstract
Background
Cross-species gene expression analyses using oligonucleotide microarrays designed to evaluate a single species can provide spurious results due to mismatches between the interrogated transcriptome and arrayed probes. Based on the most recent human and chimpanzee genome assemblies, we developed updated and accessible probe masking methods that allow human Affymetrix oligonucleotide microarrays to be used for robust genome-wide expression analyses in both species. In this process, only data from oligonucleotide probes predicted to have robust hybridization sensitivity and specificity for both transcriptomes are retained for analysis.
Results
To characterize the utility of this resource, we applied our mask protocols to existing expression data from brains, livers, hearts, testes, and kidneys derived from both species and determined the effects probe numbers have on expression scores of specific transcripts. In all five tissues, probe sets with decreasing numbers of probes showed non-linear trends towards increased variation in expression scores. The relationships between expression variation and probe number in brain data closely matched those observed in simulated expression data sets subjected to random probe masking. However, there is evidence that additional factors affect the observed relationships between gene expression scores and probe number in tissues such as liver and kidney. In parallel, we observed that decreasing the number of probes within probe sets lead to linear increases in both gained and lost inferences of differential cross-species expression in all five tissues, which will affect the interpretation of expression data subject to masking.
Conclusion
We introduce a readily implemented and updated resource for human and chimpanzee transcriptome analysis through a commonly used microarray platform. Based on empirical observations derived from the analysis of five distinct data sets, we provide novel guidelines for the interpretation of masked data that take the number of probes present in a given probe set into consideration. These guidelines are applicable to other customized applications that involve masking data from specific subsets of probes
mtDNA depletion confers specific gene expression profiles in human cells grown in culture and in xenograft
<p>Abstract</p> <p>Background</p> <p>Interactions between the gene products encoded by the mitochondrial and nuclear genomes play critical roles in eukaryotic cellular function. However, the effects mitochondrial DNA (mtDNA) levels have on the nuclear transcriptome have not been defined under physiological conditions. In order to address this issue, we characterized the gene expression profiles of A549 lung cancer cells and their mtDNA-depleted ρ<sup>0 </sup>counterparts grown in culture and as tumor xenografts in immune-deficient mice.</p> <p>Results</p> <p>Cultured A549 ρ<sup>0 </sup>cells were respiration-deficient and showed enhanced levels of transcripts relevant to metal homeostasis, initiation of the epithelial-mesenchymal transition, and glucuronidation pathways. Several well-established HIF-regulated transcripts showed increased or decreased abundance relative to the parental cell line. Furthermore, growth in culture versus xenograft has a significantly greater influence on expression profiles, including transcripts involved in mitochondrial structure and both aerobic and anaerobic energy metabolism. However, both <it>in vitro </it>and <it>in vivo</it>, mtDNA levels explained the majority of the variance observed in the expression of transcripts in glucuronidation, tRNA synthetase, and immune surveillance related pathways. mtDNA levels in A549 xenografts also affected the expression of genes, such as <it>AMACR </it>and <it>PHYH</it>, involved in peroxisomal lipid metabolic pathways.</p> <p>Conclusion</p> <p>We have identified mtDNA-dependent gene expression profiles that are shared in cultured cells and in xenografts. These profiles indicate that mtDNA-depleted cells could provide informative model systems for the testing the efficacy of select classes of therapeutics, such as anti-angiogenesis agents. Furthermore, mtDNA-depleted cells grown culture and in xenografts provide a powerful means to investigate possible relationships between mitochondrial activity and gene expression profiles in normal and pathological cells.</p
Nucleotide diversity maps reveal variation in diversity among wheat genomes and chromosomes
<p>Abstract</p> <p>Background</p> <p>A genome-wide assessment of nucleotide diversity in a polyploid species must minimize the inclusion of homoeologous sequences into diversity estimates and reliably allocate individual haplotypes into their respective genomes. The same requirements complicate the development and deployment of single nucleotide polymorphism (SNP) markers in polyploid species. We report here a strategy that satisfies these requirements and deploy it in the sequencing of genes in cultivated hexaploid wheat (<it>Triticum aestivum</it>, genomes AABBDD) and wild tetraploid wheat (<it>Triticum turgidum </it>ssp. <it>dicoccoides</it>, genomes AABB) from the putative site of wheat domestication in Turkey. Data are used to assess the distribution of diversity among and within wheat genomes and to develop a panel of SNP markers for polyploid wheat.</p> <p>Results</p> <p>Nucleotide diversity was estimated in 2114 wheat genes and was similar between the A and B genomes and reduced in the D genome. Within a genome, diversity was diminished on some chromosomes. Low diversity was always accompanied by an excess of rare alleles. A total of 5,471 SNPs was discovered in 1791 wheat genes. Totals of 1,271, 1,218, and 2,203 SNPs were discovered in 488, 463, and 641 genes of wheat putative diploid ancestors, <it>T. urartu</it>, <it>Aegilops speltoides</it>, and <it>Ae. tauschii</it>, respectively. A public database containing genome-specific primers, SNPs, and other information was constructed. A total of 987 genes with nucleotide diversity estimated in one or more of the wheat genomes was placed on an <it>Ae. tauschii </it>genetic map, and the map was superimposed on wheat deletion-bin maps. The agreement between the maps was assessed.</p> <p>Conclusions</p> <p>In a young polyploid, exemplified by <it>T. aestivum</it>, ancestral species are the primary source of genetic diversity. Low effective recombination due to self-pollination and a genetic mechanism precluding homoeologous chromosome pairing during polyploid meiosis can lead to the loss of diversity from large chromosomal regions. The net effect of these factors in <it>T. aestivum </it>is large variation in diversity among genomes and chromosomes, which impacts the development of SNP markers and their practical utility. Accumulation of new mutations in older polyploid species, such as wild emmer, results in increased diversity and its more uniform distribution across the genome.</p
Estimating the Contribution of Mutation, Recombination and Gene Conversion in the Generation of Haplotypic Diversity
Recombination occurs through both homologous crossing over and homologous gene conversion during meiosis. The contribution of recombination relative to mutation is expected to be dramatically reduced in inbreeding organisms. We report coalescent-based estimates of the recombination parameter (ρ) relative to estimates of the mutation parameter (θ) for 18 genes from the highly self-fertilizing grass, wild barley, Hordeum vulgare ssp. spontaneum. Estimates of ρ/θ are much greater than expected, with a mean [Formula: see text] / [Formula: see text] ≈ 1.5, similar to estimates from outcrossing species. We also estimate [Formula: see text] with and without the contribution of gene conversion. Genotyping errors can mimic the effect of gene conversion, upwardly biasing estimates of the role of conversion. Thus we report a novel method for identifying genotyping errors in nucleotide sequence data sets. We show that there is evidence for gene conversion in many large nucleotide sequence data sets including our data that have been purged of all detectable sequencing errors and in data sets from Drosophila melanogaster, D. simulans, and Zea mays. In total, 13 of 27 loci show evidence of gene conversion. For these loci, gene conversion is estimated to contribute an average of twice as much as crossing over to total recombination
The IRIDICA BAC BSI Assay: Rapid, Sensitive and Culture-Independent Identification of Bacteria and Candida in Blood.
Bloodstream infection (BSI) and sepsis are rising in incidence throughout the developed world. The spread of multi-drug resistant organisms presents increasing challenges to treatment. Surviving BSI is dependent on rapid and accurate identification of causal organisms, and timely application of appropriate antibiotics. Current culture-based methods used to detect and identify agents of BSI are often too slow to impact early therapy and may fail to detect relevant organisms in many positive cases. Existing methods for direct molecular detection of microbial DNA in blood are limited in either sensitivity (likely the result of small sample volumes) or in breadth of coverage, often because the PCR primers and probes used target only a few specific pathogens. There is a clear unmet need for a sensitive molecular assay capable of identifying the diverse bacteria and yeast associated with BSI directly from uncultured whole blood samples. We have developed a method of extracting DNA from larger volumes of whole blood (5 ml per sample), amplifying multiple widely conserved bacterial and fungal genes using a mismatch- and background-tolerant PCR chemistry, and identifying hundreds of diverse organisms from the amplified fragments on the basis of species-specific genetic signatures using electrospray ionization mass spectrometry (PCR/ESI-MS). We describe the analytical characteristics of the IRIDICA BAC BSI Assay and compare its pre-clinical performance to current standard-of-care methods in a collection of prospectively collected blood specimens from patients with symptoms of sepsis. The assay generated matching results in 80% of culture-positive cases (86% when common contaminants were excluded from the analysis), and twice the total number of positive detections. The described method is capable of providing organism identifications directly from uncultured blood in less than 8 hours.The IRIDICA BAC BSI Assay is not available in the United States
Comparison of IRIDICA BAC BSI Assay and standard-of-care culture results in clinical blood specimens from patients with suspected bloodstream infections, summarized by organism group (details in Table 4).
<p>Comparison of IRIDICA BAC BSI Assay and standard-of-care culture results in clinical blood specimens from patients with suspected bloodstream infections, summarized by organism group (details in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0158186#pone.0158186.t004" target="_blank">Table 4</a>).</p
Antibiotic resistance marker results summary.
<p>Antibiotic resistance marker results summary.</p
Detailed results from samples with additional detections.
<p>Detailed data from all samples yielding unmatched positive results by either culture or IRIDICA BAC BSI Assay analysis in the presence of matched or unmatched detections by the other technology (additional detections). The matched positive results shown here in the second column are also represented in Tables <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0158186#pone.0158186.t003" target="_blank">3</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0158186#pone.0158186.t004" target="_blank">4</a>, while the additional detections shown here in the rightmost two columns are not, because they have no valid comparator. See discussion of additional detections in text.</p
Comparison of positive IRIDICA BAC BSI Assay and standard-of-care culture results in clinical blood specimens from patients with suspected bloodstream infections, by organism.
<p>Possible identities of ambiguous IRIDICA BAC BSI Assay detections are separated by semicolons in cases where insufficient data was captured to provide species-level identification, and by slashes if the indicated organisms share identical reference signatures and cannot be discriminated. Commas separate multiple independent detections. These indicators are shown as they were reported by the IRIDICA BAC BSI Assay.</p