Browsing by Subject "Models, Genetic"

Now showing 1 - 20 of 43
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    29 mammalian genomes reveal novel exaptations of mobile elements for likely regulatory functions in the human genome.
    (PloS one, 2012-01) Lowe, Craig B; Haussler, David
    Recent research supports the view that changes in gene regulation, as opposed to changes in the genes themselves, play a significant role in morphological evolution. Gene regulation is largely dependent on transcription factor binding sites. Researchers are now able to use the available 29 mammalian genomes to measure selective constraint at the level of binding sites. This detailed map of constraint suggests that mammalian genomes co-opt fragments of mobile elements to act as gene regulatory sequence on a large scale. In the human genome we detect over 280,000 putative regulatory elements, totaling approximately 7 Mb of sequence, that originated as mobile element insertions. These putative regulatory regions are conserved non-exonic elements (CNEEs), which show considerable cross-species constraint and signatures of continued negative selection in humans, yet do not appear in a known mature transcript. These putative regulatory elements were co-opted from SINE, LINE, LTR and DNA transposon insertions. We demonstrate that at least 11%, and an estimated 20%, of gene regulatory sequence in the human genome showing cross-species conservation was co-opted from mobile elements. The location in the genome of CNEEs co-opted from mobile elements closely resembles that of CNEEs in general, except in the centers of the largest gene deserts where recognizable co-option events are relatively rare. We find that regions of certain mobile element insertions are more likely to be held under purifying selection than others. In particular, we show 6 examples where paralogous instances of an often co-opted mobile element region define a sequence motif that closely matches a transcription factor's binding profile.
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    A flexible statistical model for alignment of label-free proteomics data--incorporating ion mobility and product ion information.
    (BMC Bioinformatics, 2013-12-16) Benjamin, Ashlee M; Thompson, J Will; Soderblom, Erik J; Geromanos, Scott J; Henao, Ricardo; Kraus, Virginia B; Moseley, M Arthur; Lucas, Joseph E
    BACKGROUND: The goal of many proteomics experiments is to determine the abundance of proteins in biological samples, and the variation thereof in various physiological conditions. High-throughput quantitative proteomics, specifically label-free LC-MS/MS, allows rapid measurement of thousands of proteins, enabling large-scale studies of various biological systems. Prior to analyzing these information-rich datasets, raw data must undergo several computational processing steps. We present a method to address one of the essential steps in proteomics data processing--the matching of peptide measurements across samples. RESULTS: We describe a novel method for label-free proteomics data alignment with the ability to incorporate previously unused aspects of the data, particularly ion mobility drift times and product ion information. We compare the results of our alignment method to PEPPeR and OpenMS, and compare alignment accuracy achieved by different versions of our method utilizing various data characteristics. Our method results in increased match recall rates and similar or improved mismatch rates compared to PEPPeR and OpenMS feature-based alignment. We also show that the inclusion of drift time and product ion information results in higher recall rates and more confident matches, without increases in error rates. CONCLUSIONS: Based on the results presented here, we argue that the incorporation of ion mobility drift time and product ion information are worthy pursuits. Alignment methods should be flexible enough to utilize all available data, particularly with recent advancements in experimental separation methods.
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    A functional analysis of the spacer of V(D)J recombination signal sequences.
    (PLoS Biol, 2003-10) Lee, Alfred Ian; Fugmann, Sebastian D; Cowell, Lindsay G; Ptaszek, Leon M; Kelsoe, Garnett; Schatz, David G
    During lymphocyte development, V(D)J recombination assembles antigen receptor genes from component V, D, and J gene segments. These gene segments are flanked by a recombination signal sequence (RSS), which serves as the binding site for the recombination machinery. The murine Jbeta2.6 gene segment is a recombinationally inactive pseudogene, but examination of its RSS reveals no obvious reason for its failure to recombine. Mutagenesis of the Jbeta2.6 RSS demonstrates that the sequences of the heptamer, nonamer, and spacer are all important. Strikingly, changes solely in the spacer sequence can result in dramatic differences in the level of recombination. The subsequent analysis of a library of more than 4,000 spacer variants revealed that spacer residues of particular functional importance are correlated with their degree of conservation. Biochemical assays indicate distinct cooperation between the spacer and heptamer/nonamer along each step of the reaction pathway. The results suggest that the spacer serves not only to ensure the appropriate distance between the heptamer and nonamer but also regulates RSS activity by providing additional RAG:RSS interaction surfaces. We conclude that while RSSs are defined by a "digital" requirement for absolutely conserved nucleotides, the quality of RSS function is determined in an "analog" manner by numerous complex interactions between the RAG proteins and the less-well conserved nucleotides in the heptamer, the nonamer, and, importantly, the spacer. Those modulatory effects are accurately predicted by a new computational algorithm for "RSS information content." The interplay between such binary and multiplicative modes of interactions provides a general model for analyzing protein-DNA interactions in various biological systems.
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    Advances to Bayesian network inference for generating causal networks from observational biological data.
    (Bioinformatics, 2004-12-12) Yu, Jing; Smith, V Anne; Wang, Paul P; Hartemink, Alexander J; Jarvis, Erich D
    MOTIVATION: Network inference algorithms are powerful computational tools for identifying putative causal interactions among variables from observational data. Bayesian network inference algorithms hold particular promise in that they can capture linear, non-linear, combinatorial, stochastic and other types of relationships among variables across multiple levels of biological organization. However, challenges remain when applying these algorithms to limited quantities of experimental data collected from biological systems. Here, we use a simulation approach to make advances in our dynamic Bayesian network (DBN) inference algorithm, especially in the context of limited quantities of biological data. RESULTS: We test a range of scoring metrics and search heuristics to find an effective algorithm configuration for evaluating our methodological advances. We also identify sampling intervals and levels of data discretization that allow the best recovery of the simulated networks. We develop a novel influence score for DBNs that attempts to estimate both the sign (activation or repression) and relative magnitude of interactions among variables. When faced with limited quantities of observational data, combining our influence score with moderate data interpolation reduces a significant portion of false positive interactions in the recovered networks. Together, our advances allow DBN inference algorithms to be more effective in recovering biological networks from experimentally collected data. AVAILABILITY: Source code and simulated data are available upon request. SUPPLEMENTARY INFORMATION: http://www.jarvislab.net/Bioinformatics/BNAdvances/
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    Ancestral population genomics: the coalescent hidden Markov model approach.
    (Genetics, 2009-09) Dutheil, Julien Y; Ganapathy, Ganesh; Hobolth, Asger; Mailund, Thomas; Uyenoyama, Marcy K; Schierup, Mikkel H
    With incomplete lineage sorting (ILS), the genealogy of closely related species differs along their genomes. The amount of ILS depends on population parameters such as the ancestral effective population sizes and the recombination rate, but also on the number of generations between speciation events. We use a hidden Markov model parameterized according to coalescent theory to infer the genealogy along a four-species genome alignment of closely related species and estimate population parameters. We analyze a basic, panmictic demographic model and study its properties using an extensive set of coalescent simulations. We assess the effect of the model assumptions and demonstrate that the Markov property provides a good approximation to the ancestral recombination graph. Using a too restricted set of possible genealogies, necessary to reduce the computational load, can bias parameter estimates. We propose a simple correction for this bias and suggest directions for future extensions of the model. We show that the patterns of ILS along a sequence alignment can be recovered efficiently together with the ancestral recombination rate. Finally, we introduce an extension of the basic model that allows for mutation rate heterogeneity and reanalyze human-chimpanzee-gorilla-orangutan alignments, using the new models. We expect that this framework will prove useful for population genomics and provide exciting insights into genome evolution.
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    Application of a rank-based genetic association test to age-at-onset data from the Collaborative Study on the Genetics of Alcoholism study.
    (BMC Genet, 2005-12-30) Li, YJ; Martin, ER; Zhang, L; Allen, AS
    Association studies of quantitative traits have often relied on methods in which a normal distribution of the trait is assumed. However, quantitative phenotypes from complex human diseases are often censored, highly skewed, or contaminated with outlying values. We recently developed a rank-based association method that takes into account censoring and makes no distributional assumptions about the trait. In this study, we applied our new method to age-at-onset data on ALDX1 and ALDX2. Both traits are highly skewed (skewness > 1.9) and often censored. We performed a whole genome association study of age at onset of the ALDX1 trait using Illumina single-nucleotide polymorphisms. Only slightly more than 5% of markers were significant. However, we identified two regions on chromosomes 14 and 15, which each have at least four significant markers clustering together. These two regions may harbor genes that regulate age at onset of ALDX1 and ALDX2. Future fine mapping of these two regions with densely spaced markers is warranted.
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    Assessment of LD matrix measures for the analysis of biological pathway association.
    (Stat Appl Genet Mol Biol, 2010) Crosslin, David R; Qin, Xuejun; Hauser, Elizabeth R
    Complex diseases will have multiple functional sites, and it will be invaluable to understand the cross-locus interaction in terms of linkage disequilibrium (LD) between those sites (epistasis) in addition to the haplotype-LD effects. We investigated the statistical properties of a class of matrix-based statistics to assess this epistasis. These statistical methods include two LD contrast tests (Zaykin et al., 2006) and partial least squares regression (Wang et al., 2008). To estimate Type 1 error rates and power, we simulated multiple two-variant disease models using the SIMLA software package. SIMLA allows for the joint action of up to two disease genes in the simulated data with all possible multiplicative interaction effects between them. Our goal was to detect an interaction between multiple disease-causing variants by means of their linkage disequilibrium (LD) patterns with other markers. We measured the effects of marginal disease effect size, haplotype LD, disease prevalence and minor allele frequency have on cross-locus interaction (epistasis). In the setting of strong allele effects and strong interaction, the correlation between the two disease genes was weak (r=0.2). In a complex system with multiple correlations (both marginal and interaction), it was difficult to determine the source of a significant result. Despite these complications, the partial least squares and modified LD contrast methods maintained adequate power to detect the epistatic effects; however, for many of the analyses we often could not separate interaction from a strong marginal effect. While we did not exhaust the entire parameter space of possible models, we do provide guidance on the effects that population parameters have on cross-locus interaction.
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    Association of LEP G2548A and LEPR Q223R polymorphisms with cancer susceptibility: evidence from a meta-analysis.
    (PloS one, 2013-01) He, Jing; Xi, Bo; Ruiter, Rikje; Shi, Ting-Yan; Zhu, Mei-Ling; Wang, Meng-Yun; Li, Qiao-Xin; Zhou, Xiao-Yan; Qiu, Li-Xin; Wei, Qing-Yi
    BACKGROUND: Numerous epidemiological studies have examined associations of genetic variations in LEP (G2548A, -2548 nucleotide upstream of the ATG start site) and LEPR (Q223R, nonsynonymous SNP in exon 6) with cancer susceptibility; however, the findings are inconsistent. Therefore, we performed a meta-analysis to comprehensively evaluate such associations. METHODS: We searched published literature from MEDLINE, EMBASE, Web of Science and CBM for eligible publications. We also assessed genotype-based mRNA expression data from HapMap for rs7799039 (G2548A) and rs1137101 (Q223R) in normal cell lines derived from 270 subjects with different ethnicities. RESULTS: The final analysis included 16 published studies of 6569 cases and 8405 controls for the LEP G2548A and 19 studies of 7504 cases and 9581 controls for the LEPR Q223R. Overall, LEP G2548A was statistically significantly associated with an increased risk of overall cancer (AA vs. GG: OR=1.27, 95% CI=1.05-1.54; recessive model: OR=1.19, 95% CI=1.00-1.41). Further stratifications by cancer type showed an increased risk for prostate cancer (recessive model: OR=1.26, 95% CI=1.05-1.51) but not for other cancers. For LEPR Q223R, no statistical evidence for an association with risk of cancer was found for all; however, further stratification by ethnicity showed an increased risk for Africans but not for other ethnicities. No significantly differences in LEP and LEPR mRNA expression were found among genotypes or by ethnicity. CONCLUSIONS: Despite some limitations, this meta-analysis found some statistical evidence for an association between the LEP 2548AA genotype and overall risk of cancer, particularly for prostate cancer, but given this variant did not have an effect on mRNA expression, this association warrants additional validation in large and well-designed studies.
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    Chiropteran types I and II interferon genes inferred from genome sequencing traces by a statistical gene-family assembler.
    (BMC Genomics, 2010-07-21) Kepler, Thomas B; Sample, Christopher; Hudak, Kathryn; Roach, Jeffrey; Haines, Albert; Walsh, Allyson; Ramsburg, Elizabeth A
    BACKGROUND: The rate of emergence of human pathogens is steadily increasing; most of these novel agents originate in wildlife. Bats, remarkably, are the natural reservoirs of many of the most pathogenic viruses in humans. There are two bat genome projects currently underway, a circumstance that promises to speed the discovery host factors important in the coevolution of bats with their viruses. These genomes, however, are not yet assembled and one of them will provide only low coverage, making the inference of most genes of immunological interest error-prone. Many more wildlife genome projects are underway and intend to provide only shallow coverage. RESULTS: We have developed a statistical method for the assembly of gene families from partial genomes. The method takes full advantage of the quality scores generated by base-calling software, incorporating them into a complete probabilistic error model, to overcome the limitation inherent in the inference of gene family members from partial sequence information. We validated the method by inferring the human IFNA genes from the genome trace archives, and used it to infer 61 type-I interferon genes, and single type-II interferon genes in the bats Pteropus vampyrus and Myotis lucifugus. We confirmed our inferences by direct cloning and sequencing of IFNA, IFNB, IFND, and IFNK in P. vampyrus, and by demonstrating transcription of some of the inferred genes by known interferon-inducing stimuli. CONCLUSION: The statistical trace assembler described here provides a reliable method for extracting information from the many available and forthcoming partial or shallow genome sequencing projects, thereby facilitating the study of a wider variety of organisms with ecological and biomedical significance to humans than would otherwise be possible.
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    Comparative genomics based on massive parallel transcriptome sequencing reveals patterns of substitution and selection across 10 bird species.
    (Mol Ecol, 2010-03) Künstner, Axel; Wolf, Jochen BW; Backström, Niclas; Whitney, Osceola; Balakrishnan, Christopher N; Day, Lainy; Edwards, Scott V; Janes, Daniel E; Schlinger, Barney A; Wilson, Richard K; Jarvis, Erich D; Warren, Wesley C; Ellegren, Hans
    Next-generation sequencing technology provides an attractive means to obtain large-scale sequence data necessary for comparative genomic analysis. To analyse the patterns of mutation rate variation and selection intensity across the avian genome, we performed brain transcriptome sequencing using Roche 454 technology of 10 different non-model avian species. Contigs from de novo assemblies were aligned to the two available avian reference genomes, chicken and zebra finch. In total, we identified 6499 different genes across all 10 species, with approximately 1000 genes found in each full run per species. We found evidence for a higher mutation rate of the Z chromosome than of autosomes (male-biased mutation) and a negative correlation between the neutral substitution rate (d(S)) and chromosome size. Analyses of the mean d(N)/d(S) ratio (omega) of genes across chromosomes supported the Hill-Robertson effect (the effect of selection at linked loci) and point at stochastic problems with omega as an independent measure of selection. Overall, this study demonstrates the usefulness of next-generation sequencing for obtaining genomic resources for comparative genomic analysis of non-model organisms.
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    Computational correction of copy number effect improves specificity of CRISPR-Cas9 essentiality screens in cancer cells.
    (Nature genetics, 2017-12) Meyers, Robin M; Bryan, Jordan G; McFarland, James M; Weir, Barbara A; Sizemore, Ann E; Xu, Han; Dharia, Neekesh V; Montgomery, Phillip G; Cowley, Glenn S; Pantel, Sasha; Goodale, Amy; Lee, Yenarae; Ali, Levi D; Jiang, Guozhi; Lubonja, Rakela; Harrington, William F; Strickland, Matthew; Wu, Ting; Hawes, Derek C; Zhivich, Victor A; Wyatt, Meghan R; Kalani, Zohra; Chang, Jaime J; Okamoto, Michael; Stegmaier, Kimberly; Golub, Todd R; Boehm, Jesse S; Vazquez, Francisca; Root, David E; Hahn, William C; Tsherniak, Aviad
    The CRISPR-Cas9 system has revolutionized gene editing both at single genes and in multiplexed loss-of-function screens, thus enabling precise genome-scale identification of genes essential for proliferation and survival of cancer cells. However, previous studies have reported that a gene-independent antiproliferative effect of Cas9-mediated DNA cleavage confounds such measurement of genetic dependency, thereby leading to false-positive results in copy number-amplified regions. We developed CERES, a computational method to estimate gene-dependency levels from CRISPR-Cas9 essentiality screens while accounting for the copy number-specific effect. In our efforts to define a cancer dependency map, we performed genome-scale CRISPR-Cas9 essentiality screens across 342 cancer cell lines and applied CERES to this data set. We found that CERES decreased false-positive results and estimated sgRNA activity for both this data set and previously published screens performed with different sgRNA libraries. We further demonstrate the utility of this collection of screens, after CERES correction, for identifying cancer-type-specific vulnerabilities.
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    Detecting local haplotype sharing and haplotype association.
    (Genetics, 2014-07) Xu, Hanli; Guan, Yongtao
    A novel haplotype association method is presented, and its power is demonstrated. Relying on a statistical model for linkage disequilibrium (LD), the method first infers ancestral haplotypes and their loadings at each marker for each individual. The loadings are then used to quantify local haplotype sharing between individuals at each marker. A statistical model was developed to link the local haplotype sharing and phenotypes to test for association. We devised a novel method to fit the LD model, reducing the complexity from putatively quadratic to linear (in the number of ancestral haplotypes). Therefore, the LD model can be fitted to all study samples simultaneously, and, consequently, our method is applicable to big data sets. Compared to existing haplotype association methods, our method integrated out phase uncertainty, avoided arbitrariness in specifying haplotypes, and had the same number of tests as the single-SNP analysis. We applied our method to data from the Wellcome Trust Case Control Consortium and discovered eight novel associations between seven gene regions and five disease phenotypes. Among these, GRIK4, which encodes a protein that belongs to the glutamate-gated ionic channel family, is strongly associated with both coronary artery disease and rheumatoid arthritis. A software package implementing methods described in this article is freely available at http://www.haplotype.org.
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    Detecting structure of haplotypes and local ancestry.
    (Genetics, 2014-03) Guan, Yongtao
    We present a two-layer hidden Markov model to detect the structure of haplotypes for unrelated individuals. This allows us to model two scales of linkage disequilibrium (one within a group of haplotypes and one between groups), thereby taking advantage of rich haplotype information to infer local ancestry of admixed individuals. Our method outperforms competing state-of-the-art methods, particularly for regions of small ancestral track lengths. Applying our method to Mexican samples in HapMap3, we found two regions on chromosomes 6 and 8 that show significant departure of local ancestry from the genome-wide average. A software package implementing the methods described in this article is freely available at http://bcm.edu/cnrc/mcmcmc.
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    Do asexual polyploid lineages lead short evolutionary lives? A case study from the fern genus Astrolepis.
    (Evolution; international journal of organic evolution, 2011-11) Beck, JB; Windham, MD; Pryer, KM
    A life-history transition to asexuality is typically viewed as leading to a heightened extinction risk, and a number of studies have evaluated this claim by examining the relative ages of asexual versus closely related sexual lineages. Surprisingly, a rigorous assessment of the age of an asexual plant lineage has never been published, although asexuality is extraordinarily common among plants. Here, we estimate the ages of sexual diploids and asexual polyploids in the fern genus Astrolepis using a well-supported plastid phylogeny and a relaxed-clock dating approach. The 50 asexual polyploid samples we included were conservatively estimated to comprise 19 distinct lineages, including a variety of auto- and allopolyploid genomic combinations. All were either the same age or younger than the crown group comprising their maternal sexual-diploid parents based simply on their phylogenetic position. Node ages estimated with the relaxed-clock approach indicated that the average maximum age of asexual lineages was 0.4 My, and individual lineages were on average 7 to 47 times younger than the crown- and total-ages of their sexual parents. Although the confounding association between asexuality and polyploidy precludes definite conclusions regarding the effect of asexuality, our results suggest that asexuality limits evolutionary potential in Astrolepis.
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    Evaluation of genotype-specific survival using joint analysis of genetic and non-genetic subsamples of longitudinal data.
    (Biogerontology, 2011-04) Arbeev, Konstantin G; Ukraintseva, Svetlana V; Arbeeva, Liubov S; Akushevich, Igor; Kulminski, Alexander M; Yashin, Anatoliy I
    Small sample size of genetic data is often a limiting factor for desirable accuracy of estimated genetic effects on age-specific risks and survival. Longitudinal non-genetic data containing information on survival or disease onsets of study participants for whom the genetic data were not collected may provide an additional "reserve" for increasing the accuracy of respective estimates. We present a novel method for joint analyses of "genetic" (covering individuals for whom both genetic information and mortality/morbidity data are available) and "non-genetic" (covering individuals for whom only mortality/morbidity data were collected) subsamples of longitudinal data. Our simulation studies show substantial increase in the accuracy of estimates in such joint analyses compared to analyses based on genetic subsample alone. Application of this method to analysis of the effect of common apolipoprotein E (APOE) polymorphism on survival using combined genetic and non-genetic subsamples of the Framingham Heart Study original cohort data showed that female, but not male, carriers of the APOE e4 allele have significantly worse survival than non-carriers, whereas empirical analyses did not produce any significant results for either sex.
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    Evolution of leaf form in marsileaceous ferns: evidence for heterochrony.
    (Evolution; international journal of organic evolution, 2009-02) Pryer, KM; Hearn, DJ
    Using an explicit phylogenetic framework, ontogenetic patterns of leaf form are compared among the three genera of marsileaceous ferns (Marsilea, Regnellidium, and Pilularia) with the outgroup Asplenium to address the hypothesis that heterochrony played a role in their evolution. We performed a Fourier analysis on a developmental sequence of leaves from individuals of these genera. Principal components analysis of the harmonic coefficients was used to characterize the ontogenetic trajectories of leaf form in a smaller dimensional space. Results of this study suggest that the "evolutionary juvenilization" observed in these leaf sequences is best described using a mixed model of heterochrony (accelerated growth rate and early termination at a simplified leaf form). The later stages of the ancestral, more complex, ontogenetic pattern were lost in Marsileaceae, giving rise to the simplified adult leaves of Marsilea, Regnellidium, and Pilularia. Life-history traits such as ephemeral and uncertain habitats, high reproductive rates, and accelerated maturation, which are typical for marsileaceous ferns, suggest that they may be "r strategists." The evidence for heterochrony presented here illustrates that it has resulted in profound ecological and morphological consequences for the entire life history of Marsileaceae.
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    Explicit DNase sequence bias modeling enables high-resolution transcription factor footprint detection.
    (Nucleic Acids Res, 2014-10-29) Yardımcı, Galip Gürkan; Frank, Christopher L; Crawford, Gregory E; Ohler, Uwe
    DNaseI footprinting is an established assay for identifying transcription factor (TF)-DNA interactions with single base pair resolution. High-throughput DNase-seq assays have recently been used to detect in vivo DNase footprints across the genome. Multiple computational approaches have been developed to identify DNase-seq footprints as predictors of TF binding. However, recent studies have pointed to a substantial cleavage bias of DNase and its negative impact on predictive performance of footprinting. To assess the potential for using DNase-seq to identify individual binding sites, we performed DNase-seq on deproteinized genomic DNA and determined sequence cleavage bias. This allowed us to build bias corrected and TF-specific footprint models. The predictive performance of these models demonstrated that predicted footprints corresponded to high-confidence TF-DNA interactions. DNase-seq footprints were absent under a fraction of ChIP-seq peaks, which we show to be indicative of weaker binding, indirect TF-DNA interactions or possible ChIP artifacts. The modeling approach was also able to detect variation in the consensus motifs that TFs bind to. Finally, cell type specific footprints were detected within DNase hypersensitive sites that are present in multiple cell types, further supporting that footprints can identify changes in TF binding that are not detectable using other strategies.
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    Genealogical histories in structured populations.
    (Theoretical population biology, 2015-06) Kumagai, Seiji; Uyenoyama, Marcy K
    In genealogies of genes sampled from structured populations, lineages coalesce at rates dependent on the states of the lineages. For migration and coalescence events occurring on comparable time scales, for example, only lineages residing in the same deme of a geographically subdivided population can have descended from a common ancestor in the immediately preceding generation. Here, we explore aspects of genealogical structure in a population comprising two demes, between which migration may occur. We use generating functions to obtain exact densities and moments of coalescence time, number of mutations, total tree length, and age of the most recent common ancestor of the sample. We describe qualitative features of the distribution of gene genealogies, including factors that influence the geographical location of the most recent common ancestor and departures of the distribution of internode lengths from exponential.
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    Genetic evaluation of a proposed introduction: the case of the greater prairie chicken and the extinct heath hen.
    (Mol Ecol, 2004-07) Palkovacs, EP; Oppenheimer, AJ; Gladyshev, E; Toepfer, JE; Amato, G; Chase, T; Caccone, A
    Population introduction is an important tool for ecosystem restoration. However, before introductions should be conducted, it is important to evaluate the genetic, phenotypic and ecological suitability of possible replacement populations. Careful genetic analysis is particularly important if it is suspected that the extirpated population was unique or genetically divergent. On the island of Martha's Vineyard, Massachusetts, the introduction of greater prairie chickens (Tympanuchus cupido pinnatus) to replace the extinct heath hen (T. cupido cupido) is being considered as part of an ecosystem restoration project. Martha's Vineyard was home to the last remaining heath hen population until its extinction in 1932. We conducted this study to aid in determining the suitability of greater prairie chickens as a possible replacement for the heath hen. We examined mitochondrial control region sequences from extant populations of all prairie grouse species (Tympanuchus) and from museum skin heath hen specimens. Our data suggest that the Martha's Vineyard heath hen population represents a divergent mitochondrial lineage. This result is attributable either to a long period of geographical isolation from other prairie grouse populations or to a population bottleneck resulting from human disturbance. The mtDNA diagnosability of the heath hen contrasts with the network of mtDNA haplotypes of other prairie grouse (T. cupido attwateri, T. pallidicinctus and T. phasianellus), which do not form distinguishable mtDNA groupings. Our findings suggest that the Martha's Vineyard heath hen was more genetically isolated than are current populations of prairie grouse and place the emphasis for future research on examining prairie grouse adaptations to different habitat types to assess ecological exchangeability between heath hens and greater prairie chickens.
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    Genetic variability in beta-defensins is not associated with susceptibility to Staphylococcus aureus bacteremia.
    (PLoS One, 2012) Fode, Peder; Larsen, Anders Rhod; Feenstra, Bjarke; Jespersgaard, Cathrine; Skov, Robert Leo; Stegger, Marc; Fowler, Vance G; Danish SAB Study Group Consortium; Andersen, Paal Skytt
    INTRODUCTION: Human beta-defensins are key components of human innate immunity to a variety of pathogens, including Staphylococcus aureus. The aim of the present study was to investigate a potential association between gene variations in DEFB1 and DEFB103/DEFB4 and the development of S. aureus bacteremia (SAB) employing a case-control design. METHODS: Cases were unique patients with documented SAB, identified with the National S. aureus Bacteremia Register, a comprehensive dataset of all episodes of community associated-SABs (CA-SAB) occurring in children (≤20 yrs) in Denmark from 1990 to 2006. Controls were age-matched healthy individuals with no history of SAB. DNA obtained from cases and controls using the Danish Newborn Screening Biobank were genotyped for functional polymorphisms of DEFB1 by Sanger sequencing and copy number variation of the DEFB103 and DEFB4 genes using Pyrosequencing-based Paralogue Ratio Test (P-PRT). RESULTS: 193 ethnic Danish SAB cases with 382 age-matched controls were used for this study. S. aureus isolates represented a variety of bacterial (i.e., different spa types) types similar to SAB isolates in general. DEFB1 minor allele frequencies of rs11362 (cases vs. controls 0.47/0.44), rs1800972 (0.21/0.24), and rs1799946 (0.32/0.33) were not significantly different in cases compared with controls. Also, DEFB4/DEFB103 gene copy numbers (means 4.83/4.92) were not significantly different in cases compared with controls. CONCLUSIONS: Using a large, unique cohort of pediatric CA-SAB, we found no significant association between DEFB1 genetic variation or DEFB4/DEFB103 gene copy number and susceptibility for SAB.