Efficient high-resolution genetic mapping of mouse interspersed repetitive sequence PCR products, toward integrated genetic and physical mapping of the mouse genome.

The ability to carry out high-resolution genetic mapping at high throughput in the mouse is a critical rate-limiting step in the generation of genetically anchored contigs in physical mapping projects and the mapping of genetic loci for complex traits. To address this need, we have developed an efficient, high-resolution, large-scale genome mapping system. This system is based on the identification of polymorphic DNA sites between mouse strains by using interspersed repetitive sequence (IRS) PCR. Individual cloned IRS PCR products are hybridized to a DNA array of IRS PCR products derived from the DNA of individual mice segregating DNA sequences from the two parent strains. Since gel electrophoresis is not required, large numbers of samples can be genotyped in parallel. By using this approach, we have mapped > 450 polymorphic probes with filters containing the DNA of up to 517 backcross mice, potentially allowing resolution of 0.14 centimorgan. This approach also carries the potential for a high degree of efficiency in the integration of physical and genetic maps, since pooled DNAs representing libraries of yeast artificial chromosomes or other physical representations of the mouse genome can be addressed by hybridization of filter representations of the IRS PCR products of such libraries.

Use of a novel DNA melting profile assay for the identification of PCR-amplified genomic sequences encoding for variant-specific surface proteins from the clonal GS/M-83-H7 line of Giardia lamblia.

During infections, Giardia lamblia undergoes a continuous change of its major surface antigens, the variant-specific surface proteins (VSPs). Many studies on antigenic variation have been performed using G. lamblia clone GS/M-83-H7, which expresses surface antigen VSP H7. The present study was focused on the identification and characterization of vsp gene sequences within the genome of the clonal G. lamblia GS/M-83-H7 line. For this purpose, we applied a PCR which specifically amplified truncated sequences from the 3'-terminal region of the vsp genes. Upon cloning, most of the vsp gene amplification products were shown to be approximately identical in size and thus could not be distinguished from each other by conventional gel electrophoresis. In order to pre-estimate the sequence complexity within the large panel of vsp clones isolated, we elaborated a novel concept which facilitated our large-scale genetic screening approach: PCR products from cloned DNA molecules were generated and then subjected to a DNA melting profile assay based on the use of the LightCycler Instrument. This high-throughput assay system proved to be well suited to monitor sequence differences between the amplification products from closely related vsp genes and thus could be used for the primary, sequence-related discrimination of the corresponding clones. After testing 50 candidates, vsp clones could be divided into five groups, each characterized by an individual DNA melting profile of the corresponding amplification products. Sequence analysis of some of these 50 candidates confirmed data from the aforementioned assay in that clones were demonstrated to be identical within, but different between, the distinct groups. The nucleotide and deduced amino acid sequences of five representative vsp clones showed high similarities both among each other and also with the corresponding gene segment of the variant-specific surface antigen (VSP H7) expressed by the original GS/M-83-H7 variant type. Furthermore, three of the genomic vsp sequences turned out to be identical to vsp sequences that represented previously characterized transcription products from in vivo- or in vitro-switched GS/M-83-H7 trophozoites. In conclusion, the DNA melting profile assay seems to be a versatile tool for the PCR-based genotyping of moderately or highly diversified sequence orthologues.

Learning Models of Gene Expression from Synthetic DNA Sequences

Thesis (Ph.D.)--University of Washington, 2016-06

Analysis of RNA-protein interactions by flow cytometry

Flow cytometry, in combination with advances in bead coding technologies, is maturing as a powerful high-throughput approach for analyzing molecular interactions. Applications of this technology include antibody assays and single nucleotide polymorphism mapping. This review describes the recent development of a microbead flow cytometric approach to analyze RNA-protein interactions and discusses emerging bead coding strategies that together will allow genome-wide identification of RNA-protein complexes. The microbead flow cytometric approach is flexible and provides new opportunities for functional genomic studies and small-molecule screening.

Centromere identification and inactivation on a neo-Y chromosome fusion in threespine stickleback fish (Gasterosteus aculeatus)

Thesis (Ph.D.)--University of Washington, 2016-05

Using the R package Shiny to create web applications that facilitate quantitative gene expression analysis

Thesis (Master's)--University of Washington, 2016-06

Matrix effects: The Achilles heel of quantitative high-performance liquid chromatography-electrospray-tandem mass spectrometry

High-performance liquid chromatography coupled by an electrospray ion source to a tandem mass spectrometer (HPLC-EST-MS/ MS) is the current analytical method of choice for quantitation of analytes in biological matrices. With HPLC-ESI-MS/MS having the characteristics of high selectivity, sensitivity, and throughput, this technology is being increasingly used in the clinical laboratory. An important issue to be addressed in method development, validation, and routine use of HPLC-ESI-MS/MS is matrix effects. Matrix effects are the alteration of ionization efficiency by the presence of coeluting substances. These effects are unseen in the chromatograrn but have deleterious impact on methods accuracy and sensitivity. The two common ways to assess matrix effects are either by the postextraction addition method or the postcolumn infusion method. To remove or minimize matrix effects, modification to the sample extraction methodology and improved chromatographic separation must be performed. These two parameters are linked together and form the basis of developing a successful and robust quantitative HPLC-EST-MS/MS method. Due to the heterogenous nature of the population being studied, the variability of a method must be assessed in samples taken from a variety of subjects. In this paper, the major aspects of matrix effects are discussed with an approach to address matrix effects during method validation proposed. (c) 2004 The Canadian Society of Clinical Chemists. All rights reserved.

Transcriptome analysis of Neotyphodium and Epichloë grass endophytes

Large-scale gene discovery has been performed for the grass fungal endophytes Neotyphodium coenophialum, Neotyphodium lolii, and Epichloe festucae. The resulting sequences have been annotated by comparison with public DNA and protein sequence databases and using intermediate gene ontology annotation tools. Endophyte sequences have also been analysed for the presence of simple sequence repeat and single nucleotide polymorphism molecular genetic markers. Sequences and annotation are maintained within a MySQL database that may be queried using a custom web interface. Two cDNA-based microarrays have been generated from this genome resource, They permit the interrogation of 3806 Neotyphodium genes (Nchip (TM) rnicroarray), and 4195 Neotyphodium and 920 Epichloe genes (EndoChip (TM) microarray), respectively. These microarrays provide tools for high-throughput transcriptome analysis, including genome-specific gene expression studies, profiling of novel endophyte genes, and investigation of the host grass-symbiont interaction. Comparative transcriptome analysis in Neotyphodium and Epichloe was performed. (c) 2006 Elsevier

Rapid screening of 4000 individuals for germ-line variations in the BRAF gene

Background: The BRAF gene is frequently somatically altered in malignant melanoma. A majority of variations are at the valine 600 residue leading to a V600E substitution that constitutively activates the kinase. We screened 4000 patient and control DNAs for germ-line variations at the valine 600 residue. Methods: We developed a novel assay by adapting single-base variation assays and software for MALDI-TOF (matrix-assisted laser desorption/ionization time-of-flight) mass spectrometry to screen for all 5 reported variants at codon 600 of the BRAF gene. We screened a case-control collection comprising samples from 1082 melanoma patients and 154 of their unaffected relatives from 1278 families and from 2744 individuals from 659 unselected twin families with no history of melanoma. A panel of 66 melanoma cell lines was used for variation-positive controls. Results: All melanoma cell lines that we had found previously to carry a codon 600 variation were verified in this study. Three of the 4 possible variants (V600E n = 47, V600K n = 2, V600R n = 1) were detected, but no case of V600D was available. No germ-line variants were found in the samples from the 3980 melanoma patients or from the control individuals. Conclusions: This new assay is a high-throughput, automated alternative to standard sequencing and can be used as a rapid initial screen for somatic variants associated with melanoma. Germ-line variants at valine 600 are unlikely to exist and do not contribute to the reported role of the BRAF gene in melanoma predisposition. (c) 2006 American Association for Clinical Chemistry.

Implementing an adaptive sending rate by exploiting SNR in relation to throughput over Wireless Mesh Networks

Wireless Mesh Networks (WMNs) have emerged as a key technology for the next generation of wireless networking. Instead ofbeing another type of ad-hoc networking, WMNs diversify the capabilities of ad-hoc networks. There are many kinds of protocols that work over WMNs, such as IEEE 802.11a/b/g, 802.15 and 802.16. To bring about a high throughput under varying conditions, these protocols have to adapt their transmission rate. While transmission rate is a significant part, only a few algorithms such as Auto Rate Fallback (ARF) or Receiver Based Auto Rate (RBAR) have been published. In this paper we will show MAC, packet loss and physical layer conditions play important role for having good channel condition. Also we perform rate adaption along with multiple packet transmission for better throughput. By allowing for dynamically monitored, multiple packet transmission and adaptation to changes in channel quality by adjusting the packet transmission rates according to certain optimization criteria improvements in performance can be obtained. The proposed method is the detection of channel congestion by measuring the fluctuation of signal to the standard deviation of and the detection of packet loss before channel performance diminishes. We will show that the use of such techniques in WMN can significantly improve performance. The effectiveness of the proposed method is presented in an experimental wireless network testbed via packet-level simulation. Our simulation results show that regardless of the channel condition we were to improve the performance in the throughput.

Understanding the role of Dimethylsulfoniopropionate as a potential chemotactic cue for coral-associated bacteria

Most reef-building corals are known to engage in non-pathogenic symbiosis not only with unicellular dinoflagellates from the genus Symbiodinium, but also with other microscopic organisms such as bacteria, fungi, and viruses. The functional details of these highly complex associations remain largely unclear. The impetus of this study is to gain a better understanding of the symbiotic interaction between marine bacteria and their coral host. Studies have shown that certain bacterial orders associate with specific certain coral species, thus making the symbiotic synergy a non-random consortium. Consequently both corals and bacteria may be capable of emitting chemical cues that enable both parties to find one another and thus generate the symbiosis. The production of these cues by the symbionts may be the result of environmental stimuli such as elevated ocean temperatures, increased water acidity, and even predation. One potential chemical cue could be the compound DMSP (Dimethylsulfoniopropionate) and its sulphur derivatives. Reef-building corals are believed to be the major producers of the DMSP during times of stress. Marine bacteria utilize DMSP as a source of sulfur and carbon. As a result corals could potentially attract their bacterial consortium depending on their DMSP production. This would enable them to adapt to fluctuating environmental conditions by changing their bacterial communities to that which may aid in survival. To test the hypothesis that coral-produced DMSP plays a role in attracting symbiotic bacteria, this study utilized the advent of high-throughput sequencing paired with chemotactic assays to determine the response of coral-associated bacterial isolates towards the DMSP compound at differing concentrations. Chemotaxis assays revealed that some isolates responded positively towards the DMSP compound. This finding adds to existing evidence suggesting that coral-associated pathogens utilize chemotaxis as a host colonization and detection mechanism. Thus the symbiotic bacteria that make up the coral microbiome may also employ this process. Furthermore this study demonstrates that bacterial motility may be a strong contributing factor in the response to the chemotactic cue. Swarming motility may be better suited for bacteria that need to respond to a chemical gradient on the surface of the coral. Therefore the isolates that were able to swarm seemed to respond more strongly to the DMSP.

Coastal plankton communities under elevated CO2: community barcoding results, link to data files in FASTA format

The acidification of the oceans could potentially alter marine plankton communities with consequences for ecosystem functioning. While several studies have investigated effects of ocean acidifications on communities using traditional methods, few have used genetic analyses. Here, we use community barcoding to assess the impact of ocean acidification on the composition of a coastal plankton community in a large scale, in situ, long-term mesocosm experiment. High-throughput sequencing resulted in the identification of a wide range of planktonic taxa (Alveolata, Cryptophyta, Haptophyceae, Fungi, Metazoa, Hydrozoa, Rhizaria, Straminipila, Chlorophyta). Analyses based on predicted operational taxonomical units as well as taxonomical compositions revealed no differences between communities in high CO2 mesocosms (~760 µatm) and those exposed to present day CO2 conditions. Observed shifts in the planktonic community composition were mainly related to seasonal changes in temperature and nutrients.

Dissecting the Functional Impacts of Non-Coding Genetic Variation

A large proportion of the variation in traits between individuals can be attributed to variation in the nucleotide sequence of the genome. The most commonly studied traits in human genetics are related to disease and disease susceptibility. Although scientists have identified genetic causes for over 4,000 monogenic diseases, the underlying mechanisms of many highly prevalent multifactorial inheritance disorders such as diabetes, obesity, and cardiovascular disease remain largely unknown. Identifying genetic mechanisms for complex traits has been challenging because most of the variants are located outside of protein-coding regions, and determining the effects of such non-coding variants remains difficult. In this dissertation, I evaluate the hypothesis that such non-coding variants contribute to human traits and diseases by altering the regulation of genes rather than the sequence of those genes. I will specifically focus on studies to determine the functional impacts of genetic variation associated with two related complex traits: gestational hyperglycemia and fetal adiposity. At the genomic locus associated with maternal hyperglycemia, we found that genetic variation in regulatory elements altered the expression of the HKDC1 gene. Furthermore, we demonstrated that HKDC1 phosphorylates glucose in vitro and in vivo, thus demonstrating that HKDC1 is a fifth human hexokinase gene. At the fetal-adiposity associated locus, we identified variants that likely alter VEPH1 expression in preadipocytes during differentiation. To make such studies of regulatory variation high-throughput and routine, we developed POP-STARR, a novel high throughput reporter assay that can empirically measure the effects of regulatory variants directly from patient DNA. By combining targeted genome capture technologies with STARR-seq, we assayed thousands of haplotypes from 760 individuals in a single experiment. We subsequently used POP-STARR to identify three key features of regulatory variants: that regulatory variants typically have weak effects on gene expression; that the effects of regulatory variants are often coordinated with respect to disease-risk, suggesting a general mechanism by which the weak effects can together have phenotypic impact; and that nucleotide transversions have larger impacts on enhancer activity than transitions. Together, the findings presented here demonstrate successful strategies for determining the regulatory mechanisms underlying genetic associations with human traits and diseases, and value of doing so for driving novel biological discovery.

New Advancements of Scalable Statistical Methods for Learning Latent Structures in Big Data

Constant technology advances have caused data explosion in recent years. Accord- ingly modern statistical and machine learning methods must be adapted to deal with complex and heterogeneous data types. This phenomenon is particularly true for an- alyzing biological data. For example DNA sequence data can be viewed as categorical variables with each nucleotide taking four different categories. The gene expression data, depending on the quantitative technology, could be continuous numbers or counts. With the advancement of high-throughput technology, the abundance of such data becomes unprecedentedly rich. Therefore efficient statistical approaches are crucial in this big data era.

Previous statistical methods for big data often aim to find low dimensional struc- tures in the observed data. For example in a factor analysis model a latent Gaussian distributed multivariate vector is assumed. With this assumption a factor model produces a low rank estimation of the covariance of the observed variables. Another example is the latent Dirichlet allocation model for documents. The mixture pro- portions of topics, represented by a Dirichlet distributed variable, is assumed. This dissertation proposes several novel extensions to the previous statistical methods that are developed to address challenges in big data. Those novel methods are applied in multiple real world applications including construction of condition specific gene co-expression networks, estimating shared topics among newsgroups, analysis of pro- moter sequences, analysis of political-economics risk data and estimating population structure from genotype data.

Cell Fate Specification and the Regulation of RNA-dependent DNA Methylation in the Arabidopsis Root Meristem

The Arabidopsis root apical meristem (RAM) is a complex tissue capable of generating all the cell types that ultimately make up the root. The work presented in this thesis takes advantage of the versatility of high-throughput sequencing to address two independent questions about the root meristem. Although a lot of information is known regarding the cell fate decisions that occur at the RAM, cortex specification and differentiation remain poorly understood. In the first part of this thesis, I used an ethylmethanesulfonate (EMS) mutagenized marker line to perform a forward genetics screen. The goal of this screen was to identify novel genes involved in the specification and differentiation of the cortex tissue. Mapping analysis from the results obtained in this screen revealed a new allele of BRASSINOSTEROID4 with abnormal marker expression in the cortex tissue. Although this allele proved to be non-cortex specific, this project highlights new technology that allows mapping of EMS-generated mutations without the need to map-cross or back-cross. In the second part of this thesis, using fluorescence activated cell sorting (FACS) coupled with high throughput sequencing, my collaborators and I generated single-base resolution whole genome DNA methylomes, mRNA transcriptomes, and smallRNA transcriptomes for six different populations of cell types in the Arabidopsis root meristem. We were able to discover that the columella is hypermethylated in the CHH context within transposable elements. This hypermethylation is accompanied by upregulation of the RNA-dependent DNA methylation pathway (RdDM), including higher levels of 24-nt silencing RNAs (siRNAs). In summary, our studies demonstrate the versatility of high-throughput sequencing as a method for identifying single mutations or to perform complex comparative genomic analyses.