Functional data analysis approaches for genotype-phenotype association studies from next-generation sequencing

Next-generation DNA sequencing platforms can effectively detect the entire spectrum of genomic variation and is emerging to be a major tool for systematic exploration of the universe of variants and interactions in the entire genome. However, the data produced by next-generation sequencing technologies will suffer from three basic problems: sequence errors, assembly errors, and missing data. Current statistical methods for genetic analysis are well suited for detecting the association of common variants, but are less suitable to rare variants. This raises great challenge for sequence-based genetic studies of complex diseases.^ This research dissertation utilized genome continuum model as a general principle, and stochastic calculus and functional data analysis as tools for developing novel and powerful statistical methods for next generation of association studies of both qualitative and quantitative traits in the context of sequencing data, which finally lead to shifting the paradigm of association analysis from the current locus-by-locus analysis to collectively analyzing genome regions.^ In this project, the functional principal component (FPC) methods coupled with high-dimensional data reduction techniques will be used to develop novel and powerful methods for testing the associations of the entire spectrum of genetic variation within a segment of genome or a gene regardless of whether the variants are common or rare.^ The classical quantitative genetics suffer from high type I error rates and low power for rare variants. To overcome these limitations for resequencing data, this project used functional linear models with scalar response to develop statistics for identifying quantitative trait loci (QTLs) for both common and rare variants. To illustrate their applications, the functional linear models were applied to five quantitative traits in Framingham heart studies. ^ This project proposed a novel concept of gene-gene co-association in which a gene or a genomic region is taken as a unit of association analysis and used stochastic calculus to develop a unified framework for testing the association of multiple genes or genomic regions for both common and rare alleles. The proposed methods were applied to gene-gene co-association analysis of psoriasis in two independent GWAS datasets which led to discovery of networks significantly associated with psoriasis.^

A MOLECULAR APPROACH FOR DETECTING GENETIC DAMAGE USING THE ECO R1 FAMILY OF HUMAN DNA (SEQUENCING)

A clone of the primary Eco R1 family of human DNA sequences has been used as an indicator sequence for detecting alterations induced by a toxic agent. Specific clones of this family have been examined and compared to the consensus sequence to determine the normal variability of this family. Though variations were observed, data indicated that such clones can be used to study induced DNA modifications. This DNA was exposed to the toxic agent dimethyl sulfate under various conditions and a distinct pattern of aberrations was shown to occur. It is suggested that this approach be used to characterize patterns of damage induced by various agents in the ultimate development of a system capable of monitoring human genotoxic exposure. ^

DEVELOPMENT OF NOVEL METHODS TO MINIMIZE THE IMPACT OF SEQUENCING ERRORS IN THE NEXT-GENERATION SEQUENCING DATA ANALYSIS

Next-generation sequencing (NGS) technology has become a prominent tool in biological and biomedical research. However, NGS data analysis, such as de novo assembly, mapping and variants detection is far from maturity, and the high sequencing error-rate is one of the major problems. . To minimize the impact of sequencing errors, we developed a highly robust and efficient method, MTM, to correct the errors in NGS reads. We demonstrated the effectiveness of MTM on both single-cell data with highly non-uniform coverage and normal data with uniformly high coverage, reflecting that MTM’s performance does not rely on the coverage of the sequencing reads. MTM was also compared with Hammer and Quake, the best methods for correcting non-uniform and uniform data respectively. For non-uniform data, MTM outperformed both Hammer and Quake. For uniform data, MTM showed better performance than Quake and comparable results to Hammer. By making better error correction with MTM, the quality of downstream analysis, such as mapping and SNP detection, was improved. SNP calling is a major application of NGS technologies. However, the existence of sequencing errors complicates this process, especially for the low coverage (

RNA-SEQUENCING APPLICATIONS: GENE EXPRESSION QUANTIFICATION AND METHYLATOR PHENOTYPE IDENTIFICATION

My dissertation focuses on two aspects of RNA sequencing technology. The first is the methodology for modeling the overdispersion inherent in RNA-seq data for differential expression analysis. This aspect is addressed in three sections. The second aspect is the application of RNA-seq data to identify the CpG island methylator phenotype (CIMP) by integrating datasets of mRNA expression level and DNA methylation status. Section 1: The cost of DNA sequencing has reduced dramatically in the past decade. Consequently, genomic research increasingly depends on sequencing technology. However it remains elusive how the sequencing capacity influences the accuracy of mRNA expression measurement. We observe that accuracy improves along with the increasing sequencing depth. To model the overdispersion, we use the beta-binomial distribution with a new parameter indicating the dependency between overdispersion and sequencing depth. Our modified beta-binomial model performs better than the binomial or the pure beta-binomial model with a lower false discovery rate. Section 2: Although a number of methods have been proposed in order to accurately analyze differential RNA expression on the gene level, modeling on the base pair level is required. Here, we find that the overdispersion rate decreases as the sequencing depth increases on the base pair level. Also, we propose four models and compare them with each other. As expected, our beta binomial model with a dynamic overdispersion rate is shown to be superior. Section 3: We investigate biases in RNA-seq by exploring the measurement of the external control, spike-in RNA. This study is based on two datasets with spike-in controls obtained from a recent study. We observe an undiscovered bias in the measurement of the spike-in transcripts that arises from the influence of the sample transcripts in RNA-seq. Also, we find that this influence is related to the local sequence of the random hexamer that is used in priming. We suggest a model of the inequality between samples and to correct this type of bias. Section 4: The expression of a gene can be turned off when its promoter is highly methylated. Several studies have reported that a clear threshold effect exists in gene silencing that is mediated by DNA methylation. It is reasonable to assume the thresholds are specific for each gene. It is also intriguing to investigate genes that are largely controlled by DNA methylation. These genes are called “L-shaped” genes. We develop a method to determine the DNA methylation threshold and identify a new CIMP of BRCA. In conclusion, we provide a detailed understanding of the relationship between the overdispersion rate and sequencing depth. And we reveal a new bias in RNA-seq and provide a detailed understanding of the relationship between this new bias and the local sequence. Also we develop a powerful method to dichotomize methylation status and consequently we identify a new CIMP of breast cancer with a distinct classification of molecular characteristics and clinical features.

Identification, purification, sequencing and characterization of human lung fibroblast motility -stimulating factor for human soft tissue sarcoma cells

Paracrine motogenic factors, including motility cytokines and extracellular matrix molecules secreted by normal cells, can stimulate metastatic cell invasion. For extracellular matrix molecules, both the intact molecules and the degradative products may exhibit these activities, which in some cases are not shared by the intact molecules. We found that human peritumoral and lung fibroblasts secrete motility-stimulating activity for several recently established human sarcoma cell strains. The motility of lung metastasis-derived human SYN-1 sarcoma cells was preferentially stimulated by human lung and peritumoral fibroblast motility-stimulating factors (FMSFs). FMSFs were nondialyzable, susceptible to trypsin, and sensitive to dithiothreitol. Cycloheximide inhibited accumulation of FMSF activity in conditioned medium; however, addition of cycloheximide to the migration assay did not significantly affect motility-stimulating activity. Purified hepatocyte growth factor/scatter factor (HGF/SF), rabbit anti-hHGF, and RT-PCR analysis of peritumoral and lung fibroblast HGF/SF mRNA expression indicated that FMSF activity was unrelated to HGF/SF. Partial purification of FMSF by gel exclusion chromatography revealed several peaks of activity, suggesting multiple FMSF molecules or complexes.^ We purified the fibroblast motility-stimulating factor from human lung fibroblast-conditioned medium to apparent homogeneity by sequential heparin affinity chromatography and DEAE anion exchange chromatography. Lysylendopeptidase C digestion of FMSF and sequencing of peptides purified by reverse phase HPLC after digestion identified it as an N-terminal fragment of human fibronectin. Purified FMSF stimulated predominantly chemotaxis but chemokinesis as well of SYN-1 sarcoma cells and was chemotactic for a variety of human sarcoma cells, including fibrosarcoma, leiomyosarcoma, liposarcoma, synovial sarcoma and neurofibrosarcoma cells. The motility-stimulating activity present in HLF-CM was completely eliminated by either neutralization or immunodepletion with a rabbit anti-human-fibronectin antibody, thus further confirming that the fibronectin fragment was the FMSF responsible for the motility stimulation of human soft tissue sarcoma cells. Since human soft tissue sarcomas have a distinctive hematogenous metastatic pattern (predominantly lung), FMSF may play a role in this process. ^

Table 1 Microorganisms, identified with DOGE analysis. 16S rDNA sequences, obtained from sequencing of DOGE bands, were assigned to the corresponding microorganisms

Microorganisms play an important role in the transformation of material within the earth's crust. The storage of CO2 could affect the composition of inorganic and organic components in the reservoir, consequently influencing microbial activities. To study the microbial induced processes together with geochemical, petrophysical and mineralogical changes, occurring during CO2 storage, long-term laboratory experiments under simulated reservoir P-T conditions were carried out. Clean inner core sections, obtained from the reservoir region at the CO2 storage site in Ketzin (Germany) from a depth of about 650 m, were incubated in high pressure vessels together with sterile synthetic formation brine under in situ P-T conditions of 5.5 MPa and 40°C. A 16S rDNA based fingerprinting method was used to identify the dominant species in DNA extracts of pristine sandstone samples. Members of the alpha- and beta-subdivisions of Proteobacteria and the Actinobacteria were identified. So far sequences belonging to facultative anaerobic, chemoheterotrophic bacteria (Burkholderia fungorum, Agrobacterium tumefaciens) gaining their energy from the oxidation of organic molecules and a genus also capable of chemolithoautotrophic growth (Hydrogenophaga) was identified. During CO2 incubation minor changes in the microbial community composition were observed. The majority of microbes were able to adapt to the changed conditions. During CO2 exposure increased concentrations of Ca**2+, K**+, Mg**2+ and SO4**2- were observed. Partially, concentration rises are (i) due to equilibration between rock pore water and synthetic brine, and (ii) between rock and brine, and are thus independent on CO2 exposure. However, observed concentrations of Ca**2+, K**+, Mg**2+ are even higher than in the original reservoir fluid and therefore indicate mineral dissolution due to CO2 exposure.

Jelly biomass sinking speed reveals a fast carbon export mechanism

Particulate matter export fuels benthic ecosystems in continental margins and the deep sea, removing carbon from the upper ocean. Gelatinous zooplankton biomass provides a fast carbon vector that has been poorly studied. Observational data of a large-scale benthic trawling survey from 1994 to 2005 provided a unique opportunity to quantify jelly-carbon along an entire continental margin in the Mediterranean Sea and to assess potential links with biological and physical variables. Biomass depositions were sampled in shelves, slopes and canyons with peaks above 1000 carcasses per trawl, translating to standing stock values between 0.3 and 1.4 mg C m2 after trawling and integrating between 30,000 and 175,000 m2 of seabed. The benthopelagic jelly-carbon spatial distribution from the shelf to the canyons may be explained by atmospheric forcing related with NAO events and dense shelf water cascading, which are both known from the open Mediterranean. Over the decadal scale, we show that the jelly-carbon depositions temporal variability paralleled hydroclimate modifications, and that the enhanced jelly-carbon deposits are connected to a temperature-driven system where chlorophyll plays a minor role. Our results highlight the importance of gelatinous groups as indicators of large-scale ecosystem change, where jelly-carbon depositions play an important role in carbon and energy transport to benthic systems.

Shotgun proteomics reveals physiological response to ocean acidification in Crassostrea gigas

Background. Ocean acidification as a result of increased anthropogenic CO2 emissions is occurring in marine and estuarine environments worldwide. The coastal ocean experiences additional daily and seasonal fluctuations in pH that can be lower than projected end of century open ocean pH reductions. Projected and current ocean acidification have wide-ranging effects on many aquatic organisms, however the exact mechanisms of the impacts of ocean acidification on many of these animals remains to be characterized. Methods. In order to assess the impact of ocean acidification on marine invertebrates, Pacific oysters (Crassostrea gigas) were exposed to one of four different pCO2 levels for four weeks: 400 µatm (pH 8.0), 800 µatm (pH 7.7), 1000 µatm (pH 7.6), or 2800 µatm (pH 7.3). At the end of 4 weeks a variety of physiological parameters were measured to assess the impacts of ocean acidification: tissue glycogen content and fatty acid profile, shell micromechanical properties, and response to acute heat shock. To determine the effects of ocean acidification on the underlying molecular physiology of oysters and their stress response, some of the oysters from 400 µatm and 2800 µatm were exposed to an additional mechanical stress and shotgun proteomics were done on oysters from high and low pCO2 and from with and without mechanical stress. Results. At the end of the four week exposure period, oysters in all four pCO2 environments deposited new shell, but growth rate was not different among the treatments. However, micromechanical properties of the new shell were compromised by elevated pCO2. Elevated pCO2 affected neither whole body fatty acid composition, nor glycogen content, nor mortality rate associated with acute heat shock. Shotgun proteomics revealed that several physiological pathways were significantly affected by ocean acidification, including antioxidant response, carbohydrate metabolism, and transcription and translation. Additionally, the proteomic response to a second stress differed with pCO2, with numerous processes significantly affected by mechanical stimulation at high versus low pCO2 (all proteomics data are available in the ProteomeXchange under the identifier PXD000835). Discussion. Oyster physiology is significantly altered by exposure to elevated pCO2, indicating changes in energy resource use. This is especially apparent in the assessment of the effects of pCO2 on the proteomic response to a second stress. The altered stress response illustrates that ocean acidification may impact how oysters respond to other changes in their environment. These data contribute to an integrative view of the effects of ocean acidification on oysters as well as physiological trade-offs during environmental stress.

1H NMR Metabolomics Reveals Contrasting Response by Male and Female Mussels Exposed to Reduced Seawater pH, Increased Temperature, and a Pathogen

Human activities are fundamentally altering the chemistry of the world's oceans. Ocean acidification (OA) is occurring against a background of warming and an increasing occurrence of disease outbreaks, posing a significant threat to marine organisms, communities, and ecosystems. In the current study, 1H NMR spectroscopy was used to investigate the response of the blue mussel, Mytilus edulis, to a 90-day exposure to reduced seawater pH and increased temperature, followed by a subsequent pathogenic challenge. Analysis of the metabolome revealed significant differences between male and female organisms. Furthermore, males and females are shown to respond differently to environmental stress. While males were significantly affected by reduced seawater pH, increased temperature, and a bacterial challenge, it was only a reduction in seawater pH that impacted females. Despite impacting males and females differently, stressors seem to act via a generalized stress response impacting both energy metabolism and osmotic balance in both sexes. This study therefore has important implications for the interpretation of metabolomic data in mussels, as well as the impact of environmental stress in marine invertebrates in general.

Empirical Evidence Reveals Seasonally Dependent Reduction in Nitrification in Coastal Sediments Subjected to Near Future Ocean Acidification

Research so far has provided little evidence that benthic biogeochemical cycling is affected by ocean acidification under realistic climate change scenarios. We measured nutrient exchange and sediment community oxygen consumption (SCOC) rates to estimate nitrification in natural coastal permeable and fine sandy sediments under pre-phytoplankton bloom and bloom conditions. Ocean acidification, as mimicked in the laboratory by a realistic pH decrease of 0.3, significantly reduced SCOC on average by 60% and benthic nitrification rates on average by 94% in both sediment types in February (pre-bloom period), but not in April (bloom period). No changes in macrofauna functional community (density, structural and functional diversity) were observed between ambient and acidified conditions, suggesting that changes in benthic biogeochemical cycling were predominantly mediated by changes in the activity of the microbial community during the short-term incubations (14 days), rather than by changes in engineering effects of bioturbating and bio-irrigating macrofauna. As benthic nitrification makes up the gross of ocean nitrification, a slowdown of this nitrogen cycling pathway in both permeable and fine sediments in winter, could therefore have global impacts on coupled nitrification-denitrification and hence eventually on pelagic nutrient availability.

Molecular fingerprinting and amplicon sequencing of the bacterial biofilm on settlement tiles deployed along natural pH gradients in Papua New Guinea

Bacterial biofilms provide cues for the settlement of marine invertebrates such as coral larvae, and are therefore important for the resilience and recovery of coral reefs. This study aimed to better understand how ocean acidification may affect the community composition and diversity of bacterial biofilms on surfaces under naturally reduced pH conditions. Settlement tiles were deployed at coral reefs in Papua New Guinea along pH gradients created by two CO2 seeps, and upper and lower tiles surfaces were sampled 5 and 13 months after deployment. Automated Ribosomal Intergenic Spacer Analysis were used to characterize more than 200 separate bacterial communities, complemented by amplicon sequencing of the bacterial 16S rRNA gene of 16 samples. The bacterial biofilm consisted predominantly of Alpha-, Gamma- and Deltaproteobacteria, as well as Cyanobacteria, Flavobacteriia and Cytophaga, whereas putative settlement-inducing taxa only accounted for a small fraction of the community. Bacterial biofilm composition was heterogeneous with approximately 25% shared operational taxonomic units between samples. Among the observed environmental parameters, pH only had a weak effect on community composition (R² ~ 1%) and did not affect community richness and evenness. In contrast, there were strong differences between upper and lower surfaces (contrasting in light exposure and grazing intensity). There also appeared to be a strong interaction between bacterial biofilm composition and the macroscopic components of the tile community. Our results suggest that on mature settlement surfaces in situ, pH does not have a strong impact on the composition of bacterial biofilms. Other abiotic and biotic factors such as light exposure and interactions with other organisms may be more important in shaping bacterial biofilms than changes in seawater pH.

Jelly biomass sinking speed reveals a fast carbon export mechanism

Sinking of gelatinous zooplankton biomass is an important component of the biological pump removing carbon from the upper ocean. The export efficiency, e.g., how much biomass reaches the ocean interior sequestering carbon, is poorly known because of the absence of reliable sinking speed data. We measured sinking rates of gelatinous particulate organic matter (jelly-POM) from different species of scyphozoans, ctenophores, thaliaceans, and pteropods, both in the field and in the laboratory in vertical columns filled with seawater using high-quality video. Using these data, we determined taxon-specific jelly-POM export efficiencies using equations that integrate biomass decay rate, seawater temperature, and sinking speed. Two depth scenarios in several environments were considered, with jelly-POM sinking from 200 and 600 m in temperate, tropical, and polar regions. Jelly-POM sank on average between 850 and 1500 m/d (salps: 800-1200 m/d; ctenophores: 1200-1500 m/d; scyphozoans: 1000-1100 m d; pyrosomes: 1300 m/d). High latitudes represent a fast-sinking and low-remineralization corridor, regardless of species. In tropical and temperate regions, significant decomposition takes place above 1500 m unless jelly-POM sinks below the permanent thermocline. Sinking jelly-POM sequesters carbon to the deep ocean faster than anticipated, and should be incorporated into biogeochemical and modeling studies to provide more realistic quantification of export via the biological carbon pump worldwide.

Coral calcification under daily oxygen saturation and pH dynamics reveals the important role of oxygen

Coral reefs are essential to many nations, and are currently in global decline. Although climate models predict decreases in seawater pH (0.3 units) and oxygen saturation (5 percentage points), these are exceeded by the current daily pH and oxygen fluctuations on many reefs (pH 7.8-8.7 and 27-241% O2 saturation). We investigated the effect of oxygen and pH fluctuations on coral calcification in the laboratory using the model species Acropora millepora. Light calcification rates were greatly enhanced (+178%) by increased seawater pH, but only at normoxia; hyperoxia completely negated this positive effect. Dark calcification rates were significantly inhibited (51-75%) at hypoxia, whereas pH had no effect. Our preliminary results suggest that within the current oxygen and pH range, oxygen has substantial control over coral growth, whereas the role of pH is limited. This has implications for reef formation in this era of rapid climate change, which is accompanied by a decrease in seawater oxygen saturation owing to higher water temperatures and coastal eutrophication.