Computational Inference of Genome-Wide Protein-DNA Interactions Using High-Throughput Genomic Data

Transcriptional regulation has been studied intensively in recent decades. One important aspect of this regulation is the interaction between regulatory proteins, such as transcription factors (TF) and nucleosomes, and the genome. Different high-throughput techniques have been invented to map these interactions genome-wide, including ChIP-based methods (ChIP-chip, ChIP-seq, etc.), nuclease digestion methods (DNase-seq, MNase-seq, etc.), and others. However, a single experimental technique often only provides partial and noisy information about the whole picture of protein-DNA interactions. Therefore, the overarching goal of this dissertation is to provide computational developments for jointly modeling different experimental datasets to achieve a holistic inference on the protein-DNA interaction landscape.

We first present a computational framework that can incorporate the protein binding information in MNase-seq data into a thermodynamic model of protein-DNA interaction. We use a correlation-based objective function to model the MNase-seq data and a Markov chain Monte Carlo method to maximize the function. Our results show that the inferred protein-DNA interaction landscape is concordant with the MNase-seq data and provides a mechanistic explanation for the experimentally collected MNase-seq fragments. Our framework is flexible and can easily incorporate other data sources. To demonstrate this flexibility, we use prior distributions to integrate experimentally measured protein concentrations.

We also study the ability of DNase-seq data to position nucleosomes. Traditionally, DNase-seq has only been widely used to identify DNase hypersensitive sites, which tend to be open chromatin regulatory regions devoid of nucleosomes. We reveal for the first time that DNase-seq datasets also contain substantial information about nucleosome translational positioning, and that existing DNase-seq data can be used to infer nucleosome positions with high accuracy. We develop a Bayes-factor-based nucleosome scoring method to position nucleosomes using DNase-seq data. Our approach utilizes several effective strategies to extract nucleosome positioning signals from the noisy DNase-seq data, including jointly modeling data points across the nucleosome body and explicitly modeling the quadratic and oscillatory DNase I digestion pattern on nucleosomes. We show that our DNase-seq-based nucleosome map is highly consistent with previous high-resolution maps. We also show that the oscillatory DNase I digestion pattern is useful in revealing the nucleosome rotational context around TF binding sites.

Finally, we present a state-space model (SSM) for jointly modeling different kinds of genomic data to provide an accurate view of the protein-DNA interaction landscape. We also provide an efficient expectation-maximization algorithm to learn model parameters from data. We first show in simulation studies that the SSM can effectively recover underlying true protein binding configurations. We then apply the SSM to model real genomic data (both DNase-seq and MNase-seq data). Through incrementally increasing the types of genomic data in the SSM, we show that different data types can contribute complementary information for the inference of protein binding landscape and that the most accurate inference comes from modeling all available datasets.

This dissertation provides a foundation for future research by taking a step toward the genome-wide inference of protein-DNA interaction landscape through data integration.

Folate regulation of axonal regeneration in the rodent central nervous system through DNA methylation.

The folate pathway plays a crucial role in the regeneration and repair of the adult CNS after injury. Here, we have shown in rodents that such repair occurs at least in part through DNA methylation. In animals with combined spinal cord and sciatic nerve injury, folate-mediated CNS axon regeneration was found to depend on injury-related induction of the high-affinity folate receptor 1 (Folr1). The activity of folate was dependent on its activation by the enzyme dihydrofolate reductase (Dhfr) and a functional methylation cycle. The effect of folate on the regeneration of afferent spinal neurons was biphasic and dose dependent and correlated closely over its dose range with global and gene-specific DNA methylation and with expression of both the folate receptor Folr1 and the de novo DNA methyltransferases. These data implicate an epigenetic mechanism in CNS repair. Folic acid and possibly other nontoxic dietary methyl donors may therefore be useful in clinical interventions to promote brain and spinal cord healing. If indeed the benefit of folate is mediated by epigenetic mechanisms that promote endogenous axonal regeneration, this provides possible avenues for new pharmacologic approaches to treating CNS injuries.

Altered gene expression and DNA damage in peripheral blood cells from Friedreich's ataxia patients: cellular model of pathology.

The neurodegenerative disease Friedreich's ataxia (FRDA) is the most common autosomal-recessively inherited ataxia and is caused by a GAA triplet repeat expansion in the first intron of the frataxin gene. In this disease, transcription of frataxin, a mitochondrial protein involved in iron homeostasis, is impaired, resulting in a significant reduction in mRNA and protein levels. Global gene expression analysis was performed in peripheral blood samples from FRDA patients as compared to controls, which suggested altered expression patterns pertaining to genotoxic stress. We then confirmed the presence of genotoxic DNA damage by using a gene-specific quantitative PCR assay and discovered an increase in both mitochondrial and nuclear DNA damage in the blood of these patients (p<0.0001, respectively). Additionally, frataxin mRNA levels correlated with age of onset of disease and displayed unique sets of gene alterations involved in immune response, oxidative phosphorylation, and protein synthesis. Many of the key pathways observed by transcription profiling were downregulated, and we believe these data suggest that patients with prolonged frataxin deficiency undergo a systemic survival response to chronic genotoxic stress and consequent DNA damage detectable in blood. In conclusion, our results yield insight into the nature and progression of FRDA, as well as possible therapeutic approaches. Furthermore, the identification of potential biomarkers, including the DNA damage found in peripheral blood, may have predictive value in future clinical trials.

Membrane binding of plasmid DNA and endocytic pathways are involved in electrotransfection of mammalian cells.

Electric field mediated gene delivery or electrotransfection is a widely used method in various studies ranging from basic cell biology research to clinical gene therapy. Yet, mechanisms of electrotransfection are still controversial. To this end, we investigated the dependence of electrotransfection efficiency (eTE) on binding of plasmid DNA (pDNA) to plasma membrane and how treatment of cells with three endocytic inhibitors (chlorpromazine, genistein, dynasore) or silencing of dynamin expression with specific, small interfering RNA (siRNA) would affect the eTE. Our data demonstrated that the presence of divalent cations (Ca(2+) and Mg(2+)) in electrotransfection buffer enhanced pDNA adsorption to cell membrane and consequently, this enhanced adsorption led to an increase in eTE, up to a certain threshold concentration for each cation. Trypsin treatment of cells at 10 min post electrotransfection stripped off membrane-bound pDNA and resulted in a significant reduction in eTE, indicating that the time period for complete cellular uptake of pDNA (between 10 and 40 min) far exceeded the lifetime of electric field-induced transient pores (∼10 msec) in the cell membrane. Furthermore, treatment of cells with the siRNA and all three pharmacological inhibitors yielded substantial and statistically significant reductions in the eTE. These findings suggest that electrotransfection depends on two mechanisms: (i) binding of pDNA to cell membrane and (ii) endocytosis of membrane-bound pDNA.

Are the native giant tortoises from the Seychelles really extinct? A genetic perspective based on mtDNA and microsatellite data.

The extinction of the giant tortoises of the Seychelles Archipelago has long been suspected but is not beyond doubt. A recent morphological study of the giant tortoises of the western Indian Ocean concluded that specimens of two native Seychelles species survive in captivity today alongside giant tortoises of Aldabra, which are numerous in zoos as well as in the wild. This claim has been controversial because some of the morphological characters used to identify these species, several measures of carapace morphology, are reputed to be quite sensitive to captive conditions. Nonetheless, the potential survival of giant tortoise species previously thought extinct presents an exciting scenario for conservation. We used mitochondrial DNA sequences and nuclear microsatellites to examine the validity of the rediscovered species of Seychelles giant tortoises. Our results indicate that the morphotypes suspected to represent Seychelles species do not show levels of variation and genetic structuring consistent with long periods of reproductive isolation. We found no variation in the mitochondrial control region among 55 individuals examined and no genetic structuring in eight microsatellite loci, pointing to the survival of just a single lineage of Indian Ocean tortoises.

Suppression of DNA-damage checkpoint signaling by Rsk-mediated phosphorylation of Mre11.

Ataxia telangiectasia mutant (ATM) is an S/T-Q-directed kinase that is critical for the cellular response to double-stranded breaks (DSBs) in DNA. Following DNA damage, ATM is activated and recruited by the MRN protein complex [meiotic recombination 11 (Mre11)/DNA repair protein Rad50/Nijmegen breakage syndrome 1 proteins] to sites of DNA damage where ATM phosphorylates multiple substrates to trigger cell-cycle arrest. In cancer cells, this regulation may be faulty, and cell division may proceed even in the presence of damaged DNA. We show here that the ribosomal s6 kinase (Rsk), often elevated in cancers, can suppress DSB-induced ATM activation in both Xenopus egg extracts and human tumor cell lines. In analyzing each step in ATM activation, we have found that Rsk targets loading of MRN complex components onto DNA at DSB sites. Rsk can phosphorylate the Mre11 protein directly at S676 both in vitro and in intact cells and thereby can inhibit the binding of Mre11 to DNA with DSBs. Accordingly, mutation of S676 to Ala can reverse inhibition of the response to DSBs by Rsk. Collectively, these data point to Mre11 as an important locus of Rsk-mediated checkpoint inhibition acting upstream of ATM activation.

Association between DNA damage response and repair genes and risk of invasive serous ovarian cancer.

BACKGROUND: We analyzed the association between 53 genes related to DNA repair and p53-mediated damage response and serous ovarian cancer risk using case-control data from the North Carolina Ovarian Cancer Study (NCOCS), a population-based, case-control study. METHODS/PRINCIPAL FINDINGS: The analysis was restricted to 364 invasive serous ovarian cancer cases and 761 controls of white, non-Hispanic race. Statistical analysis was two staged: a screen using marginal Bayes factors (BFs) for 484 SNPs and a modeling stage in which we calculated multivariate adjusted posterior probabilities of association for 77 SNPs that passed the screen. These probabilities were conditional on subject age at diagnosis/interview, batch, a DNA quality metric and genotypes of other SNPs and allowed for uncertainty in the genetic parameterizations of the SNPs and number of associated SNPs. Six SNPs had Bayes factors greater than 10 in favor of an association with invasive serous ovarian cancer. These included rs5762746 (median OR(odds ratio)(per allele) = 0.66; 95% credible interval (CI) = 0.44-1.00) and rs6005835 (median OR(per allele) = 0.69; 95% CI = 0.53-0.91) in CHEK2, rs2078486 (median OR(per allele) = 1.65; 95% CI = 1.21-2.25) and rs12951053 (median OR(per allele) = 1.65; 95% CI = 1.20-2.26) in TP53, rs411697 (median OR (rare homozygote) = 0.53; 95% CI = 0.35 - 0.79) in BACH1 and rs10131 (median OR( rare homozygote) = not estimable) in LIG4. The six most highly associated SNPs are either predicted to be functionally significant or are in LD with such a variant. The variants in TP53 were confirmed to be associated in a large follow-up study. CONCLUSIONS/SIGNIFICANCE: Based on our findings, further follow-up of the DNA repair and response pathways in a larger dataset is warranted to confirm these results.

Regulation of DNA Double Strand Break Response

To ensure genomic integrity, dividing cells implement multiple checkpoint pathways during the course of the cell cycle. In response to DNA damage, cells may either halt the progression of the cycle (cell cycle arrest) or undergo apoptosis. This choice depends on the extent of damage and the cell's capacity for DNA repair. Cell cycle arrest induced by double-stranded DNA breaks relies on the activation of the ataxia-telangiectasia (ATM) protein kinase, which phosphorylates cell cycle effectors (e.g., Chk2 and p53) to inhibit cell cycle progression. ATM is an S/T-Q directed kinase that is critical for the cellular response to double-stranded DNA breaks. Following DNA damage, ATM is activated and recruited to sites of DNA damage by the MRN protein complex (Mre11-Rad50-Nbs1 proteins) where ATM phosphorylates multiple substrates to trigger a cell cycle arrest. In cancer cells, this regulation may be faulty and cell division may proceed even in the presence of damaged DNA. We show here that the RSK kinase, often elevated in cancers, can suppress DSB-induced ATM activation in both Xenopus egg extracts and human tumor cell lines. In analyzing each step in ATM activation, we have found that RSK disrupts the binding of the MRN complex to DSB DNA. RSK can directly phosphorylate the Mre11 protein at Ser 676 both in vitro and in intact cells and can thereby inhibit loading of Mre11 onto DSB DNA. Accordingly, mutation of Ser 676 to Ala can reverse inhibition of the DSB response by RSK. Collectively, these data point to Mre11 as an important locus of RSK-mediated checkpoint inhibition acting upstream of ATM activation.

The phosphorylation of Mre11 on Ser 676 is antagonized by phosphatases. Here, we screened for phosphatases that target this site and identified PP5 as a candidate. This finding is consistent with the fact that PP5 is required for the ATM-mediated DNA damage response, indicating that PP5 may promote DSB-induced, ATM-dependent DNA damage response by targeting Mre11 upstream of ATM.

Later Life Consequences of Developmental Mitochondrial DNA Damage in C. elegans

Mitochondria are responsible for producing the vast majority of cellular ATP, and are therefore critical to organismal health [1]. They contain thir own genomes (mtDNA) which encode 13 proteins that are all subunits of the mitochondrial respiratory chain (MRC) and are essential for oxidative phosphorylation [2]. mtDNA is present in multiple copies per cell, usually between 103 and 104 , though this number is reduced during certain developmental stages [3, 4]. The health of the mitochondrial genome is also important to the health of the organism, as mutations in mtDNA lead to human diseases that collectively affect approximately 1 in 4000 people [5, 6]. mtDNA is more susceptible than nuclear DNA (nucDNA) to damage by many environmental pollutants, for reasons including the absence of Nucleotide Excision Repair (NER) in the mitochondria [7]. NER is a highly functionally conserved DNA repair pathway that removes bulky, helix distorting lesions such as those caused by ultraviolet C (UVC) radiation and also many environmental toxicants, including benzo[a]pyrene (BaP) [8]. While these lesions cannot be repaired, they are slowly removed through a process that involves mitochondrial dynamics and autophagy [9, 10]. However, when present during development in C. elegans, this damage reduces mtDNA copy number and ATP levels [11]. We hypothesize that this damage, when present during development, will result in mitochondrial dysfunction and increase the potential for adverse outcomes later in life.

To test this hypothesis, 1st larval stage (L1) C. elegans are exposed to 3 doses of 7.5J/m2 ultraviolet C radiation 24 hours apart, leading to the accumulation of mtDNA damage [9, 11]. After exposure, many mitochondrial endpoints are assessed at multiple time points later in life. mtDNA and nucDNA damage levels and genome copy numbers are measured via QPCR and real-time PCR , respectively, every 2 day for 10 days. Steady state ATP levels are measured via luciferase expressing reporter strains and traditional ATP extraction methods. Oxygen consumption is measured using a Seahorse XFe24 extra cellular flux analyzer. Gene expression changes are measured via real time PCR and targeted metabolomics via LC-MS are used to investigate changes in organic acid, amino acid and acyl-carnitine levels. Lastly, nematode developmental delay is assessed as growth, and measured via imaging and COPAS biosort.

I have found that despite being removed, UVC induced mtDNA damage during development leads to persistent deficits in energy production later in life. mtDNA copy number is permanently reduced, as are ATP levels, though oxygen consumption is increased, indicating inefficient or uncoupled respiration. Metabolomic data and mutant sensitivity indicate a role for NADPH and oxidative stress in these results, and exposed nematodes are more sensitive to the mitochondrial poison rotenone later in life. These results fit with the developmental origin of health and disease hypothesis, and show the potential for environmental exposures to have lasting effects on mitochondrial function.

Lastly, we are currently working to investigate the potential for irreparable mtDNA lesions to drive mutagenesis in mtDNA. Mutations in mtDNA lead to a wide range of diseases, yet we currently do not understand the environmental component of what causes them. In vitro evidence suggests that UVC induced thymine dimers can be mutagenic [12]. We are using duplex sequencing of C. elegans mtDNA to determine mutation rates in nematodes exposed to our serial UVC protocol. Furthermore, by including mutant strains deficient in mitochondrial fission and mitophagy, we hope to determine if deficiencies in these processes will further increase mtDNA mutation rates, as they are implicated in human diseases.

An Exploration into Fern Genome Space.

Ferns are one of the few remaining major clades of land plants for which a complete genome sequence is lacking. Knowledge of genome space in ferns will enable broad-scale comparative analyses of land plant genes and genomes, provide insights into genome evolution across green plants, and shed light on genetic and genomic features that characterize ferns, such as their high chromosome numbers and large genome sizes. As part of an initial exploration into fern genome space, we used a whole genome shotgun sequencing approach to obtain low-density coverage (∼0.4X to 2X) for six fern species from the Polypodiales (Ceratopteris, Pteridium, Polypodium, Cystopteris), Cyatheales (Plagiogyria), and Gleicheniales (Dipteris). We explore these data to characterize the proportion of the nuclear genome represented by repetitive sequences (including DNA transposons, retrotransposons, ribosomal DNA, and simple repeats) and protein-coding genes, and to extract chloroplast and mitochondrial genome sequences. Such initial sweeps of fern genomes can provide information useful for selecting a promising candidate fern species for whole genome sequencing. We also describe variation of genomic traits across our sample and highlight some differences and similarities in repeat structure between ferns and seed plants.

New insights into Hoogsteen base pairs in DNA duplexes from a structure-based survey.

Hoogsteen (HG) base pairs (bps) provide an alternative pairing geometry to Watson-Crick (WC) bps and can play unique functional roles in duplex DNA. Here, we use structural features unique to HG bps (syn purine base, HG hydrogen bonds and constricted C1'-C1' distance across the bp) to search for HG bps in X-ray structures of DNA duplexes in the Protein Data Bank. The survey identifies 106 A•T and 34 G•C HG bps in DNA duplexes, many of which are undocumented in the literature. It also uncovers HG-like bps with syn purines lacking HG hydrogen bonds or constricted C1'-C1' distances that are analogous to conformations that have been proposed to populate the WC-to-HG transition pathway. The survey reveals HG preferences similar to those observed for transient HG bps in solution by nuclear magnetic resonance, including stronger preferences for A•T versus G•C bps, TA versus GG steps, and also suggests enrichment at terminal ends with a preference for 5'-purine. HG bps induce small local perturbations in neighboring bps and, surprisingly, a small but significant degree of DNA bending (∼14°) directed toward the major groove. The survey provides insights into the preferences and structural consequences of HG bps in duplex DNA.

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.

2000 NHGRI e-mail request for HGP sequencing center information, and corresponding aggregate data from NHGRI, compiled by Kris Wetterstrand

Email exchange in 2013 between Kathryn Maxson (Duke) and Kris Wetterstrand (NHGRI), regarding country funding and other data for the HGP sequencing centers. Also includes the email request for such information, from NHGRI to the centers, in 2000, and the aggregate data collected.