High-quality, high-throughput measurement of protein-DNA binding using HiTS-FLIP

In order to understand in more depth and on a genome wide scale the behavior of transcription factors (TFs), novel quantitative experiments with high-throughput are needed. Recently, HiTS-FLIP (High-Throughput Sequencing-Fluorescent Ligand Interaction Profiling) was invented by the Burge lab at the MIT (Nutiu et al. (2011)). Based on an Illumina GA-IIx machine for next-generation sequencing, HiTS-FLIP allows to measure the affinity of fluorescent labeled proteins to millions of DNA clusters at equilibrium in an unbiased and untargeted way examining the entire sequence space by Determination of dissociation constants (Kds) for all 12-mer DNA motifs. During my PhD I helped to improve the experimental design of this method to allow measuring the protein-DNA binding events at equilibrium omitting any washing step by utilizing the TIRF (Total Internal Reflection Fluorescence) based optics of the GA-IIx. In addition, I developed the first versions of XML based controlling software that automates the measurement procedure. Meeting the needs for processing the vast amount of data produced by each run, I developed a sophisticated, high performance software pipeline that locates DNA clusters, normalizes and extracts the fluorescent signals. Moreover, cluster contained k-mer motifs are ranked and their DNA binding affinities are quantified with high accuracy. My approach of applying phase-correlation to estimate the relative translative Offset between the observed tile images and the template images omits resequencing and thus allows to reuse the flow cell for several HiTS-FLIP experiments, which greatly reduces cost and time. Instead of using information from the sequencing images like Nutiu et al. (2011) for normalizing the cluster intensities which introduces a nucleotide specific bias, I estimate the cluster related normalization factors directly from the protein Images which captures the non-even illumination bias more accurately and leads to an improved correction for each tile image. My analysis of the ranking algorithm by Nutiu et al. (2011) has revealed that it is unable to rank all measured k-mers. Discarding all the clusters related to previously ranked k-mers has the side effect of eliminating any clusters on which k-mers could be ranked that share submotifs with previously ranked k-mers. This shortcoming affects even strong binding k-mers with only one mutation away from the top ranked k-mer. My findings show that omitting the cluster deletion step in the ranking process overcomes this limitation and allows to rank the full spectrum of all possible k-mers. In addition, the performance of the ranking algorithm is drastically reduced by my insight from a quadratic to a linear run time. The experimental improvements combined with the sophisticated processing of the data has led to a very high accuracy of the HiTS-FLIP dissociation constants (Kds) comparable to the Kds measured by the very sensitive HiP-FA assay (Jung et al. (2015)). However, experimentally HiTS-FLIP is a very challenging assay. In total, eight HiTS-FLIP experiments were performed but only one showed saturation, the others exhibited Protein aggregation occurring at the amplified DNA clusters. This biochemical issue could not be remedied. As example TF for studying the details of HiTS-FLIP, GCN4 was chosen which is a dimeric, basic leucine zipper TF and which acts as the master regulator of the amino acid starvation Response in Saccharomyces cerevisiae (Natarajan et al. (2001)). The fluorescent dye was mOrange. The HiTS-FLIP Kds for the TF GCN4 were validated by the HiP-FA assay and a Pearson correlation coefficient of R=0.99 and a relative error of delta=30.91% was achieved. Thus, a unique and comprehensive data set of utmost quantitative precision was obtained that allowed to study the complex binding behavior of GCN4 in a new way. My Downstream analyses reveal that the known 7-mer consensus motif of GCN4, which is TGACTCA, is modulated by its 2-mer neighboring flanking regions spanning an affinity range over two orders of magnitude from a Kd=1.56 nM to Kd=552.51 nM. These results suggest that the common 9-mer PWM (Position Weight Matrix) for GCN4 is insufficient to describe the binding behavior of GCN4. Rather, an additional left and right flanking nucleotide is required to extend the 9-mer to an 11-mer. My analyses regarding mutations and related delta delta G values suggest long-range interdependencies between nucleotides of the two dimeric half-sites of GCN4. Consequently, models assuming positional independence, such as a PWM, are insufficient to explain these interdependencies. Instead, the full spectrum of affinity values for all k-mers of appropriate size should be measured and applied in further analyses as proposed by Nutiu et al. (2011). Another discovery were new binding motifs of GCN4, which can only be detected with a method like HiTS-FLIP that examines the entire sequence space and allows for unbiased, de-novo motif discovery. All These new motifs contain GTGT as a submotif and the data collected suggests that GCN4 binds as monomer to these new motifs. Therefore, it might be even possible to detect different binding modes with HiTS-FLIP. My results emphasize the binding complexity of GCN4 and demonstrate the advantage of HiTS-FLIP for investigating the complexity of regulative processes

Proof of a determinant evaluation conjectured by Bombieri, Hunt and van der Poorten

A determinant evaluation is proven, a special case of which establishes a conjecture of Bombieri, Hunt, and van der Poorten (Experimental Math\. {\bf 4} (1995), 87--96) that arose in the study of Thue's method of approximating algebraic numbers.Comment: AMSTe

Fertility and Housing Market: Australian Evidence

This thesis comprises three papers examining the relationship between fertility and housing. The first paper takes a macro perceptive and presents time series evidence on the aggregate relationship between fertility rate and house prices in Australia. An exploration of underlying household decision-making is undertaken in the second and third papers using micro panel data. The second paper examines the effect of changes in house prices and housing wealth on fertility related decisions among non-moving households across housing tenures. The third paper investigates the alternative response of residential relocation in anticipation of childbearing. The first paper provides aggregate evidence on the secular relationship between fertility rates and house prices over the period 1971-2014 in Australia. Standard cointegration analysis is applied to the endogenous and nonstationary time series variables in the fertility demand function. The stationary long-run cointegrating relationship between total fertility rates, house prices, female labour force participation rates, and male and female wages is modelled for each state and territory. The macro estimation shows some evidence of a negative correlation between fertility rate and house prices, especially in some major housing markets and for the early 30s cohorts. Some age groups across states and territories exhibit a positive association between fertility rate and house prices, which may reflect the housing wealth effect on fertility consumption. Alternatively, it may be explained by the regional migration of young couples. A more comprehensive understanding on the underlying household behaviour however requires the examination on microdata. Recognising the distinctive implications of house price movement across housing tenures, the second paper examines the effect of changes in house prices and housing wealth on fertility related decisions using the Household, Income and Labour Dynamics in Australia (HILDA) survey during 2001-2015. The identification of conditionally exogenous changes in house prices with respect to fertility decision exploits the geographic and temporal variation in housing prices across localities and over time. Focusing on non-moving owner and rental occupiers, the study finds that the childbirth among homeowners respond positively to the increase in housing wealth while the fertility intention of renters respond negatively to the higher market housing prices. The positive housing wealth effect has the greatest impact on the fertility and fertility intentions of homeowners who are married or mortgaged with moderate borrowing constraints. Households can also respond to housing market development by residential relocation. The third paper considers the ease or difficulty of housing adjustment in anticipation of family growth, and explores the impact of fertility desire and expectation on residential mobility over various distances. Several empirical strategies such as correlated random effects models, simultaneous equations models, and instrumental variable models are implemented to correct for the possible bias in unobserved heterogeneity and joint determination. Using the same dataset as the second paper, the study finds a significant impact of fertility intention on residential relocation in Australia, with large heterogeneity across housing markets and relocation distances. The estimating results suggest that fertility-induced moves are mainly observed for households residing in the housing markets with low affordability pressures and often occur intra-regionally across local government areas

Upcountry Yeomanry in Antebellum Georgia: A Comparative Analysis

This dissertation is a comparative analysis of the yeomanry of Forsyth and Hancock counties in Georgia during the ten years prior to the Civil War. The premise argues that definitive characteristics of yeoman culture can only be found in counties that are dominated the yeomanry. Studies that find yeomen in planter dominated counties are defined those yeomen by the institutions that are created by and serve the planter society

The specificity and evolution of gene regulatory elements

Thesis (Ph. D.)--Massachusetts Institute of Technology, Computational and Systems Biology Program, 2010.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references.The regulation of gene expression underlies the morphological, physiological, and functional differences between human cell types, developmental stages, and healthy and disease states. Gene regulation in eukaryotes is controlled by a complex milieu including transcription factors, microRNAs (miRNAs), cis-regulatory DNA and RNA. It is the quantitative and combinatorial interactions of these regulatory elements that defines gene expression, but these interactions are incompletely understood. In this thesis, I present two new methods for determining the quantitative specificity of gene regulatory factors. First, I present a comparative genomics approach that utilizes signatures of natural selection to detect the conserved biological relevance of miRNAs and their targets. Using this method, I quantify the abundance of different conserved miRNA target types, including different seed matches and 30-compensatory targets. I show that over 60% of mammalian mRNAs are conserved targets of miRNAs and that a surprising amount of conserved miRNA targeting is mediated by seed matches with relatively low efficacy. Extending this method from mammals to other organisms, I find that miRNA targeting rules are mostly conserved, although I show evidence for new types of miRNA targets in nematodes. Taking advantage of variations in 30 UTR lengths between species, I describe general properties of miRNA targeting that are affected by 30 UTR length. Finally, I introduce a new, high-throughput assay for the quantification of transcription factor in vitro binding affinity to millions of sequences. I apply this method to GCN4, a yeast transcription factor, and reconstruct all known properties of its binding preferences. Additionally, I discover some new subtleties in its specificity and estimate dissociation constants for hundreds of thousands of sequences. I verify the utility of the binding affinities by comparing to in vivo binding data and to the regulatory response following GCN4 induction.by Robin Carl Friedman.Ph.D

High-quality, high-throughput measurement of protein-DNA binding using HiTS-FLIP

In order to understand in more depth and on a genome wide scale the behavior of transcription factors (TFs), novel quantitative experiments with high-throughput are needed. Recently, HiTS-FLIP (High-Throughput Sequencing-Fluorescent Ligand Interaction Profiling) was invented by the Burge lab at the MIT (Nutiu et al. (2011)). Based on an Illumina GA-IIx machine for next-generation sequencing, HiTS-FLIP allows to measure the affinity of fluorescent labeled proteins to millions of DNA clusters at equilibrium in an unbiased and untargeted way examining the entire sequence space by Determination of dissociation constants (Kds) for all 12-mer DNA motifs. During my PhD I helped to improve the experimental design of this method to allow measuring the protein-DNA binding events at equilibrium omitting any washing step by utilizing the TIRF (Total Internal Reflection Fluorescence) based optics of the GA-IIx. In addition, I developed the first versions of XML based controlling software that automates the measurement procedure. Meeting the needs for processing the vast amount of data produced by each run, I developed a sophisticated, high performance software pipeline that locates DNA clusters, normalizes and extracts the fluorescent signals. Moreover, cluster contained k-mer motifs are ranked and their DNA binding affinities are quantified with high accuracy. My approach of applying phase-correlation to estimate the relative translative Offset between the observed tile images and the template images omits resequencing and thus allows to reuse the flow cell for several HiTS-FLIP experiments, which greatly reduces cost and time. Instead of using information from the sequencing images like Nutiu et al. (2011) for normalizing the cluster intensities which introduces a nucleotide specific bias, I estimate the cluster related normalization factors directly from the protein Images which captures the non-even illumination bias more accurately and leads to an improved correction for each tile image. My analysis of the ranking algorithm by Nutiu et al. (2011) has revealed that it is unable to rank all measured k-mers. Discarding all the clusters related to previously ranked k-mers has the side effect of eliminating any clusters on which k-mers could be ranked that share submotifs with previously ranked k-mers. This shortcoming affects even strong binding k-mers with only one mutation away from the top ranked k-mer. My findings show that omitting the cluster deletion step in the ranking process overcomes this limitation and allows to rank the full spectrum of all possible k-mers. In addition, the performance of the ranking algorithm is drastically reduced by my insight from a quadratic to a linear run time. The experimental improvements combined with the sophisticated processing of the data has led to a very high accuracy of the HiTS-FLIP dissociation constants (Kds) comparable to the Kds measured by the very sensitive HiP-FA assay (Jung et al. (2015)). However, experimentally HiTS-FLIP is a very challenging assay. In total, eight HiTS-FLIP experiments were performed but only one showed saturation, the others exhibited Protein aggregation occurring at the amplified DNA clusters. This biochemical issue could not be remedied. As example TF for studying the details of HiTS-FLIP, GCN4 was chosen which is a dimeric, basic leucine zipper TF and which acts as the master regulator of the amino acid starvation Response in Saccharomyces cerevisiae (Natarajan et al. (2001)). The fluorescent dye was mOrange. The HiTS-FLIP Kds for the TF GCN4 were validated by the HiP-FA assay and a Pearson correlation coefficient of R=0.99 and a relative error of delta=30.91% was achieved. Thus, a unique and comprehensive data set of utmost quantitative precision was obtained that allowed to study the complex binding behavior of GCN4 in a new way. My Downstream analyses reveal that the known 7-mer consensus motif of GCN4, which is TGACTCA, is modulated by its 2-mer neighboring flanking regions spanning an affinity range over two orders of magnitude from a Kd=1.56 nM to Kd=552.51 nM. These results suggest that the common 9-mer PWM (Position Weight Matrix) for GCN4 is insufficient to describe the binding behavior of GCN4. Rather, an additional left and right flanking nucleotide is required to extend the 9-mer to an 11-mer. My analyses regarding mutations and related delta delta G values suggest long-range interdependencies between nucleotides of the two dimeric half-sites of GCN4. Consequently, models assuming positional independence, such as a PWM, are insufficient to explain these interdependencies. Instead, the full spectrum of affinity values for all k-mers of appropriate size should be measured and applied in further analyses as proposed by Nutiu et al. (2011). Another discovery were new binding motifs of GCN4, which can only be detected with a method like HiTS-FLIP that examines the entire sequence space and allows for unbiased, de-novo motif discovery. All These new motifs contain GTGT as a submotif and the data collected suggests that GCN4 binds as monomer to these new motifs. Therefore, it might be even possible to detect different binding modes with HiTS-FLIP. My results emphasize the binding complexity of GCN4 and demonstrate the advantage of HiTS-FLIP for investigating the complexity of regulative processes

Development of novel computational tools based on analysis of DNA compositional biases to identify and study the distribution of mobile genomic elements among bacteria

Horizontal gene transfer, well characterized as the transfer of genomic material between organisms contributes hugely in the evolution and speciation of bacteria. The transfer of such material brings about bacteria that are virulent and also in possession of genes that render them resistant to antibiotics. This helps to spread about and recombine genes of their kind to other bacteria. Horizontally acquired genomic elements exhibit compositional features that are deviant from the rest of the other genes in a recipient genome. They possess features such as unusual GC%, atypical codon usage, oligonucleotide usage bias and direct repeats at their flanks that can be used to distinguish them from native genes in a genome. This work focused on the developments of statistical and computational methods to aid with the detection of genes that have undergone horizontal transfer, to help track down genes that could be of medical and environmental importance. Therefore, SeqWord Gene Island Sniffer (SWGIS), a statistically driven computational tool for the prediction of genomic islands, and GEI-DB, a comprehensive database of horizontally transferred genomic elements were established. The SWGIS tool allows the precise predictions of precise inserts of horizontally acquired gene clusters in prokaryotic genomic sequences. Thus, the GEI-DB stores all the foreign genomic inserts that have been detected in the study, together with their annotations and evolutionary measures, such as groups of genomic islands that share similarities in DNA and amino acids features. CopyrightDissertation (MSc)--University of Pretoria, 2009.Biochemistryunrestricte

The Impact of 2-D and 3-D Grouping Cues on Depth From Binocular Disparity

Stereopsis is a powerful source of information about the relative depth of objects in the world. In isolation, humans can see depth from binocular disparity without any other depth cues. However, many different stimulus properties can dramatically influence the depth we perceive. For example, there is an abundance of research showing that the configuration of a stimulus can impact the percept of depth, in some cases diminishing the amount of depth experience. Much of the previous research has focused on discrimination thresholds; in one example, stereoacuity for a pair of vertical lines was shown to be markedly reduced when these lines were connected to form a rectangle apparently slanted in depth (eg: McKee, 1983). The contribution of Gestalt figural grouping to this phenomenon has not been studied. This dissertation addresses the role that perceptual grouping plays in the recovery of suprathreshold depth from disparity. First, I measured the impact of perceptual closure on depth magnitude. Observers estimated the separation in depth of a pair of vertical lines as the amount of perceptual closure was varied. In a series of experiments, I characterized the 2-D and 3-D properties that contribute to 3-D closure and the estimates of apparent depth. Estimates of perceived depth were highly correlated to the strength of subjective closure. Furthermore, I highlighted the perceptual consequences (both costs and benefits) of a new disparity-based grouping cue that interacts with perceived closure, which I call good stereoscopic continuation. This cue was shown to promote detection in a visual search task but reduces depth percepts compared to isolated features. Taken together, the results reported here show that specific 2-D and 3-D grouping constraints are required to promote recovery of a 3-D object. As a consequence, quantitative depth is reduced, but the object is rapidly detected in a visual search task. I propose that these phenomena are the result of object-based disparity smoothing operations that enhance object cohesion