Beyond the Bits: Cooperative Packet Recovery Using Physical Layer Information

PhD thesisWireless networks can suffer from high packet loss rates. This paper shows that the loss rate can be significantly reduced by exposing information readily available at the physical layer. We make the physical layer convey an estimate of its confidence that a particular bit is ``0'' or ``1'' to the higher layers. When used with cooperative design, this information dramatically improves the throughput of the wireless network. Access points that hear the same transmission combine their information to correct bits in a packet with minimal overhead. Similarly, a receiver may combine multiple erroneous transmissions to recover a correct packet. We analytically prove that our approach minimizes the errors in packet recovery. We also experimentally demonstrate its benefits using a testbed of GNU software radios. The results show that our approach can reduce loss rate by up to 10x in comparison with the current approach, and significantly outperforms prior cooperation proposals

Computational regulatory genomics : motifs, networks, and dynamics

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.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 (p. 147-169).Gene regulation, the process responsible for taking a static genome and producing the diversity and complexity of life, is largely mediated through the sequence specific binding of regulators. The short, degenerate nature of the recognized elements and the unknown rules through which they interact makes deciphering gene regulation a significant challenge. In this thesis, we utilize comparative genomics and other approaches to exploit large-scale experimental datasets and better understand the sequence elements and regulators responsible for regulatory programs. In particular, we develop new computational approaches to (1) predict the binding sites of regulators using the genomes of many, closely related species; (2) understand the sequence motifs associated with transcription factors; (3) discover and characterize microRNAs, an important class of regulators; (4) use static predictions for binding sites in conjunction with chromatin modifications to better understand the dynamics of regulation; and (5) systematically validate the predicted motif instances using a massively parallel reporter assay. We find that the predictions made by our algorithms are of high quality and are comparable to those made by leading experimental approaches. Moreover, we find that experimental and computational approaches are often complementary. Regions experimentally identified to be bound by a factor can be species and cell line specific, but they lack the resolution and unbiased nature of our predictions. Experimentally identified miRNAs have unmistakable signs of being processed, but cannot provide the same insights our machine learning framework does. Further emphasizing the importance of integration, combining chromatin mark annotations and gene expression from multiple cell types with our static motif instances allows for increasing our power and making additional biologically relevant insights. We successfully apply the algorithms in this thesis to 29 mammals and 12 flies and expect them to be applicable to other clades of eukaryotic species. Moreover, we find that our performance has not yet plateaued and believe these methods will continue to be relevant as sequencing becomes increasingly commonplace and thousands of genomes become available.by Pouya Kheradpour.Ph.D

Evidence of reduced recombination rate in human regulatory domains

Background Recombination rate is non-uniformly distributed across the human genome. The variation of recombination rate at both fine and large scales cannot be fully explained by DNA sequences alone. Epigenetic factors, particularly DNA methylation, have recently been proposed to influence the variation in recombination rate. Results We study the relationship between recombination rate and gene regulatory domains, defined by a gene and its linked control elements. We define these links using expression quantitative trait loci (eQTLs), methylation quantitative trait loci (meQTLs), chromatin conformation from publicly available datasets (Hi-C and ChIA-PET), and correlated activity links that we infer across cell types. Each link type shows a “recombination rate valley” of significantly reduced recombination rate compared to matched control regions. This recombination rate valley is most pronounced for gene regulatory domains of early embryonic development genes, housekeeping genes, and constitutive regulatory elements, which are known to show increased evolutionary constraint across species. Recombination rate valleys show increased DNA methylation, reduced doublestranded break initiation, and increased repair efficiency, specifically in the lineage leading to the germ line. Moreover, by using only the overlap of functional links and DNA methylation in germ cells, we are able to predict the recombination rate with high accuracy. Conclusions Our results suggest the existence of a recombination rate valley at regulatory domains and provide a potential molecular mechanism to interpret the interplay between genetic and epigenetic variations.National Institutes of Health (U.S.) (Award 1-U01-HG007610-01)National Science Foundation (U.S.) (Award 1254200

A single Hox locus in Drosophila produces functional microRNAs from opposite DNA strands

MicroRNAs (miRNAs) are approximately 22-nucleotide RNAs that are processed from characteristic precursor hairpins and pair to sites in messages of protein-coding genes to direct post-transcriptional repression. Here, we report that the miRNA iab-4 locus in the Drosophila Hox cluster is transcribed convergently from both DNA strands, giving rise to two distinct functional miRNAs. Both sense and antisense miRNA products target neighboring Hox genes via highly conserved sites, leading to homeotic transformations when ectopically expressed. We also report sense/antisense miRNAs in mouse and find antisense transcripts close to many miRNAs in both flies and mammals, suggesting that additional sense/antisense pairs exist

Systematic dissection of regulatory motifs in 2000 predicted human enhancers using a massively parallel reporter assay

Genome-wide chromatin annotations have permitted the mapping of putative regulatory elements across multiple human cell types. However, their experimental dissection by directed regulatory motif disruption has remained unfeasible at the genome scale. Here, we use a massively parallel reporter assay (MPRA) to measure the transcriptional levels induced by 145-bp DNA segments centered on evolutionarily conserved regulatory motif instances within enhancer chromatin states. We select five predicted activators (HNF1, HNF4, FOXA, GATA, NFE2L2) and two predicted repressors (GFI1, ZFP161) and measure reporter expression in erythroleukemia (K562) and liver carcinoma (HepG2) cell lines. We test 2104 wild-type sequences and 3314 engineered enhancer variants containing targeted motif disruptions, each using 10 barcode tags and two replicates. The resulting data strongly confirm the enhancer activity and cell-type specificity of enhancer chromatin states, the ability of 145-bp segments to recapitulate both, the necessary role of regulatory motifs in enhancer function, and the complementary roles of activator and repressor motifs. We find statistically robust evidence that (1) disrupting the predicted activator motifs abolishes enhancer function, while silent or motif-improving changes maintain enhancer activity; (2) evolutionary conservation, nucleosome exclusion, binding of other factors, and strength of the motif match are predictive of enhancer activity; (3) scrambling repressor motifs leads to aberrant reporter expression in cell lines where the enhancers are usually inactive. Our results suggest a general strategy for deciphering cis-regulatory elements by systematic large-scale manipulation and provide quantitative enhancer activity measurements across thousands of constructs that can be mined to develop predictive models of gene expression.National Institutes of Health (U.S.) (Grant HG004037)National Institutes of Health (U.S.) (Grant HG004037-S1

A comprehensive map of insulator elements for the Drosophila genome.

Insulators are DNA sequences that control the interactions among genomic regulatory elements and act as chromatin boundaries. A thorough understanding of their location and function is necessary to address the complexities of metazoan gene regulation. We studied by ChIP-chip the genome-wide binding sites of 6 insulator-associated proteins-dCTCF, CP190, BEAF-32, Su(Hw), Mod(mdg4), and GAF-to obtain the first comprehensive map of insulator elements in Drosophila embryos. We identify over 14,000 putative insulators, including all classically defined insulators. We find two major classes of insulators defined by dCTCF/CP190/BEAF-32 and Su(Hw), respectively. Distributional analyses of insulators revealed that particular sub-classes of insulator elements are excluded between cis-regulatory elements and their target promoters; divide differentially expressed, alternative, and divergent promoters; act as chromatin boundaries; are associated with chromosomal breakpoints among species; and are embedded within active chromatin domains. Together, these results provide a map demarcating the boundaries of gene regulatory units and a framework for understanding insulator function during the development and evolution of Drosophila

A Comprehensive Map of Insulator Elements for the <i>Drosophila</i> Genome

Insulators are DNA sequences that control the interactions among genomic regulatory elements and act as chromatin boundaries. A thorough understanding of their location and function is necessary to address the complexities of metazoan gene regulation. We studied by ChIP–chip the genome-wide binding sites of 6 insulator-associated proteins—dCTCF, CP190, BEAF-32, Su(Hw), Mod(mdg4), and GAF—to obtain the first comprehensive map of insulator elements in Drosophila embryos. We identify over 14,000 putative insulators, including all classically defined insulators. We find two major classes of insulators defined by dCTCF/CP190/BEAF-32 and Su(Hw), respectively. Distributional analyses of insulators revealed that particular sub-classes of insulator elements are excluded between cis-regulatory elements and their target promoters; divide differentially expressed, alternative, and divergent promoters; act as chromatin boundaries; are associated with chromosomal breakpoints among species; and are embedded within active chromatin domains. Together, these results provide a map demarcating the boundaries of gene regulatory units and a framework for understanding insulator function during the development and evolution of Drosophila.</p

Assigning roles to DNA regulatory motifs using comparative genomics

Motivation: Transcription factors (TFs) are crucial during the lifetime of the cell. Their functional roles are defined by the genes they regulate. Uncovering these roles not only sheds light on the TF at hand but puts it into the context of the complete regulatory network

Nonsyndromic cleft palate:An association study at GWAS candidate loci in a multiethnic sample

Background: Nonsyndromic cleft palate only (nsCPO) is a common and multifactorial form of orofacial clefting. In contrast to successes achieved for the other common form of orofacial clefting, that is, nonsyndromic cleft lip with/without cleft palate (nsCL/P), genome wide association studies (GWAS) of nsCPO have identified only one genome wide significant locus. Aim of the present study was to investigate whether common variants contribute to nsCPO and, if so, to identify novel risk loci. Methods: We genotyped 33 SNPs at 27 candidate loci from 2 previously published nsCPO GWAS in an independent multiethnic sample. It included: (i) a family-based sample of European ancestry (n=212); and (ii) two case/control samples of Central European (n=94/339) and Arabian ancestry (n=38/231), respectively. A separate association analysis was performed for each genotyped dataset, and meta-analyses were performed. Results: After association analysis and meta-analyses, none of the 33 SNPs showed genome-wide significance. Two variants showed nominally significant association in the imputed GWAS dataset and exhibited a further decrease in p-value in a European and an overall meta-analysis including imputed GWAS data, respectively (rs395572: PMetaEU=3.16 Ã\u97 10-4; rs6809420: PMetaAll=2.80 Ã\u97 10-4). Conclusion: Our findings suggest that there is a limited contribution of common variants to nsCPO. However, the individual effect sizes might be too small for detection of further associations in the present sample sizes. Rare variants may play a more substantial role in nsCPO than in nsCL/P, for which GWAS of smaller sample sizes have identified genome-wide significant loci. Whole-exome/genome sequencing studies of nsCPO are now warranted

High-throughput chromatin information enables accurate tissue-specific prediction of transcription factor binding sites

In silico prediction of transcription factor binding sites (TFBSs) is central to the task of gene regulatory network elucidation. Genomic DNA sequence information provides a basis for these predictions, due to the sequence specificity of TF-binding events. However, DNA sequence alone is an impoverished source of information for the task of TFBS prediction in eukaryotes, as additional factors, such as chromatin structure regulate binding events. We show that incorporating high-throughput chromatin modification estimates can greatly improve the accuracy of in silico prediction of in vivo binding for a wide range of TFs in human and mouse. This improvement is superior to the improvement gained by equivalent use of either transcription start site proximity or phylogenetic conservation information. Importantly, predictions made with the use of chromatin structure information are tissue specific. This result supports the biological hypothesis that chromatin modulates TF binding to produce tissue-specific binding profiles in higher eukaryotes, and suggests that the use of chromatin modification information can lead to accurate tissue-specific transcriptional regulatory network elucidation