Arend Sidow

Architecture of the human regulatory network derived from ENCODE data

Transcription factors bind in a combinatorial fashion to specify the on-and-off states of genes; the ensemble of these binding events forms a regulatory network, constituting the wiring diagram for a cell. To examine the principles of the human transcriptional regulatory network, we determined the genomic binding information of 119 transcription-related factors in over 450 distinct experiments. We found the combinatorial, co-association of transcription factors to be highly context specific: distinct combinations of factors bind at specific genomic locations. In particular, there are significant differences in the binding proximal and distal to genes. We organized all the transcription factor binding into a hierarchy and integrated it with other genomic information (for example, microRNA regulation), forming a dense meta-network. Factors at different levels have different properties; for instance, top-level transcription factors more strongly influence expression and middle-level ones co-regulate targets to mitigate information-flow bottlenecks. Moreover, these co-regulations give rise to many enriched network motifs (for example, noise-buffering feed-forward loops). Finally, more connected network components are under stronger selection and exhibit a greater degree of allele-specific activity (that is, differential binding to the two parental alleles). The regulatory information obtained in this study will be crucial for interpreting personal genome sequences and understanding basic principles of human biology and disease.

ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia

Chromatin immunoprecipitation (ChIP) followed by high-throughput DNA sequencing (ChIP-seq) has become a valuable and widely used approach for mapping the genomic location of transcription-factor binding and histone modifications in living cells. Despite its widespread use, there are considerable differences in how these experiments are conducted, how the results are scored and evaluated for quality, and how the data and metadata are archived for public use. These practices affect the quality and utility of any global ChIP experiment. Through our experience in performing ChIP-seq experiments, the ENCODE and modENCODE consortia have developed a set of working standards and guidelines for ChIP experiments that are updated routinely. The current guidelines address antibody validation, experimental replication, sequencing depth, data and metadata reporting, and data quality assessment. We discuss how ChIP quality, assessed in these ways, affects different uses of ChIP-seq data. All data sets used in the analysis have been deposited for public viewing and downloading at the ENCODE (http://encodeproject.org/ENCODE/) and modENCODE (http://www.modencode.org/) portals.

Identifying a High Fraction of the Human Genome to be under Selective Constraint Using GERP

Computational efforts to identify functional elements within genomes leverage comparative sequence information by looking for regions that exhibit evidence of selective constraint. One way of detecting constrained elements is to follow a bottom-up approach by computing constraint scores for individual positions of a multiple alignment and then defining constrained elements as segments of contiguous, highly scoring nucleotide positions. Here we present GERP++, a new tool that uses maximum likelihood evolutionary rate estimation for position-specific scoring and, in contrast to previous bottom-up methods, a novel dynamic programming approach to subsequently define constrained elements. GERP++ evaluates a richer set of candidate element breakpoints and ranks them based on statistical significance, eliminating the need for biased heuristic extension techniques. Using GERP++ we identify over 1.3 million constrained elements spanning over 7% of the human genome. We predict a higher fraction than earlier estimates largely due to the annotation of longer constrained elements, which improves one to one correspondence between predicted elements with known functional sequences. GERP++ is an efficient and effective tool to provide both nucleotide- and element-level constraint scores within deep multiple sequence alignments.

Genome-Wide Analysis of Transcription Factor Binding Sites Based on ChIP-Seq Data

Molecular interactions between protein complexes and DNA mediate essential gene-regulatory functions. Uncovering such interactions by chromatin immunoprecipitation coupled with massively parallel sequencing (ChIP-Seq) has recently become the focus of intense interest. We here introduce quantitative enrichment of sequence tags (QuEST), a powerful statistical framework based on the kernel density estimation approach, which uses ChIP-Seq data to determine positions where protein complexes contact DNA. Using QuEST, we discovered several thousand binding sites for the human transcription factors SRF, GABP and NRSF at an average resolution of about 20 base pairs. MEME motif-discovery tool–based analyses of the QuEST-identified sequences revealed DNA binding by cofactors of SRF, providing evidence that cofactor binding specificity can be obtained from ChIP-Seq data. By combining QuEST analyses with Gene Ontology (GO) annotations and expression data, we illustrate how general functions of transcription factors can be inferred.

A high-resolution, nucleosome position map of C. elegans reveals a lack of universal sequence-dictated positioning

Using the massively parallel technique of sequencing by oligonucleotide ligation and detection (SOLiD; Applied Biosystems), we have assessed the in vivo positions of more than 44 million putative nucleosome cores in the multicellular genetic model organism Caenorhabditis elegans. These analyses provide a global view of the chromatin architecture of a multicellular animal at extremely high density and resolution. While we observe some degree of reproducible positioning throughout the genome in our mixed stage population of animals, we note that the major chromatin feature in the worm is a diversity of allowed nucleosome positions at the vast majority of individual loci. While absolute positioning of nucleosomes can vary substantially, relative positioning of nucleosomes (in a repeated array structure likely to be maintained at least in part by steric constraints) appears to be a significant property of chromatin structure. The high density of nucleosomal reads enabled a substantial extension of previous analysis describing the usage of individual oligonucleotide sequences along the span of the nucleosome core and linker. We release this data set, via the UCSC Genome Browser, as a resource for the high-resolution analysis of chromatin conformation and DNA accessibility at individual loci within the C. elegans genome.

SHRiMP: Accurate Mapping of Short Color-space Reads

The development of Next Generation Sequencing technologies, capable of sequencing hundreds of millions of short reads (25–70 bp each) in a single run, is opening the door to population genomic studies of non-model species. In this paper we present SHRiMP - the SHort Read Mapping Package: a set of algorithms and methods to map short reads to a genome, even in the presence of a large amount of polymorphism. Our method is based upon a fast read mapping technique, separate thorough alignment methods for regular letter-space as well as AB SOLiD (color-space) reads, and a statistical model for false positive hits. We use SHRiMP to map reads from a newly sequenced Ciona savignyi individual to the reference genome. We demonstrate that SHRiMP can accurately map reads to this highly polymorphic genome, while confirming high heterozygosity of C. savignyi in this second individual. SHRiMP is freely available at http://compbio.cs.toronto.edu/shrimp.

Determinants of nucleosome organization in primary human cells

Nucleosomes are the basic packaging units of chromatin, modulating accessibility of regulatory proteins to DNA and thus influencing eukaryotic gene regulation. Elaborate chromatin remodelling mechanisms have evolved that govern nucleosome organization at promoters, regulatory elements, and other functional regions in the genome. Analyses of chromatin landscape have uncovered a variety of mechanisms, including DNA sequence preferences, that can influence nucleosome positions. To identify major determinants of nucleosome organization in the human genome, we used deep sequencing to map nucleosome positions in three primary human cell types and in vitro. A majority of the genome showed substantial flexibility of nucleosome positions, whereas a small fraction showed reproducibly positioned nucleosomes. Certain sites that position in vitro can anchor the formation of nucleosomal arrays that have cell type-specific spacing in vivo. Our results unveil an interplay of sequence-based nucleosome preferences and non-nucleosomal factors in determining nucleosome organization within mammalian cells.

Global genomic profiling reveals an extensive p53-regulated autophagy program contributing to key p53 responses

The mechanisms by which the p53 tumor suppressor acts remain incompletely understood. To gain new insights into p53 biology, we used high-throughput sequencing to analyze global p53 transcriptional networks in primary mouse embryo fibroblasts in response to DNA damage. Chromatin immunoprecipitation sequencing reveals 4785 p53-bound sites in the genome located near 3193 genes involved in diverse biological processes. RNA sequencing analysis shows that only a subset of p53-bound genes is transcriptionally regulated, yielding a list of 432 p53-bound and regulated genes. Interestingly, we identify a host of autophagy genes as direct p53 target genes. While the autophagy program is regulated predominantly by p53, the p53 family members p63 and p73 contribute to activation of this autophagy gene network. Induction of autophagy genes in response to p53 activation is associated with enhanced autophagy in diverse settings and depends on p53 transcriptional activity. While p53-induced autophagy does not affect cell cycle arrest in response to DNA damage, it is important for both robust p53-dependent apoptosis triggered by DNA damage and transformation suppression by p53. Together, our data highlight an intimate connection between p53 and autophagy through a vast transcriptional network and indicate that autophagy contributes to p53-dependent apoptosis and cancer suppression.

The integrity of a cholesterol-binding pocket in Niemann-Pick C2 protein is necessary to control lysosome cholesterol levels

The neurodegenerative disease Niemann–Pick Type C2 (NPC2) results from mutations in the NPC2 (HE1) gene that cause abnormally high cholesterol accumulation in cells. We find that purified NPC2, a secreted soluble protein, binds cholesterol specifically with a much higher affinity (Kd = 30–50 nM) than previously reported. Genetic and biochemical studies identified single amino acid changes that prevent both cholesterol binding and the restoration of normal cholesterol levels in mutant cells. The amino acids that affect cholesterol binding surround a hydrophobic pocket in the NPC2 protein structure, identifying a candidate sterol-binding location. On the basis of evolutionary analysis and mutagenesis, three other regions of the NPC2 protein emerged as important, including one required for efficient secretion.

The origin, evolution, and functional impact of short insertion–deletion variants identified in 179 human genomes

Short insertions and deletions (indels) are the second most abundant form of human genetic variation, but our understanding of their origins and functional effects lags behind that of other types of variants. Using population-scale sequencing, we have identified a high-quality set of 1.6 million indels from 179 individuals representing three diverse human populations. We show that rates of indel mutagenesis are highly heterogeneous, with 43%-48% of indels occurring in 4.03% of the genome, whereas in the remaining 96% their prevalence is 16 times lower than SNPs. Polymerase slippage can explain upwards of three-fourths of all indels, with the remainder being mostly simple deletions in complex sequence. However, insertions do occur and are significantly associated with pseudo-palindromic sequence features compatible with the fork stalling and template switching (FoSTeS) mechanism more commonly associated with large structural variations. We introduce a quantitative model of polymerase slippage, which enables us to identify indel-hypermutagenic protein-coding genes, some of which are associated with recurrent mutations leading to disease. Accounting for mutational rate heterogeneity due to sequence context, we find that indels across functional sequence are generally subject to stronger purifying selection than SNPs. We find that indel length modulates selection strength, and that indels affecting multiple functionally constrained nucleotides undergo stronger purifying selection. We further find that indels are enriched in associations with gene expression and find evidence for a contribution of nonsense-mediated decay. Finally, we show that indels can be integrated in existing genome-wide association studies (GWAS); although we do not find direct evidence that potentially causal protein-coding indels are enriched with associations to known disease-associated SNPs, our findings suggest that the causal variant underlying some of these associations may be indels.