Matthew T. Weirauch

The Genetic Landscape of a Cell

Making Connections Genetic interaction profiles highlight cross-connections between bioprocesses, providing a global view of cellular pleiotropy, and enable the prediction of genetic network hubs. Costanzo et al. (p. 425) performed a pairwise fitness screen covering approximately one-third of all potential genetic interactions in yeast, examining 5.4 million gene-gene pairs and generating quantitative profiles for ∼75% of the genome. Of the pairwise interactions tested, about 3% of the genes investigated interact under the conditions tested. On the basis of these data, a reference map for the yeast genetic network was created. A genome-wide interaction map of yeast identifies genetic interactions, networks, and function. A genome-scale genetic interaction map was constructed by examining 5.4 million gene-gene pairs for synthetic genetic interactions, generating quantitative genetic interaction profiles for ~75% of all genes in the budding yeast, Saccharomyces cerevisiae. A network based on genetic interaction profiles reveals a functional map of the cell in which genes of similar biological processes cluster together in coherent subsets, and highly correlated profiles delineate specific pathways to define gene function. The global network identifies functional cross-connections between all bioprocesses, mapping a cellular wiring diagram of pleiotropy. Genetic interaction degree correlated with a number of different gene attributes, which may be informative about genetic network hubs in other organisms. We also demonstrate that extensive and unbiased mapping of the genetic landscape provides a key for interpretation of chemical-genetic interactions and drug target identification.

A compendium of RNA-binding motifs for decoding gene regulation

RNA-binding proteins are key regulators of gene expression, yet only a small fraction have been functionally characterized. Here we report a systematic analysis of the RNA motifs recognized by RNA-binding proteins, encompassing 205 distinct genes from 24 diverse eukaryotes. The sequence specificities of RNA-binding proteins display deep evolutionary conservation, and the recognition preferences for a large fraction of metazoan RNA-binding proteins can thus be inferred from their RNA-binding domain sequence. The motifs that we identify in vitro correlate well with in vivo RNA-binding data. Moreover, we can associate them with distinct functional roles in diverse types of post-transcriptional regulation, enabling new insights into the functions of RNA-binding proteins both in normal physiology and in human disease. These data provide an unprecedented overview of RNA-binding proteins and their targets, and constitute an invaluable resource for determining post-transcriptional regulatory mechanisms in eukaryotes.

Evaluation of methods for modeling transcription factor sequence specificity

Genomic analyses often involve scanning for potential transcription factor (TF) binding sites using models of the sequence specificity of DNA binding proteins. Many approaches have been developed to model and learn a proteins DNA-binding specificity, but these methods have not been systematically compared. Here we applied 26 such approaches to in vitro protein binding microarray data for 66 mouse TFs belonging to various families. For nine TFs, we also scored the resulting motif models on in vivo data, and found that the best in vitro–derived motifs performed similarly to motifs derived from the in vivo data. Our results indicate that simple models based on mononucleotide position weight matrices trained by the best methods perform similarly to more complex models for most TFs examined, but fall short in specific cases (<10% of the TFs examined here). In addition, the best-performing motifs typically have relatively low information content, consistent with widespread degeneracy in eukaryotic TF sequence preferences.

Temporal transcriptional response to ethylene gas drives growth hormone cross-regulation in Arabidopsis

The gaseous plant hormone ethylene regulates a multitude of growth and developmental processes. How the numerous growth control pathways are coordinated by the ethylene transcriptional response remains elusive. We characterized the dynamic ethylene transcriptional response by identifying targets of the master regulator of the ethylene signaling pathway, ETHYLENE INSENSITIVE3 (EIN3), using chromatin immunoprecipitation sequencing and transcript sequencing during a timecourse of ethylene treatment. Ethylene-induced transcription occurs in temporal waves regulated by EIN3, suggesting distinct layers of transcriptional control. EIN3 binding was found to modulate a multitude of downstream transcriptional cascades, including a major feedback regulatory circuitry of the ethylene signaling pathway, as well as integrating numerous connections between most of the hormone mediated growth response pathways. These findings provide direct evidence linking each of the major plant growth and development networks in novel ways. DOI: http://dx.doi.org/10.7554/eLife.00675.001

Genome-wide association analysis of eosinophilic esophagitis provides insight into the tissue specificity of this allergic disease

Eosinophilic esophagitis (EoE) is a chronic inflammatory disorder associated with allergic hypersensitivity to food. We interrogated >1.5 million genetic variants in EoE cases of European ancestry and subsequently in a multi-site cohort with local and out-of-study control subjects. In addition to replicating association of the 5q22 locus (meta-analysis P = 1.9 × 10−16), we identified an association at 2p23 spanning CAPN14 (P = 2.5 × 10−10). CAPN14 was specifically expressed in the esophagus, was dynamically upregulated as a function of disease activity and genetic haplotype and after exposure of epithelial cells to interleukin (IL)-13, and was located in an epigenetic hotspot modified by IL-13. Genes neighboring the top 208 EoE-associated sequence variants were enriched for esophageal expression, and multiple loci for allergic sensitization were associated with EoE susceptibility (4.8 × 10−2 < P < 5.1 × 10−11). We propose a model to explain the tissue-specific nature of EoE that involves the interplay of allergic sensitization with an EoE-specific, IL-13–inducible esophageal response involving CAPN14.

Structural basis for recognition of AT-rich DNA by unrelated xenogeneic silencing proteins.

H-NS and Lsr2 are nucleoid-associated proteins from Gram-negative bacteria and Mycobacteria, respectively, that play an important role in the silencing of horizontally acquired foreign DNA that is more AT-rich than the resident genome. Despite the fact that Lsr2 and H-NS proteins are dissimilar in sequence and structure, they serve apparently similar functions and can functionally complement one another. The mechanism by which these xenogeneic silencers selectively target AT-rich DNA has been enigmatic. We performed high-resolution protein binding microarray analysis to simultaneously assess the binding preference of H-NS and Lsr2 for all possible 8-base sequences. Concurrently, we performed a detailed structure-function relationship analysis of their C-terminal DNA binding domains by NMR. Unexpectedly, we found that H-NS and Lsr2 use a common DNA binding mechanism where a short loop containing a “Q/RGR” motif selectively interacts with the DNA minor groove, where the highest affinity is for AT-rich sequences that lack A-tracts. Mutations of the Q/RGR motif abolished DNA binding activity. Netropsin, a DNA minor groove-binding molecule effectively outcompeted H-NS and Lsr2 for binding to AT-rich sequences. These results provide a unified molecular mechanism to explain findings related to xenogeneic silencing proteins, including their lack of apparent sequence specificity but preference for AT-rich sequences. Our findings also suggest that structural information contained within the DNA minor groove is deciphered by xenogeneic silencing proteins to distinguish genetic material that is self from nonself.

Mapping and dynamics of regulatory DNA and transcription factor networks in A. thaliana.

Our understanding of gene regulation in plants is constrained by our limited knowledge of plant cis-regulatory DNA and its dynamics. We mapped DNase I hypersensitive sites (DHSs) in A. thaliana seedlings and used genomic footprinting to delineate ∼ 700,000 sites of in vivo transcription factor (TF) occupancy at nucleotide resolution. We show that variation associated with 72 diverse quantitative phenotypes localizes within DHSs. TF footprints encode an extensive cis-regulatory lexicon subject to recent evolutionary pressures, and widespread TF binding within exons may have shaped codon usage patterns. The architecture of A. thaliana TF regulatory networks is strikingly similar to that of animals in spite of diverged regulatory repertoires. We analyzed regulatory landscape dynamics during heat shock and photomorphogenesis, disclosing thousands of environmentally sensitive elements and enabling mapping of key TF regulatory circuits underlying these fundamental responses. Our results provide an extensive resource for the study of A. thaliana gene regulation and functional biology.

C2H2 zinc finger proteins greatly expand the human regulatory lexicon

Cys2-His2 zinc finger (C2H2-ZF) proteins represent the largest class of putative human transcription factors. However, for most C2H2-ZF proteins it is unknown whether they even bind DNA or, if they do, to which sequences. Here, by combining data from a modified bacterial one-hybrid system with protein-binding microarray and chromatin immunoprecipitation analyses, we show that natural C2H2-ZFs encoded in the human genome bind DNA both in vitro and in vivo, and we infer the DNA recognition code using DNA-binding data for thousands of natural C2H2-ZF domains. In vivo binding data are generally consistent with our recognition code and indicate that C2H2-ZF proteins recognize more motifs than all other human transcription factors combined. We provide direct evidence that most KRAB-containing C2H2-ZF proteins bind specific endogenous retroelements (EREs), ranging from currently active to ancient families. The majority of C2H2-ZF proteins, including KRAB proteins, also show widespread binding to regulatory regions, indicating that the human genome contains an extensive and largely unstudied adaptive C2H2-ZF regulatory network that targets a diverse range of genes and pathways.

A Catalogue of Eukaryotic Transcription Factor Types, Their Evolutionary Origin, and Species Distribution

Transcription factors (TFs) play key roles in the regulation of gene expression by binding in a sequence-specific manner to genomic DNA. In eukaryotes, DNA binding is achieved by a wide range of structural forms and motifs. TFs are typically classified by their DNA-binding domain (DBD) type. In this chapter, we catalogue and survey 91 different TF DBD types in metazoa, plants, fungi, and protists. We briefly discuss well-characterized TF families representing the major DBD superclasses. We also examine the species distributions and inferred evolutionary histories of the various families, and the potential roles played by TF family expansion and dimerization.

Multi-species, multi-transcription factor binding highlights conserved control of tissue-specific biological pathways

As exome sequencing gives way to genome sequencing, the need to interpret the function of regulatory DNA becomes increasingly important. To test whether evolutionary conservation of cis-regulatory modules (CRMs) gives insight into human gene regulation, we determined transcription factor (TF) binding locations of four liver-essential TFs in liver tissue from human, macaque, mouse, rat, and dog. Approximately, two thirds of the TF-bound regions fell into CRMs. Less than half of the human CRMs were found as a CRM in the orthologous region of a second species. Shared CRMs were associated with liver pathways and disease loci identified by genome-wide association studies. Recurrent rare human disease causing mutations at the promoters of several blood coagulation and lipid metabolism genes were also identified within CRMs shared in multiple species. This suggests that multi-species analyses of experimentally determined combinatorial TF binding will help identify genomic regions critical for tissue-specific gene control. DOI: http://dx.doi.org/10.7554/eLife.02626.001