David M Granas

Bio: David M Granas is an academic researcher from Washington University in St. Louis. The author has contributed to research in topics: Gene & Enhancer. The author has an hindex of 5, co-authored 10 publications receiving 378 citations.

Inferring binding energies from selected binding sites.

Abstract: We employ a biophysical model that accounts for the non-linear relationship between binding energy and the statistics of selected binding sites. The model includes the chemical potential of the transcription factor, non-specific binding affinity of the protein for DNA, as well as sequence-specific parameters that may include non-independent contributions of bases to the interaction. We obtain maximum likelihood estimates for all of the parameters and compare the results to standard probabilistic methods of parameter estimation. On simulated data, where the true energy model is known and samples are generated with a variety of parameter values, we show that our method returns much more accurate estimates of the true parameters and much better predictions of the selected binding site distributions. We also introduce a new high-throughput SELEX (HT-SELEX) procedure to determine the binding specificity of a transcription factor in which the initial randomized library and the selected sites are sequenced with next generation methods that return hundreds of thousands of sites. We show that after a single round of selection our method can estimate binding parameters that give very good fits to the selected site distributions, much better than standard motif identification algorithms.

Identification of Cilia Genes That Affect Cell-Cycle Progression Using Whole-Genome Transcriptome Analysis in Chlamydomonas reinhardtti

Abstract: Cilia are microtubule based organelles that project from cells. Cilia are found on almost every cell type of the human body and numerous diseases, collectively termed ciliopathies, are associated with defects in cilia, including respiratory infections, male infertility, situs inversus, polycystic kidney disease, retinal degeneration, and Bardet-Biedl Syndrome. Here we show that Illumina-based whole-genome transcriptome analysis in the biflagellate green alga Chlamydomonas reinhardtii identifies 1850 genes up-regulated during ciliogenesis, 4392 genes down-regulated, and 4548 genes with no change in expression during ciliogenesis. We examined four genes up-regulated and not previously known to be involved with cilia (ZMYND10, NXN, GLOD4, SPATA4) by knockdown of the human orthologs in human retinal pigment epithelial cells (hTERT-RPE1) cells to ask whether they are involved in cilia-related processes that include cilia assembly, cilia length control, basal body/centriole numbers, and the distance between basal bodies/centrioles. All of the genes have cilia-related phenotypes and, surprisingly, our data show that knockdown of GLOD4 and SPATA4 also affects the cell cycle. These results demonstrate that whole-genome transcriptome analysis during ciliogenesis is a powerful tool to gain insight into the molecular mechanism by which centrosomes and cilia are assembled.

Measuring quantitative effects of methylation on transcription factor-DNA binding affinity.

Abstract: Methylation of CpG (cytosine-phosphate-guanine) dinucleotides is a common epigenetic mark that influences gene expression. The effects of methylation on transcription factor (TF) binding are unknown for most TFs and, even when known, such knowledge is often only qualitative. In reality, methylation sensitivity is a quantitative effect, just as changes to the DNA sequence have quantitative effects on TF binding affinity. We describe Methyl-Spec-seq, an easy-to-use method that measures the effects of CpG methylation (mCPG) on binding affinity for hundreds to thousands of variants in parallel, allowing one to quantitatively assess the effects at every position in a binding site. We demonstrate its use on several important DNA binding proteins. We calibrate the accuracy of Methyl-Spec-seq using a novel two-color competitive fluorescence anisotropy method that can accurately determine the relative affinities of two sequences in solution. We also present software that extends standard methods for representing, visualizing, and searching for matches to binding site motifs to include the effects of methylation. These tools facilitate the study of the consequences for gene regulation of epigenetic marks on DNA.

Whole genome sequencing identifies a deletion in protein phosphatase 2A that affects its stability and localization in Chlamydomonas reinhardtii

Abstract: Whole genome sequencing is a powerful tool in the discovery of single nucleotide polymorphisms (SNPs) and small insertions/deletions (indels) among mutant strains, which simplifies forward genetics approaches. However, identification of the causative mutation among a large number of non-causative SNPs in a mutant strain remains a big challenge. In the unicellular biflagellate green alga Chlamydomonas reinhardtii, we generated a SNP/indel library that contains over 2 million polymorphisms from four wild-type strains, one highly polymorphic strain that is frequently used in meiotic mapping, ten mutant strains that have flagellar assembly or motility defects, and one mutant strain, imp3, which has a mating defect. A comparison of polymorphisms in the imp3 strain and the other 15 strains allowed us to identify a deletion of the last three amino acids, Y313F314L315, in a protein phosphatase 2A catalytic subunit (PP2A3) in the imp3 strain. Introduction of a wild-type HA-tagged PP2A3 rescues the mutant phenotype, but mutant HA-PP2A3 at Y313 or L315 fail to rescue. Our immunoprecipitation results indicate that the Y313, L315, or YFLΔ mutations do not affect the binding of PP2A3 to the scaffold subunit, PP2A-2r. In contrast, the Y313, L315, or YFLΔ mutations affect both the stability and the localization of PP2A3. The PP2A3 protein is less abundant in these mutants and fails to accumulate in the basal body area as observed in transformants with either wild-type HA-PP2A3 or a HA-PP2A3 with a V310T change. The accumulation of HA-PP2A3 in the basal body region disappears in mated dikaryons, which suggests that the localization of PP2A3 may be essential to the mating process. Overall, our results demonstrate that the terminal YFL tail of PP2A3 is important in the regulation on Chlamydomonas mating.

Synthetic and genomic regulatory elements reveal aspects of cis-regulatory grammar in mouse embryonic stem cells

Abstract: Transcription factors are proteins that flip genetic switches; their role is to control when and where genes are active. They do this by binding to short stretches of DNA called cis-regulatory sequences. Each sequence can have several binding sites for different transcription factors, but it is largely unclear whether the transcription factors binding to the same regulatory sequence actually work together. It is possible that each transcription factor may work independently and there only needs to be critical mass of transcription factors bound to throw the genetic switch. If this is the case, the most important features of a cis-regulatory sequence should be the number of binding sites it contains, and how tightly the transcription factors bind to those sites. The more transcription factors and the more strongly they bind, the more active the gene should be. An alternative option is that certain transcription factors may work better together, enhancing each other's effects such that the total effect is more than the sum of its parts. If this is true, the order, orientation and spacing of the binding sites within a sequence should matter more than the number. One way to investigate to distinguish between these possibilities is to study mouse embryonic stem cells, which have a core set of four transcription factors. Looking directly at a real genome, however, can be confusing and it is difficult to measure the effects of different cis-regulatory sequences because genes differ in so many other ways. To tackle this problem, King et al. created a synthetic set of cis-regulatory sequences based on the four core transcription factors found in mouse stem cells. The synthetic set had every combination of two, three or four of the binding sites, with each site either facing forwards or backwards along the DNA strand. King et al. attached each of the synthetic cis-regulatory sequences to a reporter gene to find out how well each sequence performed. This revealed that the cis-regulatory sequences with the most binding sites and the tightest binding affinities work best, suggesting that transcription factors mainly work independently. There was evidence of some interaction between some transcription factors, because, of the synthetic sequences with four binding sites, some worked better than others, and there were patterns in the most effective binding site combinations. However, these effects were small and when King et al. went on to test sequences from the real mouse genome, the most important factor by far was the number of binding sites. Synthetic libraries of DNA sequences allow researchers to examine gene regulation more clearly than is possible in real genomes. Yet this approach does have its limitations and it is impossible to capture every type of cis-regulatory sequence in one library. The next step to extend this work is to combine the two approaches, taking sequences from the real genome and manipulating them one by one. This could help to unravel the rules that govern how cis-regulatory sequences work in real cells.

JASPAR 2020: update of the open-access database of transcription factor binding profiles

Abstract: JASPAR (http://jaspar.genereg.net) is an open-access database of curated, non-redundant transcription factor (TF)-binding profiles stored as position frequency matrices (PFMs) for TFs across multiple species in six taxonomic groups. In this 8th release of JASPAR, the CORE collection has been expanded with 245 new PFMs (169 for vertebrates, 42 for plants, 17 for nematodes, 10 for insects, and 7 for fungi), and 156 PFMs were updated (125 for vertebrates, 28 for plants and 3 for insects). These new profiles represent an 18% expansion compared to the previous release. JASPAR 2020 comes with a novel collection of unvalidated TF-binding profiles for which our curators did not find orthogonal supporting evidence in the literature. This collection has a dedicated web form to engage the community in the curation of unvalidated TF-binding profiles. Moreover, we created a Q&A forum to ease the communication between the user community and JASPAR curators. Finally, we updated the genomic tracks, inference tool, and TF-binding profile similarity clusters. All the data is available through the JASPAR website, its associated RESTful API, and through the JASPAR2020 R/Bioconductor package.

Revealing protein–lncRNA interaction

Abstract: Long non-coding RNAs (lncRNAs) are associated to a plethora of cellular functions, most of which require the interaction with one or more RNA-binding proteins (RBPs); similarly, RBPs are often able to bind a large number of different RNAs. The currently available knowledge is already drawing an intricate network of interactions, whose deregulation is frequently associated to pathological states. Several different techniques were developed in the past years to obtain protein–RNA binding data in a high-throughput fashion. In parallel, in silico inference methods were developed for the accurate computational prediction of the interaction of RBP–lncRNA pairs. The field is growing rapidly, and it is foreseeable that in the near future, the protein–lncRNA interaction network will rise, offering essential clues for a better understanding of lncRNA cellular mechanisms and their disease-associated perturbations.