Biomedical subjects

Kimmo Palin

Publications and source records attributed to Kimmo Palin.

4 recordsLinked to original sources

PubMed2026

Oriented binding of transcription factors to nucleosomes remodels chromatin at human promoters.

Transcription factors (TFs) can access nucleosomes via five distinct modes: gyre-spanning, periodic-binding, dyad-binding, and end-binding modes as well as an oriented binding mode, where the TF binding motif shows orientational preference relative to the nucleosome. Here, we report the first structure of an oriented TF:nucleosome complex, where two ELF2 proteins bind to a double motif located at superhelical location +4, unwinding four helical turns of DNA from the nucleosome. We further show that unlike previously described pioneer factors, ELF2 is able to occupy all of its unmethylated, high-affinity double motifs in vivo. Motifs of ELF2 and another oriented nucleosome binder, YY1, are highly enriched downstream of transcription start sites (TSSs) of highly expressed genes, with the motifs oriented in such a way that the TSS becomes accessible upon TF binding. Our results suggest that oriented binding may be generally important for high transcriptional activity.

Nucleosomes↗

PubMed2006

Genome-wide prediction of mammalian enhancers based on analysis of transcription-factor binding affinity.

Understanding the regulation of human gene expression requires knowledge of the "second genetic code," which consists of the binding specificities of transcription factors (TFs) and the combinatorial code by which TF binding sites are assembled to form tissue-specific enhancer elements. Using a novel high-throughput method, we determined the DNA binding specificities of GLIs 1-3, Tcf4, and c-Ets1, which mediate transcriptional responses to the Hedgehog (Hh), Wnt, and Ras/MAPK signaling pathways. To identify mammalian enhancer elements regulated by these pathways on a genomic scale, we developed a computational tool, enhancer element locator (EEL). We show that EEL can be used to identify Hh and Wnt target genes and to predict activated TFs based on changes in gene expression. Predictions validated in transgenic mouse embryos revealed the presence of multiple tissue-specific enhancers in mouse c-Myc and N-Myc genes, which has implications for organ-specific growth control and tumor-type specificity of oncogenes.

Amino Acid Sequence↗

PubMed2003

From gene networks to gene function.

We propose a novel method to identify functionally related genes based on comparisons of neighborhoods in gene networks. This method does not rely on gene sequence or protein structure homologies, and it can be applied to any organism and a wide variety of experimental data sets. The character of the predicted gene relationships depends on the underlying networks;they concern biological processes rather than the molecular function. We used the method to analyze gene networks derived from genome-wide chromatin immunoprecipitation experiments, a large-scale gene deletion study, and from the genomic positions of consensus binding sites for transcription factors of the yeast Saccharomyces cerevisiae. We identified 816 functional relationships between 159 genes and show that these relationships correspond to protein-protein interactions, co-occurrence in the same protein complexes, and/or co-occurrence in abstracts of scientific articles. Our results suggest functions for seven previously uncharacterized yeast genes: KIN3 and YMR269W may be involved in biological processes related to cell growth and/or maintenance, whereas IES6, YEL008W, YEL033W, YHL029C, YMR010W, and YMR031W-A are likely to have metabolic functions.

Computational Biology↗

PubMed2002

Correlating gene promoters and expression in gene disruption experiments.

MOTIVATION: Finding putative transcription factor binding sites in the upstream sequences of similarly expressed genes has recently become a subject of intensive studies. In this paper we investigate how much gene expression regulation can be attributed to the presence of various binding sites in the gene promoters by correlating the binding sites and the changes in gene expression resulting from gene disruptions (e.g. knockouts). RESULTS: We have developed a data analysis method for comparing mRNA measurements of gene disruption experiments with information about gene promoters. The method was applied to a well-known dataset to uncover correlations between known transcription factor binding site motifs in the upstream regions of all S. cerevisiae genes and the gene expression changes in various gene disruption experiments. The possible explanations of the correlations were categorized and analyzed using e.g. expression cascades. Several correlations turned out to be consistent with existing biological knowledge while some new ones suggest themselves for further study. AVAILABILITY: The resulting tables are available at http://www.cs.helsinki.fi/u/kpalin/CorrDisrupt/.

Algorithms↗