Histone modification pattern evolution after yeast gene duplication

<p>Abstract</p> <p>Background</p> <p>Gene duplication and subsequent functional divergence especially expression divergence have been widely considered as main sources for evolutionary innovations. Many studies evidenced that genetic regulatory network evolved rapidly shortly after gene duplication, thus leading to accelerated expression divergence and diversification. However, little is known whether epigenetic factors have mediated the evolution of expression regulation since gene duplication. In this study, we conducted detailed analyses on yeast histone modification (HM), the major epigenetics type in this organism, as well as other available functional genomics data to address this issue.</p> <p>Results</p> <p>Duplicate genes, on average, share more common HM-code patterns than random singleton pairs in their promoters and open reading frames (ORF). Though HM-code divergence between duplicates in both promoter and ORF regions increase with their sequence divergence, the HM-code in ORF region evolves slower than that in promoter region, probably owing to the functional constraints imposed on protein sequences. After excluding the confounding effect of sequence divergence (or evolutionary time), we found the evidence supporting the notion that in yeast, the HM-code may co-evolve with <it>cis</it>- and <it>trans</it>-regulatory factors. Moreover, we observed that deletion of some yeast HM-related enzymes increases the expression divergence between duplicate genes, yet the effect is lower than the case of transcription factor (TF) deletion or environmental stresses.</p> <p>Conclusions</p> <p>Our analyses demonstrate that after gene duplication, yeast histone modification profile between duplicates diverged with evolutionary time, similar to genetic regulatory elements. Moreover, we found the evidence of the co-evolution between genetic and epigenetic elements since gene duplication, together contributing to the expression divergence between duplicate genes.</p

Paralog-divergent Features May Help Reduce Off-target Effects of Drugs: Hints from Glucagon Subfamily Analysis

Side effects from targeted drugs remain a serious concern. One reason is the nonselective binding of a drug to unintended proteins such as its paralogs, which are highly homologous in sequences and have similar structures and drug-binding pockets. To identify targetable differences between paralogs, we analyzed two types (type-I and type-II) of functional divergence between two paralogs in the known target protein receptor family G-protein coupled receptors (GPCRs) at the amino acid level. Paralogous protein receptors in glucagon-like subfamily, glucagon receptor (GCGR) and glucagon-like peptide-1 receptor (GLP-1R), exhibit divergence in ligands and are clinically validated drug targets for type 2 diabetes. Our data showed that type-II amino acids were significantly enriched in the binding sites of antagonist MK-0893 to GCGR, which had a radical shift in physicochemical properties between GCGR and GLP-1R. We also examined the role of type-I amino acids between GCGR and GLP-1R. The divergent features between GCGR and GLP-1R paralogs may be helpful in their discrimination, thus enabling the identification of binding sites to reduce undesirable side effects and increase the target specificity of drugs

Genepleio Software for Effective Estimation of Gene Pleiotropy from Protein Sequences

Though pleiotropy, which refers to the phenomenon of a gene affecting multiple traits, has long played a central role in genetics, development, and evolution, estimation of the number of pleiotropy components remains a hard mission to accomplish. In this paper, we report a newly developed software package, Genepleio, to estimate the effective gene pleiotropy from phylogenetic analysis of protein sequences. Since this estimate can be interpreted as the minimum pleiotropy of a gene, it is used to play a role of reference for many empirical pleiotropy measures. This work would facilitate our understanding of how gene pleiotropy affects the pattern of genotype-phenotype map and the consequence of organismal evolution

The Evolutionary Panorama of Organ-Specifically Expressed or Repressed Orthologous Genes in Nine Vertebrate Species

<div><p>RNA sequencing (RNA-Seq) technology provides the detailed transcriptomic information for a biological sample. Using the RNA-Seq data of six organs from nine vertebrate species, we identified a number of organ-specifically expressed or repressed orthologous genes whose expression patterns are mostly conserved across nine species. Our analyses show the following results: (i) About 80% of these genes have a chordate or more ancient origin and more than half of them are the legacy of one or multiple rounds of large-scale gene duplication events. (ii) Their evolutionary rates are shaped by the organ in which they are expressed or repressed, e.g. the genes specially expressed in testis and liver generally evolve more than twice as fast as the ones specially expressed in brain and cerebellum. The organ-specific transcription factors were discriminated from these genes. The ChIP-seq data from the ENCODE project also revealed the transcription-related factors that might be involved in regulating human organ-specifically expressed or repressed genes. Some of them are shared by all six human organs. The comparison of ENCODE data with mouse/chicken ChIP-seq data proposes that organ-specifically expressed or repressed orthologous genes are regulated in various combinatorial fashions in different species, although their expression features are conserved among these species. We found that the duplication events in some gene families might help explain the quick organ/tissue divergence in vertebrate lineage. The phylogenetic analysis of testis-specifically expressed genes suggests that some of them are prone to develop new functions for other organs/tissues.</p></div

The number of specifically expressed or repressed (OSER) orthologous clusters in each organ/tissue.

<p>*The OSER clusters in nervous tissue show no significant expression difference between brain and cerebellum while have a distinct expression pattern between nervous tissues and the other organs.</p><p>The number of specifically expressed or repressed (OSER) orthologous clusters in each organ/tissue.</p

Comparison of the evolutionary rate of specifically expressed and repressed clusters in seven organs/tissues.

<p>The total phylogenetic tree branch length of each one-to-one OSER cluster was used to represent its evolutionary rate.</p

Organ-specifically expressed or repressed transcriptional factors.

<p>Organ-specifically expressed or repressed transcriptional factors.</p

Phylogenetic tree of MACC1 gene family.

<p>A <i>Ciona intestinalis</i> gene was selected as the outgroup to root the tree and only the cladogram is shown. The tree node where a possible large-scale duplication event happened is marked with a filled black square ■. 7 means the gene’s expression level is higher than 95% of all genes expressed in the organ. 6 is between 95% and 85%. 5 is between 85% and 65%. 4 is between 65% and 35%. 3 is between 35% and 15%. 2 is between 15% and 5%. 1 is lower than 5%. 0 means no expression at all. N is not available.</p

The evolutionary origins of OSER clusters in each organ/tissue.

<p>The evolutionary origins of OSER clusters in each organ/tissue.</p