Phylogenetic footprinting reveals multiple regulatory elements involved in control of the meiotic recombination gene, REC102

Evolution of cis-regulatory elements in yeast de novo and duplicated new genes

Background

New genes that originate from non-coding DNA rather than being duplicated from parent genes are called de novo genes. Their short evolution time and lack of parent genes provide a chance to study the evolution of cis-regulatory elements in the initial stage of gene emergence. Although a few reports have discussed cis-regulatory elements in new genes, knowledge of the characteristics of these elements in de novo genes is lacking. Here, we conducted a comprehensive investigation to depict the emergence and establishment of cis-regulatory elements in de novo yeast genes.

Results

In a genome-wide investigation, we found that the number of transcription factor binding sites (TFBSs) in de novo genes of S. cerevisiae increased rapidly and quickly became comparable to the number of TFBSs in established genes. This phenomenon might have resulted from certain characteristics of de novo genes; namely, a relatively frequent gain of TFBSs, an unexpectedly high number of preexisting TFBSs, or lower selection pressure in the promoter regions of the de novo genes. Furthermore, we identified differences in the promoter architecture between de novo genes and duplicated new genes, suggesting that distinct regulatory strategies might be employed by genes of different origin. Finally, our functional analyses of the yeast de novo genes revealed that they might be related to reproduction.

Conclusions

Our observations showed that de novo genes and duplicated new genes possess mutually distinct regulatory characteristics, implying that these two types of genes might have different roles in evolution.

Microevolution of cis-regulatory elements: an example from the pair-rule segmentation gene fushi tarazu in the Drosophila melanogaster subgroup

The importance of non-coding DNAs that control transcription is ever noticeable, but the characterization and analysis of the evolution of such DNAs presents challenges not found in the analysis of coding sequences. In this study of the cis-regulatory elements of the pair rule segmentation gene fushi tarazu (ftz) I report the DNA sequences of ftz's zebra element (promoter) and a region containing the proximal enhancer from a total of 45 fly lines belonging to several populations of the species Drosophila melanogaster, D. simulans, D. sechellia, D. mauritiana, D. yakuba, D. teissieri, D. orena and D. erecta. Both elements evolve at slower rate than ftz synonymous sites, thus reflecting their functional importance. The promoter evolves more slowly than the average for ftz's coding sequence while, on average, the enhancer evolves more rapidly, suggesting more functional constraint and effective purifying selection on the former. Comparative analysis of the number and nature of base substitutions failed to detect significant evidence for positive/adaptive selection in transcription-factor-binding sites. These seem to evolve at similar rates to regions not known to bind transcription factors. Although this result reflects the evolutionary flexibility of the transcription factor binding sites, it also suggests a complex and still not completely understood nature of even the characterized cis-regulatory sequences. The latter seem to contain more functional parts than those currently identified, some of which probably transcription factor binding. This study illustrates ways in which functional assignments of sequences within cis-acting sequences can be used in the search for adaptive evolution, but also highlights difficulties in how such functional assignment and analysis can be carried out.

Interactions between Mei4, Rec114, and other proteins required for meiotic DNA double-strand break formation in Saccharomyces cerevisiae

In most sexually reproducing organisms, meiotic recombination is initiated by DNA double-strand breaks (DSBs) formed by the Spo11 protein. In budding yeast, nine other proteins are also required for DSB formation, but the roles of these proteins and the interactions among them are poorly understood. We report further studies of the behaviors of these proteins. Consistent with other studies, we find that Mei4 and Rec114 bind to chromosomes from leptonema through early pachynema. Both proteins showed only limited colocalization with the meiotic cohesin subunit Rec8, suggesting that Mei4 and Rec114 associated preferentially with chromatin loops. Rec114 localization was independent of other DSB factors, but Mei4 localization was strongly dependent on Rec114 and Mer2. Systematic deletion analysis identified protein regions important for a previously described two-hybrid interaction between Mei4 and Rec114. We also report functional characterization of a previously misannotated 5' coding exon of REC102. Sequences encoded in this exon are essential for DSB formation and for Rec102 interaction with Rec104, Spo11, Rec114, and Mei4. Finally, we also examined genetic requirements for a set of previously described two-hybrid interactions that can be detected only when the reporter strain is induced to enter meiosis. This analysis reveals new functional dependencies for interactions among the DSB proteins. Taken together, these studies support the view that Mei4, Rec114, and Mer2 make up a functional subgroup that is distinct from other subgroups of the DSB proteins: Spo11-Ski8, Rec102-Rec104, and Mre11-Rad50-Xrs2. These studies also suggest that an essential function of Rec102 and Rec104 is to connect Mei4 and Rec114 to Spo11.

Context specific transcription factor prediction

One of the goals of systems biology is the identification of regulatory mechanisms that govern an organism's response to external stimuli. Transcription factors have been hypothesized as a major contributor to an organism's response to various outside stimuli, and a great deal of work has been done to predict the set of transcription factors which regulate a given gene. Most of the current methods seek to identify possible binding sites from genomic sequence. Initial attempts at predicting transcription factors from genomic sequences suffered from the problem of false positives. Making the problem more difficult, it has also been shown that while predicted binding sites might be false positives, they can be shown to bind to their corresponding sequences in vitro. One method for rectifying this is through the use of phylogenetic analysis in which only regions which show high evolutionary conservation are analyzed. However such an approach may be too stringent because of the level of degeneracy shown in transcription factor binding site position weight matrices. Due to the degeneracy, there may be only a few bases that need to be conserved across species. Therefore, while a sequence may not show a high level of evolutionary conservation, these sequences may still show high affinity for the same transcription factor. In predicting transcription factor binding we explore the notion that "Co-expression implies co-regulation" [Allocco et al. BMC Bioinformatics 5:18, 2004]. With multiple genes requiring similar transcription factors binding sites, there exists a basis for eliminating false positives. This method allows for the selection of transcription factors binding sites that are active under a given experimental paradigm, thereby allowing us to indirectly incorporate the effects of chromosome and recognition site presentation upon transcription factor binding prediction. Rather than having to rationalize that a few transcription factors binding sites are over-represented in a cluster of genes, one can show that a few transcription factors are active in the cluster of genes that have been grouped together. Although the method focuses on predicting experiment-specific transcription factor binding sites, it is possible that if such a methodology were used in an iterative process where different experiments were analyzed, one could obtain a comprehensive set of transcription factors binding sites which regulate the various dynamic responses shown by biological systems under a variety of conditions hence building a more comprehensive model of transcriptional regulation.

Methods in comparative genomics: genome correspondence, gene identification and regulatory motif discovery

In Kellis et al. (2003), we reported the genome sequences of S. paradoxus, S. mikatae, and S. bayanus and compared these three yeast species to their close relative, S. cerevisiae. Genomewide comparative analysis allowed the identification of functionally important sequences, both coding and noncoding. In this companion paper we describe the mathematical and algorithmic results underpinning the analysis of these genomes. (1) We present methods for the automatic determination of genome correspondence. The algorithms enabled the automatic identification of orthologs for more than 90% of genes and intergenic regions across the four species despite the large number of duplicated genes in the yeast genome. The remaining ambiguities in the gene correspondence revealed recent gene family expansions in regions of rapid genomic change. (2) We present methods for the identification of protein-coding genes based on their patterns of nucleotide conservation across related species. We observed the pressure to conserve the reading frame of functional proteins and developed a test for gene identification with high sensitivity and specificity. We used this test to revisit the genome of S. cerevisiae, reducing the overall gene count by 500 genes (10% of previously annotated genes) and refining the gene structure of hundreds of genes. (3) We present novel methods for the systematic de novo identification of regulatory motifs. The methods do not rely on previous knowledge of gene function and in that way differ from the current literature on computational motif discovery. Based on genomewide conservation patterns of known motifs, we developed three conservation criteria that we used to discover novel motifs. We used an enumeration approach to select strongly conserved motif cores, which we extended and collapsed into a small number of candidate regulatory motifs. These include most previously known regulatory motifs as well as several noteworthy novel motifs. The majority of discovered motifs are enriched in functionally related genes, allowing us to infer a candidate function for novel motifs. Our results demonstrate the power of comparative genomics to further our understanding of any species. Our methods are validated by the extensive experimental knowledge in yeast and will be invaluable in the study of complex genomes like that of the human.

Support for a meiotic recombination initiation complex: interactions among Rec102p, Rec104p, and Spo11p

Initiation of meiotic recombination in the yeast Saccharomyces cerevisiae requires at least 10 gene products. The initiation event creates double-strand breaks, which are then processed by other recombination enzymes. A variety of classical observations, such as the existence of recombination nodules, have suggested that the proteins catalyzing recombination form a complex. A variety of lines of evidence indicate that Rad50p, Mre11p, and Xrs2p interact, and genetic data suggesting interactions between Rec102p and Rec104p have been reported. It has recently been shown that Spo11p coimmunoprecipitates with Rec102p in meiosis as well. In this paper, we provide genetic and biochemical evidence that the meiosis-specific proteins Rec102p, Rec104p, and Spo11p all interact with each other in meiosis. Furthermore, we demonstrate that the interaction between Rec102p and Spo11p does not require Rec104p. Likewise, the interaction between Rec104p and Rec102p does not require Spo11p, although Spo11p may stabilize that association. The interactions suggest that Spo11p, Rec102p, and Rec104p may form a trimeric complex during the initiation of recombination.

Signal pathway integration in the switch from the mitotic cell cycle to meiosis in yeast

Diploid yeast, like most eukaryotes, can undergo meiotic differentiation to form haploid gametes. Meiotic differentiation and cell growth (proliferation) are mutually exclusive programs, and in yeast the switch between growth and meiosis is controlled by nutritional signals. The signaling pathways that mediate nutritional controls on meiotic initiation fall into three broad classes: those that respond to nutrient starvation, those that respond to non-fermentable carbon sources, and those that respond to glucose. At the onset of meiosis, nutritional signaling pathways converge on transcriptional regulation of two genes: IME1, which encodes a transcription factor; and IME2, which encodes a protein kinase. Transcription of IME1 and IME2 trigger initiation of meiosis, and the expression of these two genes is linked with one other, with expression of later meiotic genes and with early meiotic events such as DNA replication. In addition, the signaling pathways that control IME1 and IME2 expression are themselves integrated through a variety of mechanisms. Thus the signal network that controls the switch from growth to meiotic differentiation provides a signaling code that translates different combinations of extracellular signals into appropriate cellular responses.