Conserved sequences are one kind of genomic sequences shared by a wide spectrum of species, and most of them are non-coding sequences. Conserved sequences play critical roles in the genetic diseases. Many conserved secondary structures have been identified inside some conserved sequences. Some conserved secondary structures have been recognized as RNAs, such as microRNAs, RNA editing sequences, and stem-loops in the 3’-UTR of histone mRNAs. However, for most of the conserved secondary structures, it remains largely unknown about their biological functions and the evolutionary forces acting upon them. The data of SNPs from populations are effective in analyzing the evolutionary forces acting on a sequence. The frequencies of SNPs would be affected by the evolutionary forces acting on them, but not determined by whether they are located inside mutation hot spots. SNPs under purifying selection are always exhibiting lower derived allele frequencies (DAFs) than neutral SNPs. We identified 746 SNPs located inside conserved secondary structures by using bioinformatics methods. No significant difference of mutation patterns exists between SNPs in conserved secondary structures and other genomic regions, and hot mutation spots are also presented in the conserved secondary structures. By comparing the distribution of SNPs in conserved secondary structures and their flanking sequences, we found that SNP density in former is about 2/3 of that in latter. Further, a higher fraction of SNPs in conserved secondary structures have low DAFs than SNPs in the flanking sequences. These results indicate that many of the mutations in conserved secondary structures are removed in the human populations by purifying selection. The difference of SNP density and DAF distribution is more significant than the corresponding difference observed between conserved and nonconserved sequences, indicating that conserved secondary structures are the most conserved sequences. Even inside conserved secondary structures, we also observed an uneven distribution of the intensity of purifying selection. Sites on stems have lower SNP density than sites on loops and a higher fraction of SNPs on stems have low DAFs than SNPs on loops. This result indicates that the purifying selection against conserved secondary structures is mainly resulted from the purifying selection against sites on stems. We speculate that the difference might be owing to the fact that mutations on stems have greater impact on the secondary structures than mutations on loops. We investigated the roles of conserved secondary structures in the transcriptional regulation networks by examining their overlaps with the binding sites for transcription factors SOX2, OCT4, NANOG, SUZ12 and C-MYC. Our result indicates that many conserved secondary structures are regulating developmental transcription factor-encoding genes by providing binding sites for transcription factors. Transcription factors exhibit complicated patterns when binding to conserved secondary structures, some transcription factors can bind to a common conserved secondary structure, and some transcription factors can bind to conserved secondary structures that are associated with their encoding genes. The different binding patterns between transcription factors and conserved secondary structures are directing specific expression patterns of target genes. The expression of target gene is repressed while most of the associated intergenic conserved secondary structures are bound by SUZ12 and acitivated while most of the associated intergenic conserved secondary structures are devoild of binding of SUZ12. About 30% of the conserved secondary structures function as promoters in the transcriptional regulation networks. Because the transcription factors only bind to a small fraction of conserved secondary structures, many other transcription factors may bind to conserved secondary structures. Therefore, the transcriptional regulation networks mediated by conserved secondary structures would be much more complicated than currently appreciated.
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