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Comprehensive analysis of single nucleotide polymorphisms in human microRNAs.

Han M, Zheng Y - PLoS ONE (2013)

Bottom Line: Our results suggest that conservation, genomic context, secondary structure, and functional importance of human miRNAs affect the accumulations of SNPs in these genes.Our results also show that the number of SNPs with significantly different frequencies among various populations in the HapMap and 1000 Genome Project data are consistent with the geographical distributions of these populations.These analyses provide a better insight of SNPs in human miRNAs and the spreading of the SNPs in miRNAs in different populations.

View Article: PubMed Central - PubMed

Affiliation: State Key Laboratory of Genetic Engineering and Institute of Developmental Biology and Molecular Medicine, School of Life Sciences, Fudan University, Shanghai, China.

ABSTRACT
MicroRNAs (miRNAs) are endogenous small non-coding RNAs that repress their targets at post transcriptional level. Single Nucleotide Polymorphisms (SNPs) in miRNAs can lead to severe defects to the functions of miRNAs and might result in diseases. Although several studies have tried to identify the SNPs in human miRNA genes or only in the mature miRNAs, there are only limited endeavors to explain the distribution of SNPs in these important genes. After a genome-wide scan for SNPs in human miRNAs, we totally identified 1899 SNPs in 961 out of the 1527 reported miRNA precursors of human, which is the most complete list of SNPs in human miRNAs to date. More importantly, to explain the distributions of SNPs existed in human miRNAs, we comprehensively and systematically analyzed the identified SNPs in miRNAs from several aspects. Our results suggest that conservation, genomic context, secondary structure, and functional importance of human miRNAs affect the accumulations of SNPs in these genes. Our results also show that the number of SNPs with significantly different frequencies among various populations in the HapMap and 1000 Genome Project data are consistent with the geographical distributions of these populations. These analyses provide a better insight of SNPs in human miRNAs and the spreading of the SNPs in miRNAs in different populations.

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The SNP densities of different regions of miRNAs and different categories of miRNAs.Part A shows the distribution of the number of species in which each miRNA family appears. Part B shows the proportions of human miRNAs classified as highly conserved, lowly conserved and non-conserved miRNA families, respectively. Part C shows the comparing of SNP densities of human miRNAs among highly conserved, lowly conserved and non-conserved miRNA families in the pre-miRNAs, mature miRNAs and seed regions, respectively. Part D shows the proportion of clustered miRNAs. Part E shows the distribution of the numbers of clustered miRNAs in each miRNA cluster. Part F shows the comparisons of SNP densities between clustered miNRAs and individual miRNAs, and also between clustered miRNAs and the flanking regions of clustered miRNAs. Two sample one tailed -test was used to compare the difference of SNP densities above. In part C, F, *, ** and *** means -values smaller than 0.05, 0.01 and 0.001, respectively, and error bars indicate the standard errors of the means (SEM).
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pone-0078028-g002: The SNP densities of different regions of miRNAs and different categories of miRNAs.Part A shows the distribution of the number of species in which each miRNA family appears. Part B shows the proportions of human miRNAs classified as highly conserved, lowly conserved and non-conserved miRNA families, respectively. Part C shows the comparing of SNP densities of human miRNAs among highly conserved, lowly conserved and non-conserved miRNA families in the pre-miRNAs, mature miRNAs and seed regions, respectively. Part D shows the proportion of clustered miRNAs. Part E shows the distribution of the numbers of clustered miRNAs in each miRNA cluster. Part F shows the comparisons of SNP densities between clustered miNRAs and individual miRNAs, and also between clustered miRNAs and the flanking regions of clustered miRNAs. Two sample one tailed -test was used to compare the difference of SNP densities above. In part C, F, *, ** and *** means -values smaller than 0.05, 0.01 and 0.001, respectively, and error bars indicate the standard errors of the means (SEM).

Mentions: It was shown in Figure 2A that around 3 quarters of all miRNA families appeared in less than 10 species. Therefore, we classified all miRNA families into highly, lowly and non-conserved if a miRNA family appears in more than or equal to 10, 2 to 9 and 1 species, respectively. Based on this criterion, 200, 573 and 442 human miRNAs were classified to highly conserved, lowly conserved and non-conserved miRNA families, respectively (see Figure 2B). The SNP densities of pre-miRNAs, mature miRNAs and seed regions of the classified miRNA families are shown in Figure 2C and listed in Table S4 to S6. Figure 2C shows that both the highly and lowly conserved families have significantly lower average SNP densities than that of non-conserved families in pre-miRNA regions ( and , respectively, one tailed -test). The average SNP density of highly conserved families is significantly lower than that of lowly conserved families (, one tailed -test). We also find a significant negative correlation (, , Spearman’s rank correlation test) between the number of species in which one family appeared and the average SNP density of all the pre-miRNAs included in this family. These results suggest that the more conservative one miRNA family is, the less SNPs it can tolerate in pre-miRNA region, which is consistent with the more important functions of the conserved miRNAs. Figure 2C also demonstrates that both the highly and lowly conserved families have significantly lower average SNP densities than that of non-conserved families in mature miRNAs ( and , respectively, one tailed -test) and seed regions ( and respectively, one tailed -test). However, there is no significantly difference between the average SNP densities of highly and lowly conserved families in mature miRNAs (,one tailed -test) and seed regions (,one tailed -test). There is also no significant negative correlations (, , and , , respectively, Spearman’s rank correlation test) between the number of species in which one family appeared and the average SNP densities of all mature miRNAs and seed regions included in a miRNA family, respectively.


Comprehensive analysis of single nucleotide polymorphisms in human microRNAs.

Han M, Zheng Y - PLoS ONE (2013)

The SNP densities of different regions of miRNAs and different categories of miRNAs.Part A shows the distribution of the number of species in which each miRNA family appears. Part B shows the proportions of human miRNAs classified as highly conserved, lowly conserved and non-conserved miRNA families, respectively. Part C shows the comparing of SNP densities of human miRNAs among highly conserved, lowly conserved and non-conserved miRNA families in the pre-miRNAs, mature miRNAs and seed regions, respectively. Part D shows the proportion of clustered miRNAs. Part E shows the distribution of the numbers of clustered miRNAs in each miRNA cluster. Part F shows the comparisons of SNP densities between clustered miNRAs and individual miRNAs, and also between clustered miRNAs and the flanking regions of clustered miRNAs. Two sample one tailed -test was used to compare the difference of SNP densities above. In part C, F, *, ** and *** means -values smaller than 0.05, 0.01 and 0.001, respectively, and error bars indicate the standard errors of the means (SEM).
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC3818353&req=5

pone-0078028-g002: The SNP densities of different regions of miRNAs and different categories of miRNAs.Part A shows the distribution of the number of species in which each miRNA family appears. Part B shows the proportions of human miRNAs classified as highly conserved, lowly conserved and non-conserved miRNA families, respectively. Part C shows the comparing of SNP densities of human miRNAs among highly conserved, lowly conserved and non-conserved miRNA families in the pre-miRNAs, mature miRNAs and seed regions, respectively. Part D shows the proportion of clustered miRNAs. Part E shows the distribution of the numbers of clustered miRNAs in each miRNA cluster. Part F shows the comparisons of SNP densities between clustered miNRAs and individual miRNAs, and also between clustered miRNAs and the flanking regions of clustered miRNAs. Two sample one tailed -test was used to compare the difference of SNP densities above. In part C, F, *, ** and *** means -values smaller than 0.05, 0.01 and 0.001, respectively, and error bars indicate the standard errors of the means (SEM).
Mentions: It was shown in Figure 2A that around 3 quarters of all miRNA families appeared in less than 10 species. Therefore, we classified all miRNA families into highly, lowly and non-conserved if a miRNA family appears in more than or equal to 10, 2 to 9 and 1 species, respectively. Based on this criterion, 200, 573 and 442 human miRNAs were classified to highly conserved, lowly conserved and non-conserved miRNA families, respectively (see Figure 2B). The SNP densities of pre-miRNAs, mature miRNAs and seed regions of the classified miRNA families are shown in Figure 2C and listed in Table S4 to S6. Figure 2C shows that both the highly and lowly conserved families have significantly lower average SNP densities than that of non-conserved families in pre-miRNA regions ( and , respectively, one tailed -test). The average SNP density of highly conserved families is significantly lower than that of lowly conserved families (, one tailed -test). We also find a significant negative correlation (, , Spearman’s rank correlation test) between the number of species in which one family appeared and the average SNP density of all the pre-miRNAs included in this family. These results suggest that the more conservative one miRNA family is, the less SNPs it can tolerate in pre-miRNA region, which is consistent with the more important functions of the conserved miRNAs. Figure 2C also demonstrates that both the highly and lowly conserved families have significantly lower average SNP densities than that of non-conserved families in mature miRNAs ( and , respectively, one tailed -test) and seed regions ( and respectively, one tailed -test). However, there is no significantly difference between the average SNP densities of highly and lowly conserved families in mature miRNAs (,one tailed -test) and seed regions (,one tailed -test). There is also no significant negative correlations (, , and , , respectively, Spearman’s rank correlation test) between the number of species in which one family appeared and the average SNP densities of all mature miRNAs and seed regions included in a miRNA family, respectively.

Bottom Line: Our results suggest that conservation, genomic context, secondary structure, and functional importance of human miRNAs affect the accumulations of SNPs in these genes.Our results also show that the number of SNPs with significantly different frequencies among various populations in the HapMap and 1000 Genome Project data are consistent with the geographical distributions of these populations.These analyses provide a better insight of SNPs in human miRNAs and the spreading of the SNPs in miRNAs in different populations.

View Article: PubMed Central - PubMed

Affiliation: State Key Laboratory of Genetic Engineering and Institute of Developmental Biology and Molecular Medicine, School of Life Sciences, Fudan University, Shanghai, China.

ABSTRACT
MicroRNAs (miRNAs) are endogenous small non-coding RNAs that repress their targets at post transcriptional level. Single Nucleotide Polymorphisms (SNPs) in miRNAs can lead to severe defects to the functions of miRNAs and might result in diseases. Although several studies have tried to identify the SNPs in human miRNA genes or only in the mature miRNAs, there are only limited endeavors to explain the distribution of SNPs in these important genes. After a genome-wide scan for SNPs in human miRNAs, we totally identified 1899 SNPs in 961 out of the 1527 reported miRNA precursors of human, which is the most complete list of SNPs in human miRNAs to date. More importantly, to explain the distributions of SNPs existed in human miRNAs, we comprehensively and systematically analyzed the identified SNPs in miRNAs from several aspects. Our results suggest that conservation, genomic context, secondary structure, and functional importance of human miRNAs affect the accumulations of SNPs in these genes. Our results also show that the number of SNPs with significantly different frequencies among various populations in the HapMap and 1000 Genome Project data are consistent with the geographical distributions of these populations. These analyses provide a better insight of SNPs in human miRNAs and the spreading of the SNPs in miRNAs in different populations.

Show MeSH