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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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Related in: MedlinePlus

The heat map of the numbers of SNPs in miRNAs with significantly different frequencies between different populations in the HapMap data.The number in a cell means the number of SNPs with significantly different frequencies (with multiple test corrected -values of smaller than 0.01, see Materials and Methods for details) between the two populations of the row and column. There are 11 populations in the HapMap data. ASW, CEU, CHB, CHD, GIH, JPT, LWK, MEX, MKK, TSI, and YRI stand for African ancestry in Southwest USA; Utah residents (CEPH) with Northern and Western European ancestry; Han Chinese in Beijing, China; Chinese in Metropolitan Denver, Colorado; Gujarati Indians in Houston, Texas; Japanese in Tokyo, Japan; Luhya in Webuye, Kenya; Mexican ancestry in Los Angeles, California; Maasai in Kinyawa, Kenya; Toscani in Italia; and Yoruba in Ibadan, Nigeria, respectively. Among the 11 populations, ASW, LWK, MKK and YRI belong to Africa, marked by blue color; CHB, CHD and JPT belong to Asian, marked by yellow color; CEU and TSI belong to European, marked by green color and GIH and MEX belong to America, marked by red color. The dendrogram was generated with the hierarchical clustering implemented in Matlab.
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pone-0078028-g006: The heat map of the numbers of SNPs in miRNAs with significantly different frequencies between different populations in the HapMap data.The number in a cell means the number of SNPs with significantly different frequencies (with multiple test corrected -values of smaller than 0.01, see Materials and Methods for details) between the two populations of the row and column. There are 11 populations in the HapMap data. ASW, CEU, CHB, CHD, GIH, JPT, LWK, MEX, MKK, TSI, and YRI stand for African ancestry in Southwest USA; Utah residents (CEPH) with Northern and Western European ancestry; Han Chinese in Beijing, China; Chinese in Metropolitan Denver, Colorado; Gujarati Indians in Houston, Texas; Japanese in Tokyo, Japan; Luhya in Webuye, Kenya; Mexican ancestry in Los Angeles, California; Maasai in Kinyawa, Kenya; Toscani in Italia; and Yoruba in Ibadan, Nigeria, respectively. Among the 11 populations, ASW, LWK, MKK and YRI belong to Africa, marked by blue color; CHB, CHD and JPT belong to Asian, marked by yellow color; CEU and TSI belong to European, marked by green color and GIH and MEX belong to America, marked by red color. The dendrogram was generated with the hierarchical clustering implemented in Matlab.

Mentions: There are 121 SNPs in pre-miRNAs that have frequency information for at least 2 of the 11 populations in the HapMap database (Table S12). There are 627 SNPs in pre-miRNAs have frequency information for at least 2 of the 4 populations in the 1000 Genome Project database (Table S13). A previous study also collected the frequency information of SNPs in pre-miRNAs, however they only identified 41 SNPs and just presented the frequencies of them without detailed analysis [18]. Here, we identified the SNPs with significantly different frequencies between various populations in the HapMap and 1000 Genome Project (with multiple test corrected -values ) (see Figure 6/Table S14 and Table 2, respectively). From the diagonal of Figure 6, it can be seen that the populations from the same continents have much smaller numbers of SNPs with significantly different frequencies than populations of different continents. Another interesting point lies in that the American and European populations also have very small number of SNPs with significantly different frequencies. Actually, the two American populations are Gujarati Indians in Houston, Texas and Mexican ancestry in Los Angeles, California, respectively. Our results suggest that Gujarati Indians are similar to European populations. And the close relation between European populations and Mexican ancestry is consistent with the migration history of European populations to America. The largest number of SNPs with significantly different frequencies exists between African populations and some European and Asian populations. And the numbers of SNPs with significantly different frequencies between Asian and European (as well as American) populations are not as large as their intersections between African populations. This is probably due to the fact that Asian and European populations are actually living in the same continent. We also performed a hierarchical clustering of populations using their numbers of SNPs with significantly different frequencies between other populations. The obtained dendrogram in Figure 6 suggests that American and European populations have closer relations than other populations; and that the relations between Asian and European/American populations are closer than their relation to African populations. Furthermore, we randomly chose 121 SNPs that have frequency information in at least 2 of the 11 populations in the HapMap data for three times. Then, we also calculated the numbers of SNPs that have significantly different frequencies between different populations, and clustered the 11 populations based on the numbers of these SNPs. The obtained relationships between different populations based on the average number of SNPs with significantly different frequencies between various populations of these three replications are not consistent with their geographical distributions (see Figure S2). These results suggest that SNPs in miRNAs are more likely to be differentiated across populations than a random subset of SNPs of the same size.


Comprehensive analysis of single nucleotide polymorphisms in human microRNAs.

Han M, Zheng Y - PLoS ONE (2013)

The heat map of the numbers of SNPs in miRNAs with significantly different frequencies between different populations in the HapMap data.The number in a cell means the number of SNPs with significantly different frequencies (with multiple test corrected -values of smaller than 0.01, see Materials and Methods for details) between the two populations of the row and column. There are 11 populations in the HapMap data. ASW, CEU, CHB, CHD, GIH, JPT, LWK, MEX, MKK, TSI, and YRI stand for African ancestry in Southwest USA; Utah residents (CEPH) with Northern and Western European ancestry; Han Chinese in Beijing, China; Chinese in Metropolitan Denver, Colorado; Gujarati Indians in Houston, Texas; Japanese in Tokyo, Japan; Luhya in Webuye, Kenya; Mexican ancestry in Los Angeles, California; Maasai in Kinyawa, Kenya; Toscani in Italia; and Yoruba in Ibadan, Nigeria, respectively. Among the 11 populations, ASW, LWK, MKK and YRI belong to Africa, marked by blue color; CHB, CHD and JPT belong to Asian, marked by yellow color; CEU and TSI belong to European, marked by green color and GIH and MEX belong to America, marked by red color. The dendrogram was generated with the hierarchical clustering implemented in Matlab.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3818353&req=5

pone-0078028-g006: The heat map of the numbers of SNPs in miRNAs with significantly different frequencies between different populations in the HapMap data.The number in a cell means the number of SNPs with significantly different frequencies (with multiple test corrected -values of smaller than 0.01, see Materials and Methods for details) between the two populations of the row and column. There are 11 populations in the HapMap data. ASW, CEU, CHB, CHD, GIH, JPT, LWK, MEX, MKK, TSI, and YRI stand for African ancestry in Southwest USA; Utah residents (CEPH) with Northern and Western European ancestry; Han Chinese in Beijing, China; Chinese in Metropolitan Denver, Colorado; Gujarati Indians in Houston, Texas; Japanese in Tokyo, Japan; Luhya in Webuye, Kenya; Mexican ancestry in Los Angeles, California; Maasai in Kinyawa, Kenya; Toscani in Italia; and Yoruba in Ibadan, Nigeria, respectively. Among the 11 populations, ASW, LWK, MKK and YRI belong to Africa, marked by blue color; CHB, CHD and JPT belong to Asian, marked by yellow color; CEU and TSI belong to European, marked by green color and GIH and MEX belong to America, marked by red color. The dendrogram was generated with the hierarchical clustering implemented in Matlab.
Mentions: There are 121 SNPs in pre-miRNAs that have frequency information for at least 2 of the 11 populations in the HapMap database (Table S12). There are 627 SNPs in pre-miRNAs have frequency information for at least 2 of the 4 populations in the 1000 Genome Project database (Table S13). A previous study also collected the frequency information of SNPs in pre-miRNAs, however they only identified 41 SNPs and just presented the frequencies of them without detailed analysis [18]. Here, we identified the SNPs with significantly different frequencies between various populations in the HapMap and 1000 Genome Project (with multiple test corrected -values ) (see Figure 6/Table S14 and Table 2, respectively). From the diagonal of Figure 6, it can be seen that the populations from the same continents have much smaller numbers of SNPs with significantly different frequencies than populations of different continents. Another interesting point lies in that the American and European populations also have very small number of SNPs with significantly different frequencies. Actually, the two American populations are Gujarati Indians in Houston, Texas and Mexican ancestry in Los Angeles, California, respectively. Our results suggest that Gujarati Indians are similar to European populations. And the close relation between European populations and Mexican ancestry is consistent with the migration history of European populations to America. The largest number of SNPs with significantly different frequencies exists between African populations and some European and Asian populations. And the numbers of SNPs with significantly different frequencies between Asian and European (as well as American) populations are not as large as their intersections between African populations. This is probably due to the fact that Asian and European populations are actually living in the same continent. We also performed a hierarchical clustering of populations using their numbers of SNPs with significantly different frequencies between other populations. The obtained dendrogram in Figure 6 suggests that American and European populations have closer relations than other populations; and that the relations between Asian and European/American populations are closer than their relation to African populations. Furthermore, we randomly chose 121 SNPs that have frequency information in at least 2 of the 11 populations in the HapMap data for three times. Then, we also calculated the numbers of SNPs that have significantly different frequencies between different populations, and clustered the 11 populations based on the numbers of these SNPs. The obtained relationships between different populations based on the average number of SNPs with significantly different frequencies between various populations of these three replications are not consistent with their geographical distributions (see Figure S2). These results suggest that SNPs in miRNAs are more likely to be differentiated across populations than a random subset of SNPs of the same size.

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
Related in: MedlinePlus