Transmission distortion （TD） is a significant departure from Mendelian predictions of genes or chromosomes to offspring. While many biological processes have been implicated, there is still much to be understood abo...Transmission distortion （TD） is a significant departure from Mendelian predictions of genes or chromosomes to offspring. While many biological processes have been implicated, there is still much to be understood about TD in humans. Here we present our findings from a genome-wide scan for evidence of TD using haplotype data of 60 trio families from the International HapMap Project. Fisher＇s exact test was applied to assess the extent of TD in 629,958 SNPs across the autosomes. Based on the empirical distribution of PFisher and further permutation tests, we identified 1,205 outlier loci and 224 candidate genes with TD. Using the PANTHER gene ontology database, we found 19 categories of biological processes with an enrichment of candidate genes. In particular, the “protein phosphorylation” category contained the largest number of candidates in both HapMap samples. Further analysis uncovered an intriguing non-synonymous change in PPPIR12B, a gene related to protein phosphorylation, which appears to influence the allele transmission from male parents in the YRI （Yoruba from Ibadan, Nigeria） population. Our findings also indicate an ethnicity-related property of TD signatures in HapMap samples and provide new clues for our understanding of TD in humans.展开更多
To overcome the obstacle of the fascinating relation in predicting animal phenotype value, we have developed a neural network model to detect the complex non-linear relationships between the genotypes and phenotypes a...To overcome the obstacle of the fascinating relation in predicting animal phenotype value, we have developed a neural network model to detect the complex non-linear relationships between the genotypes and phenotypes and the possible interactions that cannot be expressed with equations. In this paper, back-propagation neural network is used to discuss the influences of different allele frequencies on estimating the polygenic phenotype value. To ensure the precision of prediction, normalization was needed to train the prediction model. The results show that back-propagation artificial neural networks can be used to predict the phenotype value and perform very well in allele frequency from 0.2 to 0.8, when the allele frequency is very small （less than 0.2） or big （more than 0.8）; however, the prediction model was not reliable and the predicted value should be carefully tested.展开更多
Common variants explain little of the variance of most common disease, prompting large-scale sequencing studies to understand the contribution of rare variants to these diseases. Imputation of rare variants from genom...Common variants explain little of the variance of most common disease, prompting large-scale sequencing studies to understand the contribution of rare variants to these diseases. Imputation of rare variants from genome-wide genotypic arrays offers a cost-efficient strategy to achieve necessary sample sizes required for adequate statistical power. To estimate the performance of imputation of rare variants, we imputed 153 individuals, each of whom was genotyped on 3 different genotype arrays including 317k, 610k and 1 million single nucleotide polymorphisms （SNPs）, to two different reference panels： HapMap2 and 1000 Genomes pilot March 2010 release （1KGpilot） by using IMPUTE version 2. We found that more than 94% and 84% of all SNPs yield acceptable accuracy （info 〉 0.4） in HapMap2 and 1KGpilot-based imputation, respectively. For rare variants （minor allele frequency （MAF） 〈5%）, the proportion of well- imputed SNPs increased as the MAF increased from 0.3% to 5% across all 3 genome-wide association study （GWAS） datasets. The proportion of well-imputed SNPs was 69%, 60% and 49% for SNPs with a MAF from 0.3% to 5% for 1M, 610k and 317k, respectively. None of the very rare variants （MAF 〈 0.3%） were well imputed. We conclude that the imputation accuracy of rare variants increases with higher density of genome-wide genotyping arrays when the size of the reference panel is small. Variants with lower MAF are more difficult to impute. These findings have important implications in the design and replication of large-scale sequencing studies.展开更多
In recent era,advancement of research involves computational management of large-scale genomic and post-genomic datasets in an obvious way.Rapidly emerging field of bioinformatics,fueled by high-throughput technologie...In recent era,advancement of research involves computational management of large-scale genomic and post-genomic datasets in an obvious way.Rapidly emerging field of bioinformatics,fueled by high-throughput technologies and genomic scale database,is believed to reshape our approach of research to a new level.Genomics has shifted the paradigm of biological perspectives exploring many scopes.Old initiatives paved the path for the newer and more advantageous one.The present review focuses on present initiatives that are implemented till now like the famous Human Genome Project and its influence on digital biology,as well as the projects that followed in its footsteps.Additionally,the authors delve into the future potential of personalized medicine and the use of genetic engineering methods like CRISPR/Cas9 in gene editing,which are thought to have the potential to revolutionize the current treatment strategy.展开更多
Natural selection, as the driving force of human evolution, has direct impact on population differentiation. However, it is still unclear to what extent the genetic differentiation has been caused by natural selection...Natural selection, as the driving force of human evolution, has direct impact on population differentiation. However, it is still unclear to what extent the genetic differentiation has been caused by natural selection. To explore this question, we performed a genome-wide scan with single nucleotide polymorphism (SNP) data from the International HapMap Project. Single locus FST analysis was applied to assess the frequency difference among populations in autosomes. Based on the empirical distribution of FST, we identified 12669 SNPs correlating to population differentiation and 1853 candidate genes subjected to geographic restricted natural selection. Further interpretation of gene ontogeny revealed 121 categories of biological process with the enrichments of candidate genes. Our results suggest that natural selection may play an important role in human population differentiation. In addition, our analysis provides new clues as well as research methods for our understanding of population differentiation and natural selection.展开更多
基金supported by the National Nature Science Foundation of China (No.30225017)
文摘Transmission distortion （TD） is a significant departure from Mendelian predictions of genes or chromosomes to offspring. While many biological processes have been implicated, there is still much to be understood about TD in humans. Here we present our findings from a genome-wide scan for evidence of TD using haplotype data of 60 trio families from the International HapMap Project. Fisher＇s exact test was applied to assess the extent of TD in 629,958 SNPs across the autosomes. Based on the empirical distribution of PFisher and further permutation tests, we identified 1,205 outlier loci and 224 candidate genes with TD. Using the PANTHER gene ontology database, we found 19 categories of biological processes with an enrichment of candidate genes. In particular, the “protein phosphorylation” category contained the largest number of candidates in both HapMap samples. Further analysis uncovered an intriguing non-synonymous change in PPPIR12B, a gene related to protein phosphorylation, which appears to influence the allele transmission from male parents in the YRI （Yoruba from Ibadan, Nigeria） population. Our findings also indicate an ethnicity-related property of TD signatures in HapMap samples and provide new clues for our understanding of TD in humans.
基金Supported by the Scientific Research Starting Foundation for Doctors, Henan Institute of Science and Technology of China
文摘To overcome the obstacle of the fascinating relation in predicting animal phenotype value, we have developed a neural network model to detect the complex non-linear relationships between the genotypes and phenotypes and the possible interactions that cannot be expressed with equations. In this paper, back-propagation neural network is used to discuss the influences of different allele frequencies on estimating the polygenic phenotype value. To ensure the precision of prediction, normalization was needed to train the prediction model. The results show that back-propagation artificial neural networks can be used to predict the phenotype value and perform very well in allele frequency from 0.2 to 0.8, when the allele frequency is very small （less than 0.2） or big （more than 0.8）; however, the prediction model was not reliable and the predicted value should be carefully tested.
文摘Common variants explain little of the variance of most common disease, prompting large-scale sequencing studies to understand the contribution of rare variants to these diseases. Imputation of rare variants from genome-wide genotypic arrays offers a cost-efficient strategy to achieve necessary sample sizes required for adequate statistical power. To estimate the performance of imputation of rare variants, we imputed 153 individuals, each of whom was genotyped on 3 different genotype arrays including 317k, 610k and 1 million single nucleotide polymorphisms （SNPs）, to two different reference panels： HapMap2 and 1000 Genomes pilot March 2010 release （1KGpilot） by using IMPUTE version 2. We found that more than 94% and 84% of all SNPs yield acceptable accuracy （info 〉 0.4） in HapMap2 and 1KGpilot-based imputation, respectively. For rare variants （minor allele frequency （MAF） 〈5%）, the proportion of well- imputed SNPs increased as the MAF increased from 0.3% to 5% across all 3 genome-wide association study （GWAS） datasets. The proportion of well-imputed SNPs was 69%, 60% and 49% for SNPs with a MAF from 0.3% to 5% for 1M, 610k and 317k, respectively. None of the very rare variants （MAF 〈 0.3%） were well imputed. We conclude that the imputation accuracy of rare variants increases with higher density of genome-wide genotyping arrays when the size of the reference panel is small. Variants with lower MAF are more difficult to impute. These findings have important implications in the design and replication of large-scale sequencing studies.
文摘In recent era,advancement of research involves computational management of large-scale genomic and post-genomic datasets in an obvious way.Rapidly emerging field of bioinformatics,fueled by high-throughput technologies and genomic scale database,is believed to reshape our approach of research to a new level.Genomics has shifted the paradigm of biological perspectives exploring many scopes.Old initiatives paved the path for the newer and more advantageous one.The present review focuses on present initiatives that are implemented till now like the famous Human Genome Project and its influence on digital biology,as well as the projects that followed in its footsteps.Additionally,the authors delve into the future potential of personalized medicine and the use of genetic engineering methods like CRISPR/Cas9 in gene editing,which are thought to have the potential to revolutionize the current treatment strategy.
文摘Natural selection, as the driving force of human evolution, has direct impact on population differentiation. However, it is still unclear to what extent the genetic differentiation has been caused by natural selection. To explore this question, we performed a genome-wide scan with single nucleotide polymorphism (SNP) data from the International HapMap Project. Single locus FST analysis was applied to assess the frequency difference among populations in autosomes. Based on the empirical distribution of FST, we identified 12669 SNPs correlating to population differentiation and 1853 candidate genes subjected to geographic restricted natural selection. Further interpretation of gene ontogeny revealed 121 categories of biological process with the enrichments of candidate genes. Our results suggest that natural selection may play an important role in human population differentiation. In addition, our analysis provides new clues as well as research methods for our understanding of population differentiation and natural selection.
