Finding Alu in primate genomes with AF-1

Shankar, Ravi; Kataria, Bhavesh; Mukerji, Mitali

doi:10.6026/97320630003287

Cited by 46 publications

(1 citation statement)

References 7 publications

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“…This is supported by the fact that a repetitive sequence (CCCACCCTTC) has been found four times in the CYP2D gene cluster. Also, Alu sequences (short repetitive sequences found exclusively in primate genomes (Shankar, Kataria, and Mukerji 2009)) were discovered in the 3' regions of CYP2D6 and CYP2D7P. Repetitive sequences like these are known to favor unequal crossover events.…”

Section: Genetic Mechanisms Leading To Duplication and Multiduplicatimentioning

confidence: 99%

Isolation and Characterization of the CYP2D6 Gene in Felidae with Comparison to Other Mammals

et al. 2010

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The highly polymorphic CYP2D6 protein metabolizes about 25% of commonly used drugs and underlies a broad spectrum of drug responses among individuals. In contrast to extensive knowledge on the human CYP2D6 gene, little is known about the gene in non-human mammals. CYP2D6 mRNA from 23 cats (Felidae) spanning seven species were compared to available CYPD6 sequences in ten additional mammals and multiple allelic variants in humans. A relatively high mean dN/dS ratio (0.565) was observed, especially within Felidae. Pairwise dN/dS ratios were non-monotonically distributed with respect to evolutionary distance suggesting either positive selection or retention of slightly deleterious mutations. Positive selection on specific codons, most notably in regions involved in substrate recognition and membrane anchoring is supported and the possible influence of diet on specific amino acid changes in substrate binding sites is discussed.

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Section: Genetic Mechanisms Leading To Duplication and Multiduplicatimentioning

confidence: 99%

Isolation and Characterization of the CYP2D6 Gene in Felidae with Comparison to Other Mammals

et al. 2010

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The human splicing code reveals new insights into the genetic determinants of disease

Xiong

Alipanahi

Lee

et al. 2015

Science

1,133

964

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Introduction Advancing whole-genome precision medicine requires understanding how gene expression is altered by genetic variants, especially those that are outside of protein-coding regions. We developed a computational technique that scores how strongly genetic variants alter RNA splicing, a critical step in gene expression whose disruption contributes to many diseases, including cancers and neurological disorders. A genome-wide analysis reveals tens of thousands of variants that alter splicing and are enriched with a wide range of known diseases. Our results provide insight into the genetic basis of spinal muscular atrophy, hereditary nonpolyposis colorectal cancer and autism spectrum disorder. Methods We used machine learning to derive a computational model that takes as input DNA sequences and applies general rules to predict splicing in human tissues. Given a test variant, our model computes a score that predicts how much the variant disrupts splicing. The model was derived in such a way that it can be used to study diverse diseases and disorders, and to determine the consequences of common, rare, and even spontaneous variants. Results Our technique is able to accurately classify disease-causing variants and provides insights into the role of aberrant splicing in disease. We scored over 650,000 DNA variants and found that disease-causing variants have higher scores than common variants and even those associated with disease in genome-wide association studies. Our model predicts substantial and unexpected aberrant splicing due to variants within introns and exons, including those far from the splice site. For example, among intronic variants that are more than 30 nucleotides away from a splice site, known disease variants alter splicing nine times more often than common variants; among missense exonic disease variants, those that least impact protein function are over five times more likely to alter splicing than other variants. Autism has been associated with disrupted splicing in brain regions, so we used our method to score variants detected using whole genome sequencing data from individuals with and without autism. Genes with high scoring variants include many that have been previously linked with autism, as well as new genes with known neurodevelopmental phenotypes. Most of the high scoring variants are intronic and cannot be detected by exome analysis techniques. When we score clinical variants in spinal muscular atrophy and colorectal cancer genes, up to 94% of variants found to disrupt splicing using minigene reporters are correctly classified. Discussion In the context of precision medicine, causal support for variants that is independent of existing studies is greatly needed. Our computational model was trained to predict splicing from DNA sequence alone, without using disease annotations or population data. Consequently, its predictions are independent of and complementary to population data, genome-wide association studies (GWAS), expression-based quantitative trait loci (QTL), and functi...

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A Comprehensive Analysis Of Normalization Approaches For Privacy Protection In Data Mining

Koduru¹

2022

IJSRCSEIT

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Data Mining is a fundamental method of extracting large volumes of data sets by unfamiliar patterns. These extracted data can be shared between enterprises to improve their corporate benefits. For the data mining process, sharing such confidential data is very important. It is very important to safeguard such information against unwanted exposure that leads to privacy leakage. In recent days, privacy in various data mining applications has become very important. In order to overcome such problem privacy, data mining techniques are preserved. It provides accurate data mining results without scarifying the original data values and ensures both accuracy and privacy. Data protection is achieved through the analysis of the data using normalization techniques in this proposed work. The approach proposed in comparison the effects of min-max, decimal scaling, and Z-Score normalization techniques. Experimental effects confirmed that the Min-max Standardization technology archived the most precision with minimum data loss.

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Finding Alu in primate genomes with AF-1

Cited by 46 publications

References 7 publications

Isolation and Characterization of the CYP2D6 Gene in Felidae with Comparison to Other Mammals

Isolation and Characterization of the CYP2D6 Gene in Felidae with Comparison to Other Mammals

The human splicing code reveals new insights into the genetic determinants of disease

A Comprehensive Analysis Of Normalization Approaches For Privacy Protection In Data Mining

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