Dataset Information

MitoSuite: a graphical tool for human mitochondrial genome profiling in massive parallel sequencing.

ABSTRACT: Recent rapid advances in high-throughput, next-generation sequencing (NGS) technologies have promoted mitochondrial genome studies in the fields of human evolution, medical genetics, and forensic casework. However, scientists unfamiliar with computer programming often find it difficult to handle the massive volumes of data that are generated by NGS. To address this limitation, we developed MitoSuite, a user-friendly graphical tool for analysis of data from high-throughput sequencing of the human mitochondrial genome. MitoSuite generates a visual report on NGS data with simple mouse operations. Moreover, it analyzes high-coverage sequencing data but runs on a stand-alone computer, without the need for file upload. Therefore, MitoSuite offers outstanding usability for handling massive NGS data, and is ideal for evolutionary, clinical, and forensic studies on the human mitochondrial genome variations. It is freely available for download from the website https://mitosuite.com.

SUBMITTER: Ishiya K

PROVIDER: S-EPMC5452969 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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MitoSuite: a graphical tool for human mitochondrial genome profiling in massive parallel sequencing.

Ishiya Koji K Ueda Shintaroh S

PeerJ 20170530

Recent rapid advances in high-throughput, next-generation sequencing (NGS) technologies have promoted mitochondrial genome studies in the fields of human evolution, medical genetics, and forensic casework. However, scientists unfamiliar with computer programming often find it difficult to handle the massive volumes of data that are generated by NGS. To address this limitation, we developed MitoSuite, a user-friendly graphical tool for analysis of data from high-throughput sequencing of the human ...[more]

PMID: 28584729

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Project description:BACKGROUND:Although the Illumina 1 G Genome Analyzer generates billions of base pairs of sequence data, challenges arise in sequence selection due to the varying sequence quality. Therefore, in the framework of the International Porcine SNP Chip Consortium, this pilot study aimed to evaluate the impact of the quality level of the sequenced bases on mapping quality and identification of true SNPs on a large scale. RESULTS:DNA pooled from five animals from a commercial boar line was digested with DraI; 150-250-bp fragments were isolated and end-sequenced using the Illumina 1 G Genome Analyzer, yielding 70,348,064 sequences 36-bp long. Rules were developed to select sequences, which were then aligned to unique positions in a reference genome. Sequences were selected based on quality, and three thresholds of sequence quality (SQ) were compared. The highest threshold of SQ allowed identification of a larger number of SNPs (17,489), distributed widely across the pig genome. In total, 3,142 SNPs were validated with a success rate of 96%. The correlation between estimated minor allele frequency (MAF) and genotyped MAF was moderate, and SNPs were highly polymorphic in other pig breeds. Lowering the SQ threshold and maintaining the same criteria for SNP identification resulted in the discovery of fewer SNPs (16,768), of which 259 were not identified using higher SQ levels. Validation of SNPs found exclusively in the lower SQ threshold had a success rate of 94% and a low correlation between estimated MAF and genotyped MAF. Base change analysis suggested that the rate of transitions in the pig genome is likely to be similar to that observed in humans. Chromosome X showed reduced nucleotide diversity relative to autosomes, as observed for other species. CONCLUSION:Large numbers of SNPs can be identified reliably by creating strict rules for sequence selection, which simultaneously decreases sequence ambiguity. Selection of sequences using a higher SQ threshold leads to more reliable identification of SNPs. Lower SQ thresholds can be used to guarantee sufficient sequence coverage, resulting in high success rate but less reliable MAF estimation. Nucleotide diversity varies between porcine chromosomes, with the X chromosome showing less variation as observed in other species.

Project description:BACKGROUND: Artificial selection has caused rapid evolution in domesticated species. The identification of selection footprints across domesticated genomes can contribute to uncover the genetic basis of phenotypic diversity. METHODOLOGY/MAIN FINDINGS: Genome wide footprints of pig domestication and selection were identified using massive parallel sequencing of pooled reduced representation libraries (RRL) representing ?2% of the genome from wild boar and four domestic pig breeds (Large White, Landrace, Duroc and Pietrain) which have been under strong selection for muscle development, growth, behavior and coat color. Using specifically developed statistical methods that account for DNA pooling, low mean sequencing depth, and sequencing errors, we provide genome-wide estimates of nucleotide diversity and genetic differentiation in pig. Widespread signals suggestive of positive and balancing selection were found and the strongest signals were observed in Pietrain, one of the breeds most intensively selected for muscle development. Most signals were population-specific but affected genomic regions which harbored genes for common biological categories including coat color, brain development, muscle development, growth, metabolism, olfaction and immunity. Genetic differentiation in regions harboring genes related to muscle development and growth was higher between breeds than between a given breed and the wild boar. CONCLUSIONS/SIGNIFICANCE: These results, suggest that although domesticated breeds have experienced similar selective pressures, selection has acted upon different genes. This might reflect the multiple domestication events of European breeds or could be the result of subsequent introgression of Asian alleles. Overall, it was estimated that approximately 7% of the porcine genome has been affected by selection events. This study illustrates that the massive parallel sequencing of genomic pools is a cost-effective approach to identify footprints of selection.

Dataset Information

MitoSuite: a graphical tool for human mitochondrial genome profiling in massive parallel sequencing.

Publications

MitoSuite: a graphical tool for human mitochondrial genome profiling in massive parallel sequencing.

Similar Datasets

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