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Big data challenges in bone research: genome-wide association studies and next-generation sequencing.

ABSTRACT: Genome-wide association studies (GWAS) have been developed as a practical method to identify genetic loci associated with disease by scanning multiple markers across the genome. Significant advances in the genetics of complex diseases have been made owing to advances in genotyping technologies, the progress of projects such as HapMap and 1000G and the emergence of genetics as a collaborative discipline. Because of its great potential to be used in parallel by multiple collaborators, it is important to adhere to strict protocols assuring data quality and analyses. Quality control analyses must be applied to each sample and each single-nucleotide polymorphism (SNP). The software package PLINK is capable of performing the whole range of necessary quality control tests. Genotype imputation has also been developed to substantially increase the power of GWAS methodology. Imputation permits the investigation of associations at genetic markers that are not directly genotyped. Results of individual GWAS reports can be combined through meta-analysis. Finally, next-generation sequencing (NGS) has gained popularity in recent years through its capacity to analyse a much greater number of markers across the genome. Although NGS platforms are capable of examining a higher number of SNPs compared with GWA studies, the results obtained by NGS require careful interpretation, as their biological correlation is incompletely understood. In this article, we will discuss the basic features of such protocols.

SUBMITTER: Alonso N

PROVIDER: S-EPMC4325556 | biostudies-other | 2015

REPOSITORIES: biostudies-other

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Project description:Pancreatic adenocarcinoma (PAC) is among the most lethal malignancies. While research has implicated multiple genes in disease pathogenesis, identification of therapeutic leads has been difficult and the majority of currently available therapies provide only marginal benefit. To address this issue, our goal was to genomically characterize individual PAC patients to understand the range of aberrations that are occurring in each tumor. Because our understanding of PAC tumorigenesis is limited, evaluation of separate cases may reveal aberrations, that are less common but may provide relevant information on the disease, or that may represent viable therapeutic targets for the patient. We used next generation sequencing to assess global somatic events across 3 PAC patients to characterize each patient and to identify potential targets. This study is the first to report whole genome sequencing (WGS) findings in paired tumor/normal samples collected from 3 separate PAC patients. We generated on average 132 billion mappable bases across all patients using WGS, and identified 142 somatic coding events including point mutations, insertion/deletions, and chromosomal copy number variants. We did not identify any significant somatic translocation events. We also performed RNA sequencing on 2 of these patients' tumors for which tumor RNA was available to evaluate expression changes that may be associated with somatic events, and generated over 100 million mapped reads for each patient. We further performed pathway analysis of all sequencing data to identify processes that may be the most heavily impacted from somatic and expression alterations. As expected, the KRAS signaling pathway was the most heavily impacted pathway (P<0.05), along with tumor-stroma interactions and tumor suppressive pathways. While sequencing of more patients is needed, the high resolution genomic and transcriptomic information we have acquired here provides valuable information on the molecular composition of PAC and helps to establish a foundation for improved therapeutic selection.

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Big data challenges in bone research: genome-wide association studies and next-generation sequencing.

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