TY - JOUR

T1 - Systems genetics of complex diseases using RNA-sequencing methods

AU - Mazzoni, Gianluca

AU - Kogelman, Lisette

AU - Suravajhala, Prashanth

AU - Kadarmideen, Haja

PY - 2015

Y1 - 2015

N2 - Next generation sequencing technologies have enabled the generation of huge quantities ofbiological data, and nowadays extensive datasets at different ‘omics levels have been generated. Systemsgenetics is a powerful approach that allows to integrate different ‘omics level and understand the biologicalmechanisms behind complex diseases or traits. In the recent past, transcriptomic studies with microarrayshave been replaced with the new powerful RNA-seq technologies. This has led to detection of novel genetranscripts, novel regulatory mechanisms, allele specific gene expression and numerous non-coding RNAs(ncRNAs). The integration of transcriptomics data with genomic data in a systems genetics contextrepresents a valuable possibility to go deep into the causal and regulatory mechanisms that generatecomplex traits and diseases. However RNA-Seq data have to be treated carefully and the choice of the rightmethodology could have a great impact on the final results. Furthermore the integration of different level isnot trivial. Here we give a comprehensive systems genetics overview of the methods and tools for analysisand the integration of RNA-Seq data including ncRNAs. We focused principally on merits and demerits oftools for post mapping quality control, normalization, differential expression analysis, gene networkanalysis, and integration of different omics data in order to generate a comprehensive guideline to systemsgenetics analysis using RNA-Seq data.

AB - Next generation sequencing technologies have enabled the generation of huge quantities ofbiological data, and nowadays extensive datasets at different ‘omics levels have been generated. Systemsgenetics is a powerful approach that allows to integrate different ‘omics level and understand the biologicalmechanisms behind complex diseases or traits. In the recent past, transcriptomic studies with microarrayshave been replaced with the new powerful RNA-seq technologies. This has led to detection of novel genetranscripts, novel regulatory mechanisms, allele specific gene expression and numerous non-coding RNAs(ncRNAs). The integration of transcriptomics data with genomic data in a systems genetics contextrepresents a valuable possibility to go deep into the causal and regulatory mechanisms that generatecomplex traits and diseases. However RNA-Seq data have to be treated carefully and the choice of the rightmethodology could have a great impact on the final results. Furthermore the integration of different level isnot trivial. Here we give a comprehensive systems genetics overview of the methods and tools for analysisand the integration of RNA-Seq data including ncRNAs. We focused principally on merits and demerits oftools for post mapping quality control, normalization, differential expression analysis, gene networkanalysis, and integration of different omics data in order to generate a comprehensive guideline to systemsgenetics analysis using RNA-Seq data.

U2 - 10.17706/ijbbb.2015.5.4.264-279

DO - 10.17706/ijbbb.2015.5.4.264-279

M3 - Journal article

VL - 5

SP - 264

EP - 279

JO - International Journal of Bioscience, Biochemistry and Bioinformatics

JF - International Journal of Bioscience, Biochemistry and Bioinformatics

SN - 2010-3638

IS - 4

ER -