The increase of patients with Alzheimer's disease (AD) has a great impact on the social and economic status. Up to date, no effective treatment can alleviate the progress of AD suggesting an alternative strategy is mandatory to reduce its prevalence. Massive neuronal loss is evident in the pathology, of AD which leads to clinical manifestations. Thus, neuroprotection for preserving the neurons from damage depends on the identification of biomarkers which is capable of early detection of disease susceptibility. In order to identify the factors contributing to AD, new research strategies such as systems biology with whole genome coverage have been employed. Analysis of transcripts in whole genome which does not default to or sort by hypothesis of etiology may be appropriate to decipher the pathogenic mechanism for AD. Both single nucleotide changes and expression quantity differences from the whole transcriptome could be assessed by base-calling and numbers of reads, respectively. RNA-Seq is suitable for the complexity of the genome from brain tissue and is capable of solving the technique errors in comparison of the postmortem tissues of controls with those of patients with neurodegenerative disease. In addition, RNA-seq can detect the mRNA species with alternative splicing and assess their amount, which could provide much more information as compared to the genomic exon-predicting sequences. Furthermore, it can also accurately define the transcription boundary in single base resolution scale. These advantages render the RNA-Seq as a unique and efficient method for research into the human brain transcriptome.