**4.2. Transcriptome profiling of economically important animals**

Similar to the value provided by transcriptome profiling of plants, transcriptome profiling of economically important animals contributes toward better understanding of disease resist‐ ance, productivity, breeding, quality of meat, etc., in animals. Ropka-Molik et al. [138] have used the NGS transcriptome profiling approach to identify genes that are differentially expressed between two pig breeds with differences in muscularity that could contribute toward the quality of meat. Gene expression profiles have been generated from different breeds of cows to identify genes that contribute toward milk protein and fat percentage in cow milk [139, 140] and milk yield [141]. Transcriptome profiling has also been used very recently to identify the genes that are differentially expressed in silkworms (*B. mori*) undergoing thermal parthenogenesis [142]. Thermal parthenogenesis is a process that is used in silkworm breeding and selection.

#### **4.3. Cancer**

Cancer is a complex and heterogeneous genetic disorder that results from either inherited or somatic genetic variations such as single nucleotide variations (SNV), insertions, deletions, copy number variations, dysregulation of gene expression, and epigenetic modifications. As changes in the gene expression pattern play a key role in tumorigenicity [143], metastasis [144], prognosis [145], and relapse [146, 147], gene expression profiling has been used extensively in cancer research and diagnosis. OncotypeDx (http://www.oncotypedx.com/) is a gene-expres‐ sion-based commercially available test that is used for breast cancer, colon cancer, and prostate cancer diagnosis and prognosis.

Contrary to microarrays and RT-PCR-based approaches used earlier, RNASeq, which can detect coding and noncoding RNA, strand orientation, and genetic variants all in one go, is a very powerful tool in deciphering the complex transcriptome changes usually found in cancer. One of the most comprehensive studies published recently is the transcriptome profiling of 4043 Cancers and 548 Normal Tissue Controls across 12 TCGA Cancer Types [148]. In this study, in addition to identifying tissue specific gene signature, the authors were able to identify a 14-gene signature that accurately distinguished the cancer samples from the normal. Using a whole transcriptome sequencing approach, Koh et al. [149] recently reported 14 candidate genes that are important in rhabdoid glioblastoma (R-GBM) tumor, a rare form of GBM. Similarly, RNASeq approach was used to identify gene signature in flow-sorted viable EpCAM + tumor epithelial cells and CD45+ tumor-infiltrating immune cells that were obtained from cervical cancer samples [150]. The authors identified TCL1A as a novel biomarker, found specifically in the immune cells, for predicting survival in cervical cancer patients.

The aforementioned studies highlight the varied approaches that can be used for identifying biomarkers or gene signatures associated with distinct cancer characteristics.
