With more and more lncRNAs discovered, new probes specific for lncRNAs can be designed. For example, Babak et al. designed probes from conserved selleck chem inhibitor intergenic and intragenic region to identify potential ncRNA transcripts [61]. However, microarray is not sensitive enough to detect RNA transcripts with low-expression level. Thus the use of microarray to identify lncRNAs is limited due to the low expression level of many lncRNAs. SAGE and EST ��SAGE (serial analysis of gene expression) technology produces large numbers of short sequence tags and is capable of identifying both known and unknown transcripts. SAGE has been used and proved to be an efficient approach in studying lncRNAs. For example, Gibb et al. compiled 272 human SAGE libraries.

By passing over 24 million tags they were able to generate lncRNA expression profiles in human normal and cancer tissues [62]. Lee et al. also used SAGE to identify potential lncRNA candidates in male germ cell [63]. However, SAGE is much more expensive than microarray, therefore is not widely employed in large-scale studies. EST (expressed sequence tag) is a short subsequence of cDNA, and is generated from one-shot sequencing of cDNA clone. The public database now contains over 72.6 million EST (GeneBank 2011), making it possible to discover novel transcripts. For example, Furuno et al. clustered EST to find functional and novel lncRNAs in mammalian [64]. Huang et al. used the public bovine-specific EST database to reconstruct transcript assemblies, and find transcripts in intergenic regions that are likely putative lncRNAs [65].

RNA-Seq ��With the development of next generation sequencing (NGS) technologies, RNA-Seq (also named whole transcriptome shotgun sequencing) has been widely used for novel transcripts discovery and gene expression analysis. Compared to traditional microarray technology, RNA-Seq has many advantages in studying gene expression. It is more sensitive in detecting less-abundant transcripts, and identifying novel alternative splicing isoforms and novel ncRNA transcripts. The basic Carfilzomib workflow for lncRNA identification using RNA-Seq is shown in Figure 1. RNA-Seq is currently the most widely used technology in identifying lncRNAs. For example, Li et al. applied RNA-Seq to identify lncRNAs during chicken muscle development [66]. Nam and Bartel integrated RNA-Seq, poly (A)-site, and ribosome mapping information to obtain lncRNAs in C. elegans [16]. Pauli et al. performed RNA-Seq experiments at eight stages during zebrafish early development, and identified 1133 noncoding multiexonic transcripts [67]. Prensner et al.