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Long intergenic non-coding RNAs (lincRNAs) play important roles in many cellular processes. Here, we present the first systematic identification and characterization of lincRNAs in fetal porcine skeletal muscle. We obtained a total of 55.02 million 90-bp paired-end reads and assembled 54,550 transcripts using cufflinks. We developed a pipeline to identify 570 multi-exon lincRNAs by integrating a set of previous approaches. These putative porcine lincRNAs share many characteristics with mammalian lincRNAs, such as a relatively short length, small number of exons and low level of sequence conservation. We found that the porcine lincRNAs were preferentially located near genes mediating transcriptional regulation rather than those with developmental functions. We further experimentally analyzed the features of a conserved mouse lincRNA gene and found that isoforms 1 and 4 of this lincRNA were enriched in the cell nucleus and were associated with polycomb repressive complex 2 (PRC2). Our results provide a catalog of fetal porcine lincRNAs for further experimental investigation of the functions of these genes in the skeletal muscle developmental process.

Natural products, containing inherently large-scale structural diversity than synthetic compounds, have been the major resources of bioactive agents and will continually play as protagonists for discovering new drugs. However, how to access this diverse chemical space efficiently and effectively is an exciting challenge for medicinal chemists and pharmacologists. While virtual screening, which has shown a great promise in drug discovery, will play an important role in digging out lead (active) compounds from natural products. This review focuses on the strategy of virtual screening based on molecular docking and, with successful examples from our laboratory, illustrates the efficiency of virtual screening in discovering active compounds from natural products. On the other hand, the sequencing of the human genome and numerous pathogen genomes has resulted in an unprecedented opportunity for discovering potential new drug targets. Chemogenomics has appeared as a new technology to initiate target discovery by using active compounds as probes to characterize proteome functions. Natural products are the ideal probes for such research. Binding affinity fingerprint is a powerful chemogenomic descriptor to characterize both small molecules and pharmacologically relevant proteins. Therefore, this review also discusses binding affinity fingerprint strategy for identifying target information from the genomic data by using natural products as the probes.

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