Circular RNAs (circRNAs) are a new class of non-coding RNAs formed by covalently closed loops through backsplicing. Recent methodologies have enabled in-depth characterization of circRNAs for identification and potential functions. CircRNAs play important roles in various biological functions as microRNA sponges, transcriptional regulators and combining with RNA binding proteins. Recent studies indicated that some cytoplasmic circRNAs can be effectively translated into detectable peptides, which enlightened us on the importance of circRNAs in cellular physiology function. Internal Ribosome Entry site (IRES)-and N 6-methyladenosines (m 6 A)-mediated cap-independent translation initiation have been suggested to be potential mechanism for circRNA translation. To date, several translated circRNAs have been uncovered to play pivotal roles in human cancers. In this review, we introduced the properties and functions of circRNAs, and characterized the possible mechanism of translation initiation and complexity of the translation ability of circRNAs. We summarized the emerging functions of circRNA-encoded proteins in human cancer. The works on circRNA translation will open a hidden human proteome, and enhance us to understand the importance of circRNAs in human cancer, which has been poorly explored so far.

Metastasis is the main event leading to death in cancer patients. Over the past decade, high-throughput technologies have provided genome-wide view of transcriptomic changes associated with cancer metastases. Many microarray and RNA sequencing studies have addressed metastases-related expression patterns in various types of cancer, and the number of relevant works continues to increase rapidly. These works have characterized genes that orchestrate the metastatic phenotype of cancer cells. However, these expression data have been deposited in various repositories, and efficiently analyzing these data is still difficult because of the lack of an integrated data mining platform. To facilitate the in-depth analyses of transcriptome data on metastasis, it is quite important to make a comprehensive integration of these metastases-related expression data. Here, we presented a database, HCMDB (the human cancer metastasis database, http://hcmdb.i-sanger.com/index), which is freely accessible to the research community query cross-platform transcriptome data on metastases. HCMDB is developed and maintained as a useful resource for building the systems-biology understanding of metastasis.

Bats can perceive the world by using a wide range of sensory systems, and some of the systems have become highly specialized, such as auditory sensory perception. Among bat species, the Old World leaf-nosed bats and horseshoe bats (rhinolophoid bats) possess the most sophisticated echolocation systems. Here, we reported the whole-genome sequencing and de novo assembles of two rhinolophoid bats-the great leaf-nosed bat (Hipposideros armiger) and the Chinese rufous horseshoe bat (Rhinolophus sinicus). Comparative genomic analyses revealed the adaptation of auditory sensory perception in the rhinolophoid bat lineages, probably resulting from the extreme selectivity used in the auditory processing by these bats. Pseudogenization of some vision-related genes in rhinolophoid bats was observed, suggesting that these genes have undergone relaxed natural selection. An extensive contraction of olfactory receptor gene repertoires was observed in the lineage leading to the common ancestor of bats. Further extensive gene contractions can be observed in the branch leading to the rhinolophoid bats. Such concordance suggested that molecular changes at one sensory gene might have direct consequences for genes controlling for other sensory modalities. To characterize the population genetic structure and patterns of evolution, we re-sequenced the genome of 20 great leaf-nosed bats from four different geographical locations of China. The result showed similar sequence diversity values and little differentiation among populations. Moreover, evidence of genetic adaptations to high altitudes in the great leaf-nosed bats was observed. Taken together, our work provided a useful resource for future research on the evolution of bats.

Nucleus-encoded circular RNAs (ncircRNAs) have been widely detected in eukaryotes, and most circRNA identification algorithms are designed to identify them. However, using these algorithms, few mitochondrion-encoded circRNAs (mcircRNAs) have been identified in plants, and the role of plant mcircRNAs has not yet been addressed. Here, we developed a circRNA identification algorithm, mitochondrion-encoded circRNA identifier (MeCi), based on common features of plant mitochondrial genomes. We identified 7,524, 9,819, 1,699, 1,821, 1,809, and 5,133 mcircRNAs in maize (Zea mays), Arabidopsis (Arabidopsis thaliana), rice (Oryza sativa), tomato (Solanum lycopersicum), cucumber (Cucumis sativus), and grape (Vitis vinifera), respectively. These mcircRNAs were experimentally validated. Plant mcircRNAs had distinct characteristics from ncircRNAs, and they were more likely to be derived from RNA degradation but not intron backsplicing. Alternative circularization was prevalent in plant mitochondria, and most parental genomic regions hosted multiple mcircRNA isoforms, which have homogenous 5′ termini but heterogeneous 3′ ends. By analysis of mitopolysome and mitoribosome profiling data, 1,463 mcircRNAs bound to ribosomes were detected in maize and Arabidopsis. Further analysis of mass spectrometry–based proteomics data identified 358 mcircRNA-derived polypeptides. Overall, we developed a computational pipeline that efficiently identifies plant mcircRNAs, and we demonstrated mcircRNAs are widespread and translated in plants.