Evolution of the mir-181 microRNA family

Evolution of the mir-181 microRNA family

Computers in Biology and Medicine 52 (2014) 82–87 Contents lists available at ScienceDirect Computers in Biology and Medicine journal homepage: www...

1007KB Sizes 0 Downloads 15 Views

Computers in Biology and Medicine 52 (2014) 82–87

Contents lists available at ScienceDirect

Computers in Biology and Medicine journal homepage: www.elsevier.com/locate/cbm

Evolution of the mir-181 microRNA family Zhen Yang a,b,1, Xueshuai Wan a,1, Zhuoya Gu b, Haohai Zhang a, Xiaobo Yang a, Lian He a, Ruoyu Miao a, Yang Zhong b,c, Haitao Zhao a,n a

Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Science, CAMS & PUMC, 100730 Beijing, China School of Life Sciences, Fudan University, Shanghai 200433, China c Institute of Biodiversity Science and Geobiology, Tibet University, Lhasa 850000, China b

art ic l e i nf o

a b s t r a c t

Article history: Received 15 November 2013 Accepted 5 June 2014

Mir-181 is an ancient microRNA (miRNA) gene family that originated in urochordata. Although their functions were subjected to extensive studies in recent years, their evolutionary process remains largely unknown. Here we systematically investigated the homologous genes of the mir-181 family by a sequence similarity search. Representative sequences of the mir-181 gene family were used to reconstruct their evolutionary history. Our results indicated that this family could have derived from multiple duplications, which include two rounds of whole genome duplications and one round of segmental replication. Functional annotation of the target genes of the mir-181 family suggested that this family could participate in some important biological processes including transcriptional and translational regulation, signaling transduction etc. This analysis presented a complex evolutionary dynamics for the origination of a miRNA gene family. & 2014 Elsevier Ltd. All rights reserved.

Keywords: miRNA Mir-181 Evolution Gene duplication

1. Introduction MicroRNAs (miRNAs) are endogenously expressed small noncoding RNAs (  22 nucleotides) that regulate the expression of protein-coding genes post-transcriptionally [1]. miRNAs mainly function by base-pairing to the 30 -untranslated regions (30 -UTR) of mRNAs to induce translational inactivation or RNA degradation [2]. As a class of important gene regulators throughout evolutionary process, miRNA-meditated gene regulation is widespread in animals, plants and viruses [3]. In recent years, study on miRNAs has advanced significantly, as knowledge about the key cellular processes and molecular functions that miRNAs involved in has been accumulating rapidly. It has been indicated that miRNAs play a role in almost all aspect of cellular functions, including: cell proliferation, differentiation, apoptosis, embryonic and development [4]. However, their origination, evolution and amplification in the genome remain largely unknown. The number of miRNA genes increased continuously in the genomes of metazoans during evolution. By investigating the phylogenetic distribution of metazoan miRNAs, Hertal et al. found that a number of miRNAs experienced several rounds of expansions in metazoans. The time of these gene expansion coincided

n

Corresponding author. Tel.: þ 86 10 65296042; fax: þ 86 10 65296043. E-mail address: [email protected] (H. Zhao). 1 Equal contribution to this work.

http://dx.doi.org/10.1016/j.compbiomed.2014.06.004 0010-4825/& 2014 Elsevier Ltd. All rights reserved.

with the origination of Bilateria (including the Protostomia and Deuterostomia), Vertebrata, and Placental Mammals [5]. It was also suggested that complexity in the gene expression regulation brought by the increasing number of miRNAs could be one of the major driving forces for animal evolution. The enlargement of the miRNA gene pool was achieved mainly through three ways: whole genome duplication, gene replication and transposition. It was proposed that the expansion of many miRNA copies and a considerable number of miRNA families was due to whole genome duplication. Evidence also suggested that origination of a gene cluster with 43 miRNAs on chromosome 19 in primates is due to the Alu-mediated rapid expansion and lineage-specific gain and loss of specific miRNAs [6]. Moreover, fragmental replication may facilitate the origin and expansion of new miRNA families. By analysis of the homology of internal miRNAs within each cluster, it was discovered that most of these miRNAs came from fragmental duplication of ancestral genes. Therefore, miRNA fragmental duplication is an important driving force for new miRNA cluster generation and miRNA family evolution in genome. In this work, we characterized the evolutionary patterns of a vertebrate-specific miRNA gene family, the miR-181, which includes six homologs in the human genome. MiR-181 has been suggested to play key regulatory roles in many biological processes. For example, it was shown to participate in mammalian skeletal-muscle differentiation by regulating homeobox protein Hox-A11 [7]. The reduced expression of the mir-181 family was identified to be related to carcinogenesis [8]. However, what

Z. Yang et al. / Computers in Biology and Medicine 52 (2014) 82–87

remains unclear is the evolutionary history of this miRNA gene family. Here we characterized the evolutionary process by phylogenetic analysis of this vertebrate miRNA family. The inferred phylogeny suggested that the miR-181 gene family formed through gene duplications, among which were whole genome duplications and segmental duplications of the common ancestor gene. We also performed a functional annotation of the targets that the mir-181 family putatively regulated. The Gene Ontology (GO) [9] and Kyoto Encyclopedia of Genes and Genomes (KEGG) [10] enrichment analysis of candidate target genes revealed that these target genes participated in essential biological processes including cell proliferation, cancer development, and immune response.

2. Material and methods 2.1. Identification of homolog genes of mir-181 family Pre-miRNA sequences of mir-181 family from human and other vertebrates were retrieved from miRBase database [11]. A total of 103 sequences were retrieved, which include 102 sequences from vertebrates and one sequence from Ciona intestinalis. To further investigate the potential homologs of the mir-181 family in other inferior vertebrate and invertebrate genomes, we selected six inferior vertebrate and invertebrate species whose genomes have been completely sequenced, including Lampetra fluviatilis, Branchiostoma floridae, Strongylocentrotus purpuratus, Anopheles gambiae, Drosophila melanogaster, Caenorhabditis elegans. A sequence similarity search for human mir-181 family in these genomes was performed by using the BLAT embedded in UCSC Genome Browser [12,13] Sequences that have more than 70% identity with human mir-181 were retrieved as potential mir-181 homologs. We then predicted the secondary structure of these potential mir-181 homologs by mFold (http://mfold.rna.albany.edu/) to further investigate the reliability of those sequences as pre-miRNAs [14]. 2.2. Phylogenetic analysis of mir-181 family We selected eight species that represente the major clade in vertebrates and carried out a phylogenetic analysis of the 56 sequences of mir-181 family from these species. Multi-sequence alignment was carried out by MUSCLE [15]. A phylogenetic tree of mir-181 gene family was constructed by using the NeighborJoining method of MEGA [16]and Maximum-Likelihood of RaxML [17]. For construction of Neighbor-Joining tree, the uncorrected p-distance substitution model and complete deletion for estimating evolution distance method were used, while other parameters were set by default. For construction of the Maximum-likelihood tree, the Kimura two-parameter substitution model was used, and other parameters were set as default.

83

target genes to investigate biological pathways that miR-181 family regulated.

3. Results 3.1. Phylogenetic distribution of mir-181 family members Six members of the mir-181 family have been identified in the human genome, which include hsa-mir-181a-1and hsa-mir-181b-1 locate on chromosome 1; hsa-mir-181a-2 and hsa-mir-181b-2 locate on chromosome 9; as well as hsa-mir-181c and hsa-mir181d locate on chromosome 19. No other protein coding genes were found in the chromosome regions containing the mir-181 family members, which indicated that members of human mir-181 family were independently transcribed. Mir-181 gene family encode a 21 bp miRNA, whose consensus sequence is: 50 -AACAUUCA(A/U) (C/U)GCUGUCGGUG(A/G)GU-30 . By searching the miRBase database, we found mir-181 homologs in 24 species, which include Homo sapiens, Pan troglodytes, Pan paniscus, Pongo pygmaeus, Gorilla gorilla, Macaca mulatta, Macaca nemestrinam, Lagothrix lagotricha, Saguinus labiatus, Mus musculus, Rattus norvegicus, Bos taurus, Sus scrofa, Canis lupusfamiliaris, Equus caballus, Monodelphis domestica, Ornithorhynchus anatinus, Gallus gallus, Taeniopygia guttata, Xenopu stropicalis, Tetraodon nigroviridis, Fugu rubripes, Danio rerio, and Ciona intestinalis. Among them, 23 species cover major categories of vertebrate, while for the urochordate C. intestinalis, we only found one family member, the cin-mir-181. To identify homologs of mir-181 family in other inferior vertebrates and invertebrates, we carried out a sequence similarity search in genomes of six species using BLAT in UCSC Genome Browser. We got one homologous sequence in each of the genomes of Lampetra fluviatilis, Branchiostoma floridae, Anopheles gambiae, and Drosophila melanogaster. We then used the mFold software to predict the secondary structure of these homologous sequences to see whether these RNAs can form the stable stemloop structure akin to its miRNA precursor. According to the algorithm, a stable stem-loop structure is possible for the putative mir-181 homologs from Lampetra japonica and D. melanogaster. However, the putative mature mir-181 sequence is not located in the stem region in the miRNA precursor. Meanwhile, the putative mir-181 homologs from B. floridae and A. gambiae cannot form the stable stem-loop structure akin to its miRNA precursor. This result indicated that functional mir-181 family genes were not present in other inferior vertebrates or invertebrates we investigated. Due to the fact that we only found one member of mir-181 family in the genome of urochordata C. intestinalis, we concluded that mir-181 was an ancient gene family originating from the member of the inferior chordate. The ancestral single copy in urochordata replicated or amplified multiple rounds to form other copies in vertebrate genome during evolution.

2.3. Prediction and function analysis of miRNA target genes 3.2. Evolutionary pattern of mir-181 gene family Target prediction for human mir-181 family was carried out by two different miRNA target gene prediction software, the TargetScan [18]and PITA [19]. Predicted results of TargetScan were retrieved from the TargetScan database (http://www.targetscan. org/) and those of PITA were from the PITA database (http://genie. weizmann.ac.il/pubs/mir07/mir07_data.html). The intersections between the two sets of predicted target genes from these different prediction software were regarded as the reliable target genes. We then analyzed the GO term distribution of biological processes and molecular functions in Gene Ontology using WebGestalt [20]. We also performed the KEGG enrichment analysis of

We constructed the phylogenetic tree using the representative 56 sequences of mir-181 family from different species. The sequence information used in this analysis was presented as Supplementary Table 1. Phylogenetic tree generated by the Neighbor-Joining method presented that mir-181 gene family clustered as gene categories instead of species variations except for xtr-mir-181a-1, xtr-mir-181a-2 and also gga-mir-181a-2, which shared more similarities with mir-181c group (Fig. 1). The six parallel homologous genes of this family could be classified as four major categories: mir-181a-1/mir-181a-2, mir-181c, mir-181d and

84

Z. Yang et al. / Computers in Biology and Medicine 52 (2014) 82–87

Fig. 1. Phylogenetic tree of the mir-181 gene family by the Neighbour-Joining method. Gene clusters were highlighted in four different colors.

mir-181b-1/mir-181b-2. Similar results were obtained based on the Maximum-Likelihood method. The evolutionary pattern of the mir-181 family suggests that this gene family following the birth-and-death model. An obvious symmetrical pattern was observed from the phylogenetic tree of this family, indicating that the four gene categories might be generated from two rounds of duplication of an ancestor gene. Moreover, mir-181a-1 and mir-181a-2, mir-181b-1 and mir-181b-2 cluster were separately and closely packed on chromosomes, which suggested that these clusters originated from fragmental replication of two ancestor genes. Two separate possible evolutionary processes of themir-181 gene family can be proposed. The first one includes

four major steps: the ancestor gene duplicated twice to generate four parallel homologous genes, two of which then replicated fragmentally to form the total six-member gene family. The second one included three major steps: the ancestor gene duplicated once to generate the two parallel homologs, one of which replicated fragmentally to form three parallel homologs. Then, all three homologs duplicated again to form the six-member gene family. Based on the principle of maximum-parsimony of evolution, we speculated that the evolution of the mir-181 gene family followed the second process: the miR-181 gene family underwent two rounds of duplication and a fragmental replication between them during vertebrate evolution to form this gene family (Fig. 2).

Z. Yang et al. / Computers in Biology and Medicine 52 (2014) 82–87

3.3. Functional analysis of human mir-181 family targets In recent years, studies on mir-181 gene family provided us better understanding of its function. Previous studies indicated that mir-181 gene family might participate in several biological pathways including signal transduction, ontogeny and carcinogenesis. To further investigate the important role and biological function of this family, we predicted the targets of the human mir-181 family and analyzed the biological function and pathway of those genes. A total of 892 target genes of mir-181 family predicted by TargetScan were downloaded from the TargetScan database, whereas 881 target genes predicted by PITA were obtained. The intersection of 536 genes from these two data sets

85

were regarded as reliable target genes. We then performed the Gene Ontology term enrichment analysis by WebGestalt2.0 as well as the KEGG metabolism pathway enrichment analysis to investigate their biological processes and molecular functions. The Gene Ontology results demonstrated that the target genes of mir-181 family were involved in multiple biological processes, including gene expression regulation, macromolecule metabolism, nucleic acid metabolism, macromolecule biosynthesis, cellular communication, cell division, growth, and proliferation. These target genes can also be categorized in terms of their molecular functions, including nucleic acid binding, DNA binding, protein binding, transcription factor binding, transcription regulator activity, kinase activity, transferase activity (Fig. 3). KEGG pathway analysis indicated that the target genes of miR-181 family were mainly involved in neurology or immunity related pathways, including neurotrophin signaling pathway, axon guidance, and T cell receptor signaling pathways (Table 1). Moreover, the target genes may also associate with cancer occurrence.

4. Discussion

Fig. 2. Evolutionary pattern of the mir-181 family in vertebrate. The solid bar represents mir-181 gene. Two rounds of duplications and one fragmental replication within one of the duplicates after first duplication during the vertebrate evolution shape this gene family.

In recent years, more and more miRNA families have been identified in various species. However, there are still no explicit answers to the questions regarding the origin of these miRNA families, the evolutionary processes leading to the formation of these gene families and similarities between the evolution process of miRNA genes and that of protein coding genes. Previous studies have demonstrated that miRNA gene amplified mainly through

Fig. 3. Gene ontology of targets of mir-181 family. (A) biological process, and (B) molecular function. The indicated numbers are the numbers of target genes predicted by the Gene Ontology method.

Table 1 Enriched KEGG pathways of the targets of mir-181 family. KEGG pathway

Number of genes

Enriched gene ID

P-value

Neurotrophin signaling pathway Long-term potentiation Axon guidance Pathways in cancer

15 11 14 20

1.49E-09 1.19E-08 1.19E-08 3.89E-08

T cell receptor signaling pathway Oocyte meiosis Regulation of actin cytoskeleton MAPK signaling pathway Focal adhesion Vascular smooth muscle contraction

11 11 14 15 13 10

8660 4215 11108 5580 801 5908 8503 596 3845 5594 10818 7529 818 7532 6197 801 107 5534 5908 5500 3845 2891 5594 2915 6197 818 23380 6092 54910 57144 1808 57715 5534 10512 3845 90249 5594 10725 10298 7869 7184 3915 3655 868 11186 7046 3845 1050 2353 2113 5156 10401 5898 3675 8030 8503 596 861 9915 5594 84433 920 57144 5534 868 8503 3845 2353 5594 10725 10298 5529 115 801 107 5534 5500 5594 7529 6197 7532 818 3696 3675 57144 8874 3655 8503 5500 55740 3845 5594 4628 5156 10298 10458 4215 5534 5908 9254 51701 7046 3845 3552 2353 5594 5156 5495 1847 4137 6197 5170 3696 3915 3675 57144 3655 5908 8503 5500 596 5594 5156 10298 5581 3778 5580 115 801 107 5592 4660 5500 5594

7.73E-07 1.13E-06 2.63E-06 5.64E-06 5.64E-06 6.94E-06

86

Z. Yang et al. / Computers in Biology and Medicine 52 (2014) 82–87

genome duplication, fragmental replication and transposition [21]. For example, the miR-17–92 cluster which is also the first oncogenic miRNA that was identified was originated from fragmental replication [22]. Yu et al. investigated the positional distribution of 326 miRNAs in the human genome and demonstrated that 148 miRNAs were arranged to form 51 clusters [23]. In present study, we analyzed the phylogenetic distribution of mir181 family in various species and found thatit is an ancient gene family originating from urochordate C. intestinalis. While C. intestinaliv contains only asingle copy of mir-181 gene, the genomes of other vertebrates contain more than one copy. We further investigated the evolution pattern of this gene family in vertebrates and found that this gene family was formed by multiple replication of the ancestor gene, including two duplications as a whole and one fragmental replication with mutation and deletion of certain genes in some species. The regulatory complexity resulted from increasing of miRNA copies may be an important driving force to promote the evolution of higher organisms [24]. Studies have shown that there are multiple rounds of whole genome duplication during vertebrates0 evolution, and functional gene multiplication caused by genome duplication maybe the major force for the complexity of the physical structure of vertebrates [25,26]. Studies have shown that the number of protein coding genes of vertebrates is four times of that of invertebrates. Most genes only have a single copy in the genome of invertebrates, whereas for vertebrates, most gene families include four members. It is speculated that the gene multiplication incidences may occur during the separation of cephalochordate and vertebrate, as well as the separation between gnathostome and agnatha. Thus the whole genome duplication may be the main reason for the increasing number of miRNA besides fragmental replication and transposon replication. Our analysis of the miR-181 gene family suggested that the expansion of this family could be the result of whole genome duplication during vertebrate evolution and accompanied by the fragmental replication and deletion of certain genes in some species. In recent years, huge amounts of information about the roles of miRNAs in cancer and other diseases have been published [27–33]. This is also true for the mir-181 family [33]. Analyses of target genes regulated by miR-181 family suggest that they are mainly involved in biological processes including DNA binding, transcription and translation regulation, signaling transduction. This shows that this ancient gene family may be closely associated with cellular division, cellular differentiation, ontogeny, development of nervous and immune system. Further study of functions of target genes regulated by mir-181 in genetic interaction network is of great significance to better understanding the mechanisms of some disease and drug development [34].

5. Conclusion In this study we found that this miRNA gene family was conserved among vertebrate species but was absent in invertebrates other than one of the urochordata species. Phylogenetic analysis indicated that the family members in vertebrates derived from two rounds of whole genome duplication during vertebrate evolution and was accompanied by the fragmental replication. Functional annotation of the targets of mir-181 family indicated that this family could participate in some important biological processes, which highlighted their functional importance.

Conflict of interests The authors declare that they have no conflict of interests.

Acknowledgments This work was supported by the China Postdoctoral Science Foundation [2013M530178], and International Science and Technology Cooperation Projects (2010DFA31840 and 2010DFB33720), the National Natural Science Foundation of China [30970623 and 91229120]. Program for New Century Excellent Talents in University (NCET-11–0288), and Beijing Natural Science Foundation (5112030).

Appendix A. Supporting information Supplementary data associated with this article can be found in the online version at http://dx.doi.org/10.1016/j.compbiomed. 2014.06.004. References [1] D.P. Bartel, MicroRNAs: genomics, biogenesis, mechanism, and function, Cell 116 (2004) 281–297. [2] L. He, G.J. Hannon, MicroRNAs: small RNAs with a big role in gene regulation, Nat. Rev. Genet. 5 (2004) 522–531. [3] S. He, Z. Yang, G. Skogerbo, F. Ren, H. Cui, et al., The properties and functions of virus encoded microRNA, siRNA, and other small noncoding RNAs, Crit. Rev. Microbiol. 34 (2008) 175–188. [4] I. Alvarez-Garcia, E.A. Miska, MicroRNA functions in animal development and human disease, Development 132 (2005) 4653–4662. [5] J. Hertel, M. Lindemeyer, K. Missal, C. Fried, A. Tanzer, et al., The expansion of the metazoan microRNA repertoire, BMC Genomics 7 (2006) 25. [6] R. Zhang, Y.Q. Wang, B. Su, Molecular evolution of a primate-specific microRNA family, Mol. Biol. Evol. 25 (2008) 1493–1502. [7] I. Naguibneva, M. Ameyar-Zazoua, A. Polesskaya, S. Ait-Si-Ali, R. Groisman, et al., The microRNA miR-181 targets the homeobox protein Hox-A11 during mammalian myoblast differentiation, Nat. Cell Biol. 8 (2006) 278–284. [8] L. Shi, Z. Cheng, J. Zhang, R. Li, P. Zhao, et al., Hsa-mir-181a and hsa-mir-181b function as tumor suppressors in human glioma cells, Brain Res. 1236 (2008) 185–193. [9] M. Ashburner, C.A. Ball, J.A. Blake, D. Botstein, H. Butler, et al., Gene ontology: tool for the unification of biology. The Gene Ontology Consortium, Nat. Genet. 25 (2000) 25–29. [10] M. Kanehisa, S. Goto, S. Kawashima, Y. Okuno, M. Hattori, The KEGG resource for deciphering the genome, Nucleic Acids Res. 32 (2004) D277–D280. [11] S. Griffiths-Jones, H.K. Saini, S. van Dongen, A.J. Enright, miRBase: tools for microRNA genomics, Nucleic Acids Res. 36 (2008) D154–D158. [12] W.J. Kent, BLAT – the BLAST-like alignment tool, Genome Res. 12 (2002) 656–664. [13] P.P. Chan, A.D. Holmes, A.M. Smith, D. Tran, T.M. Lowe, The UCSC archaeal genome browser: 2012 update, Nucleic Acids Res. 40 (2012) D646–D652. [14] M. Zuker, Mfold web server for nucleic acid folding and hybridization prediction, Nucleic Acids Res. 31 (2003) 3406–3415. [15] R.C. Edgar, MUSCLE: a multiple sequence alignment method with reduced time and space complexity, BMC Bioinf. 5 (2004) 113. [16] K. Tamura, J. Dudley, M. Nei, S. Kumar, MEGA4: molecular evolutionary genetics analysis (MEGA) software version 4.0, Mol. Biol. Evol. 24 (2007) 1596–1599. [17] A. Stamatakis, T. Ludwig, H. Meier, RAxML-III: a fast program for maximum likelihood-based inference of large phylogenetic trees, Bioinformatics 21 (2005) 456–463. [18] B.P. Lewis, I.H. Shih, M.W. Jones-Rhoades, D.P. Bartel, C.B. Burge, Prediction of mammalian microRNA targets, Cell 115 (2003) 787–798. [19] M. Kertesz, N. Iovino, U. Unnerstall, U. Gaul, E. Segal, The role of site accessibility in microRNA target recognition, Nat. Genet. 39 (2007) 1278–1284. [20] B. Zhang, S. Kirov, J. Snoddy, WebGestalt: an integrated system for exploring gene sets in various biological contexts, Nucleic Acids Res. 33 (2005) W741–W748. [21] Z. Yuan, X. Sun, D. Jiang, Y. Ding, Z. Lu, et al., Origin and evolution of a placental-specific microRNA family in the human genome, BMC Evol. Biol. 10 (2010) 346. [22] V. Olive, I. Jiang, L. He, Mir-17-92, a cluster of miRNAs in the midst of the cancer network, Int. J. Biochem. Cell Biol. 42 (2010) 1348–1354. [23] J. Yu, F. Wang, G.H. Yang, F.L. Wang, Y.N. Ma, et al., Human microRNA clusters: genomic organization and expression profile in leukemia cell lines, Biochem. Biophys. Res. Commun. 349 (2006) 59–68. [24] A. Grimson, M. Srivastava, B. Fahey, B.J. Woodcroft, H.R. Chiang, et al., Early origins and evolution of microRNAs and Piwi-interacting RNAs in animals, Nature 455 (2008) 1193–1197. [25] P. Dehal, J.L. Boore, Two rounds of whole genome duplication in the ancestral vertebrate, PLoS Biol. 3 (2005) e314.

Z. Yang et al. / Computers in Biology and Medicine 52 (2014) 82–87

[26] A. Sidow, Gen(om)e duplications in the evolution of early vertebrates, Curr. Opin. Genet. Dev. 6 (1996) 715–722. [27] Z. Yang, R. Miao, G. Li, Y. Wu, S.C. Robson, et al., Identification of recurrence related microRNAs in hepatocellular carcinoma after surgical resection, Int. J. Mol. Sci. 14 (2013) 1105–1118. [28] X. Zhao, Z. Yang, G. Li, D. Li, Y. Zhao, et al., The role and clinical implications of microRNAs in hepatocellular carcinoma, Sci. China Life Sci. 55 (2012) 906–919. [29] Z. Yang, F. Ren, C. Liu, S. He, G. Sun, et al., dbDEMC: a database of differentially expressed miRNAs in human cancers, BMC Genomics 11 (Suppl. 4) (2010) S5. [30] C. Yang, W. Wei, The miRNA expression profile of the uveal melanoma, Sci. China Life Sci. 54 (2011) 351–358.

87

[31] W. Feng, Y. Feng, MicroRNAs in neural cell development and brain diseases, Sci. China Life Sci. 54 (2011) 1103–1112. [32] Q. Shen, J. Fan, X.R. Yang, Y. Tan, W. Zhao, et al., Serum DKK1 as a protein biomarker for the diagnosis of hepatocellular carcinoma: a large-scale, multicentre study, Lancet Oncol. 13 (2012) 817–826. [33] J. Luo, M. Teng, J. Fan, F. Wang, L. Zhou, et al., Marek0 s disease virus-encoded microRNAs: genomics, expression and function, Sci. China Life Sci. 53 (2010) 1174–1180. [34] G. Li, R. Miao, H. Zhao, Progression and prospects of translational medicine in China, Sci. China Life Sci. 55 (2012) 1022–1025.