Open Access

New miRNAs cloned from neuroblastoma

  • Elena A Afanasyeva1,
  • Agnes Hotz-Wagenblatt2,
  • Karl-Heinz Glatting2 and
  • Frank Westermann1Email author
BMC Genomics20089:52

DOI: 10.1186/1471-2164-9-52

Received: 30 October 2007

Accepted: 29 January 2008

Published: 29 January 2008

Abstract

Background

MicroRNAs (miRNAs) are a novel class of gene expression regulators implicated in cancer biology. Neuroblastoma (NB) is an embryonal tumour consisting of neural crest-derived undifferentiated cells and is characterised by variable clinical courses ranging from spontaneous regression to therapy-resistant progression. Recent advances identified a subset of miRNAs with putative function in NB biology. However, the full repertoire of miRNAs expressed in NBs is not available.

Results

We describe miRNA profiles of 13 NB specimens and 2 NB cell lines as determined by miRNA cloning. A total of 3153 sequences were sequenced and analysed by a miRNA prediction tool (miRpredict). Our library covered 27% miRNAs known to date. 39 reads corresponding to 25 individual sequences were classified as novel miRNAs, including miRNA* species of 10 known miRNAs. Expression of 5 new miRNA* forms and 8 individual sequences was supported by Northern blotting. Most of the novel miRNA genes are not related to each other and do not share homology with the annotated sequences in the public miRNA database, but they are conserved within mammals or have close homologues in primates genomes.

Conclusion

We provide evidence for 29 new miRNA and miRNA-like sequences (24 novel sequences and 5 miRNAs discovered initially in other species). Some of these newly identified sequences reside within frequently altered chromosomal regions in NB tumours and may play a role in NB biology.

Background

Neuroblastoma is the second commonest solid cancer in young children accounting for 9% of all childhood cancers. It is characterised by a heterogeneous clinical behaviour ranging from spontaneous regression in 10% of all cases to rapid progression with unfavourable prognosis [1, 2]. Amplified MYCN leading to high MYCN mRNA and protein levels plays an important role in NB biology and is used as a powerful prognostic marker in NB risk stratification. In addition, several other genetic abnormalities, including gain of 17q, 11q and 1p deletion have been associated with an aggressive NB phenotype [3]. Further, microarray technology has been used to study gene expression profiles in primary NBs. Patterns of differentially expressed genes among different NB subtypes as well as gene expression classifiers have emerged allowing a better prediction of patient's outcome than established risk markers [4, 5].

MiRNAs that regulate gene expression at the posttranscriptional level have been described to play a role in carcinogenesis via executing oncogenic or tumour suppressive functions [68]. For example, let-7 miRNAs are down-regulated in lung cancer and are known to target proto-oncogene RAS transcripts [9]. Mir-17-92 cistron is to be overexpressed in human lung cancer and upregulated by c-Myc [10, 11]. miR-15 and miR-16 are frequently deleted and down-regulated in chronic lymphocytic leukemias [12]. The expression profiles of a small set of miRNAs could be used to classify different types of cancer [1315]. More recently, profiling of a subset of known miRNAs in neuroblastoma specimens suggested that MYCN acts as a regulator of miRNAs [16].

However, the full repertoire of miRNAs expressed in different cancer types, including neuroblastoma, is not yet available. Prognosis-relevant miRNAs with putative oncogenic functions could have been missed in previous cloning efforts due to their silent state or low-expression. There is evidence to date that neural lineage cells are particularly rich in miRNA diversity [1719]. In this study, we aimed at cloning novel miRNAs from NB cell lines and NB specimens that may have a role in NB biology. Here, we present the analysis of small RNA libraries derived from neuroblastoma tumour specimens and cell lines and suggest several novel miRNAs. Some of these miRNAs reside within loci of cancer-associated rearrangements and are of special interest for future studies.

Results and discussion

MiRNA cloning and abundance of previously annotated miRNAs

For NB miRNA library construction, we used RNA derived from 13 tumour samples as well as two neuroblastoma cell lines, SH-EP (MYCN single-copy) and Kelly (MYCN amplified). We followed the guidelines of Lau et al. ensuring that only those RNA species were cloned which contained 5'-phosphate [20]. The following cohort of tumours was used for cloning: four MYCN amplified, three stage 4S MYCN single-copy, two stage 4 MYCN single-copy and four stage 1 MYCN single-copy tumours (Table 1).
Table 1

MYCN status and stage of tumours

TUMOUR

STAGE*

MYCNamplification

MYCNAMP_NB1

1

+

MYCNAMP_NB2

3

+

MYCNAMP_NB3

3

+

MYCNAMP_NB4

4

+

MYCNSC_NB1

1

-

MYCNSC_NB2

1

-

MYCNSC_NB3

1

-

MYCNSC_NB4

1

-

MYCNSC_NB5

4S

-

MYCNSC_NB6

4

-

MYCNSC_NB7

4S

-

MYCNSC_NB8

4S

-

MYCNSC_NB9

4

-

* NB stage was evaluated according to INSS criteria

Approximately 80 clones per specimen or cell line were sequenced. After linker unmasking, 3185 small RNA cDNA sequences were subjected to further analyses. The percentage of "not-known-miRNA" sequences varied from 18% to 60% which corresponds to previously described fractions of other non-coding RNAs, redundant sequences as well as novel miRNAs in small RNA libraries [17, 21]. Our cloning project covered 27% (128 miRNAs) of miRNAs currently present in the public miRNA registry (miRBase 9.1) [22]. 39 miRNAs were represented by only one read. On the other hand, mir-124a (with three loci on 8p23.1, 8q12.3, 20q13.33) and -125b (11q24.1 and 21q21.1) yielded 113 and 132 reads, respectively (see Additional File 1). MiRNA cloning was established as an independent semi-quantitative method to evaluate miRNA abundance [23]. This allowed us to conclude that mir-124a and -125b were the most abundant ones. Both miRNAs are considered as having neuronal specificity [24, 25]. Among the most frequently identified miRNAs was mir-21 (17q23.2), a transcript with putative anti-apoptotic and tumour promoting activities [8]. A difference in the abundance of certain miRNAs was observed in MYCN-amplified and non-amplified specimens. In MYCN-amplified tumours/cell line, we observed a higher abundance of miRNAs from the mir-17/92 cluster (13q31.3) that is known to be up-regulated by c-Myc. The average numbers for hsa-mir-17-5p and hsa-mir-20a reads in MYCN-amplified and single-copy specimens were 5 versus 0.8 and 3.6 versus 0.6, respectively. A group of miRNA sequences that clustered on chromosome 19 was exclusively found in the library of the MYCN amplified tumour, MYCNAMP_NB2. This argues for a cistronic manner of transcription of this group of miRNA sequences. Beside annotated human miRNAs we have cloned 5 sequences that have been originally identified in rat and mouse (see Additional File 1).

Identification and validation of new miRNAs

After removing redundant sequences and the sequences derived from other non-coding RNAs, the remaining pool was checked in silico for the detection of the putative miRNA precursors using miRPredict (see Methods). This analysis yielded 25 distinct sequences (39 reads) which were classified as miRNAs. Of these 25 miRNAs, 10 sequences were miRNA* forms of previously annotated miRNA precursors (Table 2). Hsa-mir-594 was cloned by the Velculescu group, but then excluded from miRBase due to overlap with a tRNA gene [26]. Cloning of the 594* species described here provides evidence for the miRNA nature of these sequences.
Table 2

Novel human miRNA* sequences identified by cloning from NB

Sequence name

Sequence

Chromosomal location

Northern blot validation

Reads

Notes

HSA-MIR-188*

ctcccacatgcagggtttgca

Xp11.22

-

1

3'-arm

HSA-MIR-106b*

ccgcactgtgggtacttgctgc

7q22.1

+

5

3'-arm

HSA-MIR-423*

tgaggggcagagagcgaga

17q11.2

+

1

5'-arm

HSA-MIR-594*

cctaagccagggattgtgggtt

7q34

-

1

5'-arm

HSA-MIR-342*

aggggtgctatctgtgattgagg

11q32.2

+

1

5'-arm

HSA-MIR-490*

ccatggatctccaggtgggt

7q33

-

2

5'-arm

HSA-MIR-361*

cccccaggtgtgattctgatttg

Xq21.1

+

3

3'-arm

HSA-MIR-28*

cactagattgtgagctcctgga

3q28

-

1

3'-arm

HSA-MIR-127*

ctgaagctcagagggctctgat

14q32.31

-

1

5'-arm

HSA-MIR-214*

tgcctgtctacacttgctgtgca

1q24.3

+

2

5'-arm

Notes give the information which hairpin arm expresses the miRNA* form.

Other 15 sequences represent novel small RNAs which have not been annotated. Two novel sequences were found adjacent to chromosomal localisations of known miRNAs: MYCNSC_NB5_330 within a miRNA cluster on chromosome 14 as well as MYCNAMP_NB2_61 within a miRNA cluster on chromosome 19 (Table 3). Phylogenetic conservation was determined for each putative miRNA and its surrounding with respect to chimpanzee, macaque, opossum, mouse, rat, dog, bull and chicken genomes (see Additional File 2). We found that the cloned sequences with the exception of MYCNAMP_NB4_70 are conserved either within all chosen species or primates. The non-conserved MYCNAMP_NB4_70 sequence seems to be the result of a short duplication within an intron of the DPP10 transcript (Fig. 1). However, homologous regions in chimpanzee and macaque genomes are also able to form hairpins which might give rise to miRNAs. Novel miRNAs do not share any homology with each other and therefore do not comprise a family. Searching against miRBase revealed that none of the new miRNAs are related to the annotated miRNAs in miRBase, except of one sequence, MYCNAMP_NB2_5, that is homologous to hsa-mir-151 and -28. Analysis of genomic locations of the individual miRNAs showed that 5 of them are localized in extragenic regions. 8 sequences are found within introns of coding transcripts. MYCNSC_NB5_64, classified as a miRNA by miRpredict, is found within a predicted U5 gene which reduces reliability of this sequence as a miRNA (Table 3). The likely precursors of the novel miRNAs (Fig. 2) may be subdivided into two subgroups: structures with typical hairpin or borderline precursors. The latter subgroup has features divergent from a canonical miRNA hairpin, such as bulges (KELLY_276, MYCNSC_NB2_148), short stem (MYCNSC_NB5_41) or "oscillating" hairpin (MYCNAMP_NB4_70), where the candidate miRNA can reside on the 5' or 3'-arm. Lui et al. reported the cloning of a subset of non-canonical miRNAs, however the relevance of such RNAs to the classical miRNA pathway remains to be determined [27].
Table 3

Novel human miRNA sequences identified by cloning from NB

Sequence name

Sequence

Chromosomal location

Northern blot validation

Reads

Notes

MYCNAMP_NB2_5

aaggagcttacaatctagctggg

11q14.1

+

1

predicted gene

MYCNSC_NB2_148

acccagcaccccaggtttccacag

12q13.12

-

1

Tubulin-K-alpha-1

MYCNSC_NB5_330

taggacacatggtctacttct

14q32.31

+

1

within miRNA cluster

MYCNAMP_NB2_61

tcaaaactgaggggcattttct

19q13.42

+

4

within miRNA cluster

MYCNAMP_NB4_70

cctgtgttttgttggtagcctgtgttac

2q14.1

-

1

DPP10

MYCNSC_NB8_202

ccagacagaattctatgcactttc

3p12.3

-

1

KIAA0664

MYCNSC_NB5_41

tcaccccataaacacca

3p13

+

1

Extragenic

MYCNSC_NB5_281

tccattacactaccctgcctct

3p25.3

-

1

Plasma membrane calcium ATPase isoform 2

KELLY_276

tcgattcccacccctgacacca

4q13.1

+

1

Extragenic

MYCNSC_NB3_226

ctgccctggcccgagggaccga

5q31.2

-

1

Kelch-like-3

CONTIG_CHR_9

tgcaggaacttgtgagtctcc

9p21.1

+

4

Extragenic

MYCNSC_NB5_318

tggatttctttgtgaatca

9p21.1

+

1

Extragenic

MYCNAMP_NB2_241

cagggaggtgaatgtgat

Xq21.2

-

1

Extragenic

MYCNSC_NB5_64

aagctaattttttgaggcc

15q22.31

NA

1

U5 predicted, borderline case

MYCNSC_NB2_237

gatgatgctgctgatgctg

8p23.1

+

1

Pin2-interacting protein X1

Notes include the information about genomic locations and additional sequence information.

https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-9-52/MediaObjects/12864_2007_Article_1246_Fig1_HTML.jpg
Figure 1

MYCNAMP_NB4_70, a novel miRNA-like sequence resulting from a duplication event. Short sequences flanking MYCNAMP_NB4_70 were extracted from the human genome, as well as homologuous sequences from chimpanzee, macaque, mouse, rat and dog genomes and aligned. The bar indicates the MYCNAMP_NB4_70 sequence. The duplication is marked by a box.

https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-9-52/MediaObjects/12864_2007_Article_1246_Fig2_HTML.jpg
Figure 2

Predicted secondary structures of the putative novel human miRNA precursors. Human genomic sequences upstream and downstream of the novel miRNAs were folded with the computer program RNAfold. Grey areas represent the cloned miRNA. a) miRNA with canonical hairpin. b) borderline structures.

Based on the data listed above, we subjected 24 new miRNAs to Northern blot validation using biotinylated probes. Borderline case MYCNSC_NB5_64 sequences were not further examined. The expression of each putative miRNA was checked in a panel of human tissues, including different tumour specimens, normal brain, adrenal gland, spleen and skeletal muscle tissues. 5 of 10 cloned miRNA* sequences and 8 sequences from individual hairpins were Northern blot positive (Fig. 3). The other 11 sequences remained undetectable (data not shown). The probe for MYCNSC_NB5_41 yielded a signal around 30 nt which is higher than the estimated sequence size. The probes for CONTIG_CHR_9, MYCNSC_NB5_237 and MYCNAMP_NB2_5 yielded several bands different in length by 1–3 nucleotides. Some known miRNAs show such patterns in Northern blot analyses and intermediate products of miRNA maturation have been observed, but there is no comprehensive explanation for these results [19, 28, 29]. In normal tissues, Northern blot-positive miRNAs are preferentially expressed in brain, skeletal muscle tissue and adrenal gland, being less frequently expressed in spleen. The detection of miRNAs in skeletal muscle might be due to the presence of motor neurons. Several miRNAs showed differential expression in normal versus tumour specimens: CONTIG_CHR_9, KELLY_276, MYCNAMP_NB2_5 were expressed in tumours, but not in normal tissues. On the other hand, we did not find MYCNAMP_NB2_61 miRNA in tumour specimens, but we found strong expression of this sequence in brain.
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-9-52/MediaObjects/12864_2007_Article_1246_Fig3_HTML.jpg
Figure 3

Northern blot analysis of newly cloned miRNAs. N1...N10 – tumour samples; BR-Brain, AD-Adrenal gland, SK-Skeletal muscle, SP-Spleen. The positions of marker are indicated. U6 RNA was used as a loading control.

Conclusion

Recently, several studies have been performed aiming at directional cloning of tissue/tumour specific miRNAs [13, 26, 27]. The importance of such an approach is highlighted by the fact that patterns of novel miRNAs from tumours of different lineages hardly overlap and may include miRNAs with a functional role in tumourigenesis. Our study provides evidence for 29 new human miRNAs cloned from neuroblastoma. 5 of them were originally cloned from other species and have not been annotated in the human miRNA database. 10 sequences represent miRNA* species of previously annotated sequences. 14 sequences, which have not been annotated before, are suggested to be novel miRNAs. Some of these miRNAs are found within regions of chromosomal rearrangements associated with cancer. For example, new miRNAs on 9p21 residing within NB-related aberration region are of special interest for future studies [30]. miRNA profiling of these novel sequences will allow us to clarify their relevance in NB development, progression and regression.

Methods

Tumour specimens and cell culture

SH-EP and Kelly cells were cultured in RPMI supplemented with 10% fetal calf serum, glutamate and penicillin/streptomycin. NB tumour samples were collected prior to any cytoreductive treatment and were frozen immediately until RNA was isolated. Written informed consent was obtained from patients' parents for tissue sampling. Genomic MYCN status was assessed in the reference laboratories of the German NB trial in Köln and Heidelberg.

Small-RNA library construction and sequencing

Small-RNA fractions were directly isolated with the use of the mirVana miRNA Isolation Kit (Ambion). 18–26 nt RNA library construction was performed as described by Lau and coworkers [20]. Sequencing was performed by GATC BIOTECH (Konstanz, Germany).

Sequence analysis and prediction of novel miRNAs

Quality and vector trimming of sequences were performed with Vector NTI software. After unmasking linker sequences, inserts of ≥17 bp were analysed using miRPredict, a miRNA prediction pipeline [31]. miRPredict compares each potential miRNA to both known miRNAs and to other non-coding RNAs (EnsEMBL RNA database, Assembly 36) with a pattern-match algorithm using the EMBOSS program fuzznuc [32]. Sequences corresponding to other non-coding RNAs were discarded and the rest was localised in the genome via Blast search. The genomic hit together with additional 50 bases to both sides were extracted as potential precursor miRNA. In case that more than one localization in a contig was found, as indicated by equal score and expectation values of the BLAST search, all localizations were used for further processing. In the precursor DNA, palindromic structures are recognized by the program PALINDROME (EMBOSS package, allowing 4 mismatches in the stem, loop max. 40 bases, length between 15 and 50). If a palindrome was found, the palindromic region was folded with RNAFOLD (Vienna package) to get the energy value and the input file for the triplet SVM classifier [33, 34]. The triplet SVM determines the fold as miRNA-like palindrome (value +1), other palindrome (value -1) or regions with more than one loop (empty output).

To assess hairpin conservation, we extracted alignments of putative miRNA precursors from chimpanzee, macaque, mouse, rat, dog, cow, opossum and chicken genomes via EnsEMBL. Extracted sequences were checked for hairpin structures with the use of RNAfold, and aligned by RNAforester [35].

Northern blotting

Total RNA was isolated with TRIZOL reagent (Invitrogen). 30 micrograms of total RNA was loaded per lane and separated on 15% denaturing polyacrylamide gels, transferred by electroblotting to GeneScreen+ membranes (Perkin Elmer). To check for non-radioactive probe specificity, 250 pg of synthetic 5'-phosphorylated sequence identical to the respective miRNA was loaded along with 5'-phosphorylated marker sequences (20 + 30 nt, 250 pg each, see Additional Files 3 and 4). Blots were hybridized overnight at 37°C with radioactively α-(32P) labeled DNA oligo probes complementary to the cloned sequences in Church buffer, washed twice with 2 × SSC, 0.1% SDS at 37°C, and exposed to films (Fuji Film). For non-radioactive detection, blots were incubated with 3'-biotinylated probes (10 ng/ml) and then processed with North2 South Chemiluminescent Hybridization and Detection Kit (Pierce). Prolonged washing was applied after incubation with HRP-streptavidine conjugate.

Declarations

Acknowledgements

This work was supported with grants N2KR-S19T03 and 01GR0450 (to AHW) within NGFN-2 from the BMBF, "EET-pipeline" #037260 from the EU. The authors thank Larissa Savelyeva and Manfred Schwab for critical comments.

Authors’ Affiliations

(1)
Department of Tumour Genetics, B030, German Cancer Research Center
(2)
HUSAR Bioinformatics Laboratory, Department of Molecular Biophysics, B020, German Cancer Research Center

References

  1. Brodeur GM: Neuroblastoma: biological insights into a clinical enigma. Nat Rev Cancer. 2003, 3: 203-216. 10.1038/nrc1014.PubMedView ArticleGoogle Scholar
  2. Schwab M, Westermann F, Hero B, Berthold F: Neuroblastoma: biology and molecular and chromosomal pathology. Lancet Oncol. 2003, 4: 472-480. 10.1016/S1470-2045(03)01166-5.PubMedView ArticleGoogle Scholar
  3. Westermann F, Schwab M: Genetic parameters of neuroblastomas. Cancer Lett. 2002, 184: 127-147. 10.1016/S0304-3835(02)00199-4.PubMedView ArticleGoogle Scholar
  4. Wei JS, Greer BT, Westermann F, Steinberg SM, Son CG, Chen QR, Whiteford CC, Bilke S, Krasnoselsky AL, Cenacchi N, Catchpoole D, Berthold F, Schwab M, Khan J: Prediction of clinical outcome using gene expression profiling and artificial neural networks for patients with neuroblastoma. Cancer Res. 2004, 64: 6883-6891. 10.1158/0008-5472.CAN-04-0695.PubMedPubMed CentralView ArticleGoogle Scholar
  5. Berwanger B, Hartmann O, Bergmann E, Nielsen D, Krause M, Kartal A, Flynn D, Wiedemeyer R, Schwab M, Schafer H, Christiansen H, Eilers M: Loss of a FYN-regulated differentiation and growth arrest pathway in advanced stage neuroblastoma. Cancer Cell. 2002, 2: 377-386. 10.1016/S1535-6108(02)00179-4.PubMedView ArticleGoogle Scholar
  6. Brueckner B, Stresemann C, Kuner R, Mund C, Musch T, Meister M, Sultmann H, Lyko F: The human let-7a-3 locus contains an epigenetically regulated microRNA gene with oncogenic function. Cancer Res. 2007, 67: 1419-1423. 10.1158/0008-5472.CAN-06-4074.PubMedView ArticleGoogle Scholar
  7. Scott GK, Goga A, Bhaumik D, Berger CE, Sullivan CS, Benz CC: Coordinate suppression of ERBB2 and ERBB3 by enforced expression of micro-RNA miR-125a or miR-125b. J Biol Chem. 2007, 282: 1479-1486. 10.1074/jbc.M609383200.PubMedView ArticleGoogle Scholar
  8. Si ML, Zhu S, Wu H, Lu Z, Wu F, Mo YY: miR-21-mediated tumour growth. Oncogene. 2007, 25: 1-5.Google Scholar
  9. Johnson SM, Grosshans H, Shingara J, Byrom M, Jarvis R, Cheng A, Labourier E, Reinert KL, Brown D, Slack FJ: RAS is regulated by the let-7 microRNA family. Cell. 2005, 120: 635-647. 10.1016/j.cell.2005.01.014.PubMedView ArticleGoogle Scholar
  10. Hayashita Y, Osada H, Tatematsu Y, Yamada H, Yanagisawa K, Tomida S, Yatabe Y, Kawahara K, Sekido Y, Takahashi T: A polycistronic microRNA cluster, miR-17-92, is overexpressed in human lung cancers and enhances cell proliferation. Cancer Res. 2005, 65: 9628-9632. 10.1158/0008-5472.CAN-05-2352.PubMedView ArticleGoogle Scholar
  11. O'Donnell KA, Wentzel EA, Zeller KI, Dang CV, Mendell JT: c-Myc-regulated microRNAs modulate E2F1 expression. Nature. 2005, 435: 839-843. 10.1038/nature03677.PubMedView ArticleGoogle Scholar
  12. Calin GA, Dumitru CD, Shimizu M, Bichi R, Zupo S, Noch E, Aldler H, Rattan S, Keating M, Rai K, Rassenti L, Kipps T, Negrini M, Bullrich F, Croce CM: Frequent deletions and down-regulation of micro-RNA genes miR15 and miR16 at 13q14 in chronic lymphocytic leukemia. Proc Natl Acad Sci USA. 2002, 99: 15524-15529. 10.1073/pnas.242606799.PubMedPubMed CentralView ArticleGoogle Scholar
  13. Calin GA, Liu CG, Sevignani C, Ferracin M, Felli N, Dumitru CD, Shimizu M, Cimmino A, Zupo S, Dono M, Dell'Aquila ML, Alder H, Rassenti L, Kipps TJ, Bullrich F, Negrini M, Croce CM: MicroRNA profiling reveals distinct signatures in B cell chronic lymphocytic leukemias. Proc Natl Acad Sci USA. 2004, 101: 11755-11760. 10.1073/pnas.0404432101.PubMedPubMed CentralView ArticleGoogle Scholar
  14. Lee EJ, Gusev Y, Jiang J, Nuovo GJ, Lerner MR, Frankel WL, Morgan DL, Postier RG, Brackett DJ, Schmittgen TD: Expression profiling identifies microRNA signature in pancreatic cancer. Int J Cancer. 2007, 120: 1046-1054. 10.1002/ijc.22394.PubMedPubMed CentralView ArticleGoogle Scholar
  15. Mattie MD, Benz CC, Bowers J, Sensinger K, Wong L, Scott GK, Fedele V, Ginzinger D, Getts R, Haqq C: Optimized high-throughput microRNA expression profiling provides novel biomarker assessment of clinical prostate and breast cancer biopsies. Mol Cancer. 2006, 19: 5-24.Google Scholar
  16. Chen Y, Stallings RL: Differential patterns of microRNA expression in neuroblastoma are correlated with prognosis, differentiation, and apoptosis. Cancer Res. 2007, 67: 976-983. 10.1158/0008-5472.CAN-06-3667.PubMedView ArticleGoogle Scholar
  17. Berezikov E, Thuemmler F, van Laake LW, Kondova I, Bontrop R, Cuppen E, Plasterk RH: Diversity of microRNAs in human and chimpanzee brain. Nat Genet. 2006, 38: 1375-1377. 10.1038/ng1914.PubMedView ArticleGoogle Scholar
  18. Dostie J, Mourelatos Z, Yang M, Sharma A, Dreyfuss G: Numerous microRNPs in neuronal cells containing novel microRNAs. RNA. 2003, 9: 180-186. 10.1261/rna.2141503.PubMedPubMed CentralView ArticleGoogle Scholar
  19. Kim J, Krichevsky A, Grad Y, Hayes GD, Kosik KS, Church GM, Ruvkun G: Identification of many microRNAs that copurify with polyribosomes in mammalian neurons. Proc Natl Acad Sci USA. 2004, 101: 360-365. 10.1073/pnas.2333854100.PubMedPubMed CentralView ArticleGoogle Scholar
  20. Lau NC, Lim LP, Weinstein EG, Bartel DP: An abundant class of tiny RNAs with probable regulatory roles in Caenorhabditis elegans. Science. 2001, 294: 858-862. 10.1126/science.1065062.PubMedView ArticleGoogle Scholar
  21. Fu H, Tie Y, Xu C, Zhang Z, Zhu J, Shi Y, Jiang H, Sun Z, Zheng X: Identification of human fetal liver miRNAs by a novel method. FEBS Lett. 2005, 579: 3849-3854. 10.1016/j.febslet.2005.05.064.PubMedView ArticleGoogle Scholar
  22. MiRBase. [http://microrna.sanger.ac.uk/]
  23. Fulci V, Chiaretti S, Goldoni M, Azzalin G, Carucci N, Tavolaro S, Castellano L, Magrelli A, Citarella F, Messina M, Maggio R, Peragine N, Santangelo S, Mauro FR, Landgraf P, Tuschl T, Weir DB, Chien M, Russo JJ, Ju J, Sheridan R, Sander C, Zavolan M, Guarini A, Foa R, Macino G: Quantitative technologies establish a novel microRNA profile of chronic lymphocytic leukemia. Blood. 2007, 109: 4944-4951. 10.1182/blood-2006-12-062398.PubMedView ArticleGoogle Scholar
  24. Krichevsky AM, Sonntag KC, Isacson O, Kosik KS: Specific microRNAs modulate embryonic stem cell-derived neurogenesis. Stem Cells. 2006, 24: 857-864. 10.1634/stemcells.2005-0441.PubMedPubMed CentralView ArticleGoogle Scholar
  25. Lukiw WJ: Micro-RNA speciation in fetal, adult and Alzheimer's disease hippocampus. Neuroreport. 2007, 18: 297-300. 10.1097/WNR.0b013e3280148e8b.PubMedView ArticleGoogle Scholar
  26. Cummins JM, He Y, Leary RJ, Pagliarini R, Diaz LA, Sjoblom T, Barad O, Bentwich Z, Szafranska AE, Labourier E, Raymond CK, Roberts BS, Juhl H, Kinzler KW, Vogelstein B, Velculescu VE: The colorectal microRNAome. Proc Natl Acad Sci USA. 2006, 103: 3687-3692. 10.1073/pnas.0511155103.PubMedPubMed CentralView ArticleGoogle Scholar
  27. Lui WO, Pourmand N, Patterson BK, Fire A: Patterns of known and novel small RNAs in human cervical cancer. Cancer Research. 2007, 67: 6031-6043. 10.1158/0008-5472.CAN-06-0561.PubMedView ArticleGoogle Scholar
  28. Flynt AS, Li N, Thatcher EJ, Solnica-Krezel L, Patton JG: Zebrafish miR-214 modulates Hedgehog signaling to specify muscle cell fate. Nat Genet. 2007, 39: 259-263. 10.1038/ng1953.PubMedPubMed CentralView ArticleGoogle Scholar
  29. Lee Y, Jeon K, Lee JT, Kim S, Kim VN: MicroRNA maturation: stepwise processing and subcellular localization. EMBO J. 2002, 21: 4663-4670. 10.1093/emboj/cdf476.PubMedPubMed CentralView ArticleGoogle Scholar
  30. Mitelman F, Johansson B, Mertens F: Mitelman Database of Chromosome Aberrations in Cancer. 2007, [http://cgap.nci.nih.gov/Chromosomes/Mitelman]Google Scholar
  31. Hotz-Wagenblatt A, Meurer E, Glatting KH, Suhai S: MiRpredict: A miRNA prediction pipeline. Proceedings BIRD'07 conference: 12–14. 2007, March ; BerlinGoogle Scholar
  32. EnsEMBL RNA database, Assembly 36. [http://www.ensembl.org/]
  33. Hofacker IL: Vienna RNA secondary structure server. Nucleic Acids Res. 2003, 31: 3429-3431. 10.1093/nar/gkg599.PubMedPubMed CentralView ArticleGoogle Scholar
  34. Xue C, Li F, He T, Liu GP, Li Y, Zhang X: Classification of real and pseudo microRNA precursors using local structure-sequence features and support vector machine. BMC Bioinformatics. 2005, 6: 310-10.1186/1471-2105-6-310.PubMedPubMed CentralView ArticleGoogle Scholar
  35. Höchsmann M, Voss B, Giegerich R: Pure Multiple RNA Secondary Structure Alignments: A Progressive Profile Approach. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2004, 1: 53-62. 10.1109/TCBB.2004.11.PubMedView ArticleGoogle Scholar

Copyright

© Afanasyeva et al; licensee BioMed Central Ltd. 2008

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.