Discovery and characterization of medaka miRNA genes by next generation sequencing platform View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2010-12-02

AUTHORS

Sung-Chou Li, Wen-Ching Chan, Meng-Ru Ho, Kuo-Wang Tsai, Ling-Yueh Hu, Chun-Hung Lai, Chun-Nan Hsu, Pung-Pung Hwang, Wen-chang Lin

ABSTRACT

BackgroundMicroRNAs (miRNAs) are endogenous non-protein-coding RNA genes which exist in a wide variety of organisms, including animals, plants, virus and even unicellular organisms. Medaka (Oryzias latipes) is a useful model organism among vertebrate animals. However, no medaka miRNAs have been investigated systematically. It is beneficial to conduct a genome-wide miRNA discovery study using the next generation sequencing (NGS) technology, which has emerged as a powerful sequencing tool for high-throughput analysis.ResultsIn this study, we adopted ABI SOLiD platform to generate small RNA sequence reads from medaka tissues, followed by mapping these sequence reads back to medaka genome. The mapped genomic loci were considered as candidate miRNAs and further processed by a support vector machine (SVM) classifier. As result, we identified 599 novel medaka pre-miRNAs, many of which were found to encode more than one isomiRs. Besides, additional minor miRNAs (also called miRNA star) can be also detected with the improvement of sequencing depth. These quantifiable isomiRs and minor miRNAs enable us to further characterize medaka miRNA genes in many aspects. First of all, many medaka candidate pre-miRNAs position close to each other, forming many miRNA clusters, some of which are also conserved across other vertebrate animals. Secondly, during miRNA maturation, there is an arm selection preference of mature miRNAs within precursors. We observed the differences on arm selection preference between our candidate pre-miRNAs and their orthologous ones. We classified these differences into three categories based on the distribution of NGS reads. Finally, we also investigated the relationship between conservation status and expression level of miRNA genes. We concluded that the evolutionally conserved miRNAs were usually the most abundant ones.ConclusionsMedaka is a widely used model animal and usually involved in many biomedical studies, including the ones on development biology. Identifying and characterizing medaka miRNA genes would benefit the studies using medaka as a model organism. More... »

PAGES

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Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/1471-2164-11-s4-s8

DOI

http://dx.doi.org/10.1186/1471-2164-11-s4-s8

DIMENSIONS

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PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/21143817


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33 schema:description BackgroundMicroRNAs (miRNAs) are endogenous non-protein-coding RNA genes which exist in a wide variety of organisms, including animals, plants, virus and even unicellular organisms. Medaka (Oryzias latipes) is a useful model organism among vertebrate animals. However, no medaka miRNAs have been investigated systematically. It is beneficial to conduct a genome-wide miRNA discovery study using the next generation sequencing (NGS) technology, which has emerged as a powerful sequencing tool for high-throughput analysis.ResultsIn this study, we adopted ABI SOLiD platform to generate small RNA sequence reads from medaka tissues, followed by mapping these sequence reads back to medaka genome. The mapped genomic loci were considered as candidate miRNAs and further processed by a support vector machine (SVM) classifier. As result, we identified 599 novel medaka pre-miRNAs, many of which were found to encode more than one isomiRs. Besides, additional minor miRNAs (also called miRNA star) can be also detected with the improvement of sequencing depth. These quantifiable isomiRs and minor miRNAs enable us to further characterize medaka miRNA genes in many aspects. First of all, many medaka candidate pre-miRNAs position close to each other, forming many miRNA clusters, some of which are also conserved across other vertebrate animals. Secondly, during miRNA maturation, there is an arm selection preference of mature miRNAs within precursors. We observed the differences on arm selection preference between our candidate pre-miRNAs and their orthologous ones. We classified these differences into three categories based on the distribution of NGS reads. Finally, we also investigated the relationship between conservation status and expression level of miRNA genes. We concluded that the evolutionally conserved miRNAs were usually the most abundant ones.ConclusionsMedaka is a widely used model animal and usually involved in many biomedical studies, including the ones on development biology. Identifying and characterizing medaka miRNA genes would benefit the studies using medaka as a model organism.
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40 schema:keywords ABI SOLiD platform
41 BackgroundMicroRNAs
42 NGS
43 RNA genes
44 RNA sequences
45 ResultsIn
46 abundant ones
47 analysis
48 animals
49 arm selection preference
50 aspects
51 biology
52 biomedical studies
53 candidate miRNAs
54 candidates
55 categories
56 characterization
57 classifier
58 clusters
59 conservation status
60 depth
61 development biology
62 differences
63 discovery
64 discovery studies
65 distribution
66 expression levels
67 generation sequencing platforms
68 generation sequencing technology
69 genes
70 genome
71 genomic loci
72 high-throughput analysis
73 improvement
74 isomiRs
75 levels
76 loci
77 machine classifier
78 maturation
79 mature miRNAs
80 medaka
81 medaka genome
82 medaka tissues
83 miRNA cluster
84 miRNA genes
85 miRNA maturation
86 miRNAs
87 model animals
88 model organisms
89 next-generation sequencing platforms
90 next-generation sequencing technologies
91 one
92 organisms
93 plants
94 platform
95 position
96 pre-miRNAs
97 precursors
98 preferences
99 relationship
100 results
101 selection preferences
102 sequence
103 sequencing depth
104 sequencing platforms
105 sequencing technologies
106 sequencing tools
107 small RNA sequences
108 solid platform
109 status
110 study
111 support vector machine classifier
112 technology
113 tissue
114 tool
115 unicellular organisms
116 useful model organism
117 variety
118 vector machine classifier
119 vertebrate animals
120 virus
121 wide variety
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