66 research outputs found
λ§μ΄ν¬λ‘RNA μν©μ±μ λμμ κ²½λ‘μ κ΄ν μ°κ΅¬
νμλ
Όλ¬Έ(λ°μ¬) -- μμΈλνκ΅λνμ : μμ°κ³Όνλν μλͺ
κ³ΌνλΆ, 2021.8. κΉλΉλ΄λ¦¬.λ§μ΄ν¬λ‘RNAλ μ μ μλ€μ λ°νμ μ‘°μ ν¨μΌλ‘μ¨ λ€μν μλ¬Όνμ λ° λ³λ¦¬νμ νμλ€μ λ΄λΉνλ€. μΈν¬ μ νλ³λ‘ λ§μ΄ν¬λ‘RNAμ μμ΄ μμ΄νκ² λ€λ₯Έλ°, μ΄λ μ μ¬ μ‘°μ κ³Ό μ μ¬ ν μ‘°μ μ ν΅ν μν©μ± μ‘°μ μ κΈ°μΈνλ€. λ§μ΄ν¬λ‘RNA μν©μ± κ²½λ‘λ λ€μν κ³Όμ μ κ±Έμ³ μ΄λ£¨μ΄μ§λλ°, κ·Έ κ²°κ³Ό 머리ν λͺ¨μμ ꡬ쑰λ₯Ό ν¬ν¨νλ κΈ°λ€λ 1μ°¨ μ ꡬ체 RNAλ‘λΆν° λ¨μΌ κ°λ₯μ 짧μ λ§μ΄ν¬λ‘RNAκ° μμ±λλ€. νΉν, λ§μ΄ν¬λ‘RNA μν©μ±μλ λ€μν λμμ κ²½λ‘λ€μ΄ μ‘΄μ¬νλλ°, κ·Έλ‘ μΈν΄ λμΌν μ ꡬ체 RNAλ‘λΆν° μλ‘ λ€λ₯Έ λ§μ΄ν¬λ‘RNAλ€μ΄ λ§λ€μ΄μ§λ€. λ°λΌμ λμμ κ²½λ‘λ€μ λ§μ΄ν¬λ‘RNAμ λ€μμ±μ μ¦κ°μν€κ³ κΈ°λ₯μ νλνλλ° μμκ° μλ€. νμ§λ§ μ΄λ€ λ§μ΄ν¬λ‘RNAκ° λμμ κ²½λ‘μ μν΄ μμ±λλμ§ μ μ¬μ²΄ν μμ€μμ μλ €μ§ λ°κ° μλ€. λ λμμ κ²½λ‘λ€μ κ΄ν μ‘°μ μ΄ μ μλ €μ Έ μμ§ μλ€.
λ¨Όμ λ³Έ μ°κ΅¬μμλ λνμ μΈ λμμ κ²½λ‘μΈ βλμμ μ λ¨βκ³Ό βμ 리λν νμβμ κ΄ν΄ μ‘°μ¬νμλ€. λ νμμ λ§μ΄ν¬λ‘RNAμ 5β² λ° 3β² λ§λ¨μ λ³νλ₯Ό κ°νλλ°, μ΄λ λ§μ΄ν¬λ‘RNAμ κΈ°λ₯μ λ°κΎΈκ±°λ μμ μ‘°μ ν μ μλ€. λ§μ΄ν¬λ‘RNA μμ΄ λΆμλ²μ μ¬μ μ 보 μμ΄λ λ§μ΄ν¬λ‘RNAμ κ·Έ λν체λ€μ μμλΌ μ μμ΄ μ μ¬μ²΄ν μμ€μμ λ§μ΄ν¬λ‘RNAλ₯Ό μ°κ΅¬νλλ° λ리 μ΄μ©λμ΄ μλ€. νμ§λ§ κΈ°μ‘΄μ λ°©λ²μ μ¬κ°ν νΈν₯μ±μ κ°μ§κ³ μμ΄μ λ§μ΄ν¬λ‘RNAμ λμμ κ²½λ‘λ₯Ό μ‘°μ¬νκΈ°μλ λΆμ μ νμλ€. λ°λΌμ λ³Έ μ°κ΅¬μμλ κ·Έ νΈν₯μ±μ μ΅μννκΈ° μν΄ λ¬΄μμμ μμ΄μ μ§λ μ΄λν°μ ν΄λ¦¬μνΈλ κΈλ¦¬μ½μ μ¬μ©νμ¬ μ‘°κ±΄μ μ΅μ ννμκ³ , κ·Έ κ²°κ³Ό AQ-seqμ΄λΌλ μλ‘μ΄ λ§μ΄ν¬λ‘RNA μμ΄ λΆμλ²μ κ°λ°νμλ€. AQ-seqμ κ°λ₯ λΉμ¨μ μ νν μΈ‘μ ν μ μμ λΏλ§ μλλΌ κΈ°μ‘΄μ μλͺ» μλ €μ§ 5β² λ§λ¨μ μ ννκ² νμ§ν μ μλ€. μ΄λ¬ν μ΄μ λλΆμ AQ-seqμ μΈν¬ λ΄μμ μΌμ΄λλ λμμ μ λ¨ κ³Όμ μ΄ κΈ°μ‘΄μ μλ €μ§ κ²λ³΄λ€ λ λΉλ²νκ² μΌμ΄λλ€λ κ²μ λ°ν μ μμλ€. λΏλ§ μλλΌ, AQ-seqμ μ΄μ©νμ¬ λμ λΉμ¨λ‘ μ 리λνλλ λ§μ΄ν¬λ‘RNAλ€μ λμ ν μ μμλλ°, λͺ¨λ 3p κ°λ₯μμ μ λνλ€λ μ μ λΉμΆμ΄ 보μμ λ μ 리λν νμμ TUT4μ TUT7 λ¨λ°±μ§λ€μ μν΄ 2μ°¨ μ ꡬ체 λ¨κ³μμ μ£Όλ‘ μΌμ΄λλ€λ μ μ νμΈν μ μλ€. μ΄λ¬ν κ²°κ³Όλ€μ ν΅ν΄ μΈν¬ λ΄μμ λ§μ΄ν¬λ‘RNAκ° μΌλ§λ 볡μ‘νκ² κ΅¬μ±λμ΄ μλμ§ μ μ μκ³ , λ°λΌμ λ§μ΄ν¬λ‘RNA μν©μ±μ λμμ κ²½λ‘μ λν μ΄ν΄λλ₯Ό λμΌ μ μλ€.
λ€μμΌλ‘, λ³Έ μ°κ΅¬μμλ λ λ€λ₯Έ λμμ κ²½λ‘μΈ κ°λ₯ λ³νμ κ΄ν΄ μ‘°μ¬νμλ€. κ°λ₯ μ ν κ³Όμ μ λ§μ΄ν¬λ‘RNA μ΄μ€μ²΄μ λ κ°λ₯ μ€ μ΄λ κ²μ΄ μ΅μ’
μ μΌλ‘ κΈ°λ₯νλμ§λ₯Ό κ²°μ νλ λ§€μ° μ€μν λ¨κ³μ΄λ€. ν₯λ―Έλ‘κ²λ, μΈν¬ νΉμ±μ λ°λΌ μ νλλ κ°λ₯μ΄ ν¬κ² λ€λ°λ μ μλλ° μ΄λ₯Ό βκ°λ₯ λ³νβμ΄λΌ μΌμ»«λλ€. κ°λ₯ λ³νμ ν΄λΉ λ§μ΄ν¬λ‘RNA μ μ μμ κΈ°λ₯μ μμ ν λ°κΏ μ μμ§λ§ κ·Έκ²μ΄ μ΄λ»κ² μ‘°μ λλμ§μ λν΄μλ μλ €μ Έ μμ§ μλ€. κ²λ€κ° κ·Έκ²μ μ리νμ μλ―Έλ μ μλ €μ Έ μμ§ μλ€. λ³Έ μ°κ΅¬μμλ κ°μ₯ λλλ¬μ§κ² κ°λ₯ λ³νμ 보μ΄λ λ§μ΄ν¬λ‘RNA μ€ νλλ‘ miR-324λ₯Ό λ°κ²¬νμλ€. λΏλ§ μλλΌ miR-324μ κ°λ₯ λ³νμ μ 리λν ν¨μλ€μΈ TUT4μ TUT7μ΄ μ‘°μ νλ€λ κ²μ κ·λͺ
νμλ€. TUT4/7μ μν΄ miR-324μ 2μ°¨ μ κ΅¬μ²΄κ° μ 리λνλλ©΄ λ€μ΄μ ν¨μμ μ λ¨ μμΉκ° λ°λκ² λλ€. κ·Έ κ²°κ³Ό λ§λ€μ΄μ§λ λ§μ΄ν¬λ‘RNA μ΄μ€μ²΄λ 3p κ°λ₯μ μμ±νλ λ°λ©΄, μ 리λνκ° μΌμ΄λμ§ μμμ λ λ§λ€μ΄μ§λ μ΄μ€μ²΄λ λ°λλ‘ 5p κ°λ₯μ μμ±νλ€. ν₯λ―Έλ‘κ²λ, κ΅λͺ¨μΈν¬μ’
μμλ TUT4/7μ μμ΄ μ¦κ°νλ€λ κ²μ λ°κ²¬νμλλ° κ·Έλ‘ μΈν΄ miR-324μ 3p κ°λ₯ λν μ¦κ°νλ€λ κ²μ κ΄μ°°νμλ€. μ΄λ₯Ό μμ©νμ¬, μμΌλ‘ miR-324μ 5p κ°λ₯μ λ리거λ 3p κ°λ₯μ μ΅μ νλ©΄ κ΅λͺ¨μΈν¬μ’
μ μΈν¬ λΆμ΄μ μ ν΄ν μ μμλ€. λ°λΌμ λ³Έ μ°κ΅¬λ κ°λ₯ λ³ν νμμ΄ μ 리λνμ μν΄ μ‘°μ λ μ μλ€λ κ²μ λ°νκ³ μ΄λ₯Ό κ΅λͺ¨μΈν¬μ’
μ μ§λ¨ λ° μΉλ£ λͺ©μ μΌλ‘ μμ©λ μ μμμ 보μ¬μ€λ€.
μ’
ν©νλ©΄ λ³Έ μ°κ΅¬λ λμμ κ²½λ‘μ μν΄ μμ±λλ λ§μ΄ν¬λ‘RNAλ€μ λ³΄λ€ μ ννκ² λ°κ΅΄νμλ€. μ΄ κ²°κ³Όλ₯Ό ν΅ν΄ λμμ κ²½λ‘λ€μ΄ μΈν¬ λ΄μμ κ΄λ²μνκ² μΌμ΄λλ©΄μ λ§μ΄ν¬λ‘RNAλ€μ κΈ°λ₯μ μ‘°μ νλ€λ κ²μ μ μ μμλ€. κ²λ€κ° λμμ μ λ¨, μ 리λν νμ λΏλ§ μλλΌ κ°λ₯ λ³ν λν μ‘°μ λ μ μλ νμμμ λ°νλ€. λ°λΌμ λ³Έ μ°κ΅¬λ λμμ κ³Όμ μ μν΄ μ΄λ»κ² λ§μ΄ν¬λ‘RNAλ€μ΄ μ κ΅νκ² λ§λ€μ΄μ§λμ§μ κ΄ν΄ κ·Έ λΆμμ κΈ°μ κ³Ό μ€μμ±μ μ‘°λͺ
νλ€.MicroRNAs (miRNAs) modulate diverse biological and pathological processes via post-transcriptional gene silencing. The repertoire of functional miRNAs substantially varies depending on the cell types due to the regulations of miRNA biogenesis at the transcriptional and post-transcriptional levels. miRNA biogenesis involves serial maturation steps to produce single-stranded miRNAs from a hairpin-containing primary transcript. Notably, there are alternative pathways along the miRNA biogenesis, which lead to generation of multiple miRNAs from a single miRNA gene. Alternative miRNA biogenesis increases miRNA diversity and hence expands their regulatory capacity. Despite its profound effect on gene regulation, it is largely unknown which set of miRNAs undergoes alternative miRNA biogenesis and how alternative biogenesis is achieved.
First, this study investigates two alternative pathways, alternative processing and 3β² end modification of miRNAs, which produce miRNA isoforms with varying 5β² and 3β² ends. Alteration of miRNA termini affects abundance and targeting capacity of miRNAs. High-throughput small RNA sequencing (sRNA-seq) has been widely adopted to detect miRNAs and their isoforms (isomiRs) de novo. However, the severe ligation bias inherent to conventional sRNA-seq methods hampers their accurate quantification and hence reliable profiling of the alternative pathways. I here developed an improved sRNA-seq protocol, termed AQ-seq (accurate quantification by sequencing), by utilizing adapters with terminal degenerate sequences and a high concentration of polyethylene glycol (PEG) which minimize the ligation bias during library preparation. Measurement using AQ-seq allows us to correct the previously misannotated 5β² end usage as well as strand preference in public databases. Importantly, the analysis of 5β² terminal heterogeneity reveals widespread alternative processing events which have been underestimated. It also identifies highly uridylated miRNAs originating from the 3p strands, indicating regulations mediated by terminal uridylyl transferases at the pre-miRNA stage. These results reveal the complexity of the miRNA isoform landscape, allowing us to refine miRNA annotation and to advance our understanding of miRNA biogenesis.
Next, this study examines another alternative pathway, context-dependent strand selection of miRNAs. Strand selection is the last step of miRNA biogenesis, which determines the functional strand. Intriguingly, the dominant strand of some miRNAs changes depending on cellular contexts. However, the molecular mechanism and physiological significance of such alternative strand selection (or βarm switchingβ) remain elusive. Here, I find miR-324 to be one of the strongly regulated miRNAs by arm switching, and identify terminal uridylyl transferases TUT4 and TUT7 to be the key regulators. Uridylation of pre-miR-324 by TUT4/7 re-positions DICER on pre-miRNA and shifts the cleavage site. This alternative processing produces a duplex with a different terminus, from which the 3β² strand (3p) is selected instead of the 5β² strand (5p). In glioblastoma, the TUT4/7 and 3p levels are upregulated while the 5p level is reduced. Manipulation of the strand ratio is sufficient to impair glioblastoma cell proliferation. These results uncover a role of uridylation as a molecular switch in alternative strand selection and implicate its therapeutic potential.
Taken together, this study unveils miRNAs that are generated by alternative miRNA biogenesis at a transcriptome-wide scale. Notably, my extensive investigation reveals that the alternative pathways are widespread and hence significantly affect the functionality of miRNAs. It also shows that not only alternative processing and 3β² modification but also arm switching can be a regulated cellular process. Therefore, this study sheds light on the mechanism and significance of alternative miRNA biogenesis.1 Introduction 1
1.1 MicroRNA, a class of small silencing RNAs 1
1.2 Metazoan microRNA biogenesis 2
1.3 Alternative microRNA biogenesis 5
1.3.1 Alternative processing by RNase III enzymes, DROSHA and DICER 5
1.3.2 Non-templated 3β² nucleotidyl addition by terminal uridylyl transferases, TUT4 and TUT7 7
1.3.3 Alternative strand selection (or βarm switchingβ) by AGO 9
2 Discovery of widespread alternative microRNA processing and 3β² end modification by bias-minimized small RNA-seq 11
2.1 Background 11
2.2 Results 14
2.2.1 Small RNA sequencing optimization using spike-ins 14
2.2.2 miRNA and isomiR profiles uncovered by AQ-seq 17
2.2.3 Re-assessment of strand preference 22
2.2.4 Correction of the 5β² end annotation 27
2.2.5 Widespread alternative processing 29
2.2.6 Highly uridylated miRNAs 31
2.3 Discussion 40
2.4 Methods 43
3 A mechanism for microRNA arm switching regulated by uridylation 51
3.1 Background 51
3.2 Results 54
3.2.1 Arm switching of miR-324 54
3.2.2 miR-324 arm switching is controlled by TUT4 and TUT7 58
3.2.3 Uridylation leads to alternative DICER processing of pre-miR-324 66
3.2.4 Alternative DICER processing is facilitated by the double-stranded RNA binding domain (dsRBD) 69
3.2.5 Alternative DICER processing leads to arm switching 75
3.2.6 Alteration of the miR-324 strand ratio affects cell cycle progression 77
3.3 Discussion 87
3.4 Methods 91
4 Conclusion 101
Summary (in Korean) 103
Bibliography 105λ°
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νμ μλμ μ΄λ¬ν κ°λ
μ ν΅ν μ£Όκ±°μ ν μ§μ μΈ μΈ‘λ©΄μ λν μ¬μ€μ μ°κ΅¬(descriptive study) μ΄λ€. λ°λΌμ μ΄κ²μ μ£Όνμ μ±
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ν λ§λ€κΈ°, μ‘°μ¬λͺ©νμ μ§μ μ μ΄ν΄λ³΄μλ€
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μ μΌλ§λ λλμ§ κ·Έλ¦¬κ³ μ§μ
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μ΅κ·Ό μ²λ μΈ΅ μ€μ λ¬Έμ μ μΈμ μμκ°λ° λ°©ν₯(Youth unemployment and policy of human resource development in Korea)
The IMF crisis which started late in 1997 caused massive unemployment in Korea. The crisis placed a high toll on young workers, especially on those at age between 25 and 29. However, even after the crisis, the high unemployment rate of young workers persisted.
This study addresses the issue of high unemployment of younf workers in Kora. It argues that the Human capital theory(Becker, 1975) and Institutional Theory(Coase, 1965North, 1996) based on the Neo-classical economic perspective can offer only limited explanations on the unemployment of young workers in Korea. But, the New institutionalism Analysis(Granovetter, 1985Kim Hae-dong, 1995) perpective which focuses on the socio-cultural and institutional aspects provides a better explanation for high unemployment of young workers in Korea.
The recently observed high unemployment of young workers is not a cyclical unemployment, which should wither away if the economy picks up. But, it is a long-trem phenomenon, which should be systematically dealt with.
As a solution to deal with the current high unemployment of young workers, the study suggests improvement of the current vocational education and training system. Improving the current vocational education and training system for the young workers is very important in this knowledge based-economy. In particular, we need to improve the according to their skill levels and updated education and training according to the technological changesso that young workers can choose education and training programs according to their skill levels, starting from education and training programs for low-level skilled workers and moving to those for highly skilled workers
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μ΄λΌκ³ μκ°λλ λ°μ κ²μ μν(test)νμ¬ λ³΄μμ κ·Έκ²μ νλΉμ±μ΄ νμΈλλ©΄μ μ μ±
μ΄λΌκ³ μκ°λλ λ°μ κ²μ΄ κ·Έ λ¬Έμ μ λν μ μ±
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