Degradome Sequencing for Plant microRNA Target Identificationlcsciences.com/documents/degradome-sequencing-webinar.pdf · 2013. 4. 2. · microRNAs ‐What We Know 1. All miRNAs are

Degradome Sequencing for Plant

microRNA Target Identification04‐2‐13

Qi Zhu, PhDSenior Scientist

Agendag

Target Identification

miRNA in Plants

Degradome Sequencing

Q & A

Case Studies

Q

microRNAs ‐What We Know1. All miRNAs are small non‐coding RNAs, usually consisting of 20–22

nucleotides for animals and 20–24 nt for plants.

22. All miRNA precursors have a well‐predicted stem loop hairpin structure, and this fold‐back hairpin structure has a low free energy

3 Many miRNAs are evolutionarily conserved some from worm to human3. Many miRNAs are evolutionarily conserved, some from worm to human, or from ferns to core eudicots or monocots in plants

4. Bind to complementary mRNA molecules and act as negative regulators of translation

5. Present in high copy number6. Expression is tissue (and developmental stage) specific

Challenge to the Central Dogma of BiologyChallenge to the Central Dogma of BiologyDNA > transcription > RNA > translation > protein

3

25000miRNAs in miRBase

20000

25000

21,264 miRBase Entries ‐ 193 plant, animal, and virus speciesmiRBase: microRNA sequences, targets and gene nomenclature.Griffiths‐Jones S et al. NAR 2006 34(Database Issue):D140‐D144 [article]

15000

20000

15000

Illumina Releases first small RNA10000 first small RNA Sample Prep Kit

5000

0V6.1 V7.1 V8.0 V8.1 V8.2 V9.0 V9.1 V9.2 V10.0 V10.1 V11.0 V12.0 V13.0 V14.0 V15.0 V16 V17 V18 V19

Apr‐05 Oct‐05 Feb‐06 May‐06 Jul‐06 Oct‐06 Feb‐07 May‐07 Aug‐07 Dec‐07 Apr‐08 Sep‐08 Mar‐09 Sep‐09 Apr‐10 Sep‐10 Apr‐11 Nov‐11 Aug‐12 4

http://nar.oxfordjournals.org/content/34/suppl_1/D140.full

miRNA function in plants1. miRNAs regulate plant development including: leaf development, floral

development, vegetative phase change, shoot and root development and vascular developmentvascular development

2. miRNAs are involved in signal transduction

3. miRNAs are involved in plant disease and resistance

4. miRNAs are involved in environmental stress responses: a variety of biotic and abiotic environmental stresses

5. miRNAs regulate miRNA and siRNA biogenesis and function

“Based on the sheer abundance and diversity of plant miRNAs, it is likely that most, if not all, biological processes in plants involve at some point the action of one or more miRNAs.”

• Voinnet O. 2009 Origin, biogenesis, and activity of plant microRNAs. Cell 136(4):669‐87.[article] 5

www.sciencedirect.com/science/article/pii/S0092867409001287

Why Study microRNA in Plants

1. Basic Research / Discovery ‐ Identification of novel miRNAs in various plant species / specific tissues and understanding their mechanism of action p p / p gand regulatory roles.

2. Stress Response – Identification of specific miRNA based markers that play essential roles in plant growth, development, and stress response.

3. Plant Breeding – Identification of miRNAs that regulate key traits such as hybrid vigor stress resistance could be useful for plant breeding andhybrid vigor, stress resistance, could be useful for plant breeding and environmental protection programs; Germplasm screening – identification of miRNA based signatures for cataloguing plant genotypes and accessions.

miRNA in Plants – Mechanism11. Near‐perfect complementarity to targets2. Upon binding to their mRNA targets, the miRNA‐containing RISCs function as

endonucleases cleaving the mRNAendonucleases, cleaving the mRNA

3. Cleavages are precisely guided between the 10th and 11th nucleotides in the complementary regions

Schematic representation of miRNA biogenesis and function inSchematic representation of miRNA biogenesis and function in plants.

1. The transcription of MIR genes gives rise to transcripts that contain an imperfectly paired hairpin region.

2. These transcripts are processed by the DCL1 ribonuclease, h d b h dperhaps assisted by the HEN1 and HYL1 proteins, into an

imperfectly paired dsRNA of about 21 nt that has 2‐nt 3′overhangs.

3. An unidentified helicase probably aids in the selection of the single strand (the miRNA, shown in orange) that is incorporated into the RISC.

4. Within the RISC, the miRNA serves as the specificity determinant to reduce target protein levels, either by cleavage of the target mRNA in the middle of the complementarity site or by repressing its productive translation.

Dugas DV, Bartel B. (2004) Curr Opin Plant Biol 7(5):512‐20. [abstract]P

7

www.sciencedirect.com/science/article/pii/S1369526604001037

1miRNA in Plants – Mechanism

1. miRNA mechanism is part of a complex web 2. A single miRNA might have several target genes and a single gene may be

regulated by many miRNAsregulated by many miRNAs.

3. Identification of these miRNA‐target pairs is crucial to understanding the biology of the miRNA regulatory mechanism.

Zhao et al. (2012) PLoS One 7(9):e44968. [article]

8

http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0044968

miRNA Sequencing

9

ACGT101 miRNA‐Seq Data Analysis0.1% ADT filter1.1% Junk filter0.1% Sequence pattern filter

4,332,045 total reads from base-calling pipeline analysis

6.2% rRNA 0.9% snRNA

1.7% snoRNA

ACGT101 miRNA‐Seq Data Analysis

98.5%mappable 41.0%

repbase

42.9%mRNA

7.3% tRNA

4,267,554 reads are mappable16,267 reads match to mRNA, RFam

(miR excluded), & RepBase

10.8% length 26 5.1% Unmapped

87.4%pass optional filter

94.9% mapped or candidate miRNAspass optional filter

58.8% (group 1)

10.1% (group 4)

30.3% (group 3)

0.9% (group 2)

1.8% copy #

miRNA in Plants Strategies for Target Identification

11. Bioinformatics2. qRT–PCR3. Western blot4. Luciferase reporter assays4. Luciferase reporter assays5. 5'‐Rapid amplification of cDNA ends (RACE) analyses66. Degradome Sequencing

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Bioinformatics

p‐TAREF(plant‐Target Refiner)

a Support Vector Regression (SVR) approach for plant miRNA target

Jha et al., 2011 http://sourceforge.net/projects/ptaref/

identification

psRNATarget a plant small RNA target analysis server

Dai et al., 2011 http://plantgrn.noble.org/psRNATarget/

Target‐align a tool for plant microRNA target identification

Xie et al., 2010 http://www.leonxie.com/targetAlign.php

TAPIR target prediction for plant Bonnet et al., http://bioinformatics.psb.ugent.be/webtool/ /microRNAs 2010 s/tapir/

miRU an automated plant miRNA target prediction server

Zhang 2005 http://bioinfo3.noble.org/miRU.htm

• Requires experimental Confirmation• False positives• False negative(miss some bona fide targets)

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Gene Specific MethodsGene Specific Methods

1. qRT–PCR, western blotwill not distinguish between direct and secondary miRNA targetswill not distinguish between direct and secondary miRNA targets

2. luciferase reporter assayslabor intensive

dependent upon the region chosen for cloning and

can be sensitive to variances in protocol such as the method of transfection

3. 5'‐rapid amplification of cDNA ends (RACE) analysesGene Specific

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miRNA in Plants


Strategies for Target IdentificationDegradome Sequencing

1. Degradome sequencing (also referred to as parallel analysis of RNA ends (PARE), a modified 5'‐rapid amplification of cDNA ends (RACE) with high‐th h t t ithroughput next‐gen sequencing.

2. In plants, microRNAs tend to cause cleavage of their targets at the position between nucleotides 10 and 11 of the microRNA

3. Degradome sequencing provides a comprehensive means of analyzing patterns of RNA degradation.

44. Next‐gen sequencing of the 5’ ends of RNA degradation products allows identification of over‐represented 5’ ends (microRNA cleavage sites)

5. Matching cleavage sites to known microRNA sequences links microRNAs to5. Matching cleavage sites to known microRNA sequences links microRNAs to their targets

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Demonstrated in many published studiesDegradome Sequencing

Demonstrated in many published studiesQiao‐Ying Z, Cun‐Yi Y, Qi‐Bin M, Xiu‐Ping L, Wen‐Wen D, Hai N. (2012) Identification of wild soybean miRNAs and their target genes responsive to aluminum stress. BMC Plant Biol 12(1), 182. [article]

Xu MY Dong Y Zhang QX Zhang L Luo YZ Sun J Fan YL Wang L (2012) Identification of miRNAs and theirXu MY, Dong Y, Zhang QX, Zhang L, Luo YZ, Sun J, Fan YL, Wang L. (2012) Identification of miRNAs and their targets from Brassica napus by high‐throughput sequencing and degradome analysis. BMC Genomics 13:421. [article]

An FM, Chan MT. (2012) Transcriptome‐wide characterization of miRNA‐directed and non‐miRNA‐directed d l l ti l i d d l i d l bi t t t i Ph l iendonucleolytic cleavage using degradome analysis under low ambient temperature in Phalaenopsis

aphrodite subsp. formosana. Plant Cell Physiol 53(10):1737‐50. [abstract]

Hao DC, Yang L, Xiao PG, Liu M. (2012) Identification of Taxus microRNAs and their targets with high‐throughput sequencing and degradome analysis. Physiol Plant 146(4):388‐403. [abstract]

Mao W, Li Z, Xia X, Li Y, Yu J. (2012) A combined approach of high‐throughput sequencing and degradome analysis reveals tissue specific expression of microRNAs and their targets in cucumber. PLoS One7(3):e33040. [article]

Zhang JZ Ai XY Guo WW Peng SA Deng XX Hu CG (2012) Identification of miRNAs and their target genesZhang JZ, Ai XY, Guo WW, Peng SA, Deng XX, Hu CG. (2012) Identification of miRNAs and their target genes using deep sequencing and degradome analysis in trifoliate orange Poncirus trifoliata L. Raf. Mol Biotechnol51(1):44‐57. [article]

Yang J, Liu X, Xu B, Zhao N, Yang X, Zhang M. (2013) Identification of miRNAs and their targets using high‐h h i d d d l i i l i l il d i i i f il lithroughput sequencing and degradome analysis in cytoplasmic male‐sterile and its maintainer fertile lines of Brassica juncea. BMC Genomics 14(1), [abstract]

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http://www.biomedcentral.com/content/pdf/1471-2229-12-182.pdfhttp://www.biomedcentral.com/content/pdf/1471-2164-13-421.pdfhttp://pcp.oxfordjournals.org/content/early/2012/08/17/pcp.pcs118.abstractonlinelibrary.wiley.com/doi/10.1111/j.1399-3054.2012.01668.x/abstracthttp://www.plosone.org/article/info:doi/10.1371/journal.pone.0033040link.springer.com/article/10.1007/s12033-011-9439-x?no-access=truehttp://www.biomedcentral.com/1471-2164/14/9/abstract


Extract Total RNA from Plants

Norgen Biotek

Total RNA Extraction KitTotal RNA Extraction Kit

Quality Control of RNA Sample

You can check the UV spectrum of your sample with a spectrophotometer.

↑ 1.0 ↑ 1.8 260nm

230

260nm

280230nm 280nm

16

Degradome SequencingLibrary Construction

Key Features & BenefitsKey Features & Benefits

Sample Input : Total RNA 100 μg 10 μg

Purification Method:Purification Method:Phenol/Ethanol based Bead based

PCR Cycles:1st PCR (10), 2nd PCR (12‐15) PCR (12‐15)

Gel Purification:3 times/1 Exp. 1 times/1 Exp.

Sequencing Length:17/27nt based on selected enzymes

ll d i iUsually 36 nt, no adapter contamination

Experiment Time:5 days 1 days

Compatible with Illumina:Compatible with Illumina:Difficult Easy

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1. Sample Preparation1. Sample Preparation 2a. Cluster Generation2a. Cluster Generation 2b. Flow Cell2b. Flow Cell

3. Sequencing & Imaging3. Sequencing & Imaging 4. Data analysis4. Data analysis4. Data analysis4. Data analysisQuality Valuse Vs. PhredQuality Valuse Vs. Phred

Base Caller Base Caller QC and StatsQC and StatsBase Caller Base Caller QC and StatsQC and Stats

Q=-10 log10(Pe)Pe=error probability of a particular base call1 error in 100=Q201 error in 1000=Q30

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Degradome SequencingNext‐Gen SequencingInstrument: Illumina Genome Analyzer GAIIx

Length of Reads: 35 bases

Number of Reads: ~20‐30 Million

Data Output: ~0 7 1 0 GbData Output: 0.7‐1.0 Gb

Bar‐coding (Indexing) Samples:

• We recommend 1‐2 per lane, Max is 3 per lane• The total number of reads does not change with bar‐coding• Sacrifice sequencing depth for lower cost

Number of Samples /Total Reads / Lane

Number of Samples / Lane

Reads/ Sample

30 M 1 30 M30 M 2 15 M30 M 3 10 M30 M 3 10 M30 M 4 7.5 M30 M 5 6 M30 M 6 5 M 19


Tools available for degradome sequencing data analysis

PAREsnip ‐ http://srna‐workbench.cmp.uea.ac.uk

SeqTar ‐ idm.fudan.edu.cn/zhengyun.html

SoMART ‐ http://somart.ist.berkeley.edu/

CLEAVELAND ‐ http://axtell‐lab‐psu.weebly.com/cleaveland.html

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Data Analysis – Cleaveland Pipeline1. Sequencing Tag1. Sequencing Tag

D d D it

2. mRNA database2. mRNA database

Degradome Density

High Fidelity miRNA targets

Target Prediction

g y g

3. miRNA3. miRNA

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Degradome SequencingData Analysis

• Illumina base‐calling and analysis (Raw Degradome Data)

• Map the degradome reads to the appropriate transcriptome using appropriate thresholds.

S i h d d d d i• Summarize the mapped degradome data into a "degradome density file"

• Generate small RNA / mRNA prediction targets

• Compare the degradome density file to the target• Compare the degradome density file to the target predictions, and output significant hits

• Generate "t‐‐plots" of the targets

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Table. Arabidopsis microRNA (miRNA) targets identified by degradome i (P l


Score, type, P value

miRNA, corresponding tothe target cleavage site

Reads

mRNA

Figure 1. Confirmed microRNA (miRNA) targets using degradome sequencing are presented in the form of target plots (t‐plots). 24

Degradome SequencingCategory 0 ‐ targets are transcripts where the degradome reads corresponding to the expected miRNA‐mediated cleavage site were the most abundant reads matching the transcript and there is only one peak on the transcript with more than one raw read at the position.

Category 1 the total abundance of degradome sequences at the cleavage position is equal to the maximum onCategory 1 ‐ the total abundance of degradome sequences at the cleavage position is equal to the maximum on the transcript, and there is more than one raw read at the position and more than one maximum position on the transcript.

Category 2 ‐ where abundance at the cleavage position is less than the maximum but higher than the median for the transcript and more than one raw read at the position.

Category 3 ‐ where abundance at the cleavage position is equal to or less than the median for the transcript and more than one raw read at the position.

category 4 ‐ where there is only one raw read at the cleavage position.

less than the maximummaximum equal to the maximum

less than the maximum but higher than the median

equal to or less than the median Only 1 raw read

Category 0 Category 1 Category 2 Category 3 Category 4 25

Case Study – Example 1

Wild soybean (Glycine soja) has undergone long‐term natural selection d h l d i l

Soybean

and may have evolved special mechanisms to survive (AL) stress conditions .

To understand the function of miRNAs in response to biotic and abiotic stresses (including Al tolerance)…

Sequenced two small RNA libraries and two degradome libraries constructed

Precursors structures of six pairs of miRNA/miRNA*s strictly meet characteristics mentioned by Meyers et al.

two degradome libraries constructed from the roots of Al‐treated and Al‐free G. soja seedlings

Through small RNA sequencing, identified 97 known miRNAs, 31 novel miRNAs, and a further 49 p3 or p5 strands of known miRNAs.

Qiao‐Ying Z, Cun‐Yi Y, Qi‐Bin M, Xiu‐Ping L, Wen‐Wen D, Hai N. (2012) Identification of wild soybean miRNAs and their target genes responsive to aluminum stress. BMC Plant Biol 12(1), 182. [article]

Differential expressions of ten miRNAs that were responsive to Al stress . 26

http://www.biomedcentral.com/content/pdf/1471-2229-12-182.pdf


Through degradome sequencing, 86 genes were identified as targets of the k iRNA d fi

Soybean

known miRNAs and five genes were found to be the targets of the novel miRNAs obtained in this study. Gene ontology (GO) annotations of target transcripts indicated that 52 target genes p g gcleaved by conserved miRNA families might play roles in the regulation of transcription. Additionally, some genes known to be responsive to stress, were found to be cleaved under Al stressfound to be cleaved under Al stress conditions

T‐plots of miRNA targets in the four different categories The T‐plots show the distribution ofcategories. The T plots show the distribution of the degradome tags along the full‐length of the target mRNA sequence (bottom). The red line represents the sliced target transcripts and is shown by an arrow. The alignments show the miRNA with a portion of its target sequence (top). Two dots indicate matched RNA base pairs; one dot indicates a GU mismatch. The arrow shows the cleavage site.

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Oilseed rape (Brassica napus) is one of the most important crops in

Oilseed rape (Brassica napus)

China, Europe and other Asian countries with publicly available expressed sequence tags (ESTs) and genomic survey sequence (GSS) databasesdatabases

To characterize miRNA function in the regulation of diverse physiological processes in B. napus.

Used next‐gen sequencing analysis of small RNAs as well as degradome sequencing of B. napus to identify novel miRNAs and miRNA targets.g

41 conserved B. napus miRNAs and 62 candidate novel B. napus‐specific miRNAs were identified through small RNA sequencing and

Candidate new brassica‐specific miRNAs

Xu MY, Dong Y, Zhang QX, Zhang L, Luo YZ, Sun J, through small RNA sequencing and further verified by real‐time RT‐PCR.

Fan YL, Wang L. (2012) Identification of miRNAs and their targets from Brassica napus by high‐throughput sequencing and degradome analysis. BMC Genomics 13:421. [article]

28

http://www.biomedcentral.com/content/pdf/1471-2164-13-421.pdf


A total of 33 non‐redundant target ESTs for 25 conserved miRNAs, and

Oilseed rape (Brassica napus)

19 non‐redundant target ESTs for 17 B. napus‐specific miRNAs were identified through degradome sequencing and verified by RNA ligase‐mediated 5’RACE mappingligase mediated 5 RACE mapping

Confirmed microRNA (miRNA) targets using degradome sequencing are presented in the form of target plots (t‐plots). Arrows indicate signatures consistent with miRNA‐directed cleavage. The frequencies of degradome tags with 5′ends at the indicated positions are shown in blackindicated positions are shown in black, with the frequency at position 10 of the inset miRNA target alignment highlighted in red. The underlined nucleotide on the target transcript indicates the cleavage site detected inindicates the cleavage site detected in the degradome.

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P i T h l i l Ad• Primary Technological Advantage

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Liriodendron chinense x tulipikera Hybrid tulip tree

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Documents

Degradome Sequencing for Plant microRNA Target Identificationlcsciences.com/documents/degradome-sequencing-webinar.pdf · 2013. 4. 2. · microRNAs ‐What We Know 1. All miRNAs are