Transcriptomic Sequencing Analysis and Comparison of Biological Networks Involved in Grapevine Leaf and Fruit Development

摘要

The genera Vitis is one of the oldest commercially and economically important fruit crops cultivated over the globe, producing about 67.5 million tons of grape berries along with highly valued, value added and processed products such as juices, jams, liquors and wines.Leaf and fruits are the major vegetative and reproductive organs for plant growth and multiplication of plants.Hence, understanding the ongoing biological activities in metabolic networks during these organs development is very important.Grape Berry and leaf development is a complex series of physical and biochemical changes, which are controlled by many metabolic networks.To some extent, the biophysical changes that occur through the multifaceted process of berry and leaf growth should be predisposed by the activities and presence of metabolic networks.These networks are essential to be controlled by the transcriptional regulation of mRNA.The understanding of these networks will not only provide the thoughtful knowledge of the essential processes that control grape berry growth and development, but also reveal insights into the genetic basis of grape berry quality that could potentially assist the wine industry.Recent advancements and development in high-throughput Sequencing Technology have become an essential technique in different fields like digital gene expression profiling, epigenomics, genomics, and transcriptomics.These methodologies are used for dexterous sequencing of multiple RNA molecules and abandace of RNA molecules to be sequenced within a short period of time.In the present study, proceeding to illumina sequencing, determining RNA integrity numbers for poly RNA were separated from each of the four different developmental stages of cv.Summer Black leaves by using Illumina HiSeqTM 2000.The sum of 272,941,656 reads were generated from leaf at four different developmental stages, resulting more than 27 billion nucleotides of sequence data.RNA samples of each stage were indexed through unique nucleic acid identifiers and sequenced.In the present study, we observed leaf development networks and the levels of different genes expression in comparison with the leaf initiation to maturity stages.In case of fruits,De-multiplexing using the unique identifiers discovered that data consisted of 28,808,716 (100％) clean reads from fruit sample of 40 DAF, 27,941,132 reads from fruit sample 65 DAF, and 25,457,565 reads from sample 90 DAF.From the total reads, total mapped reads (23.58％), total unmapped sequence reads (76.42％), unique matches (19.93％), multiple matches (3.65％) and perfect matches (13.73％) were recorded.KEGG annotation of leaf depicted that the highest number of transcripts in 2Avs4A (2,963) followed by 1Avs4A (2,920), and 3Avs4A (2,294) out of 15,614 (71％) transcripts that were recorded.In comparison, sum of 1532 transcripts was annotated in GOs,including Cellular component, with the highest number in “Cell part” 251 out of 353 transcripts (71.1％), followed by intracellular organelle 163 out of 353 transcripts (46.2％),while in molecular function and metabolic process 375 out of 525 (71.4％)transcripts,multicellular organism process 40 out of 525 (7.6％) transcripts in biological process were the most common in 1Avs2A.In comparison for GOs in and among fruit growth at specific developmental stages, the highest transcripts were found in Biological process including cellular process of 2,350 and metabolic process of 2,251 followed by response to stimulus of 809 and biological regulation of 859 transcripts.In the comparison of Cellular component, we found the highest numver of transcripts in cell of 2,776 and organelle 1,962 followed by cell part of 2,776 transcripts, while in case of Molecular function, we observed the highest number of transcripts in binding (2,329) followed by catalytic activity of 1,768 and localization 493 transcripts.In grapevine, during the initial stages of leaf development, 1Avs2A showed only a single transcript related to photosystem Ⅰ (reaction center subunit PSI-N, chloroplast,putative/PSI-N, putative (PSAN)) was down-regulated and none of them showed upregulation during this stage; although in comparison between 1A and 4A Photosystem Ⅱ showed 5 transcripts including 4 up-regulated (reaction center family protein PsbP, CemA-like proton extrusion protein-related PetA, root FNR 2 PetH and photosystem Ⅱ eaction center protein C PsbC) and a single transcript was down-regulated (photosynthetic electron transfer C PetC).However in fruits, 32 transcripts in the early stages of fruit growth including alcohol dehydrogenase (8), hydroxymethylglutaryl-CoA synthase (3), pyruvate decarboxylase (5), lipoxygenase (LOX) (3), carotenoid cleavage dioxygenase (9), were predicted.The network related to photosynthesis in leaf, 24 transcripts were identified during different leaf growth stages involved photosystem Ⅰ reaction center subunit (5),photosystem Ⅱ reaction center protein (12).In case of fruit developmental networks, we found 32 transcripts during the early stages of fruit growth including alcohol dehydrogenase (8), hydroxymethylglutaryl-CoA synthase (3), pyruvate decarboxylase (5),lipoxygenase (LOX) (3) and carotenoid cleavage dioxygenase (9), 13 transcripts related to myb-related proteins were found, throughout the grape berry development and their expression pattems from veraison onwards were the same.The number of transcripts was differentially expressed, although the up regulation trend was increased till maturity of the berries.Anthocyanidin 5, 3-O-glucosyltransferase 8 transcripts were found and the expression trends were different during developmental phase, however the expression of the genes was decreased towards maturity.In the present study 11 sugar phosphate protein transcripts were detected, of which 4 were up regulated in young berries and the rest were differentially expressed, although the overall expression level decreased towards the maturity of the berries.We found 12 cellulose synthase catalytic subunit transcripts, in early veraison, meanwhile veraison onwards showed more down regulated as compared to up regulated ones.3 proline-rich cell wall protein related transcripts were detected throughout all the developmental stages, and in young berries the one transcript was up regulated and 2 transcripts in later stagse were up regulated.In comparison of detected reads between leaf and fruit development, leaf showed a higher number of reads.And we can also conclude from these results that the overall data generated during the analysis of both samples, that leaf showed a higher level of gene expression, however lower expression in the later stages of growth.We have reported a detailed description of the expression profiles of 2.7 billion RNA transcripts in leaf and 2.8 billion in fruit samples to the NCBI RefSeq F.vinifera collection, andshown that this is an accurate reference for transcript abundance measurements.The biosynthetic pathways and molecular function, cellular component and biological process, the number of genes were higher in fruit as compared to leaf.Here we observed the genes which are related to the same network but expressed differently.Gene functions are developmental stage and organ specific and regulate networks accordingly; the growth of the plant organs is related to two main mechanisms, i.e.local mechanism and Global mechanism.Both mediums are interlinked in all parts of plants and support each other at certain levels by regulating genes in metabolic networks.Here we discussed some important growth networks and their relation in genes regulation.

目录

声明

COPYRIGHT

DEDICATION

TABLE OF CONTENTS

LIST OF TABLES AND FIGURES

ABSTRACT

ABBREVIATIONS

CHAPTER ONE：GENERAL INTRODUCTION

1．1 Background Information

1．2 Statement of problem

1．3 Justification of study

1．4 Objective of the study

CHAPTER TWO：HIGH THROUGHPUT SEQUENCING ADVANCEMENTS AND FUTURE CHALLENGES

2．1 Abstract

2．2 Introduction

2．3 Key HTS Platforms and applications

2．3．1 Sanger capillary sequencing

2．3．2 De novo sequencing

2．3．3 Metagenomics

2．3．4 Whole genome／targeted re-sequencing

2．3．5 Targeted region specific sequencing

2．3．6 Exome sequencing

2．3．7 RNA sequencing

2．3．8 miRanalyzer

2．3．9 Whole transcriptome

2．3．10 Bioinformatics Data Analysis tools

2．4 Bioinformatic challenges

2．4．1 Ethical challenges

2．5 Future prospective

2．5．1 Third-generation sequencing technology

2．5．2 Sequencing in diagnostics

CHAPTER THREE：TRANSCRIPTOMIC ANALYSIS OF BIOLOGICAL NETWORKS INVOLVING IN GRAPEVINE(cv．SUMMER BLACK)LEAF DEVELOPMENT

3．1 Abstract

3．2 Introduction

3．3 Material and Methods

3．3．1 Leaf Sample collection

3．3．2 RNA extraction，cDNA library construction and Illumina deep sequencing

3．3．3 Analysis of gene expression level

3．3．4 Pathway enrichment analysis of DEGs

3．3．5 qRT-PCR Validation

3．4 Results and discussion

3．4．1 Sequence quality control and Illumina HiSeq RNA sequencing

3．4．2 Global transcriptome analysis，functional classification，and metabolic pathway analysis by KEGG of all detected transcripts

3．4．3 Quality control，filtering of raw reads and analysis of base composition and quality

3．4．4 Quality Control of alignment Statistics and alignment analysis

3．3．5 Distribution of reads on reference genes

3．4．6 Gene expression distribution of gene’s coverage and gene expression difference analysis during leaf growth and development

3．4．7 SNP analysis

3．4．8 Prediction and Annotation of Novel Transcripts

3．3．10 Identification of Expressed Genes Responding to Leaf Developmental Stages

3．4．11 Leaf Growth and Development Alter Photosynthesis and Chlorophyll Pathway in Grapevine

3．3．12 Genes Related to Secondary Metabolism Biosynthetic Pathways

3．4．13 Genes Related to Plant Hormone Signal Transduetion Pathways During Leaf Developmental Stages

3．5 Discussion

3．6 Conclusion

CHAPTER FOUR：TRANSCRIPTOMIC ANALYSIS OF BIOLOGICAL NETWORKS INVOLVING IN GRAPEVINE FRUIT DEVELOPMENT

4．1 ABSTRACT

4．2 Background

4．3 Materials and Inethods

4．3．1 Grape berry sampling and development

4．3．2 RNA extraction，cDNA library construction and Illumina deep sequencing

4．3．3 Differential Gene Expression Analysis

4．3．4 qRT-PCR Validation

4．3．5 Real time RT-PCR validation

4．4 Results and discussion

4．4．1 Sequence quality control and lllumina HiSeq RNA sequencing

4．4．2 Global transcriptome analysis，networks analysis by KEGG of all detected transcripts and functional classification

4．4．3 Differential expressed aroma-related genes during berry development

4．4．4 Differential expressed transcripts during Organic acid metabolism

4．4．5 Color expression patterns related transcripts

4．4．6 Differential expression transcripts related to Sucrose-metabolism networks

4．4．7 Differential Expression of Cell Wall Degradation and Softening Related Transcripts

CHAPTER FIVE：COMPARISON OF GENES AND BIOLOGICAL NETWORKS INVOLVING IN FRUIT AND LEAF DEVELOPMENT

5．1 ABSTRACT

5．2 Background

5．2 MATEIUAL AND METHOD

5．2．1 Leaf and fruit samples

5．2．2 cDNA library constructionAnalysis of gene expression leveland Illumina deep sequencing and Analysis of gene expression level

5．3 Results and discussion

5．3．1 Sequence quality control and Illumina HiSeq RNA sequencing

5．3．2 Global transcriptomic analysis of metabolic networks and functional classification

5．3．3 Expressed Genes Responding to Leaf and fruit Development

5．4．Differential expressed genes in developmental networks andmetabolic pathways

5．4．1 Genes expression related to Photosynthetic network

5．4．2 Differentially expressed genes related to flavonoid-related metabolic network

5．4．3 Pigmentation patterns in growth networks altered by Genes

5．4．4 Genes regulation and expression related to plant hormone signaling networks

5．4．5 Genes related to secondary metabolites biosynthetic networks

CHAPTER SIX：CHLOROPLAST BASED GENETIC DIVERSITY AMONG GRAPE GENOTYPES

6．1 Abstract

6．2 Background

6．3 Material and Methods

6．3．1 Plant Materials

6．3．2 Organelle DNA Extraction and PCR Amplification

6．3．3 Statistical Analysis

6．4 Results

6．5 Discussion

CHAPTER SEVEN：ASSOCIATION BETWEEN CHLOROPLAST AND MITOCHONDRIAL DNA SEQUENCES IN CHINESE PRUNUS GENOTYPES(PRUNUS PERSICA，PRUNUS DOMESTICA，AND PRUNUS A VIUM)

7．1 Abstract

7．2 Back ground

7．3 Results

7．3．1 Phyiogenetic analysis

7．3．2 Nature of the polymorphism based on sequencing Alignment

7．3．3 Sequence comparison between and among mt and cpDNA

7．4 Materials and Methods

7．4．1 Plant Materials

7．4．2 Total DNA Extraction and PCR Amplification

7．4．3 Organelle DNA extraction from PAGE

7．4．4 TA cloning and sequencing

7．5 Discussion

7．6 Conelusion

MAJOR FINDINGS

REFERENCES

PUBLICATIONS AND SUBMITTED MANUSCRIPTS

ACKNOWLEDGMENT

APPENDICES