The influence of tropomyosin gene overexpression on
neuron-specific transcriptome patterns
by Bei Jun Chen z3450837
Supervisor Dr Michael Janitz
A thesis submitted as partial fulfilment of the requirement for the degree of Master of Philosophy
School of Biotechnology and Biomolecular Sciences University of New South Wales
August, 2014
ABSTRACT
Actin cytoskeleton has been implicated in a diversity of cellular functions and its role in neuronal morphology has been intensively studied. In non-skeletal cells, distinct populations of actin filaments in different subcellular compartments are characterised by the specific isoforms of actin-associated tropomyosin. To investigate the effect of different tropomyosin isoforms on neuron physiology at the transcriptomic level, transcriptome sequence data from transgenic Tp8 mice overexpressing human cytoskeletal tropomyosin
TM5NM1 and rat neuroblastoma cell line B35 cells overexpressing human cytoskeletal tropomyosin TM1 and TM5NM1, mouse cytoskeletal tropomyosin TmBr3 and Tm4 were analysed using a Galaxy bioinformatics analysis pipeline consisted of TopHat, Cufflinks, and Cuffdiff, followed by pathway analysis using DAVID. Results showed that in vivo and in vitro TM5NM1 overexpression resulted in different numbers of differentially expressed genes and isoforms as well as enriched gene ontology terms. For instance, the expression of transthyretin (FC = 23.54, p-value = 0.008) was significantly up-regulated in the transgenic Tp8 mice but not in the B35 cell lines. While PR Domain Containing 5 gene was silenced in all transfected B35 cells, its differential expression in Tp8 mice was not detected. In Tp8 mice but not B35 cells GO terms such as GO:0002376 immune system process and GO:0048002 antigen processing and presentation of peptide antigen were found enriched. GO terms such as GO:000904 cell morphogenesis involved in differentiation and GO:0048667 cell morphogenesis involved in neuron differentiation were exclusively enriched in B35 cells. In contrast, pathway analysis of rat neuronal cell line revealed mostly similar transcriptome patterns as a result of overexpression of TM1,
TmBr3, Tm4, and TM5NM1 isoforms of tropomyosin. This is the first time the effects of
iii overexpression of distinct tropomyosin isoforms on gene expression profiles been investigated using next-generation sequencing technology.
iv TABLE OF CONTENTS
1! Introduction+...... +1!
1.1! The+role+of+tropomyosin+in+maintenance+of+actin+cytoskeleton+structure+
and+neuron+morphogenesis+...... +1!
1.1.1! The!role!of!actin!cytoskeleton!in!neuronal!morphogenesis!...... !1!
1.1.2! Tropomyosin!is!the!integrate!component!of!actin!filaments!...... !2!
1.1.3! Tropomyosin!isoforms!are!spatially!and!temporally!regulated!and!have!
different!impacts!on!neuronal!morphogenesis!...... !3!
1.1.4! Generation!of!Tp8!transgenic!mice!and!the!effect!of!TM5NM1!
overexpression!...... !6!
1.2! Methods+for+transcriptome+analysis+...... +6!
1.3! Bioinformatics+analysis+of+Next+Generation+RNA+sequencing+data+...... +9!
1.4! Pathway+Analysis+...... +11!
2! Aims+of+the+study+...... +13!
3! MATERIALS+AND+METHODS+...... +15!
3.1! RNA+isolation,+library+preparation+and+sequencing+...... +15!
3.2! RNAQseq+data+sets+...... +15!
3.3! Data+trimming+with+Trimmomatic+...... +15!
3.4! Mapping+reads+to+reference+genomes+using+TopHat+...... +16!
3.5! Alignment+statistics+reporting+by+RseQC+...... +20!
3.6! Determination+of+genes+and+isoforms+expression+level+using+Cufflinks+ 20!
3.7! Merge+of+the+transcripts+using+Cuffmerge+...... +21!
v 3.8! Identification+of+differentially+expressed+genes+and+isoforms+by+Cuffdiff
+ 21!
3.9! GO+term+enrichment+analysis+and+results+visualisation+...... +22!
3.10! Visualisation+with+CummeRbund+and+Interactive+Genome+Viewer+...... +23!
3.11! Quantification+of+transcript+expression+and+significance+determination
+ 23!
3.12! RNAQseq+bioinformatic+analysis+pipeline+...... +24!
3.13! Reference+genomes+and+gene+annotation+reference+files+...... +24!
4! RESULTS+...... +25!
4.1! RseQC+read+alignment+statistic+calculation+report+...... +25!
4.2! Expression+of+the+tropomyosin+genes+...... +25!
4.3! IGV+Plot+presentation+of+three+sample+genes+...... +30!
4.4! Differential+transcriptome+landscape+in+Tp8+mouse+...... +32!
4.5! Differentially+expressed+mouse+transthyretin+gene+...... +33!
4.5.1! Expression!levels!of!transthyretin!gene!...... !33!
4.5.2! Structural!comparison!between!the!annotated!and!novel!transcripts!of!
transthyretin!gene!...... !36!
4.5.3! Depth!of!read!coverage!over!Ttr!gene!in!Tp8!mice!...... !36!
4.6! Comparative+transcriptome+patterns+in+B35+cell+lines+...... +37!
4.6.1! TM1Hoverexpressing!cells!...... !37!
4.6.2! TmBr3Hoverexpressing!cells!...... !41!
4.6.3! Tm4Hoverexprssing!cells!...... !44!
4.6.4! TM5NM1Hoverexpressing!cells!...... !47!
4.7! Comparative+analysis+of+differential+expression+distribution+...... +50!
4.8! Pathway+analysis+for+differentially+expressed+genes+...... +54!
vi 4.9! Network+visualisation+of+enriched+GO+terms+network+using+one+
Cytoscape+plugin+Enrichment+Map+...... +61!
4.10! Supplementary+tables+...... +61!
5! DISCUSSION+...... +62!
5.1! Quality+check+of+aligned+reads+...... +62!
5.2! Choosing+bioinformatic+tools+for+RNAQseq+data+analysis+...... +62!
5.3! Comparison+of!TM5NM1!overexpression+between+Tp8+mice+and+B35+cells
+ 63!
5.4! Transthyretin:+plasma+transporter+of+thyroid+hormone+and+retinol+...... +66!
5.5! B35+cell+line+model:+transcriptome+patterns+as+a+result+of+Tm+isoforms+ overexpression+...... +67!
5.5.1! DownHregulated!genes!in!TmHoverexpressing!B35!cells!...... !67!
5.5.2! TM1!overexpression!...... !67!
5.5.3! TmBr3!overexpression!...... !68!
5.5.4! Tm4!overexpression!...... !69!
5.5.5! TM5NM1!overexpression!...... !70!
5.5.6! Overlapping!patterns!of!affected!pathways!among!Tm!transgenic!cells!...!71!
5.6! Significance+and+limitations+of+the+study+...... +72!
6! Conclusion+...... +73!
7! References+...... +74!
vii TABLE OF FIGURES
+
Figure+1:+A+schematic+illustration+of+neuronal+development.+++ 3!
Figure+2:+TM’s+association+with+actin+filaments.+! 3!
Figure+3:+Tm+isoform+structures.+ 3!
Figure+4:+Localisation+of+TM+isoforms+in+neurons.+ 4!
Figure+5:+Overview+of+an+Illumina+sequencing+workflow.+ 8!
Figure+6:+Overview+of+the+study+design.+ 14!
Figure+7:+RNAQseq+data+analysis+pipeline.+ 24!
Figure+8:+IGV+plot+of+transthyretin+gene.+ 31!
Figure+9:+IGV+plot+of+tropomyosin+α)Tm+(Tpm1)+in+TM1Qoverexpression+B35+cells.+ 31!
Figure+10:+IGV+plot+of+tropomyosin+β)Tm+(Tpm2)+in+TmBr3Qoverexpression+B35+cells.+ 31!
Figure+11:+Volcano+plot+of+gene+(A)+and+isoform+(B)+expression+in+Tp8+and+WT+mice.+ 33!
Figure+12:+Levels+of+Ttr+transcripts+TCONS_00028431,+TCONS_00028432,+and+total+gene+
expression.+ 36!
Figure+13:+Reads+coverage+over+the+3rd+exon+of+Ttr+gene+in+Tp8+mice.+ 37!
Figure+14:+Volcano+plot+of+gene+expression+in+B35+cell+lines+and+WT+mice.+ 50!
Figure+15:+Volcano+plot+of+isoform+expression+in+B35+cell+lines+and+WT+mice.+ 51!
Figure+16:+Number+of+total+expressed+genes,+DEGs,+and+DEG+ratio+in+all+analysed+groups.+ 53!
Figure+17:+Number+of+total+expressed+isoforms,+DEIs,+and+DEI+ratio+in+all+groups.+ 54!
Figure+18:+Number+of+enriched+GO+terms+in+all+analysed+groups.+ 56!
Figure+19:+Venn+diagram+of+common+annotated+DEGs+between+Tp8+mice+and+B35+cell+line+
models+overexpressed+TM5NM1.+ 57!
Figure+20:+Venn+diagram+of+common+enriched+GO+terms+in+Tp8+mice+and+B35+cell+lines+
overexpressed+TM5NM1.+ 57!
Figure+21:+Venn+diagram+of+annotated+DEGs+among+four+transgenic+groups+in+the+B35+cell+line+
model.+ 58!
viii Figure+22:+Venn+diagram+of+enriched+GO+terms+identified+in+all+groups+of+the+B35+cell+line+model.
+ 58!
Figure+23:+Heatmap+illustration.+ 60!
!
ix TABLE OF TABLES
Table+1:+RNAQseq+data+sets+generated+from+the+Tp8+mice+model+ 17!
Table+2:+RNAQseq+data+sets+generated+from+the+B35+cell+line+transgenic+models+ 18!
Table+3:++RseQC+alignment+statistics+report+ 25!
Table+4:+Expression+of+tropomyosin+transcript/gene+in+WT+and+Tp8+mice+ 26!
Table+5:+Expression+of+tropomyosin+transcript/gene+in+WT+and+TM1Qoverexprssing+B35+cells+ 27!
Table+6:+Expression+of+tropomyosin+transcript/gene+in+WT+and+TmBr3Qoverexprssing+B35+cells
+ 28!
Table+7:+Expression+of+tropomyosin+transcript/gene+in+WT+and+Tm4Qoverexprssing+B35+cells+ 29!
Table+8:+Expression+of+tropomyosin+transcript/gene+in+WT+and+TM5NM1Qoverexprssing+B35+
cells+ 30!
Table+9:+Top+30+upQ+and+downQregulated+DEGs+in+Tp8+when+compared+to+WT+mice+ 34!
Table+10:+Top+30+upQregulated+and+all+downQregulated+DEIs+in+Tp8+when+compare+to+WT+mice+35!
Table+11:+Top+30+annotated+DEGs+upQ+and+downQregulated+in+TM1Qoverexpressing+B35+cells+
when+compared+to+WT+cells+ 39!
Table+12:+Top+30+annotated+DEIs+upQ+and+downQregulated+in+TM1Qoverexpressing+B35+cells+when+
compared+to+WT+cells+ 40!
Table+13:+Top+30+annotated+DEGs+upQ+and+downQregulated+in+TmBr3Qoverexpressing+B35+cells+
when+compared+to+WT+cells+ 42!
Table+14:+Top+30+annotated+DEIs+upQ+and+downQregulated+in+TmBr3Qoverexpressing+B35+cells+
when+compared+to+WT+cells+ 43!
Table+15:+Top+30+annotated+DEGs+upQ+and+downQregulated+in+Tm4Qoverexpressing+B35+cells+
when+compared+to+WT+cells+ 45!
Table+16:+Top+30+annotated+DEIs+upQ+and+downQregulated+in+Tm4Qoverexpressing+B35+cells+when+
compared+to+WT+cells+ 46!
Table+17:+Top+30+annotated+DEGs+upQ+and+downQregulated+in+TMM5NM1Qoverexpressing+B35+
cells+when+compared+to+WT+cells+ 48!
x Table+18:+Top+30+annotated+DEIs+upQ+and+downQregulated+in+TMM5NM1Qoverexpressing+B35+
cells+when+compared+to+WT+cells+ 49!
Table+19:+Metrics+summary+of+identified+genes,+isoforms,+DEGs,+and+DEIs+in+Tp8+mice+and+B35+
transgenic+cells.+ 52!
Table+20:+Enriched+GO+term+clusters+in+Tp8+mice+group+and+Top+10+enriched+GO+term+clusters+in+
B35+cell+line+group+ 55!
xi ACKNOWLEGMENTS
My greatest appreciation goes to my supervisor Dr. Michael Janitz, I couldn’t have completed this project without the guidance and inspiration from him. It seemed almost magical that he could always have perfect suggestions to every problem I had, thanks to his professional knowledge with incredible depth and breadth in the field. I am privileged to have worked in his lab.
I would like to thank Mr. James Mills for his tremendous support with great patience since day one. The knowledge and experience he shared with me have been invaluable to my project, to him I am deeply grateful.
My appreciation to Dr. Thomas Fath, Prof. Peter Gunning, and Ms Alexandra
Suchowerska for the data, information, and support that they kindly provided.
I also thank my family for their continuous support.
xii ABBREVIATIONS
ADF actin depolymerising factor αTm tropomyosin alpha gene βTm tropomyosin beta gene DAVID The Database for Annotation, Visualisation and Integrated Discovery δTm tropomyosin delta gene bp base pairs DEG differentially expressed gene DEI differentially expressed isoform dNTP deoxyribonucleotide triphosphate F actin filamentous actin FC fold change FDR false discovery rate FPKM fragments per kilo-base of exon per million fragments mapped γTm tropomyosin gamma gene Gb giga-bases GO gene ontology Prdm5 PR Domain Containing 5 gene RNA-seq RNA sequencing RPKM reads per kilo-base of exon per million reads mapped TM tropomyosin TM1 tropomyosin 1 Tm4 tropomyosin 4 TM5NM1 tropomyosin 5 non-muscle 1 TmBr3 tropomyosin Br3 TTR transthyretin WT wild type UTR untranslated region
xiii
1 INTRODUCTION
1.1 The role of tropomyosin in maintenance of actin cytoskeleton structure and
neuron morphogenesis
Actin cytoskeletons have been implicated in a diversity of cellular functions including muscle contraction, cytokinesis, cell motility and neuronal morphogenesis. In non-skeletal cells, distinct populations of actin filaments in different subcellular compartments are characterised by the specific isoforms of its associating tropomyosin
(TM). Studies showed that TM is responsible for neuritogenesis and regulation of neurites branching patterns in B35 neuroblastoma cells in an isoform-dependent manner (Gunning et al., 2008a). Bound to the alpha-helical groove, TM is the core component of the actin filament.
1.1.1 The role of actin cytoskeleton in neuronal morphogenesis
From the round-shaped neural stem cell to a mature neuron with a distinct appearance characterised by typical neuronal cytoplasmic processes: axon and dendrites, the life of a neuron sees a series of morphological changes (Figure 1) (Luo, 2002). Actin filaments play a critical role in the morphological development through the entire life of a neuron including initial neuronal shape establishment, neuronal morphogenesis during differentiation, and structural changes throughout the neuron’s adulthood. The initial budding of the axon from many primitive neurites is the first step of a neuron’s development (Dotti et al., 1988). In vitro experiments have shown that significantly
1
increased actin dynamic and instability within a single growth cone are the determining factors of that growth cones to become the future axon (Bradke and Dotti, 1999).
Actin cytoskeleton’s role in axon growth has been extensively studied. The general view is that during the course of axon growth, the extension of filopodia and lamellipodia is driven by polymerisation of actin monomers at the leading edge of the growth cone
(Mitchison and Kirschner, 1988). The rate of filopodia and lamellipodia growth is therefore very likely to be dependent on the polymerisation rate of actin monomers. The mechanisms through which actin filaments exerts its effect on dendrites still need however to be elucidated. Studies from different groups have confirmed the existence of high concentration of filamentous actin (F actin) within dendritic spines (Matus et al., 1982,
Fischer et al., 1998). Dendritic spines are minor protrusions along dendritic shafts which form the postsynaptic sites in mammalian brains. Dendritic spines are motile via chemical and structural modifications, reflecting brain plasticity in response to stimulation. F actin has been widely accepted as the base of dendritic spines plasticity (Fischer et al., 2000,
Matus, 2000) and its high turnover rate might contribute to dendritic spine’s ability to undergo shape change upon stimulation (Star et al., 2002)
Actin cytoskeleton appears to play different roles in different sub-cellular compartments. It is believed that actin cytoskeleton spatially distinct functions are diversified through the composition of its associating protein TM.
1.1.2 Tropomyosin is the integrate component of actin filaments
TM is most commonly known for its regulation of contraction in skeletal cells, however its impact on many actin cytoskeleton properties in non-muscle cells is less well
2
Figure 1: A schematic illustration of neuronal development.
understood. Rod-shaped coiled-coil TM dimers form head-to-tail TM polymers and run along the length of the α-helical groove of an actin filament (Figure 2) (Phillips et al., 1979,
Lazarides, 1976).
There are four highly conserved TM genes: αTm, βTm, γTm, and δTm. To accommodate functional diversity of actin filaments, mammalian TM is expressed in more than 40 isoforms generated from alternative splicing and different promoter usage from at least three TM genes (Figure 3) (Cooley and Bergtrom, 2001, Lees-Miller and Helfman,
1991, Gunning et al., 2005).
Figure 2: TM’s association with actin filaments. TM5NM1 is the product of the γTm gene, it stabilises actin filaments by promoting the binding of non-muscle myosin II to actin filaments, and prevents the severing action of actin depolymerising factors (ADFs) simultaneously. By contrast, encoded by the αTm gene, TMBR3 promotes higher actin filament turnover by recruiting ADFs and prevents the binding of myosin II on actin filaments.
Figure 3: Tm isoform structures. Alternative splicing and different promoter usage of four tropomyosin genes (α, β, γ, and δ) contribute to the diversity of tropomyosin isoforms. Rectangles represent exons in each gene, exons sharing similarity are coded in the same colour.
1.1.3 Tropomyosin isoforms are spatially and temporally regulated and have different
impacts on neuronal morphogenesis
At the organ level, a specific set of TM isoforms, including TM4, TM5A, and multiple products from the γTm gene, are neuron-specific (Schevzov et al., 2005). At the cellular level, TM isoforms display unique intracellular distribution patterns in neurons at specific developmental stages (Martin and Gunning, 2008). Associated with their specific
3
actin structures, different TM isoforms localise to distinct subcellular compartments such as axon, growth cone, cell body, and dendrites during embryonic development and adulthood
(Figure 4). When culturing rat embryonic neuronal cells Weinberger and colleagues revealed that TM5NM1 and TM5NM2 isoforms were enriched in the growth cone and axon, respectively. However after neuron maturation was completed, TM5NM1 and
TM5NM2 were re-localised to the cell body and somatodendritic compartment
(Weinberger et al., 1996). Immuneprecipitation investigation targeting isoforms TM4 and
TMBR3 has shown that the expression profile of these two isoforms also changed along with the maturation of the rat neurons. The TM4 isoform was mainly expressed during neuronal developing stage. The concentration of TM4 protein was high in growth cones in cultured cells and in growing neurite sites in vivo. On the other hand, the expression of isoform TmBr3 was increased in completely differentiated neurons, with it being enriched in presynaptic terminal areas (Had et al., 1994a). As for the isoform TM5A, its presence in young mouse cortical cell culture (12 – 16 hours) was detected in 96 % of growth cones of both neurite and dendrite. Their expression in growth cones was however significantly decreased to 11% after 46 hours of culture (Schevzov et al., 1997a).
Several lines of experiments also investigated the impact of an altered TM isoforms expression profile on neuronal morphogenesis. Schevzov and colleagues found that in cultured embryonic cortical neurons from mice, overexpressed TM5NM1 was enriched in filopodia and growth cones and resulted in increase of the cones’ size and dendrites and axonal branching. In contrast overexpressed TM3 in these cells seemed to be localised uniformly within the neurons (Schevzov et al., 2005). Curthoy and colleagues
Figure 4: Localisation of TM isoforms in neurons.
4
showed that, in a B35 neuroblastoma cells, overexpression of TmBr3 and Tm4 isoforms resulted in increase of neurite number, neurite branching, and filopodia along the neurite shafts. The numbers of neurites in the control cells and cells overexpressing TmBr1 and
TmBr2 did not differ significantly. In cells overexpressing TmBr1 a reduction in growth cone size was observed whereas TmBr2 overexpression led to the elongation of primary neuritis (Curthoys et al., 2014). These findings suggest that not only subcellular compartment localisation is important for neuronal morphogenesis, but also regulation of
Tm isoform expression levels.
Reports on the role of TM1 protein in neuron development are scarce. It has been shown that the expression of TM1 is decreased in human neuroblastoma cells and presumably resulted in a disorganised cytoskeleton structure which is one of the hallmarks of transformed cells. However, the exogenous expression of TM1 failed to restore the normal actin cytoskeleton in these cells (Yager et al., 2002).
The exact mechanism through which particular TM isoforms regulate actin cytoskeleton function is unknown. Some studies suggest that TM stabilises actin cytoskeleton by protecting actin filaments from the severing action of gelsolin and the depolymerising action of actin depolymerising factor (ADF)/cofilin. ADF/cofilin is a family of conserved actin-binding proteins that are characterised by their ability to depolymerise actin and hence enhance the turnover rate of actin filaments (Carlier et al.,
1997) This remains in line with observations that actin filaments undergo rapid polymerisation and depolymerisation in areas where TM is absent (Broschat, 1990).
5
1.1.4 Generation of Tp8 transgenic mice and the effect of TM5NM1 overexpression
TM5NM1-overexpressing Tp8 mice were generated using human β-actin expression vectors containing a single copy of the human TM5NM1 gene. Human TM5NM1 protein differs one amino acid from its mouse ortholog. In general, overexpression of exogenous
TM5NM1 did not affect the expression level of other TM isoforms and the total amount of actin protein. However, it was showed that excess of TM5NM1 shifts the production of actin protein from monomeric (G protein) to filamentous (F actin), resulting in increased formation of actin filament. Hippocampal neurons from TM5NM1 transgenic mice display a phenotype characterised by significantly larger growth cone, an area where the exogenously expressed TM5NM1 is enriched (Schevzov et al., 2008).
1.2 Methods for transcriptome analysis
Transcriptome is the entire set of RNA species inside a cell, from which much of the organism complexity is derived. The transcriptome includes mRNA, structural RNA such as ribosomal RNAs, transfer RNAs, and non-coding RNAs (ncRNAs). The genomic sequences from which transcriptomes are generated remain identical in almost every single somatic cell of an organism. In contrast the transcriptome is dynamic, reflecting the gene expression profile of a certain cell within a specific tissue, during a specific developmental stage, in response to environmental influences, and in a given condition such as healthy or diseased. An ideal transcriptomic analysis should quantify each full length RNA molecule inside a single cell, thus unravelling the expression pattern of that individual cell at a single base resolution.
6
Before the advent of high-throughput next-generation sequencing technology, transcriptome analyses had been mainly done using DNA microarray. This method captures and measures the intensity of fluorescence signals emitted by cDNA molecules hybridising to their synthetic complementary DNA probes attached to a glass surface (McLachlan et al.,
2005, Bowtell, 1999). DNA microarrays allow for high throughput measurements of gene expression and had been a mainstream method of transcriptome analysis until five years ago. However, microarrays have several technological disadvantages. This includes poor detection of genes expressed at low levels; the reliance upon prior knowledge of gene sequence under investigation; high background noise due to cross-hybridisation; and complicated normalisation methods to eliminate effects arose from technical variations between multiple experiments (Okoniewski and Miller, 2006, Yang et al., 2002).
The emergence of next-generation RNA sequencing (RNA-seq) has revolutionised the field of transcriptomic analysis with its advantages in cost, efficiency, and high resolution (Mortazavi et al., 2008, Wang et al., 2009b). Currently there are a number of next-generation sequencing (NGS) platforms. Illumina is one of the companies that provides solutions for a range of RNA-seq applications. Although these platforms adopt different technologies, the principles behind DNA sequencing are essentially the same: they all rely on signals capture after dNTP is incorporated into an extending new DNA strand.
This principle is known as the sequencing-by-synthesis technology. In an Illumina RNA- seq run (Figure 5), cDNA fragments are annealed to dense lawns of oligonucleotide primers on the surface of a flow cell. These cDNA fragments are extended and sequenced via PCR reaction, generating up to 3 billion bases of single reads or 6 billion bases of paired-end reads in a single run. This process is often referred to as massive parallel sequencing.
Sequence data obtained through massive parallel sequencing are mapped to the reference
7
genome allowing for determination of alternatively spliced transcripts (isoforms) and their quantification. RNA-seq has been widely used in basic science research. For example the
X chromosome dosage compensation hypothesis was evaluated using RNA-seq method
(Xiong et al., 2010, Jue et al., 2013). Numerous experiments have employed RNA-seq to detect novel transcripts and isoforms (Mills et al., 2013a, Mills et al., 2014). In addition to the applications of RNA-seq in basic science research including quantification of gene dosage, identification of novel genes, splicing variants, and transcription factor binding sites, as well as analysis of methylation patterns, RNA-seq has the potential to be applied in clinical analysis such as cancer prognosis prediction. By comparing the expressions level of a subset of cancer genes with a wild type (WT) sample to classify the tumour type and to determine its progression.
Figure 5: Overview of an Illumina sequencing workflow.
A number of recent studies demonstrated advantages, such as deeper resolution, higher sensitivity, and greater replicability, of RNA-seq methods over conventional genomic methods such as microarray analysis. Marioni et al reported a higher replicability of RNA-seq with a low technical variation when comparing transcriptomic patterns of human liver and kidney RNA samples of using both Illumina RNA-seq and Affymetrix array method (Marioni et al., 2008). RNA-seq also permitted the identification of novel transcripts and splicing variants which is beyond the capacity of a microarray analysis.
Three other differentiation expression studies using both RNA-seq and microarray platforms with RNA samples from human T cell, mouse, and Drosophila melanogaster reported more robust quantification performance of RNA-seq coupled with delivery of
8
additional information such as novel genes and isoforms (Bottomly et al., 2011, Marioni et al., 2008, Sirbu et al., 2012, Zhang et al., 2012).
1.3 Bioinformatics analysis of Next Generation RNA sequencing data
RNA-seq analyse involves utilisation of bioinformatics tools that process sequencing data in a series of steps and finally generate output files for further interpretation and/or visualisation. Next Generation RNA sequencing systems produce millions of short reads ranged from 25 to 100 bp in length in a single run. These short reads are generated as
FASTQ files which not only contain read sequences but also sequencing quality scores.
Mapping programs use FASTQ datasets as input files. The analytical challenge begins with mapping short reads onto a reference genome, towards determination of each read’s position within the reference genome, quickly and efficiently. For traditional mapping programs such BLAST or BLAT, the alignment is both computer-power demanding and time consuming. Recently developed programs such as MAQ and Bowtie use indexing- based algorithms that allow time and cost efficient mapping of the reads to the genome (Li et al., 2008, Langmead and Salzberg, 2012). For RNA-seq data derived from mRNA, it requires special mapping tools to map the reads to the whole length genome having introns between exons. To this end TopHat is one of such splice junction mappers currently available (Trapnell and Salzberg, 2009). The abundance of mapped reads is measured in units such as read count, RPKM (reads per kilobase of exon per million reads mapped), or
FPKM (fragments per kilobase of exon per million fragments mapped). Read count is simply the number of reads that aligned to a particular DNA region such as a gene. It is an absolute measurement of transcript abundance and is used by differentiation expression analysis programs such as edgeR applying normalisation in a later stage of the analysis
9
(Robinson et al., 2010). RPKM normalises read count against both total exon lengths and library sizes. Hence the levels of gene expression within a sample or across samples can be estimated. For paired end sequencing data used in this project, a pair of complimentary reads from opposite directions constitute a fragment, expressed in FPKM, which is used to measure the relative gene expression levels (Wang et al., 2009a). Final step of analysis involves differential expression reporting, data interpretation and visualisation. Different software programs are used in each step, forming tool suites or pipelines for a complete entire process. An example is the Tuxedo package composed of TopHat, a splice junction mapper; Cufflinks, a transcripts assembler; and Cuffdiff, which compares the differences in gene and isoform expression levels. These programs were originally command line-based but have been integrated into web-based platforms such as Galaxy operated by the
Pennsylvania State University and Garvan Institute of Medical Research, Sydney, Australia for easier access by researchers worldwide (Goecks et al., 2010). Tuxedo is one of the most wildly used RNA-seq data analysis pipelines. Alternative RNA-seq data analysis tool suites comprise GenePattern, R-based DEGseq and edgeR, and RobiNA (Wang et al., 2010,
Lohse et al., 2012, Kuehn et al., 2008).
A Tuxedo pipeline analysis starts from feeding TopHat with RNA-seq output data which consists of millions of short reads up to 1000 base pairs (bp) in length depending on the sequencing platform. TopHat first maps these reads to a reference genome using a high-throughput reads aligner Bowtie, and then identify splicing junctions. Each biological or technical replicate is processed independently (Trapnell et al., 2009). The mapping results for each replicate are transferred as input data to Cufflinks which assembles mapped reads into individual transfrags, i.e. transcribed fragments and calculates the expression levels of each gene and transcript (Trapnell et al., 2012). These transfrags from each
10
sample are then merged together with annotated genome file by Cuffmerge into a unified assembly file which will be used by Cuffdiff to calculate respective expression levels of each transcript in each sample. The Cuffdiff output file can either be visualised using tools like IGV, or indexed by CummeRbund to explore differentially expressed genes (DEGs) and isoforms (DEIs) identified by Cuffdiff (Trapnell et al., 2012, Goff et al., 2012).
1.4 Pathway Analysis
Further analysis of determined DEGs in the context of biological interpretation is however challenging. A single gene can be involved in different biological processes, and a single process can have more than one gene. The difficulties in obtaining a meaningful biological interpretation of DEGs derived from high-throughput sequencing include cumbersome process of acquiring functional annotations for each DEG, dealing with redundant gene functional annotations from numerous sources, grouping DEGs according to their relevance to a specific biological process, and ranking these processes according to over-representation analysis (Huang da et al., 2009b, Huang da et al., 2009a). A number of pathway analysis tools exist aiming to tackle the task, the most prevalent ones available are:
GeneMANIA, WebGestalt, GSEA, and DAVID. GeneMANIA (Gene Multiple
Association Network Integration Algorithm for Fast Gene Function Predictions) and
WebGestalt (WEB-based Gene SeT AnaLysis Toolkit) are both list-based gene function predictors which have up-to-date sets of gene ontology (GO) annotations and they comprise tools for genomic and proteomic functional studies (Mostafavi et al., 2008, Zhang et al.,
2005). On the other hand, GSEA (Gene Set Enrichment Analysis) requires ranked gene lists as input files and mainly compares the difference in significance and concordance of a predefined gene set in two compared conditions (Subramanian et al., 2005). Pathway
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analysis tools like DAVID (The Database for Annotation, Visualisation and Integrated
Discovery) provides another robust approach for biological interpretation of discovered
DEGs. One of the functionalities offered by DAVID is identification of enriched biological processes based on GO term clusters consisted of gene lists with similar annotations, and grouping of DEGs into various biological processes. In this way, pathway analysis provides a means of elucidating cellular events that are enriched in response to genomic alteration or between different conditions such as normal and diseased (Da Wei Huang and
Lempicki, 2008, Sherman and Lempicki, 2009, Kavanagh et al., 2013).
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2 AIMS OF THE STUDY
To investigate the impact of altered Tm transcripts expression on neuronal morphogenesis that might be reflected through expression pattern changes in the transcriptomic profiles of two different organisms by:
1) Performing data and pathway analysis on RNA-seq data obtained from the
hippocampal cells of TM5NM1-overexpressing mice and compare with WT
mice;
2) Performing data and pathway analysis on RNA-seq data obtained from the TM1-
, TmBr3-, Tm4-, and TM5NM1-overexprssing B35 cells compare with WT B35
cells;
3) Performing inter-model comparison between human TM5NM1-overexpressing
mice and rat TM5NM1-oversepxressing B35 cells;
4) Performing intra-model comparison among all four Tm isoform overexpressing
B35 cells.
Figure 6 illustrates the workflow of the study. RNA samples from hippocampal cells of Tp8 mice (human TM5NM1-overexpressing) and four rat B35 cell lines overexpressing TM1, TmBr3, Tm4, and TM5NM1, together with WT samples from each model were sequenced using RNA-seq technique. RNA-seq data was first fed into TopHat for read alignment. After TopHat the expression levels of each expressed gene were calculated by Cufflinks. The differences in expressed levels in each condition were analysed by Cuffdiff, the results of which can be used for data interpretation, illustration, and pathway analysis.
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Tp8!mouse!model! B35!neuroblastoma!cell!line!
TM5NM1! Overexpressing! Wild/type! TM1& TmBr3& Tm4& TM5NM1& Wild/type!
RNA!sequencing!! (details!not!included)! Reads!alignment!with!! TopHat'
Expression!level!calculaAon! with!Cufflinks'
DEG!analysis!with! Cuffdiff'
DEGs!and/or!DEIs!analysis! Pathway!analysis!with!! results!illustraAon!with!R' DAVID'
Figure 6: Overview of the study design. RNA samples from hippocampal cells of Tp8 mice (human TM5NM1-overexpressing) and four B35 cell lines overexpressing TM1, TmBr3, Tm4, and TM5NM1, together with wild-type samples from each model were sequenced. RNA-seq data was first fed into TopHat for read alignment. After TopHat the expression levels of each expressed gene were calculated by Cufflinks. The differences in expressed levels in each condition were analysed by Cuffdiff, the results of which can be used for data interpretation, illustration, and pathway analysis.
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3 MATERIALS AND METHODS
3.1 RNA isolation, library preparation and sequencing
Hippocampal RNA sample was taken from transgenic Tp8 mice on C57BL/6 background overexpressing TM5NM1 isoform under beta-actin promoter (Dr Thomas Fath, unpublished). The four B35 rat transgenic cell lines overexpressing human TM1, rat
TmBr3, rat Tm4, and human TM5NM1 isoforms, respectively, have been developed in Dr
Thomas Fath laboratory. Total RNA was isolated using RNeasy Lipid Tissue Mini Kit
(Qiagen, Hilden, Germany) followed by RNase-free DNase treatment to remove traces of genomic DNA. The Agilent 2100 Bioanalyzer RNA Nano Chip was used to assess the
RNA quality of the total RNA. The RNA integrity number (RIN) values ranged between
6.0 and 7.0. Sequencing was performed at the NGS Facility, University of Western Sydney using paired-end 100-bp reads on Illumina HiSeq1000 protocol according to the Illumina
TruSeq RNA sample preparation guide using polyA RNA as a template.
3.2 RNA-seq data sets
In the mice model, both Tp8 and WT mice had six biological replicates in each group while in the B35 cell line model three biological replicates were sequenced for each transgenic cell group. Table 1 and 2 list RNA-seq data set structure and metrics used for this study.
3.3 Data trimming with Trimmomatic
It was observed during data processing that trimming of RNA-seq data with
Trimmomatic improved the data quality (own observations, not shown). Trimmomatic
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removes Illumina adaptors, uses information contained in pair-end reads to better locate the adaptors or primer fragments on the other read, and performs trimming of bases with quality scores below 3 in a window-sliding fashion. In this way, Trimmomatic improves data quality while retains the paired ends information (Bolger et al., 2014, Del Fabbro et al.,
2013). 24 RNA-seq files of the B35 cell line model were processed by Trimmomatic version 0.32, with the following settings:
• ILLUMINACLIP: TruSeq3-PE.fa:2:30:10
• LEADING: 3
• TRAILING:3
• SLIDINGWINDOW: 4:15
• MINLEN: 36
The sizes before and after trimming are listed in Table 2.
3.4 Mapping reads to reference genomes using TopHat
All RNA-seq files in FASTQ format were uploaded to Galaxy server at http://usegalaxy.org for mapping RNA-seq reads to their respective (mouse or rat) reference genome with TopHat (version 1.5.0) and downstream applications.
RNA-seq reads from Tp8 mice were aligned to UCSC mouse genome version mm10 while RNA-seq reads from B35 cell line model were mapped to Ensembl rat genome assembly Rnor_5.0.
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Table 1: RNA-seq data sets generated from the Tp8 mice model
Tp8 Mice RNA-seq data sets No. of reads (millions) TF3_L1_R1* 17.45 TF3_L1_R2** 17.45 TF3_L2_R1 17.83 TF3_L2_R2 17.83 TF7_L1_R1 19.01 TF7_L1_R2 19.01 Tp8 TF7_L2_R1 18.97 TF7_L2_R2 18.97 TF11_L1_R1 21.04 TF11_L1_R2 21.04 TF11_L2_R1 21.44 TF11_L2_R2 21.44 TF4_L1_R1 20.57 TF4_L1_R2 20.57 TF4_L2_R1 20.55 TF4_L2_R2 20.55 TF8_L1_R1 22.38 TF8_L1_R2 22.38 WT TF8_L2_R1 22.46 TF8_L2_R2 22.46 TF12_L1_R1 23.69 TF12_L1_R2 23.69 TF12_L2_R1 23.86 TF12_L2_R2 23.86 *: forward strand of pair-ended RNA reads; **: reverse strand of pair-ended RNA reads.
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Table 2: RNA-seq data sets generated from the B35 cell line transgenic models No. of reads (millions) B35 cell line RNA-seq data sets Untrimmed Trimmed TH1_R1 20.01 17.79 TH1_R2 20.01 17.79 TH12_R1 20.33 17.90 TM1 TH12_R2 20.33 17.90 TH17_R1 9.50 8.68 TH17_R2 9.50 8.68 TH5_R1 22.88 19.22 TH5_R2 22.88 19.22 TH34_R1 22.88 15.93 TmBr3 TH34_R2 22.88 15.93 TH37_R1 22.88 19.43 TH37_R2 22.88 19.43 TH14_R1 6.05 5.52 TH14_R2 6.05 5.52 TH19_R1 7.70 7.05 Tm4 TH19_R2 7.70 7.05 TH25_R1 7.44 6.76 TH25_R2 7.44 6.76 TH22_R1 8.60 7.72 TH22_R2 8.60 7.72 TH27_R1 9.21 8.41 TM5NM1 TH27_R2 9.21 8.41 TH30_R1 8.86 8.04 TH30_R2 8.86 8.04 TH4_R1 7.59 6.80 TH4_R2 7.59 6.80 TH8_R1 8.64 7.74 WT TH8_R2 8.64 7.74 TH10_R1 8.59 7.68 TH10_R2 8.59 7.68
The default TopHat program settings were used for both models and the output files, in BAM format, were used for downstream analysis using Cufflinks. Program parameter settings were as follows:
• Library Type: FR Unstranded;
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• Anchor Length: 8 bp;
• Maximum number of mismatches that can appear in the anchor region of
spliced alignment: 0 bp;
• The minimum intron length: 70 bp;
• The maximum intron length: 500000 bp;
• Allow indel search: Yes;
• Max insertion length: 3 bp;
• Max deletion length: 3 bp;
• Maximum number of alignments to be allowed: 20 bp;
• Minimum intron length that may be found during split-segment search: 50 bp;
• Maximum intron length that may be found during split-segment search:
500000 bp;
• Number of mismatches allowed in the initial read mapping: 2 bp;
• Number of mismatches allowed in each segment alignment for reads mapped
independently: 2 bp;
• Minimum length of read segments: 25 bp;
• Use Own Junctions: No;
• Use Closure Search: No;
• Use Coverage Search: Yes;
• Minimum intron length that may be found during coverage search: 50 bp;
• Maximum intron length that may be found during coverage search: 20000 bp;
• Use Microexon Search: No.
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3.5 Alignment statistics reporting by RseQC
Reads alignment to the respective genomes are recorded in the BAM files produced by TopHat. RseQC (version 2.5) was employed for the calculation of reads mapping statistics of these BAM files. RseQC reports uniquely and non-uniquely mapped read counts, together with the number of reads that were mapped in proper pairs (Wang et al.,
2012).
3.6 Determination of genes and isoforms expression level using Cufflinks
The BAM files from TopHat were fed into Cufflinks (version: 2.1.1) on Galaxy server for transcripts assembly and expression level calculation. Annotation files from
UCSC mouse genome version mm10 and Ensembl rat genome assembly Rnor_5.0 were used as reference annotation.
Program parameter settings were as follows:
• Max Intron Length: 300000 bp;
• Min Isoform Fraction: 0.1;
• Pre MRNA Fraction: 0.15;
• Perform Quartile Normalization: Yes;
• Use Reference Annotation: use reference annotation as a guide;
• Reference Annotation Used: from history;
• Perform Bias Correction: Yes;
• Using reference file: cached;
• Use Multi-read Correct: Yes;
• Use Effective Length Correction: Yes.
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3.7 Merge of the transcripts using Cuffmerge
Cuffmerge takes Cufflink-assembled transfrags for each sample as input files, merges them together and produces a unified GTF file as the final assembly. This final assembly can be used by Cuffdiff to screen for differentially expressed genes or transcripts across samples. Tp8 mice Cufflinks-assembled transcripts were merged together with that of WT mice using Cuffmerge (version: 1.0.0) on Galaxy server using uploaded reference annotation. In case of the data from the four B35 cell lines four merged transcripts files were produced by Cuffmerge using uploaded reference annotation which is the rat genome with biological annotations. These merged transcripts included following data comparisons:
TM1 vs WT; TmBr3 vs WT; Tm4 vs WT and TM5NM1 vs WT. Annotation files from
UCSC mouse genome version mm10 and Ensembl rat genome assembly Rnor_5.0 were used as reference annotation.
3.8 Identification of differentially expressed genes and isoforms by Cuffdiff
For Tp8 data sets TopHat-mapped reads files and the Cuffmerge-generated transcript files were fed to Cuffdiff (version: 0.0.7) on Galaxy server for differential expression analysis between WT and Tp8 mice. In case of the B35 cell line the same approach was utilised. Four groups were created including following data comparisons: TM1 vs WT;
TmBr3 vs WT; Tm4 vs WT and TM5NM1 vs WT.
The following Cuffdiff parameters were used for both data sets:
• Library Normalization Method: Quartile;
• Dispersion Estimation Method: Pooled;
• False Discovery Rate: 0.05;
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• Min Alignment Count: 10 bp;
• Use Multi-read correct: Yes;
• Perform Bias Correction: Yes;
• Include Read Group Datasets: Yes;
• Set Additional Parameters: No.
3.9 GO term enrichment analysis and results visualisation
DEGs lists produced by Cuffdiff were used as input files on DAVID 6.7 server at http://david.abcc.ncifcrf.gov. For B35 cell lines, among functional annotation clusters identified by DAVID for all four groups with a p-value below 0.05, those that were related to neuronal morphology and found in at least two groups were selected and visualised as a heatmap diagram using R (version: 3.1.0) software (Huang da et al., 2009b, Huang da et al.,
2009a, R Core Team, 2014)
Parameter settings used in DAVID pathway analysis are as following:
• GO term: GO_BP_ALL;
• Similarity Term Overlap: 3;
• Similarity Threshold: 0.50;
• Initial Group Membership: 3;
• Final Group Membership: 3;
• Multiple Linkage Threshold: 0.50;
• Enrichment Thresholds: EASE 0.05;
• Display: Benjamini.
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3.10 Visualisation with CummeRbund and Interactive Genome Viewer
An R package, CummeRbund, was used for the illustration of gene and isoform expression results using the Cuffdiff output data. CummeRbund was designed for navigation through large amount of gene and or isoform differentiation expression data produced by Cuffdiff, providing an easier approach for results illustration (Goff et al.,
2012). Interactive Genome Viewer (IGV, version: 2.3) (http:// www.broadinstitute.org/igv/), was used to visualise and compare annotated transcripts and novel transcripts discovered by Cufflinks by reading the GTF file produced by Cuffmerge
(Robinson et al., 2011).
3.11 Quantification of transcript expression and significance determination
Cufflinks measures the relative abundance of transcripts based on FPKM units and reports expressed genes if the FPKM value of each gene is greater than 0 in at least one sample. It was estimated that, for RNA samples prepared using PolyA+ whole-cell method, one transcript copy per cell corresponds to between 0.5 to 5 FPKM, depends on the total amount of RNA molecules in that cell (Kellis et al., 2014). In Cuffdiff, a gene or transcript is considered as differentially expressed if the p-value of observed FPKM log fold change in two or more samples is greater than the False Discovery Rate (FDR) after Benjamini-
Hochberg correction for multiple-testing. The default FDR value used by Cuffdiff is 0.05.
Q-value is the FDR-adjusted p-value (Trapnell et al., 2012).
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3.12 RNA-seq bioinformatic analysis pipeline
Figure 7 summarises steps involved in the bioinformatic analysis of RNA-seq data obtained from Tp8 mice and B35 cell lines overexpressing various Tm isoforms. TopHat maps RNA-seq reads onto mouse or rat genomes, Cufflinks then assembles mapped reads into transfrags. Cuffmerge merges assembled transfrags into a final assembly which is used by Cuffdiff to perform differential expression analysis between different Tm isoform- overexpressing cells and WT samples. Differential expression results can be then further processed using pathway analysis using DAVID or visualised using cummeRbund.
' RNAIseq'Data'Analysis'Pipeline''
Sample 1 Sample 2 Reads' Reads' TopHat' Mapped'reads' Mapped'reads' Cufflinks' Assembled'transfrags' Assembled'transfrags' Cuffmerge'
Final'assembly'
Cuffdiff'
Differen5al'expression'results'
DAVID' R:'cummeRbund'
Pathway'analysis'results' Results'visualisa5on'
Figure 7: RNA-seq data analysis pipeline.
3.13 Reference genomes and gene annotation reference files
UCSC mouse genome version mm10 and Ensembl rat genome assembly Rnor_5.0 were both downloaded from Illumina’s website at https://www.illumina.com/forms/ftp.ilmn.
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4 RESULTS
4.1 RseQC read alignment statistic calculation report
For each dataset processed by TopHat for reads alignment, the number of total read records, uniquely mapped reads, and properly mapped read pairs, together with percentage of uniquely mapped reads and properly mapped read pairs over total reads are summarised in Table 3. Output files from RseQC of each dataset are included in the supplementary tables.
Table 3: RseQC alignment statistics report (unit: read counts)
Properly % of properly Uniquely % of uniquely Data group Dataset Total records mapped read mapped read mapped reads mapped reads pairs pairs
TF4 70892891 61910004 87% 55261036 78% WT mice TF8 77950226 68048837 87% 61126966 78% TF12 80141887 69679711 87% 63280900 79% TF3 54229024 47053919 87% 41615464 77% Tp8 mice TF7 64596671 56181515 87% 48584556 75% TF11 72802503 63837366 88% 57802474 79% TH4 13544878 10938940 81% 7794438 58% WT B35 cells TH8 15489889 12412745 80% 8459170 55% TH10 15383730 12579130 82% 8310426 54% TH1 35036703 27611385 79% 20633888 59% TM1-overexpressing TH12 36464992 27975709 77% 22044092 60% B35 cells TH17 17093491 13807946 81% 9788792 57%
TmBr3- TH5 40934194 31117066 76% 18176352 44% overexpressing B35 TH34 33057056 25656500 78% 17277112 52% cells TH37 40924289 33353479 82% 19080394 47% TH14 10738268 8747483 81% 6354888 59% Tm4-overexpressing TH19 13738520 11160473 81% 7839566 57% B35 cells TH25 13032690 10555195 81% 7425386 57%
TM5NM1- TH22 15139936 12169494 80% 8234692 54% overexpressing B35 TH27 16393418 13171025 80% 9482020 58% cells TH30 15511939 12433527 80% 8963516 58%
4.2 Expression of the tropomyosin genes
The results of expression calculation of transcripts from the four Tm genes are summarised in Table 4, 5, 6, 7, and 8, which include the novel transcripts expression, detection of differential expression of each single transcript/gene, as well as the FPKM
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values of each transcript/gene. Of note Cufflinks identifies transcripts/genes by their NCBI or Ensembl IDs.
Table 4: Expression of tropomyosin transcript/gene in WT and Tp8 mice
WT mice Tp8 mice Gene Transcript ID Differentially FPKM FPKM expressed Novel 3.15 1.48 Tpm1-001 21.99 15.48 Tpm1-003 2.78 1.17 Tpm1-004 0 0 Tpm1-006 1.41 0.56 Tpm1-007 1.28 1.33 αTm (Tpm1) No Tpm1-011 18.07 26.27 Tpm1-013 33.18 24 Tpm1-014 4.77 5.09 Tpm1-015 0.47 0.35 Tpm1-016 22.23 30.26 Total 109.33 105.99 Tpm2-001 1.61 1.49 βTm (Tpm2) Tpm2-201 0.77 0.83 No Total 2.38 2.32 Novel 8.87 9.12 Tpm3-003 0.06 0.08 γTm (Tpm3) Tpm3-004 41.08 39.3 No Tpm3-201 0 0 Total 50.01 48.5 Tpm4-001 (Tm4) 13.34 12.8 δTm (Tpm4) No Total 13.34 12.8
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Table 5: Expression of tropomyosin transcript/gene in WT and TM1-overexprssing B35 cells
TM1- WT B35 cells overexpressing Differentially Gene Transcript ID B35 cells expressed FPKM FPKM Novel 272.31 294.89 Novel 6.36 5.98 Tpm1-201 11.67 7.43 Tpm1-202 26.83 3.29 αTm (Tpm1) Tpm1-203 0 0 No Tpm1-204 0 0 Tpm1-205 24.99 28.2 Tpm1-206 36.8 51.67 Total 378.96 391.46 Novel 7.35 40.59 Novel 13.75 15.29 Novel 0 33.37 No βTm (Tpm2) Novel 1.67 3.23 Tpm2-201 7.54 2.44 Tpm2-202 8.24 95.89 Yes Total 38.55 190.81 Yes Tpm3-201 235.83 241.16 Tpm3-202 29.32 8.35 γ-Tm (Tpm3) No Tpm3-203 18.07 11.78 Total 283.22 261.29 Novel 379 414.53 δ-Tm (Tpm4) Tpm4-0201 (Tm4) 0 0 No Total 379 414.53
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Table 6: Expression of tropomyosin transcript/gene in WT and TmBr3-overexprssing B35 cells
TmBr3- WT B35 cells overexpressing Differentially Gene Transcript ID B35 cells expressed FPKM FPKM Novel 267.56 5.44 Novel 0 1.48 Tpm1-203 0 130.57 Tpm1-206 28.58 25.97 Tpm1-204 5 0 No αTm (Tpm1) Mouse TmBr3 1 1344.97 Tpm1-202 8.27 131.12 Tpm1-201 9.02 4.77 Tpm1-205 20.35 21.41 Total 339.78 1665.73 Yes Novel 6.55 26.25 Novel 1.29 0.38 Novel 12.19 10.47 β-Tm (Tpm2) No Tpm2-201 6.53 6.42 Tpm2-202 7.32 11.5 Total 33.88 55.02 Tpm3-201 208.54 155.48 Tpm3-202 25.87 11.09 γ-Tm (Tpm3) No Tpm3-203 15.97 6.88 Total 250.38 173.45 Novel 251.09 186.25 Novel 0.81 1.03 δ-Tm (Tpm4) Novel 92.6 147.58 No Tpm4-201 (Tm4) 0.35 7.03 Total 344.85 341.89
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Table 7: Expression of tropomyosin transcript/gene in WT and Tm4-overexprssing B35 cells
Tm4- WT B35 cells overexpressing Differentially Gene Transcript ID B35 cells expressed FPKM FPKM Novel 273.76 184.9 Yes Novel 30.11 30.96 Novel 0 1.86 Tpm1-201 9.84 2.89 Tpm1-202 16.37 0.76 α-Tm (Tpm1) No Tpm1-203 10.81 16.3 Tpm1-204 6.15 0.84 Tpm1-205 24.08 17.53 Tpm1-206 16.26 9.39 Total 387.38 265.43 Yes Novel 12.81 27.99 Novel 1.54 7.55 Novel 11.84 14.42 Novel 0 0.59 No β-Tm (Tpm2) Novel 1.31 2.35 Tpm2-201 11.83 13.09 Tpm2-202 0 8.92 Total 39.33 74.91 Yes Novel 53.43 29.95 Tpm3-201 198 196.64 γ-Tm (Tpm3) Tpm3-202 4.41 0 No Tpm3-203 14.45 8.09 Total 270.29 234.68 Novel 392.187 413.48 No δ-Tm (Tpm4) Tpm4-201 (Tm4) 0 1575.92 Total 392.187 1989.4 Yes
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Table 8: Expression of tropomyosin transcript/gene in WT and TM5NM1-overexprssing B35 cells
TM5NM1- WT B35 cells overexpressing Differentially Gene Transcript ID B35 cells expressed FPKM FPKM Novel 273.79 240.1 Novel 46.21 39.95 Novel 0 1.48 Tpm1-203 24.55 16.22 Tpm1-206 0.18 0.07 No α-Tm (Tpm1) Tpm1-204 6.08 0 Tpm1-202 9.53 0.92 Tpm1-201 10.7 6.81 Tpm1-205 24.01 26.78 Total 395.05 332.33 Yes Novel 1.42 9.13 Yes Novel 0.02 0.21 Novel 1.61 6.03 Novel 11.89 13.51 β-Tm (Tpm2) No Novel 11.07 27.42 Tpm2-201 6.91 7.35 Tpm2-202 6.8 19.15 Total 39.72 82.8 Yes Tpm3-201 242.85 235.57 Tpm3-202 30.34 35.95 γ-Tm (Tpm3) No Tpm3-203 18.6 9.46 Total 291.79 280.98 Tpm4-201 (Tm4) 391.03 328 Yes δ-Tm (Tpm4) Total 391.03 328 Yes
4.3 IGV Plot presentation of three sample genes
The sample IGV plots of one differentially expressed gene transthyretin and two tropomyosin genes are presented as Figure 8, 9, and 10 (TCONS_000XXXXXs are
Cufflinks assigned transcript IDs).
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Figure 8: IGV plot of transthyretin gene. Two transcripts of the transthyretin (Ttr) gene are represented by the upper two tracks named TCONS_00028431 and TCONS_00028432 respectively. Details of the Ttr gene expression are discussed in Section 4.5.
Figure 9: IGV plot of tropomyosin α-Tm (Tpm1) in TM1-overexpression B35 cells. Eight Tpm1 transcripts are shown as tracks TCONS_00059854 to TCONS_00059861. Out of these eight Tpm1 transcripts, two are unannotated (TCONS_00059854 and TCONS_00059855).
Figure 10: IGV plot of tropomyosin β-Tm (Tpm2) in TmBr3-overexpression B35 cells. Five Tpm2 transcripts are shown as tracks TCONS_00047852 to TCONS_00047856. Out of these five Tpm2 transcripts, three are unannotated (TCONS_00047852, TCONS_00047853, and TCONS_00047854).
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4.4 Differential transcriptome landscape in Tp8 mouse
A total of 27,193 expressed genes were identified by Cufflinks in both Tp8 and WT samples, including 140 DEGs (q-value < 0.05) and 27,053 non-DEGs. 97 DEGs were up- regulated and 43 down-regulated in Tp8 transgenic mice. The top three up-regulated DEGs were: an unannotated gene located at chromosome 6 (FC = 25.65, p = 0.008), Ttr (FC =
23.54, p = 0.008), and Kcne2 (FC = 22.55, p = 0.008), the top three down-regulated DEGs were: an unannotated gene located at chromosome 10 (unique to WT, p = 0.008), S100a9
(FC = 0.25, p = 0.008), and S100a8 (FC = 0.30, p = 0.008). The top 30 DEGs that were either up- or down-regulated in Tp8 group are listed in Table 9. A total of 69,311 distinct splice variants (isoforms) in both Tp8 and WT samples were identified, which was approximately 2.55 isoforms per gene. Among the isoforms identified, 58 were DEIs (q- value < 0.05) with 43 up-regulated and 15 down-regulated in Tp8 mice. The other 69,253 were determined as expressed in Tp8 or WT but not identified as significantly affected when comparing both mice. The top three up-regulated DEIs were: an unannotated gene located at chromosome 6 (FC = 25.65, p = 0.032), Ttr (FC = 23.54, p = 0.032) , and Kcne2
(FC = 22.55, p = 0.032), the top three down-regulated DEIs were: an unannotated gene located at chromosome 10 (unique to WT, p = 0.032), Acot9 (FC = 0.29, p = 0.032), and
Xdh (FC = 0.42, p = 0.032). Figure 11 shows respective distribution of DEGs and DEIs in terms of fold change range and significance. Table 10 lists the top, in terms of fold change,
30 up-regulated DEIs and the full list of down-regulated DEIs found in Tp8 mice. We found 8 enriched GO term clusters. The top 3 clusters were: system development, immune system process, and response to hormone stimulus. Please see Table 20 for the top 10 enriched GO clusters and S11 for the full set of results.
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Figure 11: Volcano plot of gene (A) and isoform (B) expression in Tp8 and WT mice. Genes and isoforms that were statistically significant (q-value<0.05) are shown in red and are listed in Table S1 and S2.
4.5 Differentially expressed mouse transthyretin gene
4.5.1 Expression levels of transthyretin gene
The mouse transthyretin (Ttr) gene was expressed at 32.24 FPKM in the WT mice and
758.98 FPKM in the Tp8 mice, marking a nearly 24-fold up-regulation in TM5NM1- overexpressing mice. Cufflinks identified a novel transcript (Figure 8, TCONS_00028431) as one of the two transcripts of Ttr, the expression level of TCONS_00028431 is 0.06
FPKM in the WT mice and 1.56 FPKM in the Tp8 mice. The annotated isoform (Figure 8:
TCONS_00028432) is the sole contributor of the differential expression of Ttr gene, with its level being 32.19 FPKM in WT mice and 757.42 FPKM in the Tp8 mice (Figure 12).
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Table 9: Top 30 up- and down-regulated DEGs in Tp8 when compared to WT mice
Top 30 DEGs up-regulated in Tp8 when compared to WT mice NO. GENE CHROMOSOME FPKM WT FPKM Tp8 FOLD CHANGE Q VALUE 1 - chr6:116679061-116685244 0.03 0.69 25.65 0.008 2 Ttr chr18:20665155-20674326 32.24 758.98 23.54 0.008 3 Kcne2 chr16:92292388-92298133 0.14 3.18 22.55 0.008 4 Aqp1 chr6:55336298-55348555 0.15 2.31 15.31 0.008 5 Tmem72 chr6:116691699-116716780 0.07 0.90 13.71 0.008 6 Slc4a5 chr6:83226353-83304945 0.10 1.34 12.99 0.008 7 Folr1 chr7:101858330-101870788 0.68 8.35 12.21 0.008 8 Cldn2 chrX:139800750-139811388 0.20 2.11 10.57 0.008 9 F5 chr1:164115263-164220865 0.18 1.52 8.38 0.008 10 Steap1 chr5:5736321-5749317 0.19 1.57 8.10 0.008 11 Col8a1 chr16:57624255-57754737 0.20 1.20 6.02 0.008 12 1500015O10Rik chr1:43730601-43742564 2.22 12.28 5.53 0.008 13 Kansl2 chr15:98517657-98534282 3.43 17.35 5.06 0.008 14 Clic6 chr16:92498145-92541241 1.12 5.58 4.98 0.008 15 Prr32 chrX:45090903-45092790 0.35 1.71 4.94 0.008 16 Otx2 chr14:48657676-48667644 0.39 1.80 4.63 0.008 17 Slc16a8 chr15:79251015-79255488 0.20 0.87 4.40 0.008 18 Oca2 chr7:56239762-56536517 0.13 0.53 4.01 0.008 19 Prlr chr15:10177237-10349180 0.45 1.56 3.43 0.008 20 Enpp2 chr15:54838678-54952666 42.45 139.73 3.29 0.008 21 Abca4 chr3:122044320-122180061 0.32 1.01 3.22 0.008 22 Sostdc1 chr12:36314161-36318452 1.58 4.75 3.00 0.008 23 H2-Q7 chr17:35439154-35443773 0.26 0.76 2.96 0.038 24 Krt18 chr15:102028215-102032026 0.44 1.27 2.85 0.008 25 Wdr86 chr5:24711735-24730680 0.44 1.24 2.85 0.008 26 Rdh5 chr10:128913587-128919352 1.49 4.14 2.77 0.008 27 Slc39a4 chr15:76612382-76616852 0.24 0.67 2.73 0.008 28 Col8a2 chr4:126286793-126314330 0.64 1.66 2.61 0.008 29 Sulf1 chr1:12692249-12861181 1.47 3.75 2.55 0.008 30 Trpv4 chr5:114622153-114658421 0.57 1.44 2.53 0.008
Top 30 DEGs down-regulated in Tp8 when compared to WT mice NO. GENE CHROMOSOME FPKM WT FPKM Tp8 FOLD CHANGE Q VALUE 1 - chr10:108161257-108161628 0.65 0.00 Unique to WT 0.008 2 S100a9 chr3:90692629-90695721 4.47 1.11 0.25 0.008 3 S100a8 chr3:90669070-90670034 3.90 1.16 0.30 0.038 4 Lcn2 chr2:32384636-32387760 23.67 8.90 0.38 0.008 5 Rtp1 chr16:23429132-23433960 0.72 0.31 0.43 0.008 6 - chr12:19431416-19435140 0.48 0.22 0.45 0.027 7 Hif3a chr7:17030992-17062427 1.72 0.82 0.48 0.008 8 Fam65a chr8:105605228-105622218 59.78 28.63 0.48 0.008 9 Alas2 chrX:150547384-150570622 3.72 1.99 0.53 0.008 10 Xdh chr17:73883894-73950285 2.61 1.40 0.54 0.008 11 Hba-a1,Hba-a2 chr11:32283671-32284493 81.66 45.15 0.55 0.008 12 Hbb-b1,Hbb-bs chr7:103826522-103827929 345.84 193.64 0.56 0.008 13 Serpina3f,Serpina3g chr12:104214543-104241934 1.59 0.90 0.56 0.008 14 Fmo2 chr1:162874211-162898712 0.68 0.38 0.56 0.027 15 Galnt15 chr14:32028818-32062169 1.28 0.73 0.57 0.008 16 - chr4_JH584295_random:62-924 22.04 12.65 0.57 0.008 17 Hbb-bt chr7:103812523-103813923 32.82 19.11 0.58 0.008 18 Hba-a1,Hba-a2 chr11:32296488-32297310 383.24 223.22 0.58 0.008 19 Pisd-ps3 chrUn_JH584304:52188-61823 31.61 18.60 0.59 0.008 20 Adora2a chr10:75316876-75334792 1.60 0.94 0.59 0.008 21 Map3k6 chr4:133238446-133252928 1.67 1.00 0.60 0.008 22 Angptl4 chr17:33774899-33783370 3.03 1.83 0.60 0.008 23 Etnppl chr3:130617447-130637648 9.40 5.73 0.61 0.008 24 Kirrel2 chr7:30446710-30457904 4.62 3.06 0.66 0.008 25 Map3k19 chr1:127813420-127854992 1.84 1.26 0.69 0.043 26 Slc25a34 chr4:141618824-141623859 2.96 2.06 0.70 0.048 27 Mt2 chr8:94172276-94173567 416.88 291.54 0.70 0.008 28 Notch4 chr17:34564294-34588622 1.64 1.19 0.72 0.027 29 Smim3 chr18:60474190-60501983 10.24 7.41 0.72 0.015 30 Mfsd2a chr4:122946850-122961188 18.85 13.65 0.72 0.008
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Table 10: Top 30 up-regulated and all down-regulated DEIs in Tp8 when compare to WT mice
Top 30 DEGs up-regulated in Tp8 when compared to WT mice NO. GENE CHROMOSOME FPKM WT FPKM Tp8 FOLD CHANGE Q VALUE 1 - chr6:116679061-116685244 0.03 0.69 25.65 0.008 2 Ttr chr18:20665155-20674326 32.24 758.98 23.54 0.008 3 Kcne2 chr16:92292388-92298133 0.14 3.18 22.55 0.008 4 Aqp1 chr6:55336298-55348555 0.15 2.31 15.31 0.008 5 Tmem72 chr6:116691699-116716780 0.07 0.90 13.71 0.008 6 Slc4a5 chr6:83226353-83304945 0.10 1.34 12.99 0.008 7 Folr1 chr7:101858330-101870788 0.68 8.35 12.21 0.008 8 Cldn2 chrX:139800750-139811388 0.20 2.11 10.57 0.008 9 F5 chr1:164115263-164220865 0.18 1.52 8.38 0.008 10 Steap1 chr5:5736321-5749317 0.19 1.57 8.10 0.008 11 Col8a1 chr16:57624255-57754737 0.20 1.20 6.02 0.008 12 1500015O10Rik chr1:43730601-43742564 2.22 12.28 5.53 0.008 13 Kansl2 chr15:98517657-98534282 3.43 17.35 5.06 0.008 14 Clic6 chr16:92498145-92541241 1.12 5.58 4.98 0.008 15 Prr32 chrX:45090903-45092790 0.35 1.71 4.94 0.008 16 Otx2 chr14:48657676-48667644 0.39 1.80 4.63 0.008 17 Slc16a8 chr15:79251015-79255488 0.20 0.87 4.40 0.008 18 Oca2 chr7:56239762-56536517 0.13 0.53 4.01 0.008 19 Prlr chr15:10177237-10349180 0.45 1.56 3.43 0.008 20 Enpp2 chr15:54838678-54952666 42.45 139.73 3.29 0.008 21 Abca4 chr3:122044320-122180061 0.32 1.01 3.22 0.008 22 Sostdc1 chr12:36314161-36318452 1.58 4.75 3.00 0.008 23 H2-Q7 chr17:35439154-35443773 0.26 0.76 2.96 0.038 24 Krt18 chr15:102028215-102032026 0.44 1.27 2.85 0.008 25 Wdr86 chr5:24711735-24730680 0.44 1.24 2.85 0.008 26 Rdh5 chr10:128913587-128919352 1.49 4.14 2.77 0.008 27 Slc39a4 chr15:76612382-76616852 0.24 0.67 2.73 0.008 28 Col8a2 chr4:126286793-126314330 0.64 1.66 2.61 0.008 29 Sulf1 chr1:12692249-12861181 1.47 3.75 2.55 0.008 30 Trpv4 chr5:114622153-114658421 0.57 1.44 2.53 0.008
Top 30 DEGs down-regulated in Tp8 when compared to WT mice NO. GENE CHROMOSOME FPKM WT FPKM Tp8 FOLD CHANGE Q VALUE 1 - chr10:108161257-108161628 0.65 0.00 Unique to WT 0.008 2 S100a9 chr3:90692629-90695721 4.47 1.11 0.25 0.008 3 S100a8 chr3:90669070-90670034 3.90 1.16 0.30 0.038 4 Lcn2 chr2:32384636-32387760 23.67 8.90 0.38 0.008 5 Rtp1 chr16:23429132-23433960 0.72 0.31 0.43 0.008 6 - chr12:19431416-19435140 0.48 0.22 0.45 0.027 7 Hif3a chr7:17030992-17062427 1.72 0.82 0.48 0.008 8 Fam65a chr8:105605228-105622218 59.78 28.63 0.48 0.008 9 Alas2 chrX:150547384-150570622 3.72 1.99 0.53 0.008 10 Xdh chr17:73883894-73950285 2.61 1.40 0.54 0.008 11 Hba-a1,Hba-a2 chr11:32283671-32284493 81.66 45.15 0.55 0.008 12 Hbb-b1,Hbb-bs chr7:103826522-103827929 345.84 193.64 0.56 0.008 13 Serpina3f,Serpina3g chr12:104214543-104241934 1.59 0.90 0.56 0.008 14 Fmo2 chr1:162874211-162898712 0.68 0.38 0.56 0.027 15 Galnt15 chr14:32028818-32062169 1.28 0.73 0.57 0.008 16 - chr4_JH584295_random:62-924 22.04 12.65 0.57 0.008 17 Hbb-bt chr7:103812523-103813923 32.82 19.11 0.58 0.008 18 Hba-a1,Hba-a2 chr11:32296488-32297310 383.24 223.22 0.58 0.008 19 Pisd-ps3 chrUn_JH584304:52188-61823 31.61 18.60 0.59 0.008 20 Adora2a chr10:75316876-75334792 1.60 0.94 0.59 0.008 21 Map3k6 chr4:133238446-133252928 1.67 1.00 0.60 0.008 22 Angptl4 chr17:33774899-33783370 3.03 1.83 0.60 0.008 23 Etnppl chr3:130617447-130637648 9.40 5.73 0.61 0.008 24 Kirrel2 chr7:30446710-30457904 4.62 3.06 0.66 0.008 25 Map3k19 chr1:127813420-127854992 1.84 1.26 0.69 0.043 26 Slc25a34 chr4:141618824-141623859 2.96 2.06 0.70 0.048 27 Mt2 chr8:94172276-94173567 416.88 291.54 0.70 0.008 28 Notch4 chr17:34564294-34588622 1.64 1.19 0.72 0.027 29 Smim3 chr18:60474190-60501983 10.24 7.41 0.72 0.015 30 Mfsd2a chr4:122946850-122961188 18.85 13.65 0.72 0.008
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757.417' 758.97544' 1000'
100' 32.1798' 32.2421736'
10' 1.55844' WT' FPKM% 1' Tp8'
0.1' 0.0623736'
0.01' TCONS_00028431' TCONS_00028432' Ttr'total'expression'
Figure 12: Levels of Ttr transcripts TCONS_00028431, TCONS_00028432, and total gene expression. Error bar represents one standard deviation.
4.5.2 Structural comparison between the annotated and novel transcripts of
transthyretin gene
The intron/exon structures of the two Ttr isoforms are illustrated in Figure 8. In the upper panel of the figure, there are two Ttr isoforms. Ttr reference structure from genome build mm10 is shown in the lower panel. The lengths of exon 2 and 4 are the same in both isoforms. Exon 1 of the unannotated isoform TCONS_00028431 is 94 nucleotides longer that that of the annotated TCONS_00028432 while exon 3 of TCON_00028431 is 4 nucleotides shorter than that of TCONS_00028432.
4.5.3 Depth of read coverage over Ttr gene in Tp8 mice
A sample graph showing the read coverage over the 3rd exon of the Ttr gene in Tp8 mice is illustrated in Figure13. The top panel comprises a genomic ruler showing the length of the region in bp at the current resolution. The bars in the middle panel represent
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the depths of read coverage at each nucleotide position. The lower panel shows the reads mapped to the transcript sequence shown at the bottom.
Figure 13: Reads coverage over the 3rd exon of Ttr gene in Tp8 mice.
4.6 Comparative transcriptome patterns in B35 cell lines
In the rat neuroblastoma cell line B35 model, Cufflinks discovered an average of
30,239 genes expressed from the four Tm-overexpressing groups across the WT group.
The average number of isoform expression detected from these four groups across the WT group was 63,902. Among the expressed genes and isoforms found from the four groups, the average numbers of DEGs and DEIs were 2,170 (7.18% of total expressed genes) and
996 (1.56% of total expressed isoforms) respectively. DAVID identified from 153 to 460 enriched GO terms with p-values below 0.5 in four groups, with an average of 308 terms.
4.6.1 TM1-overexpressing cells
A total of 30,622 expressed genes were identified by Cufflinks across B35 cells overexpressing TM1 isoform and WT cells, including 1,368 DEGs (q-value < 0.05) and
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29,254 non-DEGs. 766 DEGs were up-regulated and 602 down-regulated in TM1- overexpressing cells. The top three up-regulated and annotated DEGs were:
ENSRNOG00000037962 (unique to TM1 group, p = 0.002), Rsg1 (unique to TM1 group, p
= 0.009) , and Pcdh9 (FC = 83.00, p = 0.002), the top three down-regulated and annotated
DEGs were: Prdm5 (unique to WT, p = 0.002), Rab15 (FC = 0.02, p = 0.035), and Pdpn
(FC = 0.08, p = 0.002). The top 30 annotated DEGs were listed in Table 11. Cufflinks also identified 65,646 isoforms including 564 DEIs (q-value < 0.05) and 65,082 non-DEIs across TM1 and WT groups, and that was approximately 2.14 isoforms per gene. 355 out of these 564 isoforms were up-regulated and 209 down-regulated in TM1 cells. The top three up-regulated and annotated DEIs were: ENSRNOG00000037962 (unique to TM1 group, p
= 0.005), ENSRNOG00000045589 (FC = 16.33, p = 0.019) , and Tpm2 (FC = 11.64, p =
0.005), the top three down-regulated and annotated DEIs were: Prdm5 (unique to WT, p =
0.005), Pdpn (FC = 0.08, p = 0.005), and Qprt (FC = 0.13, p = 0.005). The top 30 annotated isoforms that are either up- or down-regulated in TM1 cells are shown in Table 12. We found 22 enriched GO term clusters. The top 3 clusters were: biosynthetic process, regulation of developmental process, and system development. Please see Table 20 for the top 10 enriched GO clusters and S12 for the full set of results.
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Table 11: Top 30 annotated DEGs up- and down-regulated in TM1-overexpressing B35 cells when compared to WT cells
Top 30 annotated DEGs up-regulated in TM1-overexpressing B35 cells when compared to WT cells NO. GENE CHROMOSOME FPKM WT FPKM TM1 FOLD CHANGE Q VALUE 1 ENSRNOG00000037962 2:75352349-75352895 0.00 1.81 Unique to TM1 0.002 2 Rsg1 5:163450670-163454711 0.00 1.37 Unique to TM1 0.009 3 Pcdh9 15:81282518-81288234 1.46 121.47 83.00 0.002 4 Aqp8 1:200483426-200489432 1.16 24.71 21.31 0.002 5 Ntm 8:30073216-30511787 0.27 4.52 16.84 0.002 6 ENSRNOG00000045589 14:46699203-46704990 14633.00 238962.00 16.33 0.006 7 Krt31 10:87732924-87754301 0.19 2.52 13.35 0.002 8 Ptpn7 13:57010178-57023509 1.28 15.49 12.13 0.002 9 Krt7 7:140860979-140877143 0.58 5.37 9.31 0.002 10 Fscn3 4:55466551-55477464 0.49 4.04 8.32 0.002 11 Dusp27 13:89180886-89210605 0.50 3.82 7.63 0.002 12 Krt19 10:87848517-87854463 2.20 15.14 6.89 0.002 13 Socs2 7:36556865-36562223 0.89 5.99 6.70 0.002 14 Wnt2b 2:226852246-226869561 0.30 1.99 6.69 0.002 15 Slc7a1 12:10119563-10261380 28.69 188.87 6.58 0.002 16 Nefl 15:46792210-46797571 1.97 12.45 6.31 0.002 17 Krt15 10:87839484-87843297 15.54 88.40 5.69 0.002 18 Gsta1 9:26283550-26300195 0.53 2.91 5.49 0.018 19 Isl1 2:66870728-66884163 0.62 3.11 5.04 0.002 20 Pomp 12:11094517-11107003 2.58 12.87 4.99 0.006 21 Tpm2 5:63541128-63550268 38.55 190.82 4.95 0.002 22 Il1rl1 9:46818260-46866883 1.12 5.51 4.92 0.002 23 Itpripl1 3:126140445-126145143 0.46 2.23 4.88 0.002 24 MGC109340 X:106632746-106634369 0.33 1.58 4.81 0.035 25 RGD1561408 X:116076244-116092546 1.08 4.90 4.55 0.011 26 Col20a1 3:180202418-180236868 3.19 14.24 4.47 0.002 27 Hfe2 2:218142370-218146363 0.26 1.15 4.39 0.026 28 ENSRNOG00000027542 1:213268570-213306797 5.21 22.64 4.35 0.011 29 MGC114427 X:147509561-147514820 2.41 10.23 4.25 0.002 30 Krt42 10:87958843-87966157 2.65 11.04 4.17 0.002
Top 30 annotated DEGs down-regulated in TM1-overexpressing B35 cells when compared to WT cells NO. GENE CHROMOSOME FPKM WT FPKM TM1 FOLD CHANGE Q VALUE 1 Prdm5 4:161443641-161604711 2.70 0.00 Unique to WT 0.002 2 Rab15 6:109242427-109266332 3.16 0.08 0.02 0.035 3 Pdpn 5:165646113-165679595 15.08 1.23 0.08 0.002 4 Qprt 1:205534750-205550121 7.05 0.83 0.12 0.002 5 Zpld1 11:51087819-51135794 3.97 0.55 0.14 0.002 6 Cpq 7:71880823-72338526 1.64 0.23 0.14 0.030 7 Vsig10 12:46785731-46819519 2.98 0.43 0.14 0.002 8 Col2a1 7:139646746-139675763 3.14 0.50 0.16 0.002 9 Sgk3 5:13847951-13970452 5.99 0.96 0.16 0.002 10 Mecom 2:137080582-137139270 1.26 0.21 0.17 0.002 11 ENSRNOG00000030487 3:62363997-62434837 1.59 0.29 0.18 0.034 12 Plscr2 8:99199388-99210702 10.31 2.02 0.20 0.002 13 Olr1 4:211883404-211905489 2.73 0.57 0.21 0.002 14 Lrp3 1:92563399-92593301 4.84 1.03 0.21 0.002 15 Gpr17 18:24422407-24538352 2.04 0.45 0.22 0.032 16 Aig1 1:9445189-9665307 7.35 1.64 0.22 0.002 17 Trpv4 12:49492069-49529957 2.84 0.66 0.23 0.002 18 Fzd6 7:78317822-78349530 4.87 1.16 0.24 0.002 19 Lrtm2 4:217213922-217324172 3.93 0.97 0.25 0.002 20 Col11a2 20:5909381-5938415 3.72 0.92 0.25 0.002 21 Snapc2 12:4690238-4693261 100.75 25.39 0.25 0.002 22 Pllp 19:10725891-10746753 11.04 2.79 0.25 0.002 23 Car3 2:107900450-107914318 15.56 3.94 0.25 0.002 24 Aebp1 14:86792887-86802767 36.71 9.33 0.25 0.002 25 Lpin1 6:51534732-51602407 1.41 0.37 0.26 0.009 26 Klf12 15:88092572-88331655 1.87 0.49 0.26 0.002 27 Foxa2 3:148793486-148797682 5.70 1.53 0.27 0.002 28 Dkk3 1:183921624-183961838 80.74 22.01 0.27 0.002 29 Cpe 16:26785729-26888884 3.69 1.06 0.29 0.002 30 Sgsh 10:108075404-108079089 5.85 1.69 0.29 0.004
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Table 12: Top 30 annotated DEIs up- and down-regulated in TM1-overexpressing B35 cells when compared to WT cells
Top 30 annotated DEIs up-regulated in TM1-overexpressing B35 cells when compared to WT cells NO. GENE CHROMOSOME FPKM WT FPKM TM1 FOLD CHANGE Q VALUE 1 ENSRNOG00000037962 2:75352349-75352895 0.00 1.81 Unique to TM1 0.005 2 ENSRNOG00000045589 14:46699203-46704990 14633.00 238962.00 16.33 0.019 3 Tpm2 5:63541128-63550268 8.24 95.89 11.64 0.005 4 Ntm 8:30073216-30511787 0.27 2.86 10.71 0.005 5 Rpl17 18:70108977-70112081 3.14 25.91 8.24 0.039 6 Krt19 10:87848517-87854463 1.37 10.20 7.43 0.035 7 Krt15 10:87839484-87843297 15.54 88.40 5.69 0.005 8 Socs2 7:36556865-36562223 0.55 3.07 5.59 0.045 9 Nefl 15:46792210-46797571 1.81 9.84 5.44 0.005 10 Itpripl1 3:126140445-126145143 0.44 2.23 5.00 0.005 11 Pomp 12:11094517-11107003 2.58 12.87 4.99 0.019 12 Col20a1 3:180202418-180236868 1.74 8.69 4.99 0.005 13 Zfp259 8:49188978-49198583 4.89 22.34 4.57 0.016 14 Hoxd3 3:68127093-68137110 0.31 1.31 4.27 0.037 15 Vax1 1:287693960-287700713 1.95 8.14 4.18 0.005 16 Cxcl12 4:215195688-215208497 1.96 8.19 4.18 0.012 17 Nfix 19:36793701-36890342 3.17 13.02 4.11 0.005 18 Dlx5 4:32203711-32259592 1.99 7.92 3.99 0.005 19 Efnb2 16:86044170-86088761 3.00 11.75 3.92 0.005 20 Fam84a 6:48123247-48128328 1.12 4.29 3.82 0.005 21 Plac9 16:3817165-3831488 18.91 70.15 3.71 0.005 22 ENSRNOG00000031560 10:72461295-72461778 4.14 15.08 3.64 0.005 23 Ubl3 12:9951198-9998000 58.71 212.01 3.61 0.005 24 Fmnl3 X:115485185-115536737 4.60 16.48 3.58 0.005 25 Ppp1r1b 10:86100810-86109846 1.14 4.04 3.55 0.005 26 Apobec3b 7:121099571-121118792 1.68 5.78 3.43 0.048 27 MGC114427 X:147509561-147514820 1.87 6.38 3.40 0.005 28 ENSRNOG00000031967 6:115866239-115866603 24.93 84.78 3.40 0.005 29 Col22a1 7:112952139-113165457 3.59 12.16 3.38 0.005 30 Prr18 1:54238730-54242565 0.65 2.15 3.32 0.005
Top 30 annotated DEIs down-regulated in TM1-overexpressing B35 cells when compared to WT cells NO. GENE CHROMOSOME FPKM WT FPKM TM1 FOLD CHANGE Q VALUE 1 Prdm5 4:161443641-161604711 1.89 0.00 Unique to WT 0.005 2 Pdpn 5:165646113-165679595 15.08 1.23 0.08 0.005 3 Qprt 1:205534750-205550121 6.55 0.83 0.13 0.005 4 Olr1 4:211883404-211905489 2.48 0.31 0.13 0.048 5 Atf6 13:93668054-93854836 8.69 1.36 0.14 0.005 6 Vsig10 12:46785731-46819519 2.84 0.43 0.15 0.005 7 Sgk3 5:13847951-13970452 5.68 0.88 0.16 0.005 8 Col2a1 7:139646746-139675763 2.48 0.43 0.17 0.005 9 Fzd6 7:78317822-78349530 3.62 0.63 0.17 0.030 10 Car3 2:107900450-107914318 10.11 1.94 0.19 0.012 11 Snapc2 12:4690238-4693261 63.57 12.44 0.20 0.005 12 Mag 1:90500838-90516459 28.36 5.93 0.21 0.030 13 Plscr2 8:99199388-99210702 9.44 2.02 0.21 0.005 14 Pkd1 10:13732198-13813559 3.43 0.74 0.22 0.045 15 Klf12 15:88092572-88331655 1.14 0.25 0.22 0.024 16 Aebp1 14:86792887-86802767 33.31 7.25 0.22 0.005 17 Stard13 12:1007722-1356521 17.21 3.75 0.22 0.032 18 Pld1 2:133357245-133554180 5.87 1.31 0.22 0.005 19 Aig1 1:9445189-9665307 6.52 1.46 0.22 0.005 20 Foxa2 3:148793486-148797682 5.70 1.35 0.24 0.034 21 Frmd4a 17:79293876-79612843 9.88 2.44 0.25 0.024 22 Cd200 11:64474048-64501029 7.60 1.92 0.25 0.009 23 Pllp 19:10725891-10746753 11.04 2.79 0.25 0.005 24 Xylt1 1:193935672-194221114 3.49 0.92 0.26 0.005 25 Adam23 9:72279940-72437622 6.22 1.67 0.27 0.009 26 Col11a2 20:5909381-5938415 2.87 0.79 0.27 0.030 27 Cpe 16:26785729-26888884 3.69 1.06 0.29 0.005 28 ENSRNOG00000005323 6:108493026-108565613 6.63 2.02 0.30 0.009 29 Elavl1 12:4614832-4658900 18.20 5.66 0.31 0.043 30 Aatk 10:108786270-108822529 11.12 3.49 0.31 0.005
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4.6.2 TmBr3-overexpressing cells
Cufflinks identified a total of 31,421 expressed genes across TmBr3 and WT groups, including 1,141 DEGs (q-value < 0.05) and 30,280 non-DEGs. Among 1,141 DEGs 900 were found up-regulated and the other 241 down-regulated in TmBr3 group. The top three up-regulated and annotated DEGs were: ENSRNOG00000031844 (unique to TmBr3 group, p = 0.004), ENSRNOG00000027058 (unique to TmBr3 group, p = 0.002), and
ENSRNOT00000048512 (unique to TmBr3 group, p = 0.002), the top three down-regulated and annotated DEGs were: Prdm5 (unique to WT, p = 0.002), Mecom (FC = 0.02, p =
0.018), and Klfl2 (FC = 0.07, p = 0.012). The top 30 annotated genes that are either up- regulated or down-regulated in TmBr3 group are listed in Table 13. With expression of
64,928 isoforms approximately 2.07 isoforms per gene were expressed. The set of 64,928 isoforms included 513 DEIs (q-value < 0.05) with 450 isoforms up-regulated and 63 down- regulated in the TmBr3 overexpressing cells. The top three up-regulated and annotated
DEIs were: ENSRNOG00000031844 (unique to TmBr3 group, p = 0.010),
ENSRNOG00000027058 (unique to TmBr3 group, p = 0.006), and
ENSRNOT00000048512 (unique to TmBr3 group, p = 0.006), the top three down-regulated and annotated DEIs were: Prdm5 (unique to WT, p = 0.006), Gabra1 (FC = 0.07, p =
0.006), and Rab15 (FC = 0.09, p = 0.014). The top 30 annotated up- and down-regulated were listed in Table 14. We found 19 enriched GO term clusters. The top 3 clusters were: biosynthetic process, system development, and response to hormone stimulus. Please see
Table 20 for the top 10 enriched GO clusters and S13 for the full set of results.
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Table 13: Top 30 annotated DEGs up- and down-regulated in TmBr3-overexpressing B35 cells when compared to WT cells
Top 30 annotated DEGs up-regulated in TmBr3-overexpressing B35 cells when compared to WT cells NO. GENE CHROMOSOME FPKM WT FPKM TmBr3 FOLD CHANGE Q VALUE 1 ENSRNOG00000031844 13:11957532-12804561 0.00 3.34 Unique to TmBr3 0.004 2 ENSRNOG00000027058 16:4812760-5730476 0.00 3.21 Unique to TmBr3 0.002 3 ENSRNOG00000048512 1:201802552-201802872 0.00 3.07 Unique to TmBr3 0.002 4 ENSRNOG00000047915 3:22113747-22114354 0.00 2.99 Unique to TmBr3 0.002 5 ENSRNOG00000042864 15:22874178-22874627 0.00 2.83 Unique to TmBr3 0.002 6 Card11 12:17781138-17843739 0.00 2.50 Unique to TmBr3 0.002 7 ENSRNOG00000032106 15:92840302-92840693 0.00 1.98 Unique to TmBr3 0.004 8 Wfdc10 3:167298957-167300311 0.00 1.89 Unique to TmBr3 0.002 9 Lin7a 7:49443157-49896872 0.00 1.82 Unique to TmBr3 0.002 10 Ntm 8:30073168-30511888 0.44 23.94 54.00 0.002 11 Mal 3:127099277-127123286 0.35 16.13 46.59 0.002 12 Adamts15 8:32003563-32026941 0.10 4.72 46.02 0.002 13 Ramp3 14:80555462-80572980 0.27 8.62 31.49 0.032 14 Faim2 X:115662282-115689157 0.32 7.50 23.70 0.002 15 Cpa4 4:57644666-57668737 0.09 1.75 20.41 0.041 16 Rdh5 7:3306292-3312163 0.24 4.63 19.62 0.024 17 Adamts17 1:128878135-129194836 0.13 2.29 18.21 0.004 18 Cldn11 2:135520049-135533355 0.61 9.68 15.78 0.002 19 Igfbp5 9:79920612-79937408 48.03 691.02 14.39 0.011 20 Lox 18:46714684-46821060 0.34 4.91 14.36 0.002 21 Ddit4 20:31315029-31317123 3.92 55.89 14.27 0.002 22 Hs3st6 10:13938605-13944711 0.19 2.72 14.08 0.049 23 ENSRNOG00000014898 1:114022938-114275043 0.71 9.79 13.88 0.034 24 Pde4b 5:125536301-126002586 0.95 12.33 13.00 0.002 25 Hmgcs2 2:219928550-219954859 8.45 108.51 12.84 0.002 26 Aqp5 X:115753740-115757278 0.33 4.09 12.34 0.024 27 Cldn14 11:37721800-37816957 2.37 27.99 11.82 0.004 28 WIF1 7:63077645-63147645 3.76 44.40 11.79 0.002 29 Postn 2:163331049-163362444 1.91 21.46 11.23 0.002 30 Krt15 10:87839484-87843297 13.67 149.20 10.91 0.002
Top 30 annotated DEGs down-regulated in TmBr3-overexpressing B35 cells when compared to WT cells NO. GENE CHROMOSOME FPKM WT FPKM TmBr3 FOLD CHANGE Q VALUE 1 Prdm5 4:161443641-161604711 2.37 0.00 Unique to WT 0.002 2 Mecom 2:137080582-137139270 1.10 0.03 0.02 0.018 3 Klf12 15:88092656-88331655 1.69 0.12 0.07 0.012 4 Gabra1 10:27154358-27210126 32.35 2.45 0.08 0.002 5 Rab15 6:109242427-109266332 2.79 0.25 0.09 0.005 6 Mtmr7 16:54469055-54560062 1.06 0.10 0.10 0.037 7 Lrch2 X:118676481-118759461 6.59 0.67 0.10 0.002 8 mageb1l1 X:55067824-55134504 9.40 1.00 0.11 0.004 9 Ccdc68 18:67564599-67626011 18.23 2.06 0.11 0.002 10 ENSRNOG00000037911 X:75109507-75152133 22.23 3.26 0.15 0.016 11 Spon1 1:185603721-185903509 3.43 0.52 0.15 0.002 12 Ptprb 7:59359088-59441061 4.89 0.76 0.16 0.011 13 ENSRNOG00000037559 6:146361761-146375804 1.72 0.27 0.16 0.039 14 Car8 5:26009686-26106856 4.78 0.78 0.16 0.011 15 Plscr2 8:99199388-99210702 9.23 1.55 0.17 0.002 16 Tmtc1 4:246759450-246979396 1.99 0.34 0.17 0.019 17 RGD1312005 18:53346500-53361030 2.65 0.46 0.17 0.025 18 Myof 1:264066286-264215740 41.50 7.41 0.18 0.002 19 Man2a1 9:111831032-111987870 4.73 0.87 0.18 0.002 20 Leprel1 11:82548587-82690068 3.45 0.65 0.19 0.013 21 Rab27b 18:67640984-67703858 2.06 0.39 0.19 0.018 22 Mdn1 5:52539526-52587841 3.78 0.75 0.20 0.010 23 Rgs16 13:76145219-76150397 15.97 3.23 0.20 0.004 24 Parp8 2:67463951-67546909 1.20 0.25 0.21 0.036 25 Pdlim3 16:49271216-49303147 5.72 1.25 0.22 0.031 26 ENSRNOG00000039200 8:44271900-44283707 7.79 1.70 0.22 0.002 27 Nrp2 9:69307002-69422047 28.49 6.49 0.23 0.002 28 Shroom4 X:17500805-17711666 1.07 0.25 0.23 0.013 29 Trim68 1:174021169-174032378 3.40 0.80 0.23 0.046 30 Ankle1 16:19660544-19666683 5.09 1.21 0.24 0.006
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Table 14: Top 30 annotated DEIs up- and down-regulated in TmBr3-overexpressing B35 cells when compared to WT cells
Top 30 annotated DEIs up-regulated in TmBr3-overexpressing B35 cells when compared to WT cells NO. GENE CHROMOSOME FPKM WT FPKM TmBr3 FOLD CHANGE Q VALUE 1 ENSRNOG00000031844 13:11957532-12804561 0.00 3.34 Unique to TmBr3 0.010 2 ENSRNOG00000027058 16:4812760-5730476 0.00 3.21 Unique to TmBr3 0.006 3 ENSRNOG00000048512 1:201802552-201802872 0.00 3.07 Unique to TmBr3 0.006 4 ENSRNOG00000047915 3:22113747-22114354 0.00 2.99 Unique to TmBr3 0.006 5 ENSRNOG00000042864 15:22874178-22874627 0.00 2.83 Unique to TmBr3 0.006 6 ENSRNOG00000032106 15:92840302-92840693 0.00 1.98 Unique to TmBr3 0.010 7 Wfdc10 3:167298957-167300311 0.00 1.89 Unique to TmBr3 0.006 8 Lin7a 7:49443157-49896872 0.00 1.36 Unique to TmBr3 0.006 9 Card11 12:17781138-17843739 0.00 1.00 Unique to TmBr3 0.006 10 Mal 3:127099277-127123286 0.35 16.13 46.59 0.006 11 Adamts15 8:32003563-32026941 0.10 4.72 46.02 0.006 12 Adamts17 1:128878135-129194836 0.10 2.29 21.91 0.010 13 Lox 18:46714684-46821060 0.24 4.90 20.07 0.010 14 ENSRNOG00000032609 MT:5009-5321 126.65 2285.44 18.04 0.006 15 WIF1 7:63077645-63147645 2.65 42.79 16.12 0.006 16 Ddit4 20:31315029-31317123 3.51 55.79 15.90 0.006 17 Cldn11 2:135520049-135533355 0.61 9.68 15.78 0.006 18 Igfbp5 9:79920612-79937408 48.03 691.02 14.39 0.028 19 Hmgcs2 2:219928550-219954859 8.45 108.51 12.84 0.006 20 Krt15 10:87839484-87843297 13.67 149.20 10.91 0.006 21 Clca1 2:269425676-269451501 0.24 2.55 10.44 0.006 22 RGD1560088 1:91866058-91879562 0.19 2.03 10.41 0.020 23 Clec2dl1 4:227477996-227697509 1.34 13.10 9.77 0.050 24 Tmprss5 8:52026464-52049778 1.65 15.67 9.52 0.006 25 Bmp7 3:176944340-177020807 1.95 18.26 9.37 0.010 26 ENSRNOG00000003324 10:9652575-9653493 6.73 61.04 9.07 0.006 27 Dhrs3 5:166489860-166524733 5.26 46.13 8.77 0.006 28 Galntl1 6:112245992-112422114 0.46 3.94 8.66 0.010 29 Fbln5 6:134856691-134936033 5.28 44.09 8.35 0.006 30 Il11 1:75891523-75897820 0.58 4.70 8.08 0.017
Top 30 annotated DEIs down-regulated in TmBr3-overexpressing B35 cells when compared to WT cells NO. GENE CHROMOSOME FPKM WT FPKM TmBr3 FOLD CHANGE Q VALUE 1 Prdm5 4:161443641-161604711 1.68 0.00 Unique to WT 0.006 2 Gabra1 10:27154358-27210126 26.95 2.00 0.07 0.006 3 Rab15 6:109242427-109266332 2.79 0.25 0.09 0.014 4 Lrch2 X:118676481-118759461 5.66 0.64 0.11 0.006 5 Myof 1:264066286-264215740 26.19 3.41 0.13 0.006 6 Myof 1:264066286-264215740 12.62 2.10 0.17 0.031 7 Plscr2 8:99199388-99210702 8.46 1.55 0.18 0.006 8 Cenpf 13:112758854-112804974 9.77 1.95 0.20 0.020 9 Shroom4 X:17500805-17711666 1.07 0.25 0.23 0.043 10 Rgs16 13:76145219-76150397 13.19 3.19 0.24 0.006 11 Gpnmb 4:143383025-143404102 195.61 55.83 0.29 0.006 12 Bid 4:220531876-220554348 15.28 4.94 0.32 0.028 13 ENSRNOG00000018121 2:76756934-76757836 37.67 12.30 0.33 0.020 14 Spry2 15:93662776-93669293 36.51 11.93 0.33 0.035 15 Fancd2 4:208784791-208848180 8.85 2.91 0.33 0.045 16 Timm44 12:4669952-4686653 104.54 34.65 0.33 0.006 17 Ablim1 1:285260912-285401129 22.65 7.76 0.34 0.026 18 Ppic 18:47585435-47598040 75.16 27.69 0.37 0.006 19 Ctgf 1:23331546-23334660 300.70 113.27 0.38 0.006 20 Aspm 13:61564058-61609831 8.45 3.19 0.38 0.020 21 Rfc3 12:1439596-1450351 204.22 78.50 0.38 0.006 22 Mmp2 19:26629725-26659016 47.66 18.44 0.39 0.006 23 Clu 15:48926515-48939266 45.76 17.91 0.39 0.006 24 Smc4 2:184962124-184990525 29.59 11.82 0.40 0.006 25 Bub1 3:126929122-126960429 24.22 10.31 0.43 0.043
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4.6.3 Tm4-overexprssing cells
A total of 29,086 expressed genes were identified by Cufflinks across B35 cells overexpressing Tm4 isoform and WT cells, including 2,183 DEGs (q-value < 0.05) and
26,903 non-DEGs. Among DGEs, 1,227 were up-regulated and 956 down-regulated in
Tm4-overexpressing cells. The top three up-regulated and annotated DEGs were: Cyp3a62
(unique to Tm4 group, p = 0.001), Acnat2 (unique to Tm4 group, p = 0.001), and Chrna7
(FC = 11.74, p = 0.001), the top three down-regulated and annotated DEGs were: Prdm5
(unique to WT, p = 0.001), Pdpn (FC = 0.03, p = 0.001), and Qprt (FC = 0.03, p = 0.03).
The top 30 annotated genes that were either up- or down-regulated in Tm4 transgenic cells were listed in Table 15. Cufflinks also identified a total of 62,227 isoforms across Tm4 and
WT groups, and that was approximately 2.14 isoforms per gene. Among these isoforms identified, 927 were DEIs (q-value < 0.05) and 61,300 were non-DEIs. 564 out of 927
DEIs were up-regulated and the other 363 down-regulated in Tm4 group. The top three up- regulated and annotated DEIs were: Cyp3a62 (unique to Tm4 group, p = 0.003), Acnat2
(unique to Tm4 group, p = 0.003), and Nefl (FC = 10.66, p = 0.003), the top three down- regulated and annotated DEIs were: Prdm5 (unique to WT, p = 0.003), Pdpn (FC = 0.03, p
= 0.003), and Aatk (FC = 0.05, p = 0.003). The top 30 annotated isoforms that are either up- or down-regulated in Tm4 group are listed in Table 16. We found 69 enriched GO term clusters. The top 3 clusters were: system development, biological regulation, and cell morphogenesis. Please see Table 20 for the top 10 enriched GO clusters and S14 for the full set of results.
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Table 15: Top 30 annotated DEGs up- and down-regulated in Tm4-overexpressing B35 cells when compared to WT cells
Top 30 annotated DEGs up-regulated in Tm4-overexpressing B35 cells when compared to WT cells NO. GENE CHROMOSOME FPKM WT FPKM Tm4 FOLD CHANGE Q VALUE 1 Cyp3a62 12:20667011-20696614 0.00 42.55 Unique to Tm4 0.001 2 Acnat2 5:69174930-69207358 0.00 7.05 Unique to Tm4 0.001 3 Chrna7 1:125026824-125158179 0.23 2.74 11.74 0.001 4 Dusp27 13:89180886-89210662 0.51 5.75 11.18 0.001 5 Lynx1 7:115888262-115893454 0.51 5.58 10.98 0.001 6 Ptpn7 13:57010183-57023672 1.21 13.12 10.88 0.001 7 Nefl 15:46792228-46797571 2.03 20.88 10.28 0.001 8 Fscn3 4:55467407-55477443 0.35 2.69 7.78 0.003 9 Hpgd 16:37258875-37297010 0.45 3.48 7.68 0.004 10 Galntl4 1:183278638-183588615 1.04 7.45 7.17 0.001 11 Trim55 2:124140046-124182027 0.46 3.19 6.97 0.001 12 Lpl 16:22431493-22684825 1.03 6.74 6.56 0.001 13 Fam84a 6:48123623-48128328 1.49 9.18 6.18 0.001 14 Kbtbd10 3:62521704-62536888 2.82 15.82 5.61 0.001 15 ENSRNOG00000049614 17:73725990-73742064 0.86 4.69 5.46 0.001 16 Tpm4 16:19242918-19258218 392.19 1989.40 5.07 0.001 17 Isl1 2:66870616-66884176 0.60 3.00 4.99 0.001 18 Zcchc12 X:122958361-122961546 0.63 3.03 4.79 0.002 19 Aqp8 1:200483570-200489429 1.18 5.63 4.77 0.001 20 Krt15 10:87839484-87843297 15.77 74.20 4.70 0.001 21 Fam124a 15:49481136-49547796 1.57 7.30 4.65 0.001 22 Ptpn7 13:57010183-57023672 1.21 5.55 4.60 0.001 23 Abcc8 1:103194432-103275523 0.47 2.13 4.53 0.001 24 Sgca 10:82582683-82602338 1.70 7.70 4.52 0.001 25 Cdhr1 16:14230687-14250567 0.64 2.81 4.37 0.001 26 Hsd11b1 13:116482031-116528373 1.13 4.92 4.34 0.001 27 Spata2L 19:66729765-66742287 1.57 6.77 4.30 0.001 28 Ms4a11 1:234981703-234994976 1.08 4.63 4.30 0.001 29 Npr3 2:82739629-82806586 11.35 46.57 4.10 0.001 30 Cadm3 13:96356260-96388619 3.42 13.88 4.05 0.001
Top 30 annotated DEGs down-regulated in Tm4-overexpressing B35 cells when compared to WT cells NO. GENE CHROMOSOME FPKM WT FPKM Tm4 FOLD CHANGE Q VALUE 1 Prdm5 4:161443641-161604711 2.74 0.00 Unique to WT 0.001 2 Pdpn 5:165646113-165679595 15.36 0.50 0.03 0.001 3 Qprt 1:205534750-205550121 7.19 0.25 0.03 0.030 4 Igf2bp1 10:83583261-83628466 4.17 0.20 0.05 0.027 5 Spon1 1:185603721-185903509 3.96 0.35 0.09 0.001 6 Sema3f 8:115795066-115824684 7.47 0.86 0.11 0.001 7 Postn 2:163331261-163362444 2.21 0.27 0.12 0.001 8 Gabra1 10:27154358-27210126 37.32 5.72 0.15 0.001 9 Ptprb 7:59359088-59436080 5.61 0.86 0.15 0.001 10 Col2a1 7:139646746-139675763 3.21 0.55 0.17 0.001 11 Tdrkh 2:215130623-215152875 5.72 1.01 0.18 0.001 12 Hoxa3 4:146804643-146808314 2.98 0.53 0.18 0.001 13 Mag 1:90500838-90516456 78.21 14.19 0.18 0.001 14 Lrtm2 4:217213922-217324172 3.99 0.76 0.19 0.001 15 mageb1l1 X:55067824-55134504 10.84 2.28 0.21 0.001 16 Fam105a 2:100047743-100070970 18.19 3.83 0.21 0.001 17 Lef1 2:254782180-254944001 5.70 1.24 0.22 0.050 18 Zpld1 11:51087833-51135794 4.07 0.90 0.22 0.010 19 Rftn1 9:11664636-11880256 3.54 0.79 0.22 0.001 20 Col6a1 20:14817422-14835866 24.04 5.41 0.22 0.001 21 Calca 1:191158062-191162954 4.73 1.07 0.23 0.041 22 Klf12 15:88092656-88331655 1.95 0.45 0.23 0.001 23 Prr9 2:212839866-212841614 6.67 1.54 0.23 0.005 24 Dlx4 10:82765931-82774697 3.15 0.75 0.24 0.020 25 Mbnl3 X:138432130-138489164 46.13 11.03 0.24 0.001 26 Man2a1 9:111831032-111987870 5.46 1.35 0.25 0.001 27 Col8a2 5:148075832-148102414 34.51 8.60 0.25 0.001 28 ENSRNOG00000047711 3:62271278-62362722 2.58 0.65 0.25 0.001 29 Spry1 2:144010430-144015083 4.06 1.04 0.26 0.001 30 Chst15 1:211240270-211272468 3.17 0.81 0.26 0.001
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Table 16: Top 30 annotated DEIs up- and down-regulated in Tm4-overexpressing B35 cells when compared to WT cells Top 30 annotated DEIs up-regulated in Tm4-overexpressing B35 cells when compared to WT cells NO. GENE CHROMOSOME FPKM WT FPKM Tm4 FOLD CHANGE Q VALUE 1 Cyp3a62 12:20667011-20696614 0.00 21.72 Unique to Tm4 0.003 2 Acnat2 5:69174930-69207358 0.00 2.90 Unique to Tm4 0.003 3 Nefl 15:46792228-46797571 1.87 19.92 10.66 0.003 4 Galntl4 1:183278638-183588615 1.04 7.45 7.17 0.003 5 Clec2dl1 4:227478062-227697509 1.59 11.03 6.95 0.003 6 Lynx1 7:115888262-115893454 0.51 3.35 6.60 0.003 7 Fam84a 6:48123623-48128328 1.48 8.65 5.82 0.003 8 Hpgd 16:37258875-37297010 0.45 2.53 5.58 0.037 9 Fam219a 5:62424598-62474180 0.74 3.68 4.99 0.021 10 Nol9 5:172771367-172791554 0.77 3.79 4.92 0.040 11 Zcchc12 X:122958361-122961546 0.63 3.03 4.79 0.007 12 Lpl 16:22431493-22684825 0.81 3.85 4.77 0.045 13 Krt15 10:87839484-87843297 15.77 74.20 4.70 0.003 14 Zc3h7a 10:3366354-3405540 1.40 6.59 4.70 0.003 15 Zbtb7a 7:11596628-11612354 0.81 3.63 4.46 0.048 16 Tppp3 19:48289937-48293688 20.43 90.09 4.41 0.003 17 Hsd11b1 13:116482031-116528373 1.13 4.92 4.34 0.003 18 Cpne7 19:66634978-66651622 1.33 5.70 4.28 0.019 19 Npr3 2:82739629-82806586 1.72 7.29 4.24 0.037 20 Mss51 15:8340987-8353329 0.69 2.88 4.17 0.003 21 Cdk10 19:66729765-66742287 0.78 3.18 4.11 0.029 22 Dok5 3:174447046-174579714 3.24 13.06 4.03 0.037 23 Plac9 16:3817158-3831488 18.09 72.18 3.99 0.003 24 Hand2 16:36107393-36174764 7.29 29.09 3.99 0.010 25 Etfa 8:58608432-58665406 6.71 26.73 3.98 0.045 26 Col20a1 3:180203040-180236920 2.28 8.94 3.93 0.003 27 Prss36 1:206402152-206418143 0.95 3.70 3.91 0.021 28 Sirt7 10:109389097-109404470 0.90 3.49 3.87 0.020 29 Tle2 7:11155630-11172594 0.70 2.71 3.86 0.003 30 Mir24-2 19:36292029-36296144 1.96 7.53 3.84 0.003
Top 30 annotated DEIs down-regulated in Tm4-overexpressing B35 cells when compared to WT cells NO. GENE CHROMOSOME FPKM WT FPKM Tm4 FOLD CHANGE Q VALUE 1 Prdm5 4:161443641-161604711 1.94 0.00 Unique to WT 0.003 2 Pdpn 5:165646113-165679595 15.36 0.50 0.03 0.003 3 Aatk 10:108786239-108822529 20.12 1.01 0.05 0.003 4 Gabra1 10:27154358-27210126 31.09 4.70 0.15 0.003 5 Ltbp1 6:31096975-31491806 14.62 2.44 0.17 0.003 6 Hoxa3 4:146804643-146808314 2.98 0.53 0.18 0.005 7 Mpz 13:94151753-94157570 67.17 12.05 0.18 0.003 8 Chst15 1:211240270-211272468 3.17 0.61 0.19 0.003 9 Col6a1 20:14817422-14835866 11.83 2.45 0.21 0.003 10 Mbnl3 X:138432130-138489164 38.79 8.11 0.21 0.003 11 Col6a1 20:14817422-14835866 9.14 2.02 0.22 0.003 12 RGD1565746 X:55067824-55134504 8.67 1.99 0.23 0.003 13 Man2a1 9:111831032-111987870 4.15 0.96 0.23 0.003 14 Tf 8:111063654-111112787 73.30 17.04 0.23 0.003 15 Myh10 10:55017313-55148296 10.67 2.56 0.24 0.003 16 Mgat3 7:121384169-121426882 2.74 0.66 0.24 0.003 17 Slc6a4 10:62851325-62872481 5.83 1.42 0.24 0.003 18 Col8a2 5:148075832-148102414 5.50 1.37 0.25 0.027 19 Tnc 5:83890243-83974443 92.09 23.29 0.25 0.007 20 Bhlhe40 4:205170128-205176451 13.87 3.53 0.25 0.003 21 Arsi 18:55414449-55421346 4.54 1.18 0.26 0.003 22 Kif13a 17:19600216-19783173 1.89 0.49 0.26 0.036 23 Prr9 2:212839866-212841614 5.32 1.39 0.26 0.003 24 Ep400 12:53686904-53793668 5.39 1.45 0.27 0.003 25 Spry1 2:144010430-144015083 3.59 0.97 0.27 0.003 26 Cpe 16:26785729-26888884 3.80 1.03 0.27 0.003 27 Sec31a 14:10801836-10856886 16.04 4.37 0.27 0.005 28 Spata13 15:44749808-44878757 11.03 3.07 0.28 0.003 29 Tgfbi 17:10576344-10631822 46.02 13.06 0.28 0.047 30 Mgst2 2:160180713-160202851 19.39 5.51 0.28 0.003
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4.6.4 TM5NM1-overexpressing cells
A total of 29,826 expressed genes were identified by Cufflinks across B35 cells overexpressing TM5NM1 isoform and WT cells, including 3,989 DEGs (q-value < 0.05) and 25,837 non-DEGs. Among these 3,989 DGEs, 2,030 were up-regulated and 1,959 down-regulated in TM5NM1-overexpressing cells. The top three up-regulated and annotated DEGs were: Olr1684 (unique to TM5NM1 group, p = 0.0005), Kcnn4 (FC =
31.53, p = 0.0005), and Nefl (FC = 27.93, p = 0.0005), the top three down-regulated and annotated DEGs were: Prdm5 (unique to WT, p = 0.0005), Gabra1 (FC = 0.03, p =
0.0005), and Ndn (FC = 0.09, p = 0.0005). The top 30 annotated genes that are either up- or down-regulated in TM5NM1 group are listed in Table 17. Cufflinks also identified a total of 62,808 isoforms across TM5NM1 and WT groups, and that was approximately 2.11 isoforms per gene. Among these isoforms identified, 1,980 were DEIs (q-value < 0.05) and
60,828 non-DEIs. 1,109 out of these 1,980 DEIs were up-regulated and 871 down- regulated in TM5NM1 cells. The top three up-regulated and annotated DEIs were: Olr1684
(unique to TM5NM1 group, p = 0.001), Nefl (FC = 24.99, p = 0.001), and Krt19 (FC =
14.82, p = 0.001), the top three down-regulated and annotated DEIs were: Prdm5 (unique to
WT, p = 0.001), Aatk (FC = 0.06, p = 0.001), and Ndn (FC = 0.09, p = 0.001). The top 30 annotated isoforms that are either up- or down-regulated in TM5NM1 group are listed in
Table 18. We found 68 enriched GO term clusters. The top 3 clusters were: system development, cellular process, and cell morphogenesis. Please see Table 20 for the top 10 enriched GO clusters and S15 for the full set of results.
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Table 17: Top 30 annotated DEGs up- and down-regulated in TMM5NM1- overexpressing B35 cells when compared to WT cells
Top 30 annotated DEGs up-regulated in TM5NM1-overexpressing B35 cells when compared to WT cells NO. GENE CHROMOSOME FPKM WT FPKM TM5NM1 FOLD CHANGE Q VALUE 1 Olr1684 20:556459-557401 0.00 2.15 Unique to TM5NM1 0.000 2 Kcnn4 1:82493708-82508484 0.72 22.66 31.53 0.000 3 Nefl 15:46792214-46797804 1.96 54.78 27.93 0.000 4 Lpl 16:22431493-22684830 1.03 17.18 16.71 0.000 5 Krt19 10:87848517-87853235 2.06 30.57 14.82 0.000 6 Trim55 2:124140053-124182027 0.42 5.73 13.76 0.000 7 Gal 1:225376770-225682649 5.88 79.52 13.54 0.033 8 Lynx1 7:115888270-115893449 0.53 7.01 13.22 0.000 9 Mir23a,Mir24-2,Mir27a 19:36287311-36296144 1.18 14.15 12.02 0.000 10 Krt15 10:87839476-87843622 17.56 210.05 11.96 0.000 11 Kit 14:34901892-34979346 0.19 2.15 11.16 0.000 12 Aqp8 1:200483589-200489429 1.19 13.15 11.01 0.000 13 Ptpn7 13:57010179-57023286 1.84 19.36 10.50 0.000 14 Prph X:115247339-115251138 3.32 32.81 9.88 0.000 15 Prkd1 6:80600278-80914157 0.40 3.80 9.48 0.000 16 Dusp27 13:89180886-89210597 0.52 4.84 9.28 0.000 17 Frmd4b 4:194157791-194342877 0.40 3.68 9.22 0.035 18 Wnt2b 2:226855018-226869381 0.31 2.55 8.27 0.025 19 Hpgd 16:37259044-37296887 0.59 4.76 8.01 0.000 20 Ccl7 10:69058108-69059959 0.51 3.87 7.62 0.007 21 ENSRNOG00000040372 7:65372908-65491172 1.28 9.54 7.46 0.001 22 Zfhx2 15:37599255-37653522 0.55 4.09 7.41 0.048 23 Prrx2 3:15040948-15077369 1.40 10.02 7.14 0.000 24 Isl1 2:66870577-66884176 1.25 8.91 7.10 0.000 25 Actl7b 5:77650645-77651899 0.46 3.07 6.64 0.003 26 Cdhr1 16:14230687-14250569 0.65 4.05 6.19 0.000 27 GSTA6,Gsta1 9:26283550-26358469 0.99 6.06 6.13 0.000 28 Mdm4 13:54856773-54899072 0.59 3.48 5.95 0.000 29 Scara5 15:52808038-52912473 0.71 4.10 5.73 0.000 30 Magea8 X:43485997-43613439 0.41 2.35 5.70 0.010
Top 30 annotated DEGs down-regulated in TM5NM1-overexpressing B35 cells when compared to WT cells NO. GENE CHROMOSOME FPKM WT FPKM TM5NM1 FOLD CHANGE Q VALUE 1 Prdm5 4:161443641-161604711 2.78 0.00 Unique to WT 0.000 2 Gabra1 10:27154358-27210126 37.08 1.11 0.03 0.000 3 Ndn 1:124119140-124120755 9.34 0.82 0.09 0.000 4 Klf12 15:88092656-88331655 1.95 0.18 0.09 0.000 5 RGD1312005 18:53346500-53361030 3.07 0.28 0.09 0.002 6 RGD1560849 1:18305734-18532096 4.08 0.51 0.12 0.000 7 Col2a1 7:139646746-139675763 3.27 0.44 0.13 0.000 8 Mag 1:90500838-90516456 80.16 11.63 0.15 0.000 9 F2rl2 2:45296358-45569036 5.30 0.80 0.15 0.000 10 Cpq 7:71880823-72338526 1.69 0.27 0.16 0.048 11 Mfap2 5:163246453-163252003 35.41 6.68 0.19 0.000 12 Kcnj10 13:95244933-95278251 4.77 0.90 0.19 0.000 13 Mageb16 X:47191589-47235382 3.99 0.76 0.19 0.000 14 Postn 2:163331261-163362444 2.23 0.43 0.19 0.000 15 Jam2 11:27864586-27950049 2.19 0.42 0.19 0.008 16 Pitpnc1 10:95176727-95432013 3.01 0.59 0.20 0.020 17 Lrtm2 4:217213922-217324172 4.05 0.79 0.20 0.000 18 Relb 1:81783122-81810724 6.42 1.31 0.20 0.000 19 Olr1 4:211883404-211905489 2.81 0.60 0.21 0.000 20 Cpe 16:26785729-26888884 3.80 0.85 0.22 0.000 21 GJB1 X:72123957-72131894 4.15 0.94 0.23 0.000 22 Lrp3 1:92563399-92593301 5.04 1.18 0.23 0.000 23 Sgsh 10:108075841-108079088 5.10 1.21 0.24 0.011 24 Mdfi 9:14090318-14108948 1.92 0.46 0.24 0.028 25 Spon1 1:185603721-185903509 4.00 0.97 0.24 0.000 26 ENSRNOG00000046049 6:84457638-84458972 2.27 0.56 0.24 0.018 27 Mpped2 3:104336311-104510581 13.79 3.51 0.25 0.000 28 Igf2bp1 10:83583261-83628466 4.21 1.09 0.26 0.031 29 Tdrkh 2:215130623-215152875 5.75 1.51 0.26 0.000 30 Gata6 18:2434587-2466690 9.77 2.60 0.27 0.000
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Table 18: Top 30 annotated DEIs up- and down-regulated in TMM5NM1- overexpressing B35 cells when compared to WT cells
Top 30 annotated DEIs up-regulated in TM5NM1-overexpressing B35 cells when compared to WT cells NO. GENE CHROMOSOME FPKM WT FPKM TM5NM1 FOLD CHANGE Q VALUE 1 Olr1684 20:556459-557401 0.00 2.15 Unique to TM5NM1 0.001 2 Nefl 15:46792214-46797804 1.70 42.60 24.99 0.001 3 Krt19 10:87848517-87853235 2.06 30.57 14.82 0.001 4 Trim55 2:124140053-124182027 0.33 3.97 12.18 0.037 5 Krt15 10:87839476-87843622 6.11 74.20 12.14 0.001 6 Mir24-2 19:36287311-36296144 1.18 14.15 12.02 0.001 7 Krt15 10:87839476-87843622 11.45 135.85 11.86 0.001 8 Clec2dl1 4:227478062-227697509 0.60 6.95 11.51 0.001 9 Slc35e4 14:84847696-84854684 0.53 5.76 10.84 0.028 10 Ptpn7 13:57010179-57023286 1.84 18.97 10.30 0.001 11 Prph X:115247339-115251138 3.14 31.51 10.03 0.001 12 G2e3 6:81655972-81687697 0.20 1.90 9.31 0.044 13 Clec2dl1 4:227478062-227697509 0.97 8.60 8.85 0.001 14 Lpl 16:22431493-22684830 0.83 6.93 8.33 0.001 15 Ppp1r16a 7:117722027-117750152 0.22 1.74 8.01 0.016 16 Ccl7 10:69058108-69059959 0.51 3.87 7.62 0.018 17 ENSRNOG00000040372 7:65372908-65491172 1.28 9.54 7.46 0.001 18 Actl7b 5:77650645-77651899 0.46 3.07 6.64 0.008 19 Tpm2 5:63541152-63550280 1.42 9.13 6.43 0.004 20 Acss2 3:157398921-157443341 0.34 2.14 6.25 0.032 21 Wbp4 15:65408805-65436878 0.43 2.60 5.99 0.027 22 Mdm4 13:54856773-54899072 0.59 3.48 5.95 0.001 23 Ccp110 1:195365369-195388100 0.29 1.69 5.88 0.043 24 Magea8 X:43485997-43613439 0.41 2.35 5.70 0.033 25 Scamp4 7:12137244-12149704 0.90 5.15 5.70 0.041 26 Chtf18 10:14901655-14911523 0.48 2.73 5.66 0.048 27 Zranb2 2:282776998-282791456 1.12 6.17 5.53 0.005 28 Cxcl12 4:215195688-215208498 2.00 10.88 5.45 0.001 29 Cav1 4:45203433-45236460 3.53 18.63 5.28 0.022 30 Slfn3 10:70042619-70069233 1.40 7.08 5.05 0.001
Top 30 annotated DEIs down-regulated in TM5NM1-overexpressing B35 cells when compared to WT cells NO. GENE CHROMOSOME FPKM WT FPKM TM5NM1 FOLD CHANGE Q VALUE 1 Prdm5 4:161443641-161604711 1.94 0.00 Unique to WT 0.001 2 Aatk 10:108786270-108822529 21.90 1.34 0.06 0.001 3 Ndn 1:124119140-124120755 9.34 0.82 0.09 0.001 4 Tf 8:111063654-111112787 74.06 6.72 0.09 0.001 5 Csnk2a2 19:9956492-9996387 11.12 1.17 0.10 0.001 6 Atf2 3:67197619-67274694 5.86 0.78 0.13 0.020 7 Sppl2a 3:125876305-125929989 4.65 0.73 0.16 0.001 8 Vgll4 4:209861468-210168624 18.20 2.97 0.16 0.001 9 Kcnj10 13:95244933-95278251 4.77 0.78 0.16 0.001 10 Gata6 18:2434587-2466690 6.84 1.21 0.18 0.005 11 Cdh3 19:49537602-49587578 7.17 1.29 0.18 0.047 12 Mpped2 3:104336311-104510581 11.33 2.07 0.18 0.001 13 Snapc2 12:4690242-4693261 69.50 12.83 0.18 0.001 14 Mageb16 X:47191589-47235382 3.99 0.75 0.19 0.001 15 Mfap2 5:163246453-163252003 35.41 6.68 0.19 0.001 16 Taf1 X:72261626-72336051 3.03 0.58 0.19 0.001 17 Plp1 X:107379341-107394874 11.33 2.25 0.20 0.001 18 Spsb1 5:170555623-170619888 25.43 5.08 0.20 0.034 19 Gpr17 18:24422407-24538352 1.99 0.42 0.21 0.013 20 Olr1 4:211883404-211905489 2.55 0.55 0.22 0.010 21 Cpe 16:26785729-26888884 3.80 0.85 0.22 0.001 22 Cntn6 4:201062011-201374178 4.08 0.91 0.22 0.001 23 Fbln2 4:187650684-187710355 6.68 1.50 0.22 0.001 24 GJB1 X:72123957-72131894 4.15 0.94 0.23 0.001 25 Kazn 5:164348125-164739758 2.73 0.63 0.23 0.001 26 Col11a1 2:234955153-235148332 15.74 3.69 0.23 0.001 27 Crtac1 1:268979484-269122032 7.89 1.87 0.24 0.001 28 Sgsh 10:108075841-108079088 5.10 1.21 0.24 0.030 29 ENSRNOG00000046049 6:84457638-84458972 2.27 0.56 0.24 0.011 30 Pnpla6 12:4216867-4260921 4.56 1.12 0.25 0.003
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Figure 14 and 15 show respective distribution of DEGs and DEIs, respectively, in terms of fold change range and significance in the four Tm isoform-overexpressing groups (TM1,
TmBr3, Tm4, and TM5NM1) of the B35 cell line.
4.7 Comparative analysis of differential expression distribution
The numbers of identified genes and isoforms, including DEGs and DEIs, and their percentages in total expressed genes of the Tp8 mice model and each group in the B35 cell line model are summarised in Table 19.
Figure 14: Volcano plot of gene expression in B35 cell lines and WT mice. A: TM1- transgenic cells vs WT; B: TmBr3-transgenic cells vs WT; C: Tm4- transgenic cells vs WT; and D: TM5NM1- transgenic cells vs WT. Genes that were statistically significant (q-value < 0.05) are shown in red and were listed in Table S3, S4, S5, and S6.
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Figure 15: Volcano plot of isoform expression in B35 cell lines and WT mice. A: TM1- transgenic cells vs WT; B: TmBr3- transgenic cells vs WT; C: Tm4- transgenic cells vs WT; and D: TM5NM1- transgenic cells vs WT. Isoforms that were statistically significant (q-value < 0.05) are shown in red and were listed in Table S7, S8, S9, and S10.
Tp8 mice have the lowest numbers in total expressed genes (27,193), DEGs (140), and the DEG/total expressed gene ratio (0.51%), when compared to all groups in the B35 cell line. Within the four groups of the B35 cell line, TmBr3-trangenic cells have the highest number of expressed genes (31,421), but the lowest number of DEGs (1,141) and
DEG/total expressed genes ratio (3.63%). The Tm4-trangenic cells have the lowest total number of expressed genes (29,086), whereas TM5NM1-trangenic cells have the highest number of DEGs (3,989) and DEG/total expressed genes ratio (13.37%) (Figure 16).
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Table 19: Metrics summary of identified genes, isoforms, DEGs, and DEIs in Tp8 mice and B35 transgenic cells.
A: Numbers of identified genes and isoforms in Tp8 mice when comared to WT mice
No. of expressed genes: 27193 No. of expressed isoforms: 69311 No. of isoforms per gene
DEGs: 140 DEIs: 58
Up-regulated Down-regulated Non-DEGs: 27053 Up-regulated Down-regulated Non-DEIs: 69253 2.55
97 43 43 15
B: Numbers of identified genes and isoforms in B35 cells overexpressing TM1 isoforms when compared to WT B35 cells
No. of expressed genes: 30622 No. of expressed isoforms: 65646 No. of isoforms per gene
DEGs: 1368 DEIs: 564
Up-regulated Down-regulated Non-DEGs: 29254 Up-regulated Down-regulated Non-DEIs: 65082 2.14
766 602 355 209
C: Numbers of identified genes and isoforms in B35 cells overexpressing TmBr3 isoforms when compared to WT B35 cells
No. of expressed genes: 31421 No. of expressed isoforms: 64928 No. of isoforms per gene
DEGs: 1141 DEIs: 513
Up-regulated Down-regulated Non-DEGs: 30280 Up-regulated Down-regulated Non-DEIs: 64415 2.07
900 241 450 63
D: Numbers of identified genes and isoforms in B35 cells overexpressing Tm4 isoforms when compared to WT B35 cells
No. of expressed genes: 29086 No. of expressed isoforms: 62227 No. of isoforms per gene
DEGs: 2183 DEIs: 927
Up-regulated Down-regulated Non-DEGs: 26903 Up-regulated Down-regulated Non-DEIs: 61300 2.14
1227 956 564 363
E: Numbers of identified genes and isoforms in B35 cells overexpressing TM5NM1 isoforms when compared to WT B35 cells
No. of expressed genes: 29826 No. of expressed isoforms: 62808 No. of isoforms per gene
DEGs: 3989 DEIs: 1980
Up-regulated Down-regulated Non-DEGs: 25837 Up-regulated Down-regulated Non-DEIs: 60828 2.11 2030 1959 1109 871
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100000% 100.00%% 30622% 31421% 29086% 29826% 27193%
10000% 3989% 2183% 1368% 13.37%% 1141% 10.00%% 1000% 7.51%% 4.47%% 3.63%% 140% 100% 1.00%% 0.51%% 10%
1% 0.10%% No.%of%expressed%genes%
No.%of%DEGs% B35)TM1% B35)Tm4% B35)TmBr3% B35)TM5NM1%Tp8)TM5NM1% DEGs%%%
Figure 16: Number of total expressed genes, DEGs, and DEG ratio in all analysed groups.
As in the case of isoform expression, Tp8 mice with TM5NM1-overexpression genotype have the highest amount of total expressed isoforms (69,311), but the lowest amount of DEIs (58) and DEI/total expressed isoform ratio (0.08%), when compared to all groups in the B35 cell line. Within the four groups of the B35 cell line, the TM1-transgenic cells have the highest amount of expressed isoforms (65,646) while the Tm4- overexpressing cells have the lowest (62,227). The highest number of DEIs (1,980) and
DEI/total expressed isoform ratio (3,15%) are found in the TM5NM1-transgenic group, and the lowest of those are found in the TmBr3-transgenic group (513 and 0.79% respectively)
(Figure 17).
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65646$ 64928$ 62227$ 62808$ 69311$ 100000% 100.00%%
10000% 1980$ 10.00%% 927$ 1000% 564$ 513$ 3.15%$ 1.49%$ 0.86%$ 0.79%$ 1.00%% 100% 58$
0.10%% 10% 0.08%$
1% 0.01%% No.%of%expressed% isoforms% B35)TM1% B35)Tm4% No.%of%DEIs% B35)TmBr3% B35)TM5NM1%Tp8)TM5NM1% Figure 17: Number of total expressed isoforms, DEIs, and DEI ratio in all groups.
4.8 Pathway analysis for differentially expressed genes
DAVID first identifies enriched GO terms using the input DEG lists and then groups similar GO terms into clusters of distinct biological processes. These clusters were ranked according to the degree of enrichment. Enriched GO term clusters in Tp8 mice group and the top 10 enriched GO term clusters in B35 are listed in Table 20.
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Table 20: Enriched GO term clusters in Tp8 mice group and top 10 enriched GO term clusters in B35 cell line group WT vs Tp8 mice No. Cluster of enriched GO terms 1 System development 2 Immune system process 3 Response to hormone stimulus 4 Chemotaxis 5 Regulation of cell differentiation 6 Transport 7 Regulation of hydrolase activity 8 Regulation to alkaloid WT vs TM1-overexpressing B35 cells No. Cluster of enriched GO terms 1 Biosynthetic process 2 Regulation of developmental process 3 System development 4 Response to hormone stimulus 5 Organic acid metabolic process 6 Ribosome biogenesis 7 Neuron projection development 8 Negative regulation of cellular process 9 Regulation of cell migration 10 Biological regulation WT vs TmBr3-overexpressing B35 cells No. Cluster of enriched GO terms 1 Biosynthetic process 2 System development 3 Response to hormone stimulus 4 Ribosome biogenesis 5 Regulation of cell differentiation 6 Regulation of cell migration 7 Regulation of signal transduction 8 Regulation of transport 9 Bone development 10 Cell morphogenesis WT vs Tm4-overexpressing B35 cells No. Cluster of enriched GO terms 1 System development 2 Biological regulation 3 Cell morphogenesis 4 Regulation of developmental process 5 Response to hormone stimulus 6 Blood vessel development 7 Response to external stimulus 8 Response to oxidative stress 9 Cell adhesion 10 Cellular process WT vs TM5NM1-overexpressing B35 cells No. Cluster of enriched GO terms 1 System development 2 Cellular process 3 Cell morphogenesis 4 Negative regulation of cellular process 5 Cytoskeleton organization 6 Response to hormone stimulus 7 Biological regulation 8 Cell death 9 Membrane organization 10 Response to oxidative stress
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Enriched GO terms within each pairwise comparison can be found as
Supplementary Tables S11 (Tp8), S12 (B35 TM1), S13 (B35 TmBr3), S14 (B35 Tm4), and
S15 (B35 TM5NM1). Figure 18 shows the number of total enriched GO terms identified by
DAVID in Tp8 mice and B35 cells Tp8 mice overexpressing TM5NM1 have the lowest amount of enriched GO terms (65), when compared to all four B35 cell line groups.
Within the four groups of the B35 cell line, TM5NM1-transgenic cells had the greatest amount of enriched GO terms (460) while cells overexpressing TmBr3 have the least (153).
500" 442$ 460$ 450" 400" 350" 300" 250" 175$ 200" 153$ No."of"enriched"GO"terms" 150" (p)value"<"0.05)" 65$ 100" 50" 0"
B35)TM1" B35)Tm4" B35)TmBr3" B35)TM5NM1"Tp8)TM5NM1"
Figure 18: Number of enriched GO terms in all analysed groups.
Cuffdiff discovered 135 annotated DEGs in Tp8 mice overexpressing TM5NM1 isoform, and 3,246 DEGs in B35 cells overexpressing the same TM5NM1 isoform. There were 27 common DEGs between the two samples (Figure 19). Further 65 enriched GO terms were found to be significantly associated with DEGs in the Tp8 mice model. B35 cell line overexpressing TM5NM1 had 460 enriched GO terms, with 23 terms overlapping with those of the Tp8 sample (Figure 20).
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Figure 19: Venn diagram of common annotated DEGs between Tp8 mice and B35 cell line models overexpressed TM5NM1.
Figure 20: Venn diagram of common enriched GO terms in Tp8 mice and B35 cell lines overexpressed TM5NM1.
Within the B35 cell line model, there were 78 common annotated DEGs among the four groups. The numbers of uniquely annotated DEGs in each groups were as follows:
TM1: 128; TmBr3: 298; Tm4: 521; and TM5NM1: 1,821. Clearly, TM1-overexpressing
B35 cells have the lowest number of unique annotated DEGs while TM5NM1-transgenic cells had the highest (Figure 21). DAVID identified 55 common enriched GO terms among the four groups. The numbers of unique enriched GO terms in each groups were: TM1: 34;
TmBr3: 37; Tm4: 151; and TM5NM1: 163 (Figure 22). In order to further increase
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resolution of the pathway analysis enriched GO terms that were found in at least two groups of the B35 cells and had the enrichment score p-values less than 0.05 were selected for heatmap illustration using one of the R packages CummeRbund (Figure 23).
Heatmap analysis indicated several common pathways that were enriched in all
TM1-, TmBr3-, Tm4-, and TM5NM1-trangenic groups. The enriched pathways included system development, developmental process, and multicellular organismal development.
Figure 21: Venn diagram of annotated DEGs among four transgenic groups in the B35 cell line model.
Figure 22: Venn diagram of enriched GO terms identified in all groups of the B35 cell line model.
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Furthermore heatmap also revealed, as indicated by the column dendrograms, that there are two comparatives sets with similar gene and pathway profiles as a result of Tm transgenic expression. One set includes transcriptome profiles of TM1- and TmBr3- overexpressing B35 cells and the other is consisted of Tm4- and TM5NM1-overexpressing cells. Moreover Tm4 and TM5NM1 showed higher degree of GO term enrichment than
TM1 and TmBr3.
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Figure 23: Heatmap illustration. Neuron morphology related GO terms that were enriched in at least two groups in the B35 cell line model with p-value < 0.05. The p-value in DAVID pathway analysis is the modified Fisher Extract P-value which represents the degree of enrichment. Accordingly the smaller the p-value, the more enriched the GO term. The colour intensity in the heatmap corresponds to the p-value, with the lightest colour having the highest p- values and the darkest having the smallest p-values. Row dendrograms show the similarity between the enriched GO terms, while the column dendrograms represent the similarity among the four groups in terms of expression patterns.
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4.9 Network visualisation of enriched GO terms network using one Cytoscape
plugin Enrichment Map
Cytoscape is a software environment with an architecture of a core and multiple plugins for organisation of biomolecular interaction networks with expression data into a conceptual framework (Shannon et al., 2003). Based on the similarities in GO term annotations shared by members of a gene set, one of the Cytoscape plugins, Enrichment
Map, integrates gene sets into a network consisted of nodes and edges. These nodes are further grouped into biological functional clusters, therefore enables easier interpretation of the enrichment results (Merico et al., 2010). Enrichment maps for B35 cell lines overexpressing TM1, TmBr3, Tm4, and TM5NM1 are presented in Supplementary Figure 1.
A node represents a gene set and the size of the node corresponds to the size of the gene set.
Gene sets that have similar biological functions were placed next to each other, forming biological theme clusters. An edge represented common genes between two gene sets, with its thickness corresponding to the amount of shared genes.
4.10 Supplementary tables
Supplementary tables S1 to S15, supplementary figure 1 (A, B, C, and D), R sample scripts, Trimmomatic sample scripts, RSeQC output files, and Cufflinks output files (in
GTF format) are available at: https://drive.google.com/folderview?id=0B4DX0tAbqI3rOEhoYmRfVTZuQU0&usp=shar ing
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5 DISCUSSION
In this study, a comprehensive comparison of the effects induced by overexpression of four different isoforms of the Tm gene, including TM1, TmBr3, Tm4, and TM5NM1 isoforms, on the transcriptome of rodent neuronal cells in vitro or in vivo was performed.
5.1 Quality check of aligned reads
RseQC reported 76% to 88% of uniquely mapped reads over total successfully mapped reads ratios for all sample datasets that TopHat aligned. The properly mapped read pairs over total mapped reads ratios were relatively higher (around 75% to 79%) in the Tp8 mice group, while in B35 cell line group it ranged from 44% to 60% which is not uncommon in RNA-seq experiments. When a read spans exons that fall apart along the genome the aligner might consider it not being properly paired with its complementary read, therefore the actual ratios are very likely to be higher. Adjusting the mean inner distance setting might help further increase the number of properly paired reads, however it would require empirically repeating the alignment and quality check which may not be time efficient.
5.2 Choosing bioinformatic tools for RNA-seq data analysis
As discussed in the Introduction section, there are currently a number of RNA-seq analysis tools available. The Tuxedo pipeline consisted of TopHat, Cufflinks, and Cuffdiff was chosen in this project for the following reasons. First, the pipeline has been widely used in the field, there exists an active user community and comprehensive documentation is available. Second, the software of the pipeline is easily accessible: there are a number of
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public servers such as Galaxy having these software integrated to their platform. Further, local installation of the pipeline is also possible.
5.3 Comparison of TM5NM1 overexpression between Tp8 mice and B35 cells
In the Tp8 transgenic mice model, only the overexpression of TM5NM1 isoform was tested and RNA-seq was performed on cells from the hippocampal area of the mice brain. 140 DEGs, 58 DEIs, and 65 enriched GO terms with p-values smaller than 0.05 was determined when comparing Tp8 transcriptome with the WT expression profile. In contrast, in B35 cells which overexpressed the same TM5NM1 isoform, 3,989 DEGs, 1,980
DEIs, and 460 enriched GO terms were identified, i.e. significantly higher than in the Tp8 group. Furthermore, there were only 27 overlapping annotated DEGs and 23 overlapping enriched GO terms between the TM5NM1-overexpressing Tp8 mice and B35 cells cellular response of the two groups.
Based on the differential DEGs and GO metrics it seems that the overexpression of the same Tm isoform, namely TM5NM1, has elicited different patterns of cellular response in the Tp8 transgenic mice model and B35 cell. Several factors might contribute to the differences in the transcriptional profiles in these two biological models. First, at the genome-wide level, there are species-specific differences between mouse and rat.
Although having similar numbers of protein encoding genes (mouse: 22,592; rat: 22,940), the rat genome is of 2.75 gigabases (Gb) long comparing to mouse’s 2.6 Gb genome, with numbers of genes being unique to rat species (Gibbs et al., 2004). There are also species- specific differences between rat and mouse in terms of biochemistry and histological responses to drugs (Vahter, 1994, Martignoni et al., 2006, Prout et al., 1985). Furthermore it was shown that the genomic responses to the same pathophysiological stimulus might
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also be species-specific. For example, in an experiment aimed to investigate the transcriptomic responses to induced focal brain ischemia in rats and mice, Schroeter and colleagues found that inflammatory-related gene expression patterns differed in rats and mice (Schroeter et al., 2003). It might be therefore reasonable to attribute genomic differences between rats and mice as one of the causative factors that resulted in smaller number of DEGs, DEIs, and enriched GO terms observed in the Tp8 mice model when compared to rat B35 cells overexpressing the same transgene.
The overexpression of TM5NM1 was tested on in vivo (transgenic mice) and in intro
(transgenic cell line) systems respectively, it is also necessary to take the biological system difference into consideration. Outcomes of in vivo and in vitro experiments do not always correlate well when the same biological question is asked. For example, in an microarray assay conducted on two rat liver cell lines and liver tissue, it was found that these two cell lines had different mRNA expression patterns in response to toxic substance exposure, as compared to the liver tissue (Boess et al., 2003). In the current study, a majority of enriched terms which are unique to Tp8 TM5NM1-overexpressing mice are related to systemic immune response, a feature that an in vitro system is lacking. Further, the cell sample from the Tp8 mice may contain other cell types such as microglia or astrocytes other than neurons. The overexpression of exogenous TM5NM1 may trigger cellular response in microglia and astrocytes, which would probably overpower the effect mediated in neurons, thus contributing to the enriched pathways related to immune responses. It is also worth noting that mixed cell types in such a heterogeneous cell sample would have different gene expression patterns in response to TM5NM1 overexpression, creating a background noise in the overall transcriptomic profile. This would in turn lead to a lower
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number of detectable gene differentially expressed genes as compared to those of a homogeneous cell culture as B35 cells.
Overexpression of the TM5NM1 isoform has been associated with cell proliferation in neuroblastoma cells, and novel anti-TM compounds that target TM5NM1-containing filaments have been observed to reduce tumour size in melanoma mouse model (Stehn et al., 2010). Indeed, GO terms related to both positive and negative regulation of cell death and apoptosis were enriched in TM5NM1-overexpressing B35 cells (Supplementary table
S15). It might be therefore postulated that this is TM5NM1 overexpression which leads to induction of tumour suppression pathways. The enriched GO terms linked to cell death regulation and apoptosis were not however present in the TM5NM1-overexpressing Tp8 mice model. Therefore events involved in cancer pathways may also partially explain the much larger sets of DEGs, DEIs, and enriched GO terms in the B35 cells, given the fact that B35 neuroblastoma cells are transformed cells in contrast to primary hippocampal cells from Tp8 transgenic mice. This conclusion needs however more experimental support in future studies.
Taken together, this study demonstrates that when challenged with the same genetic modification, the consequential transcriptomic changes induced in vivo or in intro in terms the abundance of DEGs, DEIs, and enriched GO terms could be very different even in genetically highly similar organisms such as rat and mouse. Moreover, while there was a substantial enrichment of GO terms in relation to neuronal morphological regulation in the
TM5NM1-overexpressing B35 cells, there were no pathways specifically linked to neuron morphology in Tp8 mice. This is in contrast to the observations of the Schevzov et al 2008 reporting significantly larger cones of hippocampal neurons in Tp8 when compared to WT mice (Schevzov et al., 2008). The discordance between the transcriptomic profile and
65
neuronal morphology of the TM5NM1-transgenic cells could be a result of analytical limitation of RNA-seq and data analysis methods which failed to capture slight changes in gene expression related to neuronal morphology. It is possible that these changes in gene expression were post-translationally augmented within cellular signalling cascades which eventually led to observable changes in cellular phenotype.
5.4 Transthyretin: plasma transporter of thyroid hormone and retinol
Transthyretin (TTR) protein is a plasma transporter of thyroxine, and retinol, hence the name transthyretin (Raz and Goodman, 1969). Lowered concentration of TTR in cerebrospinal fluid has been linked to late onset of Alzheimer’s disease (Serot et al., 1997).
In experiments with rat PC12 cell line grown in TTR knocked-out (KO) serum, cells exhibited a 20% decrease of neurite number per cell and 30% reduction of neurite size when compared to cells grown in WT serum. After restoration of physiological TTR concentration in these PC12 cells, the 20% decrease in neurite number was totally rescued, underscoring the pivotal role of TTR in promoting of neurite growth (Fleming et al., 2007).
In the current study, the expression of Ttr gene is 24 times higher in TM5NM1- overexpressing Tp8 hippocampal cells, making it the most significantly changed annotated
DEG. The elevated Ttr expression might contribute to the fact that in Tp8 mice, the overexpression of TM5NM1 did not elicit enrichment in pathways related to neuron morphology, possibly due to inhibitory effect mediated by TTR.
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5.5 B35 cell line model: transcriptome patterns as a result of Tm isoforms
overexpression
5.5.1 Down-regulated genes in Tm-overexpressing B35 cells
The expression of a few genes including Prdm5, Rab15, and Gabra1 have been found significantly decreased in most Tm-overexpressing B35 cells. The down-regulation of Prdm5 expression is the most striking one with its FPKM values being zero in all of four
B35 cell line groups. PRDM5 is a transcription factor that binds to specific DNA sequences and has an established role as a tumour suppressor via negative control of cell development and cell cycle. In multiple human cell lines, PRDM5 is often silenced (Deng and Huang, 2004, Shu et al., 2011, Duan et al., 2007). The findings correlate well with the pathway analysis result in the current study in which Prdm5 is present in a number of enriched GO term clusters such as cellular metabolic process and cell cycle. The silencing of Prdm5 would have either positive or negative effects on these biological processes since enrichment of these clusters can occur in both directions. One reasonable deduction, however, is that the effect of Prdm5 silencing in cell cycle should be positive, since as a tumour suppressor it supposedly promotes cell cycle arrest.
5.5.2 TM1 overexpression
One of the products of the βTm gene, TM1 protein, consists of 284 amino acids and it is considered as one of the major high molecular weight (HMW) TMs expressed in non- muscle cells (Helfman et al., 2008). TM proteins stabilise actin filaments by protecting them from the severing action of ADFs. The absence of TM1 results in disorganisation of actin cytoskeleton after cell malignant transformation (Hendricks and Weintraub, 1981,
Bhattacharya et al., 1990, Hughes et al., 2003). This is consistent with the observation that
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in one type of transformed cells that have lost the ability of tumorigenicity suppression, the expression of TM1 is down-regulated (Boyd et al., 1995). In experiments with mouse ras- transformed NIH3T3 fibroblast cell line, which is highly malignant and lacks defined microfilament structure, restoration of TM1 expression results in re-emergence of microfilaments and inhibition of transformed phenotype (Shah et al., 2001, Braverman et al., 1996). On the other hand in experiments with human neuroblastoma cell lines, the expression of exogenous TM1 failed to restore normal actin cytoskeleton structure (Yager et al., 2002). In the present study, GO terms related to neuronal morphology, including morphogenesis, regeneration, and development of neuron and axon, were enriched in TM1- overexpressing B35 cells (Supplementary Table S12). Further, enrichment of GO terms related to cell differentiation regulation, including positive regulation of cell differentiation, has also been identified in the TM1-overexpressing B35 cells. It will require more morphological examination studies in order to establish whether these enriched GO terms might be linked to actin structure alterations in B35 cells in response to exogenous TM1 expression.
5.5.3 TmBr3 overexpression
TMBR3 is one of the protein products from the αTm gene. It has been shown that in rats TMBR3 was specifically expressed in the neurons of the brain, located around the presynaptic terminals, and its expression increased with cell maturation (Stamm et al.,
1993, Had et al., 1994b). This spatial- and temporal-specific pattern of expression suggests a specialised role of TMBR3 in neuronal development and plasticity. In the current study,
DAVID identified two enriched clusters of GO terms that were related to neuron
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morphology regulation. These enriched GO terms mainly participate in regulation of neuron differentiation, cell morphogenesis, neuron projection organization, and axonogenesis. In addition, pathway analysis also revealed an enriched cluster of GO terms in relation to cell migration. This is consistent with the previous findings in which the overexpression of TmBr3 in B35 cells resulted in increased lamellipodial formation and cell migration (Bryce et al., 2003). Interestingly, in another study the TmBr3 overexpression in
B35 cells resulted in reduction of lamella along with significantly increased numbers of neurite branching, and filopodia and neurite formation (Curthoys et al., 2014). It awaits further investigation to determine which cellular factors contribute to differential lamella formation as a result of TmBr3 overexpression.
5.5.4 Tm4 overexpression
Tm4 transcript is an alternative splicing product of the δTm gene and expressed in both muscle and non-muscle cells (Gunning et al., 2005). Experiments in rats showed that the regulation of TM4 expression has spatial and temporal character. TM4 is localized in growth cones of cultured rat neurons, and it is primarily expressed during development
(Had et al., 1994b). In this study, the exogenous expression of TM4 evoked the second largest number of DEGs, DEIs and GO term enrichment over the four tropomyosine overexpression models analysed (Table 13).
TM4 overexpression affected pathways involved in actin filament-based process, actin cytoskeleton organisation, cytoskeleton organization, regulation of actin polymerisation or depolymerisation. This observation corroborates that TM proteins are integral components of the actin cytoskeleton, and that perturbation of Tm isoform
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expression lead to alterations in cytoskeleton organisation. Perturbation of genes related to regulation to actin polymerisation or depolymerisation, observed in Tm4 overexpression model, supports previous suggestions that TM proteins stabilise actin filaments by protecting them from the action of ADFs (Bernstein and Bamburg, 1982, Cooper, 2002,
Ono and Ono, 2002).
Finally, the observed profile of biological processes affected by Tm4 overexpression, as determined by transcriptome profiling, coincides with morphological changes in B35 cell phenotype. The latter comprises increased neurite formation, neurite branching, and filopodia formation, a phenotype similar to that of TMBR3 transfected cells
(Curthoys et al., 2014).
5.5.5 TM5NM1 overexpression
TM5NM1 is one of the predominant cytoskeleton Tm isoforms in tumour cells which makes this transcript effective target for actin-disrupting cancer therapies (Gunning et al., 2008b, Schevzov et al., 1997b). The effects of altered TM5NM1 expressions on cell morphology, actin structure, cell motility, and invasion potential of tumour cells have been extensively investigated. Studies showed that in multiple cell lines, TM5NM1- overexpressing cells displayed a rounded phenotype characterised by reduced capacity of pseudopodia formation (Lees et al., 2011). Bryce et al. demonstrated that in B35 cells
TM5NM1 overexpression resulted in altered actin filament organisation, decreased lamellipodia formation and cell migration (Bryce et al., 2003). These findings correlate well with a TM5NM1 knockout experiment conducted in cultured mice neurons, in which
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the absence of TM5NM1 led to significant changes in neuron phenotype with increased branching of dendrites and axons (Fath et al., 2010).
Changes in cell morphology observed in the above experiments would imply comparable change in transcriptome profiles of these cells. Indeed, in the current study, overexpression of the TM5NM1 isoform has induced the largest number of DEGs, DEIs, and enriched GO terms within the four B35 transgenic cell lines. Moreover the greatest ratio of DEGs and DEIs versus total numbers of expressed genes and isoforms (Figure 12 and 13) has been observed.
Notably enriched GO terms include clusters related to neurogenesis, cell morphogenesis, axonogenesis, cytoskeleton organisation, and actin polymerisation or depolymerisation. This distinct composition of GO clusters indicates that the pattern of cellular responses to exogenous TM5NM1 expression is similar to that in Tm4 transgenic cells. Nevertheless a number of distinct features in the cell phenotypes of these two cell lines still exist. For example Tm4-tranfected cells have increased neurite formation and neurite branching, while TM5NM1-transfected cells present a more rounded phenotype.
5.5.6 Overlapping patterns of affected pathways among Tm transgenic cells
Despite the fact that overexpressed Tm isoforms belong to the same multi-gene family and they are structurally similar, only 78 common DEGs could be found between four transgenic B35 cell lines (Figure 17).
Along with commonalities in terms of sharing certain GO terms there were a number of pathways that were specifically affected by overexpression of the particular transgene. For example, in the TM1- and TmBr3-transfected cells, TM1 overexpression
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distinctly affected regulation of cell differentiation, neuronal projection, and axon regeneration, whereas TmBr3 overexpression perturbed pathways related to regulation of cell development and morphogenesis and control of cell motion and migration.
Within the Tm4 and TM5NM1 sets, the differences in terms of enrichment pattern between the two groups were less pronounced. TM5NM1-transfected cells had two specific clusters linked to regulation of microtubule-based process and actin filament-based process.
In contrast clusters covering regeneration and regulation of axonogenesis were more significantly changed in Tm4 than TM5NM1 set.
The morphological phenotype of TmBr3 and Tm4 overexpressing cells were similar and featured by formation and branching of neurites, along with a significant increase in filopodia formation. It might have been therefore expected that transcriptomic expression patterns of these two groups should be similar as well. In contrast to this assumption, the
Tm4 overexpressing cells shared more similar transcriptomic expression features with
TM5NM1 cells which had a rounded or elliptical shape. Hence it might be suggested that similar morphology alterations could be originated from two dissimilar transcriptomic expression profiles induced by the exogenous expression of two different Tm isoforms.
5.6 Significance and limitations of the study
A number studies have been carried out towards investigation of the impact of altered
Tm transcript isoforms expression on neuronal morphology (Pittenger et al., 1994, Lees-
Miller and Helfman, 1991, Gunning et al., 2005, Creed et al., 2008). However there have been no studies so far performed on genome-wide scale. To this end this analysis for the first time explores changes in neuron transcriptomes expression patterns in response to exogenous Tm expression and its link to neuronal phenotypes.
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Limitations of this study comprise several aspects. Firstly, poly-T oligomers were used in the total RNA purification step, hence only polyadenylated RNA fraction was sequenced. However, many RNA transcripts such as non-coding RNAs are not poly- adenylated (Derrien et al., 2012). In this case, information about these non-poly-adenylated
RNA molecules was lost during the sample preparation steps.
Secondly, the expression profiles of anti-sense RNAs and their relation to complementary sense transcript could not be covered by this study. Conventional RNA- seq, utilised in this analysis, does not allow identification of the strand origin of the transcripts sequenced, in contrast to strand-specific RNA-seq (Mills et al., 2013b)
6 CONCLUSION
This study demonstrates that when challenged by the same genetic modification, the consequential transcriptomic changes induced in vivo or in intro in terms the abundance of
DEGs, DEIs, and enriched GO terms could be very different in rat and mouse systems. In contrast, comparative pathway analysis between rat neuronal cell lines, overexpressing
TM1, TmBr3, Tm4, and TM5NM1 isoforms, respectively, revealed a high degree of similarity in terms of biological pathways affected by Tm transgene expression. On the other hand pairwise comparison of transcriptome profiles derived from particular transgenic cell lines identified distinct DEG sets featuring each comparison. Taken together this study indicates that transcriptome profiling needs to be supplemented with functional studies investigating individual biological processes, affected by transcriptome perturbation, on cellular level.
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