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Transcriptomic dissection of myogenicdifferentiation signature in caprine by RNA-Seq

0925-4773/$ - see front matter � 2014 Elsevier Ireland Ltd. All rights reserved.http://dx.doi.org/10.1016/j.mod.2014.01.001

* Corresponding author. Tel.: +91 2692 261201; fax: +91 2692 261486.E-mail address: cgjoshi@rediffmail.com (C.G. Joshi).

1 Authors have equal contribution.

Please cite this article in press as: Tripathi, A.K. et al, Transcriptomic dissection of myogenic differentiation signature in caprine byMech. Dev. (2014), http://dx.doi.org/10.1016/j.mod.2014.01.001

Ajai K. Tripathi a,b,1, Amrutlal K. Patel a,1, Ravi K. Shah a, Anand B. Patel a,Tejas M. Shah a, Vaibhav D. Bhatt a, Chaitanya G. Joshi a,*

a Department of Animal Biotechnology, College of Veterinary Science and Animal Husbandry, Anand Agricultural University,

Anand 388001, Indiab Case Western Reserve University, Cleveland, OH, USA

A R T I C L E I N F O A B S T R A C T

Article history:

Received 2 August 2013

Received in revised form

1 January 2014

Accepted 2 January 2014

Available online xxxx

Keywords:

Muscle

Transcriptome

CLC Workbench, miRNAs

Muscle growth and development from the embryonic to the adult stage of an organism

consists of a series of exquisitely regulated and orchestrated changes in expression of

genes leading to muscle maturation. In this study, we performed whole transcriptome pro-

filing of adult caprine skeletal muscle derived myoblast and fused myotubes. Using Ion Tor-

rent PGM sequencing platform, a total of 948,776 and 799,976 reads were generated in

myoblasts and fused myotubes, respectively. The sequence reads were analyzed on CLC

Genomics Workbench using Bos taurus RNA database to study the gene expression in both

stages to study different genes responsible for muscle development and regeneration. The

up and down-regulated genes were analyzed for gene ontology (GO) and KEGG pathways by

Database for Annotation, Visualization and Integrated Discovery (DAVID) database. We

found many genes exclusive to multinuclear fused myotubes and contractile nature of

skeletal muscle, whereas up-regulated genes in myoblast stage were related to cell division

and transcriptional regulation. Out of 27 genes selected for expression validation by RT-

qPCR (reverse transcriptase-quantitative polymerase chain reaction), 19 genes showed

the expression pattern comparable with CLC Genomics Workbench findings. Further,

mRNA originated muscle specific microRNAs (miRNA-1 and miRNA-133b) were also

observed in the fused myotubes along with other miRNAs with possible importance in

muscle development. This study highlights important genes responsible for muscle devel-

opment and differentiation in adult skeletal muscle system.

� 2014 Elsevier Ireland Ltd. All rights reserved.

1. Introduction

In biology, the mechanism of cell type determination in

developing multicellular organisms is one of the fundamen-

tal problems which needs better understanding. The func-

tionally competent cells carry out tissue-specific activities

that have achieved specialization through terminal differen-

tiation, where the cell population withdraw themselves

from the cell cycle as a result of appropriate configuration

of gene activation and repression. Although not normally

subject to rapid cell turnover, adult skeletal muscle also

retains the ability to grow in response to increased work

load and to repair and regenerate following damage

(Beauchamp et al., 2000).

RNA-Seq,

2 M E C H A N I S M S O F D E V E L O P M E N T x x x ( 2 0 1 4 ) x x x – x x x

Skeletal muscle is one of the several adult postmitotic tis-

sues that retain the capacity to regenerate, which relies on a

population of quiescent precursors, termed satellite cells. Pro-

liferation and differentiation of myoblasts to form mature

myotubes in vitro has been a valuable tool in the characteriza-

tion of the cellular events during myogenesis, which is a mul-

tistep process starting with progenitor cell proliferation,

followed by their exit from the cell cycle, differentiation,

alignment, and fusion to form multinucleated myotubes. A

typical feature during muscle differentiation is the variation

in expression of various genes along with myogenic factors

(Tripathi et al., 2011). Previous studies have identified several

genes that positively or negatively regulate myogenesis like

the myogenic regulatory factors (MRFs) involving myogenic

differentiation 1 (MYOD), myogenic factor 5 (MYF5), myogenin

(MYOG) and MRF4 (MYF6) (Sabourin and Rudnicki, 2000;

Tripathi et al., 2011).

It is very important to understand the dynamics of muscle

transcriptome during the myogenesis to uncover the complex

mechanism underlying muscle development, regeneration

and muscular atrophy [4]. Over the past decade microarray

and SAGE have been commonly used as a means of measur-

ing gene activity by whole tissue transcription profiling. How-

ever, drawbacks of these methods like background

interference/cross-hybridization, the ability only to measure

the relative abundance of predefined transcripts, laborious

and costly cloning and sequencing steps. More recently mas-

sive parallel sequencing has played a larger role in quantify-

ing gene expression by deep sequencing the transcriptome

as this techniques sequence the millions of transcripts simul-

taneously. This high throughput and ultra-deep sequencing

technologies have major advances in terms of robustness,

resolution, comparability and richness, and has been used

for transcriptome analysis in recent years (Mortazavi et al.,

2008; Nagalakshmi et al., 2008; t Hoen et al., 2008; Trapnell

et al., 2012). Deep sequencing the transcriptome, also known

as RNA-Seq, provides both the sequence and frequency of

RNA molecules that are present at any particular time in a

specific cell type, tissue or organ along with the ability to dis-

cover new genes and transcripts in a single assay (Trapnell

et al., 2012). Further, counting the number of mRNAs, encoded

by individual genes, provides an indicator of protein-coding

potential (Hampton et al., 2011). In continuation to our previ-

ous study, this work explores probable genes involved in myo-

tubules formation, in vitro, using Ion Torrent Personal Genome

Machine, their expression level and validation with quantita-

tive real time PCR.

2. Materials and methods

2.1. Adult caprine myoblast cell culture

Muscle tissue of approximately 5 g was obtained from Rec-

tus abdominis muscle of adult goat from slaughter house.

Precursor myoblast cells (satellite cells) were isolated and cul-

tured into Ham’s F10 medium as described previously by our

group (Tripathi et al., 2010). Myoblast cells were cultured in

MEM reduced serum (HyClone) containing 10% FBS at high

confluency to induce fusion for generating myotubes. RNA

Please cite this article in press as: Tripathi, A.K. et al, Transcriptomic disMech. Dev. (2014), http://dx.doi.org/10.1016/j.mod.2014.01.001

from myoblast cells, fused myotubes and muscle tissue were

isolated using TRIzol (Sigma) method as per manufacturer’s

instructions. The differentiated myotubes were immune

stained with anti-Desmin mouse monoclonal primary anti-

body (Sigma #D1033) and Alexa Fluor 488 conjugated goat

anti-mouse secondary antibody (Invitrogen #A11029) for char-

acterization of myotubes.

2.2. Sample preparation and transcriptome run

All the protocols were followed as per manufacturer’s

instructions. The detail protocol steps can be accessed from

Ion Torrent’s Ion Total RNA-Seq Kit (Publication Part No.:

4467098) using 316 chip. Briefly, mRNA was enriched from to-

tal RNA using RiboMinusTM Eukaryote Kit (Invitrogen) followed

by its fragmentation with RNAse III enzyme with an average

of 200–250 nt RNA fragment sizes. The fragmented mRNA

was cleaned and analyzed to assess the yield and size distri-

bution using the Qubit� RNA Assay Kit with the Qubit� Fluo-

rometer (Invitrogen) and the Agilent� RNA 6000 Pico Kit with

the Agilent� 2100 BioanalyzerTM instrument. After RNA oligo

ligation at the fragmented mRNA ends, first and second

strand cDNA was synthesized, followed by PCR amplification,

purification and size selection. The selected PCR products

were again used for emulsion PCR, followed by positive bead

recovery, chip loading and sequencing in the machine.

2.3. In silico gene expression analysis

Sequence reads were generated from myoblasts and myo-

tubes specific cDNA libraries on the Ion Torrent PGM. To cal-

culate in silico gene expression level, we performed RNA-Seq

analysis on the commercially available CLC Genomics Work-

bench v.4.7.1 (http://www.clcbio.com/genomics/) using Bos

taurus RNA database (http://www.ncbi.nlm.nih.gov/) as refer-

ence. The RNA-Seq analysis was carried out for sequence

reads obtained from myoblasts and myotubes separately

using default parameters i.e. the number of mismatches al-

lowed were two, minimum length fraction 0.9, minimum sim-

ilarity fraction 0.8 and maximum hits for a read were 10.

Genes expressed either in myoblasts and myotubes or in both

tissues were grouped, based on reads per kilobase of exon

model per million mapped reads (RPKM) values (Mortazavi

et al., 2008). The differential expression between myoblasts

and myotubes was derived using the RPKM values of the cor-

responding transcripts.

2.4. Functional annotation

The genes uniquely identified in the myoblasts or fused

myotubes with at least 5 unique gene reads and the genes

identified in both myoblasts and fused myotubes with at least

5 unique gene reads in one of the samples and greater than

twofold change in expression based on RPKM ratio were se-

lected for functional categorization of differentially expressed

genes. The genes uniquely identified in the fused myoblast

were considered as up-regulated were as genes uniquely

identified in the myoblasts cells were considered as down-

regulated in fused myoblast cells. The up and down regulated

genes were analyzed for gene ontology (GO) and KEGG

section of myogenic differentiation signature in caprine by RNA-Seq,

Table 1 – List of primers used for qPCR quantitation of selected targets in myoblasts and myotubes.

Sr. No. Gene name Primer sequence Ref. No. PCR product size

Upregulated in myoblasts1 Tubulin, alpha 1a

(TUBA1A)CAATCACCACTCTTCTGTCGT NM_001166505 229CTCACGCATAGTTGCTGTTTC

2 ADAM metallopeptidase withthrombospondin type 1 motif, 1 (ADAMTS1)

TGCCAGACCAAACACTTCCC NM_001101080 181ACTGAACTCCACCACCACAC

3 Plasminogen activator, urokinase (PLAU) GAAAGCACCACCCACTCC NM_174147 117ACCACAAGCAAAACCACCTC

4 High mobility group nucleosomalbinding domain 2 (HMGN2)

AGTGTGAAGAAGAGGCGAGAG NM_001098945 203GGAGGAGCAGGTTTAGCAGA

5 Ribosomal protein L11 (RPL11) GACCCCAGTGTTCTCCAAAG NM_001075581 300CGCTTCTTGTCTGCGATG

6 Ribosomal protein L4 (RPL4) TCACTTTGCCTGCTGTGTTC NM_001014894 126CACTGGTTTGATGACCTGCT

7 Chaperonin containing TCP1,subunit 2 (beta) (CCT2)

CCAGTAGAACACCAGGCAAA NM_001034239 279CCACACGCAGAATCACCTC

Upregulated in myotubes1 LOC100848513 GAGAGGGTGTTTGTGGAGGA XM_003586150 267

GGCGTAGAGGGCTTTTAGTG2 NADH dehydrogenase (ubiquinone)

1 beta subcomplexTGCCCAACCCTATCACCTAC NM_175818 287GTGGCTCTCACCTTCCCTCT

3 X-prolyl aminopeptidase (aminopeptidase P) 2,membrane-bound (XPNPEP2)

GGGCAGAACAACTGGAGAAG NM_001205555 118TCTTTGGTGGGGCTGTAGTG

4 Fibulin 1 (FBLN1) GTCTCACTCCCCACCTTCC NM_001098029 259ATACCACACCCCCAACCAC

5 Retinol dehydrogenase 10 (all-trans) (RDH10) GTGGTGGAGTTCTTCGTGGT NM_174734 210GTTGCTCTGGGTGTTGATGT

6 N-myristoyltransferase 1 (NMT1) ATACACTTCCGTCCACCATC NM_177504 284TAACACCAGCCCAACCTTCT

7 Fibroblast growth factor receptor 1 (FGFR1) TCGGACTCTCCCATCACTCT NM_001110207 178CTCTTCTTTGTGCCGCTCTT

8 cGMP-stimulated phosphodiesterase mRNA GGAGATGATGGACCGTGAGA L49503 181TCGGATGGTGAACTTGTGTG

9 AE binding protein 1 (AEBP1) GGTTTGTGGACGGAGGAG NM_174839 123GATGGGCAGGTTATTGTTGG

Only detected in myotubes1 Synaptogyrin 4 (SYNGR4) TGTCCTCAACAGCAACAGCAC NM_001046436 199

GAAGCAGAATCCCACAGCCCA2 Chemokine (C–C motif) ligand 27 (CCL27) CGGGATTGAGGAGATACGAG NM_001244206 243

CGGCTGGCTGAGTAGTGG3 Metastasis associated 1 (MTA1) ACATCTCCAGCAGCCTCATC NM_001075514 121

GGGTTCTCCATCTCCTCCTC4 Retinol binding protein 2, cellular (RBP2) TGGAACCTGGGAGATGGAGA NM_001101259 260

CATCACCTTCCCAGACGACC5 Leiomodin 2 (cardiac) (LMOD2) TCCAACTTCATCACGGGCAA NM_001105387 294

GTTGGCTCCTCCGTCGTATC6 RAS-like, family 12 (RASL12) TACAGATGGAGAAGCCGAGGT NM_001076933 119

GGCTTGGAGTGAAAGTGCGA

Only detected in myoblasts1 Signal peptidase complex subunit

3 homolog (S. cerevisiae) (SPCS3)TCTCGCGGATCATGCTAA NM_001076993CCTTGAGACCATTTCCGTCA

2 Voltage-dependent anion channel 3 (VDAC3) ACAGGGAAAGCATCAGGCAA NM_174729 282CAACACAGCCCAGCCATAGA

3 ATP synthase, H+ transporting,mitochondrial F1 complex,O subunit (ATP5O), nuclear gene encodingmitochondrial protein

AGAAGGAGTTGTTGCGAGTAGG NM_174244 189GGGTATTAGTCAAGCGACCATTT

4 Mitochondrial carrier 2 (MTCH2), nuclear geneencoding mitochondrial protein

TGATGGGAAGCGTGGATTGT NM_176634 217GAGGGTAGCAGCAGAACGAG

5 Protein phosphatase 1, regulatory (inhibitor)subunit 2 (PPP1R2)

CATCCTGGCGACCTATCATCC NM_001035392 134TCAGGGCTTCAGTGGTTTCT

(continued on next page)

M E C H A N I S M S O F D E V E L O P M E N T x x x ( 2 0 1 4 ) x x x – x x x 3

Please cite this article in press as: Tripathi, A.K. et al, Transcriptomic dissection of myogenic differentiation signature in caprine by RNA-Seq,Mech. Dev. (2014), http://dx.doi.org/10.1016/j.mod.2014.01.001

Table 1 – Continued

Sr. No. Gene name Primer sequence Ref. No. PCR product size

Myogenic regulatory factors1 Myogenic differentiation 1 (MYOD) TGCAACAGCGGATGACTTC NM_001009390.1 228

TTGCAGGCCCACAGTAAAC2 Myogenin (myogenic factor 4) (MYOG) GAACTACCTGCCTGTCCAC NM_001285733.1 172

CGACTTCCTCTTGCACACC3 Myogenic factor 5 (MYF5) GCAAGAGGAAGTCCACCAC NM_001287037.1 131

CAGCCTCTGGTTAGGGTTG4 Myogenic factor 6 (MYF6) CTTGAGGGTGCGGATTTCC NM_001285602.1 205

TCTCCACTACCTCCTCCACG

Endogenous reference gene1 GAPDH ATGTTTGTGATGGGCGTGA AJ431207 241

AAGCAGGGATGATGTTCTGG

4 M E C H A N I S M S O F D E V E L O P M E N T x x x ( 2 0 1 4 ) x x x – x x x

pathways by DAVID database (Huang da et al., 2009) and cat-

egorized based on enrichment of GO terms in biological pro-

cesses, molecular function and cellular component and

association with KEGG pathways for genes up/down regulated

in myotubes compared to myoblasts.

2.5. Real time RT-qPCR

Total RNA was extracted from myoblasts and myotubes as

described before to analyze the expression of myogenic regu-

latory factors (MRFs) and validate the differential expression

of 27 transcripts (Table 1) using RT-qPCR. Gene specific prim-

ers were designed from the respective transcript sequences

using Primer3 software (Rozen and Skaletsky, 2000) (Table 1).

Quality and quantity of DNAseI treated total RNA was ana-

lyzed as described earlier. The reverse transcription reactions

were performed with Oligo(dT) primers using RevertAid

Reverse Transcriptase kit (Fermentas) in 20-ll reactions

Fig. 1 – (A) Immunostaining of fused myotubes. At 96 h after in

anti-Desmin monoclonal antibody and counter stained by DAPI

factors during myogenic differentiation. qPCR analysis of MYOD

differentiated myotubes at 96 h of induction and muscle tissue.

samples (technical replicates).

Please cite this article in press as: Tripathi, A.K. et al, Transcriptomic disMech. Dev. (2014), http://dx.doi.org/10.1016/j.mod.2014.01.001

following the manufacturer’s instructions. The mRNA level

of target genes were quantified by real-time PCR analysis on

ABI PRISM 7500 fast real-time PCR system (Applied Biosys-

tems) using the Quantifast SYBR Green PCR master mix (Qia-

gen). PCR reactions contained 5 pmol of gene specific primers,

1 · Quantifast SYBR Green PCR master mix, 1.5 ll of template

cDNA (5-fold dilution after RT reaction) in a 15 ll reaction

volume. The reaction mixtures were subjected to initial

denaturation of 95 �C for 10 min followed by 40 cycles of

95 �C for 15 s and 60 �C for 1 min. The melt curve analysis

was performed by increasing the temperature from 60 to

95 �C with increase of 1 �C per 30 s followed by final hold at

25 �C. The specificity of the amplification was confirmed by

running PCR product on agarose gel electrophoresis and melt

curve analysis. All reactions were run in triplicate and cycle

threshold (CT) values for target genes were normalized with

GAPDH as reference genes. The fold change in the expression

of the target genes was calculated by the formula: 2�DDCT,

duction of differentiation, fused myotubes were stained by

. Scale bar: 50 lM. (B) Expression of myogenic regulatory

, MYOG, MYF5 and MYF6 from proliferating myoblasts,

Error bar indicates standard error of mean of triplicate

section of myogenic differentiation signature in caprine by RNA-Seq,

M E C H A N I S M S O F D E V E L O P M E N T x x x ( 2 0 1 4 ) x x x – x x x 5

where DCT = average CT of target gene-average CT of

endogenous control (GAPDH), and DDCT = DCT of target sample

(myotubes) – DCT of calibrator sample (myoblasts).

2.6. Analysis of miRNA targets and their expression

The mRNA originated miRNAs identified by RNA-Seq anal-

ysis were searched in mirDB database for identification of their

putative cellular targets. The target specieswere either human,

B. taurus or other mammalian species. The expression profile of

mRNA targets of each miRNAs identified by RNA-Seq analysis

was compared with the RPKM of respective miRNAs.

3. Results

3.1. Differentially expressed genes in myoblasts andmyotubes

Goat myoblasts cells were derived from the primary cul-

ture of muscle tissue and fused myotubes were generated

by culturing the myoblasts in the differentiation medium

for 96 h (Fig. 1A). The analysis of expression of MRFs revealed

up regulation of MYOD, MYOG and MYF6 in differentiated

Table 2 – Summary of transcriptome sequencing of myoblasts a

Features Myoblast

Counted fragments 615,066Uniquely 445,026Non-specifically 170,040Uncounted fragments 333,710Total fragments 948,776

Fig. 2 – RNA-seq mapping of transcriptome reads on the genom

reads from the transcriptome sequencing of myoblasts (upper p

Please cite this article in press as: Tripathi, A.K. et al, Transcriptomic disMech. Dev. (2014), http://dx.doi.org/10.1016/j.mod.2014.01.001

myotubes and higher level of expression of MYOG and MYF6

in muscle tissue compared to proliferating myoblasts

(Fig. 1B). The high throughput sequence data from myoblasts

and myotubes transcriptome using Ion Torrent PGM (Ion

Semiconductor Sequencing technology) generated a total of

948,776 and 799,976 reads from myoblasts and fused myotu-

bes, respectively (Table 2). These reads were further analyzed

on the commercially available CLC Genomics Workbench

v.4.7.1 using B. taurus RNA database as a reference which re-

sulted in 615,066 and 293,096 mapped reads for myoblasts

and myotubes, respectively. Fig. 2 shows the representative

image of the mapped reads of the three samples on one of

the chromosomal loci. The genes identified by RNA-Seq map-

ping were analyzed and classified as common to both myo-

blasts and fused myotubes, only observed in myoblasts and

only in myotubes (Supplementary file 1). The expression level

of each identified genes were represented as RPKM. The anal-

ysis yielded a total of 11,781 genes common to both, 6197

genes unique to myoblast and 573 genes unique to fused

myotubes (Supplementary file 1). The expression of myogenic

regulatory factors MYOD, MYOG, MYF5 and MYF6 was 278.38,

100.17, 12.85, and 1.79 RPKM, respectively in myoblasts

whereas 302.15, 283.74, 6.89, and 0 RPKM, respectively in

nd myotubes.

monolayer Fused myoblast

293,096207,62985,467

506,880799,976

e. Image shows region of the chromosome 7 with mapped

anel), and myotubes (lower panel).

section of myogenic differentiation signature in caprine by RNA-Seq,

6 M E C H A N I S M S O F D E V E L O P M E N T x x x ( 2 0 1 4 ) x x x – x x x

myotubes (Table 3). For further analysis, the genes uniquely

identified in the monolayer or fused myoblast with at least

5 unique gene reads and the genes identified in both mono-

layer and fused myoblast with at least 5 unique gene reads

in one of the samples and greater than two fold change in

expression based on RPKM ratio were selected for functional

categorization and validation by qPCR for both stages (Supple-

mentary files 2 and 3).

3.2. Functional categorization by DAVID revealeddifferential expression of genes regulating cell proliferationand myogenesis

The analysis of differentially expressed transcripts for

enrichment in various biological processes (Supplementary

Table 3 – RNA-Seq expression profile of myogenic regulatory fa

Target RPKM in myoblasts RPK

MYOD1 278.388 302MYOG 100.1754 283MYF5 12.85389 6MYF6 1.799908 0

Fig. 3 – Functional categorization of genes up regulated in myot

molecular function (B); cellular component (C); KEGG pathways

Please cite this article in press as: Tripathi, A.K. et al, Transcriptomic disMech. Dev. (2014), http://dx.doi.org/10.1016/j.mod.2014.01.001

file 4) revealed significant enrichment of over expressed genes

in myogenic processes in myotubes compared to undifferen-

tiated myoblasts. The overexpressed genes in myotubes were

most significantly enriched in biological processes like mus-

cle contraction, muscle system process, regulation of cell pro-

liferation, and vasculature development (Fig. 3A); the genes

enriched in molecular functions categories were in pattern

binding, polysaccharide binding, heparin binding, growth fac-

tor binding, glycosaminoglycan binding, extracellular matrix

structural constituent, structural constituent of muscle,

collagen binding etc. (Fig. 3B); the enrichment of genes in cel-

lular component distribution were in extracellular matrix,

contractile fiber, myofibril, endoplasmic reticulum, extracel-

lular space, collagen and sarcomere localization (Fig. 3C)

and the enrichment in the KEGG pathways were in genes

ctors.

M in myotubes Ratio (myotubes/myoblasts)

.1566 1.085379

.7442 2.832473

.892629 0.536229–

ubes by DAVID. Fold enrichment in biological process (A);

(D).

section of myogenic differentiation signature in caprine by RNA-Seq,

M E C H A N I S M S O F D E V E L O P M E N T x x x ( 2 0 1 4 ) x x x – x x x 7

involved in glycerolipid metabolism, ECM-receptor interac-

tion, and calcium signaling pathway (Fig. 3D).

The down regulated genes in myotubes were enriched in

biological processes related to cell cycle, translation, mitotic

cell cycle, translation elongation, RNA processing, and pro-

tein transport (Fig. 4A); whereas genes enriched in molecular

functions were in nucleotide binding, RNA binding, struc-

tural constituent of ribosome and ATP binding (Fig. 4B).

The enrichment of genes for cellular component distribution

were in organelle lumen, cytosol, nuclear lumen, and

ribosome localization (Fig. 4C); and enrichment in KEGG

pathways were seen in ribosome, cell cycle, proteasome,

spliceosome, RNA degradation, citrate cycle, and DNA repli-

cation (Fig. 4D).

3.3. qPCR analysis confirmed differential expression ofselected transcripts in myoblasts and myotubes

The validation of differentially expressed transcripts

observed in RNA-Seq analysis by qPCR revealed concordance

in the expression of 19 of the 27 selected genes (Table 4). The

over-expression of RASL12, LMOD2, CCL27, XPNPEP2, FBLN1,

RDH10, AEBP1, LOC100848513, NDUFB10 and PDE2A and

under expression of SPCS3, MTCH2, PPP1R2, MTA1, CCT2,

Fig. 4 – Functional categorization of genes down regulated in my

molecular function (B); cellular component (C); KEGG pathways

Please cite this article in press as: Tripathi, A.K. et al, Transcriptomic disMech. Dev. (2014), http://dx.doi.org/10.1016/j.mod.2014.01.001

HMGN2, RPL11, RPL4 and ADAMTS1 in myotubes compared

to myoblasts was confirmed by qPCR (Fig. 5). The expression

of these targets (except PPP1R2, PLAU, RBP2, TUBA1A, AEBP1

and NMT1) in muscle tissue correlated with their expression

in myotubes (Table 4).

RNA-Seq expression analysis of miRNAs and their targets

suggests co-regulated expression of miR-30a, miR-677, miR-

133b and miR-421 in myoblasts and myotubes.

The expression of primary transcripts of miRNAs and their

targets identified by RNA-Seq were further compared which

revealed the concordance in the expression of miR-30a,

miR-133b, miR-677 and miR-421 with their respective targets

(Table 5). The miR-30a transcript was detected only in myotu-

bes by RNA-Seq analysis whereas of its targets ARMC1,

TNRC6B, SESTD1, AAK1, and TNRC6A were down regulated

in myotubes. The expression of miR-677, miR-133b and miR-

421transcripts was observed in both myoblasts and myotubes

but found to be up regulated in myotubes by RNA-Seq analy-

sis. Concomitantly, the expression of miR-677 targets viz.

RSBN1, CSNK1D, CDKN2AIP, DCBLD2, and BIRC6; miR-133b

targets viz. CELF4, SGMS2, TMEM164, SGMS2, ANKRD28, and

PTBP1; and miR-421 targets viz. FAM59A, QKI, PPP1CC,

YTHDC2, CTDSPL2, GSPT1, and NUFIP2 were down regulated

in myotubes.

otubes by DAVID. Fold enrichment in biological process (A);

(D).

section of myogenic differentiation signature in caprine by RNA-Seq,

8 M E C H A N I S M S O F D E V E L O P M E N T x x x ( 2 0 1 4 ) x x x – x x x

4. Discussion

Skeletal muscle growth and development consist of a ser-

ies of carefully regulated changes in gene expression from

embryo to adult and deciphering these developmental

changes in agriculturally important species is essential to

the production of high quality meat products. In this study

we used next generation sequencing platform to determine

the identity and expression level of different genes involved

in muscle development in an in vitro cell culture system.

The major advantage of using NGS platform is in term of time

saving and high throughput of data (Trapnell et al., 2012).

Muscle tissue transcriptome of numerous mammalian spe-

cies have been studied for differential gene expression and

important transcripts involved during muscle growth and

regeneration using different next generation sequencing plat-

forms (Abdul-Hussein et al., 2012; Damon et al., 2012; McGiv-

ney et al., 2010; Sporer et al., 2011). By allowing myoblast to

fuse into multinucleated myotubes in in vitro condition, a

model was created to understand genes involved in muscle

formation. The RNA sample from myoblast and fused myotu-

bes were sequenced and reads were analyzed using B. taurus

RNA-Seq database. Total 11,781 genes were common to both

stages, whereas 6197 genes only in myoblast and 573 genes

only in fused myotubes were observed (Supplementary file

1). Further, the genes uniquely identified in the fused myo-

blast were considered as up-regulated were as genes uniquely

identified in the monolayer cells were considered as down-

regulated in fused myoblast cells including common genes

Table 4 – Comparison of RNA-Seq expression profile of selected

Target RPKM Myoblasts RPKM myotubes

SPCS3 168.03 0.00VDAC3 133.40 0.00ATP5O 85.18 0.00MTCH2 78.86 0.00PPP1R2 27.66 3.46MTA1 31.93 4.94CCT2 109.22 8.69PLAU 123.51 8.69HMGN2 259.30 18.61RPL11 567.91 43.95RPL4 1443.32 113.07RASL12 0.00 7.97LMOD2 0.00 14.57RBP2 0.00 22.27CCL27 0.00 25.09SYNGR4 0.00 30.79TUBA1A 10.81 69.91XPNPEP2 2.06 92.63FBLN1 2.21 92.77RDH10 4.89 173.08FGFR1 9.89 330.15AEBP1 20.69 605.80NMT1 49.79 1701.83LOC100848513 51.65 11886.55NDUFB10 25.43 2303.62PDE2A 2.78 85.99ADAMTS1 94.33 4.80

Genes indicated in bold shows correlation of qPCR expression profile wi

Please cite this article in press as: Tripathi, A.K. et al, Transcriptomic disMech. Dev. (2014), http://dx.doi.org/10.1016/j.mod.2014.01.001

to both stages where RPKM ratio was used to determine up

and down-regulation of genes.

We found that the genes involved in regulating cell prolif-

eration and myogenesis were differentially expressed in myo-

blast and fused myotubes (Figs. 3 and 4), which supports the

process of cell division in myoblast whereas of differentiation

in fused myotubes (Zheng et al., 2009). For example, muscle

differentiation is a well-studied process which is controlled

by MEF2 transcription factor. In this study, we also noticed

that MEF2 expression was up regulated in fused myotubes

(Elgar et al., 2008). Similarly one of the MRFs, MYF6 were

only observed in myoblast which is not involved in muscle

differentiation (Londhe and Davie, 2011). Unlike RNA-Seq,

the expression of MYF6 was found to be up regulated by qPCR.

The identification of MYF6 in myoblasts cells with 1.79 RPKM

but absence of its detection in myotubes by RNA-Seq suggests

that the transcripts identification with less coverage may not

truly represent transcript abundance. The sequencing depth

of the current transcriptome profiling study may thus only

represent moderate to high abundance transcripts and hence

we compared the relative abundance of the transcript which

were identified by P5 unique gene reads. MYOD and MYOG

have been reported to be up regulated in fused myotubes, as

observed in our study by RNA-Seq and further supported by

qPCR (Klover et al., 2009; Tripathi et al., 2011). MYF5 was found

to be down regulated in myotubes by RNA-Seq and qPCR

which is in agreement with its reported involvement in initial

stage of myogenic commitment and myoblasts proliferation

(Francetic and Li, 2011; Valdez et al., 2000). Post-natal skeletal

targets with qPCR.

Change RNA-Seq qPCR myotubes qPCR muscle

# # ## " "# " "# # ## # "# # ## # ## " ## # ## # ## # #" " "" " "" # "" " "" # #" # "" " "" " "" " "" # #" " #" No change "" " "" " "" " "# # #

th RNA-Seq.

section of myogenic differentiation signature in caprine by RNA-Seq,

M E C H A N I S M S O F D E V E L O P M E N T x x x ( 2 0 1 4 ) x x x – x x x 9

muscle growth and function are heavily influenced by hor-

mones like growth hormone (GH) and IGF-1. We also noticed

up regulated expression of IGF1 and IGF2 in fused myotubes

further consolidating their role in muscle development

(Zacchigna et al., 2008). Interestingly, H19 gene expression

has been found in human skeletal muscle which supports

its higher expression in myoblast (Leibovitch et al., 1991).

The RPKM values analyzed by CLC Genomics Workbench

were also validated by RT-qPCR. We selected total of 27 genes

which were either up regulated, down regulated or uniquely

present in myoblast or fused myotubes (Table 4). The up reg-

ulation of Fibulin-1 (FBLN-1) in fused myotubes showed its

important role as a secreted glycoprotein that is associated

with extracellular matrix (ECM) formation and rebuilding

(Chen et al., 2013). Other up-regulated and down-regulated

genes (e.g. HSPs, FOXO, RCAN2) have been reported to play

important function in muscle development and regeneration

(Hori et al., 2010; Qin et al., 2010). It is interesting to note that

Fig. 5 – qPCR analysis of selected targets in myoblasts, myotube

myotubes (A); upregulated in myotubes (B); only detected in myo

bar shows standard error of mean of two independent biologica

Please cite this article in press as: Tripathi, A.K. et al, Transcriptomic disMech. Dev. (2014), http://dx.doi.org/10.1016/j.mod.2014.01.001

expression pattern of most of the genes in myotubes were

similar to adult muscle (Fig. 5). All the top genes down-regu-

lated in fused myotubes (only found in myoblast) were mostly

related with mitochondrial energy metabolism. One such

gene, Voltage-dependent anion channel (VDAC) is a pore-

forming protein which is abundant on mitochondrial outer

membrane of all eukaryotes and is a dynamic regulator of

global mitochondrial function both in health and disease

(Anflous-Pharayra et al., 2011; Sampson et al., 1998). Another

important gene, Mitochondrial carrier homolog 2 (MTCH2),

plays vital role in maintaining the normal function of mito-

chondria. Many genes like metastasis-associated protein 1

(MTA1) and leiomodin 2 (cardiac) (LMOD2) were also found

only in fused myotubes, which have been reported at low

level in muscle tissue (Geng et al., 2008). Recently, EZH2, a

component of Polycomb Repressor Complex 2 (PRC2), has

been suggested as a master regulator of muscle terminal

differentiation process by suppressing key genes involved in

s and muscle. Genes observed to be downregulated in

blasts (C) and only detected in myotubes (D) by RNAseq. Error

l samples with three technical replicates.

section of myogenic differentiation signature in caprine by RNA-Seq,

Table 5 – RNA-Seq expression profile of miRNAs and their respective targets in myoblasts and myotubes.

miRNA RPKM(myoblasts/myotubes)

SpeciesmiRNAreported

miRNA Sequence Top targets mirDB(target scoreP90, max top5 targets listed)

Expression(RPKM)myoblasts/myotubes

Unique in myoblastsmiR-18A 12.80/0 hs-5p uaaggugcaucuagugcagauag TMEM170B –

NEDD9 10.61/11.38INADL 5.08/4.92HIF1A 136.25/94.86ELK4 29.46/10.23

miR-1584 24.90/0 gg ccggguggggcugggcugggmiR-2411 11.80/0 bt uggagugacugucagaugcagccamiR-2355 11.36/0 hs-3p auuguccuugcuguuuggagau TM9SF3 58.68/58.78

PRTFDC1 –SERTM1 –ZFP91 40.51/13.30LARP1 24.08/4.2

hs-5p auccccagauacaauggacaa SH3TC2 1.16/0ZNF99 –RBFA 24.56/38.93GRIN2A –RHBDL3 0.66/0

miR-LET71 10.82/0miR-544B-1 10.69/0miR-125A 20.66/0 mm-3p acaggugagguucuugggagcc ZFP563 –

DDX19B 37.14/3.98mm-5p ucccugagacccuuuaaccuguga RBM7 12.41/1.79hs-3p acaggugagguucuugggagcc CYP20A1 9.89/6.55

PCYOX1 56.56/4.20TRPM3 0/0.88FOXRED2 3.42/1.60TRIP12 69.32/86.91

hs-5p ucccugagacccuuuaaccuguga SH3TC2 1.16/0SLC37A2 –ZNF543 5.54/1.15LACTB 5.36/0

miR-125B-1 20.66/0 mm ucccugagacccuaacuugugamiR-191 9.98/0 mm-3p gcugcacuuggauuucguuccc COPS2 23.40/12.81

RNF180 0.50/0hs-5p caacggaaucccaaaagcagcug

miR-1940 15.14/0 mm auggaggacugagaagguggagcaguu CARD10 1.57/0.84LOC640502 –GM1078 –MAN1A2 20.05/5.07

miR-222 8.26/0 mm-3p agcuacaucuggcuacugggu RANBP9 12.43/22.90ANKRD29 –HECTD2 2.70/7.26KIT –PAIP1 46.5/49.61

mm-5p ucaguagccaguguagauccu AKAP9 7.08/1.69RNF139 5.40/1.44FAM54A 7.35/2.76FEM1B 46.28/12.81

hs-3p agcuacaucuggcuacugggu TMCC1 24.30/4.08KIT –C11ORF41 –CLIC2 4.69/1.25NAP1L5 4.2/0

hs-5p cucaguagccaguguagauccu SH3GLB1 49.75/12.04PTPN3 4.7/0SERPINE2 5.2/26.04FXR1 72.78/73.06FLRT3 74.50/70.94

10 M E C H A N I S M S O F D E V E L O P M E N T x x x ( 2 0 1 4 ) x x x – x x x

Please cite this article in press as: Tripathi, A.K. et al, Transcriptomic dissection of myogenic differentiation signature in caprine by RNA-Seq,Mech. Dev. (2014), http://dx.doi.org/10.1016/j.mod.2014.01.001

Table 5 – continued

miRNA RPKM(myoblasts/myotubes)

SpeciesmiRNAreported

miRNA Sequence Top targets mirDB(target scoreP90, max top5 targets listed)

Expression(RPKM)myoblasts/myotubes

miR-2404–2 27.13/0 bt uugcacugcaugguaucugcmiR-2424–2 bt agaucuuugguaaucugauggcumiR-664 11.09/0 mm-3p uauucauuuacuccccagccua RBM26 0.54/0

FGF7 16.32/87.06LPAR4 1.29/0SLC41A2 10.11/5.23BCOR –

mm-5p cuggcuggggaaaaugacugg LOC640502 –AAK1 5.53/0ADCY6 13.98/22.74ADCY1 0.45/0SRRM4 –

hs-3p uauucauuuauccccagccuaca ZDHHC21 7.24/4.53SH3TC2 1.16/0DCUN1D5 37.21/51.73QKI 320.70/136.34TAF5L 8.62/18.49

hs-5p acuggcuagggaaaaugauuggau OPA3 6.48/0miR-484 14.43/0 mm ucaggcucaguccccucccgau GABPA 28.73/10.37

SLC4A4 20.19/3.15MYCBP2 16.97/7.99DPYSL2 63.00/17.93

hs ucaggcucaguccccucccgau CREB3L3 –ANAPC7 21.16/6.96IFNAR1 11.07/46.75MYCBP2 16.97/7.99

Unique in myotubesmiR-1291 0/184.42 hs uggcccugacugaagaccagcagu TMEM164 8.14/0miR-30A 0/50.92 hs-3p cuuucagucggauguuugcagc ARMC1 21.33/3.33

LGI2 –TNRC6B 12.90/7.07SESTD1 17.80/4.38AAK1 5.53/0

hs-5p uguaaacauccucgacuggaag TNRC6A 7.17/3.72CELSR3 1.29/1.42PPARGC1B –EED 14.01/26.31LHX8 3.98/7.47

mm uguaaacauccucgacuggaagmiR-2332 0/49.45 bt cgguuuaaggucuuggagacaaagmiR-2456 0/47.39 bt acgcacuguccugggaaguggmiR-1-1 0/44.89 hs uggaauguaaagaaguauguau PHAX 23.85/18.70

SH3TC2 1.16/0GJA1 106.78/132.14BDNF –SLC44A1 57.75/237.81

mm-5p acauacuucuuuauaugcccaua CSNK1G3 18.62/8.03ZFP248 –CDC37L1 6.84/3.21FAM110C –G2E3 11.99/2.43

Common in bothmiR-1434 62.25/794.5 gg gugcgugaugauggaaaauumiR-2315 34.08/127.94 bt agcagaauuuuuggauacuggmiR-2358 85.21/106.62 bt ccaaauaguugggaucgugga

(continued on next page)

M E C H A N I S M S O F D E V E L O P M E N T x x x ( 2 0 1 4 ) x x x – x x x 11

Please cite this article in press as: Tripathi, A.K. et al, Transcriptomic dissection of myogenic differentiation signature in caprine by RNA-Seq,Mech. Dev. (2014), http://dx.doi.org/10.1016/j.mod.2014.01.001

Table 5 – continued

miRNA RPKM(myoblasts/myotubes)

SpeciesmiRNAreported

miRNA Sequence Top targets mirDB(target scoreP90, max top5 targets listed)

Expression(RPKM)myoblasts/myotubes

miR-677 55.08/103.38 mm-3p gaagccagaugccguuccugagaagg RSBN1 8.67/4.34ADCY1 0.45/0CSNK1D 20.58/3.86CDKN2AIP 1.02/0PDPK1 17.55/5.34

mm-5p uucagugaugauuagcuucuga DCBLD2 59.68/18.11BIRC6 23.17/9.052900064A13RIK –RICTOR 8.37/7.86

miR-133B 10.82/81.23 mm-3p uuugguccccuucaaccagcua LHFP 12.97/34.79CELF4 3.68/0SGMS2 4.8/0SMARCD1 15.63/16.76

mm-5p gcuggucaaacggaaccaaguc LOC640502 –hs uuugguccccuucaaccagcua TMEM164 8.14/0

LHFP 12.97/34.79SGMS2 4.80/0ANKRD28 18.06/11.11PTBP1 97.38/11.60CELF4 3.68/0

miR-421 10.69/40.13 hs aucaacagacauuaauugggcgc FAM59A 2.51/0QKI 320.70/136.34PPP1CC 54.42/0PLEKHG1 0.26/0.99TOMM70A 34.68/69.95

mm-3p aucaacagacauuaauugggcgc ZFP26 –IWS1 –SYNJ2BP 8.61/23.50YTHDC2 14.86/7.48CTDSPL2 25.79/15.13

mm-5p cucauuaaauguuuguugaau GSPT1 69.03/15.56NUFIP2 16.36/13.03PDSS2 3.75/3.13SULT1D1 –JAZF1 2.85/0

5p – 5 0arm of miRNA.

3p – 3 0-arm of miRNA.

Targets showing concordance with the miRNA expression are shown in bold.

12 M E C H A N I S M S O F D E V E L O P M E N T x x x ( 2 0 1 4 ) x x x – x x x

muscle differentiation by number of studies (Juan et al., 2009;

Palacios et al., 2010; Seenundun et al., 2010). However, Wood-

house et al. (2013) critically dissected its role through knock-

out models and demonstrated that EZH2 is required for

muscle satellite cell expansion but not terminal differentia-

tion. Interestingly, the expression of EZH2 was reduced in

myotubes compared to myoblasts in our study. The compari-

son of up regulated genes in satellite cells following EZH2

deletion (Woodhouse et al., 2013) with our study revealed up

regulation of some of the targets viz. S1PR1, FN1, KM, RGS5,

CYYR1, GAS7, IGF2, LMOD1 and NFATC1 by greater than 5-fold

in fused myotubes compared to myoblasts (Supplementary

file 5). However, number of targets which were up regulated

in EZH2 null satellite cells, were down regulated in differenti-

ated myotubes suggesting EZH2 independent mechanisms

leading to myoblast differentiation.

MicroRNAs (miRNAs) are a class of small RNAs that regu-

late gene expression by post-transcriptional gene silencing

Please cite this article in press as: Tripathi, A.K. et al, Transcriptomic disMech. Dev. (2014), http://dx.doi.org/10.1016/j.mod.2014.01.001

of protein encoding transcripts. These small RNAs have been

well reported to play an important role in skeletal muscle

development. Three muscle-specific miRNAs (miR-1, miR-

133, and miR-206) have been reported to increase in abun-

dance during muscle cell differentiation (Brennecke et al.,

2005; Chen et al., 2006; Nguyen and Frasch, 2006) and regulate

different stages of myogenesis (Anderson et al., 2006; McCar-

thy and Esser, 2007; Nakajima et al., 2006). miR-133 increases

proliferation of C2C12 myoblasts, whereas miR-206 and miR-1

promote differentiation (Chen et al., 2006). (Rao et al. (2006))

demonstrated that the myogenic factors MYOG and MYOD

bind to regions upstream of microRNAs-1q and -133 and,

therefore, are likely to regulate their expression. Expression

of the muscle regulatory factor, MYF5, has been reported to

regulate miR-1 and miR-206 transcription level in a chicken

cell culture model (Sweetman et al., 2008). We observed iden-

tification of miRNAs in transcriptome sequencing possibly

representing primary miRNA transcripts. Although, recent

section of myogenic differentiation signature in caprine by RNA-Seq,

M E C H A N I S M S O F D E V E L O P M E N T x x x ( 2 0 1 4 ) x x x – x x x 13

study demonstrated co-transcriptional processing of poly-

merase II derived transcripts both independently transcribed

and intron-encoded miRNAs (Morlando et al., 2008), their

identification in mRNA-Seq data suggest possibility of incom-

pletely processed transcripts. As miRNAs are generated from

mRNA like transcripts, we found many miRNA coding tran-

scripts in mRNA-Seq like miR-1 (up), miR-133b (up), miR-222

(down), miR-30a (down) in our study. The expression pattern

of these miRNAs during differentiation was supported by re-

cent study (Dmitriev et al., 2013). Importantly, the respective

miRNAs primary transcripts and their putative targets were

having corresponding expression in the myoblast and fused

myotubes (Table 5). In addition to muscle-specific miRNAs

(mir-1 andmir-133), a larger number of ubiquitous miRNAs

(mir-1291, mir-30A, mir-1584 etc.) were identified in myo-

blasts and myotubes transcriptomes, indicating the need of

further study to find their importance in muscle growth and

development.

5. Conclusion

In this study, we identified many important genes involved

in muscle development and differentiation. The validation of

RNA-Seq finding by qPCR revealed concordance in expression

of 19 out of 27 genes (70%) with RNA-Seq expression profile.

Most genes up-regulated in myotubes were grouped into mus-

cle contraction and muscle system process in biological pro-

cess and collagen, myofibrils, and contractile fibers in

cellular component localization. However, down-regulated

genes in myotubes (over-expressed in myoblast) were princi-

pally involved into cell cycle, transcriptional and translational

regulation and cellular metabolic processes. Further, mRNA-

Seq based predicted miRNAs suggested possible regulatory

control on their putative targets. Data generated from this

RNA-Seq experiment will focus on various candidate genes,

their proteins, and their functions in skeletal muscle develop-

ment which will help to design strategy for increased meat

production for human consumption.

Acknowledgement

We thank National Agriculture Innovation Project, Indian

council of Agricultural Research (NAIP-ICAR), Government of

India, for their financial support of this study.

Appendix A. Supplementary data

Supplementary data associated with this article can be

found, in the online version, at http://dx.doi.org/10.1016/

j.mod.2014.01.001.

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