Open Access

Gene expression profiling in the Cynomolgus macaque Macaca fascicularis shows variation within the normal birth range

  • Bright Starling Emerald1, 4Email author,
  • Keefe Chng1,
  • Shinya Masuda1,
  • Deborah M Sloboda2,
  • Mark H Vickers2,
  • Ravi Kambadur1, 3 and
  • Peter D Gluckman1, 2
BMC Genomics201112:509

DOI: 10.1186/1471-2164-12-509

Received: 22 February 2011

Accepted: 16 October 2011

Published: 16 October 2011

Abstract

Background

Although an adverse early-life environment has been linked to an increased risk of developing the metabolic syndrome, the molecular mechanisms underlying altered disease susceptibility as well as their relevance to humans are largely unknown. Importantly, emerging evidence suggests that these effects operate within the normal range of birth weights and involve mechanisms of developmental palsticity rather than pathology.

Method

To explore this further, we utilised a non-human primate model Macaca fascicularis (Cynomolgus macaque) which shares with humans the same progressive history of the metabolic syndrome. Using microarray we compared tissues from neonates in the average birth weight (50-75th centile) to those of lower birth weight (5-25th centile) and studied the effect of different growth trajectories within the normal range on gene expression levels in the umbilical cord, neonatal liver and skeletal muscle.

Results

We identified 1973 genes which were differentially expressed in the three tissue types between average and low birth weight animals (P < 0.05). Gene ontology analysis identified that these genes were involved in metabolic processes including cellular lipid metabolism, cellular biosynthesis, cellular macromolecule synthesis, cellular nitrogen metabolism, cellular carbohydrate metabolism, cellular catabolism, nucleotide and nucleic acid metabolism, regulation of molecular functions, biological adhesion and development.

Conclusion

These differences in gene expression levels between animals in the upper and lower percentiles of the normal birth weight range may point towards early life metabolic adaptations that in later life result in differences in disease risk.

Background

Clinical, experimental and epidemiological studies have highlighted a link between the early-life environment and the health and well-being of offspring in later life. An adverse maternal environment has been linked to an increased risk of developing metabolic and cardiovascular disorders including type 2 diabetes, obesity, hyperlipidemia, insulin resistance and hypertension [17]. An important feature of these studies is that these relationships exist within the normative birth range and do not depend on extremes of birth weight. This has led to the proposal that later life disease risk is the result of maladaptive consequences of plastic mechanisms which would normally be adaptive [8, 9].

It is proposed that developmental plasticity determines the trajectory of development through epigenetic processes such that the fetus attempts to match its later phenotype to the environment [10]. It has been proposed that low birth weight is a marker of a poor early life nutritional environment [11] and thus a smaller fetus is more likely to develop a metabolic capacity appropriate for a low nutrient postnatal environment. But, if faced with a high nutrient environment it is more likely to become obese and insulin resistant [12]. Although, epigenetic processes have been increasingly implicated largely from rodent studies involving nutritional manipulation of the dam [13, 14] the molecular mechanisms underlying altered disease susceptibility are largely unknown. There is also some evidence that these developmental trajectories, and associated long-term gene expression and epigenetic changes can be reversed by the administration of the adipokine leptin to the neonatal rat although the concentrations used were higher than physiological levels [10, 12, 15, 16]. These data suggest that a better understanding of the molecular events associated with impaired early life development may help in designing future intervention strategies.

To identify the possible molecular pathways associated with variations in the fetal environment, we have utilised a non-human primate (NHP) model, the Macaca fascicularis (Cynomolgus macaque) to elucidate whether variations within the normal birth weight range are associated with differential gene expressions patterns. Cynomolgus macaques share with humans the same progressive history of the metabolic syndrome [17] which makes this model directly relevant to humans and importantly, Cynomolgus macaque is a monotocous species in which spontaneous variation in fetal growth rather than experimental manipulation can be investigated. This study therefore we have investigated the effect of spontaneous lower birth weight on gene expression in key tissues (umbilical cord, hepatic tissue and skeletal muscle) from female Cynomolgus macaque neonates.

Methods

Collection of Umblical cords

Sixty-five pregnant Cynomolgus macaque dams, sired naturally by one male, were monitored prior to delivery at the Vietnam Primate Breeding and Development Corporation. After birth, dams were sedated (ketamine-HCl; 7 mg/kg) to facilitate collection of the umbilical cord. The cords were collected and immediately snap-frozen in liquid nitrogen and stored at -80°C for later analyses. Neonates were weighed at birth and promptly returned to the dams. All animal procedures were approved by Nafovanny, subsidiary of the Ministry of Forestry, Vietnam, and performed in accordance with the guidelines set by the national advisory committee for laboratory animal research (NACLAR) of Singapore.

Collection of hepatic and skeletal muscle samples

The normative birth range was assessed from these 65 pregnancies and 8 neonates were selected based on their birth weights to comprise 2 groups: 1) lower birth weight group (LBW); n = 4 classified as those that were within the 5th to 25th birth weight percentile, birth weight range 299-317 g and 2) average birth weight group (ABW); n = 4 classified as those that were within the 50th to 75th birth weight percentile, birth weight range 358-398 g. The normal gestation of Cynomolgus macaque is approximately 155-170 days [18]. We have estimated the gestational age based on early ultrasound measurements (greatest length of the embryo at the time of pregnancy detection) and used those pregnancies where fetuses were within normal distribution for full term Cynomolgus macaques [18]. On postnatal day 5, neonates were sedated with an intramuscular injection of ketamine-HCl (15 mg/kg), and exsanguinated under anesthesia. Liver and skeletal muscle (biceps femoris) were collected and immediately snap frozen in liquid nitrogen and stored at -80°C for later analyses

Preparation of Total RNA

Total RNA was isolated from umbilical cords and neonatal tissues using TRIzol reagent according to the manufacturer's instructions (Invitrogen). RNA integrity was confirmed by bio analyzer 2100 (Agilent Technologies, Santa Clara, USA). An RNA Integrity Number (RIN) value of 7.5 above was considered acceptable and used in further experiments.

Microarray analysis

For microarray analysis, RNA from 6 groups of samples (Cord: ABW and LBW; Liver: ABW and LBW; skeletal muscle: ABW and LBW) were labeled using QuickAmp 1-color labeling kit (Agilent Technologies) according to manufacturer's protocol. The Cy3 labeled cRNA were subsequently hybridized to Agilent Rhesus Macaque (G2519F-015421) Gene Expression microarray. The Rhesus macaque gene expression microarray used in this study represented 43,803 Rhesus monkey probes synthesized as 60-mers spotted using the Agilent SurePrint technology (Agilent Technologies). The microarrays were scanned with Agilent High resolution Scanner and the images were feature extracted using FE software version 10.5 (Agilent Technologies).

Data analysis was performed using Genespring GX ver10 (Agilent Technologies). The raw signal intensity from each samples is global normalized to 75th percentile and base-line transformed. Probes flagged with present call in at least 75% of the samples in any of the 6 groups were used for subsequent data analysis.

Two-way ANOVA was performed with p value cut-off at 0.05 to identify genes that are differentially expressed in the tissue type and birth weight. Due to limited annotation of Rhesus Monkey genome, the microarray probes are annotated against human genes and ontology. For mapping against the human genome, the probes from the monkey microarray were re-annotated using Agilent eARRAY. The probe sequences were aligned to human genome (hg18) using BLAST based algorithm and the associated human annotation was extracted from the database.

To study the gene expression profile of the birth weight in each of the tissue type, Welch T-Test with p-value cut off of 0.05 and fold change of 1.5X was performed between the ABW and LBW samples in each of the tissue groups.

Complete microarray data is available at the Gene Expression Omnibus (GEO) database under the accession number GSE32069.

Network Analysis

The microarray data was imported into Pathway Studio version 7 (Ariadne Genomics, Rockville, USA) for network analysis. Gene Set Enrichment Analysis (GSEA) was performed on ABW vs LBW in the respective tissue using Kolmogorov-Smirnov algorithm with p-value cut-off at 0.05. In addition, Network Enrichment Analysis (NEA) was performed to identify expression hub of the treatment. Sub network was generated by connecting entities to their expression target network using the Resnet 7 Mammalian database.

Quantitative RT-PCR

Five up-regulated and two down regulated genes were selected for verification using qRT-PCR. The primers were designed using the Cynomolgus if available or Rhesus macaque sequences using the primer 3 software if not available [19]. The gene symbols and the primers are listed in Table 1.
Table 1

Sequences of primers used for qRT-PCR:

PASK F 5' CTACTCCGGGAGCTGCTATC 3'

PASK R5' AGCAGCAGAACAGAGGTGTG 3'

116936 F5' GCACATCTGCCTGAAGTGAA 3'

116936 R5' GAGCAGCTTGTCCAGGAAGT 3'

ADK F5' TGGTGGCTCTACCCAGAACT 3'

ADK R5' CATCTACATGGGCTTCAGCA 3'

ELMO F5' AGCTCTGTGTGGCTTGGTTT 3'

ELMO R5' CGGTGTGAATAACGGAGTCCT 3'

SIX1 F5' GTTTAAGAACCGGAGGCAAA 3'

SIX1 R5' GGAGAGAGTTGGTTCTGCTTG 3'

SLC12A9 F5' GGCTTCAACAGCAGTACCCT 3'

SLC12A9 R5' AAGAGGACAGCAAAGACGCT 3'

RBL1 F5' TAGCCTGACCAACATGGAGA 3'

RBL1 R5' GTTCAAGCAATTCTGCCTCA 3'

Uni18SrRNA F5' AGTCCCTGCCCTTTGTACACA 3'

Uni18SrRNA R5' GATCCGAGGGCCTCACTAAAC 3'

We used skeletal muscle RNA to verify the array. Briefly, total RNA was extracted as mentioned above from four ABW and four LBW neonates and were reverse transcribed using Applied Biosystem's high-capacity cDNA reverse transcription kit using 1 μg of total RNA in a reaction volume of 20 μl. The PCR reactions were carried out in 25 μl of SYBR Green Master Mix with 200 ng of cDNA using 7500 real time PCR system (Applied Biosystems, CA, USA). The comparative Ct method was used to calculate the relative gene expression [20]. 18S RNA was used as the internal control which was validated using the method described in Schmittgen and Livak [20] and found to be stable and consistent.

Results

Microarray analysis

Two-way factorial ANOVA identified 1973 genes which were differentially expressed in the three tissue types between ABW and LBW neonates (P < 0.05). Of these, 1141 genes were up regulated in the LBW samples while 832 genes were down-regulated in the LBW samples compared to ABW (Figure 1).
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-12-509/MediaObjects/12864_2011_Article_3655_Fig1_HTML.jpg
Figure 1

Hierarchical clustergram of 1973 genes (1141 up regulated in LBW and 832 down regulated in LBW) identified by ANOVA (P < 0.05) in all the three tissues (umbilical cord (C), liver (L) and skeletal muscle (B) analyzed. The relative expression is reflected by the intensity of the color (Green = down regulated, red = up regulated)

Gene expression profiles of umbilical cord, liver and skeletal muscle were also compared using Welch-t-test. There were 250 genes significantly and differently expressed in the liver, 850 genes significantly and differently expressed in the skeletal muscle and 891 genes significantly and differently expressed in cord samples (P < 0.05, >1.5 fold difference) (Figure 2, 3). The top 50 genes whose gene expression levels changed in each tissue based on their fold difference based on Welch T-test are given in Tables 2, 3, 4.
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-12-509/MediaObjects/12864_2011_Article_3655_Fig2_HTML.jpg
Figure 2

Heat map depicting the differentially expressed genes in skeletal muscle (850 genes), liver (210 genes) and cord (891 genes) (P < 0.05, >= 1.5 fold difference). A. 733 genes (584 genes up regulated in LBW skeletal muscle, 149 genes down regulated in LBW skeletal muscle), B. 19 genes (16 genes up regulated in LBW skeletal muscle and 15 genes up regulated in LBW liver, 3 genes down regulated in LBW skeletal muscle and 4 genes down regulated in liver). C 182 genes (115 genes up regulated in LBW liver and 67 genes down regulated in LBW liver). D 5 genes (2 genes up regulated in LBW cords and 3 genes up regulated LBW liver, 3 genes down regulated in LBW cords and 2 genes down regulated in LBW liver). E. 788 genes (338 genes up regulated in LBW cord and 450 genes down regulated LBW cord). F. 94 genes (60 genes up regulated in LBW skeletal muscle and 22 up regulated in LBW cord, 34 genes down regulated in LBW skeletal muscle and 72 genes down regulated in LBW cord. G. 4 genes (4 genes up regulated in LBW skeletal muscle and liver, 4 genes down regulated in LBW cord).

https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-12-509/MediaObjects/12864_2011_Article_3655_Fig3_HTML.jpg
Figure 3

Venn diagram depicting the differentially expressed genes in skeletal muscle (850 genes), liver (210 genes) and cord (891 genes) t-test unpaired unequal variance, LBW vs ABW, p < 0.05, >= 1.5 fold difference.

Table 2

List of top 50 genes significantly differentially regulated in the skeletal muscle based on fold difference (t-test).

Gene Symbol

2Way ANOVA P value

Fold Change in Skeletal muscle, Welch t-test

Regulation in LBW

Fold change Liver, Welch t-test

Regulation in LBW

Fold change in Cords, Welch t-test

Regulation in LBW

Gene name

XM_116936

0.017913306

10.054285

up

1.080386

up

2.185324

up

PREDICTED: Homo sapiens similar to RIKEN cDNA 4832428D23 gene (LOC196541) mRNA [XM_116936]

XM_056254

0.021895792

9.569201

up

2.09208

down

1.391897

up

PREDICTED: Homo sapiens heparan sulfate (glucosamine) 3-O-sulfotransferase 4 (HS3ST4) mRNA [XM_056254]

C5orf23

0.01475329

6.0808635

up

1.072585

up

1.301361

up

Homo sapiens chromosome 5 open reading frame 23 (C5orf23), mRNA [NM_024563]

PASK

0.03426426

5.977056

up

2.995584

up

19.17474

up

Homo sapiens PAS domain containing serine/threonine kinase (PASK), mRNA [NM_015148]

WDR8

0.004681234

5.6804295

down

2.978104

down

8.061375

down

Homo sapiens WD repeat domain 8 (WDR8), mRNA [NM_017818]

ADK

1.63E-04

5.639505

down

1.368648

down

9.386349

down

Homo sapiens adenosine kinase (ADK), transcript variant ADK-short, mRNA [NM_001123]

APOBEC3G

0.040698703

4.8567457

down

1.669566

down

1.105857

down

Homo sapiens apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3G (APOBEC3G), mRNA [NM_021822]

CCL2

0.002121243

4.757898

down

1.287543

down

2.895307

down

Homo sapiens chemokine (C-C motif) ligand 2 (CCL2), mRNA [NM_002982]

A_01_P013390

0.029869065

4.6248507

down

1.099004

down

1.527467

down

 

BC044226

0.04677891

4.3998837

down

1.966762

down

1.502299

down

Homo sapiens myosin binding protein H, mRNA [BC044226]

CCL11

0.008992519

4.050988

down

3.178148

down

1.002582

up

Homo sapiens chemokine (C-C motif) ligand 11 (CCL11), mRNA [NM_002986]

POU4F3

0.02459994

3.8642302

up

1.615214

up

1.991698

down

Homo sapiens POU domain, class 4, transcription factor 3 (POU4F3), mRNA [NM_002700]

XR_011794

0.010519872

3.7855186

up

3.637105

up

2.76764

up

PREDICTED: Macaca mulatta similar to poly(A)-specific ribonuclease (PARN)-like domain containing 1 (LOC707835), mRNA [XR_011794]

H1FOO

0.011109326

3.7804163

up

1.404401

up

1.449255

down

Homo sapiens H1 histone family, member O, oocyte-specific (H1FOO), mRNA [NM_153833]

C17orf75

0.001362531

3.7583363

down

3.447702

down

1.443745

down

Homo sapiens chromosome 17 open reading frame 75 (C17orf75), mRNA [NM_022344]

RNF216

0.001650785

3.7307158

down

1.504036

down

6.793567

down

Homo sapiens TRIAD3 protein (TRIAD3), transcript variant 1, mRNA [NM_207111]

GTSF1

0.017040279

3.6632807

up

4.653995

up

2.487166

up

Homo sapiens family with sequence similarity 112, member B (FAM112B), mRNA [NM_144594]

C13orf33

0.006214988

3.5870998

down

2.664488

down

1.061963

up

Homo sapiens chromosome 13 open reading frame 33 (C13orf33), mRNA [NM_032849]

CA2

0.033340864

3.5736616

down

3.483002

down

1.194329

up

Homo sapiens carbonic anhydrase II (CA2), mRNA [NM_000067]

CO645773

0.03704907

3.5384166

down

2.022003

down

1.474969

down

ILLUMIGEN_MCQ_30118 Katze_MMPB Macaca mulatta cDNA clone IBIUW:22572 5' similar to Bases 1 to 42 highly similar to human RARRES3 (Hs.17466), mRNA sequence [CO645773]

MYST3

0.013409907

3.3029778

up

2.827006

up

1.403819

up

Homo sapiens MYST histone acetyltransferase (monocytic leukemia) 3 (MYST3), mRNA [NM_006766]

NM_000977

0.008561992

3.2655115

up

2.138359

up

2.014805

up

Homo sapiens ribosomal protein L13 (RPL13), transcript variant 1, mRNA. [NM_000977]

XR_014265

0.001382546

3.2319098

down

1.270026

down

2.168579

down

PREDICTED: Macaca mulatta hypothetical protein LOC716045 (LOC716045), mRNA [XR_014265]

NM_001004685

0.043442905

3.1747854

up

1.353824

up

1.407273

down

Homo sapiens olfactory receptor, family 2, subfamily F, member 2 (OR2F2), mRNA. [NM_001004685]

XR_014204

0.029225934

3.167453

down

3.849135

down

1.084816

up

PREDICTED: Macaca mulatta hypothetical protein LOC719546 (LOC719546), mRNA [XR_014204]

DARS

3.99E-05

3.1527941

down

1.10567

down

12.63266

down

Homo sapiens aspartyl-tRNA synthetase (DARS), mRNA [NM_001349]

GYLTL1B

9.45E-04

3.143812

up

1.169517

up

3.19979

up

Homo sapiens glycosyltransferase-like 1B (GYLTL1B), mRNA [NM_152312]

CNNM2

1.94E-04

3.1423542

up

1.00608

down

1.785853

up

Homo sapiens cyclin M2 (CNNM2), transcript variant 1, mRNA [NM_017649]

C20orf26

0.023210809

3.1168563

up

1.353857

up

1.414684

up

Homo sapiens chromosome 20 open reading frame 26 (C20orf26), mRNA [NM_015585]

SLC26A9

0.042099766

3.0884879

up

2.137558

up

1.776504

up

Homo sapiens solute carrier family 26, member 9 (SLC26A9), transcript variant 1, mRNA [NM_052934]

SEC14L3

0.025527291

3.0402198

up

1.787294

up

1.547541

down

Homo sapiens SEC14-like 3 (S. cerevisiae) (SEC14L3), mRNA [NM_174975]

TMEM20

0.001055841

2.9346027

down

1.821723

down

1.558415

down

Homo sapiens transmembrane protein 20 (TMEM20), mRNA [NM_153226]

UHRF1

0.042854026

2.9323897

down

1.272487

down

1.455897

down

Homo sapiens ubiquitin-like, containing PHD and RING finger domains, 1 (UHRF1), transcript variant 2, mRNA [NM_013282]

CST9L

0.008572864

2.9286344

up

1.46455

up

1.695363

down

Homo sapiens cystatin 9-like (mouse) (CST9L), mRNA [NM_080610]

C2

0.005425731

2.906241

down

1.470166

down

1.228973

up

Homo sapiens complement component 2 (C2), mRNA [NM_000063]

C7orf62

0.03373279

2.8281868

up

1.466387

up

1.326441

down

Homo sapiens hypothetical protein MGC26647 (MGC26647), mRNA [NM_152706]

HOXB13

0.008404698

2.822795

up

1.530259

up

1.061908

down

Homo sapiens homeobox B13 (HOXB13), mRNA [NM_006361]

ANLN

0.026928915

2.8110342

down

1.205709

down

1.210447

down

Homo sapiens anillin, actin binding protein (ANLN), mRNA [NM_018685]

TMEM45B

0.02836952

2.789488

up

1.108079

up

1.434473

up

Homo sapiens transmembrane protein 45B (TMEM45B), mRNA [NM_138788]

COL8A2

0.029133584

2.7760508

down

1.111961

down

2.334076

down

Homo sapiens collagen, type VIII, alpha 2 (COL8A2), mRNA [NM_005202]

IL15RA

3.56E-05

2.7710447

down

2.542192

down

5.776398

down

Homo sapiens interleukin 15 receptor, alpha (IL15RA), transcript variant 2, mRNA [NM_172200]

AY937248

0.002621024

2.7557867

up

1.074139

down

2.046131

up

Macaca mulatta placental protein 14 mRNA, complete cds [AY937248]

SCN3B

0.00199475

2.7342772

up

1.566765

up

1.26591

up

Homo sapiens sodium channel, voltage-gated, type III, beta (SCN3B), transcript variant 1, mRNA [NM_018400]

TRIM6

0.005424626

2.7181938

up

1.451755

up

1.960095

up

Homo sapiens tripartite motif-containing 6 (TRIM6), transcript variant 1, mRNA [NM_001003818]

TNS4

0.041628703

2.7158492

up

1.315606

up

1.297834

down

Homo sapiens tensin 4 (TNS4), mRNA [NM_032865]

PDE1C

0.026903268

2.6685586

up

1.596604

up

1.15087

down

Homo sapiens phosphodiesterase 1C, calmodulin-dependent 70kDa (PDE1C), mRNA [NM_005020]

S100A4

0.01836204

2.656307

down

1.047433

down

2.01034

down

Homo sapiens S100 calcium binding protein A4 (S100A4), transcript variant 1, mRNA [NM_002961]

AADACL1

0.017924123

2.6216743

down

1.119603

down

1.47176

down

Homo sapiens arylacetamide deacetylase-like 1 (AADACL1), mRNA [NM_020792]

XR_011345

0.029255124

2.6165082

up

1.450092

up

1.492756

down

PREDICTED: Macaca mulatta similar to otoancorin isoform 1 (LOC699600), mRNA [XR_011345]

FN1

0.02028952

2.6025481

down

1.05622

down

1.051482

down

Homo sapiens fibronectin 1 (FN1), transcript variant 1, mRNA [NM_212482]

SP7

3.05E-04

2.5985072

up

1.616763

up

1.088733

down

Homo sapiens Sp7 transcription factor (SP7), mRNA [NM_152860]

Table 3

List of top 50 genes significantly differentially regulated in liver based on fold difference (t-test).

Gene Symbol

2Way ANOVA P value

Fold Change in Liver Welch t-test

Regulation in LBW

Fold change skeletal tissue, Welch t-test

Regulation in LBW

Fold change in Cords, Welch t-test

Regulation in LBW

Gene name

ELMOD1

0.011425177

25.931845

down

1.737314

down

2.051013

up

Homo sapiens ELMO/CED-12 domain containing 1 (ELMOD1), mRNA [NM_018712]

RBBP9

0.026729036

11.012514

down

1.47388

down

5.131376

down

Homo sapiens retinoblastoma binding protein 9 (RBBP9), mRNA [NM_006606]

MMP25

0.001325307

10.996225

down

2.384582

down

1.436251

down

Homo sapiens matrix metallopeptidase 25 (MMP25), mRNA [NM_022468]

C5orf46

0.047762383

10.762607

down

1.234639

up

1.096919

up

Homo sapiens similar to AVLV472 (MGC23985), mRNA [NM_206966]

GOLSYN

2.29E-05

6.13113

up

1.05566

up

1.458383

up

Homo sapiens hypothetical protein FLJ20366 (FLJ20366), mRNA [NM_017786]

LCN15

0.005291665

5.3478875

up

1.891747

up

2.217465

up

Homo sapiens MSFL2541 (UNQ2541), mRNA [NM_203347]

CCDC146

0.030661521

5.281487

up

1.06658

up

1.360575

up

Homo sapiens KIAA1505 protein (KIAA1505), mRNA [NM_020879]

AK094929

0.001118242

5.262121

up

1.690864

up

1.110624

up

Homo sapiens cDNA FLJ37610 fis, clone BRCOC2011398. [AK094929]

SORCS3

0.00328917

5.0026994

up

2.266284

up

2.921157

up

Homo sapiens sortilin-related VPS10 domain containing receptor 3 (SORCS3), mRNA [NM_014978]

COL4A4

0.01571377

4.897748

down

1.548386

down

1.059327

down

Homo sapiens collagen, type IV, alpha 4 (COL4A4), mRNA [NM_000092]

IL1R2

0.004347455

4.777918

down

1.8715

down

1.690538

down

Homo sapiens interleukin 1 receptor, type II (IL1R2), transcript variant 1, mRNA [NM_004633]

CD200R1

0.04967409

4.7169123

down

1.052303

up

1.319852

down

Homo sapiens CD200 receptor 1 (CD200R1), transcript variant 1, mRNA [NM_138806]

GTSF1

0.017040279

4.653995

up

3.663281

up

2.487166

up

Homo sapiens family with sequence similarity 112, member B (FAM112B), mRNA [NM_144594]

SNAI1

0.005038617

4.582946

down

1.534132

down

1.847129

down

Homo sapiens snail homolog 1 (Drosophila) (SNAI1), mRNA [NM_005985]

USH1C

0.00505742

4.3276477

up

1.595945

up

1.465964

up

Homo sapiens Usher syndrome 1C (autosomal recessive, severe) (USH1C), transcript variant 1, mRNA [NM_005709]

ALLC

0.006709512

4.060955

up

1.861818

up

2.766094

up

Homo sapiens allantoicase (ALLC), transcript variant 1, mRNA [NM_018436]

CXCL3

0.04903758

3.9091544

down

1.096309

down

1.172056

up

Homo sapiens chemokine (C-X-C motif) ligand 3 (CXCL3), mRNA [NM_002090]

XR_014204

0.029225934

3.8491352

down

3.167453

down

1.084816

up

PREDICTED: Macaca mulatta hypothetical protein LOC719546 (LOC719546), mRNA [XR_014204]

XR_011794

0.010519872

3.637105

up

3.785519

up

2.76764

up

PREDICTED: Macaca mulatta similar to poly(A)-specific ribonuclease (PARN)-like domain containing 1 (LOC707835), mRNA [XR_011794]

NMNAT2

0.045685206

3.6255727

up

2.521069

down

2.189285

up

Homo sapiens nicotinamide nucleotide adenylyltransferase 2 (NMNAT2), transcript variant 1, mRNA [NM_015039]

SLC39A8

0.041505713

3.6139402

down

1.366996

down

1.390711

down

Homo sapiens solute carrier family 39 (zinc transporter), member 8 (SLC39A8), mRNA [NM_022154]

CA2

0.033340864

3.4830022

down

3.573662

down

1.194329

up

Homo sapiens carbonic anhydrase II (CA2), mRNA [NM_000067]

NTRK3

0.003890598

3.4711208

up

1.593136

up

1.043792

down

Homo sapiens neurotrophic tyrosine kinase, receptor, type 3 (NTRK3), transcript variant 1, mRNA [NM_001012338]

C17orf75

0.001362531

3.4477015

down

3.758336

down

1.443745

down

Homo sapiens chromosome 17 open reading frame 75 (C17orf75), mRNA [NM_022344]

CXCL1

0.006956845

3.392382

down

1.063934

up

4.611126

down

Homo sapiens chemokine (C-X-C motif) ligand 1 (melanoma growth stimulating activity, alpha) (CXCL1), mRNA [NM_001511]

NM_198692

0.03194352

3.3605232

down

1.343767

up

1.654617

down

Homo sapiens keratin associated protein 10-11 (KRTAP10-11), mRNA. [NM_198692]

SHANK2

0.023280138

3.3547363

up

1.255762

up

1.189415

down

Homo sapiens SH3 and multiple ankyrin repeat domains 2 (SHANK2), transcript variant 1, mRNA [NM_012309]

CCDC81

0.004982437

3.2717588

down

1.533572

down

4.912844

down

Homo sapiens coiled-coil domain containing 81 (CCDC81), mRNA [NM_021827]

CCL11

0.008992519

3.1781478

down

4.050988

down

1.002582

up

Homo sapiens chemokine (C-C motif) ligand 11 (CCL11), mRNA [NM_002986]

CO647386

0.020776557

3.1651435

down

1.030158

down

1.631509

down

ILLUMIGEN_MCQ_40418 Katze_MMPB2 Macaca mulatta cDNA clone IBIUW:21432 5' similar to Bases 185 to 778 highly similar to human CXCL2 (Hs.75765), mRNA sequence [CO647386]

GPR98

0.024752488

3.1570897

down

1.10821

down

3.919889

down

Homo sapiens G protein-coupled receptor 98 (GPR98), transcript variant 1, mRNA [NM_032119]

TMEM59L

5.34E-04

3.137047

up

1.57364

up

1.407988

up

Homo sapiens transmembrane protein 59-like (TMEM59L), mRNA [NM_012109]

UGT1A6

0.040070046

3.1353552

down

2.066639

down

1.399845

down

Homo sapiens UDP glucuronosyltransferase 1 family, polypeptide A6 (UGT1A6), transcript variant 1, mRNA [NM_001072]

KCNE2

7.02E-04

3.1135461

up

1.972823

up

1.170852

down

Homo sapiens potassium voltage-gated channel, Isk-related family, member 2 (KCNE2), mRNA [NM_172201]

XR_012376

0.022554293

3.0699794

down

1.9303

down

1.439485

down

PREDICTED: Macaca mulatta hypothetical protein LOC710335 (LOC710335), mRNA [XR_012376]

RXFP1

0.002097808

3.0400152

up

1.931833

up

1.276558

up

Homo sapiens relaxin/insulin-like family peptide receptor 1 (RXFP1), mRNA [NM_021634]

ITGBL1

0.02861261

3.0041916

down

2.563332

down

1.243521

down

Homo sapiens integrin, beta-like 1 (with EGF-like repeat domains) (ITGBL1), mRNA [NM_004791]

PASK

0.03426426

2.995584

up

5.977056

up

19.17474

up

Homo sapiens PAS domain containing serine/threonine kinase (PASK), mRNA [NM_015148]

DEFB1

0.004949556

2.9797235

down

1.065357

up

2.807533

down

Homo sapiens defensin, beta 1 (DEFB1), mRNA [NM_005218]

WDR8

0.004681234

2.9781044

down

5.68043

down

8.061375

down

Homo sapiens WD repeat domain 8 (WDR8), mRNA [NM_017818]

RIMS4

0.04112827

2.9677074

up

1.724443

up

1.024011

down

Homo sapiens regulating synaptic membrane exocytosis 4 (RIMS4), mRNA [NM_182970]

PDGFRL

0.011396675

2.9371088

down

1.21306

down

1.55284

down

Homo sapiens platelet-derived growth factor receptor-like (PDGFRL), mRNA [NM_006207]

TNRC4

0.005930619

2.9251838

up

1.208589

up

1.396738

up

Homo sapiens trinucleotide repeat containing 4 (TNRC4), mRNA [NM_007185]

UGT2B11

0.02518766

2.9193914

down

1.09908

down

2.958316

down

Homo sapiens UDP glucuronosyltransferase 2 family, polypeptide B11 (UGT2B11), mRNA [NM_001073]

FLT3LG

0.029793594

2.8908129

up

1.037797

down

1.527226

up

Homo sapiens fms-related tyrosine kinase 3 ligand (FLT3LG), mRNA [NM_001459]

IP6K3

0.03900314

2.8685477

up

1.471319

up

1.39455

down

Homo sapiens inositol hexaphosphate kinase 3 (IHPK3), mRNA [NM_054111]

ST6GALNAC1

0.03669531

2.8622296

down

1.408642

down

2.126189

down

Homo sapiens ST6 (alpha-N-acetyl-neuraminyl-2,3-beta-galactosyl-1,3)-N-acetylgalactosaminide alpha-2,6-sialyltransferase 1 (ST6GALNAC1), mRNA [NM_018414]

EFNA4

0.007086268

2.843187

down

1.084758

up

2.766163

down

Homo sapiens ephrin-A4 (EFNA4), transcript variant 1, mRNA [NM_005227]

MYST3

0.013409907

2.827006

up

3.302978

up

1.403819

up

Homo sapiens MYST histone acetyltransferase (monocytic leukemia) 3 (MYST3), mRNA [NM_006766]

XM_370715

0.001614059

2.7565975

up

1.561267

up

2.382949

up

PREDICTED: Homo sapiens similar to hypothetical protein MGC48915 (LOC387911), mRNA [XM_370715]

NM_031436

0.035783853

2.6903787

up

1.740635

up

1.698687

up

Homo sapiens aldo-keto reductase family 1, member C-like 2 (AKR1CL2), mRNA. [NM_031436]

Table 4

Top 50 genes significantly differentially regulated in cord based on fold difference (t-test).

Gene Symbol

2Way ANOVA P value

Fold Change in cord, Welch t-test

Regulation in LBW

Fold change skeletal tissue, Welch t-test

Regulation in LBW

Fold change in liver,

Regulation in LBW

Gene name

ATP5F1

0.003504217

29.998667

down

1.850386

down

1.153583

down

Homo sapiens ATP synthase, H+ transporting, mitochondrial F0 complex, subunit B1 (ATP5F1), nuclear gene encoding mitochondrial protein, mRNA [NM_001688]

EHHADH

3.25E-05

29.713446

down

1.004504

up

1.027032

down

Homo sapiens enoyl-Coenzyme A, hydratase/3-hydroxyacyl Coenzyme A dehydrogenase (EHHADH), mRNA [NM_001966]

CNPY2

6.12E-05

24.275322

down

2.033511

down

1.345912

down

Homo sapiens transmembrane protein 4 (TMEM4), mRNA [NM_014255]

IMMP1L

5.31E-04

21.21959

down

1.067236

down

1.052987

up

Homo sapiens IMP1 inner mitochondrial membrane peptidase-like (S. cerevisiae) (IMMP1L), mRNA [NM_144981]

GNL2

0.008845676

19.523186

down

1.389994

down

1.352022

up

Homo sapiens guanine nucleotide binding protein-like 2 (nucleolar) (GNL2), mRNA [NM_013285]

HRSP12

0.010644738

19.35189

down

1.121147

up

1.013192

up

Homo sapiens heat-responsive protein 12 (HRSP12), mRNA [NM_005836]

CN643639

2.57E-05

19.177528

down

1.710693

down

1.132373

up

ILLUMIGEN_MCQ_8235 Katze_MMBR Macaca mulatta cDNA clone IBIUW:3333 5' similar to Bases 1 to 682 highly similar to human Unigene Hs.513885, mRNA sequence [CN643639]

PASK

0.03426426

19.17474

up

5.977056

up

2.995584

up

Homo sapiens PAS domain containing serine/threonine kinase (PASK), mRNA [NM_015148]

NDUFC1

1.93E-04

18.786453

down

1.418954

down

1.095977

up

Homo sapiens NADH dehydrogenase (ubiquinone) 1, subcomplex unknown, 1, 6 kDa (NDUFC1), mRNA [NM_002494]

BNIP3L

3.67E-05

18.46857

down

2.523903

down

1.123252

down

Homo sapiens BCL2/adenovirus E1B 19 kDa interacting protein 3-like (BNIP3L), mRNA [NM_004331]

GALE

0.004030123

18.304993

down

1.591229

up

1.378757

down

Homo sapiens UDP-galactose-4-epimerase (GALE), transcript variant 1, mRNA [NM_000403]

XM_371837

2.06E-06

18.251152

down

1.76245

down

1.15429

down

PREDICTED: Homo sapiens similar to oxidoreductase UCPA (LOC389416), mRNA [XM_371837]

OSTCL

9.90E-05

17.57389

down

1.173702

down

1.075778

down

Homo sapiens similar to RIKEN cDNA 2310008M10 (LOC202459), mRNA [NM_145303]

WDR75

7.83E-05

17.02899

down

2.353145

down

1.037028

down

Homo sapiens WD repeat domain 75 (WDR75), mRNA [NM_032168]

SMPDL3A

1.25E-05

16.127317

down

1.290077

down

1.780315

down

Homo sapiens sphingomyelin phosphodiesterase, acid-like 3A (SMPDL3A), mRNA [NM_006714]

LIN7C

6.29E-04

15.929515

down

1.429568

down

1.006664

down

Homo sapiens lin-7 homolog C (C. elegans) (LIN7C), mRNA [NM_018362]

COX7B

8.03E-06

15.9135065

down

1.283232

down

1.138854

up

Homo sapiens cytochrome c oxidase subunit VIIb (COX7B), nuclear gene encoding mitochondrial protein, mRNA [NM_001866]

MRPL1

1.35E-06

15.901582

down

1.776047

down

1.05264

up

Homo sapiens mitochondrial ribosomal protein L1 (MRPL1), nuclear gene encoding mitochondrial protein, mRNA [NM_020236]

NPM3

3.58E-04

15.357531

down

1.39378

down

1.314134

up

Homo sapiens nucleophosmin/nucleoplasmin, 3 (NPM3), mRNA [NM_006993]

RNF126

4.43E-04

15.14725

down

1.165075

down

1.084156

down

Homo sapiens ring finger protein 126 (RNF126), transcript variant 2, mRNA [NM_194460]

ATG4C

1.86E-06

14.422242

down

1.01449

down

1.571663

down

Homo sapiens ATG4 autophagy related 4 homolog C (S. cerevisiae) (ATG4C), transcript variant 7, mRNA [NM_032852]

ACMSD

2.00E-04

14.3137

down

1.121731

up

1.098467

down

Homo sapiens aminocarboxymuconate semialdehyde decarboxylase (ACMSD), mRNA [NM_138326]

WASF3

0.0026955

14.211387

down

1.134297

down

1.574282

up

Homo sapiens WAS protein family, member 3 (WASF3), mRNA [NM_006646]

F13B

1.26E-05

13.94526

down

1.052562

down

1.02993

down

Homo sapiens coagulation factor XIII, B polypeptide (F13B), mRNA [NM_001994]

HNRNPA1L2

0.007305239

13.879195

down

1.288451

up

1.062584

down

Homo sapiens heterogeneous nuclear ribonucleoprotein A1-like (LOC144983), transcript variant 1, mRNA [NM_001011724]

XR_011737

0.001940294

13.592515

down

1.736661

down

1.168041

up

PREDICTED: Macaca mulatta similar to transcription factor B2, mitochondrial (LOC710669), mRNA [XR_011737]

CP

1.42E-04

13.285389

down

1.122256

down

1.274657

down

Homo sapiens ceruloplasmin (ferroxidase) (CP), mRNA [NM_000096]

TOLLIP

1.59E-04

12.683504

down

1.156986

down

1.00844

down

Homo sapiens toll interacting protein (TOLLIP), mRNA [NM_019009]

DARS

3.99E-05

12.632657

down

3.152794

down

1.10567

down

Homo sapiens aspartyl-tRNA synthetase (DARS), mRNA [NM_001349]

CKLF

4.24E-04

12.476327

down

1.130294

down

1.064736

down

Homo sapiens chemokine-like factor (CKLF), transcript variant 1, mRNA [NM_016951]

STT3B

1.13E-04

12.457355

down

2.027118

down

1.030927

down

Homo sapiens STT3, subunit of the oligosaccharyltransferase complex, homolog B (S. cerevisiae) (STT3B), mRNA [NM_178862]

TXNDC11

4.40E-05

12.377014

down

1.525444

down

1.011564

down

Homo sapiens thioredoxin domain containing 11 (TXNDC11), mRNA [NM_015914]

CR603105

9.80E-04

12.209639

down

1.284419

down

1.155491

down

full-length cDNA clone CS0DF006YN22 of Fetal brain of Homo sapiens (human) [CR603105]

XR_010672

5.09E-05

11.634537

down

1.602301

down

1.059423

up

PREDICTED: Macaca mulatta similar to Molybdenum cofactor synthesis protein 2 large subunit (Molybdopterin synthase large subunit) (MPT synthase large subunit) (MOCS2B) (MOCO1-B) (LOC703049), mRNA [XR_010672]

GDE1

0.03917646

11.536806

down

1.190901

up

1.20255

up

Homo sapiens membrane interacting protein of RGS16 (MIR16), mRNA [NM_016641]

CFHR2

2.07E-04

11.37657

down

1.208862

down

1.032327

down

Homo sapiens complement factor H-related 2 (CFHR2), mRNA [NM_005666]

RPL30

0.03067462

11.374878

down

1.173423

up

1.096937

up

Homo sapiens ribosomal protein L30 (RPL30), mRNA [NM_000989]

XM_495885

0.002429009

11.322625

down

1.165255

down

1.156577

down

PREDICTED: Homo sapiens similar to ribosomal protein S12 (LOC440055), mRNA [XM_495885]

NDUFB1

2.13E-04

11.293429

down

1.404433

down

1.277028

up

Homo sapiens NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 1, 7 kDa (NDUFB1), mRNA [NM_004545]

NM_032807

2.89E-04

11.240869

down

1.075345

down

1.014724

down

Homo sapiens F-box protein, helicase, 18 (FBXO18), transcript variant 1, mRNA. [NM_032807]

CSGALNACT 2

1.34E-05

11.216295

down

1.714551

down

1.080183

down

Homo sapiens chondroitin sulfate GalNAcT-2 (GALNACT-2), mRNA [NM_018590]

NM_022333

0.002598488

10.94874

down

1.130622

up

1.014866

down

Homo sapiens TIA1 cytotoxic granule-associated RNA binding protein-like 1 (TIAL1), ranscript variant 2, mRNA [NM_022333]

NM_032807

0.001172931

10.342792

down

1.522541

down

1.139832

down

Homo sapiens F-box protein, helicase, 18 (FBXO18), transcript variant 1, mRNA. [NM_032807]

AAMP

2.62E-05

10.171815

down

1.560637

down

1.085371

down

Homo sapiens angio-associated, migratory cell protein (AAMP), mRNA [NM_001087]

ESF1

1.02E-07

9.745275

down

1.620818

down

1.008674

down

Homo sapiens ESF1, nucleolar pre-rRNA processing protein, homolog (S. cerevisiae) (ESF1), mRNA [NM_016649]

DOCK7

0.01799708

9.74066

down

1.174452

up

1.171709

up

Homo sapiens dedicator of cytokinesis 7 (DOCK7), mRNA [NM_033407]

DDX3Y

4.78E-06

9.687978

down

1.356089

down

1.134329

down

Homo sapiens DEAD (Asp-Glu-Ala-Asp) box polypeptide 3, Y-linked (DDX3Y), mRNA [NM_004660]

XIAP

3.65E-05

9.587557

down

1.882389

down

1.280735

up

Homo sapiens baculoviral IAP repeat-containing 4 (BIRC4), mRNA [NM_001167]

TRPC4AP

9.51E-05

9.4549885

down

1.340843

down

1.07043

up

Homo sapiens transient receptor potential cation channel, subfamily C, member 4 associated protein (TRPC4AP), transcript variant 1, mRNA [NM_015638]

ADK

1.63E-04

9.386349

down

5.639505

down

1.368648

down

Homo sapiens adenosine kinase (ADK), transcript variant ADK-short, mRNA [NM_001123]

NM_0010022 92

3.92E-04

9.258961

down

1.016391

up

1.220083

down

Homo sapiens chromosome 1 open reading frame 139 (C1orf139), transcript variant 2, mRNA. [NM_001002292]

Of the 250 genes which were differently expressed in the liver, 182 genes were unique to the liver (115 genes up regulated in the LBW group and 67 genes down-regulated in the LBW group). There were 19 genes which were significantly and differently expressed between liver and skeletal muscle (16 up regulated in LBW skeletal muscle and 15 genes up regulated in liver and 3 down-regulated in the LBW skeletal muscle and 4 down regulated in LBW liver). There were 5 genes which are significantly and differently expressed between liver and cord (3 up regulated in LBW liver and 2 genes up regulated in LBW cord and 2 down regulated in LBW liver and 3 down regulated in the cord).

Of the 850 genes significantly and differently expressed in skeletal muscle, 733 genes were specific to the skeletal muscle; i.e. showed altered regulation only in the skeletal muscle (584 genes up regulated in the LBW samples and 149 genes down regulated in the LBW group). There were 94 genes which were significantly and differently expressed between skeletal muscle and cord (60 up regulated in LBW skeletal muscle and 22 genes up regulated in LBW cord and 34 genes down regulated in the LBW skeletal muscle and 72 genes down regulated in the LBW cord).

Of the 891 genes significantly and differently expressed in umbilical cord; 788 genes showed altered regulation only in umbilical cord (338 genes up regulated and 450 genes down regulated in LBW group). There were 4 genes which are significantly and differently expressed between liver, skeletal muscle and umbilical cord (4 genes up regulated in the LBW skeletal muscle and liver while the same four genes were down regulated in LBW cord) Figure 2, 3.

Functional classification of genes

Gene ontology was used to classify genes based on functional significance. The main component of the Gene Ontology (GO) annotation taken into consideration was metabolic function. Genes were classified into fifteen functional categories: Cellular lipid metabolic process (43 genes), Cellular biosynthetic process (95 genes), Cellular macromolecule synthesis (222 genes), Cellular nitrogen compound metabolic process (10 genes), Cellular carbohydrate metabolic process (6 genes), Cellular catabolic process (9 genes), Nucelobase, Nucleoside, nucleotide and nucleic acid metabolic process (216 genes), Other cellular metabolic process (29 genes), Other metabolic process (36 genes), Transport (141 genes), Regulation of molecular functions (28 genes), Biological adhesion (27 genes), Developmental process (74 genes) Other biological processes (252 genes) and Non classified (795) with p-value of (p > 0.05). The genes enriched for each GO term were further classified into the number of genes up regulated or down regulated in each tissue with a fold difference of 1.5 or greater (Table 5) (Additional file 1).
Table 5

Gene ontology classification to group genes using Genespring ver10 (Agilent Tech, Santa Clara) of similar functional families.

 

Skeletal muscle

Liver

Cord

 

Up regulated

Down regulated

Up regulated

Down regulated

Up regulated

Down regulated

Cellular lipid metabolic process

15

6

4

4

13

11

Cellular biosynthesis process

8

14

6

4

16

40

Cellular macromolecule synthesis

21

32

19

14

45

63

Cellular nitrogen metabolic process

4

1

4

0

7

1

Cellular carbohydrate metabolic process

2

0

0

0

2

1

Cellular catabolic process

1

2

0

0

2

1

Nucleobase, Nucleoside, nucleotide and nucleic acid metabolic process

19

17

15

4

66

43

Other cellular metabolic process

3

2

1

3

3

15

Other metabolic process

5

7

5

2

9

11

Transport

30

17

21

14

39

26

Regulation of molecular functions

4

2

1

1

12

8

Biological adhesion

6

8

4

5

8

10

Developmental process

19

11

7

4

20

16

Other biological process

38

38

25

19

65

59

Quantitative RT-PCR

To validate the micoarray results we carried out quantitative RT-PCR (qRT-PCR) using the same RNA samples in the microarray analysis. We selected seven genes (a novel gene XM_116936, PAS domain containing serine/threonine kinase (PASK), Adenisine kinase (ADK) transcript variant ADK-short, ELMO/CED-12 domain containing 1 (ELMOD1), Sine oculins homeobox homolog 1 (SIX1) Retinoblastoma like-1 (RBL1) and Solute carrier family 12 (potassium/chloride transporters) member 9 (SLC12A9) for this validation of the array using skeletal muscle cDNA. Of these 5 genes were significantly up regulated in the array and 2 genes were significantly down regulated in the array. Our results from the qPCR complement our results from the microarray (Table 6). The fold differences along with the values which derived from the microarray are presented in Table 6.
Table 6

Verification of seven genes from the microarray using Real-time RT-PCR analysis in skeletal muscle.

Gene Symbol and description

2 way ANOVA p-value (Birth weight)

Microarray Fold change (t-Test)

Regulation in LBW

qPCR-Fold Change

XM_116936

0.017913306

10.054285

Up regulated

 

PREDICTED: Homo sapiens similar to RIKEN cDNA 4832428D23 gene

   

4.780893

PASK:

0.03426426

5.977056

Up regulated

 

Homo sapiens PAS domain containing serine/threonine kinase

   

14.55481

ADK:

1.63E-04

-5.639505

Down regulated

 

Homo sapiens adenosine kinase, (transcript variant ADK-short)

   

-3.57235

ELMOD1:

    

Homo sapiens ELMO/CED-12 domain containing 1.

0.011425177

-1.7373136

Down regulated

-1.71015

SIX1:

    

Homo sapiens sine oculis homeobox homolog 1 (Drosophila).

0.045728132

1.1253903

Up in low birth weight

1.246574

RBL1:

    

Homo sapiens retinoblastoma-like 1 (p107), (transcript variant 1)

0.011705314

1.5320477

Up regulated

3.023726

SLC12A9:

    

Homo sapiens solute carrier family 12 (potassium/chloride transporters), member 9.

1.31E-05

1.3670695

Up regulated

1.694303

Discussion

In the present study, we have identified genes involved in key metabolic signaling pathways in three tissue types in a non-human primate model, that were differentially expressed according to the birth weight of the animal. Importantly, this differential expression was across the normal birth weight spectrum and therefore likely to represent adaptive pathways that the fetuses uses to predict its postnatal environment. The identification of novel signaling pathways that appear to be regulated by the early life environment is a key step in designing future experimental paradigms to understand the association between birth weight and disease risk. Metabolic disease particularly, has been strongly with early life adversity [21, 22]. Our data begin to shed light on the key signaling pathways that are vulnerable to subtle changes in the early life environment.

The strength of our study, despite its small size, is that we have focused on infants whose growth was not experimentally manipulated but lay within normal birth weight range. Many experimental models have manipulated pregnancy in an effort to produce fetal growth restriction. Such studies have shown that offspring which are born growth restricted catch-up in growth with their normally nourished counterparts and in adulthood are obese, hypertensive, hyperinsulinemic, leptin resistant and display sedentary behavior [2325]. Investigations into underlying mechanisms and the determination of gene expression levels that may explain these altered phenotypes have produced conflicting results [2628] which may reflect variations in the model systems used and the gender of the animals used [28]. Taken together, although these studies have established the link between early life nutritional adversity to later pathophysiology, there are limitations in the interpretation of rodent studies in development as applied to humans.

In the present study we aimed to study the molecular associates of growth variation within the normative range and exclude pathology. This is because the growing literature on developmental outcomes highlights that the importance of variation in risk is associated with non-pathological developmental environments. Accordingly we studied relatively small infants born between the 5th and 25th centile but excluded the smallest neonates, which may reflect obstetrical abnormalities. These infants were compared to infants in the middle of the normative range (50th-75th centile) and accordingly we excluded infants who may have had macrosomia as a result of the mother's being over-nourished by being maintained in captivity. Thus we are confident that we have excluded pathological influences and demonstrated that within the normative range patterns of gene expression may vary considerably with variable birth weights. Indeed we found a number of genes with more than a 10 fold shift in expression levels. There are important implications to this observation. Historically, experimental and epidemiological focus has been on the extremes of birth weight (either small for gestational age or large for gestational age) and there has been little focus within the normal birth weight range continuum. What is evident from the present study is that relatively small changes in the birth phenotype may be associated with profound changes in molecular physiology. In turn this also suggests the presence of highly evolved processes by which the fetus can adjust its development in response to subtle cues from mother [29].

The Cynomolgus, as in the human, has monotocous pregnancies with haemochorial placentae; they have omnivorous diets and monogastric digestion. They also share with humans the same progressive history of the metabolic syndrome [17]. We have identified alterations in the levels and expression patterns of a number of genes involved in different metabolic processes including cellular lipid metabolism, cellular biosynthesis, cellular macromolecule synthesis, cellular nitrogen metabolism, cellular carbohydrate metabolism, cellular catabolism, nucleotide and nucleic acid metabolism, biological adhesion and development.Recently, transcriptional profiling in rats subjected to gestational under nutrition was performed in young adult male rats where 249 genes were shown to be differentially expressed in the liver [28]. We compared the genes which are significantly altered in our array with those identified in the rat array study and have identified twelve similar or closely related genes from those identified in the rat: Tribbles homolog 2 (Trib2); 3-hydroxyanthanillate dioxygenase (Haao), transmembrane serine protease 6 (Tmmprss6); Thioredoxin domain containing10 (Txndc10); tralation initiation factor 4A3 (Eifa3); Ribosomal protein L31 (Rpl31); Danse 1-like 2 (Dnase1l2); Quinolate phosphoribosyl transferase (Qprt); general transcription factor IIa 2 (Gtf2a3); General transcription factor II H 3 [28]. Only four of these genes (Trib2, Trip10, EIF4A3 and Dnase1l2) were altered in the same direction in the livers of LBW macaques as in the rat array. We have also compared our observations with those identified from LBW term placentas by McCarthy and colleagues [30] and found similarities in expression changes in the genes Procollagen-lysine, 2-oxoglutarate 5-dioygense (PLOD2); Soluble interleukin-1 receptor accessory protein (IL1RAP); Solute carrier family 2 (facilitated glucose transporter) member3 (SLC2A3); Myosin V1(MYH6); Ribosomal protein S6(RPS6) and Latexin (LXN). The Tribbles homolog 2 (Trib2) is also increased in the LBW infants and suggests another possible way in way insulin/IGF-1 signalling might be impaired during development. Tribbles belongs to a family of kinase-like proteins and are reported to be negative regulators of Akt, the principle target of insulin signaling [31, 32].

Studies using animal models such as rodents to understand the developmental origins of metabolic diseases have shown that epigenetic changes in genes correlates with expression changes including metabolic enzymes such as PEPCK, transcriptional factors such as PPARα which regulate fat metabolism and factors associated with insulin action (e.g. PI3 kinase, PKC-ζ), the key regulatory genes which are responsible for bringing these changes are not known [15, 33]. One aim in our study was to identify whether there were shifts within the expression of key early regulators and from the array we have identified one such key regulatory gene the PAS Kinase (PASK), an evolutionarily conserved PAS domain containing serine/threonine kinase whose expression is altered as a result of adverse early developmental conditions. PAS domains are evolutionarily conserved and appear from archaea, bacteria to eukaryotes and are present in many signaling proteins where they act as signal sensor domain [34]. The PASK gene, whereby expression was up regulated in the LBW animals, has been shown to be a metabolic sensor based on mice knock-out studies; mice lacking PASK are resistant to high-fat induced obesity, hepatic steatosis and are resistant to insulin [35].

Conclusions

In summary, this paper has identified significant variation in gene expression in multiple tissues in primate newborns of different growth trajectories but within the normative range of birth size. Further detailed analyses may improve our understanding of how alterations in such genes due to adverse early life environment predisposes towards metabolic syndrome. These data give strength to the hypothesis that developmental plasticity operating within the normative range of birth weights can influence metabolic and other physiological systems in a way that might have later health consequences. It emphasizes that the concept of developmental programming need not involve pathological changes in growth trajectories to have molecular and presumably functional consequences.

Declarations

Acknowledgements

BSE, RK, PDG, KC, SM are supported by Agency for Science, Technology and research (Singapore). PDG, DMS, MHV are funded by the National Research Centre for Growth and Development, University of Auckland (New Zealand).

Authors’ Affiliations

(1)
Growth, Development and Metabolism Programme, Singapore Institute for Clinical Sciences, Brenner Centre for Molecular Medicine
(2)
Liggins Institute and the National Research Centre for Growth and Development, The University of Auckland
(3)
Division of Molecular Genetics & Cell Biology, School of Biological Sciences, Nanyang Technological University
(4)
Department of Anatomy, Faculty of medicine and Health Sciences, UAE University, Tawam Medical Campus

References

  1. Barker DJ, Winter PD, Osmond C, Margetts B, Simmonds SJ: Weight in infancy and death from ischaemic heart disease. Lancet. 1989, 2 (8663): 577-80.PubMedView ArticleGoogle Scholar
  2. Barker DJP: The fetal and infant origins of adult disease, London. British Medical Journal Publishing. 1993, 1-343.Google Scholar
  3. Barker DJ, Gluckman PD, Godfrey KM, Harding JE, Owens JA, Robinson JS: Fetal nutrition and cardiovascular disease in adult life. Lancet. 1993, 341 (8850): 938-41. 10.1016/0140-6736(93)91224-A.PubMedView ArticleGoogle Scholar
  4. Phillips P, Wilson D, Taylor A, Esterman A, Wakefield M: Cardiovascular risk factors in South Australians with diabetes. Aust J Public Health. 1994, 18 (4): 445-9.PubMedView ArticleGoogle Scholar
  5. Curhan GC, Chertow GM, Willett WC, Spiegelman D, Colditz GA, Manson JE, Speizer FE, Stampfer MJ: Birth weight and adult hypertension and obesity in women. Circulation. 1996, 94 (6): 1310-5.PubMedView ArticleGoogle Scholar
  6. Curhan GC, Willett WC, Rimm EB, Spiegelman D, Ascherio AL, Stampfer MJ: Birth weight and adult hypertension, diabetes mellitus, and obesity in US men. Circulation. 1996, 94 (12): 3246-50.PubMedView ArticleGoogle Scholar
  7. Burdge GC, Lillycrop KA: Nutrition, epigenetics, and developmental plasticity: implications for understanding human disease. Annu Rev Nutr. 2010, 30: 315-39. 10.1146/annurev.nutr.012809.104751.PubMedView ArticleGoogle Scholar
  8. Gluckman PD, Hanson MA, Bateson P, Beedle AS, Law CM, Bhutta ZA, Anokhin KV, Bougnères P, Chandak GR, Dasgupta P, Smith GD, Ellison PT, Forrester TE, Gilbert SF, Jablonka E, Kaplan H, Prentice AM, Simpson SJ, Uauy R, West-Eberhard MJ: Towards a new developmental synthesis: adaptive developmental plasticity and human disease. Lancet. 2009, 373 (9675): 1654-7. 10.1016/S0140-6736(09)60234-8.PubMedView ArticleGoogle Scholar
  9. Gluckman PD, Hanson MA: Living with the past: evolution, development, and patterns of disease. Science. 2004, 305 (5691): 1733-6. 10.1126/science.1095292.PubMedView ArticleGoogle Scholar
  10. Gluckman PD, Hanson MA, Beedle AS: Early life events and their consequences for later disease: a life history and evolutionary perspective. Am J Hum Biol. 2007, 19 (1): 1-19. 10.1002/ajhb.20590.PubMedView ArticleGoogle Scholar
  11. Hales CN, Barker DJ: The thrifty phenotype hypothesis. Br Med Bull. 2001, 60: 5-20. 10.1093/bmb/60.1.5.PubMedView ArticleGoogle Scholar
  12. Gluckman PD, Hanson MA, Cooper C, Thornburg KL: Effect of in utero and early-life conditions on adult health and disease. N Engl J Med. 2008, 359 (1): 61-73. 10.1056/NEJMra0708473.PubMed CentralPubMedView ArticleGoogle Scholar
  13. Burdge GC, Hanson MA, Slater-Jefferies JL, Lillycrop KA: Epigenetic regulation of transcription: a mechanism for inducing variations in phenotype (fetal programming) by differences in nutrition during early life?. Br J Nutr. 2007, 97 (6): 1036-46. 10.1017/S0007114507682920.PubMed CentralPubMedView ArticleGoogle Scholar
  14. Lillycrop KA, Slater-Jefferies JL, Hanson MA, Godfrey KM, Jackson AA, Burdge GC: Induction of altered epigenetic regulation of the hepatic glucocorticoid receptor in the offspring of rats fed a protein-restricted diet during pregnancy suggests that reduced DNA methyltransferase-1 expression is involved in impaired DNA methylation and changes in histone modifications. Br J Nutr. 2007, 97: 1064-73. 10.1017/S000711450769196X.PubMed CentralPubMedView ArticleGoogle Scholar
  15. Vickers MH, Gluckman PD, Coveny AH, Hofman PL, Cutfield WS, Gertler A, Breier BH, Harris M: Neonatal leptin treatment reverses developmental programming. Endocrinology. 2005, 146 (10): 4211-6. 10.1210/en.2005-0581.PubMedView ArticleGoogle Scholar
  16. Vickers MH, Gluckman PD, Coveny AH, Hofman PL, Cutfield WS, Gertler A, Breier BH, Harris M: The effect of neonatal leptin treatment on postnatal weight gain in male rats is dependent on maternal nutritional status during pregnancy. Endocrinology. 2008, 149 (4): 1906-13. 10.1210/en.2007-0981.PubMedView ArticleGoogle Scholar
  17. Wagner JE, Kavanagh K, Ward GM, Auerbach BJ, Harwood HJ, Kaplan JR: Old world nonhuman primate models of type 2 diabetes mellitus. ILAR J. 2006, 47 (3): 259-71.PubMedView ArticleGoogle Scholar
  18. Tarantal AF, HendrickX AG: Charecterization of prenatal growth and development in the Crab-eating macaque (Macaca fasicularis) by ultrasound. The Anatomical record. 1988, 222: 177-184. 10.1002/ar.1092220210.PubMedView ArticleGoogle Scholar
  19. Rozen S, Skaletsky H: Primer3 on the WWW for general users and for biologist programmers. Methods mol Biol. 2000, 132: 365-386.PubMedGoogle Scholar
  20. Schmittgen TD, Livak KJ: Analyzing real-time PCR data by the comparative C(T) method. Nat Protoc. 2008, 3 (6): 1101-8. 10.1038/nprot.2008.73.PubMedView ArticleGoogle Scholar
  21. Gluckman PD, Hanson MA: Maternal constraint of fetal growth and its consequences. Semin Fetal Neonatal Med. 2004, 9 (5): 419-25. 10.1016/j.siny.2004.03.001.PubMedView ArticleGoogle Scholar
  22. Godfrey KM, Gluckman PD, Hanson MA: Developmental origins of metabolic disease: life course and intergenerational perspectives. Trends Endocrinol Metab. 2010, 21 (4): 199-205. 10.1016/j.tem.2009.12.008.PubMedView ArticleGoogle Scholar
  23. Vickers MH, Breier BH, Cutfield WS, Hofman PL, Gluckman PD: Fetal origins of hyperphagia, obesity, and hypertension and postnatal amplification by hypercaloric nutrition. Am J Physiol Endocrinol Metab. 2000, 279 (1): E83-7.PubMedGoogle Scholar
  24. Vickers MH, Reddy S, Ikenasio BA, Breier BH: Dysregulation of the adipoinsular axis-a mechanism for the pathogenesis of hyperleptinemia and adipogenic diabetes induced by fetal programming. J Endocrinol. 2001, 170 (2): 323-32. 10.1677/joe.0.1700323.PubMedView ArticleGoogle Scholar
  25. Vickers MH, Breier BH, McCarthy D, Gluckman PD: Sedentary behavior during postnatal life is determined by the prenatal environment and exacerbated by postnatal hypercaloric nutrition. Am J Physiol Regul Integr Comp Physiol. 2003, 285 (1): R271-3.PubMedView ArticleGoogle Scholar
  26. Lillycrop KA, Phillips ES, Jackson AA, Hanson MA, Burdge GC: Dietary protein restriction of pregnant rats induces and folic acid supplementation prevents epigenetic modification of hepatic gene expression in the offspring. J Nutr. 2005, 135 (6): 1382-6.PubMedGoogle Scholar
  27. Lillycrop KA, Rodford J, Garratt ES, Slater-Jefferies JL, Godfrey KM, Gluckman PD, Hanson MA, Burdge GC: Maternal protein restriction with or without folic acid supplementation during pregnancy alters the hepatic transcriptome in adult male rats. Br J Nutr. 2010, 103 (12): 1711-9. 10.1017/S0007114509993795.PubMedView ArticleGoogle Scholar
  28. Morris TJ, Vickers M, Gluckman P, Gilmour S, Affara N: Transcriptional profiling of rats subjected to gestational undernourishment: implications for the developmental variations in metabolic traits. PLoS One. 2009, 4 (9): e7271-10.1371/journal.pone.0007271.PubMed CentralPubMedView ArticleGoogle Scholar
  29. Gluckman PD, Hanson MA, Morton SM, Pinal CS: Life-long echoes--a critical analysis of the developmental origins of adult disease model. Biol Neonate. 2005, 87 (2): 127-39. 10.1159/000082311.PubMedView ArticleGoogle Scholar
  30. McCarthy C, Cotter FE, McElwaine S, Twomey A, Mooney EE, Ryan F, Vaughan J: Altered gene expression patterns in intrauterine growth restriction: potential role of hypoxia. Am J Obstet Gynecol. 2007, 196 (1): 70.e1-6. 10.1016/j.ajog.2006.08.027.View ArticleGoogle Scholar
  31. Du K, Herzig S, Kulkarni RN, Montminy M: TRB3: a tribbles homolog that inhibits Akt/PKB activation by insulin in liver. Science. 2003, 300 (5625): 1574-7. 10.1126/science.1079817.PubMedView ArticleGoogle Scholar
  32. Hegedus Z, Czibula A, Kiss-Toth E: Tribbles: a family of kinase-like proteins with potent signalling regulatory function. Cell Signal. 2007, 19 (2): 238-50. 10.1016/j.cellsig.2006.06.010.PubMedView ArticleGoogle Scholar
  33. Godfrey KM, Lillycrop KA, Burdge GC, Gluckman PD, Hanson MA: Epigenetic mechanisms and the mismatch concept of the developmental origins of health and disease. Pediatr Res. 2007, 61: 5R-10R. 10.1203/pdr.0b013e318045bedb.PubMedView ArticleGoogle Scholar
  34. Rutter J, Michnoff CH, Harper SM, Gardner KH, McKnight SL: PAS kinase: an evolutionarily conserved PAS domain-regulated serine/threonine kinase. Proc Natl Acad Sci USA. 2001, 98 (16): 8991-6. 10.1073/pnas.161284798.PubMed CentralPubMedView ArticleGoogle Scholar
  35. Hao HX, Cardon CM, Swiatek W, Cooksey RC, Smith TL, Wilde J, Boudina S, Abel ED, McClain DA, Rutter J: PAS kinase is required for normal cellular energy balance. Proc Natl Acad Sci USA. 2007, 104 (39): 15466-71. 10.1073/pnas.0705407104.PubMed CentralPubMedView ArticleGoogle Scholar

Copyright

© Emerald et al; licensee BioMed Central Ltd. 2011

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.