Open Access

Development of a chicken 5 K microarray targeted towards immune function

  • Jacqueline Smith1Email author,
  • David Speed1,
  • Paul M Hocking1,
  • Richard T Talbot2,
  • Winfried GJ Degen3,
  • Virgil EJC Schijns3,
  • Elizabeth J Glass1 and
  • David W Burt1
BMC Genomics20067:49

DOI: 10.1186/1471-2164-7-49

Received: 17 November 2005

Accepted: 13 March 2006

Published: 13 March 2006

Abstract

Background

The development of microarray resources for the chicken is an important step in being able to profile gene expression changes occurring in birds in response to different challenges and stimuli. The creation of an immune-related array is highly valuable in determining the host immune response in relation to infection with a wide variety of bacterial and viral diseases.

Results

Here we report the development of chicken immune-related cDNA libraries and the subsequent construction of a microarray containing 5190 elements (in duplicate). Clones on the array originate from tissues known to contain high levels of cells related to the immune system, namely Bursa, Peyers patch, thymus and spleen. Represented on the array are genes that are known to cluster with existing chicken ESTs as well as genes that are unique to our libraries. Some of these genes have no known homologies and represent novel genes in the chicken collection. A series of reference genes (ie. genes of known immune function) are also present on the array. Functional annotation data is also provided for as many of the genes on the array as is possible.

Conclusion

Six new chicken immune cDNA libraries have been created and nearly 10,000 sequences submitted to GenBank [GenBank: AM063043-AM071350; AM071520-AM072286; AM075249-AM075607]. A 5 K immune-related array has been developed from these libraries. Individual clones and arrays are available from the ARK-Genomics resource centre.

Background

In recent years, the tools available to the field of chicken genomics have increased greatly. Detailed genetic and physical maps have been constructed [1], as well as BAC contig maps [2, 3] and a radiation hybrid panel [4]. There is also a substantial EST collection [5], SNP database and many full-length cDNAs have been sequenced. The development of these resources has culminated with the recent publication of the chicken draft sequence [6]. The chicken can now be regarded as an important model organism for use in comparative genomics, residing in a potentially informative position in the evolutionary ladder. The chicken is also an extremely useful model for developmental biologists and geneticists as well as being a commercially important species.

The latest tools being developed for the chicken are microarrays. There are several small tissue-specific arrays being used by individual labs. These include an intestinal array (3,072 clones) [7], a macrophage-specific array (4,906 clones) [8], a lymphocyte array (3,011 clones) [9] and an 11 K array based on genes found in heart progenitor cells [10]. A 13 K genome-wide array is also available from ARK-Genomics [11] (Roslin, UK) and from the Fred Hutchinson Cancer Research Centre (Seattle, USA) [12]. We have designed a 5 K immune-related array created from libraries developed from tissue (Bursa, spleen, Peyers patch, thymus) from birds which were previously inoculated with a combination of different vaccines to various common avian diseases including bacterial, protozoa and virus disease-causing organisms (E. coli, Newcastle Disease Virus (NDV), Infectious Bursal Disease Virus (IBDV), coccidiosis, Marek's Disease (MD) and salmonella). The tissues we chose are highly representative of T and B cell populations and were used in order to optimise the numbers of immunologically – related genes that would be present in our libraries. Many known immune genes that have been recently identified in the chicken EST collections [13] have also been added to the array. This array provides a valuable, cost-effective resource for the investigation of immunological gene expression. It has been created from a pool of stimulated immune tissues and contains genes that represent a wide spectrum of immune functions as well as previously unidentified sequences. Each gene on the array is also functionally annotated as much as possible. Gene ontology [14] data and Blast [15] information is provided for each clone, where that information is available.

Results and discussion

Construction of the array

Six immune-related libraries were specifically developed for the construction of a 5 K chicken array. Immune tissue from birds inoculated with different vaccine regimes (see Methods) was used to develop two standard libraries. These both underwent two rounds of normalization, thus providing us with six libraries. Initially, 10,173 clones were randomly chosen from the libraries for sequencing. The number chosen from each library depended on the titre (colonies/microlitre) of that particular library. The 10,173 clones that were sequenced were searched for poor quality sequence (<100 bp after removal of vector, repeats etc.) and unwanted Blast homologies, as described in the Methods section. The numbers of high quality sequences (9,434 – which have been submitted to Genbank) from each library are shown in Table 1. Cluster analysis was then undertaken, which resulted in the grouping of clones from which we would choose the 5,000 that were to be represented on the array.
Table 1

Clones sequenced from each library.

Library

No. of clones

Chicken immune 1 ('B cell' standard)

975

Chicken immune 2 ('B cell' normalized 1)

2,394

Chicken immune 3 ('B cell' normalized 2)

1,600

Chicken immune 4 ('T cell' standard)

2,563

Chicken immune 5 ('T cell' normalized 1)

918

Chicken immune 6 ('T cell' normalized 2)

984

Genes on the array

The clones on the array are derived from custom-made immune-related chicken cDNA libraries. Libraries developed from tissue from Bursa, spleen and Peyers patch were our representative 'B cell' libraries, and libraries developed from thymus were so-called 'T cell' libraries (the names 'B and T cell libraries' are used purely for ease of reference and in no way indicate that the libraries consist of pure cell populations). Clones from both standard and normalized libraries are present on the array. One clone representing each of the 3,811 clusters is included on the array, along with a random selection of singleton clones (1,067). The sequence of each of the clones was also subjected to a Blast search of the SwissProt and TREMBL databases and the highest hit to each sequence was reported. Searches were carried out at a stringency of 1e-10 (this relatively low stringency was to ensure that we identified as many immune homologies as possible). Chicken immune genes have a relatively low level of sequence conservation with mammals, hence the lower stringency used in these searches). We wanted to ensure that certain genes were also represented on the array as 'reference' genes. This included a range of known immune-related genes for which a clone was already available – either from the existing EST databases [12] or from our novel libraries. Various cytokines, chemokines, cell surface antigens, receptors and MHC molecules were all included (Table 2). The expression profile of genes of unknown function can thus be compared with the profiles of these genes whose roles are known. Standard array controls were also spotted on the array, including various spot report buffers (positive and negative controls for the Cy3 and Cy5 dyes), salmon sperm DNA, calf thymus DNA, bovine genomic DNA (negative controls), chicken genomic DNA, gamma actin and GAPDH (positive controls). Each clone is represented in duplicate.
Table 2

List of known immune genes added as reference genes to the array.

Gene

EST

Clone ID

Accession no.

AH221

CTN2_C0000858f10.q1kT7SCF

C0000858F10

AM064266

AH294/RANTES

603404971F1

C0000737M17

BU397782

β2 microglobulin

CTst_C0000869a17.q1kT7SCF

C0000869A17

AM068376

BAFF

CBN1_C0000466j11.q1kT7SCF

C0000467J11

AM066201

BMP10

604156553F1

C0003869J14

BU210183

BMP2

603213309F1

C0003763A3

BU444424

BMP4

603363891F1

C0000429F23

BU473912

BMP6

603604307F1

C0003811M1

BU287807

BMP7

603500540F1

C0000717O9

BU333004

BMP8A

603956728F1

603956728F1

BU425800

CC chemokine receptor 6

603508559F1

C0002794E15

BU267610

CC CKR 11

603367511F1

C0000439E3

BU465158

CC LARC/MIP-3A

603534015F1

C0002806N3

BU398190

cCAF

CBN1_C0000465h11.q1kT7SCF

C0000465H11

AM065832

CD135 antigen

603812446F1

C0001334K11

BU376898

CD137

pat.pk0038.d7.f

C0004737E4

AI980851

CD153

pat.pk0072.b5.f

C0004738K22

AI982035

CD154

603535227F1

C0001006F7

BU398104

CD18

CBN1_C0000468e11.q1kT7SCF

C0000468E11

AM066422

CD2

pgn1c.pk014.i9

pk014I9

CB017050

CD200

pat.pk0062.c8.f

C0004738C17

AI981679

CD226

pat.pk0020.d12

C0004739G22

AI980296

CD28

CTst_C0000892d20.q1kT7SCF

C0000892D20

AM070143

CD3

C0001679M3_G02_008.AB1

C0001679M3

AM070515

CD36

603543789F1

C0001028A23

BU311037

CD4

pk017a12

pk017a12

CB017654

CD40L

pgm2n.pk009.d11

pk009d11

BM488880

CD44-like

603745662F1

C0003894K15

BU253134

CD45

603767294F1

C0003827K23

BU446679

CD59

603212850F1

C0000363D13

BU447971

CD63 antigen

603783352F1

C0001268G14

BU243877

CD7

pat.pk0040.d6.f

C0004737K4

AI981043

CD79A

CBst_CHK02000039f07.q1kT7SCF

CHK0200003F7

AM071949

CD8

CTst_C0000877k01.q1kT7SCF

C0000877K1

AM069615

CD82

CTst_C0000892l24.q1kT7SCF

C0000892L24

AM070329

CD83 antigen

603771889F1

C0001238B24

BU457418

CD84

CTN1_C0000798o19.q1kT7SCF

C0000798O19

AM070961

CD98 light chain

CBN1_C0000465c24.q1kT7SCF

C0000465C24

AM065739

Chemokine receptor like 2

603764351F1

C0001219F13

BU444213

Chicken cytokine

pat.pk0050.e9.f

C0004737J11

AI981311

CHIR-A

603478533F1

C0003884A9

BU359209

CHIR-B

CBst_CHK02000039l03.q1kT7SCF

CHK0200003L3

AM072078

cMGF

pat.pk0060.h1.f

C0004737P22

AI981598

Complement C3

CBN1_C0000468j22.q1kT7SCF

C0000468J22

AM066546

Complement C4

603811612F1

C0001332G3

BU376477

Complement C7

603668434F1

C0001140D9

BU416108

Complement C8α

603782386F1

C000164L21

BU242118

complement H

603735023F1

C0001154N6

BU295434

complement receptor 1

603819479F1

C0001351N20

BU268132

Complement1

CBN2_C0000485f23.q1kT7SCF

C0000485F23

AM068133

Cremp

603114782F1

C0003743C21

BU126768

C-type lectin

HFU603551466C18

C0004763C18

AM063354

CX 3C chemokine receptor 1

603949695F1

C0003852N23

BU204148

CXC-R4

CTst_C0000878f17.q1kT7SCF

C0000878F17

AM069849

Cytokine like protein 17

603773283F1

C0001242E21

BU459791

Cytokine receptor like 9

603472805F1

C0000591J1

BU477689

Death receptor 6

CBN1_C0000466l11.q1kT7SCF

C0000467L11

AM066244

DSL-1

603321647F1

C0000418M11

BU239031

EMAP II

603364164F1

C0003776P16

BU475067

ephrin type A receptor 2

603121949F1

C0000241A13

BU133519

FAS antigen

603737578F1

C0001181L19

BU300974

FASL decoy receptor 3

CTN2_C0000856k13.q1kT7SCF

C0000856K13

AM064070

GATA-3

CTN2_C0000858a24.q1kT7SCF

C0000858A24

AM064179

GDF10

603530236F1

C0000994G10

BU351257

GDF8

603775823F1

C0001248N6

BU458566

GDF9

603741256F1

C0001166O13

BU300398

glycoprotein 130

603369157F1

C0002739A15

BU460413

GMCSF

CF258055

CF258055

CF258055

HCC1

pat.pk0059.g4.f

pk059g4

AW061438

ICSBP

603568552F1

C0001037G14

BU383423

IFNα

603486811F1

C0000622F3

BU319434

IFNα/β-R2

603783234F1

C0001268C9

BU243612

IFNγ

603766180F1

C0003825O20

BU444142

IFNγR2

603606133F1

C0001120B10

BU294744

IFP35

603123028F1

C0000243H7

BU135331

Ig light chain VJC region

C0000914E7_C03_018.AB1

C0000914E7

AM064528

Ig heavy chain VDJ region

603534767F1

C0002807F18

BU398082

IK cytokine

603368212F1

C0000440H3

BU460192

IL-10

CF258071

CF258071

CF258071

IL11 receptor

603402722F1

C0000518K5

BU250398

IL-12β

603603708F1

603603708F1

BU291084

IL12-p35

603761859F1

C0002846F16

BU474924

IL-13R2

603519773F1

C0000972A19

BU341330

IL-15

603102514F1

C0002655L4

BU202444

IL-16

603130176F1

C0002702H20

BU114872

IL17 receptor

603211483F1

C0000350E22

BU448712

IL-18

603508766F1

C0002794D18

BU271029

IL-1β

603217760F1

C0003766G15

BU455380

IL-2

pat.pk022.e2

pk022e2

AI980311

IL20 receptor

603591538F1

C0001088K9

BU241765

IL-2Rα

pat.pk0012.h3

pk0012h3

AI980106

IL-2Rγ

CBN1_C0000360j15.q1kT7SCF

C0000360J15

AM064841

IL-4

603772775F1

ChEST708f19

BU450270

Il-4R

603490820F1

603490820F1

BU324362

IL-6

pat.pk0076.f2.f

C0004739G21

AI982185

Interleukin enhancer binding factor 3

603322645F1

C0000420J12

BU239448

IRAK2

603831145F1

ChEST821j11

BU435261

IRAK4

603208981F1

ChEST185a21

BU441365

IRF1

603960463F1

C0002900N15

BU418343

IRF10

CBN1_C0000360l15.q1kT7SCF

C0000360L15

AM064884

IRF2

604146465F1

C0003862A18

BU438609

IRF3

CTst_C0000892j09.q1kT7SCF

C0000892J9

AM070266

IRF4

6O4_B10_077

C0000885O4

AM072251

IRF5

pat.pk0067.c5.f

pk067c5

AI981854

IRF6

603111427F1

C0000188F7

BU109331

JSC

CTst_C0000878m23.q1kT7SCF

C0000878M23

AM069996

K60

603470605F1

C0002774I2

BU479398

lymphotactin

603733847F1

C0001151N12

BU300469

MCSF1-receptor

603220574F1

C0000383C19

BU432910

MDV vIL-8

CBst_C0000222p17.q1kT7SCF

C0000222P17

AM071831

MHC class I

CBst_CHK02000039o05.q1kT7SCF

CHK0200003O5

AM072147

MHC class I minor

CTst_C0000873a15.q1kT7SCF

C0000873A15

AM068728

MHC class II beta

HFU603551341A11

C0004763A11

AM063247

MIF

604141521F1

C0001517I5

BU438017

MX

603775783F1

C0001248E22

BU457953

NKL

603539011F1

C0001016E4

BU309556

N-pac

604157079F1

604157079F1

BU210048

NRAMP1

pk013p5

pk013p5

BI394251

NRAMP2

603953027F1

C0001451E8

BU203948

OCIF

603157972F1

C0000333O17

BU410189

opioid receptor sigma 1

603341826F1

C0003775C8

BU254440

Orphan chemokine receptor

603234142F1

C0000403C12

BU418544

PIT54

603150061F1

C0000313I16

BU126277

platelet activating receptor

pat.pk0002.b12

C0004739A2

AI979750

PRC1

603475588F1

603475588F1

BU355757

prostaglandin synthase

CBN1_C0000466j02.q1kT7SCF

C0000467J2

AM066193

Regulator of cytokinesis 1

603475588F1

C0000598P22

BU355757

RING3

CBst_C0000222p04.q1kT7SCF

C0000222P4

AM071819

SCA-2

CTN1_C0000853f13.q1kT7SCF

C0000853F13

AM071100

SCYa13

603534566F1

603534566F1

BU397023

SCYA4

603742061F1

C0001168I15

BU299262

SIGIRR

603321436F1

C0002934H10

BU240159

SOCS1

603758706F1

C0003823K20/L1

BU218362

SOCS2

603322984F1

603322984F1

BU239208

SOCS5

603492126F1

C0000636C7

BU326390

STAT1

603957345F1

ChEST927i11

BU425993

STAT2

pat.pk0027.a6.f

C0004737C3

AI980571

STAT5b

CBst_C0000222j02.q1kT7SCF

C0000222J2

AM071688

TAP2

603732809F1

C0000758A3

BU298074

Tapasin

CTst_C0000873d22.q1kT7SCF

C0000873D22

AM068799

TARC

pat.pk0031.f10.f

C0004737K13

AI980713

T-bet

pgn1c.pk013.h8

pgn1cpk013.h8

CB016768

Tcell receptor α

CBst_CHK02000039p10.q1kT7SCF

CHK0200003P10

AM072172

Tcell receptor β

UEB603581072O18

C0004765O18

AM063532

Tcell receptor γ

CTst_C0000878m08.q1kT7SCF

C0000878M8

AM069981

Tcell receptor ζ

CTst_C0000874j17.q1kT7SCF

C0000874J17

AM069278

TGFβ

603758578F1

C0003823K20

BU215243

Thymosin beta 4

ODP603945810C04

C0004766C4

AM063804

TLR1/6/10

603760940F1

C0001211O10

BU471724

TLR2

603588755F1

C0001081M13

BU374739

TLR3

603781018F1

C0001261D6

BU242827

TLR4

603470778F1

C0002774L20

BU475859

TLR5

603230983F1

C0000395E22

BU420247

TLR7/8/9

603160284F2

C0002711G22

BU435893

TRAF1

pat.pk0072.d3.f

C0004738M6

AI982046

TRAF2

603217872F1

C0003766O18

BU455745

TRAF5

CTst_C0000877n08.q1kT7SCF

C0000877N8

AM069687

The genes in bold come from the immune libraries described in this paper

Analysis of the immune clones

All the sequences of the clones on the array were subject to Blast homology searches against the SwissProt and TREMBL databases using a cut-off value of 1e-10. Using this means of detection, many known immune-related molecules were identified, including cytokines, interferons, interleukins, transcription factors, receptors, cell differentiation antigens, MHC molecules and genes for proteins belonging to the TOLL receptor pathway. Proteins homologous to hypothetical human proteins and mouse cDNAs were also identified.

Sequences, which gave no Blast homology to anything in the nucleotide or protein databases, accounted for about 38% of the clones. Either the search parameters were too stringent to identify these genes or the chicken sequence was sufficiently divergent to be undetectable in a standard Blast search. This is a common feature of immune-related genes, and it is often very difficult to identify such genes by sequence homology to mammalian homologues. Some of these sequences may also represent non-conserved 3' UTR regions of genes. This set of clones may also include genes that have never been identified before and are not represented in the sequence databases. Further, more detailed analysis of these sequences can sometimes help elucidate the nature of the gene in question. Protein sequences can be predicted from the EST nucleotide sequence using programs such as ESTscan [[16] and [17]], which takes in to account sequencing errors and thus potential frame-shift mutations which are often present when there is only one EST sequence available for study. Conserved motifs and domains can then sometimes be identified for example, using the Pfam database [18], which is a large collection of multiple sequence alignments and hidden Markov models covering many common protein domains and families. PSI-Blast searches can also help identify to which type of family a gene will belong.

During clustering analysis, our 10,000 immune sequences were aligned with 398,000 existing chicken ESTs. This highlighted 3,845 clusters that contained one or more sequence from our immune libraries and 1,959 singleton clones. This analysis also identified 40 novel clusters that only contained sequences from our new libraries. Upon Blast analysis, 7 of these clusters were found to represent known chicken genes (initially appearing unique as they aligned to a different part of the gene sequence from existing ESTs), 18 showed homology to genes in other species and 15 clusters proved to have no known homology to anything currently in the databases. At the time, we searched against 398,000 existing chicken ESTs. Now however, there are currently 550,510 chicken ESTs in the databases (dbEST release 080505). A current search has shown that 9 of our sequences are indeed still unique to our libraries and have no known identifiable homologue, although two of the sequences do show some similarity to two predicted chicken sequences (AM065333 and the hypothetical protein XP_429359; AM065802 and the predicted P114-RHO-GEF protein XP_418249). Eight of these sequences are identifiable in the whole genome sequence, as shown in Table 3.
Table 3

Genomic location of unique chicken ESTs as identified by the University of Santa Cruz Blat site http://genome.ucsc.edu/cgi-bin/hgBlat?command=start

Clone

GenBank Accession No.

Genomic location

CBN1_C0000465p01.q1kT7

AM065989

chr15: 5562143–5562781

CBN1_C0000464a07.q1kT7

AM065333

chr11_random: 637442–638117

CBN1_C0000465g01.q1kT7

AM065802

chr28: 3396525–3399444

CBN2_C0000485f09.q1kT7SCF

AM068122

chr7: 1319368–1319989

CBst_C0000222i16.q1kT7SCF

AM071684

no hit

CTN2_C0000856o09.q1kT7

AM064132

chr17: 9342673–9343272

CBN1_C0000360j04.q1kT7

AM064831

chr21: 2494538–2494813

CBN1_C0000360n18.q1kT7

AM064932

chr1: 172893324–172893990

CBN1_C0000463a02.q1kT7

AM064982

chr4: 50741781–50742197

Gene ontology (GO) annotations

In order to try and elucidate the function of the genes on the array further, we tried to assign as much annotation to the sequences as possible. GO annotations were assigned to some sequences after searching the GGI and UMIST databases [19], while other annotation was derived from hits to orthologous human sequences from the ENSEMBL [20] and GENSCAN [21] databases, as described in the 'methods' section. Having annotation derived from orthologous human genes means that cross-species comparisons between chicken and human array data may be possible. A search of the ENSEMBL database provided information on 2,292 GO-term associations, the GGGI database 1,542 and GENSCAN 566, while the UMIST full-length cDNA database provided a further 365 annotations. The sequences on the array cover a total of 227 GO terms, with 73% of all the sequences having at least one GO entry assigned to it. The available annotation for the array sequences is broken down as follows: 52% of genes have a 'cellular component' term assigned, 60% have 'molecular function' and 56% of sequences have the 'biological process' described. 83% of all the genes on the array have some kind of gene description and after searching each sequence against the sequences in the Ensembl chicken genome collection (July 2005 genebuild [22]), 78% of sequences were found to have a known chromosomal location. Now that all these sequences have been added to GenBank and thus have an accession number which can be directly linked into the ENSEMBL databases (work currently underway), obtaining comprehensive, up-to-date annotation data will become much easier.

A file showing the complete annotation for all the sequences on the array is available as supplementary material (Additional file 1). However, Additional file 2 provides an overview of the broad functional classes that are represented by the genes on the array. These are based on more general GO annotations derived from the GO-slims database at EBI, and allow us an insight into the different classes of genes present on the array without having to look at detailed functional annotation for each individual gene.

Annotation is also available for some (9,137) of the ESTs in the UMIST collection. By comparing the relevant GO slims [23] terms for the sequences in this collection with those present on our array, we are able to see which types of genes appear to be enriched in our set, compared with a larger, more general collection of EST sequences. As can be seen (shown in bold) in Additional file 2, certain classes of gene appear to be more highly represented. For instance, genes involved in protein transport are more abundant in our set of clones, as are those involved in the response to stimulus. This is consistent with our attempts to pre-select for higher numbers of genes involved in the immune system.

Quality of the array

To assess the quality of the array, various hybridization comparisons were undertaken. Three different conditions were addressed: 1). self v self 2). biological replicate A v biological replicate B and 3). Control sample v activated sample. Dye swap experiments were also carried out for conditions 2 and 3. The 'self' sample was a reference RNA consisting of a pool of various chicken lung samples. The biological replicates were lung samples from two 6-week-old chickens that had not been treated or challenged in any way. In the third group of hybridisations, the 'control' sample was from a similarly, untreated bird and the 'activated' sample was obtained from the lungs of a bird that had been challenged with the avian influenza strain H9N2 five days previously. The graphs in Fig 1 show the tight correlation between self/self (R2 = 0.9273) and between replicates (R2 = 0.8766), whereas a much higher level of variance is seen when an activated sample is compared against a control (R2 = 0.7601).
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-7-49/MediaObjects/12864_2005_Article_432_Fig1_HTML.jpg
Figure 1

Scatter plots showing the variance between A). self/self hybridisation B). two biological replicates and C). a control sample compared with an activated sample. Very little spread is seen with the self/self hybridisation and between the two replicates, as would be expected. However, differences in gene expression can be seen between the activated and control samples.

The boxplots in Fig 2 also demonstrate the differing variances between the comparisons. The greatest variance is shown for the activated animals compared with the controls as would be expected. Regression analysis for each of the data sets confirm the increased variance with correlation coefficients of r = 0.872 for activated samples, r = 0.936 for replicate samples and r = 0.963 for self/self sample data sets.
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-7-49/MediaObjects/12864_2005_Article_432_Fig2_HTML.jpg
Figure 2

Box plots showing the variance between self/self hybridisation, two biological replicates and a control sample compared with an activated sample. Boxes represent the interquartile range from 25–75%, with the median marked. Outliers to this range are also shown.

Using the array

This array is available from the Ark-Genomics resource facility at Roslin Institute, providing an immune-focused array which, for anyone interested in immune-research, offers a much more cost-effective and time-saving platform for gene expression experiments, instead of using the large oligo arrays which have thousands more genes, many of which will be of no interest. Analysis of data is also thus much easier and far less time-consuming. Information on the array has been deposited in ArrayExpress (Accession: A-MEXP-307) [[24] and [25]] (Additional file 1) and very soon all the sequences will be submitted to the Ensembl database with links to all the GO annotation information in the GOA database [26].

Conclusion

We have constructed a 5 K chicken cDNA microarray, which is highly selected for genes expressed in tissues which have an immune function. This targeted array contains enough widely-expressed genes (whose expression won't be changing) to enable good normalization, as well as containing numerous known immune genes (from our novel libraries and from existing EST collections). The array also contains many genes with as yet unknown homology and function as well as a few novel genes which are specific to the libraries from which the array was created. These genes of unknown function could well have a role in either the adaptive or innate immune response, and thus provide a valuable resource for analysis of gene expression changes occurring in birds that have been subject to immune challenge. The array has been proven to provide highly reproducible results and is now available to the chicken/microarray community as a whole.

Methods

Sample collection

Eight groups of 38 chickens (3-week-old) were vaccinated with two different vaccine regimes. The eight groups were males and females of a commercial line of hybrid broiler (Ross 306, Aviagen, Newbridge, Midlothian, UK) and layer (Lohman Brown, Lohmann Tierzucht, Cuxhaven Germany) chicks given one of the two vaccination schemes. Group 1 were given vaccines for E. coli (0.5 ml in left breast muscle), ND and IBDV (0.5 ml in right breast muscle) formulated in alum-gel and oil-based immuno-potentiators. Intramuscular injections were given to ensure that all the birds were given an equal dose. Group 2 vaccines consisted of Paracox 8 [Eimeria sp.] (0.1 ml in drinking water), Nobilis Rismavac-CA126 [MD] (0.2 ml intramuscularly in leg) and Salenovac [S. enteritidis] (0.5 ml intramuscularly in leg). Tissue samples were obtained (unvaccinated); 5 hr, 24 hr, 72 hr and 7 days post vaccination. Samples from groups of 5 birds were pooled. Tissues collected were Bursa, spleen, Peyers patch and thymus. Tissue from Bursa, spleen and Peyers patch were pooled to make the 'B-cell' libraries and the thymus tissue was used to construct the 'T-cell' libraries. The tissues and time points chosen were in order to try and maximise the number of immune-related transcripts, including those which may only be expressed transiently. All experimental protocols were authorized under the UK Animals (Scientific Procedures) Act, 1986.

Library construction

Six libraries were constructed at Incyte Genomics (Palo Alto, CA): a standard and 2 normalized Bursa/spleen/Peyers patch libraries and a standard and 2 normalized thymus libraries. cDNA synthesis was initiated using an oligo (dT) primer, using methylated C in the first strand synthesis reaction. Following this first strand reaction, double-stranded cDNA was blunted, ligated to NotI adapters, digested with EcoRI, size-selected, and cloned into the NotI and EcoRI compatible sites of a custom modified MCS of the pBluescript (KS+) vector. Normalization was done in two rounds using conditions adapted from [[27] and [28]] except that a significantly longer re-annealing hybridization was used. Around 10,000 clones were then sequenced at the Sanger Institute according to their protocols. Using the T7 primer, sequence was generated from the 5' end of each clone by the dideoxy chain termination method using an ABI 3700 sequence analyser (Applied Biosystems, Foster City, CA).

EST sequence analysis

Bioinformatic analysis commenced with 10,173 sequences. After eliminating poor quality sequence and repeats, 9,434 of these sequences remained after screening with phred [29], RepeatMasker [30], Crossmatch [31] and XNUN [32]. Certain unwanted sequences were then identified after using the Blast algorithm [[33] and [34]] and screening the results for specific keywords. These included 'ribosomal', 'mitochondrial', 'Newcastle', 'Mareks', 'Eimeria', 'Salmonella' and 'E. coli'. 8,154 sequences passed these criteria. These sequences were then clustered against the existing UMIST and EMBL chicken EST sequences using TIGR's clustering tool, tgicl [35]. This resulted in 3,845 clusters which contained one or more sequence from our libraries and 1,959 singletons. The following clones were chosen for inclusion on the array: 3,770 cluster representatives, 1,067 singletons and 157 reference immune genes: 93 clones from the UMIST collection, 41 from our immune libraries, 21 clones from the Delaware set [36] and 2 clones courtesy of R. Zoorob (CNRS, France) (Table 2).

Construction of the array

The immune array was constructed from 4994 chicken EST clones plus 196 control elements (landing lights (positional controls), GAPDH, gamma actin, salmon sperm DNA, calf thymus DNA, chicken and bovine genomic DNA and a variety of spotting buffers). Plasmid DNA was prepared using MagAttract 96 Miniprep chemistry on a Biorobot 8000 platform (Qiagen Ltd., Crawley, UK), and the cDNA inserts were amplified using CGATTAAGTTGGGTAACGC (fwd) and CAATTTCACACAGGAAACAG (rev) in 50 ul reactions using 1 ul of DNA as a template. Amplified DNA was purified by Multiscreen 384 well PCR purification plates (Millipore, Watford, UK) on a Multiprobe II liquid handling platform (Perkin Elmer, Beaconsfield, UK) and the reactions confirmed by agarose gel electrophoresis and quantified by Picogreen assay (Molecular Probes, Invitrogen, Paisley, UK) on a Flouroskan Ascent flourescent plate reader (Thermo Life Science, Basingstoke, UK). DNA was resuspended to 150 ng/ul in spot buffer (150 mM Sodium phosphate, 0.01% SDS) before being spotted in duplicate on to amino-silane coated slides (CMT-GAPSII, Corning, Schiphol-Rijk, The Netherlands) using a Biorobotics MicroGrid II spotter (Genomic Solutions, Huntingdon, UK). Slides were then treated using succinic anhydride and 1-methyl-2-pyrrolidinone (Sigma, Poole, UK) to block unbound amino groups, followed by a wash in 95°C MilliQ water before hybridisation.

RNA preparation and labelling

Total RNA was isolated from lung tissue using a Trizol extraction according to the manufacturer's protocol (Invitrogen, Paisley, UK) and subsequently purified using the RNeasy Midi RNA Purification kit (Qiagen Ltd., Crawley, UK). RNA concentration was determined spectrophotometrically and RNA quality was determined using an Agilent 2100 Bioanalyser (Agilent Technologies, Waldbronn, Germany). Cy3 or Cy5 was incorporated into each sample using the Fairplay labelling kit (Stratagene, La Jolla, CA) and the labelled cDNA cleaned-up after passage through DyeEx columns (Qiagen Ltd., Crawley, UK). Labelling efficiency was determined by running 0.5 μl of each sample on a 1% agarose gel and measuring the intensity of fluorescence on a GeneTac LS IV scanner (Genomic Solutions, Huntingdon, UK).

Hybridizations

Microarray hybridizations were carried out overnight using a GeneTAC automated hybridization system [37] (Genomic Solutions, Huntingdon, UK). Hybridizations (125 μl) were carried out in Genomic Solutions hybridization solution (Cat. no. RP#0025) in a stepped hybridization: 55°C for 3 hr, 50°C for 3 hr and then 45°C for 12 hr. Slides were then washed in Genomic Solutions wash buffers (Cat. nos. CS#0038, CS#0039 and CS#0040). Upon removal from the hybridization stations, slides were washed for 1 min in Post-Wash buffer (CS#0040) and a further minute in isopropanol, followed by centrifugation at 1000 rpm for 6 min. Dried slides were scanned in a Scanarray 5000 scanner (GSI Lumonics, Rugby, UK) fitted with Cy3 and Cy5 filters.

Data analysis

To indicate the suitability of the new array to discriminate the differences in the experimental treatments, hybridizations comparing samples with controls and controls with controls were performed. Control (vehicle treated) animals were compared with immunologically challenged animals (activated slides) and control animals were also compared with other control individuals (replicate slides). The same animal was also compared with itself (self/self). Each comparison was completed in duplicate and with a dye flip. Dye-swaps are carried out in order to deal with any residual dye-bias remaining after labelling. However, this is generally not a problem, due to the indirect labelling method employed. Data was extracted from the slide using Bluefuse software (BlueGnome, Cambridge, UK). Features with poor confidence information (confidence <0.30, flagged D and E) were eliminated from the analysis. M v A plots [where M = log2 (Cy5/Cy3) and A = 1/2*(log2(Cy5) + log2(Cy3)] of the data for each slide (data not shown) were suitably linear to require only a simple global normalisation of the data. Data from slides of similar treatments was pooled and a boxplot produced for each comparison (Genstat v8.1, VSN International Ltd., Hemel Hempstead, Herts, UK).

Databases and sequence sources

Ensembl and Genscan predicted genes/peptide sequences for the chicken genome assembly (March 2004) were downloaded from the Ensembl database using Ensmart or the UCSC table browser [38]. Chicken EST sequences were downloaded from the TIGR Gallus gallus gene index (GGGI) [release 10.0] [[39] and [40]]. Chicken full-length cDNA sequences were downloaded from the UMIST www site (Sept 2004). Ensembl predicted peptide sequences for the human genome assembly (May 2004) were downloaded from the Ensembl database using Ensmart or the UCSC table browser.

Mapping array probes to chicken ESTs, cDNAs, genes and genome

Unique ESTs used to create the immune array were mapped to chicken cDNAs, ESTs, genes or the chicken genome assembly using NCBI Blastn (version 2.2.11). Identity was defined with > 95% sequence identity over 100-bp and then taking the top-scoring match to each EST to provide a unique sequence assignment. All repeats and low-complexity sequences were masked using RepeatMasker (version 3.1.0).

Definition of Gene Ontology terms and Gene Descriptions for array probes

Gene Ontology (GO) annotations [41] were all based on database hits in sequence similarity searches using Blastn. GO annotations were automatically transferred from these database records to the array probe entries. GO annotations were available for GGGI and UMIST EST/cDNA sequences. For chicken Ensembl or Genscan gene predictions, GO annotations were based on orthologous human peptide sequences. Orthologues were defined based on two cycles of Blastp between human and chicken proteins. An E_value cut off of less than 10-4, with the subject and query databases swapped between runs. By comparing E_values mutually best proteins pairs were selected as orthologues. When E_values were equal, bits score and sequence coverage were used as tiebreakers to select the top hit. For each array probe associated GO terms and a unique gene description was transferred from the orthologous database record. Finally a Perl script was used to create a non-redundant set of probe to GO records.

Frequency of GO and GO-Slim terms

GO terms (version 3.2.16) were downloaded from the Gene Ontology www site. More general GO terms were assigned using GoaSlim_map (June 2005) available from the GOA www site at EBI. The GO-Slim terms allowed us to estimate e.g. the frequency of array probes associated with the biological process Metabolism (GO:0008152).

Data processing

Perl scripts (version 5.8.5) and SQL were used throughout to manipulate and filter data sets.

Declarations

Acknowledgements

The authors would like to thank Incyte Genomics (|Palo Alto, CA) for construction of the normalized cDNA libraries and The Wellcome Trust Sanger Institute (Hinxton, UK) for sequencing 10,000 cDNA clones from the libraries. Thanks also to Frazer Murray of ARK-Genomics (Roslin) for invaluable technical assistance and to Theo Jansen (Intervet International B.V., Boxmeer, The Netherlands) for the preparation of the vaccine formulations. This project was funded by Intervet International B.V, Boxmeer, The Netherlands, the Biotechnology and Biological Science Research Council (BBSRC) and partly by a BSIK VIRGO consortium grant, the Netherlands (grant nr. 03012).

Authors’ Affiliations

(1)
Division of Genetics and Genomics, Roslin Institute, Roslin (Edinburgh)
(2)
Ark-Genomics, Roslin Institute, Roslin (Edinburgh)
(3)
Intervet International B.V., Dept. of Vaccine Technology and Immunology R&D

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Copyright

© Smith et al; licensee BioMed Central Ltd. 2006

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.

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