Open Access

Non-synonymous genetic variation in exonic regions of canine Toll-like receptors

  • Anna Cuscó1, 2,
  • Armand Sánchez1,
  • Laura Altet2,
  • Lluís Ferrer3 and
  • Olga Francino1Email author
Canine Genetics and Epidemiology20141:11

https://doi.org/10.1186/2052-6687-1-11

Received: 6 June 2014

Accepted: 23 September 2014

Published: 22 October 2014

Abstract

Background

Toll-like receptors (TLRs) are pattern recognition receptors (PRRs) considered to be the primary sensors of pathogens in innate immunity. Genetic variants could be associated to differences in breed innate immune response to pathogens and thus to susceptibility to infections or autoimmune diseases. There is therefore great interest in the characterization of canine TLRs.

Results

Polymorphisms in canine TLRs have been characterized by massive sequencing after enrichment of their exonic regions. DNAs from 335 dogs (seven different breeds) and 100 wolves (two different populations) were used in pools. The ratio of SNP discovery was 76.5% (in relation to CanFam 3.1); 155 out of 204 variants identified were new. Functional annotation identified 64 non-synonymous variants (43 new), 73 synonymous variants (56 new) and 67 modifier variants (57 new). 12 out of 64 non-synonymous variants are breed or wolf specific. TLR5 has been found to be the most polymorphic among canine TLRs. Finally, a TaqMan OpenArray® plate containing 64 SNPs with a possible functional effect in the protein (4 frameshifts and 60 non-synonymous codons) has been designed and validated.

Conclusions

Non-synonymous genetic variation has been characterized in exonic regions of canine Toll-like Receptors. The TaqMan OpenArray® plate developed to capture the individual variability that affects protein function will allow high-throughput genotyping either to study association to infection susceptibility or even TLR evolution in the canine genome.

Keywords

TLRs Toll-like receptor Polymorphism SNPs Non-synonymous SNPs Canine Dog Innate immunity

Lay summary

Toll-like receptors (TLRs) are pattern recognition receptors (PRRs) and are the primary sensors of pathogens in the body. Genetic variants could be associated with differences in breed response to pathogens and also to susceptibility to infections and/or autoimmune diseases. There is great interest in the characterization of canine TLRs.

Genetic variation in canine TLRs has been characterized using massive parallel sequencing. DNA from 335 dogs (seven breeds: Beagle, German Shepherd dog, Yorkshire terrier, French bulldog, Boxer, Labrador and Shar Pei) plus 100 wolves (two populations: Iberian and Russian) were sequenced in 16 pools of 25 dogs or 50 wolves. In total, we found 204 variants, of which 155 were new. Comparison of these variants with the published dog genome sequence (called CanFam 3.1) Functional annotation identified 64 non-synonymous variants (43 new), 73 synonymous variants (56 new) and 67 modifier variants (57 new). Twelve of 64 non-synonymous variants were breed or wolf specific. TLR5 has been found to be the most polymorphic among canine TLRs. Finally, a TaqMan OpenArray(R) plate containing 64 SNPs with a possible functional effect in the protein (4 frameshifts and 60 non-synonymous codons) has been designed and validated.

Non-synonymous genetic variation has been characterized in exonic regions of canine Toll-like Receptors. The TaqMan OpenArray(R) plate developed to capture the individual variability that affects protein function will allow high-throughput genotyping either to study association to infection susceptibility or even TLR evolution in the canine genome.

Background

Toll-like receptors (TLRs) are the most widely studied pattern recognition receptors (PRRs) and are considered to be the primary sensors of pathogens in innate immunity. These molecules are constituted by leucine-rich repeat (LRR) domains, a unique intramembrane domain and a Toll/Interleukin-1 receptor (TIR) domain. Pathogen-associated molecular Patterns (PAMPs) are sensed through LRR domain, and signals are transduced through TIR domain, which is always located in the cytoplasm, in order to activate innate immunity response (for a review, see [1]).

Ten TLRs have been identified in dogs. TLRs can be classified into groups, depending on the PAMPs detected and their cellular location. TLR 1, 2, 4, 5 and 6 detect pathogen extracellular components. TLRs 3, 7, 8 and 9 target nucleic acids. The ligand for TLR10 is unknown [2].

Another way to classify TLRs is their cellular location. TLRs 1, 5, 6 and 10 are expressed at the cell surface and mainly recognize bacterial products. On the other hand, TLRs 3, 7, 8 and 9 are located almost exclusively in intracellular compartments and are specialized in recognition of nucleic acids, with self versus non-self discrimination provided by the exclusive localization of the ligands rather than their different molecular structure from that of the host. TLRs 2 and 4 can be located both on the cell surface and intracellular [2, 3]. In this study, TLRs will be divided in two groups: TLRs 1, 2, 4, 5, 6 and 10 as extracellular TLRs and TLRs 3, 7, 8 and 9 as intracellular TLRs and nucleic acid sensors.

TLRs are conserved through evolution, from Drosophila to mammals (reviewed at [4]), because of its essential role in innate immunity. However, there are significant distinctions between intracellular and extracellular TLRs. Intracellular TLRs do not accept much variability, because they have evolved under strong purifying selection [5]. Viruses can only be detected through their nucleic acids; therefore intracellular TLRs have an essential non-redundant role in host survival. Moreover, mutations in those TLRs could end up with an autoimmune disease against own nucleic acids or with high susceptibility to some viral infections. On the other hand, membrane or extracellular TLRs have evolved under less evolutionary pressure, due to they can recognize one pathogen through different PAMPs (immunological redundancy). So they show a higher rate of damaging non-synonymous and STOP mutations.

Although infective pressure that has reached these molecules is one of the main mechanisms of evolution, it is not the only one. Non-adaptative evolution has also an important role, through genetic drift, bottlenecks and migratory routes [6]. This kind of evolution should be seen in dogs, due to a first bottleneck with domestication and a second one for the artificial selection of breeds [7]. For these reason it should be taken into account the need for dealing with different breeds, and even with the wolf, for the analysis of canine TLR polymorphism.

In humans, many studies are addressed to find out possible links between some TLR polymorphism and susceptibility or resistance to disease (for a review see [6]). Some genetic variants in TLRs in dogs could be associated to differences in breed innate immune response to pathogens and thus to susceptibility to infections or autoimmune diseases. So far, polymorphisms in TLR4 and TLR5 have been associated with Inflammatory Bowel disease (IBD) in German Shepherd dogs (GSD) [8], but only protective SNPs from TLR5 have been associated with IBD in other 38 dog breeds [9] There is therefore great interest in the characterization of canine TLRs. TLR5 risk-associated haplotype for canine IBD confers hyper-responsiveness to flagellin [10]. Moreover, dogs with spontaneous IBD exhibit alterations in the enteric microbiota, which bear resemblance to dysbiosis reported in humans with chronic intestinal inflammation [11].

Although no other polymorphisms have been associated to illness in dogs until date, some studies have reported differential expression of some TLRs related to inflammatory or infectious diseases, such as TLR2 in IBD [12], TLRs 2, 4, 5 and 9 in chronic enteropathies in German Shepherd [13, 14]; TLR4 in osteoarthritis [15] and in infected canine endometrium [16]; TLRs 1-4, 6-10 in sino-nasal aspergillosis and idiopathic lymphoplasmacytic rhinitis [17]; and TLR2 and TLR9 in Leishmania infected dogs [18, 19].

So our aim is the analysis of genetic variation in exonic regions of canine TLRs by massive sequencing, focusing in non-synonymous substitutions and their segregation in different dog breeds and wolf populations. A second objective is to design and validate a TaqMan OpenArray® plate of SNPs with a possible functional effect in the protein (STOP, frameshift and non-synonymous codons). High-throughput genotyping of canine TLRs with this TaqMan OpenArray® plate will allow studying the association of non-synonymous variants with individual differences in immune response, their relationship with either the commensal or the disease associated microbiota and TLR evolution in the canine genome.

Results

We have identified 156 new variants in canine TLRs by massive sequencing after the enrichment of exonic regions. DNAs from 335 dogs (seven breeds) and 100 wolves (two populations) were pooled in 16 pools and sequenced in 2 lanes of Illumina Hiseq, with a mean coverage value of 15,162.23. Dog breeds included were Beagle, Labrador, German Shepherd, Yorkshire, French Bulldog, Boxer and Shar Pei. Wolves included were Iberian (Canis lupus signatus) and Russian (European grey wolf, Canis lupus lupus). A total of 204 variants were detected: 193 SNP and 11 insertions or deletions (1 to 18 bases). Only one of the indels (insertion/deletion) mapped to an exonic region (TLR7 3′ UTR), meanwhile the others were mapping to intronic regions (5 out of 11) and intergenic regions upstream or downstream a TLR gene (5 out of 11). The SNPs identified were classified by functional annotation from ENSEMBL [20] (effect and effect impact): 73 synonymous variants, 64 non-synonymous variants and 67 modifier variants which include intergenic (upstream and downstream a TLR gene), intronic and 3′ UTR (untranslated region) variants (see Table 1). None of the variants detected in the pools analyzed had a high effect (STOP codon, frameshift mutation or splicing) on the protein function. The ratio of SNP discovery was 76.5% (in relation to CanFam 3.1); 156 out of 204 variants identified were new: 43/64 non-synonymous variants (nsSNP), 56/73 synonymous variants (synSNP) and 57/67 modifier variants.
Table 1

Variants detected in canine TLRs by massive sequencing

  

Extracellular TLRs

Intracellular TLRs

 

Effect impact

SNP effect

TLR1

TLR2

TLR4

TLR5

TLR6

TLR10

TLR3

TLR7

TLR8

TLR9

Total

Low

Syn coding

2

5

4

28

2

5

6

6

8

7

73

Moderate

Non-syn coding

4

3

12

23

4

3

1

3

4

7

64

Total coding SNP (cSNP)

6

8

16

51

6

8

7

9

12

14

137

Modifier

Downstream

1

4

0

0

2

3

0

0

2

1

12

 

Intron

0

0

6

3

0

0

10

7

0

2

28

 

Upstream

0

6

0

0

2

1

1

1

1

0

12

 

UTR 3′

0

0

4

0

0

0

0

10

0

0

14

Total non coding SNP (ncSNP)

1

10

10

3

4

4

11

18

3

3

66

Total SNP

7

18

26

54

10

12

18

27

15

17

204

Variants are classified according to their effect on the protein and their spread along cell surface or intracellular TLRs.

Genetic variation differs among all TLRs. Variants detected in either extracellular or intracellular canine TLRs by massive sequencing and its classification according their effect in the protein are shown in Table 1. TLR5 gene presents the highest polymorphism, with 28 synonymous changes and 23 non-synonymous changes (Additional file 1, Table 1), although it also codifies for the longest annotated protein (1422 aminoacids).

Table 2 shows the aminoacid (AA) change ratio, which are AA changes caused by nsSNPs or frameshift mutations divided by total number AA for each one of the TLRs. The AA change ratio confirms that indeed TLR5 and TLR4 are the most polymorphic ones. On the other hand, TLR3 seem to be the most conserved receptor, just presenting one AA change in 905 AA.
Table 2

Total number of variants affecting protein in extracellular and intracellular TLRs

Canine gene

ENSEMBL protein ID

Protein length (aa)

AA change ratio a

Extracellular TLRs

   

TLR1

ENSCAFP00000032660

790

1/113

TLR2

ENSCAFP00000012269

785

1/196

TLR4

ENSCAFP00000031395

833

1/69

TLR5

ENSCAFP00000016726

1422

1/53

TLR6

ENSCAFP00000023836

797

1/199

TLR10

ENSCAFP00000023840

807

1/269

Intracellular TLRs

   

TLR3

ENSCAFP00000011004

905

1/905

TLR7

ENSCAFP00000017193

1121

1/374

TLR8

ENSCAFP00000031505

1038

1/260

TLR9

ENSCAFP00000030804

1032

1/129

Variants from CanFam 3.1 have been added to variants identified by massive sequencing in this table. aAA change ratio: aminoacid changes caused by nsSNPs or frameshift mutations divided by the length of the protein in aminoacids.

Non-synonymous SNPs

A more exhaustive analysis was performed for the 64 nsSNP detected through massive sequencing, because they are expected to have a greater effect on the protein function. First, a glimpse on allelic frequencies of the nsSNP was performed. The frequencies of the alternative allele for all 64 nsSNPs are shown for each breed and wolf pools in Additional file 2.

Allelic frequencies for alternative variants in nsSNPs differ among breeds. Beagle and Russian wolf are the most variable pools, with 35 out of 64 nsSNPs segregating. Some of the variants identified are breed-specific (8 out of 64) or wolf-specific (4 out of 64). Most of the breed specific variants are found in TLR5 and TLR4, which as seen before, are the most polymorphic TLRs. German Shepherd dogs (GSD) and wolf share 3 nsSNPs, all located in TLR4. The same happens with Shar Pei and wolf, they share 3 nsSNPs located in TLR2, TLR5 and TLR6.

SNPs with a MAF (Minor allele frequency) <0.05 have been considered to be fixed in the cohort [21]. Usually it is the reference allele the one which is fixed, but in some cases (perhaps due to bad annotation of the SNP) is the alternative one. Iberian wolves’ cohort is the one with more fixed variants, with only 24 out of 64 that are segregating, followed by Yorkshire and Boxer, with 25 out of 64 segregating variants.

Predicted impact of canine TLRs amino acid substitutions

Polyphen-2 [22, 23], SIFT [24, 25], and PROVEAN [26, 27] tools were used in order to predict the effect of each nsSNP in the protein structure. Each of these tools uses a different algorithm to predict the consequence of the aminoacid change on the protein and classifies it as benign/tolerated/neutral or damaging/affect protein function/ deleterious (for more detail, see Methods). 28 out of 64 nsSNPs were predicted to have an effect on the protein structure by at least one of the tools used (Table 3). When frequency of the alternative variant was high for all the cohorts tested, the alternative allele was exchanged with the reference allele in ENSEMBL sequences [20] in order to perform the Polyphen-2 analysis with the less frequent variant as the “alternative variant”. Therefore, SNPs with frequencies greater than 0.25 for the alternative allele were tested also for the annotated reference allele. Then, 3 more SNPs were predicted to affect the protein structure (indicated as reference on the column dbSNP ID in Table 3). When considering also these ones, 31 out of 64 nsSNPs (48%) were predicted to have an impact on the protein structure. Results from Polyphen-2, SIFT and PROVEAN were convergent in predicting damaging effects for 8 out of 31 nsSNPs (27%). On the other hand, 6 out of 64 nsSNPs were not correctly predicted, giving unknown or low confidence results, because they were not aligning to enough similar sequences to give a reliable result. Curiously most of this nsSNPs were located on the N-terminal region of TLR5.
Table 3

Non-synonymous SNPs predicted to impact protein function either by Polyphen-2, SIFT or PROVEAN

Canine gene

Position

SNP

dbSNP ID

AA Subst

Protein domain a

Polyphen-2 result

SIFT result

Provean result

Variant freq (dog) b

Variant freq (wolf) b

EXTRACELLULAR TLRs

TLR1

3:73542337

G/T

rs23585044

S29I

ncp

Pos. damaging

Tolerated

Neutral

0,36

0,77

 

3:73543092

T/G

new

S281A

ncp

Pos. damaging

Tolerated

Neutral

0,06

0,00

 

3:73543825

C/T

new

A525V

LRRCT2

Pos. damaging

Tolerated

Deleterious

0

0,11

TLR2

15:51463020

C/A

rs22410121

S46Y

ncp

Pos. damaging

Tolerated

Neutral

0,10

0,00

 

15:51464430

C/T

new

S516L

ncp

Prob. damaging

Aff. function

Deleterious

0,14

0

TLR3

16:44623632

C/G

new

E176D

ncp

Pos. damaging

Tolerated

Neutral

0,16

0,12

TLR4

11:71356420

C/T

reference1

A8V

ncp

Prob. damaging

Tolerated

Neutral

0,77

0,57

 

11:71360887

G/A

new

V82M

ncp

Pos. damaging

Tolerated

Neutral

0,09

0,15

 

11:71364581

T/C

rs22145736

L167P

ncp

Prob. damaging

Aff. function

Deleterious

0,15

0

 

11:71364681

A/C

reference1

Q200H

ncp

Pos. damaging

Aff. function

Neutral

0,88

0,23

 

11:71365810

A/G

new

T577A

LRRCT3

Pos. damaging

Aff. function

Neutral

0,01

0

TLR5

38:23702837

C/T

rs9070447

R269C

ncp

Prob. damaging

Aff. function

Neutral

0,19

0,01

 

38:23702918

G/A

new

V296I

ncp

Pos. damaging

Tolerated

Neutral

0,05

0,26

 

38:23703629

G/A

new

G533S

ncp

Prob. damaging

Tolerated

Neutral

0,02

0

 

38:23704331

G/T

new

D767Y

ncp

Prob. damaging

Tolerated

Deleterious

0,04

0

 

38:23704531

C/G

new

N833K

LRRCT

Pos. damaging

Tolerated

Deleterious

0

0,06

 

38:23704562

C/T

new

R844C

LRRCT

Pos. damaging

Tolerated

Neutral

0,04

0,39

 

38:23704581

C/T

reference 1

S850L

LRRCT

Prob. damaging

Aff. function

Deleterious

0,68

0,02

 

38:23704695

T/G

new

F888C

low complexity

Prob. damaging

Aff. function

Deleterious

0,04

0

 

38:23705081

C/T

new

H1017Y

TIR

Benign

Aff. function

Neutral

0,02

0

 

38:23705264

G/A

new

A1078T

TIR4

Pos. damaging

Aff. function

Neutral

0,07

0,00

TLR6

3:73521250

A/G

new

Y182C

ncp

Prob. damaging

Tolerated

Deleterious

0,01

0,09

 

3:73522074

C/T

new

L457F

ncp

Prob. damaging

Aff. function

Deleterious

0,03

0

 

3:73522242

G/A

rs23570247

D513N

ncp

Pos. damaging

Tolerated

Neutral

0,73

1,00

 

3:73522441

C/T

new

P579L

LRRCT

Pos. damaging

Aff. function

Deleterious

0,01

0,07

TLR10

3:73569402

C/T

rs23518574

T361M

ncp

Prob. damaging

Aff. function

Deleterious

0,13

0,12

 

3:73570681

T/A

new

F787L

TIR5

Pos. damaging

Low confidence

Neutral

0,00

0,39

INTRACELLULAR TLRs

TLR8

X:9397240

T/C

new

V157A

ncp

Pos. damaging

Aff. function

Deleterious

0,06

0

TLR9

20:37544129

G/A

new

V87I

ncp

Benign

Aff. function

Neutral

0,02

0

 

20:37546230

C/T

new

P787L

ncp

Pos. damaging

Tolerated

Neutral

0,22

0,24

 

20:37546454

C/T

new

R862W

ncp

Prob. damaging

Tolerated

Neutral

0,2

0

In italics, SNPs that are predicted to have an effect on protein function by the three algorithms. ancp, no confident prediction. bObserved frequency by massive sequencing. 1reference allele tested as the alternative in the SNP. 2Leucine Rich Repeat C-terminal (LRRCT) domain predicted from aminoacid 528 to 582. 3LRRCT domain predicted from aminoacid 579 to 629. 4TIR domain predicted from aminoacid 927 to 1074. 5TIR domain predicted from aminoacid 641 to 784.

Protein structure of the canine TLRs was assessed using SMART [28, 29], which predicts domains taking into account aminoacid sequences: 6 out of 31 nsSNPs predicted to be damaging in canine TLRs were found to be in a Leucine Rich Repeat C-terminal (LRRCT) or really close to it. Only 1 out of 31 was found to affect TIR domain in TLR 5, other 2 were found to be really close to this domain in TLR5 and 10. With the exception of these last ones, nsSNPs were in most cases located in the sensor domain of TLRs (Table 3).

Frequencies in Table 3 are an average of all dog pools tested and both wolf populations respectively, so all variants are polymorphic (MAF > 0.05) at least in one breed. 17 out of 31 show a MAF > 0.05 when considering the average frequencies in all the pools together (15 out of 31 with MAF > 0.05 in wolf populations). However, as mentioned above, frequencies of nsSNPs differ among breeds (see Additional file 2). It’s worthy to note the differences on the alternative allele frequency observed for the 8 nsSNPs that were predicted to affect protein function by the three tools used (Figure 1).
Figure 1

Breed allelic frequencies for the 8 nsSNP with a damaging prediction from Polyphen-2, SIFT and PROVEAN.

TaqMan open array design and SNP validation

A TaqMan OpenArray® plate has been developed for the validation of the nsSNPs by individual genotyping (Table 4). This panel contains (i) 27 out of 31 nsSNPs that were predicted to have an impact on the protein structure (4 wolf-specific SNPs were not considered for the array: TLR1 A525V, TLR5 N833K, TLR6 P579L and TLR10 F787L; see Table 3); (ii) 28 out of the 33 remaining nsSNPs segregating in dogs (5 SNPs that were not suitable for a correct primer design were rejected for posterior analysis: TLR4 T36A, TLR4 T36I, TLR5 T243A, TLR5 Q213R and TLR9 A442V); and (iii) 4 frameshift and 4 non-synonymous TLR polymorphisms described on CanFam 3.1 but not detected in our cohorts (see Table 4). One of the non-synonymous variants added (rs23572381, TLR1 N634K) was designed with two different TaqMan assays due to the presence of other variants close to the interrogated SNP.
Table 4

Non-synonymous SNPs and frameshift mutations of canine TLRs in the TaqMan Open Array plate

Canine gene

SNP

Chr:bp position

dbSNP ID

AA Subst

Previous detected a

Validated?

TLR1

G/T

3:73542337

rs23585044

S29I

Massive seq

YES

 

T/G

3:73543092

new

S281A

Massive seq

YES

 

G/A

3:73543185

new

V312I

Massive seq

YES

 

T/A

3:73544153

rs23572381

N634K1

CanFam 3.1

YES2

 

T/A

3:73544153

rs23572381

N634K1

CanFam 3.1

NO

 

G/A

3:73544221

rs23572380

S657N

CanFam 3.1

YES2

TLR2

C/A

15:51463020

rs22410121

S46Y

Massive seq

YES

 

A/0

15:51464076

rs8958543

A398-

CanFam 3.1

YES2

 

C/T

15:51464430

new

S516L

Massive seq

YES

 

C/T

15:51464700

new

T606M

Massive seq

YES

TLR3

C/G

16:44623632

new

E176D

Massive seq

YES

TLR4

T/C

11:71356420

rs22120766

V8A

Massive seq

NO

 

G/C

11:71360743

rs22157966

A34P

Massive seq

YES

 

G/A

11:71360887

new

V82M

Massive seq

YES

 

T/C

11:71364581

rs22145736

L167P

Massive seq

YES

 

C/A

11:71364681

rs22189454

H200Q

Massive seq

YES

 

A/G

11:71364769

rs22189456

K230E

Massive seq

YES

 

G/A

11:71365120

new

A347T

Massive seq

YES

 

A/T

11:71365652

rs22124023

E524V

Massive seq

YES

 

A/G

11:71365810

new

T577A

Massive seq

YES

 

G/A

11:71365888

rs22123995

E603K

Massive seq

YES

TLR5

G/A

38:23702193

rs24029590

G54E

CanFam 3.1

NO

 

0/C

38:23702251

rs9070448

-74C

CanFam 3.1

YES2

 

A/G

38:23702514

rs9070450

Y161C

CanFam 3.1

NO

 

A/C

38:23702539

new

E169D

Massive seq

YES

 

G/A

38:23702562

new

S177N

Massive seq

YES

 

G/C

38:23702640

rs9070451

R203P

Massive seq

YES

 

T/C

38:23702684

rs9070452

W218R

Massive seq

NO

 

C/T

38:23702837

rs9070447

R269C

Massive seq

YES

 

G/A

38:23702918

new

V296I

Massive seq

YES

 

T/C

38:23703180

new

L383S

Massive seq

YES

 

G/A

38:23703237

new

R402Q

Massive seq

YES

 

G/A

38:23703279

new

R416Q

Massive seq

YES

 

T/0

38:23703591

rs9125247

T520-

CanFam 3.1

YES2

 

G/A

38:23703629

new

G533S

Massive seq

YES

 

G/A

38:23704233

new

R734Q

Massive seq

YES

 

G/T

38:23704331

new

D767Y

Massive seq

YES

 

C/T

38:23704562

new

R844C

Massive seq

YES

 

T/C

38:23704581

rs24029975

L850S

Massive seq

YES

 

T/G

38:23704695

new

F888C

Massive seq

YES

 

G/A

38:23704718

new

A896T

Massive seq

YES

 

C/T

38:23705081

new

H1017Y

Massive seq

YES

 

G/A

38:23705090

new

G1020S

Massive seq

YES

 

G/A

38:23705178

new

R1049Q

Massive seq

YES

 

G/A

38:23705264

new

A1078T

Massive seq

YES

TLR6

A/G

3:73521250

new

Y182C

Massive seq

YES

 

C/T

3:73522074

new

L457F

Massive seq

YES

 

G/A

3:73522242

rs23570247

D513N

Massive seq

YES

TLR7

C/G

X:9334108

new

A16G

Massive seq

YES2

 

C/A

X:9355727

new

F167L

Massive seq

YES

 

C/T

X:9358423

new

P1066L

Massive seq

YES

TLR8

T/C

X:9397240

new

V157A

Massive seq

YES

 

G/A

X:9397663

new

R298Q

Massive seq

YES

 

G/A

X:9398094

rs24607342

G442S

Massive seq

YES

 

G/A

X:9398827

rs24607358

R686H

Massive seq

YES

TLR9

G/A

20:37544129

new

V87I

Massive seq

YES

 

0/A

20:37544851

rs9188882

-328A

CanFam 3.1

YES2

 

A/G

20:37545011

new

K381E

Massive seq

YES

 

C/A

20:37545245

new

P459T

Massive seq

YES

 

A/G

20:37546031

rs22882109

S721G

Massive seq

YES

 

C/T

20:37546230

new

P787L

Massive seq

ND 3

 

C/T

20:37546454

new

R862W

Massive seq

YES

TLR10

C/T

3:73569402

rs23518574

T361M

Massive seq

YES

 

A/G

3:73570094

new

M592V

Massive seq

YES

aMassive seq indicates a SNP variant detected in our cohorts. An “rs” name is indicated in dbSNP ID if the SNP is annotated in CanFam 3.1. 1SNP considered twice with a different surrender SNP in order to detect it. 2Assay has been validated technically, although not genetically because all individuals have only the reference allele. 3ND (not determined), there are incongruent results: massive sequencing showed that this SNP was present at a frequency of 0.2 in all breeds tested, whereas it has not been genotyped through TaqMan OA plate.

A total of 99 DNA samples of the first massive sequencing pools were chosen to be individually genotyped in order to validate the SNPs with the TaqMan Open Array® designed: 15 Beagle, 15 Boxer, 14 French bulldog, 15 Labrador, 15 German Shepherd dog, 13 Yorkshire and 12 Shar Pei were used. One Shar-Pei and 2 Yorkshires do not pass the quality control for samples (call rate > 0.9) and were removed from the posterior analysis. Finally, analysis was performed with a total of 96 individuals. Fifty-nine out of the 64 SNPs (92%) included in the OpenArray have been successfully validated and all of them had a call rate greater than 0.9.

Some downstream analyses have been performed with the individual genotypes. However, it should be taken into account that these are just preliminary results, which need to be validated with larger cohorts of dogs.

All the TLR SNPs were in Hardy-Weinberg Equilibrium (HWE) on Beagle, Boxer, German Shepherd, Labrador and Shar-Pei. In Yorkshire, TLR10 has two SNPs in linkage disequilibrium which are not in HWE, one of them is predicted to affect protein function by the algorithms tested (Table 3). French Bulldog was the breed that had more SNPs that did not follow HWE proportions, with 3 SNPs in TLR4 and one SNP in TLR5 (Table 5). TLR7 and 8 were not included because they are both located in chromosome X.Principal components analysis (PCA) combined data from the individual genotypes obtained for the subset of SNPs which were not in linkage disequilibrium. It was used to illustrate if dogs cluster by breed for genetic variants in TLRs. The first two components from the PCA have been plotted in Figure 2. Visual examination of this plot shows overlapping for most breeds, excluding Labrador and perhaps German Shepherd, which seem to be more differentiated for these receptors.
Table 5

SNPs in different breeds that are not in Hardy-Weinberg Equilibrium (p < 0.05)

Breed

Canine gene

AA change

SNP

Genotypes a

p-value

SNP prediction b

Yorkshire

TLR10

T361M

C/T

1/1/9

0.0416978

Prob. damaging

Yorkshire

TLR10

M592V

A/G

1/1/9

0.0416978

Benign

French B.

TLR4

V82M

G/A

4/2/8

0.0099493

Pos. damaging

French B.

TLR4

H200Q

C/A

6/1/7

0.0013535

Pos. damaging*

French B.

TLR4

K230E

A/G

6/1/7

0.0013535

Benign

French B.

TLR5

S177N

G/A

0/11/3

0.0154748

Benign

agenotypes, indicate genotype count for reference homozygotes, heterozygotes and alternative homozygotes. bSNP prediction, using Polyphen-2 classification. *possibly damaging when reference allele is tested as alternative in the SNP.

Figure 2

Principal Component Analysis (PCA) plot of the two first components for canine TLRs.

Discussion

Canine breed specific variants in TLRs could be associated to differences in breed innate immune response to pathogens and thus to susceptibility to infections or autoimmune diseases. So far, polymorphisms in TLR4 and TLR5 have been associated with IBD in German Shepherd dogs [8], but only protective SNPs from TLR5 have been associated with IBD in other 38 dog breeds [9]. There is therefore great interest in the characterization of canine TLRs. Different dog breeds and 2 different populations of wolves (Iberian and Russian) were included in the analysis to represent some of the major phylogenetic radiations: Wolves, Ancient&Spitz breeds, Scent hounds, Working dogs, Mastiff-like dogs, Small Terriers and Retrievers [30]. A total of 204 variants have been discovered and functionally annotated in exonic regions of canine TLRs by massive sequencing: 155 of the variants were new in relation to the most recent annotation of the canine genome (CanFam 3.1; September 2012). Variants have been functionally annotated and correspond to 64 non-synonymous variants (43 new), 73 synonymous variants (56 new) and 67 modifier variants (57 new). None of the variants detected in the pools analyzed had a high effect (STOP codon, frameshift mutation or splicing) on the protein function, although 4 frameshift mutations are annotated in CanFam 3.1.

SNPs functionally annotated as non-synonymous are expected to have a greater effect on protein function, and therefore a more exhaustive analysis was performed on them. Although allelic frequencies for nsSNPs differ among breeds and 12.5% of them are breed-specific (6.25% are wolf specific), dogs from different breeds share most non-synonymous variants in TLRs.

A TaqMan OpenArray® plate containing 64 SNPs with a possible functional effect in the protein (4 frameshifts and 60 nsSNPs) has been designed and validated. 55 out of 64 SNPs contained in the OpenArray® plate have been identified in this work through massive sequencing by HISEQ; the remaining 9 were obtained from CanFam 3.1.As shown in Figure 2, the individual genotypes are not clustering by breed, with the exception of Labrador and German Shepherd dogs.

The functional impact of non-synonymous variants in dog TLRs was predicted using Polyphen-2, SIFT and PROVEAN. Knowing that TLRs are highly conserved receptors, it is not unexpected that half non-synonymous mutations in dogs have a benign effect, which agrees with results from similar approaches in other non-primate species such as bovine [31]. In dogs, TLR5 is the one that presents more damaging non-synonymous mutations (possibly damaging + probably damaging), followed by TLR4, both of them extracellular receptors.

Results from SIFT and Polyphen-2 from some nsSNPs located in TLR5 returned no output and no prediction (“unknown” or “low confidence”). In dogs, TLR5 was described as a longer protein compared to their homologs in other species. In CanFam 3.1 TLR5 has 1422 aminoacids, however other species like human, cow and pig have 858 aa, 858 aa and 856 aa, respectively. A protein BLAST was performed with the extra 5′ and 3′ TLR5 fragments, but no result was obtained. Furthermore, the 5′ sequence begins with ATG codon in the same phase as the initial coding ATG in other species, whereas the 3′ sequence eliminates the STOP codon due to some repeats in tandem (data not shown). So, bad annotation of this gene in CanFam3.1 is suggested. However, SNPs have been found in this region. In fact, there are 2 SNPs that had already been wrongly described as an aminoacid change (in ENSEMBL) moreover in this study 5 more SNPs have been detected. So it would be interesting to either determine the existence and functionality of these extra fragments in canine TLR5 cDNA or correctly annotate it in CanFam 3.1.

Intracellular TLRs, which detect nucleic acids, have less nsSNPs (15), moreover these are predicted to be less damaging variants than those identified in extracellular TLRs, suggesting that intracellular TLRs are selectively constrained. TLR9 is the intracellular TLR that accepts more nsSNPs in dogs, but the predicted effect of these nsSNPs is usually benign.

These results agree with previously reported data revealing major differences in the intensity of selection acting upon the different members of the TLR family. Different TLRs differ in their immunological redundancy, reflecting their distinct contributions to host defense [5, 32]. Intracellular TLRs act as nucleic acid sensors and have evolved under strong purifying selection, indicating their essential non-redundant role in host survival. Higher rates of damaging non-synonymous and nonsense mutations are tolerated in cell-surface or extracellular TLRs, which recognize compounds other than nucleic acids, suggesting a higher redundancy.

Location of the SNPs in the protein was approached using the software SMART [28], which identifies TLR domains using the aminoacid sequence. The intracellular TIR domain is highly conserved between different TLRs and species due to its involvement in intracellular signaling [33]. Also in dogs, TIR domains have few SNPs; only one is present in the predicted TIR domain (TLR5 H1017Y) and another two are really close to it (TLR5 A1078T and TLR10 F787L). Extracellular domains of TLRs are those that recognize PAMPs, and they have an enhanced susceptibility to mutate adapting to different microbiologic environments [33]. It can also be seen that a high number of mutations (some with damaging effects) are located in LRR domains, which form the extracellular domain of TLRs.

So far, polymorphisms in TLRs have been associated with Inflammatory Bowel disease (IBD) in German Shepherd dogs (GSD) and in other breeds. Variants in TLR5 previously reported to be associated to IBD (G22A, C100T and T1844C from [8, 9]) have been also detected in our cohorts and correspond with TLR5 T243A, TLR5 R269C and TLR5 L850S respectively.

SNP G22A, where the risk allele is A in G22A (corresponding to Thr in TLR5 T243A as named in this work), is found to be an additive allele. So when a GSD is homozygous for the risk allele it has more susceptibility to suffer IBD. This risk allele is not segregating in our GSD cohort. This could be due to the difference in the geographical origin of the GSD cohort between both studies. In [9] GSD are from UK, whilst our cohort is from Spain. SNPs C100T and T1844C were found to be significantly protective against canine IBD in many breeds [9]. The frequencies of the protective alleles (T in C100T and T in T1844C or Cys in TLR5 R269C and Leu in TLR5 L850S as named in this work) differ among breeds (Figure 3), with a frequency higher than 0.5 in Yorkshire and GSD.
Figure 3

Observed allele frequency of the alleles related with IBD in our pools (A in G22A, and T in both C100T and T1844C).

Conclusions

Polymorphisms in the exonic regions of canine TLRs have been characterized by massive sequencing and 156 out of 204 variants identified were new: 43/64 non-synonymous variants, 56/73 synonymous variants and 57/67 modifier variants. None of the variants detected in the pools analyzed had a high effect (STOP codon, frameshift mutation or splicing) on the protein function.

A TaqMan OpenArray® plate containing 64 SNPs with a possible functional effect in the protein (4 frameshifts and 60 nsSNPs) has been designed and validated to allow the high throughput genotyping of canine TLRs.

Methods

Ethics statement

The dogs in the study were examined during routinary veterinary procedures by the veterinary clinics participating in the study. All samples were collected for routine diagnostic and clinical purposes. The samples were obtained during veterinary procedures that would have been carried out anyway and DNA was extracted from residual surplus of samples and used in the study with verbal owner consent. This is a very special situation in veterinary medicine. As the data are from client-owned dogs that underwent normal veterinary exams, there was no “animal experiment” according to the legal definitions in Spain and the United Kingdom, and approval by an ethical committee was not necessary.

DNA sources

Samples available from the DNA bank at the SVGM (Molecular Genetics Veterinary Service, UAB) were used. Total DNA from blood cells had been extracted either as described elsewhere [34] or using QIAamp DNA Mini Kit (Qiagen).

DNAs from 7 different dog breeds, including 50 Beagle, 50 German Shepherd, 50 Yorkshire, 35 French bulldog, 75 Boxer, 50 Labrador and 25 Shar Pei were used. All the dogs included in this study are from Spain region, and come from hospital population or normal pet dogs. Also 2 different populations of wolves, with 50 Iberian (Canis lupus signatus) and 50 Russian (European grey wolves, Canis lupus lupus), were analyzed. DNA pools were prepared with 200 ng of DNA from 25 unrelated dogs (with the exception of one pool of French bulldogs, with only 10 dogs). Two pools of each breed were analyzed, in exception of Shar Pei (only 1 pool) and Boxer (3 pools). Pools of wolves were of 50 individuals.

Some DNA samples of the first massive sequencing analyses were chosen to be individually genotyped in order to validate SNPs in the TaqMan Open Array® designed (15 Beagle, 15 Boxer, 14 French bulldog, 15 Labrador, 15 German Shepherd, 13 Yorkshire and 12 Shar Pei).

Exon capture and massive sequencing for SNP discovery

Twenty exonic regions of 10 canine TLR genes annotated in CanFam 2.0 were chosen to perform the enrichment (see Additional file 3 with corresponding coordinates in CanFam 3.1).

Oligonucleotides were first automatically designed for the enrichment of selected regions [35]. Regions rejected in the automated design, because of the presence of gaps, repeats or shorter sizes than required (at least 120 nucleotides) were manually redesigned. Finally 235 ultra-long 120-mer biotinylated cRNA baits were designed to capture the exonic regions of canine TLRs (28,200 bases) by the Agilent Sure Select technique. High-throughput sequencing was performed using 2 lanes of Illumina HISEQ, with 8-labelled pools each, at CNAG (Centre Nacional d’Anàlisi Genòmica, Barcelona, Spain).

Sequences obtained were mapped to CanFam 3.1 (released September 2012). All pools were analysed together for variant calling, for better comparison. Alternative variant frequencies were estimated for each breed pool and wolf populations. The variants were annotated with statistical information from the Genome Analysis Tool Kit (GATK) and functional annotations were added from Ensembl using snpEff [36].

Prediction of functional impact of non-synonymous SNPs

The functional impact of non-synonymous mutations detected was predicted using Polyphen-2 [22, 23], SIFT [25, 24] and PROVEAN [27, 26]. When the mean frequency of an alternative variant on the dog population analyzed was more than 0.25, both alleles of those SNPs were tested with algorithms mentioned before as reference and alternative.

Polyphen-2 classifies mutations in three categories: benign, possibly damaging and probably damaging. Polyphen algorithm considers protein structure and/or sequence conservation information for each gene [23]. SIFT is based on the evolutionary conservation of the amino acids within protein families performing multiple sequencing analyses using PSI-Blast algorithm. Highly conserved positions tend to be intolerant to substitution, whereas those with a low degree of conservation tolerate most substitutions. Therefore, it classifies each non-synonymous polymorphism as tolerated or affect protein function and provides also a confidence measure [24]. PROVEAN introduced a region-based “delta alignment score” which measures the impact of an amino acid variation not only based on the amino acid residue at the position of interest but also the quality of sequence alignment derived from the neighborhood flanking sequences. It classifies variants either as neutral or deleterious [26].

SMART was used in order to identify protein domains of each TLR using their aminoacid sequence [28].

TaqMan OpenArray® design

A TaqMan OpenArray® was designed for genotyping and validating 64 SNPs with a possible functional effect in the protein. Selected SNPs and their surrounding sequences, 60 nucleotides upstream and 60 nucleotides downstream were introduced in Custom TaqMan® Assay Design Tool web site [37] from Life Technologies® to validate if the sequences were suitable for TaqMan assay design. Other SNPs in the context sequences were indicated with an “N” before the assays design. SNPs included are listed in Table 4.

Analysis was performed with the TaqMan Genotyper software v.1.3 (Applied Biosystems). Further analysis of individual genotypes was performed with SVS (version 7) of Golden Helix Inc. SNPs or samples that do not pass call rate >0.9 were removed for posterior analysis.

Declarations

Acknowledgements

We acknowledge Lorena Serrano (Vetgenomics) for helping with the collection of the samples; Sophia Derdak and Sergi Beltran (CNAG) for the raw data processing of the massive sequencing results; and Anna Mercadé (SVGM) for technical advice and support on the OpenArray design and validation.

Authors’ Affiliations

(1)
Molecular Genetics Veterinary Service. Veterinary School, Universitat Autònoma de Barcelona
(2)
Vetgenomics. Ed Eureka. Parc de Recerca UAB
(3)
Department of Clinical Sciences, Cummings School of Veterinary Medicine, Tufts University

References

  1. Werling D, Jungi TW: TOLL-like receptors linking innate and adaptive immune response. Vet Immunol Immunopathol 2003, 91: 1–12. 10.1016/S0165-2427(02)00228-3PubMedView ArticleGoogle Scholar
  2. Kawai T, Akira S: The role of pattern-recognition receptors in innate immunity: update on Toll-like receptors. Nat Immunol 2010, 11: 373–384. 10.1038/ni.1863PubMedView ArticleGoogle Scholar
  3. Mogensen TH: Pathogen recognition and inflammatory signaling in innate immune defenses. Clin Microbiol Rev 2009, 22: 240–273. 10.1128/CMR.00046-08PubMed CentralPubMedView ArticleGoogle Scholar
  4. Aderem A, Ulevitch RJ: Toll-like receptors in the induction of the innate immune response. Nature 2000, 406: 782–787. 10.1038/35021228PubMedView ArticleGoogle Scholar
  5. Barreiro LB, Ben-Ali M, Quach H, Laval G, Patin E, Pickrell JK, Bouchier C, Tichit M, Neyrolles O, Gicquel B, Kidd JR, Kidd KK, Alcaïs A, Ragimbeau J, Pellegrini S, Abel L, Casanova J-L, Quintana-Murci L: Evolutionary dynamics of human Toll-like receptors and their different contributions to host defense. PLoS Genet 2009, 5: e1000562. 10.1371/journal.pgen.1000562PubMed CentralPubMedView ArticleGoogle Scholar
  6. Netea MG, Wijmenga C, O’Neill LAJ: Genetic variation in Toll-like receptors and disease susceptibility. Nat Immunol 2012, 13: 535–542. 10.1038/ni.2284PubMedView ArticleGoogle Scholar
  7. Lindblad-Toh K, Wade CM, Mikkelsen TS, Karlsson EK, Jaffe DB, Kamal M, Clamp M, Chang JL, Kulbokas EJ, Zody MC, Mauceli E, Xie X, Breen M, Wayne RK, Ostrander EA, Ponting CP, Galibert F, Smith DR, DeJong PJ, Kirkness E, Alvarez P, Biagi T, Brockman W, Butler J, Chin C-W, Cook A, Cuff J, Daly MJ, DeCaprio D, Gnerre S, et al.: Genome sequence, comparative analysis and haplotype structure of the domestic dog. Nature 2005, 438: 803–819. 10.1038/nature04338PubMedView ArticleGoogle Scholar
  8. Kathrani A, House A, Catchpole B, Murphy A, German A, Werling D, Allenspach K: Polymorphisms in the TLR4 and TLR5 gene are significantly associated with inflammatory bowel disease in German shepherd dogs. PLoS One 2010, 5: e15740. 10.1371/journal.pone.0015740PubMed CentralPubMedView ArticleGoogle Scholar
  9. Kathrani A, House A, Catchpole B, Murphy A, Werling D, Allenspach K: Breed-independent toll-like receptor 5 polymorphisms show association with canine inflammatory bowel disease. Tissue Antigens 2011, 78: 94–101. 10.1111/j.1399-0039.2011.01707.xPubMedView ArticleGoogle Scholar
  10. Kathrani A, Holder A, Catchpole B, Alvarez L, Simpson K, Werling D, Allenspach K: TLR5 risk-associated haplotype for canine inflammatory bowel disease confers hyper-responsiveness to flagellin. PLoS One 2012, 7: e30117. 10.1371/journal.pone.0030117PubMed CentralPubMedView ArticleGoogle Scholar
  11. Suchodolski JS, Dowd SE, Wilke V, Steiner JM, Jergens AE: 16S rRNA gene pyrosequencing reveals bacterial dysbiosis in the duodenum of dogs with idiopathic inflammatory bowel disease. PLoS One 2012, 7: e39333. 10.1371/journal.pone.0039333PubMed CentralPubMedView ArticleGoogle Scholar
  12. McMahon LA, House AK, Catchpole B, Elson-Riggins J, Riddle A, Smith K, Werling D, Burgener IA, Allenspach K: Expression of Toll-like receptor 2 in duodenal biopsies from dogs with inflammatory bowel disease is associated with severity of disease. Vet Immunol Immunopathol 2010, 135: 158–163. 10.1016/j.vetimm.2009.11.012PubMedView ArticleGoogle Scholar
  13. Burgener IA, König A, Allenspach K, Sauter SN, Boisclair J, Doherr MG, Jungi TW: Upregulation of toll-like receptors in chronic enteropathies in dogs. J Vet Intern Med 2008, 22: 553–560. 10.1111/j.1939-1676.2008.0093.xPubMedView ArticleGoogle Scholar
  14. Allenspach K, House A, Smith K, McNeill FM, Hendricks A, Elson-Riggins J, Riddle A, Steiner JM, Werling D, Garden OA, Catchpole B, Suchodolski JS: Evaluation of mucosal bacteria and histopathology, clinical disease activity and expression of Toll-like receptors in German shepherd dogs with chronic enteropathies. Vet Microbiol 2010, 146: 326–335. 10.1016/j.vetmic.2010.05.025PubMedView ArticleGoogle Scholar
  15. Kuroki K, Stoker AM, Sims HJ, Cook JL: Expression of Toll-like receptors 2 and 4 in stifle joint synovial tissues of dogs with or without osteoarthritis. Am J Vet Res 2010, 71: 750–754. 10.2460/ajvr.71.7.750PubMedView ArticleGoogle Scholar
  16. Chotimanukul S, Sirivaidyapong S: Differential expression of Toll-like receptor 4 (TLR4) in healthy and infected canine endometrium. Theriogenology 2011, 76: 1152–1161. 10.1016/j.theriogenology.2011.05.024PubMedView ArticleGoogle Scholar
  17. Mercier E, Peters IR, Day MJ, Clercx C, Peeters D: Toll- and NOD-like receptor mRNA expression in canine sino-nasal aspergillosis and idiopathic lymphoplasmacytic rhinitis. Vet Immunol Immunopathol 2012, 145: 618–624. 10.1016/j.vetimm.2012.01.009PubMedView ArticleGoogle Scholar
  18. Figueiredo MM, Amorim IFG, Pinto AJW, Barbosa VS, Pinheiro LDJ, Deoti B, Faria AMC, Tafuri WL: Expression of Toll-like receptors 2 and 9 in cells of dog jejunum and colon naturally infected with Leishmania infantum. BMC Immunol 2013, 14: 22. 10.1186/1471-2172-14-22PubMed CentralPubMedView ArticleGoogle Scholar
  19. Melo LM, Perosso J, Almeida BFM, Silva KLO, Somenzari MA, de Lima VMF: Effects of P-MAPA immunomodulator on Toll-like receptor 2, ROS, nitric oxide, MAPKp38 and IKK in PBMC and macrophages from dogs with visceral leishmaniasis. Int Immunopharmacol 2014, 18: 373–378. 10.1016/j.intimp.2013.12.012PubMedView ArticleGoogle Scholar
  20. Ensembl genome browser 75: Canis lupus familiaris. [http://www.ensembl.org/Canis_familiaris/]
  21. Nelson MR, Marnellos G, Kammerer S, Hoyal CR, Shi MM, Cantor CR, Braun A: Large-scale validation of single nucleotide polymorphisms in gene regions. Genome Res 2004, 14: 1664–1668. 10.1101/gr.2421604PubMed CentralPubMedView ArticleGoogle Scholar
  22. PolyPhen-2: prediction of functional effects of human nsSNPs [http://genetics.bwh.harvard.edu/pph2/index.shtml]
  23. Adzhubei IA, Schmidt S, Peshkin L, Ramensky VE, Gerasimova A, Bork P, Kondrashov AS, Sunyaev SR: A method and server for predicting damaging missense mutations. Nat Methods 2010, 7: 248–249. 10.1038/nmeth0410-248PubMed CentralPubMedView ArticleGoogle Scholar
  24. Kumar P, Henikoff S, Ng PC: Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm. Nat Protoc 2009, 4: 1073–1081. 10.1038/nprot.2009.86PubMedView ArticleGoogle Scholar
  25. SIFT [http://sift.jcvi.org/]
  26. Choi Y, Sims GE, Murphy S, Miller JR, Chan AP: Predicting the functional effect of amino acid substitutions and indels. PLoS One 2012, 7: e46688. 10.1371/journal.pone.0046688PubMed CentralPubMedView ArticleGoogle Scholar
  27. PROVEAN [http://provean.jcvi.org/index.php]
  28. Letunic I, Doerks T, Bork P: SMART 7: recent updates to the protein domain annotation resource. Nucleic Acids Res 2012,40(Database issue):D302-D305.PubMed CentralPubMedView ArticleGoogle Scholar
  29. SMART [http://smart.embl-heidelberg.de/]
  30. Vonholdt BM, Pollinger JP, Lohmueller KE, Han E, Parker HG, Quignon P, Degenhardt JD, Boyko AR, Earl DA, Auton A, Reynolds A, Bryc K, Brisbin A, Knowles JC, Mosher DS, Spady TC, Elkahloun A, Geffen E, Pilot M, Jedrzejewski W, Greco C, Randi E, Bannasch D, Wilton A, Shearman J, Musiani M, Cargill M, Jones PG, Qian Z, Huang W, et al.: Genome-wide SNP and haplotype analyses reveal a rich history underlying dog domestication. Nature 2010, 464: 898–902. 10.1038/nature08837PubMed CentralPubMedView ArticleGoogle Scholar
  31. Fisher CA, Bhattarai EK, Osterstock JB, Dowd SE, Seabury PM, Vikram M, Whitlock RH, Schukken YH, Schnabel RD, Taylor JF, Womack JE, Seabury CM: Evolution of the bovine TLR gene family and member associations with Mycobacterium avium subspecies paratuberculosis infection. PLoS One 2011, 6: e27744. 10.1371/journal.pone.0027744PubMed CentralPubMedView ArticleGoogle Scholar
  32. Wlasiuk G, Nachman MW: Adaptation and constraint at Toll-like receptors in primates. Mol Biol Evol 2010, 27: 2172–2186. 10.1093/molbev/msq104PubMed CentralPubMedView ArticleGoogle Scholar
  33. Werling D, Jann OC, Offord V, Glass EJ, Coffey TJ: Variation matters: TLR structure and species-specific pathogen recognition. Trends Immunol 2009, 30: 124–130. 10.1016/j.it.2008.12.001PubMedView ArticleGoogle Scholar
  34. Francino O, Altet L, Sánchez-Robert E, Rodriguez A, Solano-Gallego L, Alberola J, Ferrer L, Sánchez A, Roura X: Advantages of real-time PCR assay for diagnosis and monitoring of canine leishmaniosis. Vet Parasitol 2006, 137: 214–221. 10.1016/j.vetpar.2006.01.011PubMedView ArticleGoogle Scholar
  35. SureDesign [https://earray.chem.agilent.com/suredesign/]
  36. Cingolani P, Platts A, Wang LL, Coon M, Nguyen T, Wang L, Land SJ, Ruden DM, Lu X: A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly 2012, 6: 80–92. 10.4161/fly.19695PubMed CentralPubMedView ArticleGoogle Scholar
  37. Custom TaqMan® Assay Design Tool - Life technologies [https://www5.appliedbiosystems.com/tools/cadt/]

Copyright

© Cuscó et al.; licensee BioMed Central Ltd. 2014

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/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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