Open Access

Genetic control of resistance to salmonellosis and to Salmonella carrier-state in fowl: a review

  • Fanny Calenge1Email author,
  • Pete Kaiser2, 4,
  • Alain Vignal3 and
  • Catherine Beaumont1
Genetics Selection Evolution201042:11

DOI: 10.1186/1297-9686-42-11

Received: 21 September 2009

Accepted: 29 April 2010

Published: 29 April 2010

Abstract

Salmonellosis is a frequent disease in poultry stocks, caused by several serotypes of the bacterial species Salmonella enterica and sometimes transmitted to humans through the consumption of contaminated meat or eggs. Symptom-free carriers of the bacteria contribute greatly to the propagation of the disease in poultry stocks. So far, several candidate genes and quantitative trait loci (QTL) for resistance to carrier state or to acute disease have been identified using artificial infection of S. enterica serovar Enteritidis or S. enterica serovar Typhimurium strains in diverse genetic backgrounds, with several different infection procedures and phenotypic assessment protocols. This diversity in experimental conditions has led to a complex sum of results, but allows a more complete description of the disease. Comparisons among studies show that genes controlling resistance to Salmonella differ according to the chicken line studied, the trait assessed and the chicken's age. The loci identified are located on 25 of the 38 chicken autosomal chromosomes. Some of these loci are clustered in several genomic regions, indicating the possibility of a common genetic control for different models. In particular, the genomic regions carrying the candidate genes TLR4 and SLC11A1, the Major Histocompatibility Complex (MHC) and the QTL SAL1 are interesting for more in-depth studies. This article reviews the main Salmonella infection models and chicken lines studied under a historical perspective and then the candidate genes and QTL identified so far.

Background

Salmonellosis is a zoonotic disease caused by the Gram-negative enteric bacterium Salmonella. More than 2500 serotypes have been described, mostly belonging to the species S. enterica[1]. Some Salmonella serotypes can infect a broad range of domestic animals including poultry, sheep, cattle and pigs and cause symptoms of varying severity ranging from mild gastro-enteritis to death. Some of these serotypes, such as S. Typhimurium and S. Enteritidis, can infect humans. Other serotypes are host-specific, infecting a single species and generally causing severe, typhoid-like symptoms sometimes leading to death (for instance, S. Gallinarum and S. Pullorum in poultry). These serotypes can be responsible for disease outbreaks leading to severe economic losses.

Prophylactic measures, vaccination and use of antibiotics are insufficient to eradicate salmonellosis in poultry stocks, whatever the serotype involved. In this context, selection of more resistant chickens can be considered as an alternative solution to decrease occurrence of the disease. The first selection experiments at the beginning of the 20th century aimed to decrease disease occurrence in poultry production systems, which was mainly caused by S. Pullorum and S. Gallinarum. As food safety became an important concern and these host-specific serotypes were better controlled, the interest of researchers and breeders extended towards decreasing food contamination, mainly due to the serotypes Enteritidis and Typhimurium. S. Enteritidis alone, which infects the eggs of contaminated hens, is responsible for one third of the human food poisoning cases in France [2] and of about 15% in the UK in 2007 http://www.defra.gov.uk/foodfarm/farmanimal/diseases/atoz/zoonoses/reports.htm. It does not cause severe symptoms in poultry, but the eggs and meat of infected animals can become a reservoir of infection for the human consumer. In particular, asymptomatic carriers have a major role in Salmonella propagation in poultry and hence in food contamination, since they cannot be easily identified and isolated. This is the reason why today resistance to carrier-state ability, and not only to general salmonellosis resistance, is taken into account by some breeders and researchers. Simulation studies demonstrate the usefulness of rearing animals more resistant to carrier state in the prevention of disease propagation in poultry, in synergy with vaccination [3].

Experiments for the selection of genetically resistant animals can be traced back as early as the 1930's [4, 5] and the first step was the demonstration that distinct disease resistances or susceptibilities exist between different lines or breeds of chicken. The second step consisted in evaluating the heritability of disease resistance-related traits, which confirmed that the observed variability among lines had a genetic origin [68]. Next, genomic regions responsible for the observed genetic variability were identified, which provided a better understanding of the mechanisms involved in resistance and should theoretically lead to marker-assisted selection (MAS). MAS can potentially accelerate the selection process, and prevent infection of animals. To date, two different approaches have been used successfully to unravel the genetic control of disease resistance variability, i.e. (1) candidate gene approaches with a priori knowledge of the genes potentially involved (for instance, [911]) and (2) quantitative approaches through quantitative trait locus (QTL) analyses, which have been conducted since the development of molecular markers in the 1990's [1215]. A final step towards obtaining more resistant animals is selection itself, with or without the contribution of molecular markers. The feasibility of selection for increased resistance to S. Enteritidis carrier-state has been demonstrated [16]. Nevertheless, molecular markers still have to be included in the selection process, in order to take advantage of the recent knowledge acquired on genetic resistance mechanisms.

In this article, we review the literature on studies aimed at identifying the genes responsible for variable resistance to salmonellosis in chicken. The article is organised as follows: (1) the different Salmonella infection models, (2) the genetic resources used, (3) the candidate gene approaches, (4) the QTL analyses conducted and (5) the co-localisations occurring between candidate genes and QTL.

1. The Salmonella infection models: a historical perspective

Many different Salmonella infection protocols are described in the literature. Here, we focus on the protocols that have been used for genetic studies. Many factors have to be taken into account to assess Salmonella resistance i.e. infectious doses, Salmonella serotypes and strains, route and age of infection, delay between infection and phenotypic observations, and the animal rearing conditions. In addition, different parameters can be measured: survival rate, lethal dose leading to 50% of dead animals (LD50), internal organ contamination, presence/absence of Salmonella, Salmonella count, etc. The main infection models used to identify genes for resistance to Salmonella are summarized in Table 1.
Table 1

Infection models used in published studies of the genetic control of resistance to Salmonella in fowl

Locus type1

Infection route

Age2

Time3

(pi)

Trait4

Cross type

Parental lines5

Ref6

MSAT

subcuta-neaous

10 d

10 d

ABR to SE vaccine

F2+BC

(low × high) ABR divergent inbred lines

[15]

MSAT

CG

subcuta-neaous

10 d

21 d

ABR to SE vaccine

F1

Broiler outbred male × 3 inbred lines (2 MHC-congenic WL + Fay)

[12]

[64]

QTL

oral

1 w

4/5 w

CSWB counts/caecal load

F2

(N × 61) × (N × 61) layer inbred lines

[14]

QTL

oral

6 w

2 w

CSWB counts/caecal load

BC

(N × 61) × 61 layer inbred lines

[14]

QTL

oral

2 w

5 d

splenic load

BC

(61 × 15I) × 61 layer inbred lines

[13]

CG

subcuta-neaous

10 d

11 d

ABR to SE vaccine

F2

(Fay × WL) × (Fay × WL)

[66]

CG

intra-oesophageal

10 d

21 d

ABR to SE vaccine

F1

Broiler outbred male × 3 inbred lines (2 MHC-congenic WL + Fay)

[6163]

CG

intra-oesophageal

1 d

7/8 d

spleen and caecal loads

F8

AIL (Broiler × Fay) × AIL (Broiler × inbred WL)

[59]

CG

intravenous

13 w

3 d

spleen and liver loads

F1

Egg-type commercial crosses

[7]

CG

oral

peak of lay

4 w

spleen load; number of contaminated organs

F1

Egg-type commercial crosses

[9]

CG

intra-muscular

1 d

death or 2 w

survival rate

BC

(WlxC) × C

[10]

CG

intra-muscular

1 d

death or 2 w

survival rate

F0

Inbred WL lines

[54]

CG

intra-oesophageal

1 d

6/7 d

caecal and spleen loads

F1

Broiler outbred male × 3 inbred lines (2 MHC-congenic WL + Fay)

[55, 6163, 78]

CG

intra-oesophageal

1 d

6 d

caecal and spleen loads

F8

(Broiler × Fay) × AIL (Broiler × inbred WL)

[60]

CG

oral

3 w

7 d

caecal load

F0

5 groups of meat type chicken

[11]

1 CG: candidate gene, MSAT: microsatellite

2 Animal age at infection or injection; d: day; w: week

3 Assessment time post inoculation (pi)

4ABR: antibody response; CSW: cloacal swab; SE: Salmonella Enteritidis

5 AIL: advanced intercross lines; Fay: Fayoumi; WL: White Leghorn

6 Reference

At the beginning of the 20th century, the breeder's main objective was to reduce mortality in industrial poultry stocks. For practical reasons, Salmonella resistance assessment was carried out on young chicks (1 day to 2 weeks). Chicks are more susceptible to salmonellosis than adults, so that discrimination among animals was evaluated via their survival rates. Chicks were infected with a high dose of the serotypes that were known to cause the most severe symptoms in infected chicken, i.e. S. Pullorum, S. Gallinarum and S. Typhimurium [4, 5, 1720]. Some studies also reported infection of hens at peak of lay [21], because the possibility of vertical transmission of bacteria to eggs was already a concern. Different infection routes were used according to the study: oral [1921], intraperitoneal [4], or subcutaneous [17]. With the improvement of alternative disease control practices, such as chemotherapy, competitive exclusion, prophylactic measures, use of antibiotics and vaccination, disease outbreaks in poultry stocks were reduced and the interest in selection for Salmonella resistance decreased.

In the 1980s, the number of human food poisoning outbreaks increased, mainly due to S. Enteritidis, which renewed the interest to select more resistant animals. Several studies aimed at comparing the effects of different serotypes on mortality rates, and of the route of inoculation (intramuscular or oral) were carried out on day-old chicks [2224]. A few studies assessed the carrier state of chickens infected with S. Enteritidis, since symptom-less carriers are the main cause of disease propagation in poultry. In such studies, the persistence of bacteria in infected chickens has to be assessed several weeks post-infection. Guillot et al. [25] infected day-old chicks with high doses (orally or intra-muscularly) but followed the persistence of bacteria in several internal organs, in addition to measuring mortality. Duchet-Suchaux et al. [26, 27] developed a model in which one week-old chicks were orally infected with a smaller dose of bacteria, thus preventing mortality and disease symptoms, in order to observe the persistence of bacteria in different organs several weeks after infection. The carrier-state in adult chickens has been less well studied. Protais et al. [28] and Lindell et al. [29] orally infected adult hens at peak of lay and followed the persistence of bacteria in different organs.

In the above studies, Salmonella resistance was assessed by observing survival rates or quantities or presence/absence of bacteria in different organs. In more recent studies, indirect, linked parameters have been used to characterise Salmonella resistance: innate or adaptive immunity-related traits [3032], antibody response after a S. Enteritidis vaccine [12, 15], or gene expression by genome-wide, microarray analyses [3335] or more targeted studies focusing on one or several genes [3641]. Observation of these traits contributes to a better understanding of the immunological and transcriptional mechanisms involved in resistance differences between lines.

2. Comparing Salmonella resistance levels between chicken lines

The first step towards the identification of resistance genes is to choose and mate parental lines that differ in Salmonella resistance levels. Phenotypic variation is very high in poultry. For research purposes, inbred lines derived from selected breeds are the material of choice because of their higher rate of homozygosity and their relationship to actual commercial breeds. The first published studies at the beginning of the 20th century reported comparisons of different layer lines, i.e. mainly White Leghorn and Rhode Island Red lines [4, 5, 1721]. Most of these studies mention the greater resistance of the Rhode Island Red compared to the White Leghorn lines. The following studies used inbred or partially inbred lines generated from commercial layer or broiler lines. Mortalities after S. Typhimurium or S. Enteritidis infection of the inbred lines N, C, 15I, Wl, 61, 72 and 0, all derived from White Leghorn layer lines, have been compared [2224, 42]. Lines C, 72 and 15I were always more susceptible, whereas lines N, 61 and Wl were always more resistant to infection. This line ranking was identical whatever the serotype used. Mortality and persistence of bacteria in internal organs were compared in the experimental White Leghorn inbred lines B13 and Y11, in the meat-type experimental line Y11, and in a commercial line (L2) [2527]. Some studies used lines which were especially selected to study disease resistance: for instance, divergent lines for low/high antibody response [25].

The effects of genetic differences in resistance to Salmonella can be investigated by studying traits related to the immune response on different chicken lines. Heterophil functionality has been measured in several commercial lines of birds differing in their resistance to S. Enteritidis [4345]. Crop immune response has been measured in eight commercial layer hens and White Leghorn chickens [32]. Some studies report genetic differences for the antibody response to S. Enteritidis [15, 46, 47]. Similarly, many studies report gene expression differences between different chicken lines after artificial infection, identified by genome-wide, microarray analyses [3335] or more targeted studies focusing on one or several genes [3641]. Other studies used lines selected for other traits (such as growth rate or feed conversion efficiency [33, 48]), which makes it possible to investigate the interaction between the main trait under study and Salmonella resistance.

3. Candidate gene approaches

A candidate gene approach requires a priori knowledge of the genes potentially involved in Salmonella resistance. The first candidate gene tested in chicken was chosen on the basis of genetic studies carried out in mice infected by S. Typhimurium. This gene, NRAMP1 (natural resistance-associated macrophage protein, now SLC11A1), has been identified on mouse chromosome 1, under the name Ity (Immunity to Typhimurium), after mice strains were classified into two categories: resistant vs. susceptible, as reviewed in [49]. The identity of Ity with two other genes, Bcg and Lsh, involved in resistance to, respectively, Mycobacterium bovis and Leishmania donovani, was demonstrated after the positional cloning of a unique gene, NRAMP1[50]. NRAMP1 has since been described as a member of a solute carrier gene family and hence renamed SLC11A1. Physiological and functional studies support the role of SLC11A1 in the control of the intracellular replication of parasites in phagosomes. A homologue of NRAMP1 has been mapped on chicken chromosome 7 [51, 52] and cloned subsequently [53]. Another major gene, TLR4 (Toll-like receptor 4), previously named Lps, belongs to a family of innate immune system receptors (Toll-like receptors) and is involved in the recognition of LPS (lipo-polysaccharide) from Gram-negative bacteria. Lps was mapped to mouse chromosome 4 after analysis of mouse strain C3H/HeJ which has both a hypo-responsiveness to LPS motifs and a higher susceptibility to S. Typhimurium. Positional cloning of Lps led to the identification of TLR4 as a positional candidate. The chicken homologue of TLR4 has been mapped to micro-chromosome 17 and cloned [54].

Several studies have attempted to determine whether SLC11A1 and TLR4 are involved in resistance variation to S. Typhimurium and S. Enteritidis. The survival rate of young chicks derived from a backcross between lines W1 and C and infected intra-muscularly one day post-hatch with S. Typhimurium was linked to SLC11A1 and TLR4, which, together, explained up to 33% of the differential resistance to infection [10, 54]. This effect was observed only during the first seven days post-infection. An effect of SLC11A1 on the early stages of systemic Salmonella infection using day-old chicks was confirmed in five groups of meat-type chickens [11] and in F1 progenies derived from crosses between a broiler line and Fayoumi or MHC-congenic lines [55, 56].

Since human Salmonella infection is mainly due to the consumption of eggs or meat from adult chickens, commercial egg-type chickens intravenously infected with S. Enteritidis have also been studied but at 13 weeks instead of at a young age [7]. Similarly, it has been demonstrated that a marker closely linked to SLC11A1 displayed a within-sire effect on liver and spleen load assessed early (three days post-infection), which confirms the possible involvement of SLC11A1 early in the process of systemic infection in these chicken lines, although infection occurred at an older age. Following bacterial contamination several weeks after infection is the only way of studying the Salmonella carrier-state. Thus, the potential role of SLC11A1 in later stages of the infection was demonstrated, firstly in mice inoculated with S. Enteritidis at 8-10 weeks with spleen bacterial counts, 42 days post-infection [57]. Interestingly, it seems that different SLC11A1 alleles were involved in early vs. late resistance. The same allele may be involved both in resistance to colonisation in early stages of the infection and in a high excretion rate in later stages. Similarly, an effect of SLC11A1 on spleen contamination was then demonstrated in chicken lines orally inoculated at peak of lay and slaughtered four weeks later [9], while in the same study the role of TLR4, although suspected, was not confirmed. More recently, the effect of the SLC11A1 locus was found significantly associated with carrier-state resistance variations in divergent chick lines [58].

In addition to these two genes, many genes related to immune response in chicken have been tested for their association with caecal or splenic load after S. Enteritidis challenge of one-day- to three-week-old chicks (Table 2; [11, 54, 55, 5963]). Other studies have focused on the antibody response to S. Enteritidis vaccination [6266]. These studies exploit either polymorphisms found in the gene itself (mainly SNP) or closely associated genetic markers. Most of these genes have been tested in progenies derived from crosses between White Leghorn MHC-congenic inbred lines and inbred Fayoumi lines. Such crosses between genetically distant parental lines are an efficient way of maximising genetic variation. However, genes identified in this way may be fixed in other populations, so that their interest for selection purposes needs to be validated.
Table 2

Physical and genetic positions of published loci for resistance to Salmonella in fowl.

Chr1

Locus type2

Locus name

Trait3

Position4cM

Mb

Ref

1

MSAT

ADL0160

ABR to SE vaccine

33

5.93

[15]

 

QTL

-

CSWB counts (SE)

85

33.57

[14]

 

QTL

-

CSWB counts (ST)

207

68.52

[14]

 

MSAT

ADL0020

ABR to SE vaccine

Splenic and caecal loads (SE)

286

94.16

[12]

[78]

 

CG

CD28

Caecal load; ABR to SE vaccine

-

113.90

[62]

 

MSAT

ADL0198

ABR to SE vaccine

Splenic and caecal load (SE)

458

171.74

[12]

[78]

 

CG

IAP1

caecal load (SE)

Splenic load (SE)

-

186.92

[11]

[55]

2

QTL

-

CSWB counts (SE)

87

26.93

[14]

 

CG

MD-2

Splenic load (SE)

-

122.83

[62]

 

MSAT

MCW0051

ABR to SE vaccine

358

129.15

[15]

3

MSAT

MCW0083

ABR to SE vaccine

51

13.99

[15]

 

MSAT

MCW0024

ABR to SE vaccine

237

-

[15]

 

CG

TGF-β4

Caecal load (SE)

-

18.29

[11]

 

CG

TGF-β2

Caecal load (SE)

ABR to SE

-

20.54

[11]

[66]

 

CG

Gal13

Caecal load (SE)

-

110.20

[60]

 

CG

Gal12

Caecal load (SE)

-

110.21

[60]

 

CG

Gal11

Caecal load (SE)

-

110.21

[60]

 

CG

Gal7

ABR to SE vaccine

-

110.25

[64]

 

CG

Gal3

ABR to SE vaccine

Caecal load (SE)

-

110.26

[60]

[64]

 

CG

Gal5

Spleen load (SE)

-

110.27

[60]

4

CG

TRAIL

Spleen and caecal load (SE)

-

9.67

[63]

 

CG

IL-2

Caecal load (SE)

-

55.26

[11]

5

QTL

-

CSWB counts (ST)

100

36.10

[14]

 

QTL

-

CSWB counts (SE)

111

39.28

[14]

 

QTL

QTL

SAL1

SAL1

Splenic load (ST)

Splenic load (ST)

157

-

53.24

54.00-54.80

[13]

[74]

 

MSAT

ADL0298

ABR to SE vaccine

Splenic and caecal load (SE)

198

60.23

[12]

[78]

 

CG

TGF-β3

Caecal load (SE)

-

40.87

[63]

6

MSAT

ADL0138

ABR to SE vaccine

Splenic and caecal load (SE)

56

10.09

[12]

[78]

 

CG

PSAP

Splenic and caecal loads (SE)

-

13.02

[11]

[55]

7

CG

SLC11A1

Survival rate (ST)

Splenic and liver loads (SE)

Splenic load (SE)

Splenic load (SE); number of contaminated organs

Splenic load (SE); ABR to SE vaccine

Caecal load (SE)

80

23.91

[10]

[7]

[55]

[9]

[61]

[79]

8

MSAT

ADL301

ABR to SE vaccine

80 EL

25.10

[15]

11

QTL

-

Caecal load (SE); CSWB counts

18

3.66

[14]

15

CG

IGL

Caecal load

ABR to SE vaccine

-

8.17

[11]

[63]

16

QTL

-

Caecal load

2

0.10

[14]

 

CG

MHC1

Splenic load (SE)

-

-

[55]

 

CG

MHC class I α1 domain

ABR to SE vaccine

-

0.04

[80]

 

CG

MHC class I α2 domain

ABR to SE vaccine

 

0.04

[80]

 

CG

MHC class I β1 domain

ABR to SE vaccine

 

0.06

[80]

17

CG

TLR4

Survival rate (ST)

Survival rate (ST)

Number of contaminated organs

-

4.06

[10]

[54]

[9]

 

MSAT

ADL0293

ABR to SE vaccine

26

6.39

[15]

19

CG

CASP1

Caecal load

-

0.64

[11]

 

CG

iNOS

Caecal load

-

9.17

[11]

26

CG

PIGR

Splenic and caecal loads

-

0.00

[59]

 

CG

MAPKAPK12

Splenic and caecal loads

-

2.35

[59]

 

CG

IL10

Splenic and caecal loads

-

2.37

[59]

28

MSAT

LEI0135

ABR to SE vaccine

0

0.18

[15]

1Chromosome

2CG: candidate gene; MSAT: microsatellite

3ABR: antibody response; CSWB: cloacal swabs; ST: S. Typhimurium; SE: S. Enteritidis

4Physical positions were obtained by searching the Ensembl Genome Browser http://www.ensembl.org/index.html with the original Accession Number given by the authors. QTL positions were calculated according to physical positions of flanking molecular marker.

Many genes have been identified in gene expression studies. Most of them are probably not directly responsible for the actual genetic variation between these lines, but they remain functional candidates until they are tested for their role in genetic variation. Genome-wide microarray studies have led to the identification of genes differentially expressed between different chicken lines infected with S. Enteritidis [3335, 67] or before/after infection with S. Enteritidis [31, 38, 68]. Other genes have been more specifically studied, such as for instance genes coding for cytokines [69, 70], Toll-like receptors [37, 71, 72] or innate immune response genes [39].

4. QTL analyses

Targeted candidate gene analyses have very rarely led to the complete unravelling of the heritable part of phenotypic variations. On the contrary, QTL analyses are designed to encompass the greatest part possible of the observed variability, with the inconvenience that the genomic regions identified are anonymous and often contain several hundred genes. Until now, few QTL studies have been carried out to identify genes for acute resistance or resistance to carrier-state in chicken (Table 1). The first QTL study of Salmonella resistance analysed data from a back-cross progeny produced from White Leghorn inbred lines ((61 × 15I) × 15I) and infected at two weeks of age with S. Typhimurium [13]. A major QTL controlling spleen bacterial load was identified on chromosome 5 and named SAL1. SAL1 was shown to be involved in bacterial clearance by macrophages [73]. Using a 6th generation backcross mapping population and high density SNP panels, the SAL1 locus was confirmed and its localisation was refined at a position between 54.0 and 54.8 Mb on the long arm of chromosome 5 [74]. This region spans 14 genes, including two very striking functional candidates: CD27-binding protein (Siva) and the RAC-alpha serine/threonine protein kinase homolog, AKT1 (protein kinase B, PKB). AKT1 is involved in cellular survival pathways, primarily by inhibiting apoptotic processes. Survival factors can suppress apoptosis in a transcription-independent manner by activating AKT1, which then phosphorylates and inactivates components of the apoptotic machinery. AKT1 can also activate NF-κB by regulating IκB kinase (IKK), resulting in transcription of pro-survival genes and stimulation of pro-inflammatory responses [75]. Hijacking of this pathway by the Salmonella effector protein SopB provides support for AKT as a plausible candidate gene for bacterial proliferation and its association with the susceptibility/resistance status of the host.

QTL for carrier-state resistance have been identified in one back-cross and one F2 progeny, both derived from the White Leghorn inbred lines 61 and N, infected at one week post-infection with either S. Typhiumurium (BC) or S. Enteritidis (F2) and assessed for their caecal and caecal lumen content bacterial loads two to six weeks later [14]. One genome-wise significant QTL on chromosome 2 and five chromosome-wise significant QTL on chromosomes 1, 5, 11 and 16 were identified (Table 2; Figure 1). Some QTL were specific to one of the two progenies studied (BC vs. F2), which can be attributed to differences in the progeny types, the serotypes used for infection, or the times of infection and phenotypic assessments. Different QTL were found for the caecal bacterial load and the caecal lumen bacterial load. Two of these QTL, on chromosomes 2 and 16, have recently been confirmed in a more targeted analysis of the same progeny [58]. Interestingly, two QTL on chromosomes 1 and 16 were validated in a completely different genetic background, i.e. lines derived from commercial chicken lines [58]. Thus, genetic studies conducted on experimental lines can be of potential interest for marker-assisted selection in commercial lines. Furthermore, two different sets of QTL and candidate genes have been confirmed in adult chickens and in chicks derived from the same commercial line, which strengthens the hypothesis of a genetic control of Salmonella carrier-state differing according to chicken's age previously formulated [16].
https://static-content.springer.com/image/art%3A10.1186%2F1297-9686-42-11/MediaObjects/12711_2009_Article_2440_Fig1_HTML.jpg
Figure 1

Physical map of published loci for resistance to Salmonella in fowl. Mapchart 2.1 software was used to draw this map [77]. Positions are indicated in Mb. QTL positions are indicated by plain black boxes to the right of chromosomes; their length was calculated to cover 20 cM centered on the QTL likelihood peak. ABR: antibody response; SE: Salmonella Enteritidis; ST: Salmonella Typhimurium.

Other studies have more specifically focused on the antibody response to S. Enteritidis vaccination. Associations were found between microsatellite markers and traits related to the antibody response to S. Enteritidis vaccination, from data obtained respectively from BC and F2 progenies derived from inbred lines selected for high/low antibody response and from F1 families derived from crosses between a broiler and either MHC-congenic White Leghorn lines or the Fayoumi line [15, 12]. Nevertheless, the significant microsatellites identified were not located in the same genomic regions. This could be due to genetic differences between the parental lines studied, but also to differences in the experimental conditions (Table 1). The time of assessment and possibly the vaccine used were different and may have influenced the outcome of infection.

5. Genomic organisation of Salmonella resistance loci

The different candidate genes, QTL and microsatellites significantly linked to Salmonella resistance are shown in Figure 1. These loci are located on 16 of the 38 autosomal chromosomes of the chicken genome. Microchromosomes are poorly represented, due to the lack of genetic markers and genome sequences in these regions. Genomic co-localisations reveal a possible common genetic background explaining variations for resistance under different experimental conditions. Genetic or physical co-localisations indicate the possibility of the co-localised loci being identical, although the possibility of close physical linkage between adjacent genes should obviously never be discarded. Three types of genetic co-localisations can be observed between the candidate genes and the Salmonella resistance QTL mentioned above. First, several co-localisations occur between QTL for antibody response-related traits [15] and candidate immune-response genes: two on chromosome 1, one on chromosome 3, and one on chromosome 6. Before the immunity-related genes can be considered as relevant candidates for the co-localising QTL, ideally they should be tested in the same conditions as the QTL with which they co-localise, i.e. in particular with the same phenotypic trait, in the same or similar progeny, using the same Salmonella serotype under the same infection or vaccination model. The absence of other potentially relevant candidates should also be verified in the QTL confidence intervals. Secondly, a cluster can be observed on chromosome 5, including two QTL for resistance to S. Enteritidis and S. Typhimurium [14], one QTL for the antibody response to S. Enteritidis vaccination [12], the QTL SAL1 and the TGF-β3 gene. It is theoretically possible that all these QTL are actually the same gene, although the refined SAL1 locus does not include TGF-β3[74]. The molecular cloning of SAL1, which is so far the QTL with the most important effect identified, would solve this question. Finally, a co-localisation involves the MHC on micro-chromosome 16 and a S. Enteritidis carrier-state QTL [14]. Due to the high density of immunity-related genes and to the poor recombination rate observed on this chromosome, identifying which gene is the causal gene at this QTL will not be easy.

Conclusion

Several candidate genes and QTL have been successfully identified as having roles in phenotypic variations related to Salmonella resistance. Despite the many differences in infection models and genetic materials used and in traits assessed, which make the comparison of these loci somewhat speculative, great progress has been achieved in the last few years to understand the genetic control of resistance to Salmonella. The diverse experimental conditions used lead to a complex sum of results, but allow a more complete description of the disease. Resistance to salmonellosis and Salmonella carrier state varies according to the chicken line under study, the chicken's age, and the trait assessed, and probably many other parameters which have not been studied yet. Comparisons of the different models used raise many questions. In particular, the genetic differences between acute and carrier-state resistance and the influence of the chicken's age on resistance are interesting theoretical issues which still need to be investigated thoroughly before selection is considered. The genomic regions carrying the candidate genes TLR4 and SLC11A1, the Major Histocompatibility Complex (MHC) and the QTL SAL1, identified using several infection models, are interesting candidates for more in-depth studies.

With the development of high-throughput technologies such as microarray expression analyses and RNA-seq [76], new-generation sequencing (NGS) technologies and high density SNP genotyping, a huge quantity of differentially expressed candidate genes and polymorphisms is already available, which should speed up the unravelling of the Salmonella resistance genetic mechanisms. The most limiting factors are and will clearly remain the frequent and inevitable lack of precision and reliability of phenotypic assessments and the poor density of genetic recombinations in the progenies under study, which both limit the precision of QTL localisation and fine-mapping. Another limiting step resides in the choice of the relevant differentially expressed genes to be tested for their involvement in genetic variation.

All these studies will no doubt lead to a large number of genes or genome regions involved in Salmonella resistance variation and extend our theoretical knowledge of the genetic control of this disease. However, for practical applications, i.e. to implement marker assisted selection in commercial populations, it will be important to identify which of these genes are the most important. The answer will vary according to the chicken population under study and the selection criteria used, which clearly is an obstacle to practical application. Genomic selection may soon settle this matter by the direct selection of resistance-related traits in populations under selection.

This new knowledge of the genetic architecture of Salmonella resistance in fowl, in addition to genomic selection, could soon lead to the selection of more resistant animals. Combined with other measures, it should contribute in reducing the spread of the disease in commercial flocks.

List of abbreviations used

MAS: 

Marker Assisted Selection

MHC: 

Major Histocompatibility Complex

QTL: 

Quantitative Trait Locus

SNP: 

Single Nucleotide Polymorphism.

Declarations

Authors’ Affiliations

(1)
INRA, UR83 Unité de Recherches Avicoles (URA)
(2)
Institute for Animal Health, Compton
(3)
INRA, UMR0444 Laboratoire de Génétique Cellulaire (LGC)
(4)
Roslin Institute and R(D)SVS, University of Edinburgh

References

  1. Brenner F, Villar R, Angulo F, Tauxe R, Swaminathan B: Salmonella nomenclature. J Clin Microbiol. 2000, 38: 2465-2467.PubMed CentralPubMedGoogle Scholar
  2. Bouvet P, Fougerat I, Guesnier F, Guibert F, K'ouas G, Lenormand P, Metz L, Ruckly C, Grimont P: Human salmonellosis surveillance in France: recent data from the national referee center. International Symposium on Salmonella and Salmonellosis; Ploufragran, France. 2002, 411-416.Google Scholar
  3. Prévost K, Magal P, Protais J, Beaumont C: Effect of genetic resistance of the hen to Salmonella carrier-state on incidence of bacterial contamination: synergy with vaccination. Vet Res. 2008, 39: 20-10.1051/vetres:2007058.View ArticlePubMedGoogle Scholar
  4. Lambert W, Knox C: The inheritance of resistance to fowl typhoid in chickens. Iowa State J Sci. 1928, 2: 179-187.Google Scholar
  5. Roberts E, Card L: Inheritance of resistance to bacterial infection in animals. Illinois Agric Exper Sta Bull. 1935, 419: 467-493.Google Scholar
  6. Berthelot F, Beaumont C, Mompart F, Girard-Santosuosso O, Pardon P, Duchet-Suchaux M: Estimated heritability of the resistance to cecal carrier state of salmonella enteritidis in chickens. Poult Sci. 1998, 77: 797-801.View ArticlePubMedGoogle Scholar
  7. Girard-Santosuosso O, Lantier F, Lantier I, Bumstead N, Elsen J-M, Beaumont C: Heritability of susceptibility to Salmonella enteritidis infection in fowls and test of the role of the chromosome carrying the NRAMP1 gene. Genet Sel Evol. 2002, 342: 211-219. 10.1186/1297-9686-34-2-211.View ArticleGoogle Scholar
  8. Beaumont C, Protais J, Guillot J, Colin P, Proux K, Millet N, Pardon P: Genetic resistance to mortality of day-old chicks and carrier-sate of hens after inoculation with Salmonella enteritidis. Avian Pathol. 1999, 28: 131-135. 10.1080/03079459994858.View ArticleGoogle Scholar
  9. Beaumont C, Protais J, Pitel F, Leveque G, Malo D, Lantier F, Plisson-Petit F, Colin P, Protais M, Roy PL, Elsen JM, Milan D, Lantier I, Neau A, Salvat G, Vignal A: Effects of two candidate genes on the Salmonella carrier-state in fowl. Poult Sci. 2003, 82: 721-726.View ArticlePubMedGoogle Scholar
  10. Hu J, Bumstead N, Barrow P, Sebastiani G, Olien L, Morgan K, D M: Resistance to salmonellosis in the chicken is linked to NRAMP1 and TNC. Genome Res. 1997, 7: 693-704.PubMedGoogle Scholar
  11. Kramer J, Malek M, Lamont S: Association of twelve candidate gene polymorphisms and response to challenge with Salmonella enteritidis in poultry. Anim Genet. 2003, 34: 339-348. 10.1046/j.1365-2052.2003.01027.x.View ArticlePubMedGoogle Scholar
  12. Kaiser M, Deeb N, Lamont S: Microsatellite markers linked to Salmonella enterica serovar Enteritidis vaccine response in young F1 broiler-cross chicks. Poult Sci. 2002, 81: 193-201.View ArticlePubMedGoogle Scholar
  13. Mariani P, Barrow P, Chang H, Groenen M, Negrini R, Bumstead N: Localization to chicken chromosome 5 of a novel locus determining salmonellosis resistance. Immunogenetics. 2001, 53: 786-791. 10.1007/s00251-001-0387-7.View ArticlePubMedGoogle Scholar
  14. Tilquin P, Barrow P, Marly J, Pitel F, Plisson-Petit F, Velge P, Vignal A, Baret P, Bumstead N, Beaumont C: A genome scan for quantitative trait loci affecting the Salmonella carrier-state in the chicken. Genet Sel Evol. 2005, 37: 539-561. 10.1186/1297-9686-37-6-539.PubMed CentralView ArticlePubMedGoogle Scholar
  15. Yunis R, Heller E, Hillel J, Cahaner A: Microsatellite markers associated with quantitative trait loci controlling antibody response to Escherichia coli and Salmonella enteritidis in young broilers. Anim Genet. 2002, 33: 407-414. 10.1046/j.1365-2052.2002.00890.x.View ArticlePubMedGoogle Scholar
  16. Beaumont C, Chapuis H, Protais J, Sellier N, Menanteau P, Fravalo P, Velge P: Resistance to Salmonella carrier state: selection may be efficient but response depends on animal's age. Genet Res. 2009, 91: 161-169. 10.1017/S0016672309000135.View ArticleGoogle Scholar
  17. DeVolt H, Quigley G, Byerly T: Studies of resistance to pullorum diseases in chickens. Poult Sci. 1941, 20: 339-341.View ArticleGoogle Scholar
  18. Hutt F, Crawford R: On breeding chicks resistant to pullorum disease without exposure thereto. Canad J Genet Cytol. 1960, 2: 357-370.View ArticleGoogle Scholar
  19. Hutt F, Scholes J: XIII. Breed differences in susceptibility to Salmonella pullorum. Poult Sci. 1941, 20: 342-352.View ArticleGoogle Scholar
  20. Prince W, Garren H: An investigation of the resistance of white leghorn chicks to Salmonella gallinarum. Poult Sci. 1966, 45: 1149-1153.View ArticlePubMedGoogle Scholar
  21. Smith H: The susceptibility of different breeds of chickens to experimental Salmonella gallinarum infection. Poultry Sci. 1956, 35: 701-705.View ArticleGoogle Scholar
  22. Bumstead N, Barrow P: Genetics of resistance to Salmonella typhimurium in newly hatched chicks. Br Poult Sci. 1988, 29: 521-529. 10.1080/00071668808417078.View ArticlePubMedGoogle Scholar
  23. Bumstead N, Barrow P: Resistance to Salmonella gallinarum, S. pullorum and S. enteritidis in inbred lines of chickens. Avian Dis. 1993, 37: 189-193. 10.2307/1591473.View ArticlePubMedGoogle Scholar
  24. Bumstead N, Millard B, Barrow P, Cook J: Genetic basis of disease resistance in chickens. Breeding for disease resistance in farm animals. Edited by: Owen J. 1991, Axford R: CAB InternationalGoogle Scholar
  25. Guillot J, Beaumont C, Bellatif F, Mouline C, Lantier F, Colin P, Protais J: Comparison of resistance of various poultry lines to infection by Salmonella enteritidis. Vet Res. 1995, 26: 81-86.PubMedGoogle Scholar
  26. Duchet-Suchaux M, Léchopier P, Marly J, Bernardet P, Delaunay R, Pardon P: Quantification of experimental Salmonella enteritidis carrier state in B13 leghorn chicks. Avian Dis. 1995, 39: 796-803. 10.2307/1592416.View ArticlePubMedGoogle Scholar
  27. Duchet-Suchaux M, Mompart F, Berthelot F, Beaumont C, Léchopier P, Pardon P: Differences in frequency, level and duration of cecal carriage between four outbred chicken lines infected orally with Salmonella enteritidis. Avian Dis. 1997, 41: 559-567. 10.2307/1592145.View ArticlePubMedGoogle Scholar
  28. Protais J, Colin P, Beaumont C, Guillot J, Lantier F, Pardon P, Bennejean G: Line differences in resistance to Salmonella enteritidis PT4 infection. Br Poult Sci. 1996, 37: 329-339. 10.1080/00071669608417864.View ArticlePubMedGoogle Scholar
  29. Lindell K, Saeed A, McCabe G: Evaluation of resistance of four strains of commercial laying hens to experimental infection with Salmonella enteritidis phage type eight. Poult Sci. 1994, 73: 757-762.View ArticlePubMedGoogle Scholar
  30. Kramer J, Visscher A, Wagenaar J, Boonstra-Blom A, Jeurissen S: Characterization of the innate and adaptive immunity to Salmonella enteritidis PT1 infection in four broiler lines. Veterinary Immunoland Immunopathol. 2001, 79: 219-233. 10.1016/S0165-2427(01)00261-6.View ArticleGoogle Scholar
  31. van Hemert S, Hoekman A, Smits M, Rebel J: Immunological and gene expression reponses to a Salmonella infection in the chicken intestine. Vet Res. 2007, 38: 51-63. 10.1051/vetres:2006048.View ArticlePubMedGoogle Scholar
  32. Vaughn L, Holt P, Moore R, Gast R, Anderson K: Crop immune response post-Salmonella Enteritidis challenge in eight commercial egg-layer strains and specific-pathogen-free White Leghorn chickens. Avian Dis. 2009, 52: 79-87. 10.1637/7982-040907-Reg.View ArticleGoogle Scholar
  33. van Hemert S, Hoekman A, Smits M, Rebel J: Gene expression responses to a Salmonella infection in the chicken intestine differ between lines. Vet Immunol Immunopathol. 2006, 114: 247-258. 10.1016/j.vetimm.2006.08.007.View ArticlePubMedGoogle Scholar
  34. Chiang H, Swaggerty C, Kogut M, Dowd S, Li X, Pevzner I, Zhou H: Gene expression profiling in chicken heterophils with Salmonella enteritidis stimulation using a chicken 44 K Agilent microarray. BMC Genomics. 2008, 9: 526-10.1186/1471-2164-9-526.PubMed CentralView ArticlePubMedGoogle Scholar
  35. Zhou H, Lamont S: Global gene expression profile after Salmonella enterica serovar enteritidis challenge in two F8 advanced intercross chicken lines. Cytogenet Genome Res. 2007, 117: 131-138. 10.1159/000103173.View ArticlePubMedGoogle Scholar
  36. Nerren J, Swaggerty C, Mackinnon K, Genovese K, He H, Pevzner I, Kogut M: Differential mRNA expression of the avian-specific toll-like receptor 15 between heterophils from Salmonella -susceptible and -resistant chickens. Immunogenetics. 2009, 61: 71-77. 10.1007/s00251-008-0340-0.View ArticlePubMedGoogle Scholar
  37. Abasht B, Kaiser M, Poel van der J, Lamont S: Genetic lines differ in Toll-like receptor gene expression in spleens of chicks inoculated with Salmonella enterica serovar Enteritidis. Poult Sci. 2009, 88: 744-749. 10.3382/ps.2008-00419.View ArticlePubMedGoogle Scholar
  38. Cheeseman J, Kaiser M, Ciraci C, Kaiser P, Lamont S: Breed effect on early cytokine mRNA expression in spleen and cecum of chickens with and without Salmonella enteritidis infection. Dev Comp Immunol. 2007, 31: 52-60. 10.1016/j.dci.2006.04.001.View ArticlePubMedGoogle Scholar
  39. Sadeyen J-R, Trotereau J, Protais J, Beaumont C, Sellier N, Salvat G, Velge P, Lalmanach A-C: Salmonella carrier-state in hens: study of host resistance by a gene expression approach. Microbes Infect. 2006, 8: 1308-1314. 10.1016/j.micinf.2005.12.014.View ArticlePubMedGoogle Scholar
  40. Swaggerty C, Kogut M, Ferro P, Rothwell L, Pevzner I, Kaiser P: Differential cytokine mRNA expression in heterophils isolated from Salmonella -resistant and -susceptible chickens. Immunology. 2004, 113: 139-148. 10.1111/j.1365-2567.2004.01939.x.PubMed CentralView ArticlePubMedGoogle Scholar
  41. Sadeyen J-R, Trotereau J, Velge P, Marly J, Beaumont C, Barrow P, Bumstead N, Lalmanach A-C: Salmonella carrier state in chicken: comparison of expression of immune response genes between susceptible and resistant animals. Microbes Infect. 2004, 6: 1278-1286. 10.1016/j.micinf.2004.07.005.View ArticlePubMedGoogle Scholar
  42. Bumstead N, Barrow P: Genetics of resistance to Salmonella typhimurium in newly hatched chicks. Br Poult Sci. 1998, 29: 521-529. 10.1080/00071668808417078.View ArticleGoogle Scholar
  43. Swaggerty C, Ferro P, Pevzner I, Kogut M: Heterophils are associated with resistance to systemic Salmonella enteritidis infections in genetically distinct chicken lines. FEMS Immunol Med Microbiol. 2005, 43: 149-154. 10.1016/j.femsim.2004.07.013.View ArticlePubMedGoogle Scholar
  44. Swaggerty C, Pevzner I, He H, Genovese K, Nisbet D, Kaiser P, Kogut M: Selection of broilers with improved innate immune responsiveness to reduce on-farm infection by foodborne pathogens. Foodborne Pathog Disease. 2009, 6: 777-783. 10.1089/fpd.2009.0307.View ArticleGoogle Scholar
  45. Swaggerty C, Pevzner I, Lowry V, Farnell M, Kogut M: Functional comparison of heterophils isolated from commercial broiler chickens. Avian pathol. 2003, 32: 95-102. 10.1080/0307945021000070769.View ArticlePubMedGoogle Scholar
  46. Kaiser M, Wing T, Lamont S: Effects of genetics, vaccine dosage, and postvaccination sampling interval on early antibody response to Salmonella enteritidis vaccine in broiler breeder chicks. Poult Sci. 1998, 77: 271-275.View ArticlePubMedGoogle Scholar
  47. Kaiser MG, Lakshmanan N, Wing T, Lamont SJ: Salmonella enterica serovar Enteritidis burden in broiler breeder chicks genetically associated with vaccine antibody response. Avian Dis. 2002, 46: 25-31. 10.1637/0005-2086(2002)046[0025:SESEBI]2.0.CO;2.View ArticlePubMedGoogle Scholar
  48. Bolder N, Janss L, Putirulan F, Wagenaar J: Resistance of broiler outbred lines to infection with Salmonella enteritidis. Avian Pathol. 2002, 31: 581-587. 10.1080/0307945021000024667.View ArticlePubMedGoogle Scholar
  49. Roy M-F, Malo D: Genetic regulation of host responses to Salmonella infection in mice. Genes Immun. 2002, 3: 381-393. 10.1038/sj.gene.6363924.View ArticlePubMedGoogle Scholar
  50. Vidal S, Tremblay M, Govoni G, Gauthier S, Sebastiani G, Malo D, Skamene E, Olivier M, Jothy S, Gros P: The Ity/Lsh/Bcg locus: natural resistance to infection with intracellular parasites is abrogated by disruption of the Nramp1 gene. J Exp Med. 1993, 182: 655-666. 10.1084/jem.182.3.655.View ArticleGoogle Scholar
  51. Girard-Santosuosso O: Partial conservation of the mammalian NRAMP1 syntenic group on chicken chromosome 7. Mamm Genome. 1997, 8: 614-616. 10.1007/s003359900515.View ArticlePubMedGoogle Scholar
  52. Hu J, Bumstead N, Burke D, FA PdL, Skamene E, Gros P, Malo D: Genetic and physical mapping of the natural resistance-associated macrophage protein 1 (NRAMP1) in chicken. Mamm Genome. 1995, 6: 809-815. 10.1007/BF00539010.View ArticlePubMedGoogle Scholar
  53. Hu J, Bumstead N, Skamene E, Gros P, Malo D: Structural organization, sequence, and expression of the chicken NRAMP1 gene encoding the natural resistance-associated macrophage protein 1. DNA Cell Biol. 1996, 15: 113-123. 10.1089/dna.1996.15.113.View ArticlePubMedGoogle Scholar
  54. Leveque G, Forgetta V, Morroll S, Smith A, Bumstead N, Barrow P, Loredo-Osti J, Morgan K, Malo D: Allelic variation in TLR4 is linked to susceptibility to Salmonella enterica serovar Typhimurium infection in chickens. Infect Imm. 2003, 71: 1116-1124. 10.1128/IAI.71.3.1116-1124.2003.View ArticleGoogle Scholar
  55. Lamont S, Kaiser M, Liu W: Candidate genes for resistance to Salmonella enteritidis colonization in chickens as detected in a novel genetic cross. Vet Immunol Immunopathol. 2002, 87: 423-428. 10.1016/S0165-2427(02)00064-8.View ArticlePubMedGoogle Scholar
  56. Liu W, Miller M, Lamont S: Association of MHC class I and class II gene polymorphisms with vaccine or challenge response to Salmonella enteritidis in young chicks. Immunogenetics. 2002, 54: 582-590. 10.1007/s00251-002-0495-z.View ArticlePubMedGoogle Scholar
  57. Caron J, Loredo-Osti J, Laroche L, Skamene E, Morgan K, Malo D: Identification of genetic loci controlling bacterial clearance in experimental Salmonella enteritidis infection: an unexpected role of Nramp1 (Slc11a1) in the persistence of infection in mice. Genes Immun. 2002, 196-204. 10.1038/sj.gene.6363850.Google Scholar
  58. Calenge F, Lecerf F, Demars J, Feve K, Vignoles F, Pitel F, Vignal A, Velge P, Sellier N, Beaumont C: QTL for resistance to Salmonella carrier state confirmed in both experimental and commercial chicken lines. Anim Genet. 2009, 40: 590-597. 10.1111/j.1365-2052.2009.01884.x.View ArticlePubMedGoogle Scholar
  59. Ghebremicael S, Hasenstein J, Lamont S: Association of interleukin-10 cluster genes and Salmonella response in the chicken. Poult Sci. 2008, 87: 22-26. 10.3382/ps.2007-00259.View ArticlePubMedGoogle Scholar
  60. Hasenstein J, Lamont S: Chicken gallinacin gene cluster associated with Salmonella response in advanced intercross line. Avian Dis. 2007, 51: 561-567. 10.1637/0005-2086(2007)51[561:CGGCAW]2.0.CO;2.View ArticlePubMedGoogle Scholar
  61. Liu W, Kaiser M, Lamont S: Natural resistance-associated macrophage protein 1 gene polymorphisms and response to vaccine against or challenge with Salmonella enteritidis in young chicks. Poult Sci. 2003, 82: 259-266.View ArticlePubMedGoogle Scholar
  62. Malek M, Hasenstein J, Lamont S: Analysis of chicken TLR4, CD28, MIF, MD-2, and LITAF genes in a Salmonella enteritidis resource population. Poult Sci. 2004, 83: 544-549.View ArticlePubMedGoogle Scholar
  63. Malek M, Lamont S: Association of INOS, TRAIL, TGF-beta2, TGF-beta3, and IGL genes with response to Salmonella enteritidis in poultry. Genet Sel Evol. 2003, 35: S99-S111. 10.1186/1297-9686-35-S1-S99.PubMed CentralView ArticlePubMedGoogle Scholar
  64. Hasenstein J, Zhang G, Lamont S: Analyses of five gallinacin genes and the salmonella enterica serovar Enteritidis response in poultry. Infect Immun. 2006, 74: 3375-3380. 10.1128/IAI.00027-06.PubMed CentralView ArticlePubMedGoogle Scholar
  65. Zhou H, Lamont S: Associations of six candidate genes with antibody response kinetics in hens. Poul Sci. 2003, 82: 1118-1126.View ArticleGoogle Scholar
  66. Zhou H, Lamont S: association of transforming growth factor beta genes with quantitative trait loci for antibody response kinetics in hens. Animal Genet. 2003, 34: 275-282. 10.1046/j.1365-2052.2003.01007.x.View ArticlePubMedGoogle Scholar
  67. van Hemert S, Hoekman A, Smits M, Rebel J: Early host gene expression responses to a Salmonella infection in the intestine of chickens with different genetic background examined with cDNA and oligonucleotide microarrays. Comp biochem physiol Part D Genomics Proteomics. 2006, 1: 292-299. 10.1016/j.cbd.2006.05.001.View ArticlePubMedGoogle Scholar
  68. Zhang S, Lillehoj H, Kim C, Keeler CJ, Babu U, Zhang M: Transcriptional response of chicken macrophages to Salmonella enterica serovar Enteritidis infection. Dev Biol (Basel). 2008, 132: 141-151.Google Scholar
  69. Kaiser M, Cheeseman J, Kaiser P, Lamont S: Cytokine expression in chicken peripheral blood mononuclear cells after in vitro exposure to Salmonella enterica serovar Enteritidis. Poult Sci. 2006, 85: 1907-1911.View ArticlePubMedGoogle Scholar
  70. Redmond S, Chuammitri P, Andreasen C, Palic D, Lamont S: Chicken heterophils from commercially selected and non-selected genetic lines express cytokines differently after exposure to Salmonella enteritidis. Vet Immunol Immunopathol. 2009, 132: 129-134. 10.1016/j.vetimm.2009.05.010.View ArticlePubMedGoogle Scholar
  71. Abasht B, Kaiser M, Lamont S: Toll-like receptor gene expression in cecum and spleen of advanced intercross line chicks infected with Salmonella enterica serovar Enteritidis. Vet Immunol Immunopathol. 2008, 123: 314-323. 10.1016/j.vetimm.2008.02.010.View ArticlePubMedGoogle Scholar
  72. Mackinnon K, He H, Nerren J, Swaggerty C, Genovese K, Kogut M: Expression profile of toll-like receptors within the gastrointestinal tract of 2-day-old Salmonella enteriditis -infected broiler chickens. Vet Microbiol. 2009, 137: 313-319. 10.1016/j.vetmic.2009.01.024.View ArticlePubMedGoogle Scholar
  73. Wigley P, Hulme S, Bumstead N, Barrow P: In vivo and in vitro studies of genetic resistance to systemic salmonellosis in the chicken encoded by the SAL1 locus. Microbes Infect. 2002, 4: 1111-1120. 10.1016/S1286-4579(02)01635-0.View ArticlePubMedGoogle Scholar
  74. Fife M, Salmon N, Hocking P, Kaiser P: Fine mapping of the chicken salmonellosis resistance locus (SAL1). Animal Genet. 2009, 40: 871-877. 10.1111/j.1365-2052.2009.01930.x.View ArticlePubMedGoogle Scholar
  75. Madrid L, Wang C, Guttridge D, Schottelius A, Baldwin A, Mayo M: Akt suppresses aptoptosis by stimulating the transactivation potential of the RelA/p65 subunit of NF-kappaB. Mol Cell Biol. 2000, 20: 1626-1638. 10.1128/MCB.20.5.1626-1638.2000.PubMed CentralView ArticlePubMedGoogle Scholar
  76. Wang Z, Gerstein M, Snyder M: RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet. 2009, 10: 57-63. 10.1038/nrg2484.PubMed CentralView ArticlePubMedGoogle Scholar
  77. Voorips R: MapChart: Software for the graphical presentation of linkage maps and QTLs. J Hered. 2002, 93: 77-78. 10.1093/jhered/93.1.77.View ArticleGoogle Scholar
  78. Kaiser MG, Lamont SF: Microsatellites linked to Salmonella enterica serovar Enteritidis burden in spleen and cecal content of young F-1 broiler-cross chicks. Poult Sci. 2002, 81: 657-663.View ArticlePubMedGoogle Scholar
  79. Kramer J, Visscher A, Wagenaar J, Cornelissen J, Jeurissen S: Comparison of natural resistance in seven genetic groups of meat-type chicken. Br Poult Sci. 2003, 44: 577-585. 10.1080/00071660310001616174.View ArticlePubMedGoogle Scholar
  80. Zhou H, Lamont S: Chicken MHC class I and II gene effects on antibody response kinetics in adult chickens. Immunogenetics. 2003, 55: 133-140. 10.1007/s00251-003-0566-9.View ArticlePubMedGoogle Scholar

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