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 American Journal of  
Food Science and Technology (AJFST)

Variation in Toll-Like Receptor 4 (TLR4) Gene in Chicken Genotypes and Its 
Association with Resistance to Attenuated Newcastle Virus 

Utip Benjamin Ekaluo1, Ekerette Emmanuel Ekerette1*, Benjamin Bendiwhobel Ushie1, Godwin Egbe John2,
Ekei Victor Ikpeme1

Volume 4 Issue 2, Year 2025
ISSN: 2834-0086 (Online)

DOI: https://doi.org/10.54536/ajfst.v4i2.6088
https://journals.e-palli.com/home/index.php/ajfst

Article Information ABSTRACT

Received: September 02, 2025

Accepted: October 05, 2025

Published: November 14, 2025

Newcastle disease (ND) remains a major constraint to poultry production, and genetic 
variation in immune-related genes may influence vaccine responsiveness. This study evaluated 
variation in the Toll-like receptor 4 (TLR4) gene among four chicken genotypes: normal 
feather (NFC), naked neck (NNC), frizzle feather (FFC), and exotic (EXC), and assessed 
their antibody responses to attenuated ND vaccination. A total of  100 day-old chicks were 
reared under uniform intensive management. Birds were vaccinated at two weeks of  age, 
with a booster administered one week later. Blood samples were collected 14 days post-
vaccination for determination of  haemagglutination inhibition (HI) titre. Genomic DNA 
was extracted from blood, and the TLR4 gene was PCR-amplified, sequenced, and analyzed 
for nucleotide and haplotype diversity, mismatch distribution, and phylogenetic relationships. 
Results showed significant differences in antibody titres among genotypes (p < 0.05), with 
FFC exhibiting the highest response, followed by NNC, NFC, and EXC. Genetic diversity 
analysis revealed the highest nucleotide diversity in FFC (π = 0.121) and lowest in EXC 
(π = 0.031), with haplotype diversity ranging from 0.822 (NNC) to 1.00 (NFC). Pairwise 
Fst and Gst values indicated low to moderate differentiation, and phylogenetic analysis 
showed admixture among genotypes, with two major clades. Mismatch distributions were 
multimodal and ragged, suggesting complex demographic histories. The findings indicate 
that indigenous genotypes, particularly FFC and NNC, combine higher genetic diversity 
with stronger antibody responses to ND vaccination. Polymorphisms in the TLR4 gene may 
contribute to enhanced immune competence, highlighting the potential of  these genotypes 
as genetic resources for breeding programmes aimed at improving disease resistance and 
sustainable poultry production.

Keywords

Antibody Response, Chicken 
Genotypes, Genetic Diversity, 
Newcastle Disease, Toll-Like 
Receptor 4

1 Department of  Genetics and Biotechnology, Faculty of  Biological Sciences, University of  Calabar, P.M.B. 1115 Calabar, Cross 
  River State, Nigeria
2 Department of  Microbiology, Faculty of  Biological Sciences, University of  Calabar, P.M.B. 1115 Calabar, Cross River State, Nigeria
* Corresponding author’s e-mail: ekerette.ekerette@unical.edu.ng

INTRODUCTION 
Poultry production plays a vital role in food security 
and livelihood in many parts of  the world, especially in 
developing countries, where it provides affordable animal 
protein and a steady source of  household income. Global 
consumption of  poultry meat has increased significantly 
in recent decades, driven by its relative affordability and 
nutritional value (Korver, 2023). However, this growth 
has been accompanied by increasing dependence on a 
limited number of  highly productive commercial breeds, 
leading to the marginalization of  indigenous chickens and 
a continual erosion of  avian genetic resources (Korver, 
2023; Senbeta & Keyata, 2024).
In Nigeria, chickens represent the most widely 
distributed poultry species, with an estimated population 
exceeding 166 million birds (FAO, 2007; Chikezie, 2021). 
Indigenous chickens, in particular, play a vital socio-
economic role in rural communities where they are 
often reared under traditional scavenging systems. Their 
ability to survive under harsh environmental conditions, 
resist endemic diseases, and thrive with minimal inputs 
makes them invaluable genetic resources for sustainable 
poultry production (Soglia et al., 2020; Xie et al., 2024; 

Ekerette et al., 2025a; Ushie et al., 2025). Despite their 
relatively low productivity compared to exotic breeds, 
indigenous chickens are recognized as reservoirs of  
important adaptive genes that can be exploited for 
genetic improvement (Ajayi, 2010; Kpomasse et al., 2023; 
Ekerette et al., 2025a, b).
Advances in molecular genetics now provide powerful 
tools for assessing genetic diversity, population structure, 
and candidate genes of  economic and adaptive 
importance (Nazari & Pourkazemi, 2023; Wu et al., 2025; 
Ekerette et al., 2025c). Increasing attention has been given 
to immune-related genes, as variation in these loci can 
influence resistance to infectious diseases. Newcastle 
disease (ND), caused by Newcastle disease virus (NDV), 
remains one of  the most economically devastating poultry 
diseases worldwide (Hu et al., 2022; Dharmayanti et al., 
2023; Efienokwu & Ekerette, 2024; Zereen et al., 2025). 
Although vaccination is routinely practiced, differences 
in immune response across chicken genotypes suggest 
that genetic background significantly influences vaccine 
efficacy (Chuwatthanakhajorn et al., 2023).
Toll-like receptors (TLRs) form a key part of  the 
innate immune system, recognizing pathogen-



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associated molecular patterns and initiating host defense 
mechanisms (Wicherska-Pawłowska et al., 2021; Chen et 
al., 2024). Among these, toll-like receptor 4 (TLR4) has 
been reported to play a crucial role in immune signaling 
against viral and bacterial infections (Olejnik et al., 2018; 
Kim et al., 2023). Polymorphisms in TLR4 may therefore 
account for differential resistance or susceptibility to 
infectious diseases, including ND. To better understand 
the genetic and immunological basis of  ND resistance, 
this study evaluated variation in the TLR4 gene among 
different chicken genotypes. It assessed their antibody 
response to Newcastle disease vaccination using the 
haemagglutination inhibition (HI) titre method. Together, 
these approaches provide insights into the genetic 
underpinnings of  immune competence in indigenous and 
exotic chicken populations.

MATERIALS AND METHODS
Location and Management Procedures
A total of  100 day-old chicks, comprising 25 birds each 
of  the normal feather (NFC), naked neck (NNC), frizzle 
feather (FFC), and exotic (EXC) genotypes, were used 
for the study. The birds were reared under an intensive 
management system at the Animal House of  the 
Department of  Genetics and Biotechnology, University 
of  Calabar, Nigeria. They were housed in standard cages 
with natural ventilation. Before arrival, the Animal House 
was fumigated with an organophosphate insecticide and 
disinfected with Dettol to minimize the risk of  disease 
outbreaks. The chicks were acclimatized for two weeks 
and provided with starter feed and water ad libitum 
during this period. After acclimatization, they were 
separated into four groups based on genotype and reared 
in distinct cages under uniform management conditions. 
The research was approved by the Research Ethics 
and Linkage Committee of  the Faculty of  Biological 
Sciences, University of  Calabar (approval number FBS/
RELC/2023/001).

Vaccination and Blood Sampling
At two weeks of  age, all birds were orally administered 
1 ml of  live attenuated Newcastle disease vaccine. 
Fourteen days post-vaccination, blood samples (1 ml 
per bird) were collected from the wing vein for antibody 
titre determination. Following a one-week interval, a 
booster vaccination was administered, and blood samples 
were again collected 14 days later for the second titre 
measurement.

Antibody Titre Measurement
Phosphate-buffered saline (PBS) was prepared with 
sodium chloride (8 g/L), potassium chloride (0.2 g/L), 
disodium hydrogen phosphate (1.15 g/L), and potassium 
dihydrogen phosphate (0.2 g/L) in 10 L of  distilled 
water (pH 7.3). Antibody levels were measured using the 
haemagglutination inhibition (HI) test with a two-fold 
serial dilution method, ranging from 10² to 10²⁵⁶. Serial 
dilutions were prepared in test tubes, followed by the 

addition of  1 ml of  antigen and 1 ml of  serum. Tubes 
were incubated at room temperature for one hour, and the 
antibody titre for each sample was recorded as the highest 
dilution showing visible inhibition of  haemagglutination 
(Efienokwu & Ekerette, 2024).

Extraction of  DNA
Genomic DNA was extracted from blood samples of  
10 birds per genotype at the Animal Science Molecular 
Genetics Laboratory, Department of  Animal Science, 
University of  Port Harcourt, Nigeria, using the Quick-
DNA MiniPrep Kit (Zymo Research, USA) following 
the protocol of  Ekerette et al. (2025c). To enhance lysis 
efficiency, beta-mercaptoethanol was added to the lysis 
buffer (500 μL per 100 ml). In brief, 200 μL of  blood 
was mixed with 800 μL of  lysis buffer in an Eppendorf  
tube, vortexed for 5 seconds, and incubated at room 
temperature for 10 minutes. The lysate was transferred 
to a Zymo-Spin column in a collection tube and 
centrifuged at 10,000 rpm for 1 min. After discarding 
the flow-through, the column was washed with 200 μL 
DNA pre-wash buffer and 500 μL g-DNA wash buffer, 
with centrifugation steps at 10,000 rpm for 1 min each. 
DNA was eluted with 50 μL elution buffer after a 
5-minute incubation and centrifugation at 15,000 rpm 
for 30 s. The purified DNA was stored at –20 °C until 
further use.

PCR Amplification and Sequencing of  TLR4 Gene
PCR amplification of  the TLR4 gene was performed 
using primers reported by Wu et al. (2014): forward: 
5′-AGTCTGAAATTGCTGAGCTCAAAT-3′ and 
reverse: 3′-GCGACGTTAAGCCATGGAAG-5′. Each 
25 μL PCR reaction contained: 2 μL genomic DNA, 
1 μL of  50 mM MgCl2, 1.5 μL of  2 mM dNTPs, 1.5 
μL of  10× PCR buffer, 0.4 μL of  each primer, 1 μL of  
STABVIDA proprietary Taq polymerase, and 17.2 μL 
double-distilled water. Amplification was performed in a 
GeneAmp® PCR System 9700 thermal cycler (Applied 
Biosystems, USA) under the following cycling conditions: 
initial denaturation at 95 °C for 5 min; 25 cycles of  
denaturation at 94 °C for 40 s, annealing at 54 °C for 45 
s, and extension at 72 °C for 1 min; with a final extension 
at 72 °C for 7 min. PCR products were purified using the 
ExoFast protocol. Sequencing of  purified PCR products 
was conducted on an ABI 3730×L sequencer (Applied 
Biosystems, USA). Each 20 μL sequencing reaction 
contained ~20 ng of  purified PCR product, 8 μL of  
BigDye Terminator Reaction Mix, 8 μL deionized water, 
and 2 μL primer. Cycling conditions included 25 cycles of  
96 °C for 10 s, 60 °C for 5 s, and 60 °C for 4 min.

Statistical Analysis
Data obtained from antibody titre measurements were 
subjected to analysis of  variance (ANOVA). Mean 
differences were separated using the least significant 
difference (LSD) test at 5% probability level. BioEdit 
software version 7.2.5 was used to view and edit the 



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sequences. Multiple sequence alignment of  all samples 
was performed using MEGA software (Tamura et al., 
2013). Estimation of  variations in the aligned regions, 
including nucleotide diversity (π) and haplotype diversity 
(Hd), was carried out using DnaSP version 5.1 (Rozas 
et al., 2017). The mismatch distribution of  the TLR4 
sequences from the chicken genotypes was also analyzed 
with DnaSP. A phylogenetic tree was reconstructed using 
MEGA X, and the visual display of  the tree was fine-
tuned using iTOL software.

RESULTS AND DISCUSSION
Anitbody Measurement 
The antibody titre measurements among the four chicken 

genotypes following Newcastle vaccination revealed 
significant differences (Figure 1). At the initial stage, the 
highest mean loge HI titre was observed in FFC (0.873 ± 
0.001), which was significantly higher (p <0.05) than the 
other genotypes. NNC (0.846 ± 0.001) and NFC (0.841 
± 0.001) did not differ significantly from each other but 
were lower than FFC. The lowest titre was recorded in 
EXC (0.816 ± 0.018), which was significantly different 
from the rest. At the final measurement, a similar pattern 
was observed. FFC maintained the highest titre (0.853 
± 0.001), followed by NNC (0.848 ± 0.027) and NFC 
(0.816 ± 0.018). EXC recorded the lowest titre (0.782 ± 
0.001d), which was significantly different from all other 
genotypes.

Figure 1: Mean antibody titre of  four chicken genotypes following vaccination with attenuated Newcastle vaccine

Genetic Diversity of  Four Chicken Genotypes 
The genetic diversity indices of  the four chicken 
genotypes revealed varying levels of  nucleotide and 
haplotype diversity (Table 1). The nucleotide diversity (π) 
ranged from 0.031 in EXC to 0.121 in FFC. The average 
number of  nucleotide differences (K) followed a similar 
trend, with the highest value recorded in FFC (14.978) and 

the lowest in EXC (4.689). Haplotype diversity (h) was 
generally high across the genotypes, with NFC showing 
the maximum value (1.00), reflecting complete haplotype 
diversity, while NNC had the lowest (0.822). The number 
of  haplotypes (H) also varied, ranging from 4 in NNC 
to 10 in NFC, with the overall population exhibiting 21 
haplotypes.

Table 1: Genetic diversity indices of  four chicken genotypes following vaccination with attenuated Newcastle vaccine

G
en

ot
yp

es

N
uc

le
ot

id
e 

di
ve

rs
ity

 (π
)

H
ap

lo
ty

pe
 

di
ve

rs
ity

 (h
) 

H
ap

lo
ty

pe
 

nu
m

be
r (

H
)

Va
ria

bl
e 

si
te

s 
(S

)

Se
qu

en
ce

 
co

ns
er

va
tio

n 
(%

)

Av
er

ag
e 

nu
m

be
r 

of
 n

uc
le

ot
id

e 
di

ffe
re

nc
es

 (K
)

N
um

be
r o

f 
re

co
m

bi
na

tio
n 

ev
en

ts
 (R

m
)

Ta
jim

a'
s 

D

NFC 0.058 ± 0.002 1.00± 
0.045

10.0 33.00 44.70 7.422 0 -1.933 (p 
<0.05)

NNC 0.055 ± 
0.0001

0.822 ± 
0.005

4.00 16.00 56.30 7.111 0 1.191 (p > 
0.10)

FFC 0.121 ± 0.001 0.978 ± 
0.003

9.00 58.00 42.00 14.978 3 -1.761 (p > 
0.05)



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The number of  variable sites (S) varied widely, from 15 in 
EXC to 58 in FFC, with the overall dataset containing 59 
variable sites. Sequence conservation percentages ranged 
from 42.0% (FFC) to 56.3% (NNC), with an overall 
conservation estimate of  37.6%. Recombination events 
(Rm) were absent in NFC and NNC but detected in FFC 
(3) and EXC (2), with a total of  3 events recorded. Tajima’s 
D values varied among the genotypes; they were negative 
in NFC (-1.933, p > 0.05), FFC (-1.761, p > 0.05), EXC 
(-0.791, p > 0.10), and in the overall population (-2.422, p > 
0.01), while NNC showed a positive value (1.191, p > 0.10).

Pairwise Genetic Differentiation among Four 
Chicken Genotypes
The pairwise differentiation indices among the four 
chicken genotypes showed variable levels of  genetic 
differentiation (Table 2). The Fst values ranged from 

-0.016 (NFC and FFC) to 0.153 (NNC and EXC). 
Negative Fst values observed in some comparisons 
(NFC and FFC, NFC and EXC, FFC and EXC) indicate 
negligible or no measurable differentiation, whereas the 
highest value between NNC and EXC (0.153) suggests 
greater differentiation. Similarly, the Gst values varied 
between -0.015 (FFC and EXC) and 0.091 (NNC 
and FFC), reflecting differences in genetic diversity 
partitioning among populations. The average number 
of  nucleotide substitutions per site (Dxy) ranged from 
0.033 (NFC and EXC) to 0.081 (NNC and FFC), while 
the net nucleotide divergence (Da) values were mostly 
low, ranging between -0.0002 (FFC and EXC) and 0.007 
(NNC and EXC, NFC and NNC). The average number 
of  nucleotide differences between populations (Kxy) 
followed the same trend, ranging from 3.580 (NFC and 
EXC) to 8.580 (NNC and FFC).

EXC 0.031 ± 0.000 0.933 ± 
0.006

8.00 15.00 54.70 4.689 2 -0.791 (p > 
0.10)

Overall 0.056 ± 
0.0003

0.935 ± 
0.001

21.00 59.00 37.60  6.028 3 -2.422 (p < 
0.01)

Table 2: Pairwise differentiation among four chicken genotypes following vaccination with attenuated Newcastle 
vaccine
Population 1 Population 2 Fst Gst Dxy Da Kxy
NFC NNC 0.112 0.047 0.061 0.007 6.490
NFC FFC -0.016 0.010 0.070 -0.002 7.420
NFC EXC -0.006 0.009 0.033 -0.0001 3.580
NNC FFC 0.06 0.091 0.081 0.006 8.580
NNC EXC 0.153 0.074 0.044 0.007 4.740
FFC EXC -0.005 -0.015 0.054 -0.0002 5.790

Mismatch Distribution
The mismatch distributions for each genotype and for the 
pooled dataset were multimodal and ragged, each showing 
multiple peaks rather than a single smooth peak (Figure 
2). Specifically, the NFC and NNC exhibited several small 
peaks across low-to-moderate pairwise differences. The 
FFC showed pronounced, sharp peaks that extended to 
larger pairwise differences, while the EXC also presented 
multiple distinct peaks at low-to-moderate differences. 
The combined distribution was similarly ragged and 
multimodal.

Phylogenetic Relationship among Chicken Genotypes 
Figure 3 presents the phylogenetic relationships of  each 
chicken genotype. Each genotype exhibited within-group 
variation, which contributed to the formation of  distinct 
sub-clades among the samples. This observed pattern 
confirms the presence of  genetic heterogeneity within 
the genotypes, as reflected in the subgrouping of  the 
samples.
The phylogenetic analysis of  all the chicken genotypes 
revealed the presence of  two major clades (Figure 4). 

The first clade contained a single sample from the 
FFC genotype, suggesting some degree of  genetic 
divergence within this variety. The second major clade 
comprised the remaining samples across all genotypes, 
which were intermixed rather than distinctly separated. 
Within this broader cluster, several sub-clades were 
observed, each containing a mixture of  different chicken 
genotypes. The clustering pattern indicated a high level 
of  genetic admixture among the genotypes, reflecting 
a close evolutionary relationship and limited genetic 
differentiation. Notably, the phylogenetic tree did not 
segregate the samples strictly according to their genotypes, 
implying possible gene flow or shared ancestry among the 
studied populations.

Discussion 
The present study examined the variation in the Toll-like 
receptor 4 (TLR4) gene among four chicken genotypes 
and its association with antibody response to Newcastle 
disease (ND) vaccination. The findings provide 
insights into the interplay between genetic diversity and 
immune competence in indigenous and exotic chickens. 



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Figure 2: Mismatch distribution of  the four chicken genotypes following vaccination with attenuated Newcastle 
vaccine. A. Normal feather chicken, B. Naked neck chicken, C. Frizzle feather chicken, D. Commercial chicken, and 
E. All genotypes 

Figure 3: Phylogenetic trees of  the four chicken genotypes following vaccination with attenuated Newcastle vaccine. 
A. Normal feather chicken, B. Naked neck chicken, C. Frizzle feather chicken, and D. Commercial chicken  



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Significant differences in haemagglutination inhibition 
(HI) titres were observed among the genotypes, with 
FFC consistently showing the highest titres, followed by 
NNC, NFC, and EXC. This pattern suggests that FFC 
possess enhanced humoral immune responsiveness to 
ND vaccination. Previous studies have demonstrated that 
genetic background influences vaccine-induced antibody 
production, likely due to differences in innate immune 
gene expression and antigen recognition efficiency (Linnik 
et al., 2016; Clemente-Suárez et al., 2025). The relatively 
lower titres observed in EXC may reflect reduced adaptive 
immune responsiveness, possibly due to long-term 
selective breeding for production traits (Seo et al., 2017; 
Fu et al., 2023) at the expense of  immunocompetence. 
The higher titres in indigenous genotypes highlight their 
potential as reservoirs of  adaptive genes (Soglia et al., 
2020; Xie et al., 2024) that can enhance disease resistance 
in breeding programmes.
Analysis of  genetic diversity indices revealed substantial 
variation among the genotypes. FFC exhibited the 
highest nucleotide diversity and average number of  
nucleotide differences, while EXC showed the lowest 
diversity. High haplotype diversity in NFC indicates the 
presence of  multiple unique allelic variants, which may 
enhance population resilience to infectious agents. These 
findings align with previous reports that indigenous 
chickens harbor considerable genetic variation due to 
their adaptation to variable environments and minimal 
human-directed selection (Soglia et al., 2020; Xie et 
al., 2024; Ekerette et al., 2025a). Conversely, reduced 
genetic diversity in EXC is consistent with intensive 
selective breeding practices aimed at improving growth 
and productivity, which can inadvertently limit genetic 
variation related to immunity.

Pairwise Fst and Gst values indicated low to moderate 
genetic differentiation among genotypes, with negative 
Fst values in some comparisons suggesting negligible 
divergence. The highest differentiation was observed 
between NNC and EXC, reflecting the evolutionary and 
breeding history of  these populations. The phylogenetic 
analysis further supported this observation, revealing 
two major clades with extensive admixture among most 
genotypes, except for one divergent FFC sample. This 
pattern indicates ongoing gene flow or shared ancestry 
and underscores the lack of  strict genetic isolation among 
the studied populations. Such admixture is consistent 
with traditional poultry management systems, where 
crossbreeding between indigenous and exotic birds is 
common (Wilkinson et al., 2012; Vargas et al., 20219).
The multimodal mismatch distributions observed across 
genotypes suggest complex demographic histories, 
such as selective pressures (Hoelzer et al., 2008). The 
pronounced peaks in FFC indicate higher genetic 
variability, consistent with the nucleotide and haplotype 
diversity data. Conversely, the relatively lower peaks in 
EXC suggest a more uniform genetic structure, likely 
resulting from artificial selection and limited effective 
population size (Fu et al., 2023).
TLR4 plays a critical role in innate immune signaling 
by recognizing pathogen-associated molecular patterns, 
including viral components, and initiating inflammatory 
responses (Olejnik et al., 2018; Kim et al., 2023). 
Polymorphisms in TLR4 may modulate the strength and 
efficiency of  immune responses, influencing susceptibility 
or resistance (Noreen et al., 2012), with no exception 
to NDV. Therefore, the observed variation in TLR4 
sequences, combined with differential antibody titres, 
suggests a potential association between specific TLR4 

Figure 4: Phylogenetic tree showing the relationship between four chicken genotypes following vaccination with 
attenuated Newcastle vaccine. Each genotype is indicated by a different colour legend, while the major clades are 
shown with separate branch colours.



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alleles and enhanced ND vaccine responsiveness. FFC and 
NNC, which exhibited higher titres, also displayed higher 
nucleotide diversity and multiple haplotypes, supporting 
the hypothesis that TLR4 variation contributes to immune 
competence. The findings emphasize the importance 
of  preserving and utilizing indigenous chicken genetic 
resources for sustainable poultry production. High 
genetic diversity and favorable immune responses in 
FFC and NNC highlight their potential for inclusion in 
selective breeding programmes aimed at improving ND 
resistance. In contrast, the low diversity and reduced 
antibody responses in EXC highlight the potential 
vulnerability of  highly selected commercial lines to 
infectious diseases. Incorporating TLR4 genotyping into 
breeding programmes could provide a molecular tool for 
selecting birds with superior innate and adaptive immune 
competence, thereby enhancing disease resilience.

CONCLUSION
This study revealed genotype-specific differences in TLR4 
diversity and immune response to Newcastle disease 
vaccination. Frizzle feather (FFC) and naked neck (NNC) 
chickens exhibited the highest antibody titres and greater 
genetic diversity, while exotic (EXC) chickens showed 
the lowest titres and least diversity. Phylogenetic analysis 
indicated genetic admixture across genotypes, with only 
one divergent FFC sample. These findings suggest that 
TLR4 polymorphisms contribute to enhanced disease 
resistance in indigenous chickens, underscoring their 
value as genetic resources for breeding programmes 
aimed at improving Newcastle disease resilience.

Acknowledgments
The authors wish to acknowledge Prof. Brillant 
Ogagaoghene Agaviezor of  the Department of  Animal 
Science, University of  Port Harcourt, Nigeria, for the 
technical support he provided that culminated in the 
success of  this research. We also sincerely appreciate the 
Tertiary Education Trust Fund (TETfund) for funding 
this research.

Conflict of  interest
The authors declare that there is no existing conflict of  
interest.

Funding
This research was funded by the Tertiary Education Trust 
Fund (TETfund) under the reference
number: TETFUND Year(s) 2019-2024 (Merged) Batch 
9/13.

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