Abstract
Simple Summary
Avian influenza is a serious threat to chickens in comparison to ducks
which are more resilient to most virus strains. Today, it is still not
completely understood why ducks have more effective inflammatory immune
responses. To this extent, the consideration of coincident SNPs
(coSNPs) is crucial to unravel genetic programs underlying the
susceptibility/resistance of both species to avian influenza.
Therefore, our aim is to investigate the differing causal effects of
coSNPs on avian-influenza-induced genes, thereby revealing the effector
molecules and signaling pathways that mediate an effective immune
response after viral infection in ducks and that lead to the disease in
chickens.
Abstract
Avian influenza is a severe viral infection that has the potential to
cause human pandemics. In particular, chickens are susceptible to many
highly pathogenic strains of the virus, resulting in significant
losses. In contrast, ducks have been reported to exhibit rapid and
effective innate immune responses to most avian influenza virus (AIV)
infections. To explore the distinct genetic programs that potentially
distinguish the susceptibility/resistance of both species to AIV, the
investigation of coincident SNPs (coSNPs) and their differing causal
effects on gene functions in both species is important to gain novel
insight into the varying immune-related responses of chickens and
ducks. By conducting a pairwise genome alignment between these species,
we identified coSNPs and their respective effect on AIV-related
differentially expressed genes (DEGs) in this study. The examination of
these genes (e.g., CD74, RUBCN, and SHTN1 for chickens and ABCA3,
MAP2K6, and VIPR2 for ducks) reveals their high relevance to AIV.
Further analysis of these genes provides promising effector molecules
(such as I
[MATH: κ :MATH]
B
[MATH: α :MATH]
, STAT1/STAT3, GSK-3
[MATH: β :MATH]
, or p53) and related key signaling pathways (such as NF-
[MATH: κ :MATH]
B, JAK/STAT, or Wnt) to elucidate the complex mechanisms of immune
responses to AIV infections in both chickens and ducks.
Keywords: single nucleotide polymorphism, coincident SNP, avian
influenza, chicken, duck, gene regulation, differentially expressed
genes, orthologous variant, downstream, effector, coSNP
1. Introduction
The awareness of potential zoonotic diseases has recently increased and
various strains of avian influenza have had more attention from the
general public due to their ongoing effect on the poultry industry. To
stress the risks and dangers of avian influenza viruses (AIVs), the
World Health Organization closely surveys major events and deaths
related to the H5N1 strain of AIV and has reported 868 cases and 457
deaths due to human infections to date [[38]1]. However, the relevance
of influenza diseases goes beyond human spread and is most severe in
domesticated Galliformes species, such as chickens. According to the
latest overview of the European Food Safety Authority, the ongoing
European avian influenza epidemic during the influenza seasons of 2021
and 2022 amounted to a total of 2520 outbreak detections of highly
pathogenic avian influenza viruses (HPAIVs) in poultry accompanied by
50 million cullings [[39]2]. AIVs belong to the Orthomyxoviridae family
of negative-sense RNA viruses. Subtypes, defined by the surface
proteins hemagglutinin (H) and neuraminidase (N), notably include H5
and H7 strains that can evolve into highly pathogenic forms in
gallinaceous poultry which are able to systemically replicate [[40]3].
In contrast to chickens, waterfowl, and typically wild birds such as
mallard ducks, are less prone to most AIV infections and often show no
or mild signs of clinical disease due to stronger inflammatory
responses. Methods of transmission are primarily via contact with
infected birds, their excretions, or through contaminated water and
feed. Immune responses also vary between species. For example, rapid
apoptosis induction during HPAIV infection in ducks and delayed
induction in chickens can influence the efficiency of viral infection
control [[41]4].
In recent decades, researchers have, therefore, made an extensive
effort towards understanding AIV disease progression in chickens and
ducks to investigate the causes of disease susceptibility and
resistance. A considerable number of comparative analyses regarding the
genetic repertoire, gene functions, and evolutionary selection related
to immune responses in different bird species, including chickens and
ducks, have been performed and published
[[42]5,[43]6,[44]7,[45]8,[46]9,[47]10,[48]11,[49]12,[50]13,[51]14,[52]1
5,[53]16,[54]17,[55]18,[56]19,[57]20,[58]21]. In this regard, pattern
recognition receptors (PRRs) have been put in the spotlight due to
their rapid initiation of immune responses to pathogens such as AIVs
[[59]7,[60]10,[61]22]. In particular, the susceptibility of chickens
can be partly explained by their lack of the retinoic acid-inducible
gene I (RIG-I) and the RIG-I binding protein RNF135
[[62]7,[63]9,[64]11,[65]22,[66]23,[67]24,[68]25,[69]26,[70]27].
However, the absence of RIG-I in chickens is partly compensated for by
the RIG-I-like receptor (RLR) MDA5 which is adapted in chickens to
target small dsRNA [[71]9,[72]23,[73]24,[74]27]. In an effort to
comprehend the underlying gene activities and pathways induced by AIVs,
several studies conducted gene expression analyses in infected chickens
and ducks
[[75]3,[76]9,[77]10,[78]11,[79]12,[80]13,[81]14,[82]15,[83]23,[84]24,[8
5]25,[86]26,[87]27,[88]28,[89]29,[90]30,[91]31,[92]32,[93]33,[94]34,[95
]35,[96]36,[97]37,[98]38,[99]39,[100]40,[101]41]. While the
host–pathogen interaction of AIVs is highly complex and nuanced,
differing between pathogen and species, recent advances have shed some
light on the mechanisms behind the immune responses of chickens and
ducks [[102]22]. For this purpose, Ranaware et al. [[103]28] showcased
the relation of disease severity to a strong up-regulation of gene
expression of interferons (IFNs), pro-inflammatory cytokines and
chemokines as well as IFN-stimulated genes (ISGs) during H5N1 HPAIV
infection in lung in chickens and observed a lack of this expression
during low pathogenic AIV (LPAIV) H9N2 infection. To further emphasize
the complex transcriptomic signature, Wang et al. [[104]34] observed
high expression of miRNAs and moderate gene expression during LPAIV
H5N3 infection in lung tissue of broilers and also highlighted the
importance of miRNA for the regulation of genes. In contrast to
chickens, ducks typically induce effective inflammatory responses to
most AIV strains. This is demonstrated by the findings of Campbell et
al. [[105]41], who studied the tissue-specific responses of ducks
during HPAIV H5N1 and LPAIV H5N2 infection, in which robust and high
gene expression was observed. Specifically, they highlight the strong
early response of PRRs and ISGs in duck tissues combined with a
decrease in expression of proinflammatory cytokines in the lung and key
components of leukocyte recruitment and complement pathways in the
intestine [[106]41]. For comprehensive overviews of differential gene
expression and innate immunity related to AIV infection in chickens and
ducks, we refer to [[107]6,[108]7,[109]8,[110]22].
While the majority of studies on AIVs have focused on either chickens
or ducks, there were also experiments conducted on both bird species
under the same conditions that permit their direct comparison
[[111]3,[112]42,[113]43,[114]44,[115]45,[116]46]. For example,
Cornelissen et al. [[117]46] discussed the innate immune responses of
LPAIV H7N1 in chickens and ducks and highlighted differences in gene
expression such as the observation of a correlation of Toll-like
receptor 7 and MDA5 responses to IFN-
[MATH: α :MATH]
and IFN-
[MATH: β :MATH]
in chickens and its absence in ducks. Other studies focused on
exploring immune-related genes during HPAIV infection
[[118]42,[119]43,[120]44,[121]45]. Hu et al. [[122]43] demonstrated
that PA-X decreases virulence of H5N1 by inhibiting viral replication
and observed stronger expression of cytokines in the hearts and brains
of ducks than in lungs and spleens, whereas the expression was evenly
spread in chickens. Another related study was conducted by Smith et al.
[[123]3] who performed transcriptome analysis and inspected the
relevance of IFN-induced transmembrane proteins and their evolutionary
selection for AIV defense in chickens and ducks. Continuing on the
study by Smith et al. [[124]3], Klees et al. [[125]47] further
investigated the dataset and conducted upstream analysis on the
differentially expressed genes (DEGs) with a focus on the effective
immune response of ducks during HPAIV infection. The findings of Klees
et al. [[126]47] put an emphasis on the regulatory motifs that control
the gene expression in ducks to curb disease progression and failed to
achieve this in chickens. Among other regulatory factors, the
importance of EGR1, FOS, SRF, SP1, EP300, RUNX2, MYC, SMAD3, SMAD4, and
ETS1 were discussed for regulatory processes in chickens and ducks.
Another fundamental aspect to systematically explore genetic programs
during AIV progression in both species is the consideration of
coincident single nucleotide polymorphisms (coSNPs) that occur at
orthologous positions [[127]48]. Due to their orthologous positions in
the genomes of species, coSNPs should presumably have a similar impact
on genes or their protein products, e.g., being disruptive or
non-disruptive. An illustration of the context of coSNPs in chickens
and ducks is shown in [128]Figure 1. While a variety of studies have
been published using coSNPs to study evolutionary processes
[[129]48,[130]49,[131]50,[132]51,[133]52,[134]53,[135]54,[136]55],
recent studies employed coSNPs to identify genetic mechanisms related
to functional variants across different species including humans,
chimpanzees or livestock [[137]56,[138]57,[139]58]. Given the
importance and availability of SNP markers in breeding, investigating
coSNPs and their differing causal impacts on gene functions could be
promising for gaining greater insight into disease resistance or
susceptibility and finding suitable genetic targets.
Figure 1.
[140]Figure 1
[141]Open in a new tab
An illustration of a coincident SNP (coSNP) in chickens and ducks.
Reference sequences from chickens and ducks are arranged in a sequence
alignment block. The centre position of this alignment, highlighted by
(*), shows the occurrence of a coSNP, which is localized at the
orthologous position.
Despite a rich literature on AIV progression in chickens and ducks, the
importance and potential of coSNPs for cross-species comparisons to
decipher the different immune-related functions underlying AIV
infection in both species has not yet been extensively studied. To
address the limited knowledge available on the causal effects of coSNPs
in association with AIV progression in chickens and ducks, we aim to
analyze the biological functions of the related genes harboring coSNPs
for the identification of affected downstream pathways and effector
molecules in this study. We initially conducted pairwise genome
alignments to identify orthologous regions, which were subsequently
used for the determination of the coSNPs. By applying the SnpEff tool
[[142]59], the potential impact of coSNPs on gene functions was
examined in chickens and ducks. Based on the results, we generated
lists of candidate genes by incorporating their different expression
patterns during AIV infection for each species. Finally, we revealed
the relevant downstream effectors that significantly influence the
activation and regulation of various downstream signaling pathways.
These findings could be promising to elucidate the complex mechanisms
of immune responses to AIV infections in both chicken and duck
populations and to further design novel hypotheses and potential
targets for breeding objectives as well as therapeutic strategies.
2. Materials and Methods
In this section, we describe the data set analyzed and methods applied,
starting with the identification of coSNPs and followed by an SNP
effect prediction and a downstream analysis of the affected genes. An
overview of our analysis workflow is given in [143]Figure 2.
Figure 2.
[144]Figure 2
[145]Open in a new tab
Overview of the workflow applied in this study. First, (a) the chicken
and duck genomes are aligned and (b) orthologous variants (coSNPs) are
identified. Second, (c) the effect of coSNPs on genes is predicted
using SnpEff [[146]59] and (d) filtered for differentially expressed
genes (DEGs) during avian influenza virus (AIV) infection. Lastly, (e)
downstream effectors are predicted based on the involved signaling
pathways.
The implementation of the coSNP identification pipeline and the
subsequent analysis steps are provided as python and R scripts in
[147]Supplementary File S1 to guarantee reproducibility.
2.1. Genome Data
In our study, we incorporated publicly available genomic data for
chickens and ducks, including gene and variant annotations for the
assemblies GRCg7b, CAU_duck1.0, and BGI_duck_1.0, which are provided by
Ensembl release 109 [[148]60]. Duck SNPs were obtained from Genome
Variation Map [[149]61] annotated to the BGI_duck_1.0 duck assembly due
to the sparsity of public collections of variants in ducks.
2.2. Identification of coSNPs
To identify coSNPs, localized at orthologous genomic positions of
chickens and ducks, we followed the methodology of Zhao et al.
[[150]57]. Our analysis pipeline consists of the following three steps:
* Lift over: Following the nf-LO workflow by Talenti and Prendergast
[[151]62], we aligned the genomes BGI_duck_1.0 and CAU_duck_1.0
with the LAST alignment program [[152]63] where fitting alignment
parameters were estimated by the last-train program [[153]64].
Afterward, bijective chain files, e.g., unique alignment blocks in
both genome versions, were created and assembled to nets with
axtChain, chainNet and netChainSubset from UCSC [[154]62,[155]65].
Finally, SNP annotations were lifted over by using CrossMap
[[156]66] to obtain remapped SNP annotations for the CAU_duck_1.0
genome. Although the variant data and genome annotations of
chickens have been annotated to the same genome (GRCg7b), it is
noteworthy that the genomic coordinates for SNP data of ducks had
to be lifted over from BGI_duck_1.0 (a scaffold assembly) to
CAU_duck1.0 (chromosome-level assembly) to fit the preceding DEG
annotations.
* coSNP localization: The same lift-over procedure was repeated for
discovering orthologous positions between the chicken genome GRCg7b
and the duck genome CAU_duck1.0. The resulting positional and
chromosomal information was used to localize genome-wide coSNPs (as
illustrated in [157]Figure 1). In summary, using a total of
4,393,763 duck and 20,066,289 chicken SNPs, we were able to
localize 84,898 coSNPs of which 37,242 were located in 7387 unique
duck and 7398 unique chicken genes. The list of identified coSNPs
is given in [158]Supplementary Table S1.
* SNP effect prediction: We have applied the SnpEff tool [[159]59]
considering the databases of the latest Ensembl release (109)
[[160]60] to predict the potential impact of coSNPs on gene
functions in chickens and ducks, respectively. For this analysis
step, we manually built the SnpEff database using the build command
for the chicken genome GRCg7b and the duck genome CAU_duck1.0 and
their respective gtf gene annotations. The genome-wide functional
classification of coSNPs by SnpEff includes: (i) low impact
variants such as synonymous variants; (ii) moderate impact variants
such as non-disruptive variants that can change protein
effectiveness; (iii) high impact variants such as disruptive
variants that can cause loss of function [[161]67]. The
consequences of coSNPs on the genes and their transcripts in both
bird species are likely to provide valuable insight into
understanding the disease progression of avian influenza. Among all
the genes in chickens and ducks that contain a coSNP, 390 and 469
genes were impacted by at least one moderate or high consequence,
respectively. A detailed overview of the coSNP consequences is
given in [162]Supplementary Table S2.
2.3. Identification of Candidate Genes
To focus on the potentially divergent effect of coSNPs on downstream
mechanisms in chickens and ducks, we consider the transcriptome data of
Smith et al. [[163]3] sampled during avian influenza disease
progression. The related experiments were conducted on 20 white leghorn
chickens and 20 domestic gray mallards focusing on the differences in
the gene expression response to HPAIV H5N1 and LPAIV H5N2 by
considering lung and ileum tissues sampled at one and three days
post-infection (dpi) including mock infections and three biological
replicates for each condition. Klees et al. [[164]47] used this data
set to identify DEGs between the experimental and control groups across
two tissues in both chickens and ducks by setting the significance
thresholds as |
[MATH:
log2 :MATH]
fold change| > 0.58 and the false discovery rate (FDR) adjusted p-value
< 0.05. They further identified the upstream regulators through a
comparative assessment of disease progression. For more information on
the experimental design and data analysis of DEGs, we refer to the
original study by Smith et al. [[165]3] and the study by Klees et al.
[[166]47].
To construct our candidate gene lists, a list of 2345 DEGs was obtained
from Klees et al. [[167]47] where all DEGs from all experimental
conditions in ducks were merged into a large set of regulated genes as
a response to AIV infection (see [168]Supplementary Table S3). We
assume that the regulation and involved pathways of these DEGs induce a
rapid and effective response in ducks because we observed a lack of
DEGs in almost all experimental conditions in chickens. This sparsity
of DEGs in chickens during AIV infection was already discussed by Klees
et al. [[169]47]. Therefore, we only considered DEGs in ducks and their
orthologous genes in chickens for our comparison. Analogous to Klees et
al. [[170]47], orthologs were retrieved from BioMart web services
[[171]68]. Finally, following the methodology by Vijayakumar et al.
[[172]67], we filtered our candidate gene lists in chickens and ducks
separately based on a moderate or high impact classification predicted
by SnpEff [[173]59]. Thus, the final gene lists for chickens and ducks
contain 69 and 49 genes, respectively, of which 35 orthologs are
common. The gene lists are given in [174]Supplementary Files S2 and S3.
2.4. Downstream Effector Analysis
To gain more insight into the functional role of candidate genes in the
initiation, modulation, and resolution of immune responses to AIVs, we
identified key signaling pathways and effector molecules using
candidate genes for both chickens and ducks. Effectors are crucial
signaling molecules that act as end products located several steps
downstream and regulate the function of numerous signaling cascades
[[175]69]. In the context of AIVs, exploring and understanding the role
of effectors in association with coSNPs and their corresponding
candidate genes could provide important knowledge for unraveling
effective or perturbed immune responses. Similar to the previous study
by Rajavel et al. [[176]69], we performed an effector molecule search
for both the chicken and the duck gene list on the bioinformatics
platform geneXplain [[177]70] using the TRANSPATH ^® database
[[178]71]. Recommended parameters of the effector search workflow were
set according to Rajavel et al. [[179]69] with a maximum search radius
of 10, a FDR adjusted p-value
[MATH: <0.05 :MATH]
and a z-score
[MATH: >1.0 :MATH]
. Furthermore, we employed a pathway enrichment search using the
Reactome database [[180]72] and an FDR adjusted p-value
[MATH: <0.05 :MATH]
to check if a pathway is mainly affected by our genes.
3. Results and Discussion
In this study, we conducted an investigation into the effects of coSNPs
by analyzing their causal impact on genes associated with resistance or
susceptibility to AIV infection in both chickens and ducks. Our
methodology involved performing pairwise genome alignments for both
species and identifying the orthologous genomic regions containing
coSNPs. These regions were then evaluated for their potential impact on
gene functions using the SnpEff tool [[181]59]. Subsequently, we
generated a list of candidate genes for each species, which were
filtered based on their differential gene expression patterns in lung
and ileum tissues during AIV infection. The corresponding downstream
pathways and effectors of the candidate genes affected by coSNPs might
be promising targets that restrict avian influenza disease progression
in ducks or alleviate disease progression in chickens.
This section is split into four parts. The first part explores and
highlights the different effects of coSNPs to gain insight into the
candidate gene lists. In the second part, we briefly present an
overview of the results of the downstream analysis. In the third part,
we contrast the enriched pathways of chickens and ducks to elaborate on
the background of the affected genes. Finally, we performed a
downstream effector analysis to identify the most important molecules
that act in the downstream signaling cascades which might be affected
by coSNPs.
3.1. Effects of coSNPs
In our analysis, we identified 49 candidate genes in ducks and 69
candidate genes in chickens, with 35 genes being common to both
species. This substantial overlap might suggest that coSNPs have a
comparable impact on genes in both bird species. Interestingly, our
investigation revealed a set of candidate genes exhibiting distinct
impact patterns in chickens and ducks that are caused by coSNPs. A
small number of notable genes related to AIV infection are exemplarily
illustrated in [182]Table 1. Comprehensive summaries of all
coSNP-induced impacts on both gene lists are available in
[183]Supplementary Tables S4 and S5.
Table 1.
Highlight of effects of coSNPs in candidate genes in chickens and
ducks. (*) denotes duck genes; (**) denotes chicken genes; no asterisks
denote known orthologous genes in both species. The complete table,
including SNP IDs, is available in [184]Supplementary Tables S4 and S5.
Effect
Gene Duck Chicken
ENSAPLG00000013923 *,
CD74 ** intron_variant missense_variant,
downstream_gene_variant
RUBCN synonymous_variant missense_variant
ABCA3 missense_variant intron_variant
MAP2K6 missense_variant intron_variant
VIPR2 missense_variant intron_variant
ENSGALG00010000247 *,
ENSAPLG00000008507 ** 3_prime_UTR_variant,
downstream_gene_variant, intron_variant stop_gained,
3_prime_UTR_variant
SHTN1 intron_variant splice_donor_variant, intron_variant
ATP8A1 splice_donor_variant, intron_variant intron_variant
ENSAPLG00000022349 *,
ERF3B ** splice_acceptor_variant, intron_variant intron_variant
[185]Open in a new tab
In our study, we identified several coSNPs that lead to missense
mutations in chickens or ducks which might affect the stability,
structure, or function of essential proteins involved in AIV defense.
Among the genes given in [186]Table 1, coSNPs in the CD74 and Rubicon
(RUBCN) genes lead to a missense mutation in chickens. The CD74 gene is
an important gene that performs diverse functions in the innate immune
response. It encodes an essential chaperone that modulates antigen
presentation in response to the class II major histocompatibility
complex and additionally plays crucial roles as a receptor on the cell
surface for the cytokine macrophage migration inhibitory factor or in
the interaction with the amyloid precursor protein [[187]73].
Interestingly, previous studies have reported a decrease in CD74
expression related to AIV infection. Ibaez et al. [[188]74] identified
a decrease in CD74 expression in the alveolar epithelial cells in mice
during H1N1 and H3N2 infection. In line with this, the findings of Xing
et al. [[189]75] show a down-regulation of CD74 during H9N2 and H6N2
LPAIV infection in the lungs of chickens. On the other hand, in ducks,
this mutation is located in an intron of the recently identified gene,
ENSAPLG00000013923, presumably encoding the ribosomal protein RPS14,
which is an integral component of the small ribosomal subunit (40S) and
plays a crucial role in protein biosynthesis. To shed further light on
the expression patterns of the candidate genes, we also examined the
underlying transcriptome data of Smith et al. [[190]3]. Our
observations revealed that ENSAPLG00000013923 was down-regulated in the
lung during H5N1 infection at 1 dpi. Another interesting gene is RUBCN,
which encodes a protein that functions as a negative regulator of
autophagy and endocytic trafficking and also plays an important role in
controlling endosome maturation [[191]76]. Moreover, RUBCN has the
ability to target various signaling complexes, therefore coordinating
immune responses. Specifically, RUBCN can act as a feedback inhibitor
to prevent unbalanced proinflammatory responses through the mediation
of RLR signaling, and its expression has been shown to impact AIV host
defense in mouse [[192]77]. A closer look at the expression values
reveals that RUBCN was up-regulated in the lung at 1 dpi during H5N1
infection, indicating its role in early pro-inflammatory response
reduction in ducks.
Furthermore, the identification of coSNPs within the candidate genes
ABCA3, MAP2K6, and VIPR2 (also known as RSAD2) has exposed missense
mutations in ducks. The ABCA3 gene belongs to the ABC transporter
family and is involved in maintaining cellular cholesterol and
phospholipid homeostasis [[193]78]. Interestingly, a paralog of ABCA3,
ABCA1, was shown to be associated with HPAIV survival in chickens
[[194]17]. Our data supports the importance of ABCA3 which was
up-regulated in the lungs of ducks at 3 dpi during H5N1 HPAIV
infection. The MAP2K6 gene is known for its critical involvement in the
MAPK signaling pathway which has been implicated in modulating the type
I IFN response [[195]28,[196]29], and has also been linked to the
survival of chickens infected with HPAIV [[197]16,[198]17]. The
differential expression of MAPK-related genes during HPAIV infection
has been observed in chicken [[199]28,[200]29], while they were
down-regulated in duck endothelial cells [[201]79]. In line with these
findings, we report the down-regulation of MAP2K6 in duck ileum at 3
dpi during H5N1 infection. The third gene, VIPR2 has a crucial function
in antiviral defense. It is stimulated by type I IFN and is
acknowledged as an inhibitor of AIVs via the suppression of viral
budding [[202]80]. Prior research indicates substantial up-regulation
of VIPR2 in various chicken and duck tissues during H5N1 infection
[[203]26], a finding that is consistent with the results of this study,
where VIPR2 was found to be up-regulated during H5N1 infection in duck
lung at 1 dpi.
While missense mutations can have a severe effect on proteins, in the
following, we want to discuss coSNPs that lead to particularly
detrimental outcomes on AIV-related genes in chickens and ducks. One of
the genes of interest is the chicken gene ENSGALG00010000247 and its
orthologous duck gene, ENSAPLG00000008507, which are novel gene
predictions and are affected by a coSNP that presumably causes a
premature stop gain. Stop gain variants, commonly known as nonsense
mutations, introduce a premature stop codon to a gene and can lead to
truncated protein products that lose their function and decrease
overall fitness if they are not cleared by nonsense-mediated decay
pathways. Considering the transcriptome data, ENSAPLG00000008507 was
up-regulated during H5N1 infection in the ileum at 1 dpi.
Another substantial impact is caused by coSNPs that occur within either
acceptor or donor splice sites of the genes Shootin 1 (SHTN1) in
chickens as well as ATP8A1 and ENSAPLG00000022349 in ducks, as shown in
[204]Table 1. Remarkably, mutations in the splicing apparatus may have
a significant impact on gene transcripts by means of alternative
splicing, potentially producing a novel protein isoform, and are
suggested to explain parts of phenotypic variability of diseases
[[205]81]. In line with this, various antiviral genes have been
reported to be modulated by alternative splicing or splicing variants,
which may either promote or impair their antiviral potency
[[206]82,[207]83]. Among the genes that affect splicing, SHTN1 is
involved in the positive regulation of neuron migration, as well as the
regulation of signaling pathways such as CDC42, RAC1, and PAK1, and the
regulation of phosphoinositide 3-kinase (PI3K) activity [[208]84].
Notably, PAK1 activation has been shown to contribute to AIV
replication in human lung epithelial cells [[209]85]. Furthermore, the
associated gene PI3K, as well as its downstream pathway involving Akt,
are implicated to have an ambivalent role in AIV replication, as they
can both support viral replication and co-activate antiviral responses
[[210]86]. However, inhibition of PI3K has been suggested to reduce
viral titers of some AIV strains [[211]87]. In addition, we also
identified two coSNPs that may lead to aberrant proteins in ducks,
namely a potentially defective splice donor site in ATP8A1 as well as a
potentially defective splice acceptor site in the duck gene
ENSAPLG00000022349 where the orthologous coSNP is located in an intron
of the chicken gene ERF3B. ATP8A1 is a p-type ATPase that participates
in various innate immunity-related processes, such as cell migration
and transportation. In particular, P4-ATPases such as ATP8A1, along
with CDC50 family members, form a phospholipid flippase complex which
is involved in the translocation of aminophospholipids such as
phosphatidylserine from the outer to the inner leaflet of membranes
[[212]88]. Interestingly, phospholipids, such as phosphatidylserine,
are components of the cell membrane and are involved in various
signaling processes such as cell cycle signaling for apoptosis, an
important process in killing infected cells. While the function of
ENSAPLG00000022349 remains unknown, it is likely to be an ortholog of
the human tripartite motif containing 35 genes (TRIM35) based on
Ensembl. TRIM proteins are known to induce E3 ubiquitin ligase activity
and have been implicated in downstream processes of the innate immune
response in mammals [[213]22,[214]89,[215]90]. Notably, TRIM25 has been
identified as an important molecule in the innate immunity of both
chickens and ducks against AIVs, interacting with RLR signaling
[[216]25,[217]26]. Furthermore, TRIM35 has been demonstrated to
positively regulate RIG-I mediated signaling by promoting TRAF3
activation during AIV infection in mouse [[218]91], indicating its
potential as an interesting protein to investigate for AIV resistance
in chickens and ducks. On the other hand, ERF3B encodes a GTPase that
belongs to the GTP-binding elongation factor family, is involved in
translation termination, and may play a role in mRNA stability and cell
cycle progression [[219]92]. Our transcriptome data revealed the
down-regulation of ATP8A1 in the ileum in ducks during H5N1 infection
at 3 dpi as well as the up-regulation of SHTN1 and ENSAPLG00000022349
in the lung at 3 dpi and 1 dpi, respectively.
Overall, the knowledge of coSNPs and the investigation of genes
harboring them provide crucial insights into their potential impact on
susceptibility or resistance to AIVs, thereby aiding in the
differentiation of underlying genetic mechanisms in chickens and ducks.
3.2. Identification of Pathways and Downstream Effectors
Based on the candidate gene lists, we performed the effector search
algorithm and a pathway enrichment analysis, for the identification of
downstream molecules as well as pathways that are targeted by the genes
of interest. Lists of the enriched pathways and key downstream
effectors are presented in [220]Table 2 and [221]Table 3. Detailed
results of effector and pathway analyses are given in
[222]Supplementary Tables S6 and S7 as well as [223]Tables S8 and S9,
respectively. Despite a high degree of overlap between the gene lists
of both species, [224]Table 2 and [225]Table 3 reveal substantial
differences in the effectors and enriched pathways, indicating
considerable variability in their respective numbers of detections.
Notably, while the number of candidate genes in ducks is smaller than
in chickens, the former exhibits a greater number of effectors.
Table 2.
Downstream pathways of the candidate gene lists in chickens and ducks.
Species Pathway
Chicken R-HSA-512988: Interleukin-3, Interleukin-5 and GM-CSF signaling
Duck R-HSA-909733: Interferon alpha/beta signaling
R-HSA-913531: Interferon Signaling
R-HSA-1280215: Cytokine Signaling in Immune system
R-HSA-168256: Immune System
[226]Open in a new tab
Table 3.
Downstream effectors of the candidate gene lists in chickens and ducks.
Chicken Duck
I
[MATH: κ :MATH]
B
[MATH: α :MATH]
GSK-3
[MATH: β :MATH]
axin1:
[MATH: β :MATH]
-catenin ADRB2R:MBP
FAK1 ATF-2
[MATH: β :MATH]
-catenin STAT3
STAT1 I
[MATH: κ :MATH]
B
[MATH: α :MATH]
STAT3 STAT1
APC:axin1:
[MATH: β :MATH]
-catenin:GSK-3
[MATH: β :MATH]
Tau (phosporylated)
- APC:axin1:
[MATH: β :MATH]
-catenin:GSK-3
[MATH: β :MATH]
- c-Myc
- p53
-
[MATH: β :MATH]
-catenin
- c-Jun
- hist1h3f
- Tau
- EGFR
[227]Open in a new tab
3.3. Pathway Analysis
Pathway enrichment analysis of the candidate genes has revealed one
pathway for chickens and four pathways for ducks, as shown in
[228]Table 2.
Notably, we identified a pathway linked to interleukins (ILs) IL-3 and
IL-5 and the granulocyte-macrophage colony-stimulating factor (GM-CSF)
in chickens, whereas several pathways associated with IFN signaling
were found in ducks. Despite both ILs and IFNs belonging to the group
of cytokines, their roles in viral response vary considerably. IFNs are
the principal regulators of innate immunity, and the early induction of
the type I IFN response is deemed an essential factor for the effective
immune response of duck following AIV infection [[229]37,[230]93]. In
this context, the antiviral activities and apoptosis induction of IFN-
[MATH: α :MATH]
and IFN-
[MATH: β :MATH]
were extensively investigated [[231]94,[232]95]. In contrast to IFNs,
the multifaceted functions of ILs can promote as well as inhibit
inflammation [[233]93]. In this regard, IL-3 and IL-5, together with
GM-CSF, are pleiotropic regulators of inflammation that play a role in
the rapid clearance of pathogens [[234]96]. GM-CSF is a glycoprotein
that enhances antigen presentation, microbicidal capacity, and
leukocyte chemotaxis, and is critical in the homeostasis process of
pulmonary alveolar macrophages, which, when deficient, can result in
pulmonary alveolar proteinosis [[235]97]. Due to its crucial dual role
in both inflammatory responses and the development of chronic
inflammation [[236]96], GM-CSF might be an attractive therapeutic
target, which has already been applied as a vaccine adjuvant against
viral infections [[237]98,[238]99,[239]100,[240]101].
In line with the findings described in [241]Section 3.1 and the
identified effectors (see [242]Section 3.4), IL-3, IL-5, and GM-CSF are
known to activate the JAK/STAT, Ras/MAPK, and PI3K pathways [[243]102].
The presence of several ILs at the site of inflammation characterizes
pathological cytokine and chemokine overproduction, commonly referred
to as a “cytokine storm” [[244]93,[245]103]. However, since our data
set did not capture the early response and due to the limited gene
expression at 1 dpi or 3 dpi, there is currently no conclusive evidence
of cytokine overexpression in chickens.
3.4. Downstream Effector Analysis
Our analysis of the candidate gene lists identified seven key
downstream effectors in chickens and 15 key downstream effectors in
ducks, as shown in [246]Table 3. Among the effectors, I
[MATH: κ :MATH]
B
[MATH: α :MATH]
, STAT1, and STAT3 were common to both bird species. Additionally,
there was an overlap between some effectors associated with APC, axin1,
[MATH: β :MATH]
-catenin, and GSK-3
[MATH: β :MATH]
in terms of protein complexes. The notation used, e.g., axin1:
[MATH: β :MATH]
-catenin, denotes a protein complex or interaction between axin1 and
[MATH: β :MATH]
-catenin. In the following sections, we present the main results
explaining the functions of these effectors in the context of AIV
infection.
3.4.1. Downstream Effectors in Chicken
Three proteins and protein complexes related to the Wnt signaling
pathway, including axin1:
[MATH: β :MATH]
-catenin,
[MATH: β :MATH]
-catenin, and APC:axin1:
[MATH: β :MATH]
-catenin-GSK-3
[MATH: β :MATH]
were identified as effectors in chickens ([247]Figure 3). In addition,
other effectors in chickens were related to NF-
[MATH: κ :MATH]
B (I
[MATH: κ :MATH]
B
[MATH: α :MATH]
) as well as IFN and JAK/STAT signaling (STAT1 and STAT3).
Figure 3.
[248]Figure 3
[249]Open in a new tab
Downstream effectors and their interactions identified in chickens.
Blue nodes denote the candidate genes, green nodes indicate
intermediate interaction partners and red nodes represent the
identified downstream effectors. A high-resolution version of this
image is provided in [250]Supplementary Figure S1.
The only chicken-specific effector is the focal adhesion kinase 1
(FAK1), which is involved in pathways related to apoptosis, cellular
adhesion, and cell migration. It has been shown that FAK regulates AIV
entry at a post-internalization step and its inhibition reduces AIV
polymerase activity in vitro in human lung and bronchial cells
[[251]104]. The activity of FAK is suggested to be required for the
nuclear localization of NF-
[MATH: κ :MATH]
B during AIV infection in mice [[252]105]. Since HPAIVs hijack
important anti-viral related pathways to promote their replication,
proper governance or inhibition of FAK and NF-
[MATH: κ :MATH]
B could be prime targets for the viral susceptibility of chickens. This
claim is supported by findings of Perlas et al. [[253]106], who
observed the up-regulation of NF-
[MATH: κ :MATH]
B-related genes (PLAU, VCAM1, TNFRSF1A) and MAPK-related genes
(TNFRSF1, PGF) in chicken breeds susceptible to HPAIV strains, whereas
they were found down-regulated in more resistant chicken breeds. In
line with this, Drobik-Czwarno et al. [[254]17] identified the NF-
[MATH: κ :MATH]
B-related gene TNFRSF1A in a region associated with HPAIV survival of
chickens.
3.4.2. Downstream Effectors in Duck
In comparison to chickens, we identified a set of eight duck-specific
effectors ([255]Figure 4). A closer look at these effectors shows a
diversity of complex functional features in ducks in response to AIV
infection. Some of the effectors have direct relevance for AIV, while
the others could be indirectly linked via interactions.
Figure 4.
[256]Figure 4
[257]Open in a new tab
Downstream effectors and their interactions identified in ducks. Blue
nodes denote the candidate genes, green nodes indicate intermediate
interaction partners and red nodes represent the identified downstream
effectors. A high-resolution version of this image is provided in
[258]Supplementary Figure S2.
In particular, p53, c-Jun, ATF-2, EGFR, and c-Myc are known for their
important roles in various immune functions. The effector p53 is known
as the “guardian of the genome” [[259]107] which is a tumor suppressor
gene that is activated indirectly by type I IFN and its function is
crucial in responding to viral infections through p53-dependent
apoptosis [[260]95]. In this regard, p53 plays an important role in
innate immunity by boosting IFN-dependent antiviral responses
[[261]108]. In mouse models, it was reported that the absence of p53
responses results in increased susceptibility to viral infections
[[262]109]. Furthermore, the proto-oncogene c-Jun is a member of the
AP-1 transcription factor (TF) family and plays a vital role in
regulating cell proliferation, differentiation, and apoptosis.
Remarkably, c-Jun and its related c-Jun N-terminal kinases (JNKs),
which bind and phosphorylate c-Jun, respond to stress stimuli and are
involved in regulating various host immune responses and genes such as
PI3K, ATF-2, SMAD4, p53, STAT3, and GM-CSF [[263]110]. In this context,
the down-regulation of c-Jun was found to suppress H5N1 viral
replication in vitro in human cells and in vivo in mouse [[264]111].
Along with c-Jun and NF-
[MATH: κ :MATH]
B, the effector ATF-2 has been reported to induce the production of
type I IFN, which is well-studied in the generation of antiviral
responses by up-regulating genes that activate dendritic cells and
natural killer cells, both of which are involved in adaptive immunity
[[265]112].
Furthermore, EGFR is a transmembrane glycoprotein that is a member of
the protein kinase superfamily. It is a receptor for the epidermal
growth factor that induces cell proliferation and acts in downstream
signal transduction, activating several proteins related to Ras/MAPK,
Akt, and JNK pathways [[266]113]. Inhibition of EGFR has been found to
decrease viral uptake in human lung epithelial cells by activating PI3K
[[267]114], suggesting that EGFR might be a potential therapeutic
target for chicken and duck disease progression caused by AIVs. Another
well-studied effector in cancer research is c-Myc, which encodes a
proto-oncogenic nuclear phosphoprotein and participates in various
cellular processes such as cell cycle progression, apoptosis, and
cellular transformation and directly or indirectly interacts with a
variety of pathways such as NF-
[MATH: κ :MATH]
B or Wnt and EGF via MAPK/ERK [[268]115,[269]116]. Of note, the mRNA of
c-Myc contains an internal ribosome entry site that enables RNA
translation even when 5’cap dependent translation is inhibited, such as
under stress responses to viral infections [[270]117]. Therefore, in
addition to its role in cancer, c-Myc may represent an intriguing
target for further investigation in AIV infection due to its
involvement in cellular apoptosis during stress responses.
The remaining effectors ADRB2R:MBP, Tau, and Hist1h3f have been
implicated in various biological processes but their direct association
with immune responses is unknown. For example, the effector ADRB2R
encodes the beta-2 adrenergic receptor, which mediates many aspects of
airway function in humans, is expressed by most immune cells, and is
mainly found in the lung [[271]118]. On the other hand, the effectors
MBP and Tau are involved in the biological processes linked to the
nervous system [[272]119,[273]120]. The Hist1h3f is another effector
which encodes the H3 clustered histone 1 and plays a crucial role in
transcriptional regulation, DNA replication, DNA repair, and
chromosomal stability. Due to their involvement in chromatin
remodeling, histones may also play a crucial role in regulating
epigenetic processes in host defense against viral infections by
controlling the DNA permissibility for rapid and directed changes in
gene expression [[274]121]. In agreement with this, Hoeksema et al.
[[275]122] have shown that histones H4 and H3 inhibit the infectivity
of some influenza strains in human lung epithelial cells. Taken
together, these effectors could be promising targets for future studies
due to their functional roles, such as (i) context-dependent production
of proinflammatory cytokines of ADRB2R [[276]118]; (ii) involvement in
the signaling of MBP; (iii) association of Tau with target genes
related to viral infection such as GSK-3
[MATH: β :MATH]
, CDK5, and JNK [[277]120]; (iv) controlling DNA permissibility to
rapidly direct viral gene expression of Hist1h3f [[278]121,[279]122].
3.4.3. Common Effectors
Due to the shared pool of affected genes, several effectors intersect
the downstream signaling of both chickens and ducks. I
[MATH: κ :MATH]
B
[MATH: α :MATH]
is among the common effectors in both chickens and ducks. It encodes a
potent inhibitor of NF-
[MATH: κ :MATH]
B, a TF that plays a pivotal role in regulating various pathways,
including immune responses to infections, where it controls the
expression of inflammatory cytokines [[280]123]. Previous studies
showed that even though NF-
[MATH: κ :MATH]
B acts as a master regulator of the innate immune defense and induces
antiviral activities, AIVs also depend on NF-
[MATH: κ :MATH]
B where viruses can employ the functions of NF-
[MATH: κ :MATH]
B to increase viral replication [[281]124,[282]125]. In line with this,
I
[MATH: κ :MATH]
B
[MATH: α :MATH]
was also found to be associated with HPAIV resistance in chicken
[[283]17] and hence might play a crucial role in the delicate control
of NF-
[MATH: κ :MATH]
B in both chickens and ducks to prevent AIVs from exploiting the
related pathways to their benefit.
Interestingly, we identified two members of the signal transducer and
activator of the transcription family (STAT), STAT1 and STAT3, as
common effectors in both chickens and ducks. Due to their prominent
role in the regulation of the IFN response via immune signaling
pathways such as JAK/STAT, STAT TFs are well-studied and there is rich
literature available for their related pathways. For example, Kuchipudi
et al. [[284]42] reported the inhibition and down-regulation of STAT3
in chickens, while the expression of STAT3 in ducks was unaffected and
up-regulated. Similarly, Jia et al. [[285]126] showed that the viral
NS1 gene interferes with STAT members and the IFN signaling to increase
viral replication in vitro. Klees et al. [[286]47] discussed the
importance of STAT TFs as upstream regulators of the DEGs following AIV
infection, which induces type I IFN response and ISGs [[287]127]. In
this regard, STAT members (STAT1, STAT3, and STAT4) were up-regulated
during H5N1 infection in ducks, but there was no response in chickens.
Additionally, Klees et al. [[288]47] determined that STAT TF binding
sites were only enriched in the promoters of the duck DEGs and not in
orthologous chicken promoters. Therefore, our findings of effectors
suggest that STAT members play an essential role in both bird species
for viral defense, but pathways in chickens may be compromised or
inhibited by AIVs due to a lack of enriched STAT binding sites and
dysregulated pathways.
The identified effectors in the final group are associated with the
protein complexes of APC, axin1,
[MATH: β :MATH]
-catenin, and GSK-3
[MATH: β :MATH]
, which are crucial components of the Wnt signaling pathways. GSK-3
[MATH: β :MATH]
, a serine-threonine kinase from the glycogen synthase kinase family,
negatively regulates glucose homeostasis and is at the crosspoint
between a multitude of pathways related to functions such as cellular
signaling or regulation of inflammation [[289]128,[290]129]. Many
pathways, such as mTOR, PI3K/Akt, and Ras/MAPK, target GSK-3 inhibition
to promote dephosphorylation of GSK-3 substrates, including c-Myc or
c-Jun, which could stimulate cell proliferation, migration, and
survival [[291]128]. A recent study highlighted the regulatory role of
GSK-3
[MATH: β :MATH]
, along with
[MATH: β :MATH]
-catenin, in controlling the antiviral innate immune response to viral
infections, causing a rapid induction of type I IFN response and
activation of IFN regulatory factor 3 [[292]130]. In the context of Wnt
signaling modulation, among other proteins, GSK-3, axin, and APC are
involved in the degradation of
[MATH: β :MATH]
-catenin [[293]131]. Furthermore, the targeted Wnt signaling pathway is
intertwined with various pathways, including the TGF-
[MATH: β :MATH]
pathway, where SMADs and
[MATH: β :MATH]
-catenin can interact via the lymphoid enhancer-binding factor and
T-cell-specific TF [[294]132]. By considering duck DEGs and their
orthologs in chickens, Klees et al. [[295]47] reported the enrichment
of SMAD members in the promoters of chicken genes. However, SMAD
members only acted as upstream master regulators of duck DEGs during
AIV infection. These findings demonstrate the complex interplay and
entanglement of pathways such as Wnt in the immune response,
emphasizing the importance of their orchestration via SMAD members.
4. Conclusions
Despite the rapid progress in genomics and transcriptomics, the nuanced
differences underlying susceptibility or resistance to avian influenza
in chickens and ducks remain incompletely understood. To decipher the
distinct genetic programs underlying immune-related functions, which
could potentially distinguish the susceptibility/resistance of both
species to avian influenza, the consideration of coSNPs is essential in
the determination of novel targets in breeding research. Hence, we
employed a genome-wide analysis to identify coSNPs and their differing
causal impacts on AIV-related candidate genes. To this end, downstream
pathway and effector analyses were examined that are likely linked to
the divergent immune responses in both species. Our findings
demonstrate that although the impact patterns of coSNPs on affected
genes are mostly similar between chickens and ducks, we discovered
several promising coSNPs that have divergent effects on genes in
chickens (e.g., CD74, RUBCN, SHTN1, and ENSGALG00010000247) and ducks
(e.g., ABCA3, MAP2K6, VIPR2, ATP8A1, and ENSAPLG00000022349)
corresponding to immune responses induced by AIVs. Moreover, the
downstream pathway and effector analysis reveal species-specific and
commonly targeted biological mechanisms, which might partially explain
the effective or ineffective immune responses of both species. In
particular, we report that the candidate genes might be linked to IL
signaling pathways in chickens and IFN and immune signaling pathways in
ducks. On top of that, our study extends the previous transcriptome
analysis by Smith et al. [[296]3] and upstream analysis by Klees et al.
[[297]47] by leveraging different causal impacts of coSNPs on gene
functions of both species to comparatively explore their downstream
mechanisms. To the best of our knowledge, this is the first study that
considers coSNPs in the context of AIV infection, offering a basis for
the formulation of novel hypotheses in future research.
Abbreviations
The following abbreviations are used in this manuscript:
AIV avian influenza virus
coSNP coincident SNP
DEG differentially expressed gene
dpi days post infection
FAK1 focal adhesion kinase 1
FDR false discovery rate
GM-CSF granulocyte-macrophage colony-stimulating factor
HPAIV highly pathogenic AIV
IFN interferon
IL interleukin
ISG IFN-stimulated gene
JNK c-Jun N-terminal kinase
LPAIV low pathogenic AIV
PI3K phosphoinositide 3-kinase
PRR pattern recognition receptor
RIG-I retinoic acid inducible gene I
RLR RIG-I-like receptor
SNP single-nucleotide polymorphism
STAT signal transducer and activator of transcription family
TF transcription factor
TRIM tripartite motif
[298]Open in a new tab
Supplementary Materials
The following supporting information can be downloaded at:
[299]https://www.mdpi.com/article/10.3390/biology12070969/s1, Figure
S1: downstream effectors of chicken; Figure S2: downstream effectors of
duck; File S1: source code of the workflow for coSNP identification and
analysis; File S2: list of chicken orthologs of duck DEGs that are
affected by a coSNP; File S3: list of duck DEGs that are affected by a
coSNP; Table S1: overview of all identified coSNPs; Table S2: overview
of the number of coSNP impacts; Table S3: overview of DEG expression;
Table S4: summary of impacts (moderate or high) of coSNPs on chicken
orthologs of duck DEGs; Table S5: summary of impacts (moderate or high)
of coSNPs on duck DEGs; Table S6: identified effectors of chicken
orthologs of duck DEGs impacted (moderate or high) by a coSNP; Table
S7: identified effectors of duck DEGs impacted (moderate or high) by a
coSNP; Table S8: Reactome enriched pathways of chicken orthologs of
duck DEGs impacted (moderate or high) by a coSNP; Table S9: Reactome
enriched pathways of duck DEGs impacted (moderate or high) by a coSNP.
[300]Click here for additional data file.^ (8.5MB, zip)
Author Contributions
M.G. designed and supervised the research. H.B. developed the pipeline
and participated in the design of the study, prepared the data sets and
conducted the bioinformatics analyses. S.W., A.O.S., A.R., F.R., M.B.
and M.W. were involved in the interpretation of the results, together
with H.B., M.G. and H.B. wrote the final version of the manuscript.
M.G. conceived and managed the project. All authors have read and
agreed to the published version of the manuscript.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
Not applicable.
Conflicts of Interest
The authors declare no conflict of interest.
Funding Statement
This research received no external funding.
Footnotes
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References