A Global Survey of SNP Marker Studies in Chickens (Gallus gallus domesticus): A Bibliometric Approach

ABSTRACT

This study reviewed the scientific literature on the application of single nucleotide polymorphism (SNP) markers in chickens (Gallus gallus domesticus), aiming to assess research trends, contributing countries, and the most investigated genes in poultry genetics. The bibliometrix package in R was used to dig through data from Web of Science and Scopus, covering the period ranging from 2008-2024. After cleaning out the duplicates, 1,668 articles remained. Since 2008, the numbers kept climbing, peaking in 2024 with 137 papers, which amounts to an average of 87 per year. The US, South Korea, and China were the largest three country origins in terms of output, with China alone producing 723 studies. Countries like Brazil were also important sources, which hints at there still being significant room for global collaboration in this field. The most frequent keywords were “growth” and “egg production,” underscoring a predominant research focus on productive and reproductive traits. The most cited genes were GH, IGF, PRL, MHC, CORT, MCR1, and VIP, which relate to growth, egg production, and disease resistance. Our data expand the body of SNP-based research in poultry science, while also highlighting the potential of those markers for use in breeding programs that aim at increasing productivity and sustainability.

Keywords:
Poultry genetics; bibliometrix; poultry production; egg production

INTRODUCTION

Chickens are distributed worldwide and comprise approximately 70 genera and 250 species. The domestic subspecies (Gallus gallus domesticus) is the predominant one, with a worldwide flock estimated at 24 billion FAO (2023); Bruce Campbell (2013). Chickens, which are members of the Phasianidae family and the order Galliformes, were domesticated thousands of years ago, and have since become essential members of human societies. In addition to being the world’s main source of protein, they are also a major source of revenue for small and medium-sized farmers (Takahashi et al., 2006). From a socioeconomic point of view, poultry farming is one of the biggest pillars of agriculture, especially when considering small and medium producers. In 2023, for instance, chicken meat and egg production reached approximately 131 million metric tons and over 1.2 trillion units, respectively. This industry is estimated to globally support around 4.3 billion jobs, directly and indirectly (FAO, 2023).

The continuous growth in demand for chicken meat and eggs has been pushing the industry for increased efficiency and productivity, and poultry is currently the world’s main protein source (Ledur, 2007; ABPA, 2023). In this context, genetics are a key resource, capable of promoting faster growth, better meat, greater disease resistance, and improved animal welfare. However, balancing growing meat demand with socially and environmentally sustainable production are both crucial and complex challenges (FAO, 2023). Genotype-by-environment interaction is a complex phenomenon, determined by the interactions between such factors as scarce resources, tropical diseases, local weather, and farm management, making the choice of both resistant and highly productive breeds key to optimize flock yields and resource use. In this context, studies using genetic markers tied to production traits have been receiving increased attention in recent research (Barros Polido et al., 2012; Amiteye, 2021).

SNPs, or Single Nucleotide Polymorphisms, are a key study theme in modern genetics, consisting of micro-differences in genotypes which can now be massively analyzed through the use of microarrays that contain thousands of markers. Such approaches make it possible to map genes connected to economically important traits and apply this knowledge to increase production and sustainability in poultry farming (Burt, 2005; Salvian et al., 2023), while also contributing to animal welfare (Blokhuis et al., 2003). The number of studies using SNPs in chickens has increased considerably in recent years. Several countries, including the United States, China, Brazil, and the United Kingdom, are investing in biotechnological tools to identify genes that influence traits of interest to the poultry industry.

Brazil plays a fundamental role in the global poultry industry, being one of the world’s largest chicken exporters. Furthermore, its vast territory boasts several climate zones, which is ideal for raising livestock (FAO, 2023; ABPA, 2024).

Interestingly, even as a substantial poultry producer, high rates of food insecurity still prevail, especially in the northeastern region of the country, where this technology could have a positive impact on such social issues (Pereira, 2025). Therefore, expanding genomic research and technological innovation for poultry farming can have an important social and economic impact, especially for small and medium-sized producers in poverty-stricken regions, where food is not easily available (EMBRAPA, 2007; Figueiredo et al., 2017).

Based on this background, the present bibliometric analysis used data extracted from the Web of Science Core Collection (Clarivate Analytics) and Scopus to examine scientific production on SNP markers in Gallus gallus domesticus. The study also evaluates the main genes cited in the literature and discusses their potential applications in marker-assisted selection projects.

MATERIALS AND METHODS

Data were obtained from the Web of Science (WoS) and Scopus platforms, focusing on articles that addressed the use of Single Nucleotide Polymorphisms (SNPs) in Gallus gallus domesticus. The analysis period spanned from 2008 to 2024, starting from 2008 to capture a significant phase in SNP research in chickens, characterized by relevant discoveries and shifts in research practices in this field (Groenen et al. 2009; Vilas Boas, 2011). Boolean search descriptors were adapted to encompass the broadest possible range of publications, and were defined as follows:

• Web of Science: ((TI=(snp)) OR TI=(snps)) AND TI=(chicken)) or AB=(snp)) OR AB=(snps)) AND AB=(chicken)) or AK=(snp)) OR AK=(snps)) AND AK=(chicken)

• Scopus: snp OR snps AND chicken

Results were extracted in BibTeX format, containing complete records with information on authors, article title, abstract, country, publication year, affiliation, citations, and keywords. After data extraction, the records from both databases were consolidated into a single dataset. Duplicate entries were identified and removed using the bibliometrix package in R (Aria & Cuccurullo, 2017), with matching criteria based on Digital Object Identifier (DOI) and article title. The search and screening process targeted only research articles, using information from titles, abstracts, and keywords.

The bibliometrix package was also used for the core bibliometric analyses, such as evaluating publication output by country and keyword frequency. The country attributed to each publication was determined based on the correspondence address of the first author. For enhanced visual network analysis, co-occurrence maps and network graphs were generated using VOSviewer software (van Eck & Waltman, 2010).

The following analytical procedures were applied for data presentation:

• Temporal publication trend analysis: The histPlot function was used to generate a graph displaying the annual number of publications combined with citation counts.

• Country-level production analysis: A mapping function based on bibliographic data was used for country analysis in VOSviewer. Publication output by country was also assessed using bibliometrix.

• Keyword frequency analysis: Keyword co-occurrence maps were created using VOSviewer, supplemented by network relationship analysis.

• Institutional analysis: A list of educational and research institutions was compiled based on the affiliation addresses of both domestic and international authors. This approach helped reveal where scientific capacity is concentrated and how collaborations are distributed across countries. It is also important to note that such lists tend to highlight well-funded institutions, while smaller universities or research centers in developing regions - including Brazil - often remain underrepresented, despite their significant contributions to poultry science under tropical conditions.

• Gene prominence analysis: AI (OpenAI, 2024) was used to extract high-occurrence genes among research papers and linking them to specific identified traits. It is however important to highlight that commonly studied gene markers are not always the most relevant for producers, particularly those based in tropical countries. Traits such as heat tolerance, pest resistance and adaptability to smallholder conditions are often key for production in these regions, but are not often key priorities of research reports.

All data followed the standard format set out by Moura et al. (2017).

RESULTS

The first query to the Web of Science (WoS) and Scopus databases yielded 2,055 articles about poultry science. This focused on studies about “SNPs in Gallus gallus domesticus”, as the search rules stated. After removing 387 copies, 1,668 separate publications were kept for the next bibliometric analysis. (Table 1).

Table 1
Total number of publications retrieved from the Web of Science and Scopus databases, the number of duplicate articles, and the final article count.

DATA DESCRIPTION	COUNT
SCOPUS	1473
WEB OF SCIENCE	582
SUBTOTAL	2055
DUPLICATES	387
TOTAL	1668

The research yield through time shows a clearly increasing trend: starting from a total of approximately 80 in 2008, this figure climbed steadily, reaching the highest yearly total of 137 papers in 2024 (Figure 1). Therefore, despite an average of 87 papers per year, a clear upward trend could be distinguished.

Figure 1
Annual number of scientific publications based on the use of SNP markers for research in Gallus gallus domesticus by publication year (2008-2024).

Articles from 67 countries exploring the use of SNPs in chickens were recorded. China led scientific output with 723 publications, followed by the United States (133 publications) and South Korea (51 publications). Other notable contributing countries included the United Kingdom (47 publications), Japan (49 publications), and Iran (41 publications) (Figure 2).

Figure 2
Geographic distribution of scientific publications on SNPs in Gallus gallus domesticus by country. Darker blue shades indicate higher publication output, while lighter shades correspond to lower output. Countries shaded in gray had no publications in the analyzed databases.

Brazil shows up in 10th place, with 27 papers on the subject when both Web of Science and Scopus are aggregated. Out of the top 20 contributors, four countries are considered “developing countries”, China, Brazil, India, and Iran, with three of those being in the BRICS block. Other countries and their respective paper counts that are also worth highlighting are Indonesia (58), India and the Netherlands (56), Russia (54), and Egypt (52). Figure 3 shows the interaction between publication numbers and collaborations, with China (red) and the USA (purple) dominating the map, reiterating their central position in both research outputs and scientific collaborations.

Figure 3
Worldwide scientific publications on SNP markers in Gallus gallus domesticus by country of corresponding author and collaborative networks. Node size corresponds to publication volume, and connecting lines represent collaborative linkages between countries.

A total of 6,868 keywords were identified. Using keywords from publications on Gallus gallus domesticus SNPs, the biggest research areas are directly related to production and zootechnical traits. Numerous keywords related to chicken, SNPs, GWASs (Genome-Wide Association Studies), egg production, growth, associations, traits, reproductive traits, candidate genes, and egg quality. (Figure 4).

Figure 4
Co-occurrence network analysis of keywords in publications on SNP markers in Gallus gallus domesticus. The bigger the node, the more times the corresponding keyword showed up, and the lines show the connections of terms in meaning.

The publication records show author affiliations with state institutions in the People’s Republic of China for more than 40% of the entries, highlighting the country’s contribution to research on single nucleotide polymorphism (SNP) markers and their application in chickens.

Among the institutions that published articles in the Web of Science (WoS) and Scopus databases, China Agricultural University ranked first with 131 publications, followed by other Chinese institutions such as Yangzhou University (127 publications) and South China Agricultural University (100 publications). All ten of the most prolific institutions were based in China (Table 2).

Table 2
Publication output by institution: Article count and affiliation records from Web of Science and Scopus.

Affiliation	Articles	Percentage
CHINA AGR UNIV	131	2.36%
YANGZHOU UNIV*	127	2.33%
SOUTH CHINA AGR UNIV*	100	1.81%
SICHUAN AGR UNIV	91	1.64%
CHINA AGRICULTURAL UNIVERSITY	79	1.43%
INST ANIM SCI	79	1.43%
HENAN AGR UNIV	67	1.21%
SOUTH CHINA AGRICULTURAL UNIVERSITY*	63	1.14%
YANGZHOU UNIVERSITY*	63	1.14%
CHUNGNAM NATL UNIV	52	0.94%

• * The variation in the formats of the university names reflects distinct affiliation records, with the counts representing entries from single authors.

The most frequently studied genes in this species include Growth Hormone (GH), Insulin-like Growth Factor (IGF), Major Histocompatibility Complex (MHC), Corticotropin (CORT), Prolactin (PRL), Melanocortin 1 Receptor (MC1R), and Vasoactive Intestinal Peptide (VIP).

These genes are predominantly connected to economically important traits such as egg production, disease resistance, and growth performance (Figure 5).

Figure 5
Frequency of the most studied genes, their associated traits in Gallus gallus domesticus research, and the number of occurrences in the articles obtained. GH: Growth Hormone, IGF: Insulin-like Growth Factor, MHC: Major Histocompatibility Complex, CORT: Corticosterone, PRL: Prolactin, MC1R: Melanocortin 1 Receptor, LEP: Leptin, VIP: Vasoactive Intestinal Peptide, MSTN: Myostatin, ASIP: Agouti Signaling Protein.

DISCUSSION

A considerable rise in scientific publications about poultry farming in general and SNP markers in chickens in particular shows a bigger interest in this research area, as well as a better understanding of how genetic markers can improve production. The regular growth in publications from 2008 points to a slow acceptance of how important those markers are in poultry science. (Ledur, 2007; Vilas Boas, 2011). The timeframe we selected lines up with when researchers first started identifying SNPs across full genomes, like the chicken genome (Groenen et al., 2009). Interestingly, this period also includes the COVID-19 years (2020-2023); with the fact that research kept a growing through this turbulent period highlighting its importance.

Rising worldwide demand for chicken meat and eggs has driven the need for improvements in poultry production efficiency. Studies emphasize the importance of SNP markers in identifying genes connected to economically valuable traits in birds (Xu et al., 2011; Liu et al., 2018).

The research output from China, the US, South Korea, and Japan makes them the leaders in this field, despite studies on SNP markers proving their relevance throughout different countries and environmental contexts (Wolc et al., 2014; Cheng et al., 2023).

China’s lead in this field is due to its massive poultry industry, large consumer market for poultry and significant investments in genetics research (Dou et al., 2022; Fang et al., 2023). The country’s large role in poultry genetics is especially prominent in terms of applied research for improved production and health traits in poultry flocks.

The United States also holds a notable place in the field, with leading research centers and universities, along with a long history of of investments in poultry genetics. Studies like Wolc et al. (2014) and Fulton (2012) report how the U.S. has contributed to identifying genetic markers tied to key traits for the poultry industry.

South Korea’s contribution is smaller than that of the two former countries but still relevant, as shown by Drobik-Czwarno et al. (2018) and Kim et al. (2023), who describes how studies in different countries are pushing forward improvements in poultry genetics and production.

Research outputs and poultry production levels are not always correlated. Brazil offers a clear example of this paradox. The country is one of the world’s leading protein producers, home to large multinational industries that export worldwide (ABPA, 2023; USDA, 2023). However, it has relatively low scientific output in this specific research domain, ranking 10th worldwide, with only 27 articles. This discrepancy suggests that the success of Brazilian industry often depends on importing foreign technology and maximizing production efficiency rather than on robust domestic, public research and development. This creates a critical gap, especially for a country with a continental-sized territory, a multi-ethnic population (IBGE, 2017), and diverse production challenges.

The country’s poultry sector is dominated primarily by large multinational corporations such as BRF S.A. (Brasil Foods), one of the world’s largest food companies and the result of the merger between Sadia and Perdigão, and JBS Aves (Seara Alimentos), part of the JBS S.A. group, another global animal protein giant (Costa & Costa, 2023).

Furthermore, this gap in public research has social implications. Although large companies thrive, Brazil still faces significant food insecurity in many vulnerable communities, particularly in the Northeast region (PENSSAN, 2022). The use of genetic markers to develop animals adapted to local conditions and select breeds that thrive in specific regions have great potential for this region, with the potential to reduce the risk of losses (mortality), decrease dependence on expensive industrial, and make animal protein production financially viable for low-income families. Furthermore, decentralizing development based on family farming, characterizing and conserving Creole (native) breeds, preserving genetic diversity, and investing in small businesses in strategic locations has a greater impact where hunger and scarcity are most prevalent (IBGE, 2017).

Notably, research was not limited to developed countries. Contributions also came from developing nations (e.g., China, Brazil, India, Indonesia, Iran, Egypt, South Africa, Thailand, Argentina, Chile, Ecuador, Malaysia, and Vietnam) and countries with low human development indices and GDP per capita (e.g., Nigeria, Pakistan, Rwanda, Tanzania, and Kenya), as classified by the International Monetary Fund (IMF) and the United Nations (UN). These countries also employed advanced techniques in SNP studies.

Regarding institutions, China’s predominance in SNP marker research reflects not only substantial government investment in R&D, but also the country’s emerging leadership in the agricultural sector. China’s National Bureau of Statistics reports that R&D spending has gone up, which already points to new possibilities in areas like agriculture. With initiatives such as Made in China 2025, focused on pushing high-tech sectors like agriculture and biotechnology, the level of investment in agricultural research has risen considerably (ISPD, 2018).

The outputs of renowned institutions like the University of Edinburgh in the UK and Iowa State University in the U.S. highlight the global character and relevance of genetic marker research in poultry. These institutions are key for building international collaboration and spreading scientific knowledge in poultry genetics. The use of SNPs in chickens also depends on the sociocultural context (East/West) of the institution, suggesting a diversity of approaches (production, resistance, aesthetics) and perspectives (cultural, sociological, religious).

The number of publications linked to Brazilian institutions is quite limited. EMBRAPA (Brazilian Agricultural Research Corporation), for example, is responsible for only 2% of the total research output. This highlights a critical gap between the country’s enormous industrial production and its scientific production and development in modern genetics, especially regarding the real challenges of tropical agriculture.

EMBRAPA has historically worked with poultry genetics to develop varieties suited to tropical conditions and sustainable production (EMBRAPA, 2007). A prime example is the “Embrapa 041 Colonial Broiler”, a free-range broiler breed developed in partnership with the Federal University of Viçosa (UFV). This breed was designed to be adapted to the Brazilian climate and local management systems, directly supporting family farmers, which is essential for regional food security (Figueiredo, 2017). This technology can be applied in priority food scarcity areas, where molecular markers, economic incentives for small-scale farmers, and the popularization of techniques could improve the situation in these regions.

However, this crucial work is severely hampered by the same problems that limit publication output in Brazil: scarce public resources and devastating budget cuts. In 2019, for example, EMBRAPA nearly halved its budget, which severely impacted its research capacity and reflected a broader crisis in science funding (Costa & Costa, 2023). Reports from the Capes and CNPq show numerous issues in poultry genetics research in Brazil, such as financial restraints, limited infrastructure and a lack of skilled staff (Costa & Costa, 2023). These issues require increased spenditure on science and technology development, as well as collaborations between the government, private companies, and research laboratories.

The keywords in the studies highlight the importance of gene expression and genetic markers tied to growth rates and egg production as the main current themes in poultry molecular genetics. Studies such as those by Muir et al. (2008) and Negash et al. (2021) highlight the importance of these themes in understanding the genetic basis of production traits and developing breeding strategies.

Most of the articles relied on next-generation sequencing (NGS) and GWAS using microarrays or chips. These tools allow for easier identification and study of genetic markers such as SNPs, providing a clearer picture of chicken genetics and key traits for poultry production (Khanzadeh, 2010; Pan et al., 2024). Moreover, the results also show the importance of environmental and management influences on genetic expression. Studies like Tixier-Boichard et al. (2011) and Negash et al. (2021) show the importance of genotype-environment interaction for trait manifestation in poultry.

GH (Growth Hormone) was the most studied trait among the studied papers. This hormone has a pivotal role in tissue development, being responsible to signal the production of IGF-1 in the liver, which in turn triggers cell growth and tissue repair. Recent studies have found that SNPs in the GH gene can adjust GH secretion levels and efficacy, thereby directly impacting growth and meat production in chickens (Wang et al., 2021).

Moreover, SNPs in the IGF-1 gene can also alter its secretion levels, thus also affecting meat growth and egg production. In chickens, this hormone is also tied to reproduction, as it triggers ovarian activity and egg laying, and to the immune system through its role in the production of antibodies and the support of cell regeneration (Kim et al., 2004; Ogunpaimo et al., 2021).

The MHC (Major Histocompatibility Complex) is crucial part of the chicken genome, with a key role in birds’ immune systems. Variations in the MHC gene can alter chicken immunity to conditions like Marek’s disease or infectious bronchitis. In short, the MHC is essential for adaptive immunity, as it connects antigens to T cells, playing a major role in whether a chicken will easily resist or be more susceptible to certain infections. (Kaufman, 2022).

CORT, or corticotropin, is a key hormone regulating the stress response in chickens. Under adverse conditions - such as abrupt environmental changes, suboptimal management practices, or high ambient temperatures - CORT levels increase rapidly, often leading to metabolic imbalance, reduced feed intake, and impaired productive performance. In tropical and subtropical production systems, chronic heat stress represents one of the most significant environmental challenges, continuously activating the hypothalamic-pituitary-adrenal (HPA) axis and elevating circulating CORT levels. Genetic variation within the CORT-related pathway, including specific single nucleotide polymorphisms (SNPs), has been associated with improved stress adaptability.

Chickens carrying favorable alleles appear to exhibit a more regulated endocrine response to stress, allowing them to better maintain energy homeostasis, sustain egg production, and optimize feed efficiency under challenging conditions (Zhang et al., 2015; Lou et al., 2019). In this context, CORT emerges as a particularly relevant candidate gene for tropical poultry systems, as its regulation is directly linked to the physiological mechanisms underlying thermal stress tolerance.

In chickens, Prolactin (PRL) is key for reproductive performance and egg laying behaviors (Bole-Feysot et al., 1998). SNPs in the PRL gene can impact ovulation and incubation, affecting how many eggs get fertilized and how many actually hatch. Some of these SNPs are also linked to parental behavior, influencing how attentive hens are with their chicks, making them key for reproductive performance (Bana et al., 2021).

The MC1R gene is one of the key determinants of chicken feather color, as it controls melanin in the cells and leads to the diversity of colors in poultry. Furthermore, some variations of MC1R can impact birds’ stress responses and growth rates. Changes in feather colors may also considerably impact sales in some commercial breeds. Finally, some SNPs have important effects of heat tolerance, a key trait for productive systems in tropical areas. The impacts on these different traits make this gene an important target for studies and breeding strategies (Qi et al., 2023).

The VIP (Vasoactive Intestinal Peptide) gene helps control egg production and brooding behavior in chickens. (Zhou et al., 2010). These genes have displayed SNPs that can be used as markers to boost productivity, notably by improving feed efficiency and gut health in chickens, helping them absorb nutrients better and fight off intestinal infections. Additionally, VIP plays an important role in modulating stress response, which can impact egg production and bird growth (Bana et al., 2021).

Interestingly, studies show that PRL gene expression can vary in terms of the dose of antiProlactin, suggesting its potential adjustment in poultry (Bana et al., 2021; Ogunpaimo et al., 2021). Furthermore, certain SNPs in this gene - specifically located in chromosomes 1, 2, 3, 9, 13, and Z (Du et al., 2020a) - can also impact egg laying quantities and brooding times (Zhou et al., 2010).

Such studies provide a basis for more precisely elucidating the molecular genetic mechanisms influencing egg laying in chickens. The development of molecular markers will further promote the breeding and selection of local breeds, and may lead to the establishment of centers for conservation and sustainable poultry development.

Chicken genetics are particularly complex, with constant repetitions, duplications, and dispersion of trait-defining SNPs through multiple chromossomes (Du et al., 2020a). The determination of Prolactin (PRL), for instance, is affected by regions in different chromossomes. This complexity, paired with the important impact of genetics on chicken production and reproduction, leads to the growing interest in research in this field.

With advances in genome-wide association studies (GWAS), several genes and QTLs (Quantitative Trait Loci) that influence laying performance have been identified. The growing interest in using markers to study these variations can play a crucial role in genomics. For example, GWAS has been used to identify variations in age at first egg (AFE) and egg number (EN) in Leghorn laying hens (Li et al., 2011). Most loci significantly connected to egg-laying performance through GWAS were found on chromosomes GGA1 (36 SNPs), GGA2 (4 SNPs), GGA3 (10 SNPs), GGA4 (7 SNPs), GGA5 (27 SNPs), and GGA21 (5 SNPs).

One SNP (GGA092322) on chromosome 13 of chickens (Gallus gallus) in intron 2 was connected to age at first egg (AFE) (Li et al., 2011). Other articles demonstrated that this variation in intron 2 of this SNP was also expressed in the brain, retina, and optical system of chickens (Kenzelmann et al., 2008).

There’s a single nucleotide polymorphism linked to egg number EN, located at 21. 67 Mb on GGA7in the 12th intron of the GRB14 gene. Active in the ovaries of mammals, the gene has relationships with the insulin receptor IR and the IGF receptor IGFR. These pathways influence ovarian function and follicle development in chickens, subsequently affecting how many eggs a hen lays. (Daly et al., 1996). In summary, IGF is responsible for governing ovarian function, as well as being related to follicle development in chickens (Kim & Seo, 2004).

Also regarding reproductive behaviour, studies have found four SNPs distributed among GGA1, GGA2, and GGA11 that may influence the number of eggs laid between days 300 and 462 (Fan et al., 2017).

Furthermore, ss1985401199, located on the Z sex chromosome, appears to be strongly connected to egg production from week 25 up until week 45; and an impressive twenty-three SNPs on GGA1, GGA5, and GGA23 demonstrate a clear connection with egg production. Among them, 21 are tightly packed in a 40. 1-43. 16 Mb area on GGA5. Also, there exists a QTL area spanning from 38. 62-38. 69 Mb on GGA5 associated with egg production at 300 days only 1. 41 Mb away from that aforementioned region. Research suggests that region may be a crucial QTL for egg laying (Shen et al., 2012; Yuan et al., 2015).

Regarding egg weight (EW), one SNP (rs13588750A) on GGA5 was significantly connected to EW at 300 days of age, with FBLN5 identified as the candidate gene (Zhang et al., 2015). Some studies link pelvic bone spread (PBS) to egg number, suggesting that this trait is strongly linked to egg production. During peak egg production, the abdominal organs in chickens increase the distance between the pelvic bones and the keel tip (Torres & Graner, 1951). The same author proposes a positive correlation between pelvic bone width and egg production. (r = +0.23 and pr = +0.16).

Cloacal temperature (CT) is considered a representative measure of body temperature, serving as a good indicator of comfort or thermal stress conditions, which can influence production indices (Brown-Brandl et al., 2003).

In the analysis of eggshell weight (ESW), two significantly associated SNPs were revealed: one located on GGA2 and another on GGA3. The promising genes identified were GALNT1 and BLK, respectively (Li et al., 2011).

One SNP located at 184.63 Mb on GGA1 showed a significant association with yolk weight (YW) in 40-week-old laying hens, with ATM as the corresponding candidate gene. Additionally, two SNPs on GGA1, situated at 8.1 Mb (171.2-179.3 Mb), demonstrated a significant correlation with eggshell thickness (EST) in 40-week-old laying hens. The candidate genes associated were LOC418918 and ENOX1 (Li et al., 2011).

Data extraction from the studies included the genes used in each study, and based on the methodology of each article, the genes and their frequency across all publications were analysed. These genes play crucial roles in chicken productivity and health, and SNPs within them hold great potential for use in genetic improvement programs. Identifying SNPs connected to traits such as growth, egg production, and disease resistance can help optimize poultry production, enabling more effective control over these factors. Combining these SNPs with other phenotypic and genetic traits can enhance production efficiency and resilience in chickens, with significant economic benefits for the poultry industry.

CONCLUSION

A comprehensive analysis of studies on single nucleotide polymorphism (SNP) genetic markers in poultry reveals the current state of scientific production, along with growing worldwide interest and collaboration in this field. China, the United States, and South Korea are examples of countries that are leaders in scientific output. The keywords “growth” and “egg production” show that poultry breeding and production traits are very important. The large number of Chinese, Korean, and Japanese institutions in this area also shows that Asia is a major center for scientific research in this field. The main genes of interest identified in SNP-based research include GH (Growth Hormone), IGF (Insulin-like Growth Factor), MHC (Major Histocompatibility Complex), CORT (Corticotropin), PRL (Prolactin), MC1R (Melanocortin 1 Receptor), and VIP (Vasoactive Intestinal Peptide). These findings provide valuable insights to guide future research and development strategies in poultry genetics, such as linking explored genes to zootechnical production outcomes.

ACKNOWLEDGEMENTS

We extend our sincere gratitude to Dr. Adriana Mello de Araújo for her essential contributions to this research. We also thank all members of the Graduate Program in Tropical Animal Science, classmates, and project partners for their valuable support. Special acknowledgment is due to the Molecular Biology Laboratory for providing critical infrastructure and technical assistance.

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• FUNDING
  This research was conducted without external financial support. All associated costs were covered by the authors.
• DATA AVAILABILITY STATEMENT
  The data that support the findings of this study are available from the corresponding author upon reasonable request.
• DISCLAIMER/PUBLISHER’S NOTE
  The published papers’ statements, opinions, and data are those of the individual author(s) and contributor(s). The editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions, or products referred to in the content.

Edited by

• Section Editor:
  Maria Fernanda Burbarelli

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Publication Dates

• Publication in this collection
  01 May 2026
• Date of issue
  2026

History

• Received
  22 Sept 2025
• Accepted
  23 Dec 2025