Abstract
Chicken layers are valued for their ability to produce eggs, an essential component of the human diet. Egg characteristics are influenced by genetic factors such as the growth differentiation factor‐9 (GDF‐9) gene, which plays a vital role in follicular development and ovulation. Variations in the GDF‐9 gene can lead to ovulation dysfunction, infertility, and reduced egg quality and production. This systematic review explored the genetic variation of the chicken GDF‐9 gene and its association with egg characteristics. Following the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) guidelines, databases including ScienceDirect, Google Scholar, PubMed, and Web of Science were used to search for articles using combinations of keywords: “chickens,” “GDF‐9 gene,” “genetic variation,” and “egg characteristics.” A total of 106 articles were retrieved, and five met the inclusion criteria. The reviewed studies identified several single nucleotide polymorphisms (SNPs) within the GDF‐9 gene—namely g.171515C>T, g.171530A>G, g.171529G>A, g.171554C>T, g.171577A>G, g.171600C>T, g.171541A>G, g.171560T>C, and g.171589C>T. Although no identical SNPs were shared among all breeds, these variants were associated with key egg traits such as age at first egg, egg number, and egg weight. The findings suggest that GDF‐9 gene polymorphisms hold strong potential for use in marker‐assisted and genomic selection to enhance reproductive performance and egg‐laying efficiency in chickens. However, the current findings are primarily based on conventional genetic association studies, and higher resolution transcriptomic approaches, such as single‐cell RNA sequencing, are needed to functionally validate these associations and clarify the molecular mechanisms underlying GDF‐9 regulation in reproductive traits. Further research using genetically diverse populations and incorporating gene expression analysis is recommended to validate these associations and strengthen the application of GDF‐9 in poultry breeding.
Keywords: egg quality, GDF-9 gene, layers, mutation, single nucleotide polymorphism
1. Introduction
The genetic improvement of layers plays a crucial role in enhancing productivity and efficiency in egg production, given the growth of the human population [1]. Egg characteristics such as egg weight (EW), shell quality, yolk index, albumen index, Haugh unit, and chemical composition influence both economic profitability and consumer preferences [2]. Those egg characteristics are affected by some genetic factors, such as the growth differentiation factor-9 gene (GDF-9) [3, 4]. The GDF-9 gene serves a vital role in follicle development, which directly influences the reproductive traits in layers [4]. Research indicates that GDF-9 gene mutations lead to ovulation dysfunction, infertility, and early ovarian failure, thus leading to poor egg characteristics and quantity [4]. Advances in molecular genetics, particularly genome‐wide association studies (GWAS), provide opportunities to identify single nucleotide polymorphisms (SNPs) associated with egg production traits [5]. Once favorable alleles are identified, marker‐assisted selection (MAS) can be employed to enhance breeding efficiency and reproductive performance [6]. Although studies by Liu et al. [4] and Huang et al. [7] have identified SNPs within the GDF‐9 gene and explored their association with reproductive traits, findings remain inconsistent across chicken breeds. According to our knowledge, there is no systematic review on the GDF‐9 genetic variations and their association with egg characteristics in chickens. Therefore, this review is aimed at systematically reviewing literature on the genetic variations of the chicken GDF‐9 gene and evaluating their association with egg characteristics. The findings will provide insight into the genetic basis of egg production, support the development of marker‐assisted breeding programs, and ultimately contribute to improving productivity and sustainability in the poultry industry.
2. Methods and Materials
2.1. Eligibility Criteria
Identification of the population, intervention, comparison, and outcomes (PICO) components of the research was performed for this systematic review, as described by Eriksen and Frandsen [8]. The “chickens” were defined as the population of the study, with the “GDF-9 gene” as an intervention, “genetic variation” as the comparison, and “egg characteristics” as the outcome. Before conducting the study, a preliminary search of the PICO components on Google Scholar, ScienceDirect, PubMed, and Web of Science was conducted.
2.2. Search Strategy for Identification of Relevant Studies
The methodology for this review used Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) by Sarkis‐Onofre et al. [9] when preparing the literature search for the review. Search databases such as Google Scholar, ScienceDirect, PubMed, and Web of Science were used to search for literature before the write‐up. The literature search for this systematic review included keywords such as chickens OR layers OR hens, AND “GDF-9 gene,” AND “genetic variation” OR mutation OR SNPs OR “genetic diversity” OR polymorphism, AND “egg characteristics” OR “egg traits” OR “egg quality” OR “egg morphology.”
2.3. Inclusion Criteria
This systematic review included articles written in English and investigated the genetic variation of the chicken GDF-9 gene and its association with egg characteristics.
2.4. Exclusion Criteria
The criteria for exclusion involved the following: duplicate articles, articles not written in English, and review articles. It also excluded articles that had only abstracts, articles that do not have keyword combinations, and the ones that use other animal species other than chicken.
2.5. Data Extraction
The data from the included articles was extracted by Maake Lehlogonolo Joel Morumbula and Thobela Loius Tyasi. The data included the first author′s name, year of publication, the country where the study was conducted, the journal that the article has been published, chicken breed, genetic variation of chicken GDF-9 gene, and egg characteristics.
3. Results
3.1. Searched Results
A total of 106 articles (n = 106) were retrieved from search databases such as Google Scholar (n = 24), PudMed (n = 26), ScienceDirect (n = 26), and Web of Science (n = 30) as shown in Figure 1. Forty articles (n = 40), which occurred as duplicates, were removed. After screening for title, abstract, and eligibility, 61 articles (n = 61) were excluded. A total of five articles (n = 5) were included in the systematic review.
Figure 1.
Flow chart of identification and selection of articles used in the systematic review.
3.2. Characterization of Included Studies
Characterization of the five included articles (n = 5) are illustrated in Table 1. The results indicated that four articles (n = 4) investigated polymorphisms in the GDF-9 gene in various Chinese indigenous breeds [4, 7, 11, 12]. Two articles (n = 2) investigated the contribution of other reproductive‐related genes, such as FOXL2 [12] and BMP-15 [7]. Only one article (n = 1) examined the levels of GDF-9 gene expression in the oviduct tissues of Lohman Brown, Golden Sabahia, and White Leghorn chickens [10]. Liu et al. [4] had the largest chicken sample size (n = 511), whereas Habashy and Adomako [10] had the smallest (n = 268).
Table 1.
Characterization of included studies.
| Author | Year | Country | Breed | Sample size | GDF-9 gene variation | Genotyping method |
|---|---|---|---|---|---|---|
| Habashy and Adomak [10] | 2023 | Egypt | Lohman Brown | 96 | Expression levels in oviduct tissues | RT‐qPCR (expression analysis) |
| Golden Sabahia | 102 | |||||
| White Leghorn | 70 | |||||
| Huang et al. [7] | 2015 | China | Shaobo hens | 350 | Polymorphisms in GDF-9 and BMP-15 genes | PCR/PCR‐RFLP and DNA sequencing |
| Liu et al. [4] | 2018 | China | Dongxiang blue‐shelled | 279 | Polymorphisms in GDF-9 gene | Direct DNA sequencing of PCR products; association analysis |
| Luhua chickens | 232 | |||||
| Lou et al. [11] | 2018 | China | Jinghai Yellow | 373 | Polymorphisms in GDF-9 gene | PCR‐SSCP screening followed by DNA sequencing |
| Qin et al. [12] | 2015 | China | Dagu hens | 360 | Polymorphisms in GDF-9 and FOXL2 genes | PCR‐SSCP and sequencing for SNP detection and genotyping |
Abbreviations: BMP-15, bone morphogenetic protein 15; FOXL2, forkhead box L2; GDF-9, growth differentiation factor‐9; PCR, polymerase chain reaction; PCR‐SSCP, polymerase chain reaction–single‐strand conformation polymorphism; RFLP, restriction fragment length polymorphism; RT‐qPCR, reverse transcription–quantitative polymerase chain reaction; SNP, single nucleotide polymorphism.
3.3. Publication by Country
The countries of origin for included studies are shown in Figure 2. The results indicated that four articles (80%) were published in China [4, 7, 11, 12], whereas one (20%) of the publications was from Egypt [12].
Figure 2.
Publication by country.
3.4. Publication by Year
All the articles included in the systematic review were published between 2015 and 2023 as shown in Figure 3. The results indicated that two articles (n = 2) were published in the years 2015 [7, 12], and 2018 [4, 11], and one article (n = 1) was published in 2023 [10].
Figure 3.
Publication by year.
3.5. Publication by Journal
The results indicated that all the included studies were published in various journals shown in Figure 4. The results indicated that the following journals had only one publication (n = 1) each: British Poultry Science Journal [7], Poultry Science [10], BioMed Research International [4], Animal Biotechnology [11], and Animal Gene [10].
Figure 4.
Publication by journal.
3.6. Distribution of Articles by GDF-9 Gene Genetic Variation
Figure 5 shows the distribution of articles by GDF-9 gene genetic variation. The results indicate that four articles (n = 4) reported genetic variation in the GDF-9 gene [4, 7, 11, 12], whereas one article (n = 1) focused on gene expression in oviduct tissues and its association with reproductive traits [10].
Figure 5.
Distribution by GDF-9 gene genetic variation.
3.7. Sequence Analysis
The sequence analysis of the GDF-9 gene is presented in Table 2. The results indicated that four articles (n = 4) reported sequence variations in different chicken breeds [4, 7, 11, 12], whereas one article (n = 1) focused on gene expression instead of sequence variation [10].
Table 2.
Sequence analysis.
| Author | Breed | Sequence analysis of the GDF-9 gene |
|---|---|---|
| Huang et al. [7] | Shaobo hens | Variations in coding regions of GDF-9 and BMP-15 |
| Qin et al. [12] | Dagu hens | Novel variants in GDF-9 and FOXL2 |
| Liu et al. [4] | Dongxiang blue‐shelled, Luhua | Exonic mutations in GDF-9 |
| Lou et al. [11] | Jinghai Yellow | Base‐replacement mutations in GDF-9 coding sequence |
| Habashy and Adomako [10] | Lohman Brown, Golden Sabahia, and White Leghorn | Expression study in oviduct tissues, no mutations reported. |
Abbreviations: BMP-15, bone morphogenetic protein 15; FOXL2, forkhead box L2; GDF-9, growth differentiation factor-9.
3.8. SNPs and Regions
Table 3 shows the polymorphisms of the GDF-9 gene. The results indicated that four articles (n = 4) identified SNPs in various chicken breeds [4, 7, 11, 12].
Table 3.
Single nucleotide polymorphisms (SNPs) and regions.
| Author | Breed | Sample size | Region | SNPs identified |
|---|---|---|---|---|
| Huang et al. [7] | Shaobo hens | 350 | Exon 1 (BMP-15) | C34T, A111G, C231T |
| Exon 2 (GDF-9) | G593A, T824C, C896T | |||
| Liu et al. [4] | Dongxiang blue‐shelled and Luhua | 511 | Promoter region | g.17156328G>T, g.17156387C>T, g.17156427A>G |
| Exon 1 | g.17156703A>C | |||
| Exon 2 | g.17158286A>G, g.17158915T>C | |||
| 3 ′ UTR | g.17159060T>C, g.17159524A>T, g.17159575C>T, g.17159624T>G, g.17159625T>C, g.17159748C>T, g.17159978A>G, g.17160044T>C, g.17160047G>A | |||
| Lou et al. [11] | Jinghai Yellow | 373 | Exon 2 (GDF-9) | g.2053G>A, g.2275T>C, g.2338C>T |
| 3 ′ UTR | g.2420T>C | |||
| Qin et al. [12] | Dagu hens | 360 | Exon 2 (GDF-9) | G1609T |
| Exon 2 (FOXL2) | A238G | |||
Abbreviations: 3 ′ UTR, 3 ′ untranslated region; BMP-15, bone morphogenetic protein 15; FOXL2, forkhead box L2; GDF-9, growth differentiation factor-9; SNP, single nucleotide polymorphism.
3.9. Genotypic and Allelic Frequencies
Table 4 presents the genotypic and allelic frequencies of the GDF-9 gene. The results indicated that three articles (n = 4) reported allele and genotype distributions [4, 7, 11, 12].
Table 4.
Genotypic and allelic frequencies.
| Author | Breed(s) | Gene | SNPs | Number | Genotypic frequencies | Allelic frequencies |
|---|---|---|---|---|---|---|
| Huang et al. [7] | Shaobo hens | BMP-15 | C34T | 81 | CC: 0.23 | C: 0.44 |
| 175 | CT: 0.50 | T: 0.56 | ||||
| 133 | TT: 0.38 | |||||
| A111G | 49 | AA: 0.14 | A: 0.46 | |||
| 207 | AG: 0.59 | G: 0.54 | ||||
| 94 | GG: 0.26 | |||||
| C231T | 98 | C1C1: 0.28 | C1: 0.55 | |||
| 189 | C1T1: 0.54 | T1: 0.45 | ||||
| 63 | T1T1: 0.18 | |||||
| GDF-9 | G593A | 203 | GG: 0.58 | G: 0.66 | ||
| 130 | GA: 0.37 | A: 0.34 | ||||
| 17 | AA: 0.05 | |||||
| T824C | 266 | TT: 0.76 | T: 0.91 | |||
| 84 | TC: 0.16 | C: 0.09 | ||||
| C896T | 46 | T1T1: 0.13 | C1: 0.77 | |||
| 74 | C1T1: 0.21 | T1: 0.23 | ||||
| 230 | C1C1: 0.66 | |||||
| Liu et al. [4] | Dongxiang blue‐shelled | GDF-9 | g.17156387C>T | 129 | CC: 0.46 | C: 0.69 |
| 128 | CT: 0.46 | T: 0.31 | ||||
| 22 | TT: 0.08 | |||||
| g.17156427A>G | 210 | AA: 0.75 | A: 0.865 | |||
| 63 | AG: 0.23 | G: 0.135 | ||||
| 6 | GG: 0.02 | |||||
| g.17156703A>C | 115 | AA: 0.41 | A: 0.635 | |||
| 126 | AC: 0.45 | C: 0.365 | ||||
| 38 | GC: 0.14 | |||||
| Luhua | GDF-9 | g.17156387C>T | 188 | CC: 0.81 | C: 0.895 | |
| 38 | CT: 0.17 | T: 0.105 | ||||
| 6 | TT: 0.02 | |||||
| g.17156427A>G | 94 | AA: 0.41 | A: 0.63 | |||
| 102 | AG: 0.44 | G: 0.37 | ||||
| 36 | GG: 0.15 | |||||
| g.17156703A>C | 73 | AA: 0.32 | A: 0.545 | |||
| 105 | AC: 0.45 | C: 0.455 | ||||
| 54 | CC: 0.23 | |||||
| Lou et al. [11] | Jinghai Yellow | GDF-9 | g.2053G>A | 169 | GG: 0.45 | G: 0.66 |
| 51 | AA: 0.14 | A: 0.34 | ||||
| 153 | AG: 0.41 | |||||
| g.2275T>C | 153 | TT: 0.43 | T: 0.66 | |||
| 41 | CC: 0.11 | C: 0.34 | ||||
| 167 | CT: 0.46 | |||||
| g.2338C>T | 167 | C1C1: 0.45 | C1: 0.67 | |||
| 40 | T1T1: 0.11 | T1: 0.33 | ||||
| 163 | C1T1: 0.44 | |||||
| g.2420T>C | 259 | T2T2: 0.70 | C1: 0.84 | |||
| 11 | C2C2: 0.03 | T1: 0.16 | ||||
| 100 | C2T2: 0.27 | |||||
| Qin et al. [12] | Dagu hens | GDF-9 | G1609T | 231 | TT: 0.642 | T: 0.821 |
| 129 | TC: 0.358 | C: 0.179 | ||||
| FOXL2 | A238G | 246 | AA: 0.683 | A: 0.842 | ||
| 114 | AB: 0.317 | B: 0.158 | ||||
Abbreviations: BMP-15, bone morphogenetic protein 15; FOXL2, forkhead box L2; GDF-9, growth differentiation factor-9.
3.10. Association of Genotypes With Reproduction Traits
The associations of GDF-9 gene variations with reproductive traits are illustrated in Table 5. The results indicated that four articles (n = 4) analyzed genotype–trait associations [4, 7, 11, 12], whereas one article (n = 1) reported on gene expression linked to reproduction [10].
Table 5.
Association of genotypes with reproduction traits.
| Author | Breed | Gene | SNPs | Reproduction traits | Genotypes | Significant |
|---|---|---|---|---|---|---|
| Habashy and Adomako [10] | Lohman Brown, Golden Sabahia, and White Leghorn | GDF-9 (expression) | — | EPR | — | ∗ |
| — | FSH | — | ∗ | |||
| — | LH | — | ∗ | |||
| — | E2 | — | ∗ | |||
| Huang et al. [7] | Shaobo hens | BMP-15 | C34T | AFE | CC CT TT | ∗ |
| WFE | CC CT TT | ns | ||||
| BWFE | CC CT TT | ns | ||||
| EN | CC CT TT | ∗ | ||||
| A111G | AFE | AA AG GG | ns | |||
| WFE | AA AG GG | ns | ||||
| BWFE | AA AG GG | ns | ||||
| EN | AA AG GG | ns | ||||
| C231T | AFE | C1C1 C1T1 T1T1 | ∗ | |||
| WFE | C1C1 C1T1 T1T1 | ns | ||||
| BWFE | C1C1 C1T1 T1T1 | ns | ||||
| EN | C1C1 C1T1 T1T1 | ns | ||||
| GDF-9 | G593A | AFE | GG GA AA | ns | ||
| WFE | GG GA AA | ∗ | ||||
| BWFE | GG GA AA | ns | ||||
| EN | GG GA AA | ∗ | ||||
| T824C | AFE | TT TC | ns | |||
| WFE | TT TC | ns | ||||
| BWFE | TT TC | ns | ||||
| EN | TT TC | ns | ||||
| C896T | AFE | T1T1 C1T1 C1C1 | ∗ | |||
| WFE | T1T1 C1T1 C1C1 | ∗ | ||||
| BWFE | T1T1 C1T1 C1C1 | ns | ||||
| EN | T1T1 C1T1 C1C1 | ns | ||||
| Liu et al. [4] | Dongxiang blue‐shelled and Luhua | GDF-9 | g.17156387C>T | AFE | CC CT TT | ∗ |
| WFE | CC CT TT | ∗ | ||||
| EWTA | CC CT TT | ns | ||||
| EN | CC CT TT | ns | ||||
| g.17156427A>G | AFE | AA AG GG | ns | |||
| WFE | AA AG GG | ns | ||||
| EWTA | AA AG GG | ∗ | ||||
| EN | AA AG GG | ns | ||||
| g.17156703A>C | AFE | AA AC GC | ∗ | |||
| WFE | AA AC GC | ns | ||||
| EWTA | AA AC GC | ns | ||||
| EN | AA AC GC | ns | ||||
| Lou et al. [11] | Jinghai Yellow | GDF-9 | g.2053G>A | AFE | GG AA AG | ns |
| WFE | GG AA AG | ns | ||||
| AEWD300 | GG AA AG | ns | ||||
| END300 | GG AA AG | ns | ||||
| g.2275T>C | AFE | TT CC CT | ns | |||
| WFE | TT CC CT | ns | ||||
| AEWD300 | TT CC CT | ns | ||||
| END300 | TT CC CT | ns | ||||
| g.2338C>T | AFE | C1C1 T1T1 C1T1 | ns | |||
| WFE | C1C1 T1T1 C1T1 | ns | ||||
| AEWD300 | C1C1 T1T1 C1T1 | ns | ||||
| END300 | C1C1 T1T1 C1T1 | ns | ||||
| g.2420T>C | AFE | T2T2 C2C2 C2T2 | ns | |||
| WFE | T2T2 C2C2 C2T2 | ns | ||||
| AEWD300 | T2T2 C2C2 C2T2 | ∗∗ | ||||
| END300 | T2T2 C2C2 C2T2 | ns | ||||
| Qin et al. [12] | Dagu hens | GDF-9 | G1609T | HHEP30 | TT TC | ∗ |
| HHEP43 | TT TC | ∗ | ||||
| HHEP57 | TT TC | ∗ | ||||
| HHEP66 | TT TC | ∗ | ||||
| EW30 | TT TC | Ns | ||||
| EW47 | TT TC | ∗ | ||||
| FOXL2 | A238G | HHEP30 | AA AB | ∗ | ||
| HHEP43 | AA AB | ∗ | ||||
| HHEP57 | AA AB | ∗ | ||||
| HHEP66 | AA AB | ∗ | ||||
| EW30 | AA AB | ns | ||||
| EW47 | AA AB | ∗ | ||||
Note: Single asterisk “∗” denotes association and double asterisks “∗∗” mean extremely associated.
Abbreviations: AEWD300, average egg weight at 300 days; AFE, age at first egg; BMP-15, bone morphogenetic protein 15; BWFE, body weight at first egg; E2, estradiol (a form of estrogen); EN, egg number; END300, egg number at 300 days; EPR, egg production rate; EW30, egg weight at 30 weeks; EW47, egg weight at 47 weeks; EWTA, egg weight at 300 days; FOXL2, forkhead box L2; FSH, follicle‐stimulating hormone; GDF-9, growth differentiation factor-9; HHEP30, hen‐housed egg production at 30 weeks; HHEP43, hen‐housed egg production at 43 weeks; HHEP57, hen‐housed egg production at 57 weeks; HHEP66, hen‐housed egg production at 66 weeks; LH, luteinizing hormone; ns, no association; WFE, weight of first egg.
4. Discussion
Egg production in chickens is a complex biological process influenced by multiple genes, including the GDF‐9 gene, which plays an essential role in follicular development and ovulation [3, 4]. Understanding the association between SNPs in the GDF‐9 gene and egg production traits is important for improving reproductive efficiency through molecular breeding approaches such as MAS [10, 13]. This systematic review is aimed at evaluating literature on the association between variations of the GDF-9 gene in chickens and egg characteristics. A total of five peer‐reviewed articles were included in this systematic review based on defined inclusion criteria. The findings revealed several SNPs within the GDF‐9 gene, among which nine were repeatedly reported: g.171515C>T, g.171530A>G, g.171529G>A, g.171554C>T, g.171577A>G, g.171600C>T, g.171541A>G, g.171560T>C, and g.171589C>T. Most of these polymorphisms were significantly associated with egg traits such as age at first egg (AFE), egg number (EN), and EW. [7] identified GDF‐9 polymorphisms (g.171515C>T and g.171530A>G) in Shaobo hens, which were strongly correlated with AFE and EN at 300 days. Similarly, Liu et al. [4] detected four SNPs (g.171577A>G, g.171529G>A, g.171554C>T, and g.171600C>T) in Dongxiang blue‐shelled and Luhua chickens that were associated with reproductive traits, including AFE, WFE, EWTA, EN, and BWTA. Lou et al. [11] further identified SNPs (g.171541A>G, g.171560T>C, and g.171589C>T) in Jinghai Yellow chickens, where certain diplotype combinations showed stronger associations with AFE, EN300, and average EW than individual SNPs. Qin et al. [12] reported novel SNPs (g.171527G>A, g.171589C>T, g.46642995A>G, g.46643104T>C, and g.46643151C>T) in Dagu hens, with specific haplotypes significantly associated with AFE, EN, and EW. Based on our knowledge, this is the first systematic review to summarize findings on the association between GDF‐9 gene SNPs and egg production traits in chickens; therefore, no direct comparison with previous systematic reviews could be made. The findings imply that genetic variants in the GDF‐9 gene may serve as useful molecular markers for selecting layers with superior reproductive performance and egg‐laying efficiency. These results can be applied to the design of genomic and MAS programs aimed at improving egg productivity and overall breeding efficiency in chickens. The contribution of this review to the body of knowledge is the identification of specific GDF‐9 SNPs that are consistently associated with reproductive and egg production traits. These markers provide a valuable foundation for molecular selection and genetic improvement in layer chickens. However, several limitations were noted. Most included studies were conducted in China, which may restrict the applicability of the findings to other chicken populations. In addition, small sample sizes in some studies may have reduced statistical power and affected the strength of associations reported. This systematic review suggests that there is insufficient evidence on the effects of GDF‐9 gene polymorphisms in genetically diverse or indigenous chicken populations. Thus, future studies should validate the identified SNPs using larger and more diverse chicken populations across different environments. Future research should also integrate polymorphism analysis with gene expression profiling to better understand the functional mechanisms of GDF‐9 in egg production. Although several studies have identified associations between GDF‐9 polymorphisms and egg production traits, the precise cellular and molecular mechanisms regulating follicular development remain poorly understood. GDF‐9′s regulatory action within ovarian follicles is anticipated to be very varied among various cell types, such as granulosa cells, theca cells, stromal cells, and oocytes, because it operates via the transforming growth factor‐beta (TGF‐β) signaling pathway [14]. This cellular heterogeneity cannot be fully resolved using conventional bulk transcriptomic approaches. To better understand how GDF‐9‐mediated TGF‐β signaling controls follicular development and egg production traits in chickens, future research should make use of single‐cell transcriptomic technologies like single‐cell RNA sequencing (scRNA‐seq) to characterize cell‐type–specific signaling dynamics [14, 15]. Future research should therefore move beyond bulk tissue‐level analyses and adopt single‐cell resolution approaches such as scRNA‐seq. This technology enables the characterization of heterogeneous ovarian cell populations, including granulosa cells, theca cells, stromal cells, and oocytes at different developmental stages, thereby providing deeper insight into follicular development and intraovarian signaling pathways [15]. Furthermore, scRNA‐seq can facilitate the identification of cell‐specific expression patterns and signaling interactions associated with GDF‐9 and its downstream pathways during folliculogenesis. Previous studies have demonstrated that GDF‐9 plays a critical role in oocyte–granulosa cell communication and follicular growth regulation [14]. To further dissect the regulatory network of the GDF‐9 pathway, future studies should employ scRNA‐seq to identify cell‐type–specific expression patterns and molecular interactions, as demonstrated in recent high‐resolution biological studies (PMID: 39245652; PMID: 39147128). Integrating traditional genetic variation analyses with emerging single‐cell transcriptomic technologies may represent the next frontier in improving poultry reproductive efficiency and precision breeding strategies.
5. Conclusion
In conclusion, the findings of this systematic review demonstrate that genetic variation in the GDF‐9 gene is significantly associated with key egg production traits, including AFE, EN, and EW. These results suggest that GDF‐9 polymorphisms can be used as potential molecular markers to enhance selection accuracy and improve reproductive performance in layer chickens. However, the practical application of GDF‐9 in poultry breeding programs will benefit from a deeper mechanistic understanding of its regulatory functions, particularly through advanced approaches such as single‐cell transcriptomic analysis, which may provide cell‐type–specific insights into reproductive pathways and improve precision breeding strategies.
Funding
No funding was received for this manuscript.
Conflicts of Interest
The authors declare no conflicts of interest.
Acknowledgments
I would like to acknowledge the University of Limpopo for granting access to articles.
Maake, Lehlogonolo Joel Morumbula , Mhlabini, Salome , Magonyane, Travor Tshepiso , Mahlo, Raisibe Lisbert , Mathapo, Madumetja Cyril , Tyasi, Thobela Loius , Genetic Variation of Chicken Growth Differentiation Factor‐9 Gene and Association With Egg Characteristics: A Systematic Review, The Scientific World Journal, 2026, 2659937, 11 pages, 2026. 10.1155/tswj/2659937
Academic Editor: Mugimane Manjanatha
Contributor Information
Thobela Loius Tyasi, Email: louis.tyasi@ul.ac.za.
Mugimane Manjanatha, Email: mugimane.manjanatha@fda.hhs.gov.
Data Availability Statement
Data are available upon request.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Data are available upon request.