REVIEW PAPER
A COMPREHENSIVE BIBLIOMETRIC ANALYSIS OF GENE FAMILY RESEARCH ON ABIOTIC OR BIOTIC STRESS
Yuhe Kan1, Dan Xi1, Huilian Liu1, Kunhao Yang2, Liang Yan3, and Ruirui Xu1*
1 College of Biology and Oceanography, Weifang University, Weifang, Shandong, 261061 P.R. China
2 Lunan Pharmaceutical Group Co., Ltd, Linyi, Shandong, 276000 P.R. China
3 School of Chemical Sciences, University of Chinese Academy of Sciences, Beijing, 100000 P.R. China
Corresponding author’s E-mail: xuruirui2006@163.com
ABSTRACT
The research of gene families on abiotic or biotic stress has been extensively studied for nearly 30 years, but the developments, emerging areas of growth, or new insight in the field haven’t been reported until now. This study was aimed to analyze the developments in the field of gene families related to abiotic or biotic stress. Thus, we conducted a bibliometric analysis utilizing the Bibliometrix R package to examine publications obtained from the WoS database. The findings indicate a significant annual rise in scientific production. Notably, China and Japan emerge as impactful contributors to this field. BMC Genomics is the most influential source, and Yong Zhou is the most influential author. The publication by Cantero et al., (2006) is recognized as the most influential in this context. Arabidopsis is still a popular model organism for gene family study under abiotic stress. The keywords expression, identification, tolerance, and gene family are the most discussed. The database, heat, and tolerance are trending topics in the future. These findings can guide researchers to search for intended information rapidly, find new topics and collaboration opportunities, and provide comprehensive bibliometric analysis in the research field of gene families related to abiotic or biotic stress.
Keywords: bibliometrics, gene family, abiotic or biotic stress, publication growth, trend topic
.
INTRODUCTION
Gene families consist of DNA segments that have undergone repeated duplication and divergence over time through common descent, originating from a shared ancestral DNA sequence that has been replicated and modified extensively (Liberles and Dittmar, 2008; Fang et al., 2022). It plays an ever-growing, crucial role in regulating genes and facilitating vital biological functions during both normal development and the progression of diseases (Grinberg and Millen, 2005; Ahmed et al., 2014). Recently, several gene families have been widely recognized, such as the homeobox gene family, the myosin gene family, and the heat shock protein family. The homeobox gene A10 (HOXA10) maintains embryonic development (Zanatta et al., 2010). The regulation of cell elasticity, cell migration, exocytosis, and endocytosis in B-lymphocytes can be attributed to the myosin gene family, including myosin 1 G (Myo1g) (Olety et al., 2010; López-Ortega et al., 2016). Heat-shock transcription factors (HSFs) regulate the heat-shock response and some crucial developmental processes in plants (Almoguera et al., 2020). In recent years, advancements in sequencing technology have led to an accumulation of scientific knowledge from gene family research, surpassing the information collected in previous years. For example, the genome-wide sequencing of 500 plant species has been completed (Antonelli et al., 2020), promoting research on plant genomics at the molecular level. Plant whole genome sequencing allows researchers to identify and classify new gene families based on sequence similarity and functional characteristics, trace the origin and evolution of gene families by comparing the genomes of different species, facilitates the functional annotation of gene families based on homology with well-characterized genes in other organisms. For example, Single Molecule Real Time (SMRT) sequencing platform can overcome some obstacles including repeats and GC rich regions in genome and was used to sequence and assemble gluten gene families from different cultivars of wheat (Zhang and Messing, 2017). For the rapid analysis of plant gene families, many gene family databases, including the Gene Family Database in Poplar (GFDP) (Wang et al., 2018), PlantGF (Li et al., 2022), GenFam (Bedre and Mandadi, 2019), and the Apple Gene Function & Gene Family DataBase (AppleGFDB) (Zhang et al., 2013), have been constructed. Those gene family databases can provide valuable resource for collecting gene family members and providing comprehensive annotations. For example, AppleGFDB can help collecting, storing, arranging, and integrating functional genomics information of the apple. It was estimated that the publications related to gene families may have exponential growth in the future.
The knowledge of the impact of abiotic or biotic stress on biology is essential for understanding ecosystem dynamics (Garchitorena et al., 2015), informing conservation and management practices (Hernández-Lambraño et al., 2019), safeguarding plants against biotic pests (Anuar et al., 2023), improving agricultural productivity (Calanca, 2017), and unraveling evolutionary processes (Balbinott and Margis, 2022). Recently, researchers have focused attention on studying the relationships between gene families and abiotic or biotic stress. For example, the WRKY gene family in plants plays a crucial role in mediating responses to both abiotic and biotic stresses, such as drought, salinity, and pathogen attacks (Bai et al., 2018). Understanding the functional roles of specific gene families, like WRKY, in stress responses provides valuable insights into the molecular mechanisms involved.
In order to examine and condense empirical studies on gene families related to research on abiotic or biotic stress, a conventional systematic literature review can establish connections or correlations among objectives, methodologies, outcomes, and variables found in existing literature (Uluhan et al., 2019; Aksu and Memon, 2023). This approach helps to generate generalizable knowledge and identify new avenues for further research. However, systematic literature reviews carry the potential for bias, encompassing factors such as selection bias, insufficient blinding, attrition bias, selective outcome reporting, and publication bias, among others (Owens, 2021). Hence, a quantitative bibliometric analysis is urgent to summarize global progress and trends.
Bibliometric analysis is a quantitative method used to evaluate and analyze scientific literature. It involves examining patterns and trends within bibliographic data to gain insights into the publication output, leading sources, most relevant authors, most productive countries, institutions, authors and their collaborations, top keywords, trend topics, and so on in this field (Aria and Cuccurullo, 2017). Overall, bibliometric analysis provides a systematic approach to understanding the structure, dynamics, and impact of scientific literature, offering valuable insights for researchers, funding agencies, and policymakers in making informed decisions regarding research priorities, collaborations, and resource allocation. Some bibliographic databases, such as WoS and Scopus, can help to find some basic information, including article type, publication per year, most cited authors, and most popular sources, but some data analysis, including bibliometric networks, emerging trends, citation networks of scientific publications and citation counts of research output, et al., must be conducted by using different types of software tools, such as VOSviewer (Van Eck and Waltman, 2010), CiteSpace (Chen, 2006), Publish or Perish (Harzing, 2007), and CitNetExplorer (Van Eck and Waltman, 2014). However, they are not flexible, and the result analysis is not comprehensive. Bibliomertix, based on the R language, is an extensive and powerful software tool for conducting bibliometric analysis in science (Moral-Munoz et al., 2020). In this paper, we perform bibliometric analyses using the Bibliomertix R package, which is flexible, quickly upgraded, and seamlessly integrated with other statistical R packages. This enables us to conduct a thorough analysis of current academic literature on gene families related to abiotic or biotic stress. The aim is to provide some vital information including annual scientific production, the influence ranking and network of countries, journals, authors, documents and trend topics in this field.
MATERIALS AND METHODS
The methodological framework of the bibliometric study was established according to a report by Aria and Cuccurullo (2017), which was first published in 2017. Within this section, the conventional workflow for bibliometrics is outlined, encompassing aspects such as study design, data collection, and data analysis, referencing the study conducted by Omotehinwa (2022) was in Figure 1.
Study design. The aim is to identify the knowledge base of study on gene families in abiotic or biotic stress. In addition, the study limitations should be considered or selected. To clarify our research objectives, the specific questions answered by this study are enumerated as follows:
- What is the annual scientific production in this field?
- What are the most influential countries and countries that collaborate?
- What is the most popular source and its network of co-citations?
- What are the most influential authors, authors’ co-citations and institutional collaborations?
- What are the most cited document and its networks of co-citation?
- What are the top keywords, networks of co-occurrences and trending topics among the keywords?
Data collection. The primary approach employed in this study is bibliometric research methodology to address the research problem. The experimental dataset is sourced from the abstract and citation database of WoS (Web of Science) (https://www.webofscience.com), which is the most common, well-known, and characterized by a higher-quality data source suggested by the official website for bibliometric studies. As an illustration, the WoS offers the "Keyword Plus" (ID tag), recommended by many publications as the optimal content field for conducting topic analysis, whereas Scopus lacks this metadata. We obtained 3520 documents in WoS core collection database when it involved defining search strings as follows: topic ("gene family" OR "gene families") AND topic ("abiotic stress" OR "biotic stress"). All records were exported to plaintext documents in batches via the WoS document search interface since 500 records at a time are limited in the database. The publication type only with “J” (articles) and language with “ENGLISH” were filtered, and documents of type “Letter”, “Note”, “Editorial”, “Retracted”, and author with “NA” were removed. The filtering returned 3176 documents analyzed in this study.
Data analysis and visualization. The filtered file was converted into bibliographic data frames for analysis after uploading. In this study, data analysis was carried out to determine the growth rate of publications, the basic information of countries, authors, institutions, sources, documents, keywords and their collaborations, co-citations, and co-occurrences as presented by networks, as well as trending topics. We use the command-based Bibliometrics package (v4.2.1) in R Studio to visualize the analysis. The analysis was performed on January 7, 2024.
RESULTS
Main information: The main information about the data collected was summarized in Table 1. 3176 articles published in 296 scientific journals between 1997 and 2023 from the WoS database were obtained through our filtering process. The usage of the author's Keywords (DE) or Keywords Plus (ID) is approximately double the number of relevant items. On average, there are five authors (4.67) per article. Other information includes the total number of authors and references, the author’s collaboration, and more information about the entire document in this dataset.
Annual scientific production: Figure 2 presents the annual scientific productions covering the period 1997-2023. This curve is divided into three phases, which are characterized by the years 1997-2013, 2014-2019, and 2020-2022. In 1997-2013, the number of publications was slightly increased, but it suddenly climbed to 113 papers in 2014, which was about two times that in 2013. The number of papers between 2014 and 2019 increased largely and kept about 100~250 each year. After 2019, it began to accelerate significantly until 2022, which has been the highest and most significant year regarding scientific output (570 publications). In 2023, the number of publications was slightly lower than in 2022.
The most productive, cited countries and their collaboration: We showed the top 10 countries with scientific contributions to this field (Figure 3a and Table S1). China was the most publication-productive country, which is about ten times more than India, which ranked in second place. The citation impact metrics (total citations and average article citations) were commonly used to measure the academic influence of countries. Total citations are a reflection of the overall impact and productivity of a country's research output, indicating a substantial body of influential research produced by its academics. On the other hand, average article citations serve as a metric to gauge the average impact of individual articles, suggesting that the country's research holds greater influence on a per-article basis. Figure 3b presents the most top 10 cited countries based on the number of single-country total citations. China is the first cited country. Somehow, the dispersion between China and India (the second ranked country) is quite noticeable in total citations (more than six times). For analysis of average article citations, the top 3 countries are Japan, the USA, and Germany. Noticeably, China is in first place with total citations, but it has relatively low average article citations and is in last place.
The most productive countries worked collaboratively (Figure 3c and Table S1). China has significantly contributed to the collaboration network, with every network member having collaborated with both China and the United States in some capacity. The collaboration between the United States and China is particularly noteworthy among these interactions.
The most popular sources and their co-citation network: It is crucial to comprehend journals that concentrate on publishing papers and assess their impact according to numbers of publications, total citations, and academic divisions of the Chinese Academy of Sciences (CASAD, a widely used ranking system in China) (Shen et al., 2020) (http://www.fenqubiao.com/). This information on publication sources will guide researchers to read or submit papers to those journals. The top 10 journals with the highest number of articles published were listed in Figure 4a and Table S2. In terms of numbers of publications, the most productive journals were Int. J. Mol. Sci. (291), Front. Plant Sci. (288), and BMC Genomics (180). However, BMC Genomics, with amazingly 6144 total citations, is the most leading journal, followed by Front. Plant Sci. (TC = 5496) and BMC Plant Bio. (TC = 4507). The co-citation network of top 10 sources with high total link strength in the database is presented in Figure 4b. Interestingly, all sources had almost same link numbers and same total link strength, meaning that they focus on the same research field.
The most relevant authors, author’s collaborations and their institutional collaborations: The current paragraph highlights the most prolific researchers, authors' productions over the years, authors' collaborations, and institutional collaborations in this field. Table 2 provides a summary of the top 10 influential authors ranked by DF (dominance factor) with their number of publications, total citations, and corresponding h-index et al. The h-index, proposed by J.E. Hirsch in 2005, quantifies an author's cumulative impact and performance by assessing the relationship between publications and citations, effectively measuring the fusion of quantity and quality in their scholarly output (Hirsch, 2005). Several bibliometric studies use the DF factor to filter influential authors (Gatto and Drago, 2020; Campra et al., 2022), since DF gives priority to the first author of multi-authored articles compared with h-index or total citation. Wei Hu has the highest h-index and total citations among top 10 authors. It was also highlighted that Yong Zhou was the first author in publications with multi-author articles. Figure 5a illustrates top 10 authors' production over time. Wei Hu and Yan Yan had more total citations in 2017 than in other years, as indicated by the darker circles.
The network of authors' collaborations showed eight clusters in Figure 5b. The blue cluster revealed that Yan Li (Nanjing Agricultural University), Jun Wang (Shanghai Jiao Tong University), and Jian Wang (Zhoukou Normal University) have well-established collaborations. A well-established collaboration (green cluster) can also be seen between Jing Wang from the Chinese Academy of Agricultural Sciences, China, Chao Chen from Northeast Agricultural University, China, and Hui Wang from Southwest Minzu University, China. Yan Yan had the most authors' collaborations with a high total link strength. In addition, it can be inferred that all authors in the cluster were Chinese, meaning that the Chinese authors largely facilitate collaborations.
Figure 5c shows the network of institutional collaborations. All the institutions clustered in blue and red were based in China except the National Research Institute for Agriculture, Food, and Environment (INRAE), the green cluster is institutions in the USA. Connections are largely between institutions within the same country. The Chinese Academy of Agricultural Science and the Ministry of Agriculture and Rural Affairs, both in China, have well-established collaborations. One of the most collaborative institutions in this field was the Ministry of Agriculture and Rural Affairs.
The most cited documents and document’s co-citations:Table 3 lists the top 10 articles including authors’ information, publication year, publication sources (journal), digital object identifier (DOI), global citation score (GCS), local citation score (LCS), and research area. The publications were ranked by LCS since it is reasonable and popular to measure the number of times each publication has been cited by other publications within the dataset analyzed in this study rather than GCS in the entire WoS database. The most influential publication with high LCS was Cantero et al., (2006).
The network of co-citations showed a relationship between two documents. As shown in Figure 6, we can observe that the research papers by Livak (2001) and Chen (2020) et al. have been co-cited by other documents. The color of the nodes in the co-citation network indicated different research fields. The blue nodes depict tools or web servers for method development focusing on bioinformation, and the red nodes relate to databases or protein evolution analysis of new functions.
The most relevant words, keyword co-occurrence assessments, and trend topics: The author’s keywords and keyword plus were retrieved from publications to show the relative keywords in these fields. The most significant keyword in the word cloud generated from keyword plus (ID) is arabidopsis, which encompasses other frequent keywords such as expression, tolerance, identification, and gene family (Figure 7a). The authors’ keywords in Table S3 were abiotic stress, gene expression, phylogenetic analysis, evolution, genome-wide analysis, and so on.
The Keywords Co-occurrence Network (KCN) (Figure 7b) was constructed using the top 50 keywords, which include both keyword plus and author's keywords. This approach aims to gain new insights into a field by examining the co-occurring keywords in the analyzed literature (Radhakrishnan et al., 2017). The blue and red clusters represent distinct research topics. Specifically, the blue cluster contains the most frequently occurring keyword, arabidopsis. The keywords in the red cluster had lower overall frequencies compared to the red cluster. However, they provided valuable information related to subjects of abiotic and biotic stress, including oxidative stress, salt tolerance (stress), disease resistance, abscisic acid (ABA), and salicylic acid (SA), as well as stress tolerance.
The trend topic plot is shown in Figure 7c. The trending topics before 2017 related to the keywords disease resistance, signaling pathways, cDNAs, key enzyme, and so on may involve research in the field of plant biology on plant signaling, disease resistance mechanisms, and related gene expression and metabolic pathways. The heat, tolerance and database were the most discussed and trend topic in 2019 and 2023, indicating that genome evolution and function in the field of biology may be trending topics.
Table 1. Main information and summary of the dataset.
Description
|
Period
|
1997-2023
|
Sources (journals)
|
296
|
Annual growth rate %
|
24.21
|
Document average Age
|
5.08
|
Average citations per doc
|
23.49
|
Average citations per year per doc
|
2.829
|
References
|
81428
|
Document Type
|
Articles
|
3176
|
Document Contents
|
Keywords plus (ID)
|
4893
|
Author's keywords (DE)
|
5423
|
Authors
|
Authors
|
14819
|
Author appearances
|
22925
|
Authors of single-authored docs documents
|
11
|
Authors of multi-authored docs documents
|
14808
|
Authors Collaboration
|
Single-authored docs
|
12
|
Docs per Author
|
0.214
|
Authors per docs
|
4.67
|
Co-Authors per docs
|
7.22
|
International co-authorships (%)
|
16.28
|
Table 2. The top10 most influential authors.
Rank by DF
|
Author
|
Dominance Factor
|
Tot Articles
|
Single- Authored
|
Multi- Authored
|
First- Authored
|
Rank by Articles
|
H-index
|
Total citations
|
1
|
Yong Zhou
|
0.48148148
|
27
|
0
|
27
|
13
|
1
|
12
|
349
|
2
|
Wei Wang
|
0.35294118
|
17
|
0
|
17
|
6
|
7
|
9
|
500
|
3
|
Wei Hu
|
0.32000000
|
25
|
0
|
25
|
8
|
3
|
19
|
1046
|
4
|
Yapeng Fan
|
0.18750000
|
16
|
0
|
16
|
3
|
9
|
5
|
65
|
5
|
Yan Li
|
0.11111111
|
18
|
0
|
18
|
2
|
6
|
7
|
319
|
6
|
Yan Wang
|
0.10000000
|
20
|
0
|
20
|
2
|
5
|
11
|
444
|
7
|
Jing Wang
|
0.07692308
|
26
|
0
|
26
|
2
|
2
|
9
|
195
|
8
|
Yu Wang
|
0.06250000
|
16
|
0
|
16
|
1
|
9
|
8
|
244
|
9
|
Juan Wang
|
0.05882353
|
17
|
0
|
17
|
1
|
7
|
6
|
131
|
10
|
Yan Yan
|
0.04545455
|
22
|
0
|
22
|
1
|
4
|
15
|
851
|
Table 3. The top10 cited documents.
Paper
|
DOI
|
LCS
|
GCS
|
Research area
|
Cantero, 2006, Plant Physiol. Biochem.
|
10.1016/j.plaphy.2006.02.002
|
19
|
124
|
rabidopsis annexin gene family
|
Hegedus, 2003, Plant Mol. Biol.
|
10.1023/B:PLAN.0000006944.61384.11
|
17
|
240
|
BnNAC gene family
|
Reyna, 2006, Mol. Plant-Microbe Interact.
|
10.1094/MPMI-19-0530
|
17
|
146
|
MAPK gene family
|
Jang, 2004, Plant Mol. Biol.
|
10.1023/B:PLAN.0000040900.61345.a6
|
16
|
368
|
PIP gene family
|
Wagner, 2002, Plant Mol. Biol.
|
10.1023/A:1015557300450
|
15
|
401
|
GST super-family
|
Maskin, 2001, Plant Sci.
|
10.1016/S0168-9452(01)00464-2
|
9
|
77
|
Asr gene family
|
Kaplan, 2004, Plant Physiol.
|
10.1104/pp.104.040808
|
9
|
328
|
BMY gene family
|
Schultz, 2002, Plant Physiol.
|
10.1104/pp.003459
|
7
|
186
|
AGP gene family
|
Skinner, 2005, Plant Mol. Biol.
|
10.1007/s11103-005-2498-2
|
7
|
199
|
CBF gene family
|
Sánchez, 2006, Planta
|
10.1007/s00425-005-0144-5
|
6
|
71
|
PEPC gene family
|
Table S1. Top countries’ scientific production.
#
|
Country
|
Articles
|
Freq
|
SCP
|
MCP
|
MCP_Ratio
|
1
|
China
|
2293
|
0.72426
|
2044
|
249
|
0.109
|
2
|
India
|
238
|
0.07517
|
208
|
30
|
0.126
|
3
|
USA
|
111
|
0.03506
|
74
|
37
|
0.333
|
4
|
Korea
|
83
|
0.02622
|
60
|
23
|
0.277
|
5
|
Brazil
|
33
|
0.01042
|
21
|
12
|
0.364
|
6
|
Italy
|
32
|
0.01011
|
15
|
17
|
0.531
|
7
|
Germany
|
28
|
0.00884
|
13
|
15
|
0.536
|
8
|
Spain
|
27
|
0.00853
|
17
|
10
|
0.370
|
9
|
Australia
|
24
|
0.00758
|
13
|
11
|
0.458
|
10
|
Canada
|
21
|
0.00663
|
17
|
4
|
0.190
|
Note: SCP: Single Country Publications; MCP: Multiple Country Publications
Table S2. Top10 preferred periodicals.
Sources
|
Articles
|
Total citations
|
CASAD
|
Int. J. Mol. Sci.
|
291
|
2585
|
Q2
|
Front. Plant Sci.
|
288
|
5496
|
Q2
|
BMC Genomics
|
180
|
6144
|
Q2
|
BMC Plant Bio.
|
162
|
4507
|
Q2
|
Plants
|
131
|
617
|
Q2
|
PLoS One
|
111
|
4129
|
Q3
|
Genes
|
98
|
1071
|
Q3
|
PeerJ
|
92
|
733
|
Q3
|
Plant Physiol. Biochem.
|
92
|
1993
|
Q2
|
Gene
|
80
|
1566
|
Q3
|
Note: The journals are ranked based on the numbers of articles. CASAD: Academic Divisions of the Chinese Academy of Sciences.
Table S3. Most significant words from author’s keywords and keyword plus.
#
|
Author Keywords (DE)
|
Articles
|
Keywords-Plus (ID)
|
Articles
|
1
|
abiotic stress
|
1120
|
arabidopsis
|
1210
|
2
|
gene expression
|
378
|
expression
|
844
|
3
|
gene family
|
222
|
tolerance
|
662
|
4
|
phylogenetic analysis
|
212
|
identification
|
486
|
5
|
expression analysis
|
203
|
gene family
|
479
|
6
|
expression pattern
|
164
|
protein
|
445
|
7
|
genome-wide analysis
|
117
|
evolution
|
440
|
8
|
drought stress
|
116
|
Rice
|
408
|
9
|
salt stress
|
112
|
abiotic stress
|
360
|
10
|
Evolution
|
110
|
drought
|
358
|

Figure 1 The workflow including study design, data collecting and data analysis in this study.

Figure 2 The publication growth.

Figure 3 (a) Most productive countries; (b) Citations per country; (c) Networks of countries collaboration. Note: SCP: Single country publications; MCP: Multiple country publications.

Figure 4 (a) Primary source journal; (b) Co-citation of the sources.

Figure 5 (a) Top-authors' production over the time. (b) Authors' collaboration network. (c) Institution collaboration network.

Figure 6 A co-citation network graph of documents.

Figure 7 (a) Word cloud generated from keyword plus (ID); (b) Keywords co-occurrence network (KCN); (c) Trend topics.
DISCUSSION
Abiotic stresses such as drought, salinity, heat, and cold, as well as biotic stresses such as diseases and pests, pose significant threats to global food security. Understanding the gene families involved in stress response can help in developing stress-tolerant crop varieties through genetic engineering or breeding programs. This bibliometric analysis that focuses on gene family research on abiotic or biotic stress tries to establish the study trend in terms of authors, citations, journals, country, and also topics.
The number of articles still increases, largely with an annual scientific production growth rate of 24.21% from 1997 to 2023 (Table 1). The reason behind the significant increase was that sequencing has been a mature and advanced technology to study the whole genome since 2014. After that, the progress in sequencing methods pioneered by Illumina, GenapSys, PacBio, and Nanopore, some has significantly increased sequencing volume to several billion nucleotides within a brief period and at a low cost (Satam et al., 2023), which also helped to establish gene family databases in recent years, such as GenFam (Bedre and Mandadi, 2019) (https://www.mandadilab.com/genfam/, 2018), PlantGF (Li et al., 2022) (http://biodb.sdau.edu.cn/PGF/index.html, 2022), GFDP (Wang et al., 2018) (http://gfdp.ahau-edu.cn/, 2018), and TAIR (Garcia-Hernandez et al., 2002) (https://www.arabidopsis.org/index.jsp, 2007). Hence, the inexpensive, high-throughput sequencing technology will greatly accelerate the exploration of the gene family involved in plants’ responses to environmental stress. In 2023, scientific production suddenly declined, largely due to the impact of COVID-19.
The countries’ academic influence was assessed by using the index of total citations and average citations. In terms of the number of publications and total citations, China stands out as the most productive in publishing research articles. Japan holds the most substantial global influence based on average total citation indicators, despite having a relatively smaller number of articles. So, the quality of publications from China still needs to be improved. Furthermore, China plays a crucial role in the collaborative network among the top countries and maintains strong collaboration with the USA. The increasing collaboration between China and the U.S. in the field of science can be attributed to several factors, such as the rise in Chinese research funding, a higher number of internationally educated Chinese scientists and engineers, and modifications to the databases that track China's contributions to science (Wagner et al., 2015).
The analysis finds that the Int. J. Mol. Sci. is the most preferred periodical for researchers publishing articles on gene families with research on abiotic and biotic stress between the years 1997 and 2023 because it has broad interest in biology (https://www.mdpi.com/journal/ijms/about). However, the journal “BMC Genomics” is the most influential in this field. In addition, six and four journals fall into Q2 and Q3, according to CASAD in 2022. 60% of journals based on gene families have relatively high quality (top 25% journals, Q2), indicated by CASAD, which was in accordance with the h-index.
The study reveals that Yong Zhou and Hu Wei are the most influential authors on the topic. In terms of dominance ranking, Zhou Yong emerges as the primary author. Their contributions primarily revolve around analysis, with a similar focus. Yong Zhou is an associate professor at the Key Laboratory of Crop Physiology, Ecology, and Genetic Breeding, Ministry of Education, Jiangxi Agricultural University, China. He has carried out various research, taught, and presented his results in biological functions, and expression regulation of plant leaf development, and stress associated with genes. Wei Hu is an associate researcher at the Institute of Tropical Bioscience and Biotechnology, Chinese Academy of Tropical Agricultural Sciences, China. Through his studies, he mainly engaged in research on the molecular mechanisms of plant responses to stress, plant genetic engineering, and plant genomics. In terms of author’s production over time, the publication by Wei Hu with the most total citations per year in 2017 reported that the PYL-PP2C-SnRK2 genes in bananas play a role in tissue development, fruit development, and ripening, as well as responding to abiotic stress (Hu et al., 2017). In addition, the regional cooperation among authors from China was obvious, as illustrated by the network of author collaborations. The institutional collaborations tend to have geographical boundaries, and Chinese institutions have strong cooperation.
The publications with high LCS mean high relativity in the field of plants’ responses to environmental stress. The authors in those publications all focus on gene family research with abiotic stress. As to the publications with high LCS, the most co-cited publication is Cantero et al., (2006), real-time quantitative PCR was employed to monitor changes in annexin expression in response to various abiotic stresses, including salt, drought, and high- and low-temperature conditions (Cantero et al., 2006). But, Nakashima et al., (2007) should pay more attention because of the high GCS. Nakashima proposed that OsNAC6, as a transcriptional activator in response to abiotic and biotic stresses in plants, activates the expression of peroxidase (Nakashima et al., 2007). The network of co-citations showed two clades, including developmental tools for evolution analysis and databases or web servers with sequence alignment analysis. Overall, the results indicate that the study of gene families in plants’ responses to environmental stress involves two main aspects, including the use of developmental tools including databases and network servers, reflecting the diversity and complexity of the field of plant gene family research.
The keywords in a publication indicate the primary research areas of focus, and the frequency of keyword occurrence indicates the topics emphasized in that specific research area. As per our analysis, Arabidopsis, gene expression, tolerance, and gene family are the most commonly recurring keywords. Arabidopsis, as a commonly used model plant, has significantly advanced our comprehension of gene family studies, aided by its comprehensively annotated genome and related databases like TAIR. Utilizing A. thaliana as a primary reference, researchers have unveiled a series of transcription factors in plants that exert a pivotal role in plant growth, stress responses, and metabolite synthesis. For example, a study focused on GbWRKY20 derived from Ginkgo biloba, recognized as a vital transcription factor in various plant processes, by performing phylogenetic analysis using Arabidopsis as a model. Expression analysis has elucidated that GbWRKY20 exhibits distinct responses to heat, drought, NaCl, cold, and methyl jasmonate treatments, implying its potential involvement in plant growth and responses to abiotic stresses and hormonal treatments (Zhou et al., 2021). Abscisic acid (ABA) is a phytohormone that plays a pivotal role in plant responses to various environmental stresses, particularly drought. In response to drought conditions, ABA initiates a range of physiological processes, including stomatal closure, modulation of the root system, organization of soil microbial communities, activation of transcriptional and post-transcriptional gene expression, and metabolic adjustments (Muhammad Aslam et al., 2022). SA, a naturally occurring plant hormone, holds a central role in facilitating stress tolerance among plants. It is notably recognized for its contribution to the plant defense response against a broad spectrum of biotic and abiotic stresses. The mechanisms governing SA's actions in stress tolerance can be intricate and continue to be an active area of research. Potential mechanisms underlying SA-mediated plant stress tolerance include: (1) SA's interaction with osmolytes; (2) engagement with mineral nutrients; (3) participation in ROS signaling and the modulation of antioxidants; (4) interplay with major secondary metabolites; and (5) interactions with other hormones (Khan et al., 2015). The trend topic, including heat, tolerance, and databases may involve the study of how plants evolve adaptive mechanisms to combat abiotic stresses, including adaptive strategies at the genetic and ecological levels. Last but not least, the database for gene function or evolution analysis is urgently needed to be developed for studying plants without a referenced genome.
Limitation: Our bibliometric review has some limitations. First, the publications available only in the English language were collected by us. Secondly, we only collected publications in the Web of Science core collection database rather than all databases. Hence, several publications related to gene families in abiotic or biotic stress research may be skipped; nevertheless, these electronic preprints in the preprint citation index database are not peer-reviewed articles.
Perspective: Future research referring to gene families and abiotic or biotic stress is expected to advance our understanding of the molecular mechanisms underlying stress responses and enable the development of innovative strategies for stress tolerance in organisms. Several key research directions are anticipated to shape this field in the coming years.
- Elucidating the epigenetic mechanisms is vital for underlying the stress response in plants. Multiple studies show that epigenetic modifications help plants rapidly adapt to aggressive biotic and abiotic stresses by activating or silencing gene expression (Ashapkin et al., 2020). In a recent report, Lin-Lin Hu proposed that histone modification (HM) genes in allotetraploid rapeseed could play a role in ammonium, salt, boron, cadmium, nitrate, and potassium stress responses by co-expression network analysis, suggesting the significance of BnaHMs in regulating stress adaptation in rapeseed (Hu et al., 2023). Additional epigenetic modifications, such as DNA methylation and acetylation, play a crucial role in regulating the expression of plant genes under diverse abiotic stress conditions (Roychowdhury et al., 2023).
- By integrating high-throughput sequencing data, researchers can identify key genes involved in stress responses, providing a comprehensive view of the regulatory mechanisms underlying gene family dynamics. For example, Qi Xie’s group has made breakthrough progress in understanding the molecular mechanism of plant alkali tolerance (Zhang et al., 2023). They detected a negative regulation of the alkaline tolerance major gene AT1 (Alkaline tolerance 1) in sorghum through genome-wide association study analysis. Knockout of AT1 and its homologous genes enhanced alkali tolerance in sorghum, rice (Oryza sativa), foxtail millet (Setaria italica), and maize (Zea mays), and increased yield under alkaline stress. Hence, high-throughput sequencing technology could help reveal new mechanisms for crop adaptation to environmental stress by identifying key genes.
- Applying the panomics pipeline or an omics-integration approach to decode a plant's responses to abiotic stress tolerance is instrumental in comprehending the molecular mechanisms underlying the plant's reactions to abiotic stress. This comprehensive analysis sheds light on the interplay of genes, transcripts, proteins, epigenomes, cellular metabolic circuits, and the resulting phenotype (Roychowdhury et al., 2023). For instance, both single-omics analysis (SOA) and multi-omics integration (MOI) studies have yielded novel insights into the early response of oil palm plants to salinity stress. This study identified specific genes, proteins, metabolites, and pathways directly impacted by this stress (Bittencourt et al., 2022). In the future, leveraging extensive data gathered from multi-omics layers, coupled with advanced bioinformatics and computational tools, will offer valuable insights into the mechanisms governing stress responses. This approach will facilitate the development of targeted strategies for enhancing stress tolerance.
- Exploiting the full potential of crop wild relatives (CWRs) can reveal unique alleles, gene family configurations, and regulatory elements associated with stress tolerance. By screening Asian Vigna wild types, Naito et al. identified genes associated with salt stress response, including sodium and potassium transporters (Naito et al., 2022). Utilizing CWRs as a source of crucial abiotic traits for developing well-adapted and climate-smart varieties will significantly contribute to sustainable agricultural production.
In summary, future research in the field of gene families and abiotic or biotic stress will leverage multidisciplinary approaches, advanced technologies, and comprehensive data integration to unravel the molecular mechanisms underlying stress responses and develop strategies for stress tolerance improvement. These research directions hold great potential for enhancing the resilience of organisms to environmental stressors and promoting sustainable agriculture and ecosystem management.
Conclusion: Abiotic stresses, including drought, salinity, heat, and cold, as well as biotic stresses such as diseases and pests, pose significant threats to global food security (Teshome et al., 2020; Zhang et al., 2022). Understanding the gene families involved in stress response can help in developing stress-tolerant crop varieties through genetic engineering or breeding programs (Bhatnagar-Mathur et al., 2008). Considering the expansion of sequencing data, systematic literature reviews are limited for researchers to get comprehensive knowledge of interesting objects. Hence, a quantitative bibliometric analysis is urgent to summarize global progress and trends.
The results revealed that annual scientific production has largely increased. China and Japan are impactful countries in this field. BMC Genomics is the most influential source, and Yong Zhou is the most influential author. The institutional collaborations have geographical proximity. The publication of Cantero et al. (2006) is considered the most influential publication. WhetherArabidopsis is still a popular model organism for gene family study with abiotic stress, the researchers may be likely to pay more attention to gene family research for exploring the response of abiotic stress based on Arabidopsis in the future. The keywords expression, identification, tolerance, and gene family are the most discussed. The database, heat, and tolerance are trending topics in the future. Our study offered valuable insights for researchers to identify new areas of research, relevant sources, and potential collaborations, enabling them to make informed decisions while studying the gene family for stress response research and its applications.
Funding: This work was supported by the General Program of Shandong Natural Science Foundation Grant Numbers ZR2022MC064, the Open Project Program of the State Key Laboratory of Crop Biology Grant Numbers 2021KF06 in China, and Weifang University Doctor Startup Fund Grant Numbers 2024BS22.
Conflict of Interest: The authors declare that they have no conflicts of interest.
Additional Information: The scripts used are saved in GitHub https://github.com/Yuhe-Kan/scripts_of_bibliometric_for_gene_family_of-stress_2023_12-main.
Supplementary Material: Supplementary material is available on
Acknowledgments: Yuhe Kan conceived and designed the experiments, analyzed the data, approved the final draft. Dan Xi, Huilian Liu, Kunhao Yang and Liang Yan contributed analysis tools and approved the final draft. Ruirui Xu conceived and designed the experiments, authored or reviewed drafts of the paper, approved the final draft.
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