1 Introduction

Cotton is a very important crop in the global textile industry, but its yield is always affected by many pests and diseases, such as Verticillium wilt, Fusarium wilt, root-knot nematodes, whiteflies, aphids, and cotton bollworms (Li et al., 2016; Abdelraheem et al., 2019; Huo et al., 2023). These problems often reduce cotton yields and deteriorate fiber quality, posing great challenges to the sustainable cultivation of cotton. Common methods used in the past, such as spraying pesticides, are not very effective. Pesticides may not only be bad for the environment, but also easily cause pests to develop resistance. Therefore, people are now increasingly hoping to breed some cotton varieties that are resistant at the genetic level (Chen et al., 2021; Sun et al., 2023).

Now, the development of genomics has greatly changed the way we identify key genes and functions related to cotton disease and pest resistance. High-throughput technologies such as genome-wide association studies (GWAS), transcriptome analysis, and CRISPR/Cas9 gene editing can help us discover quantitative trait loci (QTLs), potential resistance genes, and regulatory networks that control these resistance traits (Li et al., 2017; Zaidi et al., 2019; Zhang et al., 2023b; Wang et al., 2024). These methods can use resistance-related loci in breeding, which not only facilitates us to select resistance with markers, but also provides new ideas for us to develop broader-spectrum and more durable cotton resistance.

This study not only summarizes some theories, but also wants to string together the new genomic technologies, key genes and practical methods currently used in cotton disease and insect resistance breeding. In fact, there have been many studies on how QTL is located and what molecular mechanisms are related to resistance. But what's interesting is that tools such as GWAS, transcriptome, and gene editing have shown quite different effects in different experiments, and specific problems need to be analyzed specifically. We will focus on picking out a few key sites to talk about their functions, and also talk about how these results are implemented in actual breeding. Although the focus is on cotton resistance, it is not limited to disease and insect prevention. Some new technologies and discoveries that have emerged in recent years have just opened up ideas for us to explore sustainable cotton cultivation-this is also a part we particularly want to emphasize.

2 Major Cotton Diseases and Insect Pests

2.1 Overview of significant cotton pathogens

Cotton is not always attacked by large-scale diseases, but once it encounters suitable climatic conditions, the situation often becomes difficult quickly. For example, in recent years, with the rise in temperature and changes in humidity, some pathogens that were originally well controlled have begun to break out frequently and spread quickly. Cotton is actually threatened by many things, not just a certain type of pathogen, but also fungi, bacteria, viruses, and nematodes. They often do not appear alone, but "go into battle" together. Verticillium wilt and Fusarium wilt are particularly typical. The former is caused by Verticillium dahliae, and the latter is mainly related to Fusarium oxysporum. Once the yield is affected, the loss is immediately apparent (McGarry et al., 2024). And like bacterial wilt, there are some diseases that occur on the leaves. Although they are not necessarily fatal, they will slow down the growth and reduce the fiber quality (Manavalan, 2022). As for viruses and nematodes, they may not kill cotton directly, but they are very troublesome to control and are prone to recurrence. If climate factors are not taken into account, it may be okay, but the reality is that pathogens are becoming more and more "adapted to the environment" and more and more difficult to deal with.

2.2 Key insect pests of cotton

Cotton can be attacked by many pests, some of which are piercing-sucking pests and some are chewing pests, and they can cause great losses. Common piercing-sucking pests include whitefly (Bemisia tabaci), big leaf aphid (Amrasca biguttula biguttula), thrips (Thrips tabaci) and cotton aphid (Aphis gossypii) (Sonalkar, 2020). There are also many chewing pests, especially cotton bollworms, such as pink bollworm (Pectinophora gossypiella), spotted bollworm (Earias insulana and E. vitelli) and American bollworm (Helicoverpa armigera), which are also very harmful to cotton (Razzaq et al., 2023). Although planting Bt cotton can control some bollworms, some pests are not affected by Bt cotton, especially piercing-sucking pests, which have increased in number (Figure 1) (Minorsky, 2018).

2.3 Combined impact on cotton productivity and quality

Pests and diseases combined will reduce cotton production and deteriorate the fiber quality, thus affecting the economic benefits of cotton cultivation as a whole (Tarazi et al., 2019). Pathogens and pests not only reduce production, but also deteriorate the length, fineness, and strength of cotton fibers (Asif et al., 2024). Future climate change may make the situation worse because it will increase the types and number of pests and diseases, and even make some previously uncommon pests common (Ateeq-Ur-Rehman et al., 2020). Therefore, in order to continue to grow cotton well in the face of frequent pests and diseases, good management methods are needed, and varieties that are resistant to diseases and insects are also needed.

3 Genomic Tools for Resistance Loci Identification

3.1 Genome-wide association studies (GWAS) and linkage mapping

In fact, at the beginning, when studying cotton resistance, many people relied more on traditional linkage maps. But as SNP chips became more and more popular, the resolution of GWAS has been significantly improved - especially when looking for quantitative trait loci (QTL) related to Verticillium wilt and Fusarium wilt, this method is very practical (Abdelraheem et al., 2019). Of course, GWAS alone is not a panacea, and it often needs to be combined with linkage map analysis. For example, in the study of bacterial wilt, these two methods were used together to find important loci such as BB-13, which can be used as molecular markers in breeding later (Gowda et al., 2022; Schoonmaker et al., 2023). However, the data differences between different experiments are also quite large. In order to solve this problem, researchers later used Meta-QTL analysis to integrate multiple studies and select consensus regions and candidate genes that are stable under different genetic backgrounds (Huo et al., 2023).

3.2 Transcriptomics and gene expression profiling

Gene expression differences are complex, and there are changes in different tissues and at different time points. It is not easy to really figure out which genes are related to resistance. The emergence of TWAS and RNA-seq has solved some of the problems. These technologies allow us to see some key expression QTLs (eQTLs) and gene modules, especially those involved in immune response or controlling ROS levels. But expression data alone is not enough. It must be analyzed together with GWAS or QTL data to more confidently lock in those genes that are directly related to disease resistance. Some candidate genes are expressed completely differently in resistant and susceptible varieties, and there are also differences in sequence (Zhao et al., 2021). Of course, not all genes that seem useful can be successfully verified in the end. But functional verification methods such as gene silencing have confirmed that some genes do play a key role in resistance mechanisms (Cui et al., 2021).

3.3 Pan-genome and comparative genomic approaches

Through pan-genomics and comparative genomics, we have a better understanding of the types of resistance genes in cotton and how they evolve. Studies have found that many resistance-related genes (RGA) tend to be concentrated in certain areas, and they change and evolve through some means, such as sequence exchange, tandem duplication or segment duplication (Chen et al., 2015). In addition, some comparative genomic analyses have also found that some gene fragments from wild cotton species have also entered the genome of cultivated species and may enhance disease resistance. Some new resistance mechanisms are also believed to be related to specific gene families (such as proteins with double TIR domains) (Zhang et al., 2023c). QTL integration analysis conducted under different research and environmental conditions helps to accurately identify those stable resistance sites and hotspots, which is very helpful for breeding work (Abdelraheem et al., 2017).

4 Key Loci Conferring Disease and Insect Resistance

4.1 NB-LRR genes and R-gene clusters

Not all resistance genes are so "high-profile", but NB-LRR does often appear in studies of cotton disease resistance, so people often call it "disease resistance gene". Some important discoveries actually come from GWAS and QTL mapping, especially when studying Verticillium wilt and Fusarium wilt, researchers have found many areas where NBS-LRR genes are concentrated (Zhang et al., 2015; Abdelraheem et al., 2019; Huo et al., 2023). Some of these areas correspond to only one disease, while others can resist several. Take GbCNL130 for example, it belongs to the CC-NBS-LRR type. By activating the salicylic acid pathway, it can also drive a group of resistance genes to "go online" together, and its defense against Verticillium wilt is very obvious (Li et al., 2021). However, not all genes are so "cooperative". For example, TIR-NB-LRR genes like GhRVD1 have a double TIR structure. Although it is relatively rare, it is closely related to the type of immune response that is particularly strong. It often appears in the mechanism that triggers cell death after pathogen infection and is critical for long-term resistance (Zhang et al., 2023c).

4.2 Bt and related transgenic loci for insect resistance

To protect cotton from insects, traditional methods alone are not enough. The introduction of genetically modified Bt technology is a turning point. Bt toxins can directly make chewing pests "lose their fighting power", so Bt cotton can express one or more Bt genes, and the effect is indeed good (Zafar et al., 2020). But this technology has not been without trouble. For example, in some places, cotton bollworms have gene mutations (such as HaTSPAN1), and as a result, Bt toxins are not so effective against them (Guan et al., 2020). In order to prevent resistance from being "cracked", scientists have come up with many ways. Some stack multiple Bt genes together, and some simply use Bt and RNAi technology together, with the aim of controlling different pests while making the effect more stable and less likely to fail.

4.3 Metabolic and signaling genes associated with resistance

Not all genes that help with resistance look like NB-LRR. Some genes are usually "silent", but they are critical in regulating metabolism and signal transduction. For example, GhnsLTPsA10, this gene encodes a lipid transport protein, which doesn't sound very "disease-resistant", but it does make cotton more "resistant" to Verticillium wilt and Fusarium wilt. It can also regulate phenylpropanoid metabolism, thereby affecting the synthesis of flavonoids and lignin, and has some effect on fighting cotton aphids and cotton bollworms (Chen et al., 2021). Similar ones include GhCPK33 and GhCPK74, which belong to the calcium-dependent protein kinase (CDPK) family. Mutants made by CRISPR-Cas9 have also confirmed that they are indeed involved in cotton's defense response (Wang et al., 2024). Therefore, in addition to the traditional "main" resistance genes, these "auxiliary" genes related to signals and metabolism cannot be ignored. Combining them may be a long-term solution for disease and insect resistance.

5 Functional Validation and Gene Editing Technologies

5.1 Gene silencing and overexpression studies

In order to verify whether the candidate resistance genes in cotton are effective, the commonly used methods are gene silencing and overexpression. Now there are some rapid methods, such as the transient expression system based on protoplasts, which can quickly detect whether the gene is effective without the need for stable transformation (Zhang et al., 2023a). These systems can also help us study how genes are expressed, where proteins are located, and whether there are interactions between proteins. These works have saved a lot of time for the study of cotton functional genomics.

5.2 CRISPR/Cas-based genome editing in cotton

Not all editing tools are suitable for cotton, especially this complex allotetraploid crop. However, the emergence of CRISPR/Cas has indeed made things much simpler. Systems such as CRISPR/Cas9 and Cpf1 (also called Cas12a) can now precisely edit a single gene or even different copies of multiple genes in cotton. It is quite smooth to use and has high efficiency, sometimes reaching about 87% (Gao et al., 2017; Li et al., 2022a). More importantly, the rate of accidental injury is not high, and the chance of error is relatively small. Of course, not every editing is so "ideal". In order to make the efficiency more stable, some studies have begun to use viruses to deliver sgRNA, and some have used geminiviruses as vectors (Li et al., 2019; Lei et al., 2022). Although these methods sound complicated, they do improve the accuracy in practice. Now, mutants made with these tools have been widely used in functional studies. Which genes are really useful in disease and insect resistance? Which ones have improved agronomic traits? Through these editing experiments, we can basically figure it out (Zhu et al., 2018).

5.3 Marker-assisted and genomic selection

Marker-assisted selection (MAS) and genomic selection (GS) are two breeding methods that combine molecular markers and genomic information to speed up the selection of resistant varieties. Through the gene editing and functional verification mentioned above, we can find some reliable resistance sites and then turn these sites into MAS markers. The GS method uses genome-wide marker data to predict which varieties are more valuable for breeding, thereby selecting good genotypes. If these methods are used in conjunction with gene editing, multiple disease-resistant genes can be combined to breed stronger and more pest-resistant cotton varieties.

6 Case Study: Field Implementation of Resistance Loci

6.1 Deployment of resistance loci in commercial cultivars

Scientists have now introduced resistance genes into commercial cotton varieties through traditional breeding and modern biotechnology, and have achieved some results. Technologies such as recombinases can precisely add multiple disease resistance genes to target cotton lines. Some lines have now integrated Verticillium wilt resistance genes and are used as basic materials for further breeding (Li et al., 2022b). In addition, since the 1990s, favorable alleles such as Lsnp1, Lsnp4, Lsnp5, Lsnp8 and Lsnp9 have been increasingly used, and their promotion has also helped improve the resistance of Chinese cotton to Verticillium wilt. Marker-assisted selection (MAS) and dedicated PCR markers such as KASP have also made it easier to use disease resistance QTLs (such as those for leaf curl virus and Verticillium wilt) in breeding.

6.2 Resistance performance in variable environments

Sometimes, resistance genes that perform well in the laboratory are not suitable for the field. But this is not always the case. Many studies have tested key resistance loci in the field and in the greenhouse, and the results are quite consistent. In particular, the QTL related to Verticillium wilt has similar resistance effects regardless of the year and the location. What's more interesting is that some QTLs not only prevent Verticillium wilt, but also Fusarium wilt, killing two birds with one stone. However, it does not mean that a single QTL can solve all problems. Sometimes, putting multiple resistance loci together can have a better effect. This "combination punch" approach can make cotton more stable and last longer in various environments (Abdelraheem et al., 2019). In addition, using multi-parent materials for experiments and combining them with meta-analysis can screen out QTL hotspots that are reliable under different genetic backgrounds and climatic conditions. This step is actually quite critical (Abdelraheem et al., 2017).

6.3 Institutional and private-sector collaborations

In order for these resistance genes to be truly used in the field, cooperation between research institutions, breeding units and enterprises is very important. The development and verification of molecular markers, as well as the sharing of genetic information through platforms such as CottonGen, have greatly simplified the breeding process and accelerated the promotion of resistant varieties (Figure 2) (Schoonmaker et al., 2023). This kind of cooperation allows genetic research in the laboratory to be truly implemented and turned into practical variety improvement results, which can ultimately effectively improve cotton's resistance to diseases and pests and help farmers better manage diseases and pests (Zhao et al., 2021).

7 Challenges and Future Perspectives

7.1 Evolution of pathogens and pests

Resistance is not a one-time thing. Even if the early performance is good, it may be "cracked" by pests and diseases after a few years. Black root rot is an example. It was not so common before, but it is becoming more and more frequent now. Some new pests that were not taken seriously before have also begun to appear and cause losses. Sometimes, these new threats will directly bypass the original effective resistance genes and even make Bt technology ineffective (Egan and Stiller, 2022). For example, some pests have adapted to Bt toxins and are not as responsive to Bt cotton as before (Khalid and Amjad, 2023). Therefore, it is definitely not enough to rely on existing methods alone. We must keep an eye on the changes in the fields, continue to monitor, and constantly look for new resistance resources, superimpose gene combinations, and try to extend the validity period.

7.2 Managing genetic trade-offs and complexity

Things are often not that simple. If we focus all our attention on a single resistance trait during breeding, we may unknowingly sacrifice other traits. Some disease-resistant genes are expressed more strongly, but the result is that the plants become more vulnerable to other diseases. Cotton itself is polyploid, which makes the relationship between genes more complicated. In many cases, a gene may affect more than one trait (Arora et al., 2017; Huang et al., 2021; Zhao et al., 2022). Of course, we hope to take into account resistance, yield, and fiber quality, but in reality it is not easy to do several things at the same time. Although tools such as CRISPR/Cas and genomic selection do bring new hope, we still have to be cautious in the operation process, so as not to solve a problem and bring new troubles (Yang et al., 2022).

7.3 Policy, regulation, and technology adoption

Technology is not the biggest problem, promotion is. There are more and more research results on gene editing and genetic modification, but not many are widely used. Behind this, in addition to the strict regulatory process, public acceptance is also a hurdle. Many people still have concerns about genetic modification, coupled with concerns about biosafety, and there is a lot of resistance to the implementation of new varieties (Khan et al., 2023a). To break the deadlock, technology alone is not enough, but also needs to be accompanied by clear and transparent policies. Concepts such as "genetically modified cleanliness" are worth promoting (Khan et al., 2023b). In addition, cooperation among scientists, companies, and policymakers is also necessary. Only through real collaboration can these cutting-edge research be turned into disease-resistant and insect-resistant cotton varieties that can be grown in the fields and that farmers are willing to use.

8 Concluding Remarks

The study of the genetic basis of cotton resistance to pests and diseases is not new, but progress has indeed been faster in recent years. The well-known gene cluster NB-LRR is still the focus of research, but there are also some new discoveries, such as the double TIR structural protein, which is very "intense" in triggering immune responses. Of course, not all data can show these differences at the beginning. It is necessary to combine phenotypic and genomic information to slowly piece together the outline of the resistance-related spectrum. Analysis methods such as GWAS, TWAS, and meta-QTL have their own focuses and are also useful. However, data alone is not enough. Some look like candidate genes, but they are not verified in the end. Scientists have done a lot of experiments through gene silencing and overexpression, and fortunately, a group of key genes that play a role in cotton defense have been confirmed. In addition, wild cotton and some old local varieties are not so easy to appear in the mainstream research field of vision, but their genetic resources have helped a lot and broadened the available resistance gene pool. These "non-mainstream" materials can sometimes bring unexpected breakthroughs.

At present, the discovery and verification of these resistance sites have begun to play a role in breeding. Through molecular marker-assisted selection (MAS) and genomic selection (GS) methods, researchers are using these resistance sites to breed more disease-resistant cotton varieties, such as varieties that are resistant to Verticillium wilt, Fusarium wilt and cotton leaf curl virus. In actual breeding projects, the use of high-quality alleles and multiple QTL clusters has indeed made cotton perform better in the field and maintain resistance longer. These technologies provide breeders with more accurate tools to help breed adaptable cotton varieties more quickly.

In order to truly turn these genomic studies into useful results, joint efforts are needed from all sides. There must be continuous cooperation between academic research, breeding work and enterprises to turn laboratory discoveries into results in the field. In the face of the ever-changing problems of pathogens and pests, it is also necessary to deal with the balance between genetic traits, and also solve some policy and management problems. Combining advanced genomic technologies, functional verification methods and actual field breeding is the key to promoting sustainable cotton production, so as to ensure that crops have long-term resistance.

Acknowledgments

We thank the anonymous reviewers for their careful review of the draft and their specific feedback helped us improve the quality of the manuscript.

Conflict of Interest Disclosure

The authors affirm that this research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest.

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