Marker combination for identifying drought resistance of cotton and application of marker combination

Abstract

The invention relates to the technical field of molecular breeding, in particular to a marker combination for identifying drought resistance of cotton and application of the marker combination. According to the present invention, the marker combination comprises CIPK18 (CotAD02537), COR47 (CotAD58358), TPS7 (CotAD00585), TRG-31 (CotAD76943), and At4g27290 (CotAD23188), and can be used for the detection of tumor cells, tumor cells, tumor cells, tumor cells, tumor cells, tumor cells, tumor cells, tumor cells, tumor cells, tumor cells, tumor cells, tumor cells, tumor cells, tumor cells, tumor cells, tumor cells, tumor cells, tumor cells, tumor cells and tumor cells. On the basis of the condition of Internet of Things, the influence of natural drought on growth and development of cotton and a subcellular microstructure and the expression condition of related genes are researched, and the drought resistance character and the drought resistance molecular mechanism of the cotton are excavated; the up-regulation expression multiples of the markers in the drought-resistant material in nutritive organs such as leaves are remarkably improved, and the markers can be used for auxiliary identification of the drought-resistant character of the cotton.

Description

Technical Field

[0001] This invention relates to the field of molecular breeding technology, and in particular to a combination of biomarkers for identifying drought resistance in cotton and their applications. Background Technology

[0002] Studies have shown that arid and semi-arid regions account for approximately 36% of the total land area globally, and 43% of arable land. Among all abiotic stresses, drought stress causes the most damage to plants, second only to pests and diseases (Chen et al., 2019). Drought stress disrupts the water balance of crops, and stomatal closure further affects photosynthesis and respiration, thus impacting normal plant growth and development (Geilfus, 2019), leading to severe crop yield reduction (Boyer, 1982). Water scarcity is a common challenge facing cotton production worldwide (Zhang et al., 2019); the contradiction between limited land resources and the demand for cotton cultivation necessitates cotton varieties with stronger drought resistance (Zhang et al., 2019).

[0003] Currently, the screening or identification of drought-resistant cotton materials mainly adopts full-growth-cycle identification or artificial dry greenhouse seedling stage experiments. Full-growth-cycle cotton identification and dry greenhouse identification are in line with production realities and are more reliable in evaluation. However, cotton only has one growing season each year, which is long, requires a large area, has low identification efficiency, and is costly. It can only be used when there are few materials available. Furthermore, it has a significant impact from changes in the year and climate, is closely related to soil texture and field water holding capacity, and moisture is not easy to standardize. The comparability of results between years and between parallel experiments is also poor.

[0004] With the development of molecular biology, biomarker-assisted selection is considered an important tool for incorporating genetic diversity into breeding programs. Developing more and more effective biomarkers for drought resistance in cotton is of great significance to the development of cotton breeding and the cotton planting industry.

[0005] In view of this, the present invention is hereby proposed. Summary of the Invention

[0006] To address the aforementioned technical problems, this invention provides a combination of markers for identifying the drought resistance of cotton and their applications.

[0007] Specifically, the technical solution of the present invention is as follows:

[0008] In a first aspect, the present invention provides a combination of markers for identifying drought resistance in cotton, including CIPK18 (CotAD_02537), COR47 (CotAD_58358), TPS7 (CotAD_00585), TRG-31 (CotAD_76943) and At4g27290 (CotAD_23188).

[0009] This invention studies the effects of natural drought on cotton growth, development, and subcellular microstructure under Internet of Things (IoT) conditions, as well as the expression of related genes. It explores the drought resistance traits and molecular mechanisms of cotton and finds that, compared with the control conditions, under natural drought stress, the upregulation of CIPK18 (CotAD_02537), COR47 (CotAD_58358), TPS7 (CotAD_00585), TRG-31 (CotAD_76943), and At4g27290 (CotAD_23188) in vegetative organs such as leaves is significantly increased, which can be used as an auxiliary identification method for drought resistance traits in cotton.

[0010] The control conditions were: soil moisture content of 17.43% ± 0.667%, and / or, soil moisture content automatically detected by the IoT probe of 0.215 ± 0.02 m. 3 / m 3 The natural drought stress conditions are: soil moisture content of 12.02% ± 0.667%, and / or, the soil moisture content automatically detected by the IoT probe is 0.158 ± 0.02 m³. 3 / m 3 .

[0011] Specifically, under drought stress conditions, in the vegetative organs of drought-resistant cotton:

[0012] CIPK18 (CotAD_02537) expression was upregulated by more than 3 folds;

[0013] And / or, the expression level of COR47 (CotAD_58358) is upregulated by a factor of >3;

[0014] And / or, the expression level of TPS7 (CotAD_00585) is upregulated by a factor of >2;

[0015] And / or, the expression level of TRG-31 (CotAD_76943) was upregulated by a factor of >4.5;

[0016] And / or, the expression level of At4g27290 (CotAD_23188) was upregulated by a factor of >1.5.

[0017] Secondly, the present invention provides the application of the above-mentioned combination of markers or their detection reagents in the preparation of products for identifying the drought resistance of cotton.

[0018] Thirdly, the present invention provides a product for identifying the drought resistance of cotton, the product comprising the combination of markers or its detection reagent.

[0019] Preferably, the product is a drug or a reagent kit.

[0020] Fourthly, the present invention provides an apparatus for identifying the drought resistance of cotton, the apparatus comprising:

[0021] The detection module is used to detect the expression level of the biomarker combination in the test sample; the test sample is selected from vegetative organs under drought stress.

[0022] The input module is used to obtain the detection results from the detection module;

[0023] The judgment module is used to compare the detection results obtained by the input module with standard data to determine the drought resistance of cotton.

[0024] The output module is used to output the identification results.

[0025] Preferably, the sample to be tested is selected from leaves under drought stress.

[0026] Preferably, the judgment criteria of the judgment module include:

[0027] If the expression levels of CIPK18 (CotAD_02537) are upregulated by a factor of >3, COR47 (CotAD_58358) by a factor of >3, TPS7 (CotAD_00585) by a factor of >2, TRG-31 (CotAD_76943) by a factor of >4.5, and At4g27290 (CotAD_23188) by a factor of >1.5 in the sample to be tested, then it is judged to be drought resistant.

[0028] Fifthly, given that CIPK18 (CotAD_02537), COR47 (CotAD_58358), TPS7 (CotAD_00585), TRG-31 (CotAD_76943), and At4g27290 (CotAD_23188) are significantly upregulated in cotton leaves under drought stress, this invention also provides the application of the above-mentioned marker combinations or biological materials containing the above-mentioned marker combinations in the breeding of drought-resistant cotton varieties.

[0029] For example, bioengineering techniques can be used to introduce expression vectors containing the aforementioned genes into cotton plants, screening out lines with high expression of the corresponding genes to obtain drought-resistant cotton varieties. Alternatively, in traditional hybridization breeding processes, qualitative detection of the aforementioned genes on propagation materials or seedlings can be performed to achieve early screening of drought-resistant varieties and shorten the breeding cycle.

[0030] Beneficial effects:

[0031] This invention provides a biomarker combination for identifying drought resistance in cotton and its application. The biomarker combination includes CIPK18 (CotAD_02537), COR47 (CotAD_58358), TPS7 (CotAD_00585), TRG-31 (CotAD_76943), and At4g27290 (CotAD_23188). Based on the Internet of Things (IoT) framework, this invention studies the effects of natural drought on cotton growth, development, and subcellular microstructure, as well as the expression of related genes. It explores the drought resistance traits and molecular mechanisms of cotton, discovering that under drought stress, the upregulation of the aforementioned biomarkers in drought-resistant materials is significantly increased in vegetative organs such as leaves, and can be used as an auxiliary method for identifying drought resistance traits in cotton. Attached Figure Description

[0032] To more clearly illustrate the technical solutions in this invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be described below.

[0033] Figure 1 The results of soil moisture content change measurement based on the Internet of Things in Example 1 of this invention are shown below. Note: A represents the change in soil moisture under control conditions; B represents the change in soil moisture under drought stress conditions.

[0034] Figure 2 This shows the changes in soil electrical conductivity and temperature after continuous drought stress in Example 1 of the present invention. Note: A is the relationship between soil electrical conductivity and moisture content under drought stress; B is a comparison of soil temperature under control and drought treatment.

[0035] Figure 3 This is a comparison of two methods for determining soil moisture content in Example 1 of the present invention.

[0036] Figure 4 This is a comparison of the morphology of two materials under continuous soil drought stress in Example 1 of the present invention.

[0037] Figure 5 The image shows the changes in various organs of H177 under continuous drought stress in Example 1 of this invention. Note: A. Leaf; B. Bud; C. Main stem; D. Flower; E. Bell. The left side of the photo shows the control treatment, and the right side shows the drought treatment.

[0038] Figure 6 The field performance of the control treatment, drought treatment and rehydration treatment in Example 1 of the present invention is shown. Note: A, before rehydration; B, 1 hour after rehydration; C, 10 days after rehydration.

[0039] Figure 7 The values ​​represent plant height, relative leaf water content, chlorophyll content, and seed cotton yield in the control treatment, drought treatment, and rehydration treatment of Example 1 of this invention.

[0040] Figure 8 The results show the comparison of leaf morphology between two materials under control and drought conditions in Example 1 of this invention.

[0041] Figure 9 This figure shows a comparison of subcellular structures in the H177 control treatment and the drought treatment in Example 1 of the present invention. Note: The upper half of the figure represents the control treatment, and from left to right, the blue arrows point to starch grains, gray globules, chloroplast grana, mitochondria, and nucleus, respectively; the lower half of the figure represents the drought treatment, and the red arrows point to starch grains, cell membranes, gray globules, chloroplast grana, and mitochondria, respectively.

[0042] Figure 10 This figure shows a comparison of subcellular structures in the JF3018 control treatment and the drought treatment in Example 1 of the present invention. Note: The upper half of the figure represents the control treatment, with the blue arrows pointing from left to right to the vacuoles, grana of chloroplasts, nucleus, and mitochondria, respectively; the lower half of the figure represents the drought treatment, with the red arrows pointing to the gray globules, cell membrane, grana lamellae of chloroplasts, broken gray globules, and degraded mitochondria, respectively. Detailed Implementation

[0043] To investigate the impact of drought on cotton growth and development and to reveal the mechanism by which sustained natural drought affects cotton morphology and molecular expression, this invention uses cotton materials with varying drought resistance as experimental subjects. Under IoT conditions, changes in soil moisture, temperature, and electrical conductivity were continuously monitored. The study investigated plant height, chlorophyll content, relative leaf water content, subcellular microstructure changes in leaves, and the expression of leaf-related genes under conditions of full irrigation and sustained drought. The following results were obtained:

[0044] There was a significant linear positive correlation between soil moisture content measured by the traditional drying method and soil moisture content measured by the probe. Under continuous drought stress throughout the growth period, soil moisture content decreased slightly faster in the early growth stage of cotton and slower in the later stage. The relationship between soil moisture content and soil electrical conductivity showed an S-shaped curve. Under continuous drought stress, cotton leaves became smaller, lost their luster, and darkened to a grayish-brown color. Stems became shorter, thinner, and more fibrous, internodes became shorter, and hardness increased but elasticity improved. Buds became smaller, bud stalks became shorter, bracts became smaller, flowers became smaller, pedicels became thinner and shorter, petals were open and smaller, and most importantly, stigmas became significantly longer and extended beyond the stamens. Bolls became shorter and smaller, and boll stalks became shorter. Plant height, relative leaf water content, and leaf chlorophyll content at a soil moisture content of around 12% showed highly significant differences among cotton materials with different drought resistance. Among the drought-resistant material H177, under continuous soil drought stress, the chloroplast structure in the leaves... The chloroplasts maintained a relatively stable structure, with significantly fewer gray globules than in the drought-intolerant material JH3018. Chloroplast function remained relatively intact, and other subcellular structures were more complete than in the drought-intolerant material. Analysis of drought-resistance-related gene expression in leaves and stigmas showed that under continuous water stress, eight drought-resistance-related genes were upregulated in leaves compared to the control. In the drought-tolerant material H177, eight drought-resistance-related genes were upregulated in leaves after continuous drought stress, with five of them showing high fold-up. These five genes were CIPK18 (CotAD_02537), COR47 (CotAD_58358), TPS7 (CotAD_00585), TRG-31 (CotAD_76943), and At4g27290 (CotAD_23188). No genes were upregulated in the stigma.

[0045] The above results indicate that continuous monitoring of soil moisture changes based on the Internet of Things (IoT) in smart agriculture is accurate and feasible. A single thorough watering of a 30cm deep soil pool (with a bottom) before sowing ensures cotton can complete its entire growth cycle. A 30cm deep soil pool with a bottom can be used to assess the drought resistance of cotton throughout its entire growth period. Regarding the degree of plant height reduction, vegetative growth was more affected than reproductive growth after continuous drought stress, but vegetative growth recovered faster than reproductive growth after rehydration. Drought-resistant cotton materials maintain relatively high chlorophyll content, relative water content, and relatively intact subcellular structures in their leaves under continuous drought stress to achieve their drought resistance function. After continuous drought stress, eight genes in cotton leaves were upregulated, with five showing high fold increases, enhancing the cotton's drought resistance through joint regulation. No genes were upregulated in the stigma, indicating that the molecular function of the stigma remained unchanged under drought stress.

[0046] The technical solutions provided by the present invention will be described in detail below with reference to the embodiments, but they should not be construed as limiting the scope of protection of the present invention. Unless otherwise specified, the experimental methods used in the embodiments are all conventional methods; the materials and reagents used are all commercially available.

[0047] Example 1

[0048] This embodiment uses cotton materials with varying drought resistance as experimental subjects. Under IoT conditions, changes in soil moisture, temperature, and electrical conductivity are continuously monitored. The study investigates plant height, chlorophyll content, relative leaf water content, subcellular microstructure changes in leaves, and the expression of leaf-related genes under conditions of full irrigation and continuous drought. Specific experimental details are as follows:

[0049] 1. Materials and Methods

[0050] 1.1 Experimental Materials and Sources

[0051] The test materials included three upland cotton varieties, the sources and parent combinations of which are shown in Table 1. Among them, H177 is a drought-resistant material, and JF3018 is a non-drought-resistant material.

[0052] Table 1. Source, pedigree, and drought resistance of the tested materials

[0053] name Source or cultivation unit Parental combination drought resistance H177 Cotton Research Institute, Chinese Academy of Agricultural Sciences Handan 177 Selection Department drought resistant JF3018 Cotton Research Institute, Chinese Academy of Agricultural Sciences GK12×Zhongmian Institute 12 Not drought resistant

[0054] 1.2 Experimental Site and Field Planting

[0055] This experiment was conducted in 2021-2022 in a rain shelter at the experimental farm of the Cotton Research Institute of the Chinese Academy of Agricultural Sciences (located in Baibi Town, Anyang County, Anyang City, Henan Province). The soil type was yellow-brown soil with a light loam texture, similar to that reported by Wang Junjuan et al. (2017) and Dong Helin et al. (2010). The pre-frost seed cotton yield, quality, and agronomic traits were averaged from the two years' data, while other indicators were based on the 2022 data.

[0056] The sowing date for 2021 is April 25th, and the sowing date for 2022 is April 28th. Sowing is normally done in bottomed cement pools within a rainproof shed. The cement pools are 20 meters long, 2 meters wide, and 0.3 meters deep. Each material is sown in 10 rows, with 3 replicates. The row spacing is 50cm, and the row length is 2 meters. Thinning is done when the seedlings have one true leaf, with approximately 10-15 seedlings per row.

[0057] 1.3 Soil drought stress treatment and soil moisture measurement

[0058] Both the control and drought-stressed ponds were housed in rainproof sheds. Before sowing, each pond was tilled and thoroughly irrigated to retain sufficient soil moisture. In the control ponds, irrigation was conducted after the soil moisture level dropped to a certain point, ensuring the soil moisture content remained above 15%. The first irrigation was approximately June 18th (about 50 days after sowing). In the drought-stressed ponds, no irrigation was provided from sowing to harvest, allowing the soil moisture to decrease naturally. Re-irrigation treatment: When the cotton seedlings of the non-drought-resistant material showed signs of true leaf wilting (around July 9th, about 70 days after sowing), re-irrigation was conducted. The re-irrigation treatment was approximately 20 days later than the control treatment's first irrigation. After re-irrigation, irrigation was generally synchronized with the control, maintaining the soil moisture content at no less than 15%. Soil moisture was monitored in real time for the control, drought, and rehydration treatments. Soil moisture measurement was conducted simultaneously using smart agriculture IoT monitoring and the traditional drying method. The specific procedure for soil moisture measurement using the drying method is as follows: Throughout the growing season, soil samples were taken at each key time point (approximately every 7-10 days) using a soil sampler. The traditional drying method was used to measure soil moisture. The sampling method involved taking samples around each probe, with three replicates for each point. Soil samples were taken from the soil surface to the bottom of the tank at each point. After sampling, the soil was quickly placed into a well-sealed, pre-weighed aluminum box (W1) and weighed (W2). The soil was then dried at 80°C for 8 hours, cooled to room temperature, and weighed (W3). The soil moisture content (%) was calculated, and the average of the three samples represents the soil moisture content obtained by the traditional drying method.

[0059] Soil moisture content / % = [(W2-W1)-(W3-W1)] / (W3-W1)×100

[0060] 1.4 Installation of IoT in Smart Agriculture

[0061] Cloud-based intelligent data management and cloud-based equipment management were employed for real-time soil moisture monitoring in control, drought, and rehydration treatments. Data management enables real-time remote acquisition, transmission, download, and analysis of data, images, and videos. Equipment management allows for real-time monitoring and remote control of equipment information. After sowing, a soil three-parameter sensor (SMCS-3) was installed at a depth of 20cm in the middle of the cotton rows to measure soil moisture, temperature, and electrical conductivity. Specifically, the probe was inserted parallel to the soil profile after excavation to the required depth, ensuring a true reflection of the actual soil conditions as the profile structure remained unchanged. One probe was installed every 5 rows, and every 3 probes were connected to one data acquisition unit (CR1000 model). Two data acquisition units were used for the control and drought treatments respectively. These units were connected to a remote controller (SMCC) via the Internet of Things (IoT). Soil moisture, temperature, and electrical conductivity data were monitored and recorded every 5 minutes and uploaded to a computer or mobile phone. Soil moisture and temperature changes could be monitored and viewed anytime, anywhere via the internet (Smart Agriculture website www.smartcotton.cn). The units for soil moisture, temperature, and electrical conductivity are m, respectively. 3 / m 3 ℃ and mS / cm.

[0062] 1.5 Measurement and sampling of traits such as plant height and chlorophyll content

[0063] When the moisture content in the drought stress treatment pond dropped to a certain level, the drought stress symptoms of both materials became obvious. Plant height, chlorophyll content of the second-to-last leaf, and relative leaf water content were measured for the three materials after rehydration for 10 days, including the control and drought stress treatments. Three biological replicates were performed for each variety and each treatment. Plant height was measured as the distance from the cotyledon node to the growing point. SPAD values ​​were determined in vivo using a chlorophyll meter (SPAD.502Plus, Japan). For relative leaf water content, leaves from each treatment were quickly harvested, placed in a plastic bag, weighed, and then blanched at 105℃ for 30 minutes in a constant temperature oven, followed by drying at 80℃ for 8 hours, and then weighed again.

[0064] Relative moisture content of leaves (%) = (fresh weight of leaves - dried weight of leaves) / fresh weight of leaves × 100

[0065] 1.6 Changes in subcellular structure of cotton leaves under drought stress

[0066] Around July 30th, the top three leaves of drought-resistant material H177 and non-drought-resistant material JF3018 were collected under both control and drought conditions (soil moisture around 9%). Sample collection: The fixative was pre-treated: 1.5 ml of fixative was added to a 2 ml round-bottom centrifuge tube and pre-cooled at 4°C for 5-6 hours. Sampling method: Samples were taken from the same part (top three leaves) of both drought-treated and control varieties (lines). Using a sharp scalpel, five 0.5 cm × 1.0 cm pieces were cut from each leaf, avoiding the veins. The samples were immediately immersed in 2% glutaraldehyde fixative (prepared with 0.05 mol / L phosphate buffer, pH 6.8). After sampling, the centrifuge tubes were placed under a vacuum pump at 0.2-0.4 psi for approximately 1 hour to remove gas from the leaf tissue, allowing the sample to sink into the fixative and enabling better penetration of the fixative into the leaf tissue. Five small samples were taken from the same leaf and placed in the same centrifuge tube. A separate tube was taken from each treatment for sample backup. Subsequent sample embedding, sectioning, and electron microscopy observation were completed in the key laboratory of Nanjing Agricultural University.

[0067] Sample embedding and sectioning: Following the method of Zhu Lixia et al. (1983), after sample fixation, the samples were dehydrated with gradient ethanol and embedded in Embed-812 resin to prepare embedding blocks. Each sample embedding block was sectioned with a diamond scalpel to a thickness of 60 nm. The sections were stained with uranium acetate and lead citrate, and observed and photographed under a Hitachi 7800 transmission electron microscope.

[0068] 1.7 Real-time quantitative analysis of drought resistance-related genes in leaves

[0069] 1.7.1 Sampling and RNA Extraction

[0070] The second-to-last leaves and stigmas of the control, drought-treated, and rehydrated plants (10 days after treatment) were collected using the EASYspinPlus plant RNA rapid extraction kit produced by Beijing Adley Biotechnology Co., Ltd., and RNA was extracted from them. The concentration and purity of total RNA were determined. 260 / 280 =2.0, while using a mass concentration of 10 g·L －1 RNA integrity was detected by agarose gel electrophoresis. Based on literature reports by Wang Junjuan et al. (2016; 2019) and Yin Zujun et al. (2019), the CDS (Coding DNA sequence) sequences of 18 genes related to cotton stress resistance were searched and downloaded from the Cotton FGD database (https: / / cottonfgd.org / about / download.html). Real-time quantitative PCR specific primers were designed using Primer5 software (Table 2).

[0071] Table 2 Primers for real-time quantitative analysis of 18 drought-related genes

[0072]

[0073]

[0074] 1.7.2 Real-time fluorescence quantitative analysis.

[0075] Using Histone-3 (Accession No.: AF024716) and 18S (Accession No.: L24145) genes as internal control genes, real-time quantitative PCR was performed on three drought-related genes. The PCR program was set as follows: 94℃, 30s; 94℃, 5s; 55℃, 34s; 72℃, 34s, for a total of 40 cycles. Relative quantification of the target genes was performed using 2... –ΔΔCT The method (Afrin et al., 2015) included 3 biological replicates and 3 technical replicates per treatment, and the expression level was statistically analyzed by mean.

[0076] 1.8 Instruments and Equipment

[0077] Chlorophyll meter (SPAD.502Plus, Japan); GZP-250B intelligent light growth chamber; BCD-215KADZ Haier refrigerator; Nanodrop2000 nucleic acid analyzer; CS101-2EB electric heating drying oven; transmission electron microscope (TEM) was Hitachi 7800.

[0078] 1.9 Data Processing

[0079] Microsoft Excel 2013 was used for general data processing, and Stata 11.0 was used for statistical analysis.

[0080] 2 Results

[0081] 2.1 Soil Changes under Control Treatment and Drought Stress

[0082] 2.1.1 Changes in soil moisture in the pond under continuous drought stress

[0083] On April 20th, both the control and drought-treated ponds were thoroughly watered. Sowing began on April 28th, and probes were immediately installed after sowing to collect data. Seedlings emerged completely around May 8th (10 days after sowing), and data collection continued throughout the growth period until harvest on September 30th. Observations throughout the growth period revealed that after cotton sowing and emergence, the soil moisture content in the drought-stressed pond decreased slowly each day, remaining stable within 24 hours. Figure 1As shown in Figure B, at a soil depth of 20cm, the soil moisture content decreased rapidly before May 16th, then decreased relatively slowly between May 17th and July 3rd, and then decreased even more slowly after July 4th. The change curve is L-shaped, and the soil moisture content variation range throughout the growing season is 0.08-0.366m. 3 / m 3 The probe detected a daily variation of approximately 0.001m. 3 / m 3 -0.002m 3 / m 3 Therefore, the probe is sensitive to moisture detection. The average soil moisture content in the drought-treated pond throughout the entire growth period was 0.150 m³. 3 / m 3 Because the pond was only 30cm deep and the soil moisture content was insufficient, the probe reading in the control pond dropped to 0.171m. 3 / m 3 Watering was carried out approximately 8 times throughout the entire growth period, specifically on June 18th, July 5th, July 14th, July 30th, August 11th, August 18th, August 26th, and September 13th, until the soil in the control ponds reached saturation. The water level probe sensitively detected changes in moisture content after each watering. Watering was stopped approximately one hour after watering when the soil in the control ponds reached saturation. The average soil moisture content in the control treatment ponds throughout the entire growth period was 0.221 m³. 3 / m 3 .

[0084] 2.1.2 Changes in soil electrical conductivity and temperature after prolonged drought stress

[0085] Depend on Figure 2 As shown in Figure A, with increasing drought stress, soil moisture content and soil electrical conductivity decrease slowly, exhibiting an S-shaped curve. The soil moisture content reaches approximately 0.080 m³ / s. 3 / m 3 -0.143m 3 / m 3 Within a certain range, soil electrical conductivity changes slowly with increasing moisture content; when soil moisture content is around 0.145 m... 3 / m 3 -0.193m 3 / m 3 Within a certain range, soil electrical conductivity and moisture content showed a significant positive linear correlation; soil moisture content greater than 0.241 m³... 3 / m 3 At that time, the soil electrical conductivity slowly increased again.

[0086] Depend on Figure 2As shown in Figure B, before irrigation in the control pond on June 18th, the soil temperatures in both the control and drought treatment ponds were similar. After June 18th, due to frequent watering, the soil temperature in the control pond was lower than that in the drought treatment pond. Throughout the growing season, soil temperature in both treatments varied with the seasons. Between April 14th and May 28th, soil temperature steadily increased. Between June 1st and August 25th, soil temperature remained relatively stable in both ponds. After the end of August, soil temperature began to slowly decrease.

[0087] 2.2 Comparison of traditional measurement methods and IoT monitoring of soil moisture content

[0088] To verify the relationship between moisture content measured by sensors in smart agriculture and moisture content measured by traditional drying methods, soil samples were taken at key time points throughout the growing season. Three samples were taken at fixed points near each sensor, dried, and the soil moisture content was measured. The average of the three samples was compared with the soil moisture content detected by the sensor at the corresponding time points. The soil sampling dates were April 25, April 28, May 6, May 27, June 18, July 30, and August 18.

[0089] like Figure 3 As shown, there is a significant linear positive correlation between soil moisture content measured by the traditional drying method and soil moisture content measured by the probe, with a correlation coefficient of r = 0.96609. The formula is: y = 95.0021x - 2.9947, where y represents the soil moisture content (%) measured by the traditional drying method and x represents the soil moisture content (m³) detected by the probe. 3 / m 3 The results show that the moisture content detected by the probe at a depth of 20cm in a soil layer with a total depth of 30cm can predict the moisture content of the entire soil layer. This also demonstrates that it is feasible to monitor soil moisture changes using the Internet of Things, and the soil moisture content can be predicted at any time based on this formula.

[0090] 2.3 Morphological changes in cotton plants under continuous water stress

[0091] Depend on Figure 4 It can be seen that under natural drought stress, on June 18th, the cotyledons of both materials remained intact, showing no wilting or drought symptoms. At this time, both materials had 5-6 true leaves, and the soil moisture content detected by the probe was 0.178 m³. 3 / m 3On June 25th, both materials showed yellowing of cotyledons, but there was no difference in symptoms between the two materials. Starting July 9th, the difference in drought symptoms between the two materials became significant. In the drought-resistant material H177, the leaves remained flat, while in the non-drought-resistant material JF3018, the leaves began to show slight wilting. At this time, the IoT probe detected a soil moisture content of 0.158 m³. 3 / m 3 As described in section 2.2, the soil moisture content measured by the traditional drying method was approximately 12.02%. At this point, the morphological differences between the two drought-resistant varieties were significant. For Zhong H177, leaf wilting was not obvious before August 18th, but became slightly wilted by September 22nd when the seeds opened. In contrast, for Zhong JF3018, leaf wilting began on July 9th, with cotyledons already fallen off, and wilting gradually became more pronounced thereafter.

[0092] Both cotton plants, after being subjected to sustained drought stress under natural conditions, showed a common characteristic: vegetative growth essentially ceased after July 9th, with no new leaves appearing, and plant height stopped increasing, entering a natural topping-out phase. Reproductive growth, however, continued, with the main stem becoming more elastic, and the leaves thickening and darkening in color. The other two cotton plants, although no longer exhibiting vegetative growth, retained most of their true leaves until August 18th, except for the cotyledons. Even after the cotton began to open its bolls on September 22nd, 3-4 leaves remained. These leaves, possessing certain functions, were essential for ensuring the cotton could continue its reproductive growth.

[0093] Under persistent soil drought stress, it is difficult to obtain reproductive organs such as flowers, buds, and bolls from non-drought-resistant materials. Therefore, the relatively drought-resistant material H177 was used to observe the changes in various organs under drought and fully irrigated conditions. Sampling was conducted on July 30th, a period that ensures sufficient acquisition of flowers, buds, and bolls. Figure 5 As shown, observation and sampling were conducted on July 30th, and at that time, the IoT probe detected a soil moisture content of 0.133 m³. 3 / m 3 The corresponding soil moisture content measured by the drying method is approximately 9.04%.

[0094] Depend on Figure 5It can be seen that the drought-treated pond had not been watered since sowing, and the soil moisture content continued to decline. By July 30, the soil moisture content had dropped to about 9.04%. Under continuous drought stress, the development of all organs of H177 was slow. Compared with the control, the second leaf from the bottom was smaller, lost its luster, and darkened to a grayish-brown color. The notches were lighter, and there were white spots on the leaves, especially near the veins where chlorosis was obvious. The leaf base spots were lighter. The stems were shorter, thinner, and had more veins. The internodes were shorter, and the hardness increased, but the elasticity improved. The buds were smaller, the bud stalks were shorter, and the bracts were smaller. The flowers were smaller, the pedicels were thinner and shorter, the petals were open and smaller, and most importantly, the stigmas were significantly longer and extended beyond the stamens. The bells were shorter and smaller, and the bell stalks were shorter.

[0095] 2.4 Changes in cotton plant height, chlorophyll content, and relative leaf water content under continuous drought stress and after rehydration

[0096] Analysis as shown in section 2.3 indicated that on July 9th, the soil moisture content in the drought-stressed treatment was approximately 12.02%, while the soil moisture content in the control treatment was 17.43%. At this point, there was no phenotypic difference between the two materials in the control group, but significant differences in phenotypic symptoms due to drought. The second-to-last leaves from both the control and drought-stressed treatments were then collected, treated with liquid nitrogen, and stored at -80℃ for subsequent RNA extraction. One drought-stressed pool was then rehydrated. Ten days after rehydration, plant height, chlorophyll content of the third-to-last leaf, and relative leaf water content were measured in the control, drought-stressed, and rehydrated pools.

[0097] Depend on Figure 6 As shown in Figure A, there was a significant difference in plant growth status between the control and drought treatment ponds on July 9th. Figure 6 As shown in Figure B, 1 hour after rehydration in the drought-treated pond, the leaves of the non-drought-resistant material recovered from their wilted state to a flattened state; 10 days after rehydration, the vegetative growth (such as leaf size and plant height) of the rehydrated material rapidly recovered. Figure 6 (Figure C in the middle)

[0098] Plant height, chlorophyll content, and relative leaf water content were measured before rehydration, in the drought treatment pond, and in the rehydration treatment pond. Figure 7 As shown in Figure A, the plant height of the two materials did not differ significantly in the control treatment. Drought treatment significantly reduced the plant height of both materials, with H177 and JF3018 showing reductions of 59.88% and 74.01% respectively compared to the control. The non-drought-resistant materials experienced a greater decrease in plant height than the drought-resistant materials, and the difference in plant height between the two was extremely significant. After 10 days of rehydration, the plant height of both materials rapidly recovered to about half of the control treatment, and the difference between the two materials was not significant. In the control treatment, the relative leaf water content of the two materials did not differ significantly, while in the drought treatment, the relative leaf water content of the two materials differed significantly. After rehydration, the relative leaf water content of the two materials did not differ significantly. Figure 7 (Figure B); In the control treatment, there was no significant difference in chlorophyll content between the two materials. In the drought treatment, the chlorophyll content of the two materials was significantly higher than that of the control treatment, and the difference between the two materials was significant. After rehydration, due to the growth of new leaves, the chlorophyll content of the two materials decreased again, significantly lower than that of the drought treatment, and the difference between the two materials was not significant. Figure 7 (See Figure C). A soil moisture content of around 12% significantly or substantially reduces cotton plant height and relative leaf water content, while significantly increasing leaf chlorophyll content. Therefore, plant height, relative leaf water content, and leaf chlorophyll content at a soil moisture content of around 12.00% can effectively identify the drought resistance of different cotton materials.

[0099] Impact of drought treatment on seed cotton yield: Around September 30th, the drought-treated cotton boll opening was completed, and harvesting was finished on September 30th; while the control and rehydrated cotton boll opening was completed around October 20th. The persistent drought stress caused cotton to mature approximately 20 days earlier. Compared to the control, the drought-treated cotton yield decreased by 70.82%-87.52% per mu; compared to the control, the rehydrated cotton yield decreased by 85.77%-92.77% per mu. Figure 7 (Figure D) After rehydration following drought stress, vegetative growth recovered quickly (e.g., plant height returned to near that of the control), but yield was lower than that under continuous drought treatment. This indicates that drought treatment mainly inhibited the reproductive growth of cotton. Rehydration after 20 days of drought treatment had already caused irreparable damage to yield, especially for non-drought-resistant materials, where seed cotton yield was almost zero. Rehydration caused the cotton plants to receive some kind of signal and engage in frantic vegetative growth.

[0100] 2.5 Changes in subcellular structure of cotton leaves under continuous drought stress

[0101] To observe the changes in subcellular structure of cotton leaves under drought stress, samples were taken from the third-to-last leaves of both the control and drought treatments on July 30th. Figure 8 It can be seen that under the control treatment, the leaves of both materials are well-developed and glossy, while under the drought treatment, the leaf area of ​​both materials is reduced. The leaves of the non-drought-resistant material JF3018 are smaller than those of the drought-resistant material H177. At this time, the soil moisture content under the control treatment and the drought treatment is 23.02% and 9.04%, respectively.

[0102] Transmission electron microscopy was used to observe the subcellular structure of leaves from two materials after control and drought treatments, respectively. The results showed that under control conditions, the cell structure of ZhongH177 leaves was intact, the cell membrane was intact, chloroplasts were closely attached to the cell wall and were elongated oval in shape, the grana lamellae were orderly, and the chloroplasts contained large amylopectins and a small number of gray globules. Mitochondria, nuclei, and vacuoles remained intact. Under drought treatment, the cell structure of ZhongH177 leaves remained largely intact, but the cell membrane was damaged. The number and size of gray globules in the chloroplasts increased, the amylopectins decreased, and the chloroplast grana lamellae remained relatively intact. No significant changes were observed in other subcellular structures. Figure 9 ).

[0103] Under control conditions, the JF3018 cell structure remained intact, with full and complete vacuoles. Chloroplasts contained numerous oil droplets and a small amount of amylopectin. Mitochondria, nuclei, and vacuoles were all intact. Under drought conditions, the JF3018 cell structure remained largely intact, although the cell membrane was damaged. Most mitochondria remained intact, and the endoplasmic reticulum and Golgi apparatus were also largely intact. In some cells, chloroplasts gradually detached from the cell membrane, filling the chloroplasts with numerous gray globules that compressed the matrix lamellae, causing them to deform or become disorganized. Some gray globules in the chloroplasts decomposed. Some mitochondria disintegrated. Figure 10 ).

[0104] In the drought-resistant material H177, the chloroplast structure remained relatively stable under sustained drought stress. The number of gray globules in the chloroplasts was less than in the drought-intolerant material JH3018, and their function remained relatively intact. Other subcellular structures within the cells were also relatively more intact than in the drought-intolerant material, which may explain H177's drought resistance. In contrast, under drought stress, JH3018 showed a significant increase in gray globules in the chloroplasts of its leaves, with some gray globules decomposing. Other subcellular structures, such as some mitochondria, also showed decomposition, which may explain JH3018's drought intolerance. However, some subcellular structures, such as chloroplasts, in JH3018 maintained relatively intact structures under drought stress, which may be an important factor in its continued viability under sustained drought and a reason why cotton as a species is relatively drought-resistant.

[0105] 2.6 Expression analysis of cotton leaf and stigma-related genes under drought stress

[0106] Under continuous soil drought stress throughout the cotton growing season, most cotton leaves remained viable and did not fall off, and the stigmas of the cotton plants significantly elongated and protruded beyond the flowers. This example further explored the underlying causes of these results and their relationship with drought-resistant genes. Expression analysis of relevant drought-resistant genes was performed on the leaves and stigmas of two cotton materials under control and drought treatment conditions, and the results are shown in Table 3.

[0107] Table 3. Fold change of drought resistance-related genes in cotton leaves and stigmas under continuous drought stress compared to the control.

[0108]

[0109]

[0110] As shown in Table 3, compared with the control, both drought-resistant material H177 and non-drought-resistant material JH3018 showed upregulated expression of 8 genes in leaves under continuous soil drought stress, accounting for 44.44% of the total genes. However, the upregulated genes were not entirely consistent, and the upregulation folds also differed. The expression folds of most upregulated genes in the leaves of drought-resistant material H177 were significantly higher than those in JH3018, including CIPK18 (CotAD_02537), COR47 (CotAD_58358), and TPS7 (CotAD_02537). The expression folds of 00585), TRG-31 (CotAD_76943), and At4g27290 (CotAD_23188) in leaves were relatively high, at 3.671, 3.546, 2.749, 5.995, and 2.224, respectively. Although the stigmas of the two materials underwent significant morphological changes after drought stress, no drought-related genes were upregulated on the stigmas. This indicates that the stigmas, as reproductive organs, are mainly responsible for reproduction and not for resisting drought stress, demonstrating a clear division of labor with the leaves, which are organs for vegetative growth.

[0111] 3 Results

[0112] 3.1 Changes in cotton morphology and IoT monitoring under persistent drought stress

[0113] Under continuous drought stress, cotton morphology underwent significant changes, with a very significant reduction in plant size, leaf area shrinkage, changes in stems, and a very significant reduction in buds, flowers, and bolls. Leaves were dull, rough to the touch, hardened, and had many veins, with some leaves exhibiting abnormal development. Some flowers and bolls also showed abnormal development.

[0114] Monitoring soil moisture changes via the Internet of Things (IoT) allows researchers to organically combine changes in cotton soil moisture with cotton morphological symptoms anytime, anywhere, facilitating relevant studies based on drought symptoms. Soil moisture content decreases rapidly in the early stages and slowly in the later stages. This trend causes cotton to exhibit drought symptoms when it has 5-6 true leaves. At this point, cotton rapidly ceases vegetative growth, naturally tops up, and the cotyledons fall off, while the true leaves remain largely intact. In drought-resistant cotton, the chlorophyll content in the leaves does not change significantly with decreasing soil moisture and maintains certain functions, allowing it to complete reproductive growth under limited soil moisture conditions.

[0115] Comparison of two moisture monitoring methods: The traditional drying method is time-consuming and labor-intensive, and is not conducive to real-time monitoring of soil moisture dynamics. In contrast, the IoT monitoring probe is more sensitive to moisture, its accuracy fully meets the requirements, and it is significantly positively correlated with the traditional drying method, so it is effective and reliable.

[0116] 3.2 Relationship between changes in soil moisture content and cotton leaf function

[0117] Sufficient watering before sowing, with a soil depth of at least 30cm, can ensure the completion of the cotton's entire growth cycle. As drought stress intensifies, apart from the cotyledons turning yellow and falling off early, the other true leaves do not turn yellow but wilt directly. This is the cotton's rapid protective response to sudden water stress.

[0118] Soil moisture content decreases rapidly in the early stages of cotton growth and then continues to decrease slowly in the later stages. Cotton sacrifices vegetative growth to preserve the simplest reproductive growth. The chloroplast structure of its leaves remains relatively intact, and the chlorophyll content is high. These characteristics may allow cotton to complete reproductive growth even after ceasing vegetative growth. This may be an advantage that cotton has retained during evolution, enabling the species to survive in harsh environmental conditions.

[0119] This invention, through observation of fine cell structure, revealed that cotton leaves exhibited cell membrane damage under soil drought stress, with less drought-tolerant plants showing more severe damage. Generally, stress preferentially affects the plant's membrane lipid system, increasing its permeability, thus verifying a correlation between changes in cell membrane permeability and the degree of drought.

[0120] Subcellular structure analysis of leaves showed that, regardless of whether the material was drought-tolerant or drought-intolerant, the number of mesophyll granules increased after drought stress compared to the control treatment. This increase was particularly pronounced in the drought-intolerant material, which may explain why the leaf function of the drought-tolerant material remained relatively intact. This relative integrity of leaf function in drought-tolerant materials is an effective guarantee for achieving higher yields under sustained drought stress. This change in subcellular structure of leaves after drought stress is similar to that observed in leaf senescence.

[0121] 3.3 Expression of drought-resistance-related genes in cotton leaves under drought stress

[0122] Compared with the control, after drought stress, eight drought-related genes were upregulated in both materials. Among them, five genes with the largest upregulation in the drought-resistant material H177 were CIPK18 (CotAD_02537), COR47 (CotAD_58358), TPS7 (CotAD_00585), TRG-31 (CotAD_76943), and At4g27290 (CotAD_23188). These genes also showed relatively high upregulation in leaves, with fold changes of 3.671, 3.546, 2.749, 5.995, and 2.224, respectively. These genes play an important regulatory role in drought resistance in cotton.

[0123] The embodiments described above are merely illustrative of several implementations of the present invention, designed to facilitate a detailed understanding of the technical solutions of the present invention. However, they should not be construed as limiting the scope of patent protection. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention.

Claims

1. A combination of biomarkers for identifying drought resistance in cotton, characterized in that, These include CIPK18 (CotAD_02537), COR47 (CotAD_58358), TPS7 (CotAD_00585), TRG-31 (CotAD_76943), and At4g27290 (CotAD_23188).

2. The marker combination according to claim 1, characterized in that, Compared with the control condition, under natural drought stress, the expression levels of CIPK18 (CotAD_02537), COR47 (CotAD_58358), TPS7 (CotAD_00585), TRG-31 (CotAD_76943), and At4g27290 (CotAD_23188) in the vegetative organs of drought-resistant cotton were significantly upregulated.

3. The marker combination according to claim 2, characterized in that, The control conditions were: soil moisture content of 17.43% ± 0.667%, and / or, soil moisture content automatically detected by the IoT probe of 0.215 ± 0.02 m. 3 / m 3 The natural drought stress conditions are: soil moisture content of 12.02% ± 0.667%, and / or, the soil moisture content automatically detected by the IoT probe is 0.158 ± 0.02 m³. 3 / m 3 .

4. The marker combination according to claim 2, characterized in that, Compared to the control condition, under drought stress, the following characteristics were observed in the vegetative organs of drought-resistant cotton: CIPK18 (CotAD_02537) expression was upregulated by more than 3 folds; And / or, the expression level of COR47 (CotAD_58358) is upregulated by a factor of >3; And / or, the expression level of TPS7 (CotAD_00585) is upregulated by a factor of >2; And / or, the expression level of TRG-31 (CotAD_76943) was upregulated by a factor of >4.5; And / or, the expression level of At4g27290 (CotAD_23188) was upregulated by a factor of >1.

5.

5. The use of the marker combination or its detection reagent according to any one of claims 1-4 in the preparation of products for identifying the drought resistance of cotton.

6. A product for identifying the drought resistance of cotton, characterized in that, The product includes the combination of markers or their detection reagents as described in any one of claims 1-4.

7. The product according to claim 6, characterized in that, The product is a drug or a reagent kit.

8. A device for identifying the drought resistance of cotton, characterized in that, The device includes: The detection module is used to detect the expression level of the biomarker combination according to any one of claims 1-4 in the test sample; the test sample is selected from vegetative organs under drought stress; The input module is used to obtain the detection results from the detection module; The judgment module is used to compare the detection results obtained by the input module with standard data to determine the drought resistance of cotton. The output module is used to output the identification results.

9. The apparatus according to claim 8, characterized in that, The test samples were selected from leaves under drought stress; And / or, the judgment criteria of the judgment module include: if the expression level of CIPK18 (CotAD_02537) is upregulated by a factor of >3, the expression level of COR47 (CotAD_58358) is upregulated by a factor of >3, the expression level of TPS7 (CotAD_00585) is upregulated by a factor of >2, the expression level of TRG-31 (CotAD_76943) is upregulated by a factor of >4.5, and the expression level of At4g27290 (CotAD_23188) is upregulated by a factor of >1.5 in the sample to be tested, then it is judged to be drought resistant.

10. The application of the combination of markers according to any one of claims 1-4 or biological materials containing the combination of markers according to any one of claims 1-4 in the breeding of drought-resistant cotton varieties.

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