Application of salt tolerance-related lncRNA and its target genes in cotton breeding

Abstract

The invention belongs to the field of biotechnology and discloses an application of a salt-tolerance related lncRNA and its target gene in cotton breeding. The invention specifically discloses the application of lncRNA: XLOC_43671 and its target gene Gohir.D02G125200 and lncRNA: XLOC_34861 and its target gene Gohir.A12G114800 in identifying cotton salt tolerance and molecular-assisted breeding of salt-tolerant cotton varieties.

Description

Technical Field

[0001] The invention belongs to the field of biotechnology, and specifically relates to application of salt-tolerance related lncRNA and target genes thereof in cotton breeding. Background Art

[0002] At present, soil salinization has become one of the more serious abiotic stresses in the world (Amundson et al. 2015). Saline-alkali land is a very important reserve soil resource in the world, but more than 500 million hectares of it cannot be used for agricultural production (Amini et al. 2016). If saline-alkali land can be utilized, it can not only protect biodiversity and ensure food security, but also alleviate many problems such as the contradiction between people and land (Hassani et al. 2021). Soil salinization is not only not conducive to the healthy development of the global ecological environment, but also has become one of the important factors restricting the development of modern agriculture in China and even the world (Amini et al. 2016). According to statistics, more than 50% of the land will be salinized by 2050 (Wang et al. 2003). Under salt stress, the first toxicity suffered by plants is osmotic stress. As the salt concentration increases, the osmotic stress aggravates, causing ion homeostasis imbalance (Qin et al. 2016), and harmful substances accumulate in the body, thus affecting the growth, development and morphology of plants (Zhang and Shi 2013). In addition, plants are prone to produce a certain amount of reactive oxygen species (ROS) after being subjected to salt stress. The accumulation of ROS in plants can easily damage cell membranes (Bhatia et al. 2010). Salt stress can have a serious impact on cotton photosynthesis. Under salt stress, the stomata of cotton leaves are closed (Cheeseman 2013), making it difficult to absorb CO2, thereby causing a decrease in photosynthetic rate. At the same time, the chloroplast structure is destroyed and the chlorophyll content is reduced, resulting in a decrease in photosynthetic carbon assimilation capacity, which is also an important reason for the weakening of photosynthesis (Mittal et al. 2012).

[0003] Globally, cotton has always been a very important economic crop. It is a renewable high-quality fiber, a raw material for the textile industry, etc. (Gereziher et al. 2021), but land salinization in cotton-growing areas is a huge challenge to cotton production. Long-term high salinity inhibits the growth and development of cotton, resulting in reduced yield, decreased fiber quality and other hazards. How to effectively breed salt-tolerant cotton varieties is one of the key means to ensure stable production. Analyzing the mechanism of cotton's response to salt stress and deeply exploring and studying salt-resistant genes can speed up the process of breeding new salt-tolerant cotton varieties and alleviate the contradiction between grain and cotton for land. Summary of the invention

[0004] The present invention aims to provide an application of a salt-tolerance related lncRNA and a target gene thereof in cotton breeding.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] The present invention provides lncRNA: XLOC_43671 and its target gene Gohir.D02G125200 and lncRNA: XLOC_34861 and its target gene Gohir.A12G114800.

[0007] The sequence of XLOC_43671 is shown in SEQ ID NO.1.

[0008] The sequence of XLOC_34861 is shown in SEQ ID NO.2.

[0009] The sequence of Gohir.D02G125200 is shown in SEQ ID NO.3.

[0010] The sequence of Gohir.A12G114800 is shown in SEQ ID NO.4.

[0011] The invention provides a method for identifying salt tolerance of cotton, and predicts the salt tolerance of cotton by detecting the expression level of XLOC_43671 and / or XLOC_34861 in a sample. XLOC_43671 and / or XLOC_34861 are highly expressed in salt-tolerant cotton.

[0012] The invention provides a method for identifying salt tolerance of cotton, and predicts the salt tolerance of cotton by detecting the expression level of Gohir.D02G125200 and / or Gohir.A12G114800 in a sample. Gohir.D02G125200 and / or Gohir.A12G114800 are highly expressed in salt-tolerant cotton.

[0013] The present invention provides application of XLOC_43671 and / or XLOC_34861 in molecular assisted breeding of salt-tolerant cotton varieties.

[0014] The present invention provides the use of Gohir.D02G125200 and / or Gohir.A12G114800 in molecular assisted breeding of salt-tolerant cotton varieties.

[0015] Compared with the prior art, the present invention discovered for the first time the high expression of XLOC_43671 and / or XLOC_34861 in salt-tolerant cotton. Salt-tolerant cotton can be identified by detecting the content of XLOC_43671 and / or XLOC_34861 or their target genes. At the same time, the salt tolerance of cotton can be changed by changing the content of the above genes. The present invention has broad application prospects in the field of cotton salt tolerance selection and breeding. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 For the identification of long noncoding RNAs (lncRNAs) and mRNAs in cotton;

[0017] Figure 2 For comparative analysis of lncRNA and mRNA;

[0018] Figure 3 This is a heat map of correlations between 12 samples;

[0019] Figure 4 The expression characteristics of lncRNAs and mRNAs in salt-tolerant cotton and salt-sensitive cotton after salt stress;

[0020] Figure 5 The relative expression results of lncRNAs after salt treatment;

[0021] Figure 6 The relative expression results of protein coding genes after salt treatment;

[0022] Figure 7 It is the heat map of the relative expression results of lncRNAs and mRNAs;

[0023] Figure 8 It is the correlation diagram between the lncRNA and mRNA transcriptome results and the RT-qPCR results. The horizontal axis represents the RT-qPCR results, and the vertical axis represents the transcriptome sequencing results.

[0024] Fig. 9 The interaction regulatory network between lncRNAs and mRNAs after salt stress;

[0025] Fig.10 GO classification and KEGG pathway enrichment analysis of cotton lncRNA differential target genes;

[0026] Fig.11 VIGS results of salt-responsive lncRNAs (XLOC_043671 and XLOC_034831) in upland cotton;

[0027] Fig.12 VIGS verification of upland cotton genes Gohir.A12G114800 and Gohir.D02G125200. DETAILED DESCRIPTION

[0028] The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention. Without departing from the spirit and substance of the present invention, modifications or substitutions made to the methods, steps or conditions of the present invention are within the scope of the present invention.

[0029] Unless otherwise specified, the experimental materials, reagents, and instruments used in the examples of the present invention are all commercially available. Unless otherwise specified, the technical means used in the examples are all conventional means well known to those skilled in the art.

[0030] Example 1 Screening of salt-tolerant genes

[0031] 1. RNA sequencing and lncRNA identification

[0032] To identify lncRNAs and mRNAs involved in salt stress response in cotton seedlings, we constructed RNA libraries from the salt-tolerant Darwin cotton introgression line XiangFZ031 and its upland cotton parent salt-sensitive material CRI12. The libraries contained three control replicates and three treatment replicates for both materials, for a total of 12 samples. After RNA library construction, sequencing was performed using the Illumina HiSeq platform. After filtering out low-quality reads, 206 Gb of clean data were obtained, with an average of 17.1 Gb per sample. Then, the HISAT2 program was used to align each sample with the upland cotton reference genome TM-1 to obtain position information on the reference genome or gene, as well as sequence feature information specific to the sequenced sample. The credibility of the assembled data was evaluated by base quality values ​​and alignment efficiency, and it was finally found that the Q20 of the 12 samples was ≥98.7%, Q30 was ≥95.8%, and the alignment efficiency was greater than 96% (Table 1). These quality control indicators showed high accuracy of genome alignment and sequencing, which is crucial for subsequent genome analysis.

[0033] Table 1: Sequencing data statistics

[0034]

[0035] Note: SampleID: Sample name in the sample information sheet; ≥Q30%: The percentage of bases with CleanData quality values ​​greater than or equal to 30; reads_mapped: The percentage of reads mapped to the reference genome.

[0036] After a series of strict filtering, the coding potential was screened by using the CPC, CNCI, and Pfam databases ( Figure 1A), we finally identified 519 highly reliable lncRNAs. In addition, we obtained 75,376 highly reliable mRNAs through sequencing analysis, and used circos diagrams to show the location distribution of lncRNAs and mRNAs obtained by sequencing on 26 chromosomes of cotton ( Figure 1 B). As can be seen from the figure, lncRNAs and mRNAs are evenly distributed on the 26 cotton chromosomes. According to their positions relative to protein-coding genes, the inferred lncRNAs are further divided into three types: intergenic lncRNA (lincRNA), intronic lncRNA (intronic lncRNA), and anti-sense lncRNA (anti-sense lncRNA) ( Figure 1 C). The obtained lncRNAs are mainly lincRNAs, with a total of 469 lncRNAs, accounting for 90.3% of all lncRNAs. The second largest type is anti-sense lncRNA, with 42, accounting for 8.1% of the total, and the smallest is intronic lncRNA, with only 8, accounting for 1.5%. Therefore, lincRNAs, as the main type of lncRNAs, may be an important member involved in the salt stress response of upland cotton.

[0037] 2. Comparison of structural characteristics and expression levels of lncRNA and mRNA

[0038] In order to study the genomic characteristics of lncRNA, we compared it with the obtained mRNAs in terms of sequence, structure and expression level. By observing the comparison of transcript length, number of exons and length of open reading frames (ORFs) between lncRNA and mRNA, we can obtain the difference between lncRNA and mRNA molecules and verify whether the predicted lncRNA molecules meet the general characteristics.

[0039] As can be seen from the figure, most lncRNAs are shorter than mRNAs ( Figure 2A), the length of lncRNAs is mostly distributed between 200-1600nt, accounting for 86.5%; on the contrary, almost all mRNAs are longer than 200nt, accounting for 99.3%, of which 200-1600nt mRNAs account for 49%, 1600nt-3000nt account for 39%, and longer than 3000nt account for 11.4%. The number of exons of lncRNAs ranges from 2 to 10, and a total of 431 lncRNAs have 2 exons, accounting for 83% of the total. However, the number of exons of mRNAs ranges from 1 to more than 30, and the vast majority of mRNAs have only 1 exon, with a total of 107,216, accounting for 53.3% ( Figure 2 B). At the same time, the length of the open reading frame of lncRNAs is distributed between 1 and 300 nt, and 92.8% of the lncRNAs have an open reading frame length of 1 to 100 nt. The length of the open reading frame of mRNAs ranges from 1 to 2000 nt ( Figure 2 C). In addition, by comparing the expression levels of mRNAs and lncRNAs, the difference in expression levels of lncRNAs and mRNAs was obtained. In order to average the expression values ​​of each transcript of lncRNAs and mRNAs, the log10(FPKM+1) values ​​of the two were used to draw a violin plot ( Figure 2 D), the results showed that the expression level of lncRNAs was significantly lower than that of mRNAs.

[0040] In summary, lncRNAs and mRNAs differ in structure and expression level. The transcript length of lncRNAs is shorter than that of mRNAs, with fewer exons, shorter open reading frames, and lower expression levels than mRNAs. These results may suggest that mRNA and lncRNAs have different functions after salt stress and are involved in different response mechanisms.

[0041] 3. Differential expression analysis of lncRNAs and mRNAs

[0042] In order to study the differential expression patterns of lncRNAs and mRNAs, the 12 samples were first evaluated for repeated correlation. The Pearson's Correlation Coefficient r was used as an evaluation index for biological replicate correlation. The closer r is to 1, the stronger the correlation between the two replicate samples ( Figure 3 ). It can be seen from the figure that the biological replicates of the three groups in the control group and the treatment group of the two materials are all greater than 0.9, which indicates that the differentially expressed genes found next are highly reliable.

[0043] In the process of differentially expressed gene detection, |Fold Change|≥1.5 and FDR<0.05 were used as screening criteria. The difference fold (Fold Change) represents the ratio of the expression levels between two samples (groups). Finally, after salt stress treatment, a total of 90 DELs were found, accounting for 17.3% of all lncRNAs; 10,552 DEGs were also identified, accounting for 13.8%. This shows that after salt stress, in addition to the obvious differences in protein-coding genes, cotton seedlings are more inclined to regulate lncRNA expression. The results are shown in the volcano plot. A total of 9 DELs were differentially expressed after CRI12 salt treatment, of which 5 were upregulated and 4 were downregulated compared with the control; at the same time, there were 2,283 DEGs in CRI12, 994 of which were upregulated and 1,289 were downregulated compared with the control ( Figure 4 A). There were 89 DELs differentially expressed in XiangFZ031, 52 of which were upregulated and 37 were downregulated compared with the control; 10,399 DEGs were also found, 4,277 of which were upregulated and 6,122 were downregulated ( Figure 4 B). We found that in both materials, the number of upregulated DELs was greater than the number of downregulated DELs. The number of downregulated genes in DEGs was greater than the number of upregulated genes, and most of the coding genes were in a repressed state after salt stress. This result shows that in cotton materials, compared with mRNA, most lncRNAs are in an actively regulated state, their expression levels are upregulated, and then they play different biological functions and participate in salt stress regulation.

[0044] To further understand the differences in DELs and DEGs between the two materials, a Venn diagram was drawn and it was found that a total of 81 DELs were specifically expressed in XiangFZ031, and only 1 DEL was specific to CRI12 ( Figure 4 C). 8302 DEGs were specifically expressed in XiangFZ031, and 344 DEGs were specific to CRI12 ( Figure 4 D). This result indicates that more DELs and DEGs of the salt-tolerant material XiangFZ031 were involved in salt response regulation after salt stress, and may be involved in more salt stress response mechanisms.

[0045] 4. Identification of salt-responsive candidate genes and lncRNA expression

[0046] We randomly selected 10 lncRNAs and performed RT-qPCR validation on them ( Figure 5). These lncRNAs have different expression patterns when cotton seedlings are subjected to salt stress. For example, XLOC_000650, XLOC_027187, XLOC_043671, XLOC_034831, and XLOC_013428 were not significantly expressed in upland cotton CRI12 after salt stress, but were significantly upregulated in the salt-tolerant material XiangFZ031. In contrast, XLOC_013777 was not significantly expressed in CRI12 after salt stress, but was significantly downregulated in XiangFZ031. In addition, we also found that XLOC_006527 and XLOC_031821 were significantly downregulated in both materials after salt stress.

[0047] At the same time, we also selected 12 differentially expressed protein-coding genes for RT-qPCR validation ( Figure 6 ). We found that Gohir.A12G114800, Gohir.A05G285000, Gohir.A10G000500, Gohir.D12G214600, Gohir.D05G241600 and Gohir.D04G027500 were not significantly expressed in CRI12 after salt stress, but were able to respond positively and were significantly upregulated in XiangFZ031. Gohir.A13G137700 and Gohir.D02G125200 were significantly upregulated in both materials after salt stress, while Gohir.D12G045600, Gohir.A07G051700, Gohir.A05G351800 and Gohir.A01G229500 were significantly downregulated in both materials. These results show that after cotton seedlings with different salt tolerance are subjected to the same salt stress, the same lncRNA and mRNA may show different expression patterns and participate in salt response-related pathways, thus leading to differences in cotton tolerance to salt. Finally, the tbtools software was used to draw an expression calorimeter for the above RT-qPCR results ( Figure 7 ).

[0048] Correlation analysis between lncRNA and mRNA verified by RT-qPCR and transcriptome sequencing data results ( Figure 8 ), the linear equation was Y=0.9047*X+0.5782, and the correlation coefficient R was 0.92. This showed that the transcriptome sequencing results were highly correlated with the RT-qPCR results, the data were reliable and effective, and also laid the foundation for the functional verification of lncRNA and target genes in response to cotton salt.

[0049] 5. Prediction of lncRNA target genes and analysis of co-expression network of DELs and DEGs

[0050] The function of lncRNA is mainly achieved by acting on protein-coding target genes in cis or trans. The basic principle of cis target gene prediction is that the function of lncRNA is related to the protein-coding genes adjacent to its coordinates, so the protein-coding genes adjacent to the lncRNA (100k upstream and downstream) are screened as target genes. Through cis prediction, we identified a total of 84 DELs targeting 837 possible protein-coding genes. In addition, we believe that the function of lncRNA does not depend on the positional relationship with the coding gene, but is related to the co-expressed protein-coding genes. The target gene can be predicted by correlation analysis of the expression of lncRNA and protein-coding genes between samples or co-expression analysis. This Trans method identified 39 DELs targeting 597 protein-coding genes.

[0051] In order to further understand the interaction between DELs and DEGs, co-localization analysis revealed that 60 DELs and 217 DEGs may have interactive regulatory relationships after salt stress ( Fig. 9 ). And the possible interaction network was constructed using Cytoscape3.7.2. Figure 8 As shown, the regulatory relationship between lncRNA and mRNA in cotton is relatively simple, with more than two-thirds of the regulated relationships having fewer than three nodes.

[0052] 6. Functional enrichment analysis of lncRNA differential target genes

[0053] In order to analyze the functions of the identified lncRNA differential target genes, GO classification and KEGG enrichment analysis were performed on the 217 co-localized genes identified in the previous interaction network ( Fig.10 ). Based on the GO enrichment results, the top 20 pathways were selected for visualization ( Fig.10AC), among the 217 genes, a total of 202 genes were enriched in organelles and intracellular organelles, participating in the composition and development of organelles (GO:0043226organelle; GO:0043229, intracellularorganelle). In the molecular function-related classification of genes, a total of 34 genes were enriched in hydrolase activity (GO:0016787hydrolase activity), in addition, some genes had RNA polymerase activity (GO:0034062RNA polymerase activity), DNA binding (GO:0010385DNA binding), etc. The biological processes involved in these genes were mainly enriched in organelle organization (GO:0006996organelleorganization).

[0054] In addition, we performed KEGG pathway enrichment analysis on the pathways where these target genes were located ( Fig.10 D), the top 20 enriched pathways were selected based on the number of genes enriched in the pathway and the p-value. These genes were enriched in pathways such as metabolism-related pathways (ko01100) and ribosome composition (ko03010). The above results indicate that the pathways enriched by these genes may play an important role in the response of cotton to salt stress.

[0055] Example 2 VIGS functional verification of candidate lncRNA

[0056] To further verify the association between lncRNAs and their target genes, we used virus-induced gene silencing to silence two lncRNAs whose expression levels were significantly upregulated after salt stress ( Figure 7 ). This approach was used to further investigate the regulatory role of lncRNAs in salt stress. In addition, we silenced the CLA1 gene in plants as a positive control, which encodes 1-deoxyfructose-5-phosphate synthase involved in chloroplast development. The CLA1 gene is highly conserved throughout evolution, and its silencing resulted in a distinct albinism phenotype.

[0057] One of the two lncRNAs is lncRNA:XLOC_043671, which cis-regulates Gohir.D02G125200, which mainly encodes a fatty acid hydroxylase with oxidoreductase activity. The other is lncRNA:XLOC_034831, which cis-regulates Gohir.A12G114800. Gohir.A12G114800 belongs to the homeobox domain (HD-Zip) transcription factor family and is involved in DNA binding. After the albinism phenotype of TRV:CLA1 was treated with salt ( Fig.11 A). In addition, RT-qPCR showed that the relative expression of the target gene Gohir.D02G125200 decreased in TRV:XLOC_043671 plants after lncRNA:XLOC_043671 was silenced ( Fig.11 CD). Similarly, after silencing of lncRNA:XLOC_034831, the expression level of the target gene Gohir.A12G114800 was also downregulated ( Fig.11 Compared with TRV:00, TRV:XLOC_043671 and TRV:XLOC_034831 plants showed leaf curling, yellowing and slower growth ( Fig.11 B). In addition, we observed that the chlorophyll content in the leaves of lncRNA-silenced plants was lower than that of TRV:00 plants. The lncRNA-silenced seedlings also accumulated lower levels of proline, indicating an increased sensitivity to salt ( Fig.11 EG, JL). These findings suggest that lncRNAs play a regulatory role in modulating the expression of target genes, thereby positively regulating plant salt tolerance.

[0058] In summary, after we silenced two candidate lncRNAs (XLOC_043671, XLOC_034831), the identified lncRNA-regulated salt-responsive target genes were also downregulated. This result indirectly confirmed the existence of a targeting relationship between lncRNA: XLOC_043671 and Gohir.D02G125200, and between XLOC_034831 and Gohir.A12G114800. This indirect downregulation of the expression of the targeted genes Gohir.D02G125200 and Gohir.A12G114800 may be the reason for the low salt tolerance of the plant.

[0059] Example 3 VIGS Functional Verification of Candidate Genes

[0060] Through the previous RT-qPCR results, we found that the co-expressed genes Gohir.D02G125200 and Gohir.A12G114800 of lncRNA (XLOC_043671 and XLOC_034831) were significantly upregulated after salt stress ( Figure 7 ), in order to further study the functions of these two candidate genes under salt stress, we used virus-induced gene silencing technology to silence the two genes Gohir.D02G125200 and Gohir.A12G114800 in the salt-tolerant cotton line XiangFZ031. The plants with silenced GhCLA1 gene were used as positive controls. After two weeks of silencing, the leaves showed a whitening phenotype, indicating that the experimental procedure was correct and effective ( Fig.12 A). Then, 14 days after salt treatment, we measured the plant height, fresh weight of aboveground parts, dry weight of aboveground parts, and chlorophyll content of the negative control (TRV:00) and the experimental group (TRV:Gohir.A12G114800). Then, we found through RT-qPCR experiments that the target gene was significantly downregulated in the silenced plants, indicating that the gene was effectively silenced ( Fig.12 D). After salt treatment, we found that TRV:Gohir.A12G114800 had a higher degree of wilting, yellow leaves, lower chlorophyll content, decreased leaf water content, lighter fresh weight and dry weight of aboveground parts, and its salt tolerance was significantly reduced compared with the control group ( Fig.12 B, FI). This result indicated that Gohir.A12G114800 significantly upregulated its expression level after salt treatment, thus improving the salt tolerance of cotton seedlings.

[0061] In addition, we also silenced another candidate gene, Gohir.D02G125200, and RT-qPCR results showed that this gene was effectively silenced ( Fig.12 E). After the albino phenotype appeared, various indicators such as plant height, aboveground fresh weight, aboveground dry weight, and chlorophyll content were measured. The results showed that compared with the control group, there was no significant difference in plant height for TRV:Gohir.D02G125200, but the leaves were more severely curled and yellowed, and the aboveground fresh weight and dry weight were significantly different ( Fig.12 C, JM). These indicators all indicate that the salt tolerance of cotton seedlings decreased significantly after silencing Gohir.D02G125200. The results of various measurements indicate that the downregulation of the Gohir.D02G125200 gene leads to a decrease in cotton salt tolerance.

[0062] The primer information involved in the present invention is shown in Table 2.

[0063] Table 2 RT-qPCR and VIGS primers for DELs and DEGs

[0064]

Claims

1. A method for identifying salt tolerance of cotton, characterized in that: The salt tolerance of cotton was predicted by detecting the expression level of XLOC_43671 in the sample; the sequence of XLOC_43671 is shown in SEQ ID NO.1, and XLOC_43671 is highly expressed in salt-tolerant cotton.

2. A method for identifying salt tolerance of cotton, characterized in that: The salt tolerance of cotton is predicted by detecting the expression level of Gohir.D02G125200 in the sample; the sequence of Gohir.D02G125200 is shown in SEQ ID NO.3; Gohir.D02G125200 is highly expressed in salt-tolerant cotton.

3. Application of XLOC_43671 in molecular-assisted breeding of salt-tolerant cotton varieties; The sequence of XLOC_43671 is shown in SEQ ID NO.1, and XLOC_43671 is highly expressed in salt-tolerant cotton.

4. Application of Gohir.D02G125200 in molecular-assisted breeding of salt-tolerant cotton varieties; the sequence of Gohir.D02G125200 is shown in SEQ ID NO.3, and Gohir.D02G125200 is highly expressed in salt-tolerant cotton.

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