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2023 Volume 2
Article Contents
Abstract
Introduction
Materials and methods
Plant materials
Metabolomic profiling and statistical analysis
RNA-seq profiling and statistical analysis
Construction of co-expression network
Selective pressure analysis of the candidate genes
Population sampling, DNA isolation, PCR amplification, sequencing, and sequence alignment
Population genetics analysis
Results
Global metabolic profiling in two altitudinal ecotypes of sandrice
Transcriptome analysis in two altitudinal ecotypes of sandrice
Correlation analysis of DEMs and DEGs in two altitudinal ecotypes
Population genetics and divergence among populations across varying altitude gradients
Discussion
The role of flavonoids and phenylpropanoids in sandrice's adaptation to alpine environments
Alpine adaptive evolution of phenylpropanoid and flavonoid biosynthesis pathways in sandrice
Author contributions
Data availability
Acknowledgments
Conflict of interest
Supplementary information
Rights and permissions
References
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Promotion of root development by slightly alkaline pH involves an auxin mediated adaption mechanism

  • 1.

    State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, MOA Key Laboratory of Plant Nutrition and Fertilization in Lower-Middle Reaches of the Yangtze River, Nanjing Agricultural University, Nanjing 210095, China

  • 2.

    The Collage of Life Science, Anhui Agricultural University, Hefei 230036, China

  • 3.

    International Genome Center, Jiangsu University, Zhenjiang 212013, China

  • 4.

    Excellence and Innovation Centre, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China

  • 5.

    Key Laboratory of Saline-Alkali Soil Improvement and Utilization (Coastal Saline-Alkali Lands), Ministry of Agriculture and Rural Affairs, Nanjing 210014, China

  • # These authors contributed equally: Xingliang Duan, Long Luo

More Information
  • The present study performed experiments to identify the superior pH for Arabidopsis root growth base on its development (radical root length and lateral root density); and then approached the mechanism by which optimized pH primes root development. The results showed that neutral to slightly alkaline pH (7.0−8.0) in medium was the optimum range in which the plant had longer primary roots and denser lateral roots. Auxin reporter DII:VENUS transgenic line cultured in standard (5.8) and slightly alkaline (7.5) pH indicated that in pH 7.5 conditions, there was less fluorescence in the root cap compared to in acidic conditions. Furthermore, the DR5:Luciferase transgenic plant showed pH 7.5 accelerated the auxin oscillation frequency, was 17.83% shorter than that in pH 5.8. Later, a series of mutant germplasms showed slightly alkaline conditions promoting root development were independent from PLT transcript factors, but mainly mediated by auxin transportation. Transcriptomic dynamic analysis showed pH 7.5 conditions could trigger the changes in the pathways of plant hormones signal transduction and ABC transporter. The mutants of the ABC transporter coding genes were thus tested and the results showed that mutant abcb20 could block the slightly alkaline (7.5) pH promoting root development completely, as well as several other mutants blocking it partially.

  • Introduction

    As the world's third pole and Asia's water tower, the Qinghai-Xizang Plateau (QXP) acts as a vital ecological security barrier for the world[1]. In addition, the QXP is also one of the important biodiversity hotspots and harbours many rare resource plants[2]. In recent decades, with global climate change and human activities, the alpine meadow ecosystem on the QXP is facing great risks of grassland degradation and land desertification, which would greatly affect the safety of ecosystems around the world[3]. Therefore, there is an urgent need to repair the desertified lands on the QXP. Among the numerous prevention and control technologies/methods for desertified lands, the construction of stable vegetation adapted to the local climate environment has become the consensus on the sustainable development of desert ecosystems[4]. Due to the long-term stresses of low oxygen, strong ultraviolet radiation, drought, and the harsh conditions of alpine environments, plants on the QXP typically grow very slowly. Therefore, once vegetation degradation occurs on the QXP, restoration efforts become considerably more challenging. Compared to other plant species, desert-adapted plant species exhibit greater resilient to the harsh environmental conditions of the QXP, making them ideal for restoring degraded vegetation. Therefore, plant species naturally adapted to deserts on the QXP are the optimal choice for vegetation reconstruction in alpine desertified lands.

    Over the past decades, numerous researches have been carried out to dissect the genetic basis of plateau adaptation in species endemic to the extreme environments on the QXP[5,6]. Among these studies, most were focused on human and animal species[7−9], while studies on plant adaptation to the QXP have started to gain more attentions in recent years, driven by an increased recognition of the importance of plant diversity for ecosystem resilience[10−12]. Based on comparative transcriptome, metabolome, and/or genome analysis, an increasing number of studies have substantiated that most of the plants thriving on the QXP possess an abundance of secondary metabolites and robust genetic resources tailored to withstand its severe natural conditions[13,14]. Most studies have focused on sister species within genera, however, due to the long history of species differentiation, population dynamics, and/or breeding systems vary significantly across species, making it rare to investigate the genetic basis of altitude gradient adaptation within the same plant species. Nevertheless, plants native to the deserts of the QXP exhibit remarkable tolerance to multiple stresses such as UV-B radiation, drought, cold, and hypoxia, rendering them optimal pioneer species for restoring desertified lands in this region. Furthermore, a clarified molecular basis of local adaptation in different ecotypes within a plant species can not only forecast the evolutionary trajectory of plant adaptation to future climate changes[15,16], but also provide crucial molecular insights and genetic resources for improving and selecting plant species capable of surviving extreme environments and severe climate fluctuations on the QXP[17]. Meanwhile, due to long-term adaptation to the harsh environment and special climatic conditions of the QXP, indigenous plants have produced many secondary metabolites with medicinal value during their adaptive evolution. Therefore, multi-omics studies among natural populations of plant species are necessary to unravel the molecular metabolic mechanisms underlying the adaptation of desert plants to altitude gradients on the QXP, which can not only reconcile the conflicts between local agricultural development and ecological conservation in these fragile ecosystems, but also provide valuable insights into the indigenous nature of high-altitude medicinal plants.

    Agriophyllum squarrosum (L.) Moq., commonly known as sandrice, thrives in the vast deserts and sandy landscapes of arid and semi-arid regions throughout the interior of Asia (www.efloras.org). Field investigations underscore its remarkable ecological versatility, thriving at altitudes from about 50 to over 4,000 m, particularly adapting well to the harsh desert conditions of the QXP, where it exhibits strong growth and reproductive success[18,19]. Additionally, sandrice plays a crucial ecological role in reducing wind velocity by at least 90% when withered, and it enriches nutrient-poor soils with carbon and nitrogen, significantly sustaining and restoring fragile desert ecosystems[18,20]. Moreover, despite growing in the infertile sandy soils, sandrice seeds are rich in essential nutrients like amino acids, crude fiber, and polyunsaturated fatty acids, making it an ideal natural functional food[21]. Furthermore, its above-ground parts are abundant in bio-actives, including flavonoids, organic acids, terpenoids, and alkaloids[22], and have been traditionally used in Mongolian medicine for treating kidney inflammation, dyspepsia, fever, and pain relief[23]. Notably, recent studies have indicated that sandrice shows great potential as both an antibiotic substitute and a functional forage crop in antibiotic-free ruminant farming, owing to the abundance of bio-active compounds found in its aerial parts[24,25]. Therefore, exploring the mechanism of alpine adaptation in sandrice would not only help combat desertification in the plateau region, but also enhance our understanding of the factors contributing to the high medicinal quality of its alpine ecotypes.

    Previous biogeographic studies have underscored notable genetic divergence among sandrice populations across heterogeneous deserts and sandy lands. However, minimal genetic divergence was observed between the alpine group and its adjacent central desert group, despite notable habitat heterogeneity between them[19,26]. Notably, based on metabolomic analysis and common garden experiments, variations were observed in the accumulation of medicinal metabolites with significant pharmacological activity, such as flavonoids, among populations from different altitudinal habitats, even under the same environmental conditions.[27,28]. Recently, cold-stress treatment among ecotypes from different altitude gradients further indicates that flavonoids are crucial for sandrice to defend against low temperatures[29]. These phenomena suggest that flavonoid biosynthesis pathways in sandrice may have been favored through long-term local adaptation to the QXP, and further contributes to its distinctive medicinal properties.

    To investigate the apparent paradox of significant differences in secondary metabolite accumulation despite similar genetic backgrounds in sandrice, and to further verify the role of flavonoid biosynthesis pathway in the alpine adaptation of sandrice, this study conducted the first in situ metabolome and transcriptome analyses comparing two ecotypes of sandrice. These ecotypes occupy habitats at different altitudes while sharing the same genetic composition: ETL from the alpine group (2,917 m altitude) and CC from the central desert group (1,530 m altitude). Then, population genetic analysis across 22 natural populations was carried out to determine whether these adaptive functional genes underwent directional evolution along the altitude gradient, compared to neutral genes. This endeavour aims to elucidate the molecular metabolic basis underlying sandrice's adpatation to harsh alpine desert environments, especially the role of metabolites with medicinal value in plant adaptive evolution, which will further provide molecular guidance and genetic resources for the restoration of desertification on the QXP and facilitate molecular marker-assisted breeding to enhance the medicinal quality of this promising plant sepcies.

    Materials and methods

    Plant materials

    Based on the neutral genetic markers, two wild ecotypes that shared the same genetic composition were collected at the same mature growth period from different altitudinal habitats. One was located in Ertala (ETL), Gonghe county, Qinghai province (36°11'39.48'' N, 100°31'28.26'' E, 2,917 m) on the QXP, while the other one was located in Changcheng county (CC), Gansu province (37°54'10.98'' N, 102°54'4.2'' E, 1,530 m) in the southern edge of the Tengger Desert (Fig. 1a). To minimize variations caused by different growth stages, the ETL ecotype was collected in mid-September 2016, while the CC ecotype was collected in early October. Both the CC and ETL ecotypes were in the early reproductive stage at the time of collection. All collected samples were accurately identified by Prof. Xiao-Fei Ma, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences. Fresh tissues from each ecotype, including leaves, stems and spikes, were promptly flash-frozen in liquid nitrogen and stored at −80 °C in an ultra-low temperature freezer for further extraction of metabolites and RNA.

    Figure 1.  Comparative metabolomic profilings of two altitudinal ecotypes of A. squarrosum. (a) Geographical localization of two altitudinal ecotypes of A. squarrosum provenances. (b) PCA plot of two ecotypes metabolomes revealing the first two principal components with t[1] = 30.5% and t[2] = 16.7%. The meaning of each abbreviation is as follows: L (leaf), St. (stem), Sp. (spike). Each samples have three biological replicates. (c) Heat map showing standardized contents of partial classified metabolites in different tissues of ETL and CC ecotype. These metabolites are classed into two groups according to their chemical characters.
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    Metabolomic profiling and statistical analysis

    As the non-targeted approach provides the advantage of discovering important metabolites that might otherwise remain undetected with a targeted approach, to identify the key metabolites and metabolic pathways, particularly the major secondary metabolic pathways, involved in plateau adaptation for sandrice, samples with three biological replicates of each ecotype were prepared for UPLC-MS non-targeted metabonomics using LC-ESI-Q TRAP-MS/MS systems at Metware Biotechnology Co., Ltd (Wuhan, China). The quantification of the metabolites was carried out in MRM mode and the analytical conditions were as the study of Chen et al.[30]. Analyst 1.6.1 and MultiQuant 3.0.2 software were used for data set acquisition, peak recognition, and normalization. Metabolites were annotated by mapping them to the self-built database MWDB (Metware Biotechnology Co., Ltd. Wuhan, China) as well as public databases to identify their chemical structures. Quantitative analysis of metabolites was carried out by a multi-reaction monitoring mode (MRM) on a triple quadrupole mass spectrometer.

    To further determine the differentially enriched metabolites (DEMs) between the two ecotypes, PCA (Principal Component Analysis) and PLS-DA (PLS Discriminant Analysis) were performed with SIMCA 13.0 software. DEMs were determined based on relative content, with thresholds set at a variable importance in the projection (VIP) value of ≥ 1 and a fold change of ≥ 2 or ≤ 0.5.

    RNA-seq profiling and statistical analysis

    Total RNA was extracted from each tissue using RNAprep Pure Plant Kit (Tiangen Biotech Co., Ltd, Bejing, China). Double-strand cDNA was constructed following the study of Shi et al.[31]. These fragments were firstly purified with QiaQuick PCR extraction kit (QIAGEN Inc., Valencia, CA, USA) according to the construction, then were end-repaired with A added to the 3' ends, and finally ligated to sequencing adaptors. The ligated cDNA products under size-selected demands were further concentrated by PCR amplification to construct the cDNA libraries. Library preparations were sequenced on an Illumina HiseqTM3000 platform with a 150-bp paired-end mode. Raw sequenced data have been submitted to the NCBI database with the accession number PRJNA659807.

    Raw reads containing unknown sequences ('N') exceeding 5% and low-quality reads (with a base quality less than Q20) were eliminated from the dataset. The remaining filtered clean reads were then utilized for de novo assembly with Trinity version 2.4.0[32]. According to the pair-end information, contigs were clustered and assembled into sequences as long as possible after removing redundancies, and then the clustered longest contigs were subsequently amalgamated into the total unigenes. Functional annotation of each unigene was performing BLASTx searches against the public protein and/or nucleotide databases (such as the NCBI Nr, Nt databases, Swiss-Prot protein database, KOG database, GO database, InterPro, and the KEGG database) with an E-value cutoff of 1e-5. Differentially expressed genes (DEGs) between different tissues of the two ecotypes were estimated by DESeq2. A significance threshold was set with a p-value less than 0.05 and an absolute value of fold-change over 2 to determine significant differential expression[33]. Enrichment analysis of DEGs in the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways was performed using KOBAS software (version 2.0.12) and visualized with ggplot2.

    Construction of co-expression network

    To explore the potential regulatory relationships between genes and metabolites, the relative expression of DEGs and the relative contents of DEMs within two interested pathways of phenylpropanoid and flavonoids biosynthesis pathways were firstly standardized respectively using z-score standardization. Then, Pearson correlation coefficients between DEGs and DEMs were calculated by R version 4.2.3. Correlation pairs were selected with an absolute value threshold over 0.9 and p-value lower than 0.05. Finally, the gene-metabolite co-expression network was visualized with Cytoscape-v3.7.2 (available at www.gnu.org/licenses/lgpl-2.1.html).

    Selective pressure analysis of the candidate genes

    To explore orthologous genes that have potentially undergoing adaptive differentiation between two ecotypes in response to differing altitudinal environments, the transcriptome sequences of each ecotype were first assembled separately by Trinity version 2.4.0[32]. Subsequently, the resulting clean sequences were searched by BLASTp version 2.2.31 under the threshold of E-value < 1e-5, and then were predicted and translated into protein-coding sequences by TransDecoder version 3.0.0. Meanwhile, OrthoMCL-V2.0.9 software was employed to discern potential orthologs and paralogs among the protein sequences derived from each ecotype's transcriptome. Then, pairwise comparisons were further conducted on putative single-copy orthologs to estimate selective pressure, and ParaAT was used to parallelly construct protein-CDS alignments for these orthologs[34]. Finally, the synonymous substitution rates (Ks), non-synonymous rates (Ka) and Ka/Ks value were calculated for each putative single-copy homologous gene between the two ecotypes with KaKs_Calculator 2.0[35] under the YN model of approximate method[36]. Pairs with Ks > 0.1 were excluded to avoid potential paralogs. The positive selection genes (PSGs) with Ka/Ks value higher than 1 were further verified by the codeml program in PAML[37].

    Population sampling, DNA isolation, PCR amplification, sequencing, and sequence alignment

    To further verify whether sandrice has significantly diverged among ecotypes along with different altitude gradients, population analysis was also conducted among populations of sandrice inhabiting different altitudes. A total of 22 sandrice populations with four to six individuals for each population were collected, including the alpine group from the Qaidam Basin with an altitude of 2,000−3,500 m, the middle altitude group from Tengger desert, Ulan Buhe Desert, Kubuqi Desert, and Mu Us sandy land with an altitude of 1,000−2,000 m, and the low altitude group from Otindag sandy land, Horqin sandy land, and Hulun Buir sandy land with altitude of 0−1,000 m (Supplementary Table S1). Meanwhile, a population of A. minus was also collected from Gurbantunggut desert as the outgroup. All the samples were selected apart from > 50 m for each individual. Fresh leaves were dried and preserved in silica gel, and voucher specimens were deposited in the Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences.

    Total genomic DNA was isolated from the tissue samples with TIANGEN Plant Genomic DNA Kit (Tiangen Biotech Co., Ltd, Bejing, China) following the manufacturer's protocol. All the DNA samples were quantified by Qubit assay HS kit (Life Technologies, Burlington, ON, Canada) with assays read on a Qubit v2.0 (Life Technologies). In total, 24 pairs of primers were designed by PRIMER version 5.0 based on the RNA-seq data (Supplementary Table S2). Among them, genes under positive selection identified by selective pressure analysis, especially those associated with the known stress-resistance pathways of phenylpropanoid and flavonoid biosynthesis pathways[13,38−41], were identified as candidate genes. Conversely, neutral genes annotated with irrelevant functions to stress resistance were considered reference genes (Supplementary Table S2). All these gene fragments were amplified across these 22 populations using 2 × Taq Plus highfidelity PCR MasterMix (Tiangen, Beijing, China) in a Gene-Amp PCR system 9700 DNA Thermal Cycler (PE Applied Biosystems, Norwalk, USA) following the programs listed in Supplementary Table S2. PCR products were purified with TIAN quick Midi Purification Kits (Tiangen, Beijing, China) and then were Sanger-sequenced with both forward and reverse primers by GENEWIZ company (Tianjin, China). Multiple sequences were aligned and adjusted manually by BIOEDIT version 7.2.6.1 software[42]. The structures of all gene fragments were defined by alignment with their corresponding mRNA sequences and their best hits of BLAST on ESTs (Expressed Sequence tags) from NCBI. All these new sequences were deposited in GenBank under accession numbers OM338032-OM338057, OP846852-OP846955.

    Population genetics analysis

    Genetic diversity was estimated for each gene fragment in three groups with different altitudinal gradients by calculating the number of segregating sites (S), nucleotide diversity statistics (θw; π)[43,44], the number of haplotypes (Nh) and haplotype diversity (He)[45] for all sites, silent sites, and nonsynonymous sites with DnaSP version 5.10[46]. Meanwhile, the fixation index (FST) of each loci was also computed among high, middle, and low altitude groups to estimate the genetic divergence degree with AMOVA in the program Arlequin version 3.1.1 with default settings[47].

    Furthermore, to detect whether there were any signals of evolutionary adaptation to different altitudinal gradients habitats, neutrality tests were performed for each fragment with several methods, including Tajima's D test , Fu & Li's D* and F* test[43], Fay & Wu's H test[48], DH test[49], McDonald-Kreitman (MK) test[50] and the maximum frequency of derived mutations (MFDM) test[51]. Finally, to understand the evolutionary relationships and patterns of these putative alpine adaptive genes across different altitude populations, genealogical topologies were constructed using the median-joining (MJ) model in NETWORK Version 4.6.1.259[52] for their haplotypes.

    Results

    Global metabolic profiling in two altitudinal ecotypes of sandrice

    Based on the non-targeted UPLC-MS/MS metabolic profiling, a total of 506 metabolites were detected. Among these metabolites, 244 metabolites could be matched to known biochemical structures (Supplementary Fig. S1), including 39 flavonoids, 39 amino acids and derivatives, 27 nucleotide and derivatives, 19 polyphenols, 18 vitamins, 16 alkaloids, 11 lipids, seven organic acids, eight coumarins, eight terpnoids, nine carbohydrates, and 43 additional compounds. PCA analysis revealed distinct clustering of metabolites, segregating into ETL and CC groups based on two altitudinal ecotypes and different tissue types (Fig. 1b). Remarkably, metabolite profiles in leaves differed from those in stems and spikes. However, metabolites in stem samples exhibited similarities or equivalences to those in spikes.

    Among the 244 metabolites, the most prevalent secondary metabolites were identified as flavonoids, alkaloids, and polyphenols. In comparison with CC, ETL exhibited higher levels of total hesperetin, quercetin, betaine, trigonelline, caffeic acid, and ferulic acid. Conversely, CC displayed greater accumulation of total tricin, chrysoeriol, etamiphylline, theobromine, sinapic acid, and p-coumaric acid (Fig. 1c). Among three tissues of the two ecotypes, the most remarkable and largest number of DEMs were identified as flavonoid and polyphenol compounds, followed by nucleotides and derivatives, as well as lipids. In ETL, the contents of eriodictyol chalcone and ferulic acid O-hexoside significantly accumulated, whereas tricin 7-O-rutinoside showed a notable accumulation in CC. Compared to CC, the leaf of ETL exhibited significant increases in apigenin 7-O-rutinoside and quercetin-3-beta-O-galactoside, while the content of chrysoeriol O-hexoside decreased significantly. In the stem and spike of ETL, hesperetin 5-O-glucoside content was significantly higher, whereas two glycosylated tricins (tricin O-rutinoside and tricin 5-O-hexoside) were significantly reduced. Additionally, kaempferide showed a significant decrease in levels specifically in the stem of ETL (Table 1).

    Table 1.  List of metabolites in phenylpropanoid and flavonoid biosynthesis pathways in two altitudinal ecotypes of A. squarrosum.
    Class Metabolite name ETL vs CC
    Leaf Stem Spike
    FC VIP FC VIP FC VIP
    Flavonoid Naringenin 7-O-glucoside 0.98 0.01 0.61 0.56 0.52 0.56
    Hesperetin 5-O-glucoside 1.30 0.27 2.00 1.22 2.38 1.22
    Apigenin 7-O-rutinoside 105.03 1.59 2.44 0.66 2.18 0.66
    Luteolin 7-O-glucoside 1.44 0.67 1.31 0.43 0.93 0.43
    Luteolin O-hexoside 1.77 0.96 1.33 0.78 0.92 0.78
    Chrysoeriol O-hexoside 0.39↓ 1.52 0.45 0.94 0.65 0.94
    Chrysoeriol C-hexoside 0.42 0.57 0.33 0.72 0.26 0.72
    Selgin O-hexoside 1.03 0.54 1.16 0.53 1.07 0.53
    Tricin O-rutinoside 0.32 0.89 0.17↓ 1.02 0.32↓ 1.02
    Tricin 7-O-rutinoside 0.34↓ 1.09 0.20↓ 1.27 0.40↓ 1.27
    Tricin 5-O-hexoside 0.83 0.12 0.43↓ 1.19 0.38↓ 1.19
    Eriodictyol chalcone 5.93 1.39 3.43 1.42 2.62 1.42
    Quercetin-3-beta-O-galactoside 4.23 1.03 1.19 0.08 1.07 0.08
    Kaempferol 3-O-glucoside 1.55 0.96 1.24 0.38 0.95 0.38
    Kaempferide 1.23 0.69 0.48↓ 1.42 0.62 1.42
    Phenylpropanoids p-Coumaric acid 0.83 1.22 0.69 0.88 0.79 0.88
    Caffeic acid 1.74 1.00 1.00 0.22 2.28 0.22
    Ferulic acid O-hexoside 3.46 1.26 4.20 1.48 2.75 1.48
    The relative abundance of metabolites were displayed in Supplementary Table S1. FC, the fold change of metabolites when ETL compared CC; VIP, variable importance in the projection value. Bold font indicates significantly changed metabolites (FC ≥ 2 or ≤ 0.5,VIP ≥ 0.5). represents increased metabolites in ETL. ↓ represents decreased metabolites in ETL.
     | Show Table
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    Transcriptome analysis in two altitudinal ecotypes of sandrice

    After the removal of sequences with low quality, poly-N, and adaptors, 884,051,398 clean reads were filtered from the 128.96 Gb raw data, with Q30 over 81.13% and the average N50 of 690.38 bp (Supplementary Table S3). Subsequently, these high-quality trimmed clean reads were de novo assembled into contigs and then a joint transcript of 135,686 unigenes. Finally, 69,977 annotated unigenes were identified across all transcripts, each represented in at least one database (Supplementary Table S4). The most abundant KOG terms identified in the unigenes included those related to general function prediction only, signal transduction mechanisms, post-translational modification, protein turnover, and chaperones (Supplementary Fig. S2a). The GO enrichment analysis of the entire transcriptome revealed that the annotated unigenes predominantly participated in metabolic processes and cellular processes (Supplementary Fig. S2b).

    In comparison to the gene expression levels in CC, 16,680 unigenes were up-regulated and 12,773 unigenes were down-regulated in ETL. Additionally, Venn analysis of DEGs revealed that the number of tissue-specific DEGs was higher in the leaf and stem than in the spike (Fig. 2a). The highest number of DEGs with the strongest differential expression level was detected in leaves. KEGG analysis revealed that DEGs of three tissues between the high and middle ecotypes of sandrice were predominantly enriched in pathways such as photosynthesis, starch and sucrose metabolism, flavonoid synthesis, phenylpropanoid synthesis, ribosomal regulation, and carbon metabolism. (Fig. 2b−d).

    Figure 2.  The state and KEGG pathway enrichment of differentially expressed genes (DEGs) in different tissues from high- and middle-ecotypes of A. squarrosum. (a) Venn diagram indicating the overlapping and unique up-regulated (left) and down-regulated (right). (b)−(d) KEGG pathway enrichment analysis of DEGs in leaf, stem and spike. The number of genes is indicated by the size of the circle and the color of the circle shows significant enrichment through P-value. The top 20 pathways with the minimum P-value are shown in each tissue.
    DownLoad: Full-Size Img PowerPoint

    To explore candidate genes involved in high-altitude adaptation, comparative transcriptome analysis was further conducted. A total of 10,275 pairs of single-copy putative orthologous genes were identified after filtering out those with unexpected stop codons. Among them, 127 pairs of orthologous genes showed signs of positive selection with Ka/Ks values greater than 1 (Supplementary Table S5). Although no significantly over-represented KEGG categories were detected, and half of these positively selected genes (PSGs) could not be well-matched to several annotation databases, some PSGs were still putatively annotated to functions related to DNA repair, response to stress, and metabolism (Table 2).

    Table 2.  Typical differentiated genes for high elevation adaptation.
    Unigene ID ETL_Leaf
    FPKM    		 CC_leaf
    FPKM    		 ETL_spike
    FPKM    		 CC_spike
    FPKM    		 ETL_stem
    FPKM    		 CC_stem
    FPKM    		 La Ka Ks Ka/Ks Gene annotation Possible functions and biological process
    TR86494|c0_g1_i1 0 0 1.71 2.76 0.20 0.34 1044 0.00787 0.00365 2.157 Shikimate O-hydroxycinnamoyltransferase (HCT) Phenylpropanoid biosynthesis;
    Flavonoid biosynthesis
    TR80792|c3_g1_i2 51.14 25.12 6.13 1.94 29.94 4.86 1176 0.00780 0.00423 1.845 Flavonol synthase (FLS) Phenylpropanoid biosynthesis;
    Flavonoid biosynthesis
    TR45359|c0_g2_i1 29.58 5.35 1.73 0.27 7.19 1.72 489 0.0164 0.00899 1.828 Caffeoyl-CoA O-methyltransferase (CCoAOMT) Phenylpropanoid biosynthesis;
    Flavonoid biosynthesis
    TR934|c0_g1_i1 0.94 0.84 2.68 2.48 2.49 1.38 1143 0.00288 0.00272 1.056 A/G-specific adenine DNA glycosylase (ANG ) Base excision repair
    TR74739|c0_g2_i1 2.13 3.45 3.52 3.52 3.50 2.85 1791 0.00514 0.00318 1.615 Uracil-DNA glycosylase (UNG) Base excision repair; Immune diseases
    TR39350|c0_g4_i1 1.59 3.59 1.53 2.28 9.18 6.21 1434 0.00358 0.00330 1.087 Vegetative cell wall protein gp1(GP1) Defense response
    TR39755|c0_g1_i1 7.79 2.74 5.65 4.64 7.37 3.86 1089 0.00505 0.00345 1.463 Elongator complex protein 4 (ELP4) Response to oxidative stress, abscisic acid signaling pathway
    TR40190|c7_g5_i1 25.76 28.38 23.06 20.04 31.05 27.46 300 0.02602 0.00831 3.130 Calcium-dependent protein kinase 1 (CDPK1) Plant-pathogen interaction; Response to drought, cold stress; Salicylic acid biosynthesis
    FPKM, gene expression level; La, the length of candidate genes (bp); Ka, nonsynonymous substitution rate; Ks, synonymous substitution rate; Ka/Ks, selective strength; p-value, the value computed by Fisher exact test when calculating Ka/Ks
     | Show Table
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    For example, two genes (TR934|c0_g1_i1, TR74739|c0_g2_i1), which encoded A/G-specific adenine DNA glycosylase (ANG) and uracil-DNA glycosylase (UNG) participated in DNA base excision repair; TR39350|c0_g4_i1 encoding Vegetative cell wall protein gp1 (GP1) took part in defense response; TR39755|c0_g1_i1 encoding a subunit of elongator complex (ELP4), mediated ABA signaling pathway and manifested oxidative stress resistance. TR40190|c7_g5_i1, which encoded putative calcium-dependent protein kinase family protein (CDPK1), played a vital role in pathogen resistance abiotic stress and salicylic acid biosynthesis. Besides, three genes encoding shikimate O-hydroxycinnamoyltransferase (HCT), flavonol synthase (FLS), and caffeoyl-CoA O-methyltransferase (CCoAOMT), which are involved in phenylpropanoid and flavonoid pathway, were suggested to be under strong positive selection between the two altitudinal ecotypes (Table 2).

    Correlation analysis of DEMs and DEGs in two altitudinal ecotypes

    The integrated analysis between DEMs and DEGs in the phenylpropanoid and flavonoid pathway revealed a significant relationship between the accumulation of metabolisms and the expression of key genes. For example, PAL, CHS, CHI, F3H, and FLS showed significant up-regulation in the high-altitude ecotype ETL compared to CC, consisting of significantly elevated enrichment of corresponding downstream flavonoid and phenylpropanoid contents in ETL (Fig. 3a). Subsequently, as illustrated in Fig. 3b, correlation analysis between gene expression in flavonoid and phenylpropane metabolic pathways and the enrichment of metabolites further revealed that the expression of the COMT1 is positively correlated with the accumulation of most metabolites in the flavonoid and phenylpropanoid metabolic pathways, except for luteolin-O-hexoside and quercetin 3-O-glucoside, which exhibit negative correlations. In terms of differential accumulation of metabolites between the two altitude ecotypes, the level of naringenin 5-O-glucoside directly correlated with the differential expression of CHI, CHS, and F3H. Meanwhile, the accumulation of chrysin 5-O-hexoside was positively correlated with the expression of CHS and COMT. The high expression of these genes would reduce the availability of the substrate naringenin for chrysin synthesis, thereby prompting the production of products from alternative pathways (Fig. 3a). Differences in the accumulation of ferulic acid O-hexoside correlated directly with the differential expression of PAL. Furthermore, the content of quercetin 3-O-glucoside was negatively correlated with the expression levels of CHI, CHS, 4CL, and F3H genes in the high-altitude ecotype of sandrice, leading to reduced quercetin synthesis compared to the mid-altitude ecotype.

    Figure 3.  Phenylpropanoid and flavonoid pathways in A. squarrosum. (a) The schematic representation of gene and metabolite changes in phenylpropanoid and flavonoid pathways. The dotted line represented unreported pathway. (b) The interacted network constituted from genes and metabolites co-expression in phenylpropanoid and flavonoid pathways.
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    Population genetics and divergence among populations across varying altitude gradients

    Population genetics analysis revealed that putative alpine adaptive genes exhibited higher levels of nucleotide diversity compared to each reference locus, as well as the haplotype diversity (Supplementary Table S6). Interestingly, further analysis of genetic diversity across different altitude gradient groups revealed discernible differences, despite the statistical insignificance (Supplementary Fig. S3). Specifically, gene segments at higher altitudes exhibited notably lower nucleotide diversity. Notably, certain gene segments in high-altitude populations, such as PAL, C3H, FOMT, FNS, F3H, CYP75B4, and CHS, displayed nucleotide diversity as low as zero (Supplementary Fig. S3).

    Fixation index (FST) values were also estimated to assess genetic differentiation among high, middle, and low altitude populations with population genetic data from candidate genes and reference loci, supplemented by SNPs obtained through restriction site-associated DNA sequencing (RAD-seq), which provided a representation of genome-wide variation. Significant genetic differentiation was observed among the high-, middle-, and low-altitude populations (Fig. 4). Specifically, between the high and middle altitude populations, several candidate genes showed notable levels of FST: UNG (FST = 0.410), CDPK1 (FST = 0.228), FLS (FST = 0.144), GP1 (FST = 0.104), and CCoAOMT (FST = 0.099), which were all higher than the average genome-wide FST level (FST = 0.051), indicating significant genetic divergence. Within the phenylpropanoid and flavonoids pathway, F3'H (FST = 0.525), and CHI (FST = 0.300) exhibited the highest levels of genetic differentiation between the high and middle populations.

    Figure 4.  Genetic differentiation among different altitudinal populations in A. squarrosum. (a) High- and middle-altitude populations. (b) High- and low-altitude populations. (c) Middle- and low-altitude populations. The red dashed line represents the average genome-wide FST level.
    DownLoad: Full-Size Img PowerPoint

    Neutrality tests were further conducted for all candidate genes and reference loci among 22 populations of sandrice along with altitudinal clines. Among these, four PSGs (ELP4, GP1, FLS, and HCT) were fixed in the high-altitude group with only one allele, as well as nine genes involved in phenylpropanoid and flavonoids pathways, such as FLS, HCT, PAL, C3H, FOMT, FNS, F3H, CYP75B4, and CHS (Supplementary Table S6). Furthermore, as indicated by Tajima's D, Fu & Li's D*, F* values, UNG showed robust signal of positive selection in the high-altitude populations (Supplementary Table S7). Interestingly, for PSG CCoAOMT, involved in the phenylpropanoid and flavonoids pathway, Tajima's D and F* were significantly greater than zero. The MK test of CCoAOMT was also significant, suggesting that it was under balancing selection at the population level. However, the previous Ka/Ks value indicated positive selection for this gene (Table 2). Furthermore, haplotype network and topology analysis of CCoAOMT across different altitude populations showed that H1 might be the ancestral haplotype, while haplotypes H3 and H4 were specific to the high-altitude populations (Fig. 5a). Combined with distinct expression patterns of its alleles in high and middle altitude ecotypes, as revealed by transcriptome data featuring a non-synonymous mutation (Fig. 5b), CCoAOMT appears to have been selected due to ecological differentiation.

    Figure 5.  Haplotype distribution of CCoAOMT in A. squarrosum populations and the expression of two alleles of this gene based on transcriptome data. (a) Haplotype topology of CCoAOMT. (b) Expression levels and mutation sites of the two CCoAOMT alleles in high-altitude and middle-altitude ecotypes of A. squarrosum.
    DownLoad: Full-Size Img PowerPoint

    Discussion

    The QXP, adjacent to arid Central Asia, offers diverse habitats for biomes, however, it is highly sensitive to ongoing climate changes, particularly extensive desertification of alpine meadows[3]. Vegetation colonizing these desertified areas has evolved adaptive traits to cope with extreme environmental conditions resulting from climate change scenarios, and are also a priority candidate for vegetation reconstruction in alpine desertified lands[17]. However, few studies have explored the molecular basis of adaptation in plant species native to alpine desert ecosystems, especially concerning ecotypes across altitude gradients. As a pioneering species in vegetation restoration of desertified lands, sandrice provides compelling evidence that long-term local adaptation to multiple stresses drives adaptive divergence. This adaptation could significantly impact the success of ecological restoration and development in alpine grassland ecosystems threatened by desertification. Meanwhile, it also provides a solid foundation for improving and developing the medicinal value of sandrice.

    The role of flavonoids and phenylpropanoids in sandrice's adaptation to alpine environments

    Metabolites, particularly secondary metabolites, are pivotal for shaping species-specific traits and are integral to how plants respond to challenging environmental conditions[53]. Previous research indicates that in adapting to alpine conditions, plants have evolved to produce a rich array of secondary metabolites, including phenylpropanoids, flavonoids, ascorbic acid, etc. Besides the outstanding pharmaceutical values, these compounds are also pivotal in helping plants resist environmental stressors, providing numerous advantages such as antioxidative properties, the scavenging of reactive oxygen species (ROS), UV-B radiation absorption, enhanced cold tolerance, and the maintenance of osmotic balance[54]. Phenolics such as flavonoids and phenylpropanoids have even been demonstrated to exhibit species-specific distribution patterns that accumulate along altitudinal gradients in certain plant species[13,41,55]. In this study, compared to the mid-altitude ecotype of CC, significant enrichments of secondary metabolites were observed in the alpine ecotype of ETL, particularly in the phenylpropanoid and flavonoid biosynthesis pathways, such as hesperetin, betaine, quercetin, apigenin, caffeic acid, ferulic acid, etc (Fig. 2c). Interestingly, among these DEMs, apigenin, nobiletin, and ferulic acid were primarily found in glycoside forms (Table 1), which demonstrated potent antioxidant activity by effectively scavenging ROS to safeguard cellular functions and biotic stressor resistance[55,56]. Significant accumulations of flavonoid glycosides have also been found in qingke (Hordeum vulgare L. var. nudum), a crop that has been cultivated and exposed to long-term and intense UV-B radiation on the QXP[10]. Previous studies based on common garden experiments have demonstrated flavonoid accumulation in sandrice is positively correlated with temperature and UV-B radiation, but negatively affected by precipitation and sunshine duration[27,28]. Thus, for the alpine ecotype of sandrice, the significant accumulation of metabolisms, especially the flavonoids, and phenylpropanoids, would hypothetically be induced for adaptation to the long-term harsh alpine desert environment stressors, which further contribute to the high medicinal quality of alpine ecotype.

    Alpine adaptive evolution of phenylpropanoid and flavonoid biosynthesis pathways in sandrice

    Besides detecting a substantial number of DEMs within the phenylpropanoid and flavonoid biosynthesis pathways between mid-altitude and alpine ecotypes, a significant clustering of DEGs associated with the phenylpropanoid and flavonoid biosynthesis pathways was also observed between these two ecotypes (Fig. 2). Correlation analysis of DEMs and DEGs further demonstrated that the differential expression of constitutive genes in the phenylpropanoid and flavonoid biosynthesis pathways would contribute to the divergent enrichments of the downstream DEMs in sandrice. For instance, it has been observed that the transcriptional up-regulation of flavonoid biosynthesis genes (such as PAL, CHS, CHI, FLS, F3H, etc.) significantly enhances the accumulation of hesperetin, apigenin, and quercetin (Fig. 3a, b). These metabolites have been documented to boost plant resistance against UV-B radiation, drought, extreme temperatures, pathogens, and oxidative damage[55,56].

    Meanwhile, Ka/Ks analysis between the two altitudinal ecotypes identified that DEGs involved in the phenylpropanoid and flavonoid biosynthesis pathways, such as FLS, CCoAOMT, and HCT, experienced significant positive selection (Table 2). Furthermore, population genetic studies also identified alleles of nine genes (FLS, HCT, PAL, C3H, FOMT, FNS, F3H, CYP75B4, and CHS) out of the 15 tested genes from the phenylpropanoid and flavonoid biosynthesis pathways were fixed in the high-altitude populations (Supplementary Table S6). Previous studies based on RAD-seq and several neutral genetic markers have elucidated that there is no significant genetic differentiation between the high- and middle-altitude populations. This indicates that the high-altitude populations and mid-altitude populations share the same origination and dispersal patterns[19,26]. Thus, the fixation of alleles for these genes in the high-altitude populations might have occurred after populations' colonization on the QXP. Previous simulation and population genetic analyses in wild barley have revealed that advantageous alleles could be selectively preserved and tend to become fixed within the populations under strong environmental pressures[57]. To survive the harsh desert conditions of the QXP, advantageous alleles in the genes related to the phenylpropanoid and flavonoid biosynthesis pathways might be selectively retained. Then, under the environment's directional selection, these alleles could progressively replace other alleles and eventually establish themselves within the high-altitude populations.

    Interestingly, Ka/Ks analysis revealed that CCoAOMT, another critical gene in the biosynthesis of flavonoids and phenylpropanoids, is under diversifying selection between two altitudinal ecotypes (Table 2). Additionally, signals of balancing selection on this gene were also observed among the high-altitude populations, and the mid-altitude populations as well (Supplementary Table S7). CCoAOMT is a key enzyme that catalyzes the methylation of caffeoyl-CoA to feruloyl-CoA. This reaction is crucial in the production of monolignols, the fundamental building blocks of lignin. Lignin is vital for maintaining the structural integrity of plants and enhancing their resistance to pathogens, and also play a significant role in enabling plants to withstand abiotic stresses such as cold and drought[58,59]. In recent years, increasing research underscores that balancing selection, by preserving genetic diversity, is a fundamental evolutionary mechanism significantly contributing to the adaptability and survival of species in changing environments, ensuring populations can cope with new challenges and thrive across diverse ecological niches[26,60]. This result suggested that the balancing selection of genes involved in the phenylpropanoid and flavonoid biosynthesis pathways plays a pivotal role in enabling sandrice to endure and prosper under the varied extreme conditions of desert environments, including the harsher environment of alpine deserts.

    In general, to survive and thrive in the diverse and extreme desert environment for sandrice, functional genes such as those involved in phenylpropanoid and flavonoid biosynthesis pathways experienced balanced selection among populations with different ecological niches, which could preserve high genetic diversity to ensure populations that can cope with diverse challenges. However, populations of sandrice inhabiting the alpine deserts endure even harsher conditions compared to those in other northern deserts. Under such environmental stress and selective pressure, a greater number of functional genes of phenylpropanoid and flavonoid biosynthesis pathways undergo directional selection, resulting in a shift in the population's genetic makeup toward certain favorable alleles. In some cases, this process leads to the presence of only one advantageous allele for specific functional genes within the population, influencing gene expression and subsequently regulating the high accumulation of downstream flavonoids and phenylpropanoids to enable the population to thrive in the harsh environments of the QXP deserts. As a result of long-term local adaptation, the accumulation of flavonoids and phenylpropanoids in sandrice has significantly diverged among ecotypes from different altitudes, even within the same common garden[27,28].

    In addition to the phenylpropanoid and flavonoid biosynthesis pathways, pathways of photosynthesis, starch and sucrose metabolism, flavonoid synthesis, phenylpropanoid synthesis, ribosomal regulation, and carbon metabolism, and several genes related to chronic hypoxia, oxidative stress, DNA damage repair, and stress response regulation, such as ANG, UNG, PRX3, ELP4, CDPK1, and GP1, are also suggested to play crucial roles in sandrice's adaptation to the harsh desert environment of QXP (Fig. 2, Table 2). To gain a comprehensive understanding of sandrice's adaptation mechanisms to alpine deserts and the formation of medicinal components in sandrice under high-altitude environmental factors, further genetic evidence is needed to validate the molecular functions and regulatory relationships among these adaptive alleles and pathways, the expression of functional genes, and the subsequent synthesis and accumulation of those anti-stress metabolites.

  • The authors confirm contribution to the paper as follows: study conception and design: Ma XF, Yan X, Yin X; data collection: Yin X, Qian C, Fan X, Zhou S; analysis and interpretation of results: Yin X, Qian C, Fang T, Yang J, Chang Y; draft manuscript preparation: Qian C, Yin X, Yan X, Chang Y. All authors reviewed the results and approved the final version of the manuscript.

  • All the raw sequenced data was submitted to GenBank (www.ncbi.nlm.nih.gov) (accession numbers: PRJNA659807; OM338032-OM338057, OP846852-OP846955).

    • Acknowledgments

    This research was supported by the National Natural Science Foundation of China (Grant No. 32271695); Lanzhou Youth Science and Technology Talent Innovation Project (Grant No. 2023-QN-140); Chinese Academy of Sciences Strategic Biological Resources Program (Grant No. KFJ-BRP-007-015); Gansu Province to Guide the Development of Scientific and Technological Innovation Special Fund Competitive Project (Grant No. Y939BD1001), and National Natural Science Foundation of China (NSFC, Grant Nos 32171608 and 32201378).

  • The authors declare that they have no conflict of interest.

  • Supplemental Fig. S1 Effects of acidic conditions on plant root growth. (a) plant growth status, (b) primary root length, lateral root number, lateral root density (means ± SD, asterisks denote significant differences compared with control condition (pH 5.8) at * p < 0.05; ** p < 0.01，n ≥ 8) (Student t-test, Bar = 1 cm ).
    Supplemental Fig. S2 Effect of slightly alkaline conditions on LRP of Arabidopsis. (a) Lateral root primordium of each stage, “×” indicate pericycle, (b) number of LRP+ LR+ emergence (means ± SD, asterisks denote significant differences between columns at * p < 0.05, ** p < 0.01, n ≥ 8) (Student t-test, Bar = 0.02 mm).
    Supplemental Fig. S3 Effects of alkaline conditions on Arabidopsis PLT mutants root growth. (a) plant growth status, (b) primary root length, lateral root number (means ± SD, asterisks denote significant differences compared with control condition (pH 5.8) at * p < 0.05; ** p < 0.01, n ≥ 8) (Student t-test, Bar = 1 cm ).
    Supplemental Fig. S4 Effects of alkaline conditions on the root growth of arabidopsis mutants ibr1ibr3ibr10 and ech2ibr1ibr3ibr10. (a) plant growth status, (b) primary root length, lateral root number (means ± SD, asterisks denote significant differences compared with control condition (pH 5.8) at * p < 0.05; ** p < 0.01, n ≥ 8) (Student t-test, Bar = 1 cm ).
    Supplemental Fig. S5 The mutant seedlings of ABC transporter coding genes cultivated in pH-5.8 and -7.5 conditions.

  • Xuan W, Opdenacker D, Vanneste S, Beeckman T. 2018. Long-term in vivo imaging of luciferase-based reporter gene expression in Arabidopsis roots. In Root Development. Methods in Molecular Biology, eds. Ristova D, Barbez E. New York: Humana Press. pp. 177−90. https://doi.org/10.1007/978-1-4939-7747-5_13

    Google Scholar

    Anders S, Pyl PT, Huber W. 2015. HTSeq—a Python framework to work with high-throughput sequencing data. Bioinformatics 31:166−69

    doi: 10.1093/bioinformatics/btu638

    CrossRef    Google Scholar

    Bao Y, Aggarwal P, Robbins NE II, Sturrock CJ, Thompson MC, et al. 2014. Plant roots use a patterning mechanism to position lateral root branches toward available water. Proceedings of the National Academy of Sciences of the United States of America 111:9319−24

    doi: 10.1073/pnas.1400966111

    CrossRef    Google Scholar

    Beeckman T, Engler G. 1994. An easy technique for the clearing of histochemically stained plant tissue. Plant Molecular Biology Reporter 12:37−42

    doi: 10.1007/BF02668662

    CrossRef    Google Scholar

    Benfey PN, Scheres B. 2000. Root development. Current Biology 10:R813−R815

    doi: 10.1016/s0960-9822(00)00814-9

    CrossRef    Google Scholar

    Brautigan DJ, Rengasamy P, Chittleborough DJ. 2012. Aluminium speciation and phytotoxicity in alkaline soils. Plant and Soil 360:187−96

    doi: 10.1007/s11104-012-1232-5

    CrossRef    Google Scholar

    Brunoud G, Wells DM, Oliva M, Larrieu A, Mirabet V, et al. 2012. A novel sensor to map auxin response and distribution at high spatio-temporal resolution. Nature 482:103−6

    doi: 10.1038/nature10791

    CrossRef    Google Scholar

    Cavallari N, Artner C, Benkova E. 2021. Auxin-regulated lateral root organogenesis. Cold Spring Harbor Perspectives in Biology 13:a039941

    doi: 10.1101/cshperspect.a039941

    CrossRef    Google Scholar

    Chen Q, Liu Y, Maere S, Lee E, van Isterdael G, et al. 2015. A coherent transcriptional feed-forward motif model for mediating auxin-sensitive PIN3 expression during lateral root development. Nature Communications 6:8821

    doi: 10.1038/ncomms9821

    CrossRef    Google Scholar

    Chen S, Zhou Y, Chen Y, Gu J. 2018. Fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 34:i884−i890

    doi: 10.1093/bioinformatics/bty560

    CrossRef    Google Scholar

    Choudhury FK, Rivero RM, Blumwald E, Mittler R. 2017. Reactive oxygen species, abiotic stress and stress combination. The Plant Journal 90:856−67

    doi: 10.1111/tpj.13299

    CrossRef    Google Scholar

    Cross AT, Stevens JC, Sadler R, Moreira-Grez B, Ivanov D, et al. 2021. Compromised root development constrains the establishment potential of native plants in unamended alkaline post-mining substrates. Plant and Soil 461:163−79

    doi: 10.1007/s11104-018-3876-2

    CrossRef    Google Scholar

    De Rybel B, Vassileva V, Parizot B, Demeulenaere M, Grunewald W, et al. 2010. A novel Aux/IAA28 signaling cascade activates GATA23-dependent specification of lateral root founder cell identity. Current Biology 20:1697−706

    doi: 10.1016/j.cub.2010.09.007

    CrossRef    Google Scholar

    de Smet I, Vassileva V, de Rybel B, Levesque MP, Grunewald W, et al. 2008. Receptor-like kinase ACR4 restricts formative cell divisions in the Arabidopsis root. Science 322:594−97

    doi: 10.1126/science.1160158

    CrossRef    Google Scholar

    Dietrich D, Pang L, Kobayashi A, Fozard JA, Boudolf V, et al. 2017. Root hydrotropism is controlled via a cortex-specific growth mechanism. Nature Plants 3:17057

    doi: 10.1038/nplants.2017.57

    CrossRef    Google Scholar

    Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, et al. 2013. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29:15−21

    doi: 10.1093/bioinformatics/bts635

    CrossRef    Google Scholar

    Du Y, Scheres B. 2017. PLETHORA transcription factors orchestrate de novo organ patterning during Arabidopsis lateral root outgrowth. Proceedings of the National Academy of Sciences of the United States of America 114:11709−14

    doi: 10.1073/pnas.1714410114

    CrossRef    Google Scholar

    Duan X, Xu S, Xie Y, Li L, Qi W, et al. 2021. Periodic root branching is influenced by light through an HY1-HY5-auxin pathway. Current Biology 31:3834−3847.E5

    doi: 10.1016/j.cub.2021.06.055

    CrossRef    Google Scholar

    Dubrovsky JG, Sauer M, Napsucialy-Mendivil S, Ivanchenko MG, Friml J, et al. 2008. Auxin acts as a local morphogenetic trigger to specify lateral root founder cells. Proceedings of the National Academy of Sciences of the United States of America 105:8790−94

    doi: 10.1073/pnas.0712307105

    CrossRef    Google Scholar

    Ďurkovič J, Lux A. 2010. Micropropagation with a novel pattern of adventitious rooting in American sweetgum (Liquidambar styraciflua L.). Trees 24:491−7

    doi: 10.1007/s00468-010-0418-9

    CrossRef    Google Scholar

    Feng W, Lindner H, Robbins NE, Dinneny JR. 2016. Growing out of stress: the role of cell- and organ-scale growth control in plant water-stress responses. The Plant Cell 28:1769−82

    doi: 10.1105/tpc.16.00182

    CrossRef    Google Scholar

    Friml J, Gallei M, Gelová Z, Johnson A, Mazur E, et al. 2022. ABP1-TMK auxin perception for global phosphorylation and auxin canalization. Nature 609:575−81

    doi: 10.1038/s41586-022-05187-x

    CrossRef    Google Scholar

    Fujinami R, Yamada T, Nakajima A, Takagi S, Idogawa A, et al. 2017. Root apical meristem diversity in extant lycophytes and implications for root origins. New Phytologist 215:1210−20

    doi: 10.1111/nph.14630

    CrossRef    Google Scholar

    Galinha C, Hofhuis H, Luijten M, Willemsen V, Blilou I, et al. 2007. PLETHORA proteins as dose-dependent master regulators of Arabidopsis root development. Nature 449:1053−57

    doi: 10.1038/nature06206

    CrossRef    Google Scholar

    Galvan-Ampudia CS, Julkowska MM, Darwish E, Gandullo J, Korver RA, et al. 2013. Halotropism is a response of plant roots to avoid a saline environment. Current Biology 23:2044−50

    doi: 10.1016/j.cub.2013.08.042

    CrossRef    Google Scholar

    Geng G, Wang G, Stevanato P, Lv C, Wang Q, et al. 2021. Physiological and proteomic analysis of different molecular mechanisms of sugar beet response to acidic and alkaline pH environment. Frontiers in Plant Science 12:682799

    doi: 10.3389/fpls.2021.682799

    CrossRef    Google Scholar

    Giehl RFH, von Wirén N. 2014. Root nutrient foraging. Plant Physiology 166:509−17

    doi: 10.1104/pp.114.245225

    CrossRef    Google Scholar

    Gjetting SK, Ytting CK, Schulz A, Fuglsang AT. 2012. Live imaging of intra- and extracellular pH in plants using pHusion, a novel genetically encoded biosensor. Journal of Experimental Botany 63:3207−18

    doi: 10.1093/jxb/ers040

    CrossRef    Google Scholar

    Gujas B, Alonso-Blanco C, Hardtke CS. 2012. Natural Arabidopsis brx loss-of-function alleles confer root adaptation to acidic soil. Current Biology 22:1962−68

    doi: 10.1016/j.cub.2012.08.026

    CrossRef    Google Scholar

    Guo JH, Liu XJ, Zhang Y, Shen JL, Han WX, et al. 2010. Significant acidification in major Chinese croplands. Science 327:1008−10

    doi: 10.1126/science.1182570

    CrossRef    Google Scholar

    Hopkins F, Gonzalez-Meler MA, Flower CE, Lynch DJ, Czimczik C, et al. 2013. Ecosystem-level controls on root-rhizosphere respiration. New Phytologist 199:339−51

    doi: 10.1111/nph.12271

    CrossRef    Google Scholar

    Jia L, Xie Y, Wang Z, Luo L, Zhang C, et al. 2020. Rice plants respond to ammonium stress by adopting a helical root growth pattern. The Plant Journal 104:1023−37

    doi: 10.1111/tpj.14978

    CrossRef    Google Scholar

    Kim JY, Henrichs S, Bailly A, Vincenzetti V, Sovero V, et al. 2010. Identification of an ABCB/P-glycoprotein-specific inhibitor of auxin transport by chemical genomics. The Journal of Biological Chemistry 285:23309−17

    doi: 10.1074/jbc.M110.105981

    CrossRef    Google Scholar

    Kim Y, Chung YS, Lee E, Tripathi P, Heo S, et al. 2020. Root response to drought stress in rice (Oryza sativa L.). International Journal of Molecular Sciences 21:1513

    doi: 10.3390/ijms21041513

    CrossRef    Google Scholar

    Kircher S, Schopfer P. 2018. The plant hormone auxin beats the time for oscillating light-regulated lateral root induction. Development 145:dev169839

    doi: 10.1242/dev.169839

    CrossRef    Google Scholar

    Lagerwerff JV, Brower DL. 1972. Exchange adsorption of trace quantities of cadmium in soils treated with chlorides of aluminum, calcium and sodium. Soil Science Society of America Journal 36:734−37

    doi: 10.2136/sssaj1972.03615995003600050017x

    CrossRef    Google Scholar

    Li C, Liu G, Geng X, He C, Quan T, et al. 2021. Local regulation of auxin transport in root-apex transition zone mediates aluminium-induced Arabidopsis root-growth inhibition. The Plant Journal 108:55−66

    doi: 10.1111/tpj.15424

    CrossRef    Google Scholar

    Liu L, Song W, Huang S, Jiang K, Moriwaki Y, et al. 2022. Extracellular pH sensing by plant cell-surface peptide-receptor complexes. Cell 185:3341−3355.e13

    doi: 10.1016/j.cell.2022.07.012

    CrossRef    Google Scholar

    Love MI, Huber W, Anders S. 2014. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology 15:550

    doi: 10.1186/s13059-014-0550-8

    CrossRef    Google Scholar

    Luo H, Xu H, Chu C, He F, Fang S. 2020a. High temperature can change root system architecture and intensify root interactions of plant seedlings. Frontiers in Plant Science 11:160

    doi: 10.3389/fpls.2020.00160

    CrossRef    Google Scholar

    Luo L, Zhang Y, Xu G. 2020b. How does nitrogen shape plant architecture? Journal of Experimental Botany 71:4415−27

    doi: 10.1093/jxb/eraa187

    CrossRef    Google Scholar

    Ma X, Yan H, Yang J, Liu Y, Li Z, et al. 2021. PlantGSAD: a comprehensive gene set annotation database for plant species. Nucleic Acids Research 50:D1456−D1467

    doi: 10.1093/nar/gkab794

    CrossRef    Google Scholar

    Malamy JE, Benfey PN. 1997. Organization and cell differentiation in lateral roots of Arabidopsis thaliana. Development 124:33−44

    doi: 10.1242/dev.124.1.33

    CrossRef    Google Scholar

    Möller BK, Xuan W, Beeckman T. 2017. Dynamic control of lateral root positioning. Current Opinion in Plant Biology 35:1−7

    doi: 10.1016/j.pbi.2016.09.001

    CrossRef    Google Scholar

    Moreno-Risueno MA, van Norman JM, Moreno A, Zhang J, Ahnert SE, et al. 2010. Oscillating gene expression determines competence for periodic Arabidopsis root branching. Science 329:1306−11

    doi: 10.1126/science.1191937

    CrossRef    Google Scholar

    Msimbira LA, Smith DL. 2020. The roles of plant growth promoting microbes in enhancing plant tolerance to acidity and alkalinity stresses. Frontiers in Sustainable Food Systems 4:106

    doi: 10.3389/fsufs.2020.00106

    CrossRef    Google Scholar

    Ojeda-Rivera JO, Oropeza-Aburto A, Herrera-Estrella L. 2020. Dissection of root transcriptional responses to low pH, aluminum toxicity and iron excess under pi-limiting conditions in Arabidopsis wild-type and stop1 seedlings. Frontiers in Plant Science 11:01200

    doi: 10.3389/fpls.2020.01200

    CrossRef    Google Scholar

    Orman-Ligeza B, Morris EC, Parizot B, Lavigne T, Babé A, et al. 2018. The xerobranching response represses lateral root formation when roots are not in contact with water. Current Biology 28:3165−3173.e5

    doi: 10.1016/j.cub.2018.07.074

    CrossRef    Google Scholar

    van Gelderen K, Kang C, Paalman R, Keuskamp D, Hayes S, et al. 2018. Far-red light detection in the shoot regulates lateral root development through the HY5 transcription factor. The Plant Cell 30:101−16

    doi: 10.1105/tpc.17.00771

    CrossRef    Google Scholar

    van Norman JM, Xuan W, Beeckman T, Benfey PN. 2013. To branch or not to branch: the role of pre-patterning in lateral root formation. Development 140:4301−10

    doi: 10.1242/dev.090548

    CrossRef    Google Scholar

    Vermeer JEM, von Wangenheim D, Barberon M, Lee Y, Stelzer EHK, et al. 2014. A spatial accommodation by neighboring cells is required for organ initiation in Arabidopsis. Science 343:178−83

    doi: 10.1126/science.1245871

    CrossRef    Google Scholar

    Wang S, Zhao Z, Ge S, Zhang K, Tian C, et al. 2022. The effects of Suaeda salsa/Zea mays L. intercropping on plant growth and soil chemical characteristics in saline soil. Agriculture 12:107

    doi: 10.3390/agriculture12010107

    CrossRef    Google Scholar

    Xuan W, Audenaert D, Parizot B, Möller BK, Njo MF, et al. 2015. Root cap-derived auxin pre-patterns the longitudinal axis of the Arabidopsis root. Current Biology 25:1381−8

    doi: 10.1016/j.cub.2015.03.046

    CrossRef    Google Scholar

    Xuan W, Band LR, Kumpf RP, van Damme D, Parizot B, et al. 2016. Cyclic programmed cell death stimulates hormone signaling and root development in Arabidopsis. Science 351:384−87

    doi: 10.1126/science.aad2776

    CrossRef    Google Scholar

    Xuan W, Opdenacker D, Vanneste S, Beeckman T. 2018. Long-term in vivo imaging of luciferase-based reporter gene expression in Arabidopsis roots. In Root Development. Methods in Molecular Biology, eds. Ristova D, Barbez E. Vol 1761. New York: Humana Press. pp. 177−90 https://doi.org/10.1007/978-1-4939-7747-5_13

    Google Scholar

    Zhang J, Wang X, Zhang L, Zhao F. 2021. Reducing cadmium bioavailability and accumulation in vegetable by an alkalizing bacterial strain. The Science of the Total Environment 758:143596

    doi: 10.1016/j.scitotenv.2020.143596

    CrossRef    Google Scholar

  • Cite this article

    Duan X, Luo L, Wang Z, Wang W, Ye C, et al. 2023. Promotion of root development by slightly alkaline pH involves an auxin mediated adaption mechanism. Soil Science and Environment 2:6 doi: 10.48130/SSE-2023-0006
    Duan X, Luo L, Wang Z, Wang W, Ye C, et al. 2023. Promotion of root development by slightly alkaline pH involves an auxin mediated adaption mechanism. Soil Science and Environment 2:6 doi: 10.48130/SSE-2023-0006
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Promotion of root development by slightly alkaline pH involves an auxin mediated adaption mechanism

  • 1.

    State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, MOA Key Laboratory of Plant Nutrition and Fertilization in Lower-Middle Reaches of the Yangtze River, Nanjing Agricultural University, Nanjing 210095, China

  • 2.

    The Collage of Life Science, Anhui Agricultural University, Hefei 230036, China

  • 3.

    International Genome Center, Jiangsu University, Zhenjiang 212013, China

  • 4.

    Excellence and Innovation Centre, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China

  • 5.

    Key Laboratory of Saline-Alkali Soil Improvement and Utilization (Coastal Saline-Alkali Lands), Ministry of Agriculture and Rural Affairs, Nanjing 210014, China

  • Received: 07 April 2023
  • Accepted: 02 June 2023
  • Published online: 07 July 2023
Soil Science and Environment  2,  Article number: 6  (2023)  |  Cite this article

Abstract: The present study performed experiments to identify the superior pH for Arabidopsis root growth base on its development (radical root length and lateral root density); and then approached the mechanism by which optimized pH primes root development. The results showed that neutral to slightly alkaline pH (7.0−8.0) in medium was the optimum range in which the plant had longer primary roots and denser lateral roots. Auxin reporter DII:VENUS transgenic line cultured in standard (5.8) and slightly alkaline (7.5) pH indicated that in pH 7.5 conditions, there was less fluorescence in the root cap compared to in acidic conditions. Furthermore, the DR5:Luciferase transgenic plant showed pH 7.5 accelerated the auxin oscillation frequency, was 17.83% shorter than that in pH 5.8. Later, a series of mutant germplasms showed slightly alkaline conditions promoting root development were independent from PLT transcript factors, but mainly mediated by auxin transportation. Transcriptomic dynamic analysis showed pH 7.5 conditions could trigger the changes in the pathways of plant hormones signal transduction and ABC transporter. The mutants of the ABC transporter coding genes were thus tested and the results showed that mutant abcb20 could block the slightly alkaline (7.5) pH promoting root development completely, as well as several other mutants blocking it partially.

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    Introduction

    • The plant root is an important organ throughout the life cycle of almost all terrestrial plant species. Plant roots not only anchor plants to the soil but also facilitate water and nutrient uptake (Benfey and Scheres, 2000; Luo et al., 2020b). Root exudates engineer rhizosphere microbiota. In turn, microbiota play pivotal roles in plant nutrient use efficiency and combat harmful organisms (Hopkins et al., 2013). Therefore, root development and its system architecture (RSA) play an important role in crop productivity, and illustrating the mechanism of root development and architecture adapting to the ever-changing environment provides meaningful information for breeding and cultivation.

      RSA is a post-embryonic development process. For instance in Arabidopsis, the most acknowledged model plant: its primary root elongation is coordinated by the cell division activity of the root apical meristem, and subsequent elongation of the cells when they enter the elongation zone. Its lateral roots (LRs) develop along the primary root with regular spacing. The LRs development initiates from a patch of xylem pole pericycle cells that undergo nuclear migration, asymmetric cell division, followed by cell wall remodeling of the overlaying cells, and after several subsequent rounds of cell division in the developing primordium, finally result in emergence of a LR (Dubrovsky et al., 2008; de Smet et al., 2008; de Rybel et al., 2010; Vermeer et al., 2014). The initiation and development of LRs have been demonstrated to be governed by the plant hormone auxin through its biosynthesis, transport and redistribution in the root (by AUXs and PIN auxin carriers), and signaling pathway (Adamowski and Friml, 2015; Chen et al., 2015; Kircher & Schopfer, 2018). More recently, LR development was found to be triggered by oscillation of auxin related gene expression stimulated in a confined root zone (known as oscillation zone, OZ), where a patch of xylem pole pericycle cells are primed to divide and make a lateral root primordium (LRP) (Moreno-Risueno et al., 2010; van Norman et al., 2013). This oscillatory process is described as the root clock, and is characterized by both the amplitude and the frequency of gene expression in OZ visualized by DR5:Luciferase expression (Moreno-Risueno et al., 2010; Xuan et al., 2015; Duan et al., 2021). It is proposed that the oscillatory behavior of gene expression is dictated by the generation of auxin pulses in the main root derived from a release of auxin from dying lateral root cap (LRC) cells that are undergoing programmed cell death (PCD) (Xuan et al., 2016; Möller et al., 2017).

      The development of plant root is continuous and sensitive to the environmental factors such as light, temperature, moisture, soil pH and ion concentration (van Gelderen et al., 2018; Kim et al., 2020; Luo et al., 2020a; Msimbira & Smith, 2020; Wang et al., 2022; Liu et al., 2022). For instance, lateral roots are found to emerge towards water sources under water-deficit (termed as hydro-patterning), and reduce initiation under drought stress (xero-branching response); primary root can adjust growth direction to avoid salt stress (halo-tropism) (Galvan-Ampudia et al., 2013; Bao et al., 2014; Giehl & von Wiren, 2014; Feng et al., 2016; Dietrich et al., 2017; Orman-Ligeza et al., 2018). Soil pH is a pivotal parameter shaping root architecture. Both soil acidification and alkalization have negative effects on plant root development (Msimbira & Smith, 2020), and is looming worldwide. For instance, according to the soil survey results, the area of acidified soil in China is as high as 2.04 × 108 hm2, mainly distributed in the subtropical and tropical areas south of the Yangtze River, Yunnan, Guizhou and Sichuan (Guo et al., 2010). Acidified soil environments cause a decrease in plant root cellular pH. When the pH value of soil solution is below 5.0, the plant cell biological activities are gradually inhibited as the concentration of Al3+ and Mn2+ ions reaching a toxic level, and interfer with the absorption of essential macronutrients (Guo et al., 2010). A high acidic environment is also harmful to root development because the outside proton over inflow into cytoplasm is destructive to root development. Soil alkalization means that Ca2+ and Mg2+ adsorbed in the soil colloid are replaced by a large amount of Na+ during soil desalination, resulting in soil pH ≥ 8.5 (Lagerwerff & Brower, 1972; Zhang et al., 2021). The salt content of the alkaline soil is usually below 0.5%, but the soil solution contains a large amount of Na2CO3 and NaHCO3. Alkaline soil is easy to harden, mainly due to the changes of physical and chemical properties, resulting in poor water retention and air permeability making it difficult for roots to breathe and absorb water. The High-affinity K+ transporter (HKT) family genes, Na+/H+ exchanger (NHX) family genes, and Salt overly sensitive 1 (SOS1) are overexpressed in plant roots, stems and leaves when plants roots are subjected to alkaline stress (Choudhury et al., 2017).

      As shown above, it has been reported that plant root development could be largely affected by environmental pH conditions (Cross et al., 2021). Recent studies also showed both LR formation and PR elongation are restricted under low environmental pH (acidic) conditions (Ojeda-Rivera et al., 2020; Friml et al., 2022). In this study, gradient pH setting treatments showed that the seedlings cultured in slight alkaline conditions (pH = 7.5) had better primary and lateral root growth. We found that slightly alkaline conditions are essential for maintaining the oscillation periodicity, amplitude in the oscillation zone (OZ), and promoting periodic LR branching. Further experiments showed that slightly alkaline promoting root development were mainly mediated by polar auxin transport (PAT), and auxin signaling genes: TIR1, AFB2, ARF7 and ARF19 were triggered for lateral root development. Therefore, slightly alkaline is a key factor in coordinating the effects on root development via modulating auxin homeostasis in Arabidopsis.

    Materials and methods

      Plant materials and growth conditions

    • Arabidopsis thaliana (Columbia) wild type lines were used in this study. Seed surfaces were sterilized with 70% (v/v) ethanol for 2 min followed by 30% (v/v) bleach for 15 min. Subsequently, the seeds were rinsed at least five times with sterile water, and kept at 4 °C in the refrigerator. After 3 d of vernalization, the Arabidopsis seeds were sown on Petri dishes containing sterile half-strength Murashige and Skoog (1/2MS) medium (0.5× MS salts, 1% sucrose, 10 mg/L myo-inositol, 0.5 g·L−1 2-(N-morpholino) ethanesulfonic acid, and 1% w/v agar) in a growth chamber (AR1200, Wuhan Ruihua Instrument & Equipment, China) at 22 °C under continuous light (100 μmol·m−2·s−1). The medium pH was adjusted with KOH. Arabidopsis seedlings were directly germinated on the 1/2MS medium with indicated pH, and their root phenotype was analyzed after 10 d.

      Chemical preparation and treatments

    • 1-N-Naphtyl Phtalamic Acid (NPA) and 2-[4-(diethylamino)-2-hydroxybenzoyl] benzoic acid (BUM) (Product No. 202908) was order from Shanghai Macklin Biochemical Co., Ltd Iodacetamide (IAM, ordered from Sigma, Product No. I1149), and Propidium iodide (PI, ordered from Sigma, Product No. P4864) were acquired from Sigma. D-luciferin (Product No. L1349) was acquired from Duchefa Biochemie. PI was dissolved in ddH2O, and D-Luciferin was dissolved in 0.01% Tween 80.

      For chemical treatments, the required amount of the stock solutions was added to (50 °C) melted 1/2 MS agar-containing medium, and mixed in 50-mL Falcon tubes before being poured into petri dishes (13 cm × 13 cm). Arabidopsis seeds were transferred to 13 cm square 1/2 MS agar plates containing the compounds after 5 d germination and treated for another 7 d. Primary root length and LR number were subsequently measured.

      Primary root and lateral root phenotype analyses

    • To quantify the root phenotype in wild-type plants and mutants, the emerged lateral roots of the 8-d-old seedlings were counted under a microscope. Subsequently, the whole seedlings were scanned with an EPSON XL11000 flatbed scanner and the length of the primary root was measured. For microscopic inspection of primordium stages, root samples were cleared as described previously (Malamy & Benfey, 1997), all samples were analyzed by differential interference contrast microscopy (Leica DM2500).

      Histochemical analysis

    • For the visualization of the expression of DR5:GUS and pCYCB1:GUS in the root tip, the histochemical GUS analysis was performed in 3-d-old seedlings under different pH value conditions, essentially as described previously (Beeckman & Engler, 1994), and all samples were analyzed by differential interference contrast microscopy (Leica DM2500 and OLYMPUS MVX10).

      Luciferase imaging and expression analysis

    • A Lumazone imaging system equipped with a charge-coupled device (CCD) camera (Andor iKon-M, DU934P-BV) was used to image the luciferase signal in the vertical growing Arabidopsis root tip according to a previous study (Xuan et al., 2018).

      Confocal microscopy and quantification

    • A Leica SP8X laser-scanning microscope were used for fluorescence imaging of roots. For the propidium iodide (PI)-treated root images, the seedlings were stained with 2 mg/mL PI for 5 min, washed with water, then seedlings transferred to slides for confocal imaging. The quantification of fluorescence signal intensity, the cortex cell number, and cell length were performed on the individual root.

      RNA-seq analysis

    • Arabidopsis seeds were germinated and cultured as described above in normal medium of pH5.8, and then after transferring them into medium of pH7.5, their roots were sampled after 0, 2 and 6 h, with three independent biological repeats. RNA-seq datasets were then analyzed following a custom protocol previously published (Duan et al., 2021). Briefly, raw data were also cleaned using Fastp v0.20 (Chen et al., 2018) and were then aligned to the Arabidopsis reference genome (TAIR10, www.arabidopsis.org) using STAR v2.7.8a with a splicing-aware method and two-pass model (Dobin et al., 2013). The gene expression matrix was quantified and normalized with FPKM (fragments per kilobase of transcript per million fragments mapped) using HTSeq. Only the genes with an FPKM > 1 in at least three samples were used for downstream gene expression analysis (Anders et al. 2015). DESeq2 (Love et al., 2014) was used to perform differential gene expression (DEG) analysis with Log2 (Fold change) ≥ 1 and the adjusted p-value < 0.05. Enrichment analysis based on KEGG database was carried out using PlantGSAD (Ma et al., 2021). The Benjamini–Yekutieli method was used for P-value adjustment.

      Statistical analysis

    • All the experiments in this study were performed at least three times. In each experiment, at least 10 individual seedlings per genotype were treated with or without slightly alkaline condition and used for further data analysis. To perform the statistical analysis regarding the time interval oscillations, at least eight individual seedlings were imaged and used for analysis. The data were analyzed using routines implemented in Prism 8 software (GraphPad Software). The significant difference among sets of data was determined by one-way ANOVA with post hoc Tukey test and Student's t test (p < 0.05). All the results are presented as the mean ± standard deviation (SD).

    Results and discussion

      Promotion of root growth of Arabidopsis seedlings by neutral and slightly alkaline pH

    • To investigate the root growth under acidic to alkaline conditions, the Arabidopsis seedlings were grown on the set of medium with pH gradient increasing from the acidic (5.8) to alkaline (9.0) since germination. Interestingly, in comparison with the seedlings grown in the medium of pH 5.8 (as the standard pH), the seedlings in neutral and slightly alkaline pH (7.0−8.0) had longer primary root (PR) and more lateral roots (PR) formation (Fig. 1a, b). This finding suggested the neutral and slight alkaline conditions could promote root development. Present research also showed that the growth of Arabidopsis PR and LR were substantially inhibited when the medium pH was at 8.5 and 9.0 (Fig. 1a, b), which hinted that the severe alkaline condition (pH ≥ 8.5) could be stressful to Arabidopsis. Simultaneously, the seedlings grown in the medium with very acidic pH (5.0) showed even shorter PR and less LRs as compared to the standard condition (pH 5.8) (Supplemental Fig. S1). These results collectively indicate that acidic and alkaline conditions hinder Arabidopsis root development, while neutral and slightly alkaline conditions promote root development.

      Figure 1. 

      Effects of alkaline and acidic pH on plant root growth. (a) Plant growth status, (b) primary root length, lateral root number, lateral root density; (c) dynamic changes of root growth of Arabidopsis under slightly alkaline (7.5) and the standard (5.8) pH cultivation. (means ± SD, asterisks denote significant differences compared with control condition pH 5.8, * p < 0.05; ** p < 0.01, n ≥ 8) (Student t-test, Bar = 1 cm).

      Further investigation was carried out using two different medium cultivation of pH 5.8 (as standard) and 7.5 (standing for neutral to slightly alkaline pH) from 5-d to 11-d after germination, and the primary root length and LR number were monitored daily. As shown in Fig. 1c, throughout the whole procedure, the root development at pH 7.5 remained superior to the standard conditions. To validate and visualize the apoplastic alkalinization in root induced by the slight alkaline pH (7.5), we analyzed the apoplastic pH using the apo-pHusion marker line (Gjetting et al., 2012). In the CK (pH 5.8), the apoplastic pH remained relatively acidic, while apoplastic pH raised and promoted root growth in the slightly alkaline conditions (Fig. 2a, b).

      Figure 2. 

      Effect of slightly alkaline pH on apoplast alkalinization, auxin signal, number of stem cells, and cell cycle in primary root apex. (a), (b) Localization and quantifications of apoplastic pH in the apo-pHusion marker line in the root meristem zone of light-grown Col-0 seedlings. (c), (d) the status of the meristem of primary root apex, yellow arrows indicate quiescent center, white arrows indicate the boundary between meristem zone and elongation zone, and the column charts showed the number of root meristem cells, root meristem length. (e) GUS staining showed the expression of CYCB1 in primary root apex. (f) Fluorescent protein in root apex of DII:VENUS. Bar = 0.1 mm, and the quantitative fluorescence strength were showed in the chart, n ≥ 8. (Means ± SD, asterisks denote significant differences between columns at * p < 0.05; ** p < 0.01, n ≥ 8). (Student t-test, Bar = 0.1 mm).

      Root meristem activity is triggered by slightly alkaline pH

    • The elongation of PR is determined by the cell division activity of root meristem at the root tip (Fujinami et al., 2017). We thereby checked the cell division activity of the Arabidopsis root in slightly alkaline pH (7.5) and the standard acidic (5.8). The developing roots in pH 7.5 had increased meristem-cell number and longer meristem length than those in pH 5.8 (Fig. 2c, d). The root tips in pH 7.5 had 19.98% increase in its meristem-cell number, and 21.42% increase in the meristem cell length than those in pH 5.8. Arabidopsis pCYCB1::GUS transgenic lines were cultivated in pH 7.5 and 5.8. The plant roots in the slightly alkaline medium showed stronger GUS blue color (Fig. 2e), which indicated higher cell division activity. As cell cycle progression is regulated by plant hormone auxin, we further investigated the auxin signaling in the meristem by using a high auxin sensitive reporter DII:VENUS, which is fast degraded by auxin (Brunoud et al., 2012). As shown in Fig. 2f, the Arabidopsis seedlings grown in the pH 7.5 medium showed less DII:VENUS signal (57.05% descending) in the root meristem than those in pH 5.8, indicating a higher intracellular auxin accumulation in the root meristem. Thus, the promotion on PR elongation by slightly alkaline pH might be due to the induced auxin signaling and cell division activity in the root meristem.

      Slightly alkaline pH facilitates the pre-branch site formation

    • Potential effects induced by the slightly alkaline pH on LR development stage was further analyzed. The cultivation of pH 7.5 medium enhanced the LR emergence, and more LR primordia were detected, than in the standard. Furthermore, the DR5:LUC reporter gene was engaged to illustrate the early LR formation event. The transgenic Arabidopsis line DR5:LUC showed an oscillatory expression pattern in oscillation zone and triggered the formation of pre-branch sites (Fig. 3a). Pre-branch site hallmarks LR founder cells and LR primordium, which subsequently develops into LRs. The DR5:LUC expression sets along the root in pH 7.5 had a 37.99% increase compared with those in the standard (Fig. 3b). Remarkably, by quantifying the DR5:LUC signal along the primary root, we also detected a stronger DR5:LUC signal in the seedling subjected to pH 7.5 than 5.8 (Fig. 3b). These results provided evidence that the LR primordium (LRP) of the plants from pH 7.5 cultivation had higher level auxin accumulation and it is consistent with the results presented above. Time-course monitoring the DR5 oscillations demonstrated shorter oscillation course in the plant of pH 7.5 cultivation and in consequence of a higher frequency, than that in the standard (Fig. 3c, d). On the other hand, the shape of LRP was not altered by different medium pH, implying that the accumulated auxin signaling in LRPs might affect the development of LR primordium (Supplemental Fig. S2). These data strongly suggest the increased pre-branch site and LR number upon slightly alkaline pH could be due to a high frequency of pre-branch site formation.

      Figure 3. 

      Expression of Luciferase, prebranch sites and signal frequency in Arabidopsis DR5:Luciferase root. (a) Expression of Luciferase, red arrows indicate prebranch sites, (b) prebranch site number and luminescence, (c), (d) position of oscillation region signal and the cycle of biological clock signals. (Means ± SD, asterisks denote significant differences between columns at * p < 0.05; ** p < 0.01, n ≥ 8). (Student t-test, Bar = 1 cm).

      PLT-restricted lateral root formation and primary root elongation is alleviated under slightly alkaline pH

    • PLETHORA (PLT)-like AP2 domain transcription factors are key regulators on both primary root elongation and LR formation in Arabidopsis. Previous research on PLT mutants showed the PLT mutant plants had shorter primary root with less LRs than wildtype (WT) (Galinha et al., 2007; Du & Scheres, 2017). Thus, plt1-4 and plt2-2 single mutants, and plt1-4plt2-2 double mutant, as well as the WT were engaged to approach the mechanism of which slightly alkaline condition promoting root development. In comparison with WT, the plt1-4 mutant and plt1-4plt2-2 double mutant, had shorter roots than WT, when plt2-2 mutant showed no visible difference (Supplemental Fig. S3a). On the other hand, in all the mutants, pH 7.5 cultivation improved root development, based on PR length and LR number. Compared with standard pH cultivation, the PR elongation was 10.41%, 12.05%, 16.84% and 127.74% raise in WT, plt1-4, plt2-2 and the double mutant, respectively; while the increase in LR number was 25.65%, 26.27%, 23.13% and 56.64% (Supplemental Fig. S3b). These data thus suggested that the activation of root growth by slightly alkaline pH might be independent from PLT signaling pathway.

      Slightly alkaline pH induced LR formation is mediated by canonical auxin signaling cascades

    • Auxin is the key regulator of LR formation and primary root elongation. The knock-out mutants of auxin receptor TIR1 or its downstream signaling cascades auxin response factor ARF7 and ARF19 severely reduces LR initiation (Du & Scheres, 2017; Cavallari et al., 2021). The results described above also showed auxin might be involved in the signal pathway regulation which led to the root phenotype. Hence, the root development test on double mutants of tir1afb2 and arf7arf19 were conducted as depicted above. As shown in Fig. 4a and b, the LR formation was substantially reduced in tir1afb2 mutant. However, the LRs were not observed in arf7arf19 mutant in pH 5.8 and 7.5. Furthermore, the LR primordium was also not detected under both conditions. This phenomenon thus implicated auxin signaling ought to be essential in the process of slightly alkaline pH promoting LR formation. On the other hand, the PR elongation of arf7arf19 and tir1afb2 mutants were still promoted by slightly alkaline pH cultivation. Accordingly, we concluded that ARF7, 19 and TIR1, AFB2 should be required for LR formation rather than PR elongation in the promotion. Hence, mutant germplasms null in auxin transport and biosynthesis were engaged in further experiments.

      Figure 4. 

      Effects of alkaline conditions on the root growth of arabidopsis mutants tir1afb2 and arf7arf19. (a) Plant growth status, (b) primary root length, lateral root number. (Means ± SD, asterisks denote significant differences compared with control condition (pH 5.8) at * p < 0.05; ** p < 0.01, n ≥ 8, n.d., not detected). (Student t-test, Bar = 1 cm ).

      Polar auxin transport is required for slightly alkaline pH induced LR branching and PR elongation

    • Our results have shown an enhanced auxin signaling in the roots of the seedlings grown under slightly alkaline pH (Fig. 1). In plants, the local auxin accumulation is facilitated by both auxin biosynthesis and polar auxin transport (PAT). Root cap-specific IBA-to-IAA conversion auxin has been suggested to contribute to the auxin accumulation in the meristem and oscillation zone to activate the establishment of pre-branch site (Xuan et al., 2015). The seedlings of ibr1ibr3ibr3 and ech2ibr1ibr3ibr3 mutants, which are defective on the conversion of IBA to IAA, exhibited less LR number and shorter PR length under pH 5.8 conditions. However, the LR number and PR length were significantly increased in ibr1ibr3ibr3 and ech2ibr1ibr3ibr3 mutants pH 7.5 condition (Supplemental Fig. S4). The results indicated that the root cap-specific auxin biosynthesis is not accounted for the slightly alkaline pH induced LR and PR development.

      In Arabidopsis, the PAT is facilitated by both auxin efflux and influx carriers, which directs the auxin flux throughout the cells. The block of PAT results in the defects of both LR formation and primary root elongation (Ďurkovič & Lux, 2010). To investigate the involvement of PAT, we first analysis the root phenotype in the presence of two potent PAT inhibitors 1-N-NaphtylPhtalamic Acid (NPA) and 2-[4-(diethylamino)-2-hydroxybenzoyl] benzoic acid (BUM) (Kim et al., 2010). NPA was reported to block the entire auxin efflux from the cell, whilst BUM specifically dampens the transport activity of ABCB transporters. In agreement with previous reports, the treatment with NPA and BUM at a concentration ranging from 0.1 uM to 1 uM, significantly reduced LR number and primary root elongation in a dose-dependent manner, whereas BUM treatment exhibited more severe inhibitory effects on root growth than NPA treatment in both slightly alkaline (7.5) and standard (5.8) pH (Fig. 5a). Noticeably, slightly alkaline pH induced LR formation which was found to be repressed by 0.3 µM BUM, while 1 µM BUM completely blocked the LR formation and primary root elongation. Similarly, NPA also reduced the slightly alkaline pH induced LR formation and primary root elongation compared to the standard. When the NPA treatment was at 0.3 µM, the pH 7.5 cultivation showed no promotion effect on PR, but remarkably the 1.0 µM NPA treatment had switched the phenomenon of which the plant had even longer primary roots in pH 5.8 than in pH 7.5 (Fig. 5b). These findings suggested that the PAT is required for slightly alkaline-induced LR formation and primary root elongation.

      Figure 5. 

      Effects of auxin transport inhibitors NPA and BUM on root growth under alkaline conditions. (a) Plant growth status, (b) primary root length, lateral root number. (Means ± SD, asterisks denote significant differences compared with control conditions (pH 5.8) at * p < 0.05; ** p < 0.01, n ≥ 8). (Student t-test, Bar = 1 cm ).

      We further analyzed the root phenotype of PAT defective mutants aux1-21, pin2pgp1pgp19, and pin2pin3pin7 (Fig. 6a). The aux1-21 mutant is defective for root auxin uptake (Jia et al., 2020), whereas pin2pgp1pgp19 and pin2pin3pin7 mutants are defective for auxin efflux (Li et al., 2021). To our surprise, the root growth of aux1-21 mutant remains sensitive to slightly alkaline pH as the PR elongation was significantly induced. However, the LR number and gravitropic root response of aux1-21 was not altered under slightly alkaline pH (Fig. 6b). Furthermore, the pin2pgp1pgp19 and pin2pin3pin7 triple mutants completely suppressed the slightly alkaline pH induced LR formation, while the enhancement of primary root elongation was fully repressed in pin2pin3pin7 mutant but partially inhibited in pin2pgp1pgp19 mutant (Fig. 6b). Meanwhile, we also observed that slightly alkaline condition could trigger the accumulation of PGP1-GFP, PGP19-GFP and PIN2-GFP signal in the root meristem. This result further implicated a transcriptional regulation of auxin efflux carrier coding genes triggered by slightly alkaline pH (Fig. 7). These data suggested that auxin efflux carriers were involved in the root development response to environmental pH.

      Figure 6. 

      Effects of alkaline conditions on the root growth of Arabidopsis mutants aux1-21, pin2pgp1pgp19, pin2pin3pin7. (a) Plant growth status, (b) primary root length, lateral root number. (Means ± SD, asterisks denote significant differences compared with control condition (pH 5.8) at * p < 0.05; ** p < 0.01, n ≥ 8). (Student t-test, Bar =1 cm ).

      Figure 7. 

      Effect of slightly alkaline conditions on polar auxin transport in Arabidopsis. (a), (b) Localization and quantifications of PGP1-GFP, PGP19-GFP and PIN2-GFP signal in the root meristem zone of light-grown Col-0 seedlings. (Means ± SD, asterisks denote significant differences compared with control condition pH 5.8, * p < 0.05; ** p < 0.01, n ≥ 8). (Student t-test, Bar = 50 μm).

      Transcriptome analysis dissected the mechanism of slightly alkaline pH promoting root development, which also indicated auxin signal pathway cascade and transporters were necessary for the procedure

    • Seedlings growing in standard pH medium were transferred into slightly alkaline conditions, and their root transcriptome dynamics were monitored at 0, 2 and 6 h later. There were 1,297 differentially expressed genes (DEGs) identified in the comparison of 0 h-VS-2 h, and 1,989 DEGs in that of 2 h-VS-6 h. KEGG enrichment analysis showed the DEGs of 0 h-VS-2 h, were mainly involved in 10 pathways as showed in Fig. 8a, and among them the pathway of plant hormone signal transduction was included. The DEGs involved in that pathway were mainly concerned with auxin. On the other hand, nitrogen metabolism, starch and sucrose metabolism were also activated, which also implied the promotion effect of pH 7.5.

      Figure 8. 

      Dynamic transcriptomic analysis on root tissue cultivated in pH 7.5 conditions. (a), (b), and the phenotype of ABC transporter gene mutants responding to (c) differing pH-value conditions. In (c), the green triangles showed the genes were DEGs of the 2h-VS-6h; the red triangles showed the mutants of which their primary root length or lateral root number did not response to pH 7.5.

      KEGG enrichment analysis showed the DEGs of 2h-VS-6h were involved mainly in five pathways, and the pathway of ABC transporters were included. There were 18 ABC transporter family protein coding genes included.

      Based on the result of the transcriptome above, all the mutants of the ABC transporter family in our germplasm collection were tested for their root phenotype in pH 5.8 and pH 7.5 cultivation. The primary root length and LR number were recorded in the same way as the experiments performed previously, the data are shown in the column chart of Fig. 8b. A total of 18 mutant germplasms were analyzed as shown in Fig. 8c and Supplemental Fig. S5. Interestingly, several of them showed reduced sensitivity to sightly alkaline conditions than WT. Mutant germplasms of abcb1, abcb2, abcb7, abcb16, and abcb20 did not show significant more LRs generated in pH 7.5 cultivation than the standard; while abcb11, abcd15 and abcb20 did not show significant longer primary roots in pH 7.5 than 5.8. Among them, the root development of abcb20 was null to pH variation. It is remarkable and worthy of note that although mutant of abcb20 block the promoting effect on the root development by slightly alkaline pH, without severe deformity as the double or triple mutants and the chemical inhibitors treatment, like sharp decrease or disappearing LR generation or loss of gravitropism.

    Conclusions

    • Soil pH is a vital environmental factor influencing plant growth and development, especially for roots. In the present research, model plant Arabidopsis were cultivated in a standardized system to test a set of continuously altered pH conditions for their corresponding plant root development behaviors. The results showed neutral to slightly alkaline (7.0−8.0) pH could promote root development, in comparison with acidic (pH ≤ 5.8) or severe akaline (pH ≥ 9.0), which is consistent with a previous study (Gujas et al., 2012). Similar phenomena have been reported in crop cultivation in soil, for instance alkaline soil cultivated sugarbeet exhibited better root development in comparison with its cultivation in acidic soil (Geng et al., 2021); Bradutigan et al. have reported that when pea plant were cultivated in soil with a high pH (pH > 9.0), root growth was inhibited compared with the plants grown in pH 7.5 soil (Brautigan et al., 2012).

      Our results revealed that slightly alkaline (7.5) pH cultivation could lead to the accumulation of auxin in the root apical meristem by affecting the auxin polar transport. In turn, it enhanced cycle gene expression and triggered the cell division activity at the meristem, leading to the promotion of PR elongation, and this procedure was independent from PLETHORA. Furthermore, the auxin signaling is accumulated in the oscillation zone. The high concentration of auxin thus induced the oscillation frequency and pre-branch site initiation, which resulted in more lateral root emergence. Thus, auxin accumulation in root apical meristem plays a key role in the molecular regulation mechanism of slightly alkaline pH promoting root development. Mutants of auxin transporter, biosynthesis as well as inhibitors were further engaged for the study, and the results showed that slightly alkaline pH promoting root development was mediated mainly by auxin transportation but not by auxin biosynthesis. PINs and ABCBs mediated auxin polar transport were essential for the accumulation of auxin in the root tip. Transcriptomic dynamic analysis showed pH 7.5 cultivation could trigger the changes in the pathways of plant hormones signal transduction and ABC transporter. The mutants of ABC transporter encoding genes were thus tested and the mutants of several ABC transporter members could partially block neutral and slightly alkaline promoting root development, when the root growth of abcb20 mutant was shown to be completely insensitive to neutral and slightly alkaline conditions. In summary, the present research showed neutral and slightly alkaline promoting Arabidopsis root development depended on auxin transportation in which the ABC transporter family were deeply involved, and ABCB20, ABCB1, ABCB2, ABCB7, ABCB11, ABCB15, ABCB16 play very important roles in the procedure.

      Acknowledgments

      • This work was supported by the Project of Sanya Yazhou Bay Science and Technology City (No. SCKJ-JYRC-2022-21), the Fundamental Research Funds for the Central Universities (KYQN2023049 and KYT2023001), National Natural Science Foundation (No. 32202585), China Postdoctoral Science Foundation (2022M721641), and International Postdoctoral Exchange Fellowship Program (YJ20210263).

      Conflict of interest

      • The authors declare that they have no conflict of interest.

      • # These authors contributed equally: Xingliang Duan, Long Luo

      Supplementary information
      • Supplemental Fig. S1 Effects of acidic conditions on plant root growth. (a) plant growth status, (b) primary root length, lateral root number, lateral root density (means ± SD, asterisks denote significant differences compared with control condition (pH 5.8) at * p < 0.05; ** p < 0.01，n ≥ 8) (Student t-test, Bar = 1 cm ).
      • Supplemental Fig. S2 Effect of slightly alkaline conditions on LRP of Arabidopsis. (a) Lateral root primordium of each stage, “×” indicate pericycle, (b) number of LRP+ LR+ emergence (means ± SD, asterisks denote significant differences between columns at * p < 0.05, ** p < 0.01, n ≥ 8) (Student t-test, Bar = 0.02 mm).
      • Supplemental Fig. S3 Effects of alkaline conditions on Arabidopsis PLT mutants root growth. (a) plant growth status, (b) primary root length, lateral root number (means ± SD, asterisks denote significant differences compared with control condition (pH 5.8) at * p < 0.05; ** p < 0.01, n ≥ 8) (Student t-test, Bar = 1 cm ).
      • Supplemental Fig. S4 Effects of alkaline conditions on the root growth of arabidopsis mutants ibr1ibr3ibr10 and ech2ibr1ibr3ibr10. (a) plant growth status, (b) primary root length, lateral root number (means ± SD, asterisks denote significant differences compared with control condition (pH 5.8) at * p < 0.05; ** p < 0.01, n ≥ 8) (Student t-test, Bar = 1 cm ).
      • Supplemental Fig. S5 The mutant seedlings of ABC transporter coding genes cultivated in pH-5.8 and -7.5 conditions.
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      • Copyright: © 2023 by the author(s). Published by Maximum Academic Press, Fayetteville, GA. This article is an open access article distributed under Creative Commons Attribution License (CC BY 4.0), visit https://creativecommons.org/licenses/by/4.0/.
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    Duan X, Luo L, Wang Z, Wang W, Ye C, et al. 2023. Promotion of root development by slightly alkaline pH involves an auxin mediated adaption mechanism. Soil Science and Environment 2:6 doi: 10.48130/SSE-2023-0006
    Duan X, Luo L, Wang Z, Wang W, Ye C, et al. 2023. Promotion of root development by slightly alkaline pH involves an auxin mediated adaption mechanism. Soil Science and Environment 2:6 doi: 10.48130/SSE-2023-0006
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  • Introduction
  • Materials and methods

  • Plant materials and growth conditions

  • Chemical preparation and treatments

  • Primary root and lateral root phenotype analyses

  • Histochemical analysis

  • Luciferase imaging and expression analysis

  • Confocal microscopy and quantification

  • RNA-seq analysis

  • Statistical analysis

  • Results and discussion

  • Promotion of root growth of Arabidopsis seedlings by neutral and slightly alkaline pH

  • Root meristem activity is triggered by slightly alkaline pH

  • Slightly alkaline pH facilitates the pre-branch site formation

  • PLT-restricted lateral root formation and primary root elongation is alleviated under slightly alkaline pH

  • Slightly alkaline pH induced LR formation is mediated by canonical auxin signaling cascades

  • Polar auxin transport is required for slightly alkaline pH induced LR branching and PR elongation

  • Transcriptome analysis dissected the mechanism of slightly alkaline pH promoting root development, which also indicated auxin signal pathway cascade and transporters were necessary for the procedure

  • Conclusions
  • Acknowledgments
  • Conflict of interest
  • Supplementary information
  • Rights and permissions
  • About this article
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