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Abstract Background The mitogen-activated protein kinase (MAPK) cascade is crucial cell signal transduction mechanism that plays an important role in plant growth and development, metabolism, and stress responses. The MAPK cascade includes three protein kinases, MAPK, MAPKK, and MAPKKK. The three protein kinases mediate signaling to downstream response molecules by sequential phosphorylation. The MAPK gene family has been identified and analyzed in many plants, however it has not been investigated in alfalfa. Results In this study, Medicago sativa MAPK genes (referred to as MsMAPKs) were identified in the tetraploid alfalfa genome. Eighty MsMAPKs were divided into four groups, with eight in group A, 21 in group B, 21 in group C and 30 in group D. Analysis of the basic structures of the MsMAPKs revealed presence of a conserved TXY motif. Groups A, B and C contained a TEY motif, while group D contained a TDY motif. RNA-seq analysis revealed tissue-specificity of two MsMAPKs and tissue-wide expression of 35 MsMAPKs. Further analysis identified MsMAPK members responsive to drought, salt, and cold stress conditions. Two MsMAPKs (MsMAPK70 and MsMAPK75) responds to salt and cold stresses; two MsMAPKs (MsMAPK60 and MsMAPK73) responds to cold and drought stresses; four MsMAPKs (MsMAPK1, MsMAPK33, MsMAPK64 and MsMAPK71) responds to salt and drought stresses; and two MsMAPKs (MsMAPK5 and MsMAPK7) responded to all three stresses. Conclusion This study comprehensively identified and analysed the alfalfa MAPK gene family. Candidate genes related to abiotic stresses were screened by analysing the RNA-seq data. The results provide key information for further analysis of alfalfa MAPK gene functions and improvement of stress tolerance.

Abstract Background Plant height (PH) is an important agronomic trait influenced by a complex genetic network. However, the genetic basis for the variation in PH in Medicago sativa remains largely unknown. In this study, a comprehensive genome-wide association analysis was performed to identify genomic regions associated with PH using a diverse panel of 220 accessions of M. sativa worldwide. Results Our study identified eight novel single nucleotide polymorphisms (SNPs) significantly associated with PH evaluated in five environments, explaining 8.59–12.27% of the phenotypic variance. Among these SNPs, the favorable genotype of chr6__31716285 had a low frequency of 16.4%. Msa0882400, located proximal to this SNP, was annotated as phosphate transporter 3;1, and its role in regulating alfalfa PH was supported by transcriptome and candidate gene association analysis. In addition, 21 candidate genes were annotated within the associated regions that are involved in various biological processes related to plant growth and development. Conclusions Our findings provide new molecular markers for marker-assisted selection in M. sativa breeding programs. Furthermore, this study enhances our understanding of the underlying genetic and molecular mechanisms governing PH variations in M. sativa.

Abstract Background Lipoxygenase (LOX) is a multifunctional enzyme that is primarily related to plant organ growth and development, biotic and abiotic stress responses, and production of flavor-associated metabolites. In higher plants, the LOX family encompasses several isozymes with varying expression patterns between tissues and developmental stages. These affect processes including seed germination, seed storage, seedling growth, fruit ripening, and leaf senescence. LOX family genes have multiple functions in response to hormones such as methyl jasmonate (MeJA) and salicylic acid. Results In this study, we identified 30 and 95 LOX homologs in Medicago truncatula and Medicago sativa, respectively. These genes were characterized with analyses of their basic physical and chemical properties, structures, chromosomal distributions, and phylogenetic relationships to understand structural variations and their physical locations. Phylogenetic analysis was conducted for members of the three LOX subfamilies (9-LOX, type I 13-LOX, and type II 13-LOX) in Arabidopsis thaliana, Glycine max, M. truncatula, and M. sativa. Analysis of predicted promoter elements revealed several relevant cis-acting elements in MtLOX and MsLOX genes, including abscisic acid (ABA) response elements (ABREs), MeJA response elements (CGTCA-motifs), and antioxidant response elements (AREs). Cis-element data combined with transcriptomic data demonstrated that LOX gene family members in these species were most likely related to abiotic stress responses, hormone responses, and plant development. Gene expression patterns were confirmed via quantitative reverse transcription PCR. Several MtLOX genes (namely MtLOX15, MtLOX16, MtLOX20, and MtLOX24) belonging to the type I 13-LOX subfamily and other LOX genes (MtLOX7, MtLOX11, MsLOX23, MsLOX87, MsLOX90, and MsLOX94) showed significantly different expression levels in the flower tissue, suggesting roles in reproductive growth. Type I 13-LOXs (MtLOX16, MtLOX20, MtLOX21, MtLOX24, MsLOX57, MsLOX84, MsLOX85, and MsLOX94) and type II 13-LOXs (MtLOX5, MtLOX6, MtLOX9, MtLOX10, MsLOX18, MsLOX23, and MsLOX30) were MeJA-inducible and were predicted to function in the jasmonic acid signaling pathway. Furthermore, exogenous MtLOX24 expression in Arabidopsis verified that MtLOX24 was involved in MeJA responses, which may be related to insect-induced abiotic stress. Conclusions We identified six and four LOX genes specifically expressed in the flowers of M. truncatula and M. sativa, respectively. Eight and seven LOX genes were induced by MeJA in M. truncatula and M. sativa, and the LOX genes identified were mainly distributed in the type I and type II 13-LOX subfamilies. MtLOX24 was up-regulated at 8 h after MeJA induction, and exogenous expression in Arabidopsis demonstrated that MtLOX24 promoted resistance to MeJA-induced stress. This study provides valuable new information regarding the evolutionary history and functions of LOX genes in the genus Medicago.

Drought is a major abiotic stress that limits the growth and yield of alfalfa, a vital forage legume. The plant metalloproteinase Filamentation temperature-sensitive H (FtsH) is an ATP- and Zn2+-dependent enzyme that plays a significant character in the plant’s response to environmental stress. However, its functional role in drought resistance remains largely unexplored. This study investigates the drought tolerance role of alfalfa MsFtsH8 by analyzing the growth, physiology, and gene expression of overexpressing plants under drought conditions. The results demonstrated that both MsFtsH8-overexpressing Arabidopsis and alfalfa plants exhibited superior growth condition and enhanced membrane stability. The overexpressing alfalfa plants also showed reduced MDA levels, higher proline content, lower H2O2 accumulation, an increased activity of antioxidant-related enzymes (SOD, POD, and CAT) activity, and an elevated expression of antioxidant-related genes. These results indicated that the overexpression of MsFtsH8 enhanced growth, improved osmotic regulation, reduced ROS levels, and increased antioxidative capacity, ultimately leading to greater drought tolerance in alfalfa. Our findings suggest that MsFtsH8 mitigates oxidative damage caused by drought by modulating the plant’s antioxidant system, thus improving drought tolerance in alfalfa. This study provides a molecular basis and candidate genes for enhancing drought resistance in alfalfa through genetic engineering.

Flowering, the transition from the vegetative to the reproductive stage, is vital for reproductive success, affecting forage quality, the yield of aboveground biomass, and seed production in alfalfa. To explore the transcriptomic profile of alfalfa flowering transition, we compared gene expression between shoot apices (SAs) at the vegetative stage and flower buds (FBs) at the reproductive stage by mRNA sequencing. A total of 3,409 DEGs were identified, and based on gene ontology (GO), 42.53% of the most enriched 15 processes were associated with plant reproduction, including growth phase transition and floral organ development. For the former category, 79.1% of DEGs showed higher expression levels in SA than FB, suggesting they were sequentially turned on and off at the two test stages. For the DEGs encoding the components of circadian rhythm, sugar metabolism, phytohormone signaling, and floral organ identity genes, 60.71% showed higher abundance in FB than SA. Among them, MsAP1, an APETALA1 (AP1) homolog of Arabidopsis thaliana, showed high expression in flower buds and co-expressed with genes related to flower organ development. Moreover, ectopic expression of MsAP1 in Arabidopsis resulted in dwarfism and early flowering under long-day conditions. The MsAP1-overexpression plant displayed morphological abnormalities including fused whorls, enlarged pistils, determinate inflorescence, and small pods. In addition, MsAP1 is localized in the nucleus and exhibits significant transcriptional activity. These findings revealed a transcriptional regulation network of alfalfa transition from juvenile phase to flowering and provided genetic evidence of the dual role of MsAP1 in flowering and floral organ development.

Lipoxygenase (LOX) is associated with responses to plant hormones, environmental stresses, and signaling substances. Methyl jasmonate (MeJA) treatment triggers the production of LOX, polyphenol oxidase, and protease inhibitors in various plants, producing resistance to herbivory. To examine the response of MtLOX24 to MeJA, the phenotypic and physiological changes in Medicago truncatula MtLOX24 overexpression and lox mutant plants were investigated. Additionally, wild-type R108, the MtLOX24-overexpressing line L4, and the mutant lox-1 were utilized as experimental materials to characterize the differentially expressed genes (DEGs) and metabolic pathways in response to MeJA. The results indicate that after treatment with 200 µM of MeJA, the damage in the mutants lox-1 and lox-2 was more serious than in the overexpressing lines L4 and L6, with more significant leaf wilting, yellowing, and oxidative damage in lox-1 and lox-2. Exogenous application of MeJA induced H2O2 production and POD activity but reduced CAT activity in the lox mutants. Transcriptome analysis revealed 10,238 DEGs in six libraries of normal-growing groups (cR108, cL4, and clox1) and MeJA-treated groups (R108, L4, and lox1). GO and KEGG functional enrichment analysis demonstrated that under normal growth conditions, the DEGs between the cL4 vs. cR108 and the clox-1 vs. cR108 groups were primarily enriched in signaling pathways such as plant–pathogen interactions, flavonoid biosynthesis, plant hormone signal transduction, the MAPK signaling pathway, and glutathione metabolism. The DEGs of the R108 vs. cR108 and L4 vs. cL4 groups after MeJA treatment were mainly enriched in glutathione metabolism, phenylpropanoid biosynthesis, the MAPK signaling pathway, circadian rhythm, and α-linolenic acid metabolism. Among them, under normal growth conditions, genes like PTI5, PR1, HSPs, PALs, CAD, CCoAOMT, and CYPs showed significant differences between L4 and the wild type, suggesting that the expression of these genes is impacted by MtLOX24 overexpression. CDPKs, CaMCMLs, IFS, JAZ, and other genes were also significantly different between L4 and the wild type upon MeJA treatment, suggesting that they might be important genes involved in JA signaling. This study provides a reference for the study of the response mechanism of MtLOX24 under MeJA signaling.

Long non-coding RNAs (lncRNAs) are pivotal regulators of the abiotic stress responses in plants, yet their specific involvement in salt/alkali stress during alfalfa germination remains incompletely understood. Here, we subjected Zhongmu No.1 alfalfa (Medicago sativa L.) seeds to salt stress (20 mM NaCl and 20 mM Na2SO4 solutions) or alkali stress (5 mM NaHCO3 and 5 mM Na2CO3 solutions) treatments for 3 days, followed by total RNA extraction and RNA-seq analysis to delineate stress-responsive alfalfa lncRNAs. We identified 17,473 novel alfalfa lncRNAs, among which 101 and 123 were differentially expressed lncRNAs (DElncRNAs) under salt and alkali stress, respectively, compared to the control. Furthermore, we predicted 16 and 237 differentially expressed target genes regulated by DElncRNAs through cis/trans-regulatory mechanisms under salt or alkali stress, respectively. A functional enrichment analysis of DElncRNA target genes indicated that lncRNAs were implicated in the fatty acid metabolism pathway under salt stress, while they played a significant role in the phenylpropanoid and flavonoid biosynthesis pathway under alkali stress. Notably, lncRNAs were found to participate in the plant hormone signal transduction pathway, a common regulatory mechanism in both salt and alkali stress responses. These findings contribute to a deeper understanding of the mechanisms underlying alfalfa’s response to salt and alkali stresses.

Earthquakes can cause serious damage to buildings, roads and other infrastructure. The large amount of dust and particulate matter generated when these structures collapse and are damaged can quickly enter the air, leading to a decline in air quality. At the same time, earthquakes may cause secondary disasters such as fires and landslides, which will also produce large amounts of soot and particulate matter, which will have a negative impact on air quality. Therefore, earthquake disaster risk assessment studies are carried out to identify potentially hazardous areas and facilities in advance in order to reduce the air pollution problems that may be caused by earthquakes. Existing research on earthquake disaster risk assessment mainly evaluates earthquake risk from the perspective of geology or seismology, but there are few studies based on multidisciplinary assessment that integrates geology, seismology, engineering and social sciences into socioeconomic factors. To this end, based on remote sensing and GIS technology, this paper takes Qinghai Province, a seismically active area, as the research area, and integrates land use data, natural environment data, social environment data and seismic parameter zoning data to construct a comprehensive assessment model for earthquake disaster vulnerability and risk. The results showed that there were 5 very high-risk areas, 7 high-risk areas, 10 medium-risk areas, 11 low-risk areas and 12 very low-risk areas in Qinghai Province. The high-risk areas are mainly distributed in the central and western parts of Qinghai Province, where the earthquake breeding environment is sufficient, the scale of active faults is huge and the adaptability of the carrier is low. The results of an earthquake disaster risk assessment can provide a reference for the government to formulate environmental protection policies. According to the assessment results, the government can formulate targeted measures to strengthen air pollution control and improve air quality.

DREB has been reported to be involved in plant growth and response to environmental factors. However, the function of DREB in growth and development has not been elucidated in alfalfa (Medicago sativa L.), a perennial tetraploid forage cultivated worldwide. In this study, an ortholog of MtDREB1C was characterized from alfalfa and named MsDREB1C accordingly. MsDREB1C was significantly induced by abiotic stress. The transcription factor MsDREB1C resided in the nucleus and had self-transactivation activity. The MsDREB1C overexpression (OE) alfalfa displayed growth retardation under both long-day and short-day conditions, which was supported by decreased MsGA20ox and upregulated MsGA2ox in the OE lines. Consistently, a decrease in active gibberellin (GA) was detected, suggesting a negative effect of MsDREB1C on GA accumulation in alfalfa. Interestingly, the forage quality of the OE lines was better than that of WT lines, with higher crude protein and lower lignin content, which was supported by an increase in the leaf–stem ratio (LSR) and repression of several lignin-synthesis genes (MsNST, MsPAL1, MsC4H, and Ms4CL). Therefore, this study revealed the effects of MsDREB1C overexpression on growth and forage quality via modifying GA accumulation and lignin synthesis, respectively. Our findings provide a valuable candidate for improving the critical agronomic traits of alfalfa, such as overwintering and feeding value of the forage.

Abstract Background Leaf size affects crop canopy morphology and photosynthetic efficiency, which can influence forage yield and quality. It is of great significance to mine the key genes controlling leaf development for breeding new alfalfa varieties. In this study, we mapped leaf length (LL), leaf width (LW), and leaf area (LA) in an F1 mapping population derived from a cultivar named ZhongmuNo.1 with larger leaf area and a landrace named Cangzhou with smaller leaf area. Results This study showed that the larger LW was more conducive to increasing LA. A total of 24 significant quantitative trait loci (QTL) associated with leaf size were identified on both the paternal and maternal linkage maps. Among them, nine QTL explained about 11.50–22.45% phenotypic variation. RNA-seq analysis identified 2,443 leaf-specific genes and 3,770 differentially expressed genes. Combining QTL mapping, RNA-seq alalysis, and qRT-PCR, we identified seven candidate genes associated with leaf development in five major QTL regions. Conclusion Our study will provide a theoretical basis for marker-assisted breeding and lay a foundation for further revealing molecular mechanism of leaf development in alfalfa.

Alfalfa (M. sativa), a perennial legume forage, is known for its high yield and good quality. As a long-day plant, it is sensitive to changes in the day length, which affects the flowering time and plant growth, and limits alfalfa yield. Photoperiod-mediated delayed flowering in alfalfa helps to extend the vegetative growth period and increase the yield. We isolated a blue-light phytohormone gene from the alfalfa genome that is an ortholog of soybean FKF1 and named it MsFKF1. Gene expression analyses showed that MsFKF1 responds to blue light and the circadian clock in alfalfa. We found that MsFKF1 regulates the flowering time through the plant circadian clock pathway by inhibiting the transcription of E1 and COL, thus suppressing FLOWERING LOCUS T a1 (FTa1) transcription. In addition, transgenic lines exhibited higher plant height and accumulated more biomass in comparison to wild-type plants. However, the increased fiber (NDF and ADF) and lignin content also led to a reduction in the digestibility of the forage. The key genes related to GA biosynthesis, GA20OX1, increased in the transgenic lines, while GA2OX1 decreased for the inactive GA transformation. These findings offer novel insights on the function of MsFKF1 in the regulation of the flowering time and plant height in cultivated M. sativa. These insights into MsFKF1’s roles in alfalfa offer potential strategies for molecular breeding aimed at optimizing flowering time and biomass yield.

Leaf size significantly impacts photosynthetic capacity and forage yield in alfalfa, a major legume forage crop. Therefore, elucidating the genetic factors governing leaf development is critical for breeding improved alfalfa varieties. In this study, a genome-wide association analysis (GWAS) was performed to dissect the genetic architecture of leaf length (LL) and leaf width (LW) using 220 alfalfa accessions phenotyped over three years. Substantial variation for both traits was observed across environments, with coefficients of variation ranging from 10.09–16.53%. GWAS identified 26 significant SNPs associated with leaf morphology spread across seven chromosomes. Each SNP accounts for 9.7–15.6% of the phenotypic variance. Haplotype analyses confirmed positive correlations between the number of superior alleles and both LL and LW. BLAST searches revealed six candidate genes involved in leaf development within 20 kb flanking regions of significant SNPs. Our results provide novel marker-trait associations and candidate loci to facilitate molecular breeding efforts to optimize leaf size and improve productivity in alfalfa. This study establishes a foundation for integrating favorable alleles into future alfalfa varieties.

Abstract Background SQUAMOSA promoter-binding protein-like (SPL) transcription factors are widely present in plants and are involved in signal transduction, the stress response and development. The SPL gene family has been characterized in several model species, such as A. thaliana and G. max. However, there is no in-depth analysis of the SPL gene family in forage, especially alfalfa (Medicago sativa L.), one of the most important forage crops worldwide. Result In total, 76 putative MsSPL genes were identified in the alfalfa genome with an uneven distribution. Based on their identity and gene structure, these MsSPLs were divided into eight phylogenetic groups. Seventy-three MsSPL gene pairs arose from segmental duplication events, and the MsSPLs on the four subgenomes of individual chromosomes displayed high collinearity with the corresponding M. truncatula genome. The prediction of the cis-elements in the promoter regions of the MsSPLs detected two copies of ABA (abscisic acid)-responsive elements (ABREs) on average, implying their potential involvement in alfalfa adaptation to adverse environments. The transcriptome sequencing of MsSPLs in roots and leaves revealed that 54 MsSPLs were expressed in both tissues. Upon salt treatment, three MsSPLs (MsSPL17, MsSPL23 and MsSPL36) were significantly regulated, and the transcription level of MsSPL36 in leaves was repressed to 46.6% of the control level. Conclusion In this study, based on sequence homology, we identified 76 SPL genes in the alfalfa. The SPLs with high identity shared similar gene structures and motifs. In total, 71.1% (54 of 76) of the MsSPLs were expressed in both roots and leaves, and the majority (74.1%) preferred underground tissues to aerial tissues. MsSPL36 in leaves was significantly repressed under salt stress. These findings provide comprehensive information regarding the SPB-box gene family for improve alfalfa tolerance to high salinity.

Alfalfa (Medicago sativa L.) is the most important legume forage crop worldwide with high nutritional value and yield. For a long time, the breeding of alfalfa was hampered by lacking reliable information on the autotetraploid genome and molecular markers linked to important agronomic traits. We herein reported the de novo assembly of the allele-aware chromosome-level genome of Zhongmu-4, a cultivar widely cultivated in China, and a comprehensive database of genomic variations based on resequencing of 220 germplasms. Approximate 2.74 Gb contigs (N50 of 2.06 Mb), accounting for 88.39% of the estimated genome, were assembled, and 2.56 Gb contigs were anchored to 32 pseudo-chromosomes. A total of 34,922 allelic genes were identified from the allele-aware genome. We observed the expansion of gene families, especially those related to the nitrogen metabolism, and the increase of repetitive elements including transposable elements, which probably resulted in the increase of Zhongmu-4 genome compared with Medicago truncatula. Population structure analysis revealed that the accessions from Asia and South America had relatively lower genetic diversity than those from Europe, suggesting that geography may influence alfalfa genetic divergence during local adaption. Genome-wide association studies identified 101 single nucleotide polymorphisms (SNPs) associated with 27 agronomic traits. Two candidate genes were predicted to be correlated with fall dormancy and salt response. We believe that the allele-aware chromosome-level genome sequence of Zhongmu-4 combined with the resequencing data of the diverse alfalfa germplasms will facilitate genetic research and genomics-assisted breeding in variety improvement of alfalfa.

Biomass yield and Feed Quality are the most important traits in alfalfa (Medicago sativa L.), which directly affect its economic value. Drought stress is one of the main limiting factors affecting alfalfa production worldwide. However, the genetic and especially the molecular mechanisms for drought tolerance in alfalfa are poorly understood. In this study, linkage mapping was performed in an F1 population by combining 12 phenotypic data (biomass yield, plant height, and 10 Feed Quality-related traits). A total of 48 significant QTLs were identified on the high-density genetic linkage maps that were constructed in our previous study. Among them, nine main QTLs, which explained more than 10% phenotypic variance, were detected for biomass yield (one), plant height (one), CP (two), ASH (one), P (two), K(one), and Mg (one). A total of 31 candidate genes were identified in the nine main QTL intervals based on the RNA-seq analysis under the drought condition. Blast-P was further performed to screen candidate genes controlling drought tolerance, and 22 functional protein candidates were finally identified. The results of the present study will be useful for improving drought tolerance of alfalfa varieties by marker-assisted selection (MAS), and provide promising candidates for further gene cloning and mechanism study.

Alfalfa (Medicago sativa) is one of the most important leguminous forages, widely planted in temperate and subtropical regions. As a homozygous tetraploid, its complex genetic background limits genetic improvement of biomass yield attributes through conventional breeding methods. Genomic selection (GS) could improve breeding efficiency by using high-density molecular markers that cover the whole genome to assess genomic breeding values. In this study, two full-sib F1 populations, consisting of 149 and 392 individual plants (P149 and P392), were constructed using parents with differences in yield traits, and the yield traits of the F1 populations were measured for several years in multiple environments. Comparisons of individual yields were greatly affected by environments, and the best linear unbiased prediction (BLUP) could accurately represent the original yield data. The two hybrid F1 populations were genotyped using GBS and RAD-seq techniques, respectively, and 47,367 and 161,170 SNP markers were identified. To develop yield prediction models for a single location and across locations, genotypic and phenotypic data from alfalfa yields in multiple environments were combined with various prediction models. The prediction accuracies of the F1 population, including 149 individuals, were 0.11 to 0.70, and those of the F1 population, consisting of 392 individuals, were 0.14 to 0.67. The BayesC and RF models had the highest average prediction accuracy of 0.60 for two F1 populations. The accuracy of the prediction models for P392 was higher than that of P149. By analyzing multiple prediction models, moderate prediction accuracies are obtained, although accuracies will likely decline across multiple locations. Our study provided evidence that GS can accelerate the improvement of alfalfa yield traits.

Uridine diphosphate glycosyltransferases (UGTs) are enzymes that catalyze glycosylation modifications and play an essential role in regulating plant metabolism. Alfalfa (Medicago sativa L.) is the most important legume in the world due to its high yields and protein content; however, the UGT genes in alfalfa have not yet been studied. Identifying UGT genes with metabolic roles in alfalfa is essential for identifying and modifying genetic traits that are relevant to yield and quality. In this study, 90 of the 239 UGT genes identified from the alfalfa “Zhongmu No. 1” genome database were found to be related to secondary metabolism, and a series of gene family characterization analyses were conducted on each. The results demonstrated that all 90 UGT genes were unevenly distributed on eight chromosomes with few introns and that tandem duplications were the crucial driving force expanding the UGT family in alfalfa. Notably, the 90 UGT genes can be clustered into ten evolutionary groups which contain specific PSPG motifs, and genes in these ten groups have specific tissue expressions. This suggests that the UGT genes in each group could have similar glycosylation roles corresponding to analogous secondary metabolites in alfalfa. Additionally, multiple cis-acting elements found in MsUGT promoter regions, such as phytohormone and flavonoids, indicate that 90 UGT members could be induced by these features, which are also related to secondary metabolism. Therefore, our study identified 90 UGT members inten evolutionary groups that are likely related to glycosylation modifications with secondary metabolites in alfalfa. These findings help uncover pivotal regulatory mechanisms associated with secondary metabolism in plant yield and quality and contribute to genetic modification and breeding in alfalfa and other plant species.

The cellulose synthase (CesA) and cellulose synthase-like (Csl) superfamily encodes critical enzymes involved in processing plant cellulose and hemicellulosic polysaccharides. The alfalfa (Medicago sativa L.) genome was sequenced in recent years, but this superfamily remains poorly understood at the genome-wide level. We identified 37 members of the CesA/Csl family from the alfalfa genome in this study as well as their chromosomal locations and synteny. We uncovered 28 CesA/Csl expressed across all tissues and CslD genes specifically expressed in the root. In addition, cis-acting element analysis showed that CesA/Csl contained several abiotic stress-related elements. Moreover, transcriptomic analysis of alfalfa seedlings demonstrated the involvement of this superfamily in responses to cold, drought, and salt stresses. Specifically, CslD increased expression in cold conditions and decreased under osmotic stress, highlighting its potential role in stress adaptation. The findings offer valuable information for the practical exploration of the functions of CesA/Csl during plant development and the development of enhanced tolerance to different stress conditions.

The transition to flowering at the right time is very important for adapting to local conditions and maximizing alfalfa yield. However, the understanding of the genetic basis of the alfalfa flowering time remains limited. There are few reliable genes or markers for selection, which hinders progress in genetic research and molecular breeding of this trait in alfalfa. We sequenced 220 alfalfa cultivars and conducted a genome-wide association study (GWAS) involving 875,023 single-nucleotide polymorphisms (SNPs). The phenotypic analysis showed that the breeding status and geographical origin strongly influenced the alfalfa flowering time. Our GWAS revealed 63 loci significantly related to the flowering time. Ninety-five candidate genes were detected at these SNP loci within 40 kb (20 kb up- and downstream). Thirty-six percent of the candidate genes are involved in development and pollen tube growth, indicating that these genes are key genetic mechanisms of alfalfa growth and development. The transcriptomic analysis showed that 1,924, 2,405, and 3,779 differentially expressed genes (DEGs) were upregulated across the three growth stages, while 1,651, 2,613, and 4,730 DEGs were downregulated across the stages. Combining the results of our GWAS and transcriptome analysis, in total, 38 candidate genes (7 differentially expressed during the bud stage, 13 differentially expressed during the initial flowering stage, and 18 differentially expressed during the full flowering stage) were identified. Two SNPs located in the upstream region of the Msa0888690 gene (which is involved in isop renoids) were significantly related to flowering. The two significant SNPs within the upstream region of Msa0888690 existed as four different haplotypes in this panel. The genes identified in this study represent a series of candidate targets for further research investigating the alfalfa flowering time and could be used for alfalfa molecular breeding.

Alfalfa (Medicago sativa L.) is a perennial forage crop known as the “Queen of Forages.” To dissect the genetic mechanism of flowering time (FT) in alfalfa, high−density linkage maps were constructed for both parents of an F1 mapping population derived from a cross between Cangzhou (P1) and ZhongmuNO.1 (P2), consisting of 150 progenies. The FT showed a transgressive segregation pattern in the mapping population. A total of 13,773 single-nucleotide polymorphism markers was obtained by using restriction-site associated DNA sequencing and distributed on 64 linkage groups, with a total length of 3,780.49 and 4,113.45 cM and an average marker interval of 0.58 and 0.59 cM for P1 and P2 parent, respectively. Quantitative trait loci (QTL) analyses were performed using the least square means of each year as well as the best linear unbiased prediction values across 4 years. Sixteen QTLs for FT were detected for P1 and 22 QTLs for P2, accounting for 1.40–16.04% of FT variation. RNA-Seq analysis at three flowering stages identified 5,039, 7,058, and 7,996 genes that were differentially expressed between two parents, respectively. Based on QTL mapping, DEGs analysis, and functional annotation, seven candidate genes associated with flowering time were finally detected. This study discovered QTLs and candidate genes for alfalfa FT, making it a useful resource for breeding studies on this essential crop.

Alfalfa (Medicago sativa L.) is the most widely grown forage legume crop worldwide. Yield and plant height are important agronomic traits influenced by genetic and environmental factors. The objective of this study was to identify quantitative trait loci (QTL) and molecular markers associated with alfalfa yield and plant height. To understand the genetic basis of these traits, a full-sib F1 population composed of 392 individuals was developed by crossing a low-yielding precocious alfalfa genotype (male parent) with a high-yielding late-maturing alfalfa cultivar (female parent). The linkage maps were constructed with 3818 single-nucleotide polymorphism (SNP) markers on 64 linkage groups. QTL for yield and plant height were mapped using phenotypic data for three years. Sixteen QTL associated with yield and plant height were identified on chromosomes 1 to 8. Six QTL explained more than 10% of phenotypic variation, representing major loci controlling yield and plant height. One locus on chromosome 1 controlling yield traits had not been identified in previous studies. Three QTL co-located with other QTL (qyield-1 and qheight-7, qheight-5 and qyield-4, qheight-6, and qyield-6). With further validation, the markers closely linked with these QTL may be used for marker-assisted selection in breeding new alfalfa varieties with high yield.

Abstract Background To explore the molecular regulatory mechanisms of early stem and leaf development, proteomic analysis was performed on leaves and stems of F genotype alfalfa, with thin stems and small leaves, and M genotype alfalfa, with thick stems and large leaves. Results Based on fold-change thresholds of > 1.20 or

Salt stress is the main abiotic factor affecting alfalfa yield and quality. However, knowledge of the genetic basis of the salt stress response in alfalfa is still limited. Here, a genome-wide association study (GWAS) involving 875,023 single-nucleotide polymorphisms (SNPs) was conducted on 220 alfalfa varieties under both normal and salt-stress conditions. Phenotypic analysis showed that breeding status and geographical origin play important roles in the alfalfa salt stress response. For germination ability under salt stress, a total of 15 significant SNPs explaining 9%–14% of the phenotypic variation were identified. For tolerance to salt stress in the seedling stage, a total of 18 significant SNPs explaining 12%–23% of the phenotypic variation were identified. Transcriptome analysis revealed 2,097 and 812 differentially expressed genes (DEGs) that were upregulated and 2,445 and 928 DEGs that were downregulated in the leaves and roots, respectively, under salt stress. Among these DEGs, many encoding transcription factors (TFs) were found, including MYB-, CBF-, NAC-, and bZIP-encoding genes. Combining the results of our GWAS analysis and transcriptome analysis, we identified a total of eight candidate genes (five candidate genes for tolerance to salt stress and three candidate genes for germination ability under salt stress). Two SNPs located within the upstream region of MsAUX28, which encodes an auxin response protein, were significantly associated with tolerance to salt stress. The two significant SNPs within the upstream region of MsAUX28 existed as three different haplotypes in this panel. Hap 1 (G/G, A/A) was under selection in the alfalfa domestication and improvement process.

Abstract Background Alfalfa (Medicago sativa L.) is an important forage crop grown worldwide. Alfalfa is called the “queen of forage crops” due to its high forage yield and nutritional characteristics. The aim of this study was to undertake quantitative trait loci (QTL) mapping of yield and yield-related traits in an F1 population of two alfalfa varieties that differ in their yield and yield-related traits. Results We constructed a high-density linkage map using single nucleotide polymorphism (SNP) markers generated by restriction-site associated DNA sequencing (RAD-seq). The linkage map contains 4346 SNP and 119 simple sequence repeat (SSR) markers, with 32 linkage groups for each parent. The average marker distances were 3.00 and 1.32 cM, with coverages of 3455 cM and 4381 cM for paternal and maternal linkage maps, respectively. Using these maps and phenotypic data, we identified a total of 21 QTL for yield and yield components, including five for yield, five for plant height, five for branch number, and six for shoot diameter. Among them, six QTL were co-located for more than one trait. Five QTL explained more than 10% of the phenotypic variation. Conclusions We used RAD-seq to construct a linkage map for alfalfa that greatly enhanced marker density compared to previous studies. This high-density linkage map of alfalfa is a useful reference for mapping yield-related traits. Identified yield-related loci could be used to validate their usefulness in developing markers for maker-assisted selection in breeding populations to improve yield potential in alfalfa.

Extremely hard-hit areas face frequent secondary geological hazards and difficulties in vegetation recovery, and subsequent effects have a significant impact on land cover changes. At present, there is a lack of research on the dynamic restoration of, and changes in, the ecological environment before and after an earthquake, and especially a lack of quantitative assessment of the impact of earthquakes on land cover at the microscopic scale of spatial distribution of landscape indices. Taking the Lushan earthquake in Sichuan Province as an example, this paper obtained land cover data from the study area between 2012 and 2020, and analyzes the spatial distribution characteristics and influencing factors of land cover change frequency by using a comprehensive land cover degree index, land cover transfer matrix and landscape ecology index. The results show that the types of cropland, forest, built-up and bare land have changed significantly in the study area. During the earthquake recovery period, the comprehensive land cover index of the study area showed an increasing trend, and land cover has been continuously improved under the effect of artificial measures and natural restoration. After 2013, patch density (PD) and landscape shape index (LSI) values decreased and aggregation index (AI) values increased for the vast majority of landscape land classes, indicating a benign ecological development across the region in the post-earthquake period. The research results are not only helpful to establish scientific ecological environmental management in the earthquake-stricken areas, but also helpful to formulate medium- and long-term ecological environmental monitoring and ecological restoration plans based on land cover change patterns.

Forage quality determined mainly by protein content and fiber composition has a crucial influence on digestibility and nutrition intake for animal feeding. To explore the genetic basis of quality traits, we conducted QTL mapping based on the phenotypic data of crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), and lignin of an F1 alfalfa population generated by crossing of two alfalfa parents with significant difference in quality. In total, 83 QTLs were identified with contribution to the phenotypic variation (PVE) ranging from 1.45 to 14.35%. Among them, 47 QTLs interacted significantly with environment and 12 QTLs were associated with more than one trait. Epistatic effect was also detected for 73 pairs of QTLs with PVE of 1.08–14.06%. The results suggested that the inheritance of quality-related traits was jointly affected by additive, epistasis and environment. In addition, 83.33% of the co-localized QTLs were shared by ADF and NDF with the same genetic direction, while the additive effect of crude protein-associated QTLs was opposite to that fiber composition on the same locus, suggesting that the loci may antagonistically contribute to protein content and fiber composition. Further analysis of a QTL related to all the three traits of fiber composition (qNDF1C, qADF1C-2, and qlignin1C-2) showed that five candidate genes were homologs of cellulose synthase-like protein A1 in Medicago truncatula, indicating the potential role in fiber synthesis. For the protein-associated loci we identified, qCP4C-1 was located in the shortest region (chr 4.3 39.3–39.4 Mb), and two of the seven corresponding genes in this region were predicted to be E3 ubiquitin-protein ligase in protein metabolism. Therefore, our results provide some reliable regions significantly associated with alfalfa quality, and identification of the key genes would facilitate marker-assisted selection for favorable alleles in breeding program of alfalfa quality improvement.

High-precision spatial mapping of paddy planting areas is very important for food security risk assessment and agricultural monitoring. Previous studies have mainly been based on multi-source satellite imagery, the fusion of Synthetic Aperture Radar (SAR) with optical data, and the combined use of multi-scale and multi-source sensors. However, there have been few studies on paddy spatial mapping using collaborative multi-source remote sensing product information, especially in tropical regions such as Southeast Asia. Therefore, based on the Google Earth Engine (GEE) platform, in this study, Cambodia, which is dominated by agriculture, was taken as the study area, and an extraction scheme for paddy planting areas was developed from collaborative multi-source information, including multi-source remote sensing images (Sentinel-1 and Sentinel-2), multi-source remote sensing land cover products (GFSAD30SEACE, GLC_FCS30-2015, FROM_GLC2015, SERVIR MEKONG, and GUF), paddy phenology information, and topographic features. Evaluation and analysis of the extraction results and the SERVIR MEKONG and ESACCI-LC paddy products revealed that the accuracy of the paddy planting areas extracted using the proposed method is the highest, with an overall accuracy of 89.90%. The results of the proposed method are better than those of the other products in terms of the outline of the paddy planting areas and the description of the road information. The results of this study provide a reference for future high-precision paddy mapping.

Rocky desertification is one of the most critical ecological and environmental problems in areas underlain by carbonate rocks globally. Land cover and land use in the region affects large-scale ecosystem processes on a global scale, and many Earth system models rely on accurate land cover information. Therefore, it is important to evaluate current global land cover products and to understand the differences between them, and the findings of these studies can provide guidance to different researchers when using or making land cover products. Whereas there are many studies on the assessment of coarser resolution land cover products, there are few studies on the assessment of higher resolution land cover products (10 m). In order to provide guidance for users of 10 m data, this paper uses the rock deserted southwest region of China as the experimental area. We analyzed the consistency and accuracy of the FROM-GLC, ESA WorldCover 10 and ESRI products using spatial pattern consistency, absolute accuracy assessment of three validation samples, and analyzed their intrinsic relationships among classification systems, classification methods, and validation samples. The results show that (1) the overall accuracy of the FROM-GLC product is the highest, ranging from 49.47 to 62.42%; followed by the overall accuracy of the ESA product, ranging from 45.13 to 64.50%; and the overall accuracy of the ESRI product is the lowest, between 39.03 and 61.94%. (2) The consistency between FROM-GLC and ESA is higher than the consistency between other products, with an area correlation coefficient of 0.94. Analysis of the spatial consistency of the three products shows that the proportion of perfectly consistent areas is low at 44.89%, mainly in areas with low surface heterogeneity and more homogeneous cover types. (3) Across the study area, the main land cover types such as forest and water bodies were the most consistent across the three product species, while the grassland, shrubland, and bareland were lower. All products showed high accuracy in homogeneous areas, with local accuracy varied in other areas, especially at high altitudes in the central and western regions. Therefore, land cover users cannot use these products directly when conducting relevant studies in rocky desertification areas, as their use may introduce serious errors.

The ecological and natural conditions in drought regions are harsh. Water shortages and land desertification are prominent features of these regions. The land cover in these regions has a large impact on global climate change, as well as on ecological protection and construction. To make rational and sustainable use of land resources, it is crucial to quickly grasp the accuracy and spatial distribution differences of multi-source remote sensing land cover products in drought regions. Therefore, taking northwestern China as the study area, in this study, the accuracy and spatial pattern distribution differences of three high-resolution (10 m) land cover products, namely, the Finer Resolution Observation and Monitoring of Global Land Cover (FROM-GLC), European Space Agency (ESA), and Environmental Systems Research Institute (ESRI) products, were compared and analyzed via area composition similarity, spatial pattern consistency, and absolute accuracy assessment for three validation samples. The results show that the FROM-GLC product had the highest overall accuracy, ranging from 53.81% to 73.45%. The ESRI product had the lowest overall accuracy, ranging from 35.90% to 64.16%. The spatial consistencies of the three products were low, accounting for 46.26% of the total area, and they were mostly distributed in a single area (mainly bare land and forest). The low accuracy for grassland, bare land, shrubland, and other vegetation types was the primary reason for the large differences between the three products. Future research should focus on improving the mapping accuracy for these vegetation types. Accuracies for water and cropland of the three products were consistent, and, thus, the FROM-GLC, ESA, and ESRI products can be used as auxiliary data in research related to water resources and cropland resources in drought regions.

Abstract Flowering time is an important agronomic trait of alfalfa (Medicago sativa L.). Managing flowering time can produce economic benefits for farmers. To understand the genetic basis of this trait, quantitative trait loci (QTL) mapping was conducted in a full‐sib population that consisted of 392 individuals segregating based on flowering time. High density linkage maps were constructed using single nucleotide polymorphism (SNP) markers generated by genotyping‐by‐sequencing (GBS). The linkage maps contained 3,818 SNP markers on 64 linkage groups in two parents. The average marker density was 4.33 cM for Parent 1 (P1) and 1.47 cM for Parent 2 (P2). Phenotypic data for flowering time was collected for three years at one location. Twenty‐eight QTLs were identified associated with flowering time. Eleven QTLs explained more than 10% of the phenotypic variation. Among them, five main effect QTLs located on linkage group (LG) 7D of P1 and five main effect QTLs located on LG 6D of P2 were identified. Three QTLs were co‐located with other QTLs. The identified linked markers to QTLs could be used for marker‐assisted selection in breeding programs to develop new alfalfa varieties to modulate flowering time.

Related to ABSCISIC ACID INSENSITIVE3 (ABI3)/VIVIPAROUS1(VP1)(RAV) transcription factors, which encode a B3 domain and an APETALA2(AP2) domain, belong to the APETALA2/ethylene-responsive element binding factor(AP2/ERF) or B3 superfamily and play an important role in regulating plant growth and development and responding to abiotic stress. Although there have been many functional studies on RAV, the functional differences between RAVs are not clear. Therefore, in this study, the functional differences of RAVs of Medicago truncatula were analyzed. Based on sequence data from the plant transcription factor database and the M. truncatula genome database, we cloned three RAV genes from M. truncatula, named MtRAV1, MtRAV2, and MtRAV3. The cis-acting elements of these genes promoters were predicted, and the expression patterns of MtRAVs under exogenous conditions (4°C, NaCl, Polyethylene Glycol, Abscisic acid) were analyzed. MtRAVs transgenic Arabidopsis thaliana were obtained and subjected to adversity treatment. Subcellular localization results indicated that MtRAVs were located in the nucleus. A much lower expression level was observed for MtRAV3 than the levels of MtRAV1 and MtRAV2 in M. truncatula for growth in normal conditions, but under 4°C or PEG and NaCl treatment, the expression level of MtRAV3 was significantly increased. Only the MtRAV3 overexpression transgenic plants showed strong cold resistance, but the overexpressed MtRAV1 and MtRAV2 transgenic plants showed no difference from wild type plants. MtRAV transgenic plants exhibited similar response to exogenous mannitol, NaCl, and ABA, and the expression of some adverse-related marker genes were up-regulated, such as COLD REGULATED 414 THYLAKOID MEMBRANE 1 (COR414-TM1), Arabidopsis thaliana drought-induced 21 (AtDI21), and Arabidopsis thaliana phosphatidylinositol-specific phospholipase C (ATPLC). MtRAVs transgenic Arabidopsis thaliana exhibited increasing of branch number. These results indicated that there was some function redundancy during MtRAVs proteins of M. truncatula, and MtRAV3 has increased function compared to the other two genes. The results of this study should provide the foundation for future application of MtRAVs in legumes.

Offshore marine aquaculture can not only provide a large amount of high-quality food for humans, but also effectively relieve the pressure on land space. However, it is difficult for traditional statistical data to reflect changes in spatial dynamics in marine aquaculture. It is also difficult to effectively manage marine space development given the current status of spatial planning regarding land–sea integration. This study used multiphase satellite remote sensing images of Shandong Province together with an automatic extraction algorithm for aquaculture to obtain spatial distribution data of marine aquaculture (surface of seawater visible by remote sensing, types of rafts, and cage aquaculture). GIS spatial overlay analysis technology was used to superimpose marine functional zoning (2010–2020) data for comparative analysis to evaluate implementation effectiveness and existing problems in marine functional zoning. Results showed that the critical time regarding substantial change in marine aquaculture area was around 2010, concurrent with the implementation of the current round of marine functional areas. The aquaculture area in the agricultural and fishery planning area increased from 228.33 km2 in 2010 to 344.6 km2 in 2018, and the overall proportion of aquaculture increased from 65.53% to 70.48%. This indicated that marine function planning can exert a guiding influence. The port area and protection area were found to be other major areas for the expansion of marine aquaculture. We also used field investigations in uncovering the phenomenon of the combined marine functions of marine aquaculture and tourism. On this basis, the role of spatial information technology in marine spatial planning was analyzed, which revealed the importance of coordinated integration of land–sea space for effective control of marine development.

Land cover changes in tropical rainforest climate zones play an important role in global climate change and the functioning of the Earth’s natural system. Existing research on the consistency of different land cover products has mainly focused on administrative divisions (continental or national scales). However, the ongoing production of large regional or global land cover products with higher resolutions requires us to have a better grasp of confusing land types and their geographical locations for different zoning (e.g., geographical zoning) in order to guide the optimization of strategies such as zoning and sample selection in automated land cover classification. Therefore, we selected the GlobeLand30-2010, GLC_FCS30-2015, and FROM_GLC2015 global land cover products with a 30-m resolution covering Indonesia, which has a tropical rainforest climate, as a case study, and then analyzed these products in terms of areal consistency, spatial consistency, and accuracy evaluation. The results revealed that (a) all three land cover products revealed that forest is the main land cover type in Indonesia. The area correlation coefficient of any two products is better than 0.89; (b) the areas that are completely consistent among the three products account for 58% of the total area of Indonesia, mainly distributed in the central and northern parts of Kalimantan and Papua, which are dominated by forest land types. The spatial consistency of the three products is low, however, due to the complex surface types and staggered distributions of grassland, shrub, cultivated land, artificial surface, and other land cover types in Java, eastern Sumatra, and the eastern, southern, and northwestern sections of Kalimantan, where the elevation is less than 200 m. Given these results, land cover producers should take heed of the classification accuracy of these areas; (c) the absolute accuracy evaluation demonstrated that the GLC_FCS30-2015 product has the highest overall accuracy (65.59%), followed by the overall accuracy of the GlobeLand30-2010 product (61.65%), while the FROM_GLC2015 exhibits the lowest overall accuracy (57.71%). The mapping accuracy of the three products is higher for forests and artificial surfaces. The cropland mapping accuracy of the GLC_FCS30-2015 product is higher than those of the other two products. The mapping accuracy of all products is low for grassland, shrubland, bareland, and wetland. The classification accuracy of these land cover types requires further improvement and cannot be used directly by land cover users when conducting relevant research in tropical rainforest climate zones, since the utilization of these products could lead to serious errors.

Comparisons of the accuracy and consistency of different remote-sensing land cover datasets are important for the rational application of multi-source land cover datasets to regional development, or to studies of global or local environmental change. Existing comparisons of accuracy or spatial consistency among land cover datasets primarily use confusion or transfer matrices and focus on the type and area consistency of land cover. However, less attention has been paid to the consistency of spatial patterns, and quantitative analyses of spatial pattern consistency are rare. However, when proportions of land cover types are similar, spatial patterns are essential for studies of the ecological functions of a landscape system. In this study, we used classical landscape indices that quantifies spatial patterns to analyze the spatial pattern consistency among different land cover datasets, and chose three datasets (GlobeLand30-2010, FROM-GLC2010, and SERVIR MEKONG2010) in northern Laos as a case study. We also analyzed spatial pattern consistency at different scales after comparing the landscape indices method with the confusion matrix method. We found that the degree of consistency between GlobeLand30-2010 and SERVIR MEKONG2010 was higher than that of GlobeLand30-2010 and FROM-GLC2010, FROM-GLC2010, and SERVIR MEKONG2010 based on the confusion matrix, mainly because of the best forest consistency and then water. However, the spatial consistency results of the landscape indices analysis show that the three datasets have large differences in the number of patches (NP), patch density (PD), and landscape shape index (LSI) at the original scale of 30 m, and decrease with the increase of the scale. Meanwhile, the aggregation index (AI) shows different changes, such as the changing trend of the forest aggregation index increasing with the scale. Our results suggested that, when using or producing land cover datasets, it is necessary not only to ensure the consistency of landscape types and areas, but also to ensure that differences among spatial patterns are minimized, especially those exacerbated by scale. Attention to these factors will avoid larger deviations and even erroneous conclusions from these data products.

Information, especially spatial distribution data, related to coastal raft aquaculture is critical to the sustainable development of marine resources and environmental protection. Commercial high spatial resolution satellite imagery can accurately locate raft aquaculture. However, this type of analysis using this expensive imagery requires a large number of images. In contrast, medium resolution satellite imagery, such as Landsat 8 images, are available at no cost, cover large areas with less data volume, and provide acceptable results. Therefore, we used Landsat 8 images to extract the presence of coastal raft aquaculture. Because the high chlorophyll concentration of coastal raft aquaculture areas cause the Normalized Difference Vegetation Index (NDVI) and the edge features to be salient for the water background, we integrated these features into the proposed method. Three sites from north to south in Eastern China were used to validate the method and compare it with our former proposed method using only object-based visually salient NDVI (OBVS-NDVI) features. The new proposed method not only maintains the true positive results of OBVS-NDVI, but also eliminates most false negative results of OBVS-NDVI. Thus, the new proposed method has potential for use in rapid monitoring of coastal raft aquaculture on a large scale.

Homogentisate solanesyltransferase (HST) plays an important role in plastoquinone (PQ) biosynthesis and acts as the electron acceptor in the carotenoids and abscisic acid (ABA) biosynthesis pathways. We isolated and identified a T-DNA insertion mutant of the HST gene that displayed the albino and dwarf phenotypes. PCR analyses and functional complementation also confirmed that the mutant phenotypes were caused by disruption of the HST gene. The mutants also had some developmental defects, including trichome development and stomata closure defects. Chloroplast development was also arrested and chlorophyll (Chl) was almost absent. Developmental defects in the chloroplasts were consistent with the SDS-PAGE result and the RNAi transgenic phenotype. Exogenous gibberellin (GA) could partially rescue the dwarf phenotype and the root development defects and exogenous ABA could rescue the stomata closure defects. Further analysis showed that ABA and GA levels were both very low in the pds2-1 mutants, which suggested that biosynthesis inhibition by GAs and ABA contributed to the pds2-1 mutants' phenotypes. An early flowering phenotype was found in pds2-1 mutants, which showed that disruption of the HST gene promoted flowering by partially regulating plant hormones. RNA-sequencing showed that disruption of the HST gene resulted in expression changes to many of the genes involved in flowering time regulation and in the biosynthesis of PQ, Chl, GAs, ABA and carotenoids. These results suggest that HST is essential for chloroplast development, hormone biosynthesis, pigment accumulation and plant development.