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2024 Volume 4
Article Contents
Abstract
Maize is a major staple crop and a model species for plant biology and genetic studies
Hundreds of genomic regions were selected during maize domestication
Domestication genes for morphological traits
Teosinte branched1 (tb1) and increased apical dominance in maize
Teosinte glume architecture 1 (tga1) and reduced glumes in maize
Grassy tillers1 (gt1) and suppression of prolificacy in maize
UPA2 and leaf angle
GLOSSY15 (Gl15) and vegetative phase change
Domestication genes related to identity and morphology of inflorescence
Domestication genes of kernel-related traits
ZmSh1 and seed shattering
Nutritional quality
Domestication genes related to disease resistance and abiotic stresses
Pre-Columbia spread of maize from tropical to temperate
Selective genes underlying agronomic trait improvement during modern maize breeding
Key genes/pathways regulating shade avoidance responses and plant architecture in maize
Complementary and differential selection of heterotic groups during modern maize breeding
Perspectives
Acknowledgments
Conflict of interest
Supplementary information
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Bioactive components and antimicrobial potential of extracts from Artemisia species and their repellent activities against Aphid (Macrosiphoniella sanborni)

  • 1.

    State Key Laboratory of Crop Genetics and Germplasm Enhancement and Utilization; Key Laboratory of Flower Biology and Germplasm Innovation, Ministry of Agriculture and Rural Affairs; Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration; College of Horticulture, Nanjing Agricultural University, Nanjing 210095, China

  • 2.

    Zhongshan Biological Breeding Laboratory, No. 50 Zhongling Street, Nanjing 210014, China

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  • Species from the Artemisia genus frequently have high resistance to pests and pathogens due to their being rich in secondary metabolites. Therefore, identifying bioactive components from Artemisia plants is essential for developing botanical pesticides and selecting parents for breeding resistant varieties of cultivated Chrysanthemum morifolium. This study investigated the resistance of four Artemisia species to aphids (Macrosiphoniella sanborni) and the antimicrobial properties of their extracts. Choice and no-choice assays showed that the tested four species had strong repellent and antifeedant effects on aphids compared with chrysanthemum. The antimicrobial activity of ethyl acetate extracts from different tissues against four pathogenic fungi was tested by disc diffusion assay. Among them, the extracts from Artemisia maximowicziana showed the strongest antimicrobial effect. The inhibition rates of Alternaria alternata, Colletotrichum siamense, and Phoma sp. caused by leaf extracts from A. maximowicziana were 53.8%, 54.95%, and 61.46%, respectively. And the inhibition increased to 75.44%, 51.65%, and 79.51%, respectively, using the stem extracts. However, the root extracts of Artemisia spp. showed only up to 25% to Fusarium solani. GC-MS analysis showed that the volatiles of Artemisia spp. were mostly abundant in terpenoids, but the components and contents were remarkably different among species. Further analysis of Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) showed the most contributed component among all potentially antimicrobial bioactive components was (−)-thujol. In this study, A. maximowicziana was identified as the material with potential value as a parent for crossbreeding, and its primary volatile compound (−)-thujol with potential resistant active is worth further investigation.

  • Maize is a major staple crop and a model species for plant biology and genetic studies

    As a major staple crop, today maize accounts for approximately 40% of total worldwide cereal production (http://faostat.fao.org/). Since its domestication ~9,000 years ago from a subgroup of teosinte (Zea mays ssp. parviglumis) in the tropical lowlands of southwest Mexico[1], its cultivating area has greatly expanded, covering most of the world[2]. Human's breeding and utilization of maize have gone through several stages, from landraces, open-pollinated varieties (OPVs), double-cross hybrids (1930s-1950s) and since the middle 1950s, single-cross hybrids. Nowadays, global maize production is mostly provided by single-cross hybrids, which exhibit higher-yielding and better stress tolerance than OPVs and double-cross hybrids[3].

    Besides its agronomic importance, maize has also been used as a model plant species for genetic studies due to its out-crossing habit, large quantities of seeds produced and the availability of diverse germplasm. The abundant mutants of maize facilitated the development of the first genetic and cytogenetic maps of plants, and made it an ideal plant species to identify regulators of developmental processes[4−6]. Although initially lagging behind other model plant species (such as Arabidopsis and rice) in multi-omics research, the recent rapid development in sequencing and transformation technologies, and various new tools (such as CRISPR technologies, double haploids etc.) are repositioning maize research at the frontiers of plant research, and surely, it will continue to reveal fundamental insights into plant biology, as well as to accelerate molecular breeding for this vitally important crop[7, 8].

    Hundreds of genomic regions were selected during maize domestication

    During domestication from teosinte to maize, a number of distinguishing morphological and physiological changes occurred, including increased apical dominance, reduced glumes, suppression of ear prolificacy, increase in kernel row number, loss of seed shattering, nutritional changes etc.[9] (Fig. 1). At the genomic level, genome-wide genetic diversity was reduced due to a population bottleneck effect, accompanied by directional selection at specific genomic regions underlying agronomically important traits. Over a century ago, Beadle initially proposed that four or five genes or blocks of genes might be responsible for much of the phenotypic changes between maize and teosinte[10,11]. Later studies by Doebley et al. used teosinte–maize F2 populations to dissect several quantitative trait loci (QTL) to the responsible genes (such as tb1 and tga1)[12,13]. On the other hand, based on analysis of single-nucleotide polymorphisms (SNPs) in 774 genes, Wright et al.[14] estimated that 2%−4% of maize genes (~800−1,700 genes genome-wide) were selected during maize domestication and subsequent improvement. Taking advantage of the next-generation sequencing (NGS) technologies, Hufford et al.[15] conducted resequencing analysis of a set of wild relatives, landraces and improved maize varieties, and identified ~500 selective genomic regions during maize domestication. In a recent study, Xu et al.[16] conducted a genome-wide survey of 982 maize inbred lines and 190 teosinte accession. They identified 394 domestication sweeps and 360 adaptation sweeps. Collectively, these studies suggest that maize domestication likely involved hundreds of genomic regions. Nevertheless, much fewer domestication genes have been functionally studied so far.

    Figure 1.  Main traits of maize involved in domestication and improvement.
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    Domestication genes for morphological traits

    Teosinte branched1 (tb1) and increased apical dominance in maize

    During maize domestication, a most profound morphological change is an increase in apical dominance, transforming a multi-branched plant architecture in teosinte to a single stalked plant (terminated by a tassel) in maize. The tillers and long branches of teosinte are terminated by tassels and bear many small ears. Similarly, the single maize stalk bears few ears and is terminated by a tassel[9,12,17]. A series of landmark studies by Doebley et al. elegantly demonstrated that tb1, which encodes a TCP transcription factor, is responsible for this transformation[18, 19]. Later studies showed that insertion of a Hopscotch transposon located ~60 kb upstream of tb1 enhances the expression of tb1 in maize, thereby repressing branch outgrowth[20, 21]. Through ChIP-seq and RNA-seq analyses, Dong et al.[22] demonstrated that tb1 acts to regulate multiple phytohormone signaling pathways (gibberellins, abscisic acid and jasmonic acid) and sugar sensing. Moreover, several other domestication loci, including teosinte glume architecture1 (tga1), prol1.1/grassy tillers1, were identified as its putative targets. Elucidating the precise regulatory mechanisms of these loci and signaling pathways will be an interesting and rewarding area of future research. Also worth noting, studies showed that tb1 and its homologous genes in Arabidopsis (Branched1 or BRC1) and rice (FINE CULM1 or FC1) play a conserved role in repressing the outgrowth of axillary branches in both dicotyledon and monocotyledon plants[23, 24].

    Teosinte glume architecture 1 (tga1) and reduced glumes in maize

    Teosinte ears possess two ranks of fruitcase-enclosed kernels, while maize produces hundreds of naked kernels on the ear[13]. tga1, which encodes a squamosa-promoter binding protein (SBP) transcription factor, underlies this transformation[25]. It has been shown that a de novo mutation occurred during maize domestication, causing a single amino acid substitution (Lys to Asn) in the TGA1 protein, altering its binding activity to its target genes, including a group of MADS-box genes that regulate glume identity[26].

    Grassy tillers1 (gt1) and suppression of prolificacy in maize

    Prolificacy, the number of ears per plants, is also a domestication trait. It has been shown that grassy tillers 1 (gt1), which encodes an HD-ZIP I transcription factor, suppresses prolificacy by promoting lateral bud dormancy and suppressing elongation of the later ear branches[27]. The expression of gt1 is induced by shading and requires the activity of tb1, suggesting that gt1 acts downstream of tb1 to mediate the suppressed branching activity in response to shade. Later studies mapped a large effect QTL for prolificacy (prol1.1) to a 2.7 kb 'causative region' upstream of the gt1gene[28]. In addition, a recent study identified a new QTL, qEN7 (for ear number on chromosome 7). Zm00001d020683, which encodes a putative INDETERMINATE DOMAIN (IDD) transcription factor, was identified as the likely candidate gene based on its expression pattern and signature of selection during maize improvement[29]. However, its functionality and regulatory relationship with tb1 and gt1 remain to be elucidated.

    UPA2 and leaf angle

    Smaller leaf angle and thus more compact plant architecture is a desired trait for modern maize varieties. Tian et al.[30] used a maize-teosinte BC2S3 population and cloned two QTLs (Upright Plant Architecture1 and 2 [UPA1 and UPA2]) that regulate leaf angle. Interestingly, the authors showed that the functional variant of UPA2 is a 2-bp InDel located 9.5 kb upstream of ZmRAVL1, which encodes a B3 domain transcription factor. The 2-bp Indel flanks the binding site of the transcription factor Drooping Leaf1 (DRL1)[31], which represses ZmRAVL1 expression through interacting with Liguleless1 (LG1), a SBP-box transcription factor essential for leaf ligule and auricle development[32]. UPA1 encodes brassinosteroid C-6 oxidase1 (brd1), a key enzyme for biosynthesis of active brassinolide (BR). The teosinte-derived allele of UPA2 binds DRL1 more strongly, leading to lower expression of ZmRAVL1 and thus, lower expression of brd1 and BR levels, and ultimately smaller leaf angle. Notably, the authors demonstrated that the teosinte-derived allele of UPA2 confers enhanced yields under high planting densities when introgressed into modern maize varieties[30, 33].

    GLOSSY15 (Gl15) and vegetative phase change

    Maize plants exhibit salient vegetative phase change, which marks the vegetative transition from the juvenile stage to the adult stage, characterized by several changes in maize leaves produced before and after the transition, such as production of leaf epicuticular wax and epidermal hairs. Previous studies reported that Glossy15 (Gl15), which encodes an AP2-like transcription factor, promotes juvenile leaf identity and suppressing adult leaf identity. Ectopic overexpression of Gl15 causes delayed vegetative phase change and flowering, while loss-of-function gl15 mutant displayed earlier vegetative phase change[34]. In another study, Gl15 was identified as a major QTL (qVT9-1) controlling the difference in the vegetative transition between maize and teosinte. Further, it was shown that a pre-existing low-frequency standing variation, SNP2154-G, was selected during domestication and likely represents the causal variation underlying differential expression of Gl15, and thus the difference in the vegetative transition between maize and teosinte[35].

    Domestication genes related to identity and morphology of inflorescence

    A number of studies documented evidence that tassels replace upper ears1 (tru1) is a key regulator of the conversion of the male terminal lateral inflorescence (tassel) in teosinte to a female terminal inflorescence (ear) in maize. tru1 encodes a BTB/POZ ankyrin repeat domain protein, and it is directly targeted by tb1, suggesting their close regulatory relationship[36]. In addition, a number of regulators of maize inflorescence morphology, were also shown as selective targets during maize domestication, including ramosa1 (ra1)[37, 38], which encodes a putative transcription factor repressing inflorescence (the ear and tassel) branching, Zea Agamous-like1 (zagl1)[39], which encodes a MADS-box transcription factor regulating flowering time and ear size, Zea floricaula leafy2 (zfl2, homologue of Arabidopsis Leafy)[40, 41], which likely regulates ear rank number, and barren inflorescence2 (bif2, ortholog of the Arabidopsis serine/threonine kinase PINOID)[42, 43], which regulates the formation of spikelet pair meristems and branch meristems on the tassel. The detailed regulatory networks of these key regulators of maize inflorescence still remain to be further elucidated.

    Domestication genes of kernel-related traits

    Kernel row number (KRN) and kernel weight are two important determinants of maize yield. A number of domestication genes modulating KRN and kernel weight have been identified and cloned, including KRN1, KRN2, KRN4 and qHKW1. KRN4 was mapped to a 3-kb regulatory region located ~60 kb downstream of Unbranched3 (UB3), which encodes a SBP transcription factor and negatively regulates KRN through imparting on multiple hormone signaling pathways (cytokinin, auxin and CLV-WUS)[44, 45]. Studies have also shown that a harbinger TE in the intergenic region and a SNP (S35) in the third exon of UB3 act in an additive fashion to regulate the expression level of UB3 and thus KRN[46].

    KRN1 encodes an AP2 transcription factor that pleiotropically affects plant height, spike density and grain size of maize[47], and is allelic to ids1/Ts6 (indeterminate spikelet 1/Tassel seed 6)[48]. Noteworthy, KRN1 is homologous to the wheat domestication gene Q, a major regulator of spike/spikelet morphology and grain threshability in wheat[49].

    KRN2 encodes a WD40 domain protein and it negatively regulates kernel row number[50]. Selection in a ~700-bp upstream region (containing the 5’UTR) of KRN2 during domestication resulted in reduced expression and thus increased kernel row number. Interestingly, its orthologous gene in rice, OsKRN2, was shown also a selected gene during rice domestication to negatively regulate secondary panicle branches and thus grain number. These observations suggest convergent selection of yield-related genes occurred during parallel domestication of cereal crops.

    qHKW1 is a major QTL for hundred-kernel weight (HKW)[51]. It encodes a CLAVATA1 (CLV1)/BARELY ANY MERISTEM (BAM)-related receptor kinase-like protein positively regulating HKW. A 8.9 Kb insertion in its promoter region was find to enhance its expression, leading to enhanced HKW[52]. In addition, Chen et al.[53] reported cloning of a major QTL for kernel morphology, qKM4.08, which encodes ZmVPS29, a retromer complex component. Sequencing and association analysis revealed that ZmVPS29 was a selective target during maize domestication. They authors also identified two significant polymorphic sites in its promoter region significantly associated with the kernel morphology. Moreover, a strong selective signature was detected in ZmSWEET4c during maize domestication. ZmSWEET4c encodes a hexose transporter protein functioning in sugar transport across the basal endosperm transfer cell layer (BETL) during seed filling[54]. The favorable alleles of these genes could serve as valuable targets for genetic improvement of maize yield.

    In a recent effort to more systematically analyze teosinte alleles that could contribute to yield potential of maize, Wang et al.[55] constructed four backcrossed maize-teosinte recombinant inbred line (RIL) populations and conducted detailed phenotyping of 26 agronomic traits under five environmental conditions. They identified 71 QTL associated with 24 plant architecture and yield related traits through inclusive composite interval mapping. Interestingly, they identified Zm00001eb352570 and Zm00001eb352580, both encode ethylene-responsive transcription factors, as two key candidate genes regulating ear height and the ratio of ear to plant height. Chen et al.[56] constructed a teosinte nested association mapping (TeoNAM) population, and performed joint-linkage mapping and GWAS analyses of 22 domestication and agronomic traits. They identified the maize homologue of PROSTRATE GROWTH1, a rice domestication gene controlling the switch from prostrate to erect growth, is also a QTL associated with tillering in teosinte and maize. Additionally, they also detected multiple QTL for days-to-anthesis (such as ZCN8 and ZmMADS69) and other traits (such as tassel branch number and tillering) that could be exploited for maize improvement. These lines of work highlight again the value of mining the vast amounts of superior alleles hidden in teosinte for future maize genetic improvement.

    ZmSh1 and seed shattering

    Loss of seed shattering was also a key trait of maize domestication, like in other cereals. shattering1 (sh1), which encodes a zinc finger and YABBY domain protein regulating seed shattering. Interesting, sh1 was demonstrated to undergo parallel domestication in several cereals, including rice, maize, sorghum, and foxtail millet[57]. Later studies showed that the foxtail millet sh1 gene represses lignin biosynthesis in the abscission layer, and that an 855-bp Harbinger transposable element insertion in sh1 causes loss of seed shattering in foxtail millet[58].

    Nutritional quality

    In addition to morphological traits, a number of physiological and nutritional related traits have also been selected during maize domestication. Based on survey of the nucleotide diversity, Whitt et al.[59] reported that six genes involved in starch metabolism (ae1, bt2, sh1, sh2, su1 and wx1) are selective targets during maize domestication. Palaisa et al.[60] reported selection of the Y1 gene (encoding a phytoene synthase) for increased nutritional value. Karn et al.[61] identified two, three, and six QTLs for starch, protein and oil respectively and showed that teosinte alleles can be exploited for the improvement of kernel composition traits in modern maize germplasm. Fan et at.[62] reported a strong selection imposed on waxy (wx) in the Chinese waxy maize population. Moreover, a recent exciting study reported the identification of a teosinte-derived allele of teosinte high protein 9 (Thp9) conferring increased protein level and nitrogen utilization efficiency (NUE). It was further shown that Thp9 encodes an asparagine synthetase 4 and that incorrect splicing of Thp9-B73 transcripts in temperate maize varieties is responsible for its diminished expression, and thus reduced NUE and protein content[63].

    Domestication genes related to disease resistance and abiotic stresses

    Teosintes is known to confer superior disease resistance and adaptation to extreme environments (such as low phosphorus and high salinity). de Lange et al. and Lennon et al.[64−66] reported the identification of teosinte-derived QTLs for resistance to gray leaf spot and southern leaf blight in maize. Mano & Omori reported that teosinte-derived QTLs could confer flooding tolerance[67]. Feng et al.[68] identified four teosinte-derived QTL that could improve resistance to Fusarium ear rot (FER) caused by Fusarium verticillioides. Recently, Wang et al.[69] reported a MYB transcription repressor of teosinte origin (ZmMM1) that confers resistance to northern leaf blight (NLB), southern corn rust (SCR) and gray leaf spot (GLS) in maize, while Zhang et al.[70] reported the identification of an elite allele of SNP947-G ZmHKT1 (encoding a sodium transporter) derived from teosinte can effectively improve salt tolerance via exporting Na+ from the above-ground plant parts. Gao et al.[71] reported that ZmSRO1d-R can regulate the balance between crop yield and drought resistance by increasing the guard cells' ROS level, and it underwent selection during maize domestication and breeding. These studies argue for the need of putting more efforts to tapping into the genetic resources hidden in the maize’s wild relatives. The so far cloned genes involved in maize domestication are summarized in Table 1. Notably, the enrichment of transcription factors in the cloned domestication genes highlights a crucial role of transcriptional re-wiring in maize domestication.

    Table 1.  Key domestication genes cloned in maize.
    GenePhenotypeFunctional annotationSelection typeCausative changeReferences
    tb1Plant architectureTCP transcription factorIncreased expression~60 kb upstream of tb1 enhancing expression[18−22]
    tga1Hardened fruitcaseSBP-domain transcription factorProtein functionA SNP in exon (K-N)[25, 26]
    gt1Plant architectureHomeodomain leucine zipperIncreased expressionprol1.1 in 2.7 kb upstream of the promoter region increasing expression[27, 28]
    Zm00001d020683Plant architectureINDETERMINATE DOMAIN transcription factorProtein functionUnknown[29]
    UPA1Leaf angleBrassinosteroid C-6 oxidase1Protein functionUnknown[30]
    UPA2Leaf angleB3 domain transcription factorIncreased expressionA 2 bp indel in 9.5 kb upstream of ZmRALV1[30]
    Gl15Vegetative phase changeAP2-like transcription factorAltered expressionSNP2154: a stop codon (G-A)[34, 35]
    tru1Plant architectureBTB/POZ ankyrin repeat proteinIncreased expressionUnknown[36]
    ra1Inflorescence architectureTranscription factorAltered expressionUnknown[37, 38]
    zflPlant architectureTranscription factorAltered expressionUnknown[40, 41]
    UB3Kernel row numberSBP-box transcription factorAltered expressionA TE in the intergenic region;[44−46]
    SNP (S35): third exon of UB3
    (A-G) increasing expression of UB3 and KRN
    KRN1/ids1/Ts6Kernel row numberAP2 Transcription factorIncreased expressionUnknown[47, 48]
    KRN2Kernel row numberWD40 domainDecreased expressionUnknown[50]
    qHKW1Kernel row weightCLV1/BAM-related receptor kinase-like proteinIncreased expression8.9 kb insertion upstream of HKW[51, 52]
    ZmVPS29Kernel morphologyA retromer complex componentProtein functionTwo SNPs (S-1830 and S-1558) in the promoter of ZmVPS29[53]
    ZmSWEET4cSeed fillingHexose transporterProtein functionUnknown[54]
    ZmSh1ShatteringA zinc finger and YABBY transcription factorProtein functionUnknown[57, 58]
    Thp9Nutrition qualityAsparagine synthetase 4 enzymeProtein functionA deletion in 10th intron of Thp9 reducing NUE and protein content[63]
    ZmMM1Biotic stressMYB Transcription repressorProtein functionUnknown[69]
    ZmHKT1Abiotic stressA sodium transporterProtein functionSNP947-G: a nonsynonymous variation increasing salt tolerance[70]
    ZmSRO1d-RDrought resistance and productionPolyADP-ribose polymerase and C-terminal RST domainProtein functionThree non-synonymous variants: SNP131 (A44G), SNP134 (V45A) and InDel433[71]
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    Pre-Columbia spread of maize from tropical to temperate

    After its domestication from its wild progenitor teosinte in southwestern Mexico in the tropics, maize has now become the mostly cultivated crop worldwide owing to its extensive range expansion and adaptation to diverse environmental conditions (such as temperature and day length). A key prerequisite for the spread of maize from tropical to temperate regions is reduced photoperiod sensitivity[72]. It was recently shown that CENTRORADIALIS 8 (ZCN8), an Flowering Locus T (FT) homologue, underlies a major quantitative trait locus (qDTA8) for flowering time[73]. Interestingly, it has been shown that step-wise cis-regulatory changes occurred in ZCN8 during maize domestication and post-domestication expansion. SNP-1245 is a target of selection during early maize domestication for latitudinal adaptation, and after its fixation, selection of InDel-2339 (most likely introgressed from Zea mays ssp. Mexicana) likely contributed to the spread of maize from tropical to temperate regions[74].

    ZCN8 interacts with the basic leucine zipper transcription factor DLF1 (Delayed flowering 1) to form the florigen activation complex (FAC) in maize. Interestingly, DFL1 was found to underlie qLB7-1, a flowering time QTL identified in a BC2S3 population of maize-teosinte. Moreover, it was shown that DLF1 directly activates ZmMADS4 and ZmMADS67 in the shoot apex to promote floral transition[75]. In addition, ZmMADS69 underlies the flowering time QTL qDTA3-2 and encodes a MADS-box transcription factor. It acts to inhibit the expression of ZmRap2.7, thereby relieving its repression on ZCN8 expression and causing earlier flowering. Population genetic analyses showed that DLF1, ZmMADS67 and ZmMADS69 are all targets of artificial selection and likely contributed to the spread of maize from the tropics to temperate zones[75, 76].

    In addition, a few genes regulating the photoperiod pathway and contributing to the acclimation of maize to higher latitudes in North America have been cloned, including Vgt1, ZmCCT (also named ZmCCT10), ZmCCT9 and ZmELF3.1. Vgt1 was shown to act as a cis-regulatory element of ZmRap2.7, and a MITE TE located ~70 kb upstream of Vgt1 was found to be significantly associated with flowering time and was a major target for selection during the expansion of maize to the temperate and high-latitude regions[77−79]. ZmCCT is another major flowering-time QTL and it encodes a CCT-domain protein homologous to rice Ghd7[80]. Its causal variation is a 5122-bp CACTA-like TE inserted ~2.5 kb upstream of ZmCCT10[72, 81]. ZmCCT9 was identified a QTL for days to anthesis (qDTA9). A Harbinger-like TE located ~57 kb upstream of ZmCCT9 showed the most significant association with DTA and thus believed to be the causal variation[82]. Notably, the CATCA-like TE of ZmCCT10 and the Harbinger-like TE of ZmCCT9 are not observed in surveyed teosinte accessions, hinting that they are de novo mutations occurred after the initial domestication of maize[72, 82]. ZmELF3.1 was shown to underlie the flowering time QTL qFT3_218. It was demonstrated that ZmELF3.1 and its homolog ZmELF3.2 can form the maize Evening Complex (EC) through physically interacting with ZmELF4.1/ZmELF4.2, and ZmLUX1/ZmLUX2. Knockout mutants of Zmelf3.1 and Zmelf3.1/3.2 double mutant presented delayed flowering under both long-day and short-day conditions. It was further shown that the maize EC promote flowering through repressing the expression of several known flowering suppressor genes (e.g., ZmCCT9, ZmCCT10, ZmCOL3, ZmPRR37a and ZmPRR73), and consequently alleviating their inhibition on several maize florigen genes (ZCN8, ZCN7 and ZCN12). Insertion of two closely linked retrotransposon elements upstream of the ZmELF3.1 coding region increases the expression of ZmELF3.1, thus promoting flowering[83]. The increase frequencies of the causal TEs in Vgt1, ZmCCT10, ZmCCT9 and ZmELF3.1 in temperate maize compared to tropical maize highlight a critical role of these genes during the spread and adaptation of maize to higher latitudinal temperate regions through promoting flowering under long-day conditions[72,81−83].

    In addition, Barnes et al.[84] recently showed that the High Phosphatidyl Choline 1 (HPC1) gene, which encodes a phospholipase A1 enzyme, contributed to the spread of the initially domesticated maize from the warm Mexican southwest to the highlands of Mexico and South America by modulating phosphatidylcholine levels. The Mexicana-derived allele harbors a polymorphism and impaired protein function, leading to accelerated flowering and better fitness in highlands.

    Besides the above characterized QTLs and genes, additional genetic elements likely also contributed to the pre-Columbia spreading of maize. Hufford et al.[85] proposed that incorporation of mexicana alleles into maize may helped the expansion of maize to the highlands of central Mexico based on detection of bi-directional gene flow between maize and Mexicana. This proposal was supported by a recent study showing evidence of introgression for over 10% of the maize genome from the mexicana genome[86]. Consistently, Calfee et al.[87] found that sequences of mexicana ancestry increases in high-elevation maize populations, supporting the notion that introgression from mexicana facilitating adaptation of maize to the highland environment. Moreover, a recent study examined the genome-wide genetic diversity of the Zea genus and showed that dozens of flowering-related genes (such as GI, BAS1 and PRR7) are associated with high-latitude adaptation[88]. These studies together demonstrate unequivocally that introgression of genes from Mexicana and selection of genes in the photoperiod pathway contributed to the spread of maize to the temperate regions.

    The so far cloned genes involved in pre-Columbia spread of maize are summarized in Fig. 2 and Table 2.

    Figure 2.  Genes involved in Pre-Columbia spread of maize to higher latitudes and the temperate regions. The production of world maize in 2020 is presented by the green bar in the map from Ritchie et al. (2023). Ritchie H, Rosado P, and Roser M. 2023. "Agricultural Production". Published online at OurWorldInData.org. Retrieved from: 'https:ourowrldindata.org/agricultural-production' [online Resource].
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    Table 2.  Flowering time related genes contributing to Pre-Columbia spread of maize.
    GeneFunctional annotationCausative changeReferences
    ZCN8Florigen proteinSNP-1245 and Indel-2339 in promoter[73, 74]
    DLF1Basic leucine zipper transcription factorUnknown[75]
    ZmMADS69MADS-box transcription factorUnknown[76]
    ZmRap2.7AP2-like transcription factorMITE TE inserted ~70 kb upstream[77−79]
    ZmCCTCCT-domain protein5122-bp CACTA-like TE inserted ~2.5 kb upstream[72,81]
    ZmCCT9CCT transcription factorA harbinger-like element at 57 kb upstream[82]
    ZmELF3.1Unknownwo retrotransposons in the promote[84]
    HPC1Phospholipase A1 enzymUnknown[83]
    ZmPRR7UnknownUnknown[88]
    ZmCOL9CO-like-transcription factorUnknown[88]
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    Selective genes underlying agronomic trait improvement during modern maize breeding

    Subsequent to domestication ~9,000 years ago, maize has been continuously subject to human selection during the post-domestication breeding process. Through re-sequencing analysis of 35 improved maize lines, 23 traditional landraces and 17 wild relatives, Hufford et al.[15] identified 484 and 695 selective sweeps during maize domestication and improvement, respectively. Moreover, they found that about a quarter (23%) of domestication sweeps (107) were also selected during improvement, indicating that a substantial portion of the domestication loci underwent continuous selection during post-domestication breeding.

    Genetic improvement of maize culminated in the development of high planting density tolerant hybrid maize to increase grain yield per unit land area[89, 90]. To investigate the key morphological traits that have been selected during modern maize breeding, we recently conducted sequencing and phenotypic analyses of 350 elite maize inbred lines widely used in the US and China over the past few decades. We identified four convergently improved morphological traits related to adapting to increased planting density, i.e., reduced leaf angle, reduced tassel branch number (TBN), reduced relative plant height (EH/PH) and accelerated flowering. Genome-wide Association Study (GWAS) identified a total of 166 loci associated with the four selected traits, and found evidence of convergent increases in allele frequency at putatively favorable alleles for the identified loci. Moreover, genome scan using the cross-population composite likelihood ratio approach (XP-CLR) identified a total of 1,888 selective sweeps during modern maize breeding in the US and China. Gene ontology analysis of the 5,356 genes encompassed in the selective sweeps revealed enrichment of genes related to biosynthesis or signaling processes of auxin and other phytohormones, and in responses to light, biotic and abiotic stresses. This study provides a valuable resource for mining genes regulating morphological and physiological traits underlying adaptation to high-density planting[91].

    In another study, Li et al.[92] identified ZmPGP1 (ABCB1 or Br2) as a selected target gene during maize domestication and genetic improvement. ZmPGP1 is involved in auxin polar transport, and has been shown to have a pleiotropic effect on plant height, stalk diameter, leaf length, leaf angle, root development and yield. Sequence and phenotypic analyses of ZmPGP1 identified SNP1473 as the most significant variant for kernel length and ear grain weight and that the SNP1473T allele is selected during both the domestication and improvement processes. Moreover, the authors identified a rare allele of ZmPGP1 carrying a 241-bp deletion in the last exon, which results in significantly reduced plant height and ear height and increased stalk diameter and erected leaves, yet no negative effect on yield[93], highlighting a potential utility in breeding high-density tolerant maize cultivars.

    Key genes/pathways regulating shade avoidance responses and plant architecture in maize

    Shade avoidance syndrome (SAS) is a set of adaptive responses triggered when plants sense a reduction in the red to far-red light (R:FR) ratio under high planting density conditions, commonly manifested by increased plant height (and thus more prone to lodging), suppressed branching, accelerated flowering and reduced resistance to pathogens and pests[94, 95]. High-density planting could also cause extended anthesis-silking interval (ASI), reduced tassel size and smaller ear, and even barrenness[96, 97]. Thus, breeding of maize cultivars of attenuated SAS is a priority for adaptation to increased planting density.

    Extensive studies have been performed in Arabidopsis to dissect the regulatory mechanism of SAS and this topic has been recently extensively reviewed[98]. We recently showed that a major signaling mechanism regulating SAS in Arabidopsis is the phytochrome-PIFs module regulates the miR156-SPL module-mediated aging pathway[99]. We proposed that in maize there might be a similar phytochrome-PIFs-miR156-SPL regulatory pathway regulating SAS and that the maize SPL genes could be exploited as valuable targets for genetic improvement of plant architecture tailored for high-density planting[100].

    In support of this, it has been shown that the ZmphyBs (ZmphyB1 and ZmphyB2), ZmphyCs (ZmphyC1 and ZmphyC2) and ZmPIFs are involved in regulating SAS in maize[101−103]. In addition, earlier studies have shown that as direct targets of miR156s, three homologous SPL transcription factors, UB2, UB3 and TSH4, regulate multiple agronomic traits including vegetative tillering, plant height, tassel branch number and kernel row number[44, 104]. Moreover, it has been shown that ZmphyBs[101, 105] and ZmPIF3.1[91], ZmPIF4.1[102] and TSH4[91] are selective targets during modern maize breeding (Table 3).

    Table 3.  Selective genes underpinning genetic improvement during modern maize breeding.
    GenePhenotypeFunctional annotationSelection typeCausative changeReferences
    ZmPIF3.1Plant heightBasic helix-loop-helix transcription factorIncreased expressionUnknown[91]
    TSH4Tassel branch numberTranscription factorAltered expressionUnknown[91]
    ZmPGP1Plant architectureATP binding cassette transporterAltered expressionA 241 bp deletion in the last exon of ZmPGP1[92, 93]
    PhyB2Light signalPhytochrome BAltered expressionA 10 bp deletion in the translation start site[101]
    ZmPIF4.1Light signalBasic helix-loop-helix transcription factorAltered expressionUnknown[102]
    ZmKOB1Grain yieldGlycotransferase-like proteinProtein functionUnknown[121]
     | Show Table
    DownLoad: CSV

    In a recent study to dissect the signaling process regulating inflorescence development in response to the shade signal, Kong et al.[106] compared the gene expression changes along the male and female inflorescence development under simulated shade treatments and normal light conditions, and identified a large set of genes that are co-regulated by developmental progression and simulated shade treatments. They found that these co-regulated genes are enriched in plant hormone signaling pathways and transcription factors. By network analyses, they found that UB2, UB3 and TSH4 act as a central regulatory node controlling maize inflorescence development in response to shade signal, and their loss-of-function mutants exhibit reduced sensitivity to simulated shade treatments. This study provides a valuable genetic source for mining and manipulating key shading-responsive genes for improved tassel and ear traits under high density planting conditions.

    Complementary and differential selection of heterotic groups during modern maize breeding

    Nowadays, global maize production is mostly provided by hybrid maize, which exhibits heterosis (or hybrid vigor) in yields and stress tolerance over open-pollinated varieties[3]. Hybrid maize breeding has gone through several stages, from the 'inbred-hybrid method' stage by Shull[107] and East[108] in the early twentieth century, to the 'double-cross hybrids' stage (1930s−1950s) by Jones[109], and then the 'single-cross hybrids' stage since the 1960s. Since its development, single-cross hybrid was quickly adopted globally due to its superior heterosis and easiness of production[3].

    Single-cross maize hybrids are produced from crossing two unrelated parental inbred lines (female × male) belonging to genetically distinct pools of germplasm, called heterotic groups. Heterotic groups allow better exploitation of heterosis, since inter-group hybrids display a higher level of heterosis than intra-group hybrids. A specific pair of female and male heterotic groups expressing pronounced heterosis is termed as a heterotic pattern[110, 111]. Initially, the parental lines were derived from a limited number of key founder inbred lines and empirically classified into different heterotic groups (such as SSS and NSS)[112]. Over time, they have expanded dramatically, accompanied by formation of new 'heterotic groups' (such as Iodent, PA and PB). Nowadays, Stiff Stalk Synthetics (SSS) and PA are generally used as FHGs (female heterotic groups), while Non Stiff Stalk (NSS), PB and Sipingtou (SPT) are generally used as the MHGs (male heterotic groups) in temperate hybrid maize breeding[113].

    With the development of molecular biology, various molecular markers, ranging from RFLPs, SSRs, and more recently high-density genome-wide SNP data have been utilized to assign newly developed inbred lines into various heterotic groups, and to guide crosses between heterotic pools to produce the most productive hybrids[114−116]. Multiple studies with molecular markers have suggested that heterotic groups have diverged genetically over time for better heterosis[117−120]. However, there has been a lack of a systematic assessment of the effect and contribution of breeding selection on phenotypic improvement and the underlying genomic changes of FHGs and MHGs for different heterotic patterns on a population scale during modern hybrid maize breeding.

    To systematically assess the phenotypic improvement and the underlying genomic changes of FHGs and MHGs during modern hybrid maize breeding, we recently conducted re-sequencing and phenotypic analyses of 21 agronomic traits for a panel of 1,604 modern elite maize lines[121]. Several interesting observations were made: (1) The MHGs experienced more intensive selection than the FMGs during the progression from era I (before the year 2000) to era II (after the year 2000). Significant changes were observed for 18 out of 21 traits in the MHGs, but only 10 of the 21 traits showed significant changes in the FHGs; (2) The MHGs and FHGs experienced both convergent and divergent selection towards different sets of agronomic traits. Both the MHGs and FHGs experienced a decrease in flowering time and an increase in yield and plant architecture related traits, but three traits potentially related to seed dehydration rate were selected in opposite direction in the MHGs and FHGs. GWAS analysis identified 4,329 genes associated with the 21 traits. Consistent with the observed convergent and divergent changes of different traits, we observed convergent increase for the frequencies of favorable alleles for the convergently selected traits in both the MHGs and FHGs, and anti-directional changes for the frequencies of favorable alleles for the oppositely selected traits. These observations highlight a critical contribution of accumulation of favorable alleles to agronomic trait improvement of the parental lines of both FHGs and MHGs during modern maize breeding.

    Moreover, FST statistics showed increased genetic differentiation between the respective MHGs and FHGs of the US_SS × US_NSS and PA × SPT heterotic patterns from era I to era II. Further, we detected significant positive correlations between the number of accumulated heterozygous superior alleles of the differentiated genes with increased grain yield per plant and better parent heterosis, supporting a role of the differentiated genes in promoting maize heterosis. Further, mutational and overexpressional studies demonstrated a role of ZmKOB1, which encodes a putative glycotransferase, in promoting grain yield[121]. While this study complemented earlier studies on maize domestication and variation maps in maize, a pitfall of this study is that variation is limited to SNP polymorphisms. Further exploitation of more variants (Indels, PAVs, CNVs etc.) in the historical maize panel will greatly deepen our understanding of the impact of artificial selection on the maize genome, and identify valuable new targets for genetic improvement of maize.

    Perspectives

    The ever-increasing worldwide population and anticipated climate deterioration pose a great challenge to global food security and call for more effective and precise breeding methods for crops. To accommodate the projected population increase in the next 30 years, it is estimated that cereal production needs to increase at least 70% by 2050 (FAO). As a staple cereal crop, breeding of maize cultivars that are not only high-yielding and with superior quality, but also resilient to environmental stresses, is essential to meet this demand. The recent advances in genome sequencing, genotyping and phenotyping technologies, generation of multi-omics data (including genomic, phenomic, epigenomic, transcriptomic, proteomic, and metabolomic data), creation of novel superior alleles by genome editing, development of more efficient double haploid technologies, integrating with machine learning and artificial intelligence are ushering the transition of maize breeding from the Breeding 3.0 stage (biological breeding) into the Breeding 4.0 stage (intelligent breeding)[122, 123]. However, several major challenges remain to be effectively tackled before such a transition could be implemented. First, most agronomic traits of maize are controlled by numerous small-effect QTL and complex genotype-environment interactions (G × E). Thus, elucidating the contribution of the abundant genetic variation in the maize population to phenotypic plasticity remains a major challenge in the post-genomic era of maize genetics and breeding. Secondly, most maize cultivars cultivated nowadays are hybrids that exhibit superior heterosis than their parental lines. Hybrid maize breeding involves the development of elite inbred lines with high general combining ability (GCA) and specific combining ability (SCA) that allows maximal exploitation of heterosis. Despite much effort to dissect the mechanisms of maize heterosis, the molecular basis of maize heterosis is still a debated topic[124−126]. Thirdly, only limited maize germplasm is amenable to genetic manipulation (genetic transformation, genome editing etc.), which significantly hinders the efficiency of genetic improvement. Development of efficient genotype-independent transformation procedure will greatly boost maize functional genomic research and breeding. Noteworthy, the Smart Corn System recently launched by Bayer is promised to revolutionize global corn production in the coming years. At the heart of the new system is short stature hybrid corn (~30%−40% shorter than traditional hybrids), which offers several advantages: sturdier stems and exceptional lodging resistance under higher planting densities (grow 20%−30% more plants per hectare), higher and more stable yield production per unit land area, easier management and application of plant protection products, better use of solar energy, water and other natural resources, and improved greenhouse gas footprint[127]. Indeed, a new age of maize green revolution is yet to come!

    Acknowledgments

    This work was supported by grants from the Key Research and Development Program of Guangdong Province (2022B0202060005), National Natural Science Foundation of China (32130077) and Hainan Yazhou Bay Seed Lab (B21HJ8101). We thank Professors Hai Wang (China Agricultural University) and Jinshun Zhong (South China Agricultural University) for valuable comments and helpful discussion on the manuscript. We apologize to authors whose excellent work could not be cited due to space limitations.

  • The authors declare that they have no conflict of interest. Haiyang Wang is an Editorial Board member of Seed Biology who was blinded from reviewing or making decisions on the manuscript. The article was subject to the journal's standard procedures, with peer-review handled independently of this Editorial Board member and his research groups.

  • Supplemental Table S1 Components in leaf, stem and root of A. keiskeana.
    Supplemental Table S2 Components in leaf, stem and root of A. viridisquama.
    Supplemental Table S3 Components in leaf, stem and root of A. maximowicziana.
    Supplemental Table S4 Components in leaf, stem and root of A. sacrorum.
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  • Cite this article

    Yang M, Li M, Chen F, Chen S. 2024. Bioactive components and antimicrobial potential of extracts from Artemisia species and their repellent activities against Aphid (Macrosiphoniella sanborni). Ornamental Plant Research 4: e025 doi: 10.48130/opr-0024-0021
    Yang M, Li M, Chen F, Chen S. 2024. Bioactive components and antimicrobial potential of extracts from Artemisia species and their repellent activities against Aphid (Macrosiphoniella sanborni). Ornamental Plant Research 4: e025 doi: 10.48130/opr-0024-0021
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Bioactive components and antimicrobial potential of extracts from Artemisia species and their repellent activities against Aphid (Macrosiphoniella sanborni)

  • 1.

    State Key Laboratory of Crop Genetics and Germplasm Enhancement and Utilization; Key Laboratory of Flower Biology and Germplasm Innovation, Ministry of Agriculture and Rural Affairs; Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration; College of Horticulture, Nanjing Agricultural University, Nanjing 210095, China

  • 2.

    Zhongshan Biological Breeding Laboratory, No. 50 Zhongling Street, Nanjing 210014, China

  • Received: 18 March 2024
  • Revised: 11 June 2024
  • Accepted: 18 June 2024
  • Published online: 02 September 2024
Ornamental Plant Research  4,  Article number: e025  (2024)  |  Cite this article

Abstract: Species from the Artemisia genus frequently have high resistance to pests and pathogens due to their being rich in secondary metabolites. Therefore, identifying bioactive components from Artemisia plants is essential for developing botanical pesticides and selecting parents for breeding resistant varieties of cultivated Chrysanthemum morifolium. This study investigated the resistance of four Artemisia species to aphids (Macrosiphoniella sanborni) and the antimicrobial properties of their extracts. Choice and no-choice assays showed that the tested four species had strong repellent and antifeedant effects on aphids compared with chrysanthemum. The antimicrobial activity of ethyl acetate extracts from different tissues against four pathogenic fungi was tested by disc diffusion assay. Among them, the extracts from Artemisia maximowicziana showed the strongest antimicrobial effect. The inhibition rates of Alternaria alternata, Colletotrichum siamense, and Phoma sp. caused by leaf extracts from A. maximowicziana were 53.8%, 54.95%, and 61.46%, respectively. And the inhibition increased to 75.44%, 51.65%, and 79.51%, respectively, using the stem extracts. However, the root extracts of Artemisia spp. showed only up to 25% to Fusarium solani. GC-MS analysis showed that the volatiles of Artemisia spp. were mostly abundant in terpenoids, but the components and contents were remarkably different among species. Further analysis of Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) showed the most contributed component among all potentially antimicrobial bioactive components was (−)-thujol. In this study, A. maximowicziana was identified as the material with potential value as a parent for crossbreeding, and its primary volatile compound (−)-thujol with potential resistant active is worth further investigation.

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    Introduction

    • The genus Artemisia, comprising small herbs and shrubs, contains over 500 species distributed worldwide[1]. As the largest genus in the family Asteraceae, many Artemisia species have been traditionally used as medicinal plants. They contain abundant secondary metabolites including volatiles, flavonoids, organic acids, and lactones, and have shown therapeutic potential for treating diseases such as malaria, hepatitis, cancer, and inflammation[2,3].

      Most Artemisia species produce intense aromas due to their volatile organic compounds (VOCs) abundance. These VOCs can effectively deter herbivores and inhibit pathogenic microbes, conferring a selective advantage on plants[3]. Numerous studies have identified the insecticidal and antimicrobial potential of essential oils and extracts from the Artemisia species[4]. The essential oil of Artemisia lavandulaefolia exhibited contact and fumigant toxicity against Plutella xylostella adults[5]. The methanol leaf extracts and essential oil of Artemisia annua significantly reduced the body weight of cotton bollworm larvae at 2% concentration and strongly inhibited the growth of Fusarium oxysporum and F. solani[6,7]. However, the bioactivity of plant volatiles depends on genotype, tissue, environment, types of pests and diseases, etc. Therefore, more Artemisia species should be identified and evaluated for their insecticidal and antimicrobial potential assay. Exploring Artemisia germplasm diversity is critical for discovering novel bioactive compounds and developing biopesticides. Furthermore, Artemisia can provide potential parents for breeding resistant varieties of closely related species such as chrysanthemum.

      Chrysanthemum (Chrysanthemum morifolium), one of the four traditionally famous flowers in China and the second most essential cut flowers globally, is of extremely high ornamental and economic value. Chrysanthemum is vulnerable to various pests and pathogens. The chrysanthemum aphid, Macrosiphoniella sanborni, is the most damaging pest, which not only hinders vegetative growth but also impacts the ornamental quality of flowers[8]. For pathogens, Alternaria alternata, Colletotrichum siamense, Phoma sp., and Fusarium solani are the primary pathogens of chrysanthemums that infect the aerial part or roots, causing chrysanthemums to wither, rot, and even die. At present, the control of these pests and diseases mainly relies on the use of chemical pesticides, which usually lead to environmental pollution, pesticide residue, and produce a negative impact on human health. As a related species of chrysanthemum, many Artemisia species are reportedly resistant to aphids and pathogens. For example, the essential oils from Artemisia monosperma strongly inhibited the mycelium growth of A. alternata and F. solani[9]. The present researchers previously found that Artemisia vulgaris, Artemisia japonica, Artemisia scoparia, and A. annua showed a strong repellent and antifeedant effect after inoculating aphids[10]. An intergeneric hybridization between aphid-susceptible Chrysanthemum 'Zhongshanjingui' (maternal parent) and A. vulgaris (paternal parent) showed much higher resistance to chrysanthemum aphid than maternal chrysanthemum[11]. Therefore, Artemisia plants have broad prospects in integrated pest and disease control and provide materials and new strategies for chrysanthemum green control and the breeding of pest or pathogen-resistant chrysanthemum cultivars.

      The four Artemisia species, including A. keiskeana, A. viridisquama, A. maximowicziana, and A. sacrorum, distributed widely in China, are traditional Chinese medicinal plants used to treat many diseases (www.iplant.cn). Current research mainly focuses on their pharmacological activities, while their biological activities against pathogens and pests of plants are rarely reported[12−16]. This study aimed to evaluate the aphid resistance and antimicrobial properties of extracts from four Artemisia species. The repellent effects against aphids (M. sanborni) were assessed using choice and no-choice experiments, compared to C. morifolium 'Jinba'. The antimicrobial activity of ethyl acetate extracts of their different tissues was compared using the disc diffusion method against four selected pathogenic microorganisms. To identify potential active components, we analyzed the extracts by gas chromatography-mass spectroscopy (GC-MS) and then evaluated them using the OPLS-DA method.

    Materials and methods

      Plant materials

    • A. keiskeana, A. viridisquama, A. maximowicziana, A. sacrorum, and C. morifolium 'Jinba' were obtained from the Chrysanthemum Germplasm Resource Preserving Center, Nanjing Agricultural University, Nanjing, China. All plants were propagated from cuttings and grown in a greenhouse at 25 ± 2 °C, 70% relative humidity, and a 16 h/8 h light/dark photoperiod. The light intensity was 100 μmol·m−2·s−1. One-month-old plants were used for the following experiments.

      Aphid performance assay on Artemisia species and C. morifolium 'Jinba'

    • Aphids reared on C. morifolium 'Jinba' at 25 ± 2 °C, 70% relative humidity, and a 16 h/8 h (light/dark) photoperiod was used. Aphid performance on Artemisia species and C. morifolium 'Jinba' were tested using a no-choice assay according to previous methods with slight modification[10]. Each assay contained 12 individual plants with three biological replications. Ten adult aphids were inoculated on the terminal bud of plants after 4 h starvation. Then, each plant was placed in a 25 cm × 12 cm polyester cylinder capped with gauze. Total aphid numbers were counted every other day.

      Aphid olfactory bioassay

    • Aphid olfactory responses were measured using a Y-tube olfactometer (25 cm × 15 cm × 15 cm, 1 cm diam, 75° angle) based on previous methods with slight modification[17]. The arms were connected by Teflon tubes to chambers containing the odor sources. Charcoal-filtered air was pumped through each chamber at a velocity of 100 mL·min−1. Adult aphids starved for 4 h were placed at one end of the Y-tube. The aphids that moved into one of the arms up to 3 cm and stayed over the 30 s were recorded as making an effective choice, and those that did not choose within 5 min were deemed as 'no choice'. Each assay contains ten individual aphids with four biological replications. The Y-tube was rotated 180° to change the odor source every 5 min. The olfactometer tube was washed with 70% ethanol and dried at 100 °C for 5 min.

      Volatiles collection and analysis

    • The second to fourth leaves from the plant apex, stems, and roots were harvested for volatile extraction. 200 mg of tissue was ground in liquid nitrogen and extracted with 1 mL ethyl acetate containing 0.002% (w/v) nonyl acetate as an internal standard. The extraction was performed under shaking at 200 rpm for 1 h at room temperature. After centrifugation at 12,000 rpm for 15 min, the supernatant of extracts was collected and stored at −80 °C for further analysis and the antimicrobial assay in vitro.

      The extracts were analyzed by GC-MS (Agilent 9000 B-7000D) and equipped with an HP-5 MS capillary column (30 m × 0.25 mm × 0.25 μm film thickness). The GC procedure was set as follows: 1 μl of each sample was injected at 250 °C with 5:1 split mode. The oven temperature was increased at 5 °C·min−1 from 40 to 80 °C and held for 2 min, then increased to 160 °C at 5 °C·min−1 and held for 2 min, followed by increasing to 250 °C at 10 °C·min−1. The flow rate of helium carrier gas was set at 1 mL·min−1. All MS data was collected from 40 to 400 m/z.

      The extracts' components were identified by matching retention time and mass spectra to libraries (National Institute of Standards and Technology, NIST-2008). The content of each component was calculated using the internal standard method. The calculation formula is as follows: the content of each component (μg·g−1 FW) = [(peak area of each constituent × content of internal standard)/peak area of internal standard]/sample fresh weight, where FW represents fresh weight.

      Antimicrobial properties of the extracts from Artemisia plants

    • Four frequently occurring pathogenic microorganisms were employed, including A. alternata, C. siamense, Phoma sp., and F. solani, isolated from infected chrysanthemums. The in vitro antimicrobial activity of ethyl acetate extracts was evaluated by the agar diffusion method. Fungal plates cultured for five days were selected. Then, an agar mycelium block with a diameter of 0.6 cm was placed in the center of the potato agar medium with evenly spread 200 μL of extracts. 200 μL of ethyl acetate was used as the negative control. The plates were incubated at 28 °C for 4 d. The colony diameter of the fungi was measured with a caliper and photographed. Each treatment was repeated five times.

      Antimicrobial activity was evaluated by calculating the inhibition percentage of colony diameter compared to the negative control as follows: Inhibition rate (IR) = (M − T)/M × 100, where M = diameter of negative control colonies and T = diameter of test colonies.

      Statistical analysis

    • SPSS v 20.0 was used for all statistical analyses. Data were expressed as mean ± standard deviation (SD). Duncan's multiple range test (p < 0.05) and one-way analysis of variance were performed to determine the significance of the data. Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) was conducted using SIMCA 14.1. GraphPad Prism 10 was used to cluster heat map analysis.

    Results

      Aphid performance on Artemisia species and C. morifolium 'Jinba'

    • Aphid populations were monitored every other day for 7 d following the inoculation of ten adults onto each plant. Aphid populations on Artemisia spp. gradually decreased, reaching almost zero on the 7th day. However, the number of aphids on C. morifolium 'Jinba' gradually increased, reaching about 5.9 times on the 7th day (Table 1; Fig. 1). The results suggest that the tested Artemisia spp. exhibited apparent antifeedant effects on aphids compared to C. morifolium 'Jinba'.

      Table 1.  Identification of resistance of Artemisia species to aphids.

      Plants No. of aphids at different days after inoculation Multiplication rate
      1 d 3 d 5 d 7 d
      C. morifolium 'Jinba' 10.0 ± 0.00c 15.9 ± 2.15d 31.7 ± 5.43e 59.1 ± 7.29f 5.9 ± 0.73
      A. keiskeana 10.0 ± 0.00c 2.6 ± 1.51b 0.6 ± 0.79a 0.0 ± 0.00a 0.00 ± 0.00
      A. viridisquama 10.0 ± 0.00c 3.5 ± 1.73 b 0.4 ± 0.67a 0.0 ± 0.00a 0.00 ± 0.00
      A. maximowicziana 10.0 ± 0.00c 3.3 ± 1.95 b 0.2 ± 0.63a 0.0 ± 0.00a 0.00 ± 0.00
      A. sacrorum 10.0 ± 0.00c 2.7 ± 0.98b 0.1 ± 0.29a 0.0 ± 0.00a 0.00 ± 0.00
      Values (given as mean ± SD) labelled with different letters represent significant differences (p < 0.01).

      Figure 1. 

      Aphid density on C. morifolium 'jinba' and four Artemisia species at 5 d after aphid inoculation.

      Y-tube olfactometer bioassay

    • To determine the repellent effects of Artemisia spp. volatiles on aphids, dual-choice assays were performed using a Y-tube olfactometer. Each Artemisia species coupled with C. morifolium 'Jinba' as a pair of odor sources in the assay. Compared to C. morifolium 'Jinba', all tested Artemisia species elicited obvious avoidance responses to aphids (Fig. 2). In particular, A. sacrorum has the strongest repellent effect on aphids, followed by A. viridisquama.

      Figure 2. 

      Choices of aphid to Artemisia species and C. morifolium 'Jinba' in the Y-tube olfactometer. The asterisks with the choice bars indicate significant preference. **p < 0.01.

      Antimicrobial activity

      Antifungal effect of leaf and stem extracts on Alternaria alternata, Colletotrichum siamense and Phoma sp.

    • A. alternata, C. siamense, and Phoma sp. commonly infect aerial tissues including the leaf and stem of chrysanthemum. Therefore, to track antifungal agents of aerial tissues of Artemisia spp., leaf and stem extracts were prepared and tested for antifungal activity against the three fungi.

      For inhibition activity assay of the extracts on A. alternata, leaf extracts of A. keiskeana and stem extracts of A. keiskeana, A. viridisquama, and A. maximowicziana strongly inhibited the growth of A. alternata with inhibition rates of 71.35%, 71.93%, 74.85%, and 75.44%, respectively. In comparison, A. sacrorum showed the weakest inhibition, with rates of 29.24% (Table 2; Fig. 3a).

      Table 2.  Inhibitory effect of volatiles from leaves and stems of four kinds of Artemisia on the growth of A. alternata, C. siamense, and Phoma sp.

      Plants Tissue Inhibition rate (IR)
      A. alternata C. siamense Phoma sp.
      A. keiskeana L 71.35 ± 1.17 57.14 ± 6.08 40.00 ± 2.40
      S 71.93 ± 1.50 35.71 ± 3.02 19.51 ± 3.72
      A. viridisquama L 33.00 ± 6.43 25.82 ± 1.92 12.20 ± 2.18
      S 74.85 ± 3.31 42.86 ± 6.87 20.00 ± 1.86
      A. maximowicziana L 53.80 ± 3.80 54.95 ± 2.91 61.46 ± 2.84
      S 75.44 ± 3.31 51.65 ± 7.14 79.51 ± 2.56
      A. sacrorum L 29.24 ± 3.80 19.78 ± 7.93 13.66 ± 3.28
      S 29.24 ± 2.34 38.00 ± 4.12 15.12 ± 1.86
      Values were given as mean ± SD. L, leaf; S, stem.

      Figure 3. 

      Inhibitory effect of different tissue extracts from four Artemisia plants on mycelia growth. (a), (b) and (c) colony diameter (cm) of A. alternata, C. siamense, and Phoma sp. after treatment with leaf and stem extracts for 4 d, respectively; (d) growth (cm) of F. solani after treatment with root extracts for 4 d. Different letters represent significant differences (p < 0.05).

      For inhibition activity assay of the extracts on C. siamense, the best inhibitory activity against C. siamense was found in leaf extracts of A. keiskeana and leaf and stem extracts of A. maximowicziana (57.14%, 54.95%, and 51.65%, respectively), followed by stem extracts of A. viridisquama, A. sacrorum, and A. keiskeana, with inhibitory rates of 42.86%, 38%, and 35.71%, respectively (Table 2; Fig. 3b).

      For inhibition activity assay of the extracts on Phoma sp., leaf and stem extracts of A. maximowicziana showed superior inhibition, and the inhibitory rate was 61.46% and 79.51%, respectively. Stem extracts of A. keiskeana showed moderate inhibition with an inhibition rate of 40%. The rest had slight inhibition on Phoma sp. with rates below 20% (Table 2; Fig. 3c).

      Antifungal effect of root extracts from Artemisia species on Fusarium solani

    • F. solani is the primary pathogen causing chrysanthemum root rot[18,19]. The antimicrobial activity of root volatiles of Artemisia spp. was tested against the mycelial growth of F. solani. The result indicated that these root extracts showed an inhibitory effect. Among them, the inhibitory activity of root extracts from A. keiskeana, A. viridisquama, A. maximowicziana, and A. sacrorum was 23.04%, 24.88%, 16.59% and 17.05%, respectively (Table 3; Fig. 3d).

      Table 3.  Inhibitory effect of volatiles from roots of four kinds of Artemisia on the growth of F. solani.

      Plants Tissue Inhibition rate (IR)
      A. keiskeana R 23.04 ± 4.84
      A. viridisquama R 24.88 ± 7.14
      A. maximowicziana R 16.59 ± 2.99
      A. sacrorum R 17.05 ± 3.68
      Values were given as mean ± SD. R, root.

      Analysis of volatile compounds

    • To further investigate the potential bioactive components that confer resistance against aphids and pathogens, root, leaf, and stem extracts from Artemisia spp. were analyzed by GC-MS. Constituents were identified by matching mass spectra to the NIST library. Volatile content was quantified relative to an internal standard (Supplemental Tables S1−S4).

      Nineteen compounds were identified in A. keiskeana (Supplemental Table S1). (−)-Alpha-pinene and camphene occurred across all tissues, with the highest levels in leaves followed by that in stems. The major leaf volatiles were (+)-2-bornanone (126.3 μg·g−1 FW), caryophyllene (135.6 μg·g−1 FW), and phytyl acetate (205.6 μg·g−1 FW). (−)-Beta-elemene (109.2 μg·g−1 FW) and aromadendrene (101.4 μg·g−1 FW) predominated in the roots (Supplemental Table S1).

      Fifteen volatiles were found in A. viridisquama (Supplemental Table S2). Phytyl acetate (221.0 μg·g−1 FW), eucalyptol (47.1 μg·g−1 FW) and neophytadiene (67.1 μg·g−1 FW) were most abundant.

      Twenty-five compounds were detected in A. maximowicziana, including six bioactive oxidized monoterpenes like (E)-thujone and (−)-thujol (Supplemental Table S3). (E)-thujone and (−)-thujol were the main components in leaf and stem extracts, the content of which in leaves was up to 174.4 μg·g−1 FW and 498.7 μg·g−1 FW, respectively.

      A. sacrorum contained 26 volatile compounds (Supplemental Table S4), dominated by monoterpenes, sesquiterpenes, and diterpenes. (+)-2-Bornanone (193.3 μg·g−1 FW) and (−)-zingiberene (131.2 μg·g−1 FW) predominated in leaves.

      Overall, 43 volatiles were detected across all Artemisia species (Fig. 4), and terpenoids were the predominant volatiles across all species and tissues. Camphene, gamma-elemene, phytyl acetate, and caryophyllene occurred in all species. Especially certain oxygenated monoterpenes (cis-4-thujanol, (E)-thujone, (−)-thujol, etc.) were unique to A. maximowicziana. Some sesquiterpenes, like (−)-beta-elemene, are only found in the root extracts of A. keiskeana. However, which components of these extracts played a vital role in the antifungal activity remains to be further analyzed.

      Figure 4. 

      Main components (above 1% of total volatiles present in chromatograms) of ethyl acetate extracts from the leaf, stem and root of four Artemisia species. Colors reflect the VOC's average relative content, n = 3. MT: monoterpenes; OMT: oxygenated monoterpenes; ST: sesquiterpenes; OST: oxygenated sesquiterpenes; SL: sesquiterpene lactones; DT: diterpenes; ODT: oxygenated diterpenes.

      Screening of key bioactive components of extracts with antifungal effect

    • The contribution of each volatile compound of extracts to antimicrobial activity was assessed by Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) based on the variable's importance in the project (VIP). VIP values were used to describe the overall contribution of each variable to the model. VIP ≥ 1 commonly used as the screening criterion showed that the variable has a significant influence on the model. Among the 35 components in stem and leaf extracts from four Artemisia species, 12 compounds including (−)-thujol, (+)-2-bornanone, phytyl acetate, (−)-zingiberene, (E)-thujone, unknown (unidentified compound), germacrene D, caryophyllene, endo-borneol, beta-ylangene, dihydrocolumellarin and neophytadiene, the VIP values of which were greater than 1, inhibited the growth of A. alternata hypha (Fig. 5a). Ten components-(−)-thujol, (E)-thujone, phytyl acetate, (+)-2-bornanone, endo-borneol, unknow (unidentified compound), germacrene D, caryophyllene, (−)-zingiberene and beta-ylangene contributed to the inhibition of C. siamense mycelial growth (Fig. 5b). For Phoma sp., the mycelial growth was inhibited by 12 key active compounds including (−)-thujol, phytyl acetate, (+)-2-bornanone, caryophyllene, (E)-thujone, (−)-zingiberene, germacrene D, neophytadiene, unknown (unidentified compound), endo-borneol, phytol, and beta-ylangene (Fig. 5c). The primary antifungal agents in the extracts varied among different pathogens, with (−)-thujol exhibiting the most potent influence. Regarding soil-borne pathogenic fungi F. solani, (−)-beta-elemene, aromandendrene, cis-beta-farnesene, 1R,4S,7S,11R-2,2,4,8-tetrame, santolina triene, modephene and caryophyllene from root extracts were effective constituents that could inhibit the growth of the hypha of F. solani, of which (−)-beta-elemene showed the greatest inhibitory effect on F. solani (Fig. 5d).

      Figure 5. 

      Screening of key bioactive components of extracts with antifungal effect against (a) A. alternata, (b) C. siamense, (c) Phoma sp. and (d) F. solani by OPLS-DA. VIP ≥ 1 was used as the screening criterion.

    Discussion

    • Artemisia species are of great value due to their abundant bioactive compounds with pharmaceutical and pesticide applications. They also serve as parent materials for intergeneric hybrids with crops like chrysanthemum. Here, the aphid (M. sanborni) resistance of four Artemisia species and the antimicrobial properties of their extracts were investigated, to screen out excellent germplasm materials and active compounds.

      Plant volatiles defend against aphids in direct and indirect ways, the former usually by direct contact or fumigation to repel and keep them from feeding, and even be toxic[20,21]. The essential oils of Artemisia monosperma were the most potent toxicants to Aphis nerii, displaying an LC50 value of 0.06 mg·L−1[22]. Sesquiterpenes from Solanum habrochaites have been verified to not only have a direct avoidance or anti-feeding effect on potato aphids but also affect their longevity and fecundity[23,24]. In this study, the four Artemisia species tested contained abundant bioactive terpenoids like caryophyllene, beta-farnesene, beta-bergamotene, beta-bisabolene, cis-4-thujanol, etc., known to deter aphids[23,25,26], likely contributing to the observed antifeeding and repellent effects. It suggests that all four Artemisia species are promising aphid-resistant germplasm with prospective bioactive volatiles.

      The antifungal activity of Artemisia extracts depends on the extraction solvent, plant part, and pathogen species. Antifungal effects of A. annua leaf methanol extracts on F. oxysporum and F. solani increased with concentration, whereas root and stem extracts showed no inhibition[7]. Artemisia proceriformis oil more strongly inhibited Septoria glycines and Septoria tritici (MIC100 = 2.7 mg·mL−1) versus Fusarium graminearum and Fusarium verticillioides (MIC100 = 10.6 mg·mL−1)[27]. Here, differences in the antifungal activity of Artemisia extracts were also found. A. keiskeana leaf and stem extracts inhibited A. alternata over 70% but had minimal effects on Phoma sp. (Table 2). The inhibitory effect of stem extract from A. viridisquama on A. alternata was significantly higher than that of leaf extract. Moreover, we also noticed that A. maximowicziana extracts strongly inhibited all three aerial pathogens by over 50%. Thus, it represents a promising broad-spectrum botanical fungicide candidate.

      GC-MS profiling of volatiles revealed that, as expected, terpenoids dominated the volatile profile, aligning with findings in other Artemisia species[1]. It mainly consisted of 1, 8-cineole, beta-pinene, thujone, artemisia ketone, camphor, caryophyllene, camphene, and germacrene D[4]. However, there were great differences in main compounds with some special species. For example, A. maximowicziana studied in this paper, whose major component was (−)-thujol, contained about three times as much as (E)-thujone. In addition, phytyl acetate, which was not mentioned in the previously reported Artemisia, was found to have a high content in all four tested Artemisia species.

      Different pests and pathogens have different susceptibility to varied active compounds. The essential oil and extracts of Artemisia absinthium have demonstrated anti-settling, antifeedant and antimicrobial activity against various pests and pathogens such as Myzus persicae, Spodoptera littoralis, Tetranychus cinnabarinus, Diaphorina citri, Fusarium spp. and Botrytis cinerea[28−31]. Specifically, (−)-cis-chrysanthenol and linalool have been identified as the primary antifungal agents of extracts against Fusarium spp. and B. cinerea[29], while carvacrol, (−)-α-bisabolol and chamazulene were toxic constituents of volatile oils against D. citri[29,31]. In this study, the antifungal effects of (−)-thujol were potentially broad spectrum. For root pathogens, L-camphor, DL-camphor, β-caryophyllene, and camphene were reported to have antifungal efficacy against F. oxysporum and F. solani comparable to the synthetic fungicides flutriafol, and hymexazol[7]. Here, however, the VIP value of camphene was less than 1; probably, its content in the root was too low to be effective for the resistance. Based on previous reports and our findings, the four Artemisia plants contained 15 bioactive constituents-(−)-thujol, (+)-2-bornanone, phytyl acetate, (−)-zingiberene, (E)-thujone, unknown (unidentified compound), germacrene D, caryophyllene, endo-borneol and beta-ylangene, camphene, cis-beta-farnesene, beta-bergamotene, beta-bisabolene, cis-4-thujanol—may mediate the antifungal and anti-insect effects. However, the active ingredients individually and in combinations against aphids and the tested pathogens should be further studied.

    Conclusions

    • In conclusion, the four Artemisia species tested showed certain repellent and antifeedant effects on aphids, and antifungal effects on A. alternata, C. siamense, Phoma sp., and F. solani. Their volatile extracts contain multiple bioactive compounds with the potential to be biofungicides. These findings provide a material and theoretical basis for developing new biopesticides and breeding of pest- and disease-resistant chrysanthemum cultivars.

    Author contributions

    • The authors confirm contribution to the paper as follows: study conception and design: Chen S, Chen F; data collection: Yang M, Li M; analysis and interpretation of results: Yang M, Li M; draft manuscript preparation: Yang M. All authors reviewed the results and approved the final version of the manuscript.

    Data availability

    • All data generated or analyzed during this study are included in this published article and its supplementary information files.

      Acknowledgments

      • This work was supported by the National Natural Science Foundation of China (32372749), Hainan Provincial Natural Science Foundation of China (323CXTD386), the Program for Key Research and Development, Jiangsu, China (BE2023367, BE2022417), A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions, PAPD. We thank Dr. Yuehua Ma (Central Laboratory of College of Horticulture, Nanjing Agricultural University) for assistance in using GC-MS (Agilent 9000 B-7000D).

      Conflict of interest

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

      Supplementary information
      Rights and permissions
      • Copyright: © 2024 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/.
    Figure (5)  Table (3) References (31)
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    Yang M, Li M, Chen F, Chen S. 2024. Bioactive components and antimicrobial potential of extracts from Artemisia species and their repellent activities against Aphid (Macrosiphoniella sanborni). Ornamental Plant Research 4: e025 doi: 10.48130/opr-0024-0021
    Yang M, Li M, Chen F, Chen S. 2024. Bioactive components and antimicrobial potential of extracts from Artemisia species and their repellent activities against Aphid (Macrosiphoniella sanborni). Ornamental Plant Research 4: e025 doi: 10.48130/opr-0024-0021
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  • Introduction
  • Materials and methods

  • Plant materials

  • Aphid performance assay on Artemisia species and C. morifolium 'Jinba'

  • Aphid olfactory bioassay

  • Volatiles collection and analysis

  • Antimicrobial properties of the extracts from Artemisia plants

  • Statistical analysis

  • Results

  • Aphid performance on Artemisia species and C. morifolium 'Jinba'

  • Y-tube olfactometer bioassay

  • Antimicrobial activity

  • Antifungal effect of leaf and stem extracts on Alternaria alternata, Colletotrichum siamense and Phoma sp.
  • Antifungal effect of root extracts from Artemisia species on Fusarium solani

  • Analysis of volatile compounds

  • Screening of key bioactive components of extracts with antifungal effect

  • Discussion
  • Conclusions
  • Author contributions
  • Data availability
  • Acknowledgments
  • Conflict of interest
  • Supplementary information
  • Rights and permissions
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