Showing papers by "Detlef Weigel published in 2023"

The immune receptor SNC1 monitors helper NLRs targeted by a bacterial effector

Abstract: Plants deploy intracellular receptors to counteract pathogen effectors that suppress cell-surface receptor-mediated immunity. To what extent pathogens manipulate also immunity mediated by intracellular receptors, and how plants tackle such manipulation, remains unknown. Arabidopsis thaliana encodes three very similar ADR1 class helper NLRs (ADR1, ADR1-L1 and ADR1-L2), which play key roles in plant immunity initiated by intracellular receptors. Here, we report that Pseudomonas syringae AvrPtoB, an effector with E3 ligase activity, can suppress ADR1-L1- and ADR1-L2-mediated cell death. ADR1, however, evades such suppression by diversification of two ubiquitination sites targeted by AvrPtoB. The intracellular sensor NLR SNC1 interacts with and guards the CCR domains of ADR1-L1 and ADR-L2. Removal of ADR1-L1 and ADR1-L2 or delivery of AvrPtoB activates SNC1, which then signals through ADR1 to trigger immunity. Our work not only uncovers the long sought-after physiological function of SNC1 in pathogen defense, but also that reveals how plants can use dual strategies, sequence diversification and a multiple layered guard-guardee system, to counteract pathogen attack on core immunity functions.

Transposon dynamics in the emerging oilseed crop Thlaspi arvense

Abstract: Genome evolution is partly driven by the mobility of transposable elements (TEs) which often leads to deleterious effects, but their activity can also facilitate genetic novelty and catalyze local adaptation. We explored how the intraspecific diversity of TE polymorphisms is shaping the broad geographic success and adaptation capacity of the emerging oil crop Thlaspi arvense. We achieved this by classifying the TE inventory of this species based on a high-quality genome assembly, age estimation of retrotransposon TE families and a comprehensive assessment of their mobilization potential. Our survey of TE insertion polymorphisms (TIPs) captured 280 accessions from 12 regions across the Northern hemisphere. We quantified over 90,000 TIPs, with their distribution mirroring genetic differentiation as measured by single nucleotide polymorphisms (SNPs). The number and types of mobile TE families vary substantially across populations, but there are also shared patterns common to all accessions. We found that Ty3/Athila elements are the main drivers of TE diversity in T. arvense populations, while a single Ty1/Alesia lineage might be particularly important for molding transcriptome divergence. We further observed that the number of retrotransposon TIPs is associated with variation at genes related to epigenetic regulation while DNA transposons are associated with variation at a Heat Shock Protein (HSP19). We propose that the high rate of mobilization activity can be harnessed for targeted gene expression diversification, which may ultimately present a toolbox for the potential use of transposition in breeding and domestication of T. arvense.

Editor's evaluation: Genome editing of an African elite rice variety confers resistance against endemic and emerging Xanthomonas oryzae pv. oryzae strains

Abstract: Full text Figures and data Side by side Abstract Editor's evaluation Introduction Results Discussion Methods Data availability References Decision letter Author response Article and author information Metrics Abstract Bacterial leaf blight (BB) of rice, caused by Xanthomonas oryzae pv. oryzae (Xoo), threatens global food security and the livelihood of small-scale rice producers. Analyses of Xoo collections from Asia, Africa and the Americas demonstrated complete continental segregation, despite robust global rice trade. Here, we report unprecedented BB outbreaks in Tanzania. The causative strains, unlike endemic African Xoo, carry Asian-type TAL effectors targeting the sucrose transporter SWEET11a and iTALes suppressing Xa1. Phylogenomics clustered these strains with Xoo from Southern-China. African rice varieties do not carry effective resistance. To protect African rice production against this emerging threat, we developed a hybrid CRISPR-Cas9/Cpf1 system to edit all known TALe-binding elements in three SWEET promoters of the East African elite variety Komboka. The edited lines show broad-spectrum resistance against Asian and African strains of Xoo, including strains recently discovered in Tanzania. The strategy could help to protect global rice crops from BB pandemics. Editor's evaluation This valuable study shows that new, virulent genotypes of Xanthomonas oryze pv. oryzae, that are similar to strains present in east Asia, cause outbreaks of bacterial blight of rice in Tanzania. The authors' use of CRISPR-based gene editing on multiple pathogen targets in an elite African rice variety to create lines resistant to both endemic and emerging pathogen strains in Africa makes for a compelling contribution to meet this alarming development. https://doi.org/10.7554/eLife.84864.sa0 Decision letter Reviews on Sciety eLife's review process Introduction Rice is one of the most important staple foods for developing countries in Asia and Africa (Odongo et al., 2021). African consumers increasingly replace traditional staples such as sorghum, millet, and maize with rice. Today, African farmers, 90% of which are small-scale food producers with <1 ha of land (Pandey et al., 2010), produce ~60% of local rice demand. The demand will likely increase with the expected doubling of the population until 2050. Productivity is often hampered by diseases, such as Bacterial Leaf Blight (BB), Rice Yellow Mottle Virus (RYMV), and Rice Blast (RB) (Jiang et al., 2020; Longue et al., 2018; Mutiga et al., 2021). Breeding high-yielding varieties with resistance to these diseases will be an important factor needed for food security in Africa. BB, caused by the bacterium Xanthomonas oryzae pv. oryzae (Xoo), is a devastating rice disease in many rice-growing countries. Xoo comprises a wide spectrum of pathovars with diverse virulence mechanisms. In rice, resistance (R) genes for BB have been identified and are used extensively to breed resistant varieties. However, resistance based on single R genes was rapidly overcome by new pathovars (Vera Cruz et al., 2000). Regular monitoring of the virulence of current Xoo populations on a collection of rice tester lines carrying single or combinations of R genes has provided effective guidance for stacking different R genes to obtain broad-spectrum resistance in Asian rice varieties (Arra et al., 2017; Arra et al., 2018). In Africa, BB was first reported in Mali and Cameroon in the late 1970s, and later in several other West African countries (Buddenhagen et al., 1979; Verdier et al., 2012b). Recently, East African countries also reported BB epidemics (Duku et al., 2016). While information on the spread and severity of BB in Africa is scarce, BB is not yet considered a major threat in Africa; nevertheless, BB is an established disease. The situation is unstable, because climate change affects disease spread, and damage is expected to become more severe in the future due to climate change (Amos, 2013; Laha et al., 2016; Sere and Ouedraogo, 2005; Verdier et al., 2012b). Increased demand and the need to improve food security make it essential to generate broad-spectrum and durable resistance in local varieties specifically for Africa. Key aspects of the mechanisms underlying BB disease have been elucidated and provide an efficient roadmap for resistance breeding. Xoo strains secrete a suite of Transcription Activator-Like effectors (TALes) into rice xylem parenchyma cells via type III secretion systems. Once inside the host cell, TALes are targeted to the nucleus, where they bind to effector binding elements (EBEs) in the promoters of specific host genes via a unique domain of tandemly arranged 34 amino-acid long repeats. TALes function as transcriptional activators that trigger ectopic induction of target genes (Richter et al., 2014). Several Xoo TALes induce one or several host SWEET sucrose uniporter genes (SWEET11a, 13 and 14), presumably causing sucrose release from the xylem parenchyma into the apoplasm at the sites where the bacteria reside and reproduce (note that due to the discovery of a previously misannotated sucrose transporting paralog, SWEET11a was renamed formerly SWEET11 Wu et al., 2022). Sucrose is consumed by the bacteria, resulting in effective reproduction (Sadoine et al., 2021). Allelic EBE variants that cannot be recognized by TALes function as recessive gene-for-gene resistance genes. Without SWEET induction, Xoo is not a potent pathogen. To date, six target EBEs in SWEET promoters have been identified in a comprehensive Xoo collection. Notably, Asian and African Xoo strains are phylogenetically distinct and use distinct TALes to target SWEETs (Oliva et al., 2019; Tran et al., 2018). African Xoo strains exclusively use TalC and TalF, which both target SWEET14, while Asian strains encode PthXo1, PthXo2 (variants A, B, C), PthXo3 and AvrXa7, which target SWEET11a, 13, and 14, respectively (Eom et al., 2019; Oliva et al., 2019). American Xoo strains lack TALes and hence are poorly virulent (Verdier et al., 2012a). Based on the information of the TALe compendium and the SWEET target sites, broad-spectrum resistance to Asian strains was successfully introduced into Oryza sativa ssp. japonica cv. Kitaake and the spp. indica varieties IR64 and Ciherang-Sub1 by genome editing the EBEs in all three SWEET promoters (Eom et al., 2019; Oliva et al., 2019). The edited lines may prove to be valuable breeding materials that could benefit small-scale producers in Asia. To prepare for emerging strains with novel virulence mechanisms, the diagnostic SWEETR kit was developed, enabling effective characterization of causative strains and their SWEET-based disease mechanisms, and identification of suitable resistance strategies, such as the best possible SWEETR-gene combinations for deployment in the target country (Eom et al., 2019). First observations of BB in Africa were made as early as 1979 in Mali and Cameroon (Buddenhagen et al., 1979). Since then, the disease has been reported mostly in West Africa, including Senegal, Benin, Burkina Faso, Ivory Coast, Mali, and Niger (Afolabi et al., 2016; Gonzalez et al., 2007; Tall et al., 2020; Tekete et al., 2020). More recently, BB was also reported in the East African countries Uganda and Tanzania (Duku et al., 2016; Oliva et al., 2019). However, at present, little information on the genetic diversity and dynamics of Xoo populations is available for Africa. While pathogenic strains have sporadically been isolated from rice plants and characterized, there has been no systematic analysis of Xoo strains and BB disease severity across Africa. Moreover, diverse rice varieties are used across Africa, and there is only limited information on the acreage used for different varieties. These factors make it challenging to breed durably resistant lines for Africa. Numerous international partnerships have introduced varieties and cultivation techniques to major rice production areas in different countries in Africa. For instance, in 1975, one of the first irrigated perimeters with rice research labs and a training farm was developed in Dakawa, a major rice production zone in Tanzania, as a result of a multi-year partnership with North Korea (van et al., 2022). National (NAFCO) and international institutions (USAID, Cornell University) remain active in Dakawa to build irrigation schemes and implement The System of Rice Intensification (SRI). In 2011, a collaboration with China resulted in 50 ha of irrigated fields managed by local farmers. A Technology Demonstration Center that trains local farmers and technicians and grows Chinese varieties, including hybrid rice has been established (Makundi, 2017). Recent disease surveys in Tanzania, described here, identified an outbreak of BB in 2019 that has spread in subsequent years. We show that the causative strains have features that distinguish them from endemic African Xoo strains, and unravelled the virulence mechanisms that make them a major threat to African rice production. Recently, Kenya and Nigeria exempted SDN-1 genome-edited crops generated using site-directed nuclease without a transgene (SDN-1) from GMO regulations (Buchholzer and Frommer, 2023). This exemption provides a regulatory framework for the introduction of genome-edited, BB-resistant rice into African countries such as Kenya and Nigeria. As a first step towards the generation of BB-resistant rice cultivars for small-scale rice producers in these countries, we used an optimized transformation protocol to edit susceptibility genes in the rice cultivar Komboka, which is popular in East African countries (Luu et al., 2020). Komboka (IRO5N-221) is a relatively new high-yielding, semi-aromatic rice variety jointly developed by IRRI (International Rice Research Institute) and KALRO (Kenya Agricultural & Livestock Research Organization; BBSRC Varieties Kenya.pdf) that grows to an average height of 110cm and has a yield potential of~7 tons/ha, - almost twice that of Basmati, another popular variety planted in Kenya and Rwanda (The Star 2020). Komboka plants mature in~115days, respond well to fertilization, and are suitable for irrigated lowland cultivation in Africa (Kitilu et al., 2019). Komboka had been classified as moderately resistant to BB, RYMV, and RB; however, detailed resistance profiles for specific strains or races are not available, rendering this information of little value for breeding resistance in the context of specific pathovars present locally. Here, BB-resistance and susceptibility genes of Komboka were analyzed, and a combination of Cas9, Cpf1 and multiplexed gRNAs was used to edit all known EBEs in the SWEET genes, resulting in broad-spectrum resistance to not only previously known African and Asian strains, but also the newly introduced Xoo strains identified from the outbreak in Tanzania. Results Identification of an unprecedented disease outbreak in Tanzania Local breeders reported that although BB was found in Tanzania, it was not considered a major disease due to low incidence and low severity up until 2019 (RM, pers. comm.). Here, we report on an unprecedented BB outbreak identified in the irrigated schemes of Dakawa and Lukenge in 2019 and 2021, respectively (Figure 1; Figure 1—figure supplement 1, Figure 1—figure supplement 2). The two sites are ~60 km apart in the Morogoro region, an area that for decades has been a center of partnership initiatives that aim at increasing rice production (Makundi, 2017). We performed disease surveys in this area in 2019 and detected a severe outbreak in Dakawa on TXD 306 (SARO-5), a rice variety popular in irrigated ecologies in Tanzania (Figure 1—figure supplement 1). Later on, in 2021 in Lukenge, several fields also showed severe signs of infections (Figure 1; Figure 1—figure supplement 2). Leaves collected in 2019 and 2021 with typical BB symptoms were processed, resulting in the isolation of seven strains from Dakawa and 106 from Lukenge, all validated as Xoo using diagnostic primers (Lang et al., 2010; Table 1, Supplementary file 1a). In 2022, we surveyed BB on a larger scale and collected over 600 leaf samples from plants with typical BB symptoms from 37 fields in six different regions in Tanzania. The results of the survey show that BB has spread across Tanzania (Figure 1; Supplementary file 1b). Multiple Locus Variable Number of Tandem Repeat Analyses and/or whole genome SNP analysis is in progress and is expected to provide new insights into the genetic structure of the Xoo population in Tanzania. A careful analysis of yield losses has not yet been possible. Out of six fields surveyed in Dakawa in 2019, one was very severely infected (Figure 1—figure supplement 1). The yield loss in this field was estimated to be >60%. One of the fields surveyed in Lukenge in 2021 had an estimated yield loss of 10–15%. In 2022, several Dakawa fields had estimated yield losses of 5–10%, others <5%. Yield loss at other sites such as Igunga was estimated to 10%, in Mombo <5%. Note that estimates of severity and yield losses are snapshots, and careful and systematic multiyear analyses will be required for a reliable evaluation of severity, spread and yield losses. Figure 1 with 2 supplements see all Download asset Open asset Detection of an outbreak and survey of BB in Tanzania. (A) No reports of serious BB infections before 2019. (B) Detection in Dakawa; in 2019, (C) in Lukenge in 2021, (D–I) survey results from 2022 at different degrees of severity. Note that sampling and scoring occurred initially in the Morogoro region in Dakawa in 2019 and in Lukenge 2021, (no info on 2020 due to Covid-19); scoring and sampling was expanded to additional fields across Tanzania in 2022. Due to sampling bias early in the outbreak, data should be interpreted with caution. One may project that BB caused by the introduced strains will manifest in Tanzania and could spread to neighboring countries. Leaf area affected: yellow 4–6%, orange 7–12%, red 13–25% and purple 26–50%. Table 1 Efficiency of resistance genes in IRBB rice lines towards a diversity panel of 26 African Xoo strains. Quantitative scores of lesion length produced upon leaf-clip inoculation of a diversity panel consisting of 26 Xanthomonas oryzae pv. oryzae strains from West and East Africa on IRBB near-isogenic-lines (NILs) carrying different Xanthomonas resistance genes (Xa) and on the variety Azucena used as susceptible control (IRBB1: Xa1; IRBB3: Xa3; IRBB4: Xa4; IRBB5: xa5; IRBB7: Xa7; IRBB23: Xa23; IR24: recipient parent). Resistance or susceptibility of rice plants to Xoo was determined based on lesion length measured 14 days after inoculation: Resistant (R) <5 cm; moderately resistant (MR)=5–10 cm; moderately susceptible (MS)=10–15 cm; and susceptible (S) >15 cm. Strain NameCIX codeCountryAzucenaIR24IRBB1IRBB3IRBB4IRBB5IRBB7IRBB23KombokaNatiPark607BeninSRRRRRRRRKarfiguela13705Burkina FasoSRRRRRRRRN2-44482NigerSRRRRRRRRTanguieta3609BeninSMRRMRRRMRRRToula20629NigerSMRRMRRRMRRRBAI2504127Burkina FasoSMRRMRMRRRRRS62-2-222374SenegalSMRRMSRRMRRRCII-14083Ivory CoastSMSMRMSRRMRRRCII-21042Ivory CoastSMSMRMSMRRMRRRNAI92787NigerSMSMRMSMRMRMSRRAXO19471917CameroonSSRSRRMSRRMAI145894MaliSSRSMRMSSRRBAI34092Burkina FasoSMSMRSMRMRMSRRCFBP19482801CameroonSMSMRSMRMRSRRNAI54099NigerSSMRSMRMRSRRMAI734079MaliSSRSMSMRSRRS82-4-32976SenegalSMSMRSMSMRMSRRMAI1324517MaliSSRSSMSSRRiTzDak19-14457TanzaniaSSSSSSSSSiTzDak19-24458TanzaniaSSSSSSSSSiTzDak19-34462TanzaniaSSSSSSSSSiTzLuk21-14506TanzaniandndndndndndndndndiTzLuk21-24509TanzaniandndndndndndndndndiTzLuk21-34505TanzaniandndndndndndndndSiTzLuk21-44507TanzaniandndndndndndndndSiTzLuk21-54508Tanzaniandndndndndndndndnd n.d. not determined. To systematically analyze the newly isolated strains from Tanzania, and to compare them to the broader African Xoo landscape, we used 8 strains isolated from Dakawa in 2019 and Lukenge in 2021, as well as 18 representative strains from a collection of 833 strains sampled from rice fields in nine other African countries between 2003 and 2021. These endemic African strains had previously been identified as Xoo based on molecular diagnostic and pathogenicity assays (BS, unpubl. results; Supplementary file 1a). To evaluate the effectiveness of the resistance genes Xa1, Xa3, Xa4, xa5, Xa7, and Xa23, known to be efficient against African Xoo (Gonzalez et al., 2007; Tekete et al., 2020), six Near Isogenic Lines (NILs) of rice each harboring one of these single BB resistance gene, were inoculated with 18 endemic African strains and three strains isolated from Dakawa in 2019 (iTzDak19-1, iTzDak19-2 and iTzDak19-3; strain naming: Dak for Dakawa, Tz for Tanzania, and the novel strains collected in 2019 and 2021 obtained an 'i’ for introduced) (Table 1; Figure 2). NILs harboring Xa1, Xa23, xa5 or Xa4 were resistant to most endemic African strains, but surprisingly, iTzDak19-1, iTzDak19-2, and iTzDak19-3 were virulent on all NILs tested. These unusual iTz strains were therefore characterized in more detail (see below). The strains from Lukenge were isolated much later and could so far not be included in the race-typing analysis, but were also characterized in more detail as decribed below. Figure 2 with 3 supplements see all Download asset Open asset Resistance spectrum of wild-type Komboka rice against African Xoo strains. Leaf-clip inoculation of wild-type Komboka rice plants with a panel of 21 Xoo strains originating from 8 African countries along with Asian reference strain PXO86 from the Philippines. Lesion length (in cm) was measured 14 days after Xoo inoculation. Data from three independent experiments are represented. Letters in the boxplot represent significant differences. As a representative of the isolates from Lukenge iTzLuk21-3 was tested for virulence on Komboka and shown to be fully susceptible (Figure 2—figure supplement 1). Resistance of Komboka to endemic African Xoo but not to new Tanzanian strains Komboka, an emerging elite variety released in several East African countries (Tanzania, Kenya, Uganda and Burundi) has been described as moderately resistant to Xoo, yet the nature of its resistance has not been elucidated. Using our African Xoo diversity panel, we found that most African strains were avirulent on Komboka, except for representatives of newly isolated strains from Dakawa (2019) and Lukenge (2021); (Figure 2, Figure 2—figure supplement 1; Table 1). By comparison, all strains were highly virulent on the susceptible variety Azucena (Figure 2—figure supplement 2; Table 1). Since Xa1, Xa4, xa5, and Xa23 confer resistance against Xoo (Table 1), we investigated R gene presence in the Komboka genome. Mining of the IRRI QTL database (https://rbi.irri.org/resources-and-tools/qtl-profiles) revealed that Komboka contains genetic markers linked to Xa4 but not xa5 or Xa23, while there was no information on Xa1 in the database (Figure 2—figure supplement 3A). We confirmed the presence of Xa4 in Komboka by tracing an Xa4-associated marker and by sequencing (Figure 2—figure supplement 3B,C; Supplementary file 1c). Consistent with the broad-spectrum resistance of Xa1 against endemic African Xoo strains, we found that Komboka carries a dominant Xa1 allele that is highly similar to Xa45(t) (Ji et al., 2020; Figure 2—figure supplement 3D, E). The combination of Xa4 and Xa45(t) in Komboka liekly can explain the observed resistance to most African Xoo strains. However, the R genes present in Komboka do not protect against the iTz strains recently isolated from the outbreak in Tanzania. Tanzanian Xoo strains cluster with Asian Xoo via whole genome SNP-based phylogeny To identify the mechanisms underlying the virulence of the Tanzanian strains, three strains collected from Dakawa in 2019, and five from Lukenge in 2021, were subjected to whole-genome sequencing and SNP-based phylogenetic analyses (Supplementary file 1a, Supplementary file 2). Notably, all eight strains clustered with Asian rather than African Xoo isolates (Figure 3A). By contrast, older Tanzanian strains TzDak11-1, TzDak11-2 and TzDak18-1, which had been collected in Dakawa before 2019, grouped with the endemic African lineage, consistent with previous reports (Oliva et al., 2019). Based on the analysis of the core genome, the eight recently isolated strains carried only 1–4 core genome SNPs (Figure 3—figure supplement 1), intimating that they derive from a single introduction event. The phylogenetic analysis indicates that the new strains (named iTz; ‘i’ for introduced; Tz for Tanzania); are most closely related to strains from Yunnan province, China. Additional analyses will be necessary to identify the exact source of inoculum given the relatively small evolutionary distance between the strains from Yunnan and the iTz strains (Figure 3B). The new strains all carry iTALe genes similar to tal3a of PXO99A (Figure 3C and ). iTALe genes encode truncated TALes that suppress Xa1 resistance, but had so far only been reported in Asian Xoo isolates. In addition, the strains contain a TALe (named PthXo1B) highly similar to the Asian PthXo1, with the addition of two RVDs at the N-terminus of the repeat array (Figure 3D; Supplementary file 1d). EBE prediction indicated that PthXo1B can bind to the SWEET11a promoter at a site overlapping with the EBE that is targeted by PthXo1 (Figure 3D). Consistent with a SWEET11a-based susceptibility, ossweet11a knock-out mutants from the diagnostic SWEETR kit were resistant to representative strains from the outbreak in Dakawa and Lukenge, iTzDak19-1 and iTzLuk21-3, whereas ossweet13 or ossweet14 knock-out mutants remained susceptible (Figure 4A). Moreover, SWEET11a mRNA levels were elevated in Kitaake leaves after inoculation with iTzDak19-1 and iTzLuk21-3 (Figure 4B). Together, our data show that the iTz strains collected in 2019–2021 in the Morogoro region are >99.99% identical to each other, and phylogenetically related to Asian Xoo strains. The strains contain both iTALe and pthXo1 homologs unique to Asian Xoo isolates, providing insights into the virulence mechanism and providing a basis for the development of approaches that can protect African rice varieties, and in particular Komboka, against the novel iTz strains found in the outbreak (Oliva et al., 2019). Figure 3 with 1 supplement see all Download asset Open asset Analysis of the genomes of Tanzanian Xoo isolates. (A) Core genome Xanthomonas oryzae phylogenetic tree. Only the names of Tanzanian isolates are indicated. Abbreviations: Xoo, X. oryzae pv. oryzae; Xoc, X. oryzae pv. oryzicola; Xol, X. oryzae pv. leersiae. (B) Close-up view of the branches of the tree in A, including the newly isolated Tanzanian strains and neighboring clades. Black-filled nodes have a bootstrap support value equal to or above 80%. The scale bar reflects branch length in mean number of nucleotide substitutions per site. Colored squares reflect the continent of origin (as in A). Text color refers to the subregion of origin. (C) Multiple alignment of the N- terminal domain sequences of PXO99A iTALes and the putative iTALes from the eight newly isolated Tanzanian iTz strains. The -terminal domain of PthXo1 from strainPXO99A was used as canonical TALe. TALe references; lowercase letters represent amino acids. Gaps are colored gray. (D) Talvez EBE predictions on the SWEET11a promoter. Repeat Variable Di-residue (RVD) sequences (rounded boxes) are aligned along their predicted matching nucleotide along the promoter sequence (the lowest row). Black-filled RVDs match their target nucleotide in the Talvez RVD-nucleotide association matrix with the best possible score for this RVD. Those in violet match with an intermediate score. Values in the rounded boxes near the TALe names correspond to Talvez prediction scores. Sequences are provided in Figure 3—source data 1. Figure 3—source data 1 Compressed archive with Fasta Sequence files of Xoo strains CIX4462, CIX4506 and CIX4462. CIX4505, CIX4507, CIX4508, CIX4457, CIX4458, Xoo3-1. https://cdn.elifesciences.org/articles/84864/elife-84864-fig3-data1-v2.docx Download elife-84864-fig3-data1-v2.docx Figure 4 Download asset Open asset Virulence of the new Tanzanian Xoo strains depends on the induction of SWEET11a. (A) Lesion lengths were measured 14 days after leaf-clipping inoculation of Kitaake individual sweet knock out lines (ossweet11a, ossweet13 and ossweet14) in the cultivar Kitaake (Eom et al., 2019) with PXO99A (PthXo1), PXO61 (PthXo2B/PthXo3), MAI1 (TalC/TalF), and Tanzanian strains (iTzDak19-1 and iTzLuk21-3) from the recent outbreaks (highlighted by a red bar). Results from two independent experiments are represented. (B) Relative mRNA levels (2-ΔCt) of SWEET11a, SWEET13 and SWEET14 in wild-type Kitaake upon infection by PXO99A (PthXo1), BAI3 (TalC), and Tanzanian pthXo1B dependent Xoo strains. Samples were collected 48 hr post infiltration. Data from three independent experiments were pooled and are represented together. Ct values were normalized to the rice EF1α elongation factor (∆Ct). Editing SWEET promoter sequences in Komboka to obtain resistance to Asian and African strains As a prerequisite for editing SWEET promoters in Komboka, the promoter regions of SWEET11a, 13 and 14 were sequenced. The promoters contain EBEs for PthXo1 and PthXo1A, PthXo2A, PthXo3, AvrXa7, TalC, and TalF, respectively (Figure 5; Figure 5—figure supplement 1, Supplementary file 1e). To protect Komboka against endemic strains from Africa as well as introduced Asian strains, all six known EBEs in the promoters of SWEET11a, 13 and 14 were edited using a hybrid Cas9/Cpf1 editing system. Due to blunt cleavage, Cas9 preferentially produces SNPs, while Cpf1 (Cas12) produces staggered cuts, creating predominantly small deletions. We hypothesized that small deletions may produce more robust resistance because the sequences would differ more from the target EBE. Moreover, the probability of obtaining combinations of optimal mutations in all EBEs is expected to be higher compared to Cas9 approaches (Oliva et al., 2019). Due to the PAM requirement, it was not possible to design sgRNAs for Cpf1 at all EBEs; therefore, Cpf1 was combined with Cas9. Two CRISPR/Cpf1 gRNAs (cXo1 and cXo2) were designed to target PthXo1 /PthXo1 A and PthXo2A EBEs in SWEET11a and SWEET13, respectively (Figure 5—figure supplements 1 and 2; Supplementary file 1f). Since the EBEs for AvrXa7, PthXo3 and TalF in SWEET14 are overlapping, one CRISPR-Cpf1 gRNA (cTalF) was designed to target the overlapping region of all three EBEs. Because no TTTV PAM sequence was available near the EBE for TalC for designing a gRNA required by Cpf1, a Cas9 gRNA (gTalC) was designed to target the TalC EBE. From a first round of transformation, six representative T2 lines were tested for resistance using six representative Xoo strains: ME2 (PXO99A mutant deficient in PthXo1), PXO99A (PthXo1), PXO61 (PthXo2B, PthXo3), PXO86 (AvrXa7), MAI1 (TalC, TalF), and BAI3 (TalC) (Figure 5A, Figure 5—figure supplement 3, Supplementary file 1g-k). All six lines from this first round of transformation were resistant to the tested strains. One line (1.5_19) was fully resistant to all strains, while five lines were fully resistant to five strains, but only moderately resistant to PXO86. This difference in resistance is most likely explained by the presence of a rather small 4 bp deletion in the EBE for AvrXa7, while line 1.5_19 carried the same 4 bp deletion plus an additional base pair substitution (G/T) (Figure 5B). Since the clipping assays us very high bacterial titers, it is generally assumed that moderate resistance will be sufficient for effective resistance in field conditions (Adhikari et al., 1995; Fred et al., 2016). However, TALes were reported to have less specific nucleotide binding at the 3’-end, hence the G/T substitution in line 1.5_19 could potentially be overcome by adaptation of AvrXa7 (Richter et al., 2014). To obtain more robust resistance to all known Xoo strain, a second round of transformation was carried out. Two T2 lines (14_19 and 14_65), which contained deletions in all EBEs, including 11- and 5 bp deletions in the AvrXa7 EBE, respectively, were resistant to all strains tested, including PXO86 (Figure 6). Lines 1.5_19 and 1.2_40 were also resistant to iTzDak19-1 and iTzLuk21-3, consistent with the 12- and 9 bp deletions in the predicted PthXo1 EBE (Figure 7). As one may have predicted, induction of SWEET11a by iTzDak19-1 and iTzLuk21-3 was abolished in lines 1.2_40 and 1.5_19 (Figure 7—figure supplement 1). Taken together, Komboka lines with full resistance to representative Asian and African Xoo strains were obtained; notably with resistance to two representative strains from the emerging iTz population from Dakawa and Lukenge. Figure 5 with 3 supplements see all Download asset Open asset Resistance of EBE-edited Komboka lines against six representative Xoo strains. (A) Reactions of WT and six edited Komboka lines to infection by Xoo strains (PXO99A, PXO61, PXO86, BAI3, and MAI1) harboring PthXo1, PthXo2 PthXo3, AvrXa7, TalC and/or TalF. ME2 is a PXO99A mutant strain with mutant deficient in PthXo1 and served as a negative control. The Komboka lines were carried edits in all six EBE sites validated by DNA sequencing.(B). Details of the EBEs targeted by PthXo3, AvrXa7 and TalF, and respective mutations in the six edited lines. Figure 6 Download asset Open asset Genotypes and phenotypes of two EBE-edited lines generated in a second transformation experiment. (A) Mutations at the EBEs for PthXo1, PthXo2, TalC, TalF, PthXo3, and AvrXa7 in two Komboka edited lines, 14_19 and 14_65. (B). Reactions of wild-type Komboka and the two edited lines to the infection

Editor's evaluation: Environment as a limiting factor of the historical global spread of mungbean

Abstract: Full text Figures and data Side by side Abstract Editor's evaluation eLife digest Introduction Results Discussion Materials and methods Appendix 1 Data availability References Decision letter Author response Article and author information Metrics Abstract While the domestication process has been investigated in many crops, the detailed route of cultivation range expansion and factors governing this process received relatively little attention. Here, using mungbean (Vigna radiata var. radiata) as a test case, we investigated the genomes of more than 1000 accessions to illustrate climatic adaptation’s role in dictating the unique routes of cultivation range expansion. Despite the geographical proximity between South and Central Asia, genetic evidence suggests mungbean cultivation first spread from South Asia to Southeast, East and finally reached Central Asia. Combining evidence from demographic inference, climatic niche modeling, plant morphology, and records from ancient Chinese sources, we showed that the specific route was shaped by the unique combinations of climatic constraints and farmer practices across Asia, which imposed divergent selection favoring higher yield in the south but short-season and more drought-tolerant accessions in the north. Our results suggest that mungbean did not radiate from the domestication center as expected purely under human activity, but instead, the spread of mungbean cultivation is highly constrained by climatic adaptation, echoing the idea that human commensals are more difficult to spread through the south-north axis of continents. Editor's evaluation This is an important interdisciplinary effort, with compelling genetic evidence, that informs on the spread of an important crop. The work will be of broad interest to those studying the domestication and dissemination of cultivated plants. https://doi.org/10.7554/eLife.85725.sa0 Decision letter eLife's review process eLife digest Mungbean, also known as green gram, is an important crop plant in China, India, the Philippines and many other countries across Asia. Archaeological evidence suggests that humans first cultivated mungbeans from wild relatives in India over 4,000 years ago. However, it remains unclear how cultivation has spread to other countries and whether human activity alone dictated the route of the cultivated mungbean’s expansion across Asia, or whether environmental factors, such as climate, also had an impact. To understand how a species of plant has evolved, researchers may collect specimens from the wild or from cultivated areas. Each group of plants of the same species they collect in a given location at a single point in time is known collectively as an accession. Ong et al. used a combination of genome sequencing, computational modelling and plant biology approaches to study more than 1,000 accessions of cultivated mungbean and trace the route of the crop’s expansion across Asia. The data support the archaeological evidence that mungbean cultivation first spread from South Asia to Southeast Asia, then spread northwards to East Asia and afterwards to Central Asia. Computational modelling of local climates and the physical characteristics of different mungbean accessions suggest that the availability of water in the local area likely influenced the route. Specifically, accessions from arid Central Asia were better adapted to drought conditions than accessions from wetter South Asia. However, these drought adaptations decreased the yield of the plants, which may explain why the more drought tolerant accessions have not been widely grown in wetter parts of Asia. This study shows that human activity has not solely dictated where mungbean has been cultivated. Instead, both human activity and the various adaptations accessions evolved in response to their local environments shaped the route the crop took across Asia. In the future these findings may help plant breeders to identify varieties of mungbean and other crops with drought tolerance and other potentially useful traits for agriculture. Introduction Domestication is a process that is cultivated by humans, leading to associated genetic and morphological changes. These changes may be intentional from human selection or unintentional as a result of adaptation to the environments of cultivation (Fuller, 2007). Later, the cultivated plants spread out from their initial geographical range (Meyer and Purugganan, 2013), and elucidating the factors affecting the range expansion of crops is another focus of active research (Gutaker et al., 2020). In the old world, during the process of ‘prehistoric food globalization’ (Jones et al., 2011), crops originated from distinct regions were transported and grown in Eurasia. Archeological evidence has shown that such ‘trans-Eurasian exchange’ had happened by 1500 BC (Liu et al., 2019), and the proposed spread routes from archeological studies were supported by modern genetic evidence especially in rice (Gutaker et al., 2020) and barley (Lister et al., 2018). Interestingly, the spread may accompany genetic changes for the adaptation to novel environments. For example, in barley, variations in the gene Photoperiod-H1 (Ppd-H1) resulting in the non-responsiveness to longer daylengths were likely associated with the historical expansion to high-latitude regions (Jones et al., 2008; Jones et al., 2016). While these mid-latitude cereals have been extensively studied, investigations of crops originated from other climate zones are needed. Using the South Asian (SA) legume mungbean as a test case, here, we investigate how climatic adaptation might affect crop spread route and the evolutionary changes making such spread possible. Mungbean (Vigna radiata [L.] Wilczek var. radiata), also known as green gram, is an important grain legume in Asia (Nair and Schreinemachers, 2020), providing carbohydrates, protein, folate, and iron for local diets and thereby contributing to food security (Kim et al., 2015). Among pulses, mungbean is capable of tolerating moderate drought or heat stress and has a significant role in rainfed agriculture across arid and semiarid areas (Pratap et al., 2019), which are likely to have increased vulnerabilities to climate change. Although there have been studies about the genetic diversity of cultivated and wild mungbean (Ha et al., 2021; Kang et al., 2014; Noble et al., 2018; Sangiri et al., 2007), the evolutionary history of cultivated mungbean after domestication still lacks genetic studies. Existing archeological evidence suggests that South Asia is the probable area of mungbean domestication, and at least two independent domestication events have been suggested, including Maharashtra and the eastern Harappan zone (Fuller and Harvey, 2006). The early archeological records suggest that the selection of large seed sizes occurred in the eastern Harappan zone by the third millennium BC and in Maharashtra, dating to the late second to early first millennium BC (Fuller and Harvey, 2006). This pulse later spread to mainland Southeast Asia and has been reported in southern Thailand dating to the late first millennium BC (Castillo et al., 2016). Further north, the earliest record of mungbean in China was from the book Qimin Yaoshu (齊民要術, 544 AD). While mungbean is also cultivated in Central Asia today, it was not identified in archaeobotanical evidence ranging from several millennium BC to the medieval period (Miller, 1999; Spengler et al., 2018b; Spengler et al., 2017), suggesting later arrival. While the archaeobotanical studies elucidated the route of mungbean cultivation range expansion, researches are still needed to identify the genetic evidence and factors shaping such spread route. A recent genetic study revealed that present-day cultivated mungbeans have the same haplotype in the promoter region, reducing the expression of VrMYB26a (Lin et al., 2022), a candidate gene controlling the important domestication trait, pod shattering, in several Vigna species (Takahashi et al., 2020). This suggests the loss of pod-shattering phenotype in cultivated mungbean may have a common origin and despite the archaeobotanical findings of several independent early cultivations of mungbean in South Asia (Fuller and Harvey, 2006), descendants from one of these cultivation origins might have dominated South Asia before the pan-Asia expansion. Since large regions remain archaeologically unexplored, utilization of genetic data can be a crucial complementation to reconstruct crop evolutionary history. Using seed proteins (Tomooka et al., 1992) and isozymes (Dela Vina and Tomooka, 1994), previous studies proposed two expansion routes out of India, one in the south to Southeast Asia and the other in the north along the silk road to China. While later studies used DNA markers to investigate mungbean population structure (Breria et al., 2020; Gwag et al., 2010; Islam and Blair, 2018; Noble et al., 2018; Sandhu and Singh, 2021; Sangiri et al., 2007), few have examined these hypothesized routes in detail. Therefore, genomic examination of the cultivation rage expansion proposed by archaeobotanical studies and the elucidation of its contributing factors are strongly needed. In this study, we compiled an international effort, reporting a global mungbean diversity panel of more than 1100 accessions derived from (i) the mungbean mini-core collection of the World Vegetable Center (WorldVeg) genebank, (ii) the Australian Diversity Panel (ADP), and (iii) the Vavilov Institute (VIR), which hosts a one-century-old collection enriched with mid-latitude Asian accessions that are underrepresented in other genebanks, many of which were old landraces collected by Nikolai I. Vavilov and his teams in the early 20th century (Burlyaeva et al., 2019). These germplasms harbor a wide range of morphological variations (Figure 1A) and constitute the most comprehensive representation of worldwide mungbean genetic variation. We used this resource to investigate the global history of mungbean after domestication to reveal a spread route highly affected by climatic constraints across Asia, eventually shaping the phenotypic characteristics for local adaptation to distinct environments. Figure 1 with 1 supplement see all Download asset Open asset Diversity of worldwide mungbean. (A) Variation in seed color. (B) ADMIXTURE ancestry coefficients, where accessions were grouped by group assignments (Q≥0.7). (C) Principal component analysis (PCA) plot of 1092 cultivated mungbean accessions. Accessions were colored based on their assignment to four inferred genetic groups (Q≥0.7), while accessions with Q<0.7 were colored gray. (D) Neighbor-joining (NJ) phylogenetic tree of 788 accessions with Q≥0.7 with wild mungbean as outgroup (black color). Results Population structure and spread of mungbean Using DArTseq, we successfully obtained new genotype data of 290 mungbean accessions from VIR Supplementary file 1a. Together with previous data (Breria et al., 2020; Noble et al., 2018), our final set included 1108 samples with 16 wild and 1092 cultivated mungbean. A total of 40,897 SNPs were obtained. Of these, 34,469 bi-allelic SNPs, with a missing rate less than 10%, were mapped on 11 chromosomes and retained for subsequent analyses. The genetic structure was investigated based on the 10,359 LD-pruned SNPs. Principal component analysis (PCA, Figure 1C) showed a triangular pattern of genetic variation among cultivated mungbeans, consistent with previous studies (Breria et al., 2020; Noble et al., 2018; Sokolkova et al., 2020) and ADMIXTURE K=3 (Figure 1B). The geographic distribution of these genetic groups is not random, as these three groups are distributed in South Asia (India and Pakistan), Southeast Asia (Cambodia, Indonesia, Philippines, Thailand, Vietnam, and Taiwan), and more northernly parts of Asia (China, Korea, Japan, Russia, and Central Asia). As K increased, the cross-validation (CV) error decreased a little after K=4 (Figure 1—figure supplement 1), where the north group could be further divided (Figure 1B). Therefore, worldwide diversity of cultivated mungbean could be separated into four major genetic groups corresponding to their geography: SA, Southeast Asian (SEA), East Asian (EA), and Central Asian (CA) groups. Note that the genetic groups were named after the region where most of their members distribute, and exceptions exist. For example, many EA accessions also distribute in Central Asia, and some SEA accessions were found near the eastern and northeastern coasts of India. Throughout this work, we make clear distinction between genetic group names (e.g. SA) and a geographic region (e.g. South Asia). Therefore, unlike any other previous work in this species, this study incorporates global genetic variation among cultivated mungbean of this important crop. Using wild progenitor V. radiata var. sublobata (Wild hereafter) as the outgroup, the accession- (Figure 1D) and population-level (Figure 2A) phylogenies both suggest CA to be genetically closest to EA. The SEA group is more distant, and SA is the most diverged. This relationship is supported by the outgroup f3 tests showing CA shared the highest level of genetic drift with EA, followed by SEA and SA (Supplementary file 1b). Pairwise FST and dxy also give the same conclusion (Figure 2B). Similarly, the f4 tests (Figure 2C) strongly reject the cases where SEA and CA form a clade relative to SA and EA (f4[SA,EA;SEA,CA]=0.016, Z=9.519) or SEA and EA form a clade relative to SA and CA (f4[SA,CA;SEA,EA]=0.021, Z=13.956), again suggesting EA and CA to be closest. With regards to the relationship among Wild, SA, SEA, and EA, f4 tests suggest SEA and EA form a clade relative to Wild and SA (non-significant results in f4[Wild,SA;EA,SEA] but opposite in other combinations). Notably, both TreeMix (Figure 2A) and the f4 test (Figure 2C, f4[SA,SEA;CA,EA]=0.005, Z=6.843) suggest gene flow between SEA and EA. Consistent with archeological evidence of SA domestication, the nucleotide diversity (π) decreased from SA (1.0×10–3) to SEA (7.0×10–4) and EA (5.0×10–4), while the CA group has lowest diversity (3.0×10–4; Figure 2B). Linkage disequilibrium (LD) also decays the fastest in Wild and then the SA group (Figure 2D), followed by other genetic groups. In summary, all analyses are consistent with our proposed order of cultivated mungbean divergence. Figure 2 with 2 supplements see all Download asset Open asset Fine-scale genetic relationship and admixture among four inferred genetic groups. (A) TreeMix topologies with one suggested migration event. Colors on nodes represent support values after 500 bootstraps. (B) Diversity patterns within and between inferred genetic groups as estimated using nucleotide diversity (π in diagonal, where the size of the circle represents the level of π) and population differentiation (FST in upper diagonal and dxy in lower diagonal). (C) f4 statistics. Points represent the mean f4 statistic, and lines are the SE. Only f4 statistics with Z-score>|3| are considered statistically significant. The dashed line denotes f4=0. (D) Linkage disequilibrium (LD) decay. (E) Isolation by distance plot of genetic distance versus geographic distance, with the southern group in red circles and the northern group in blue circles. (F) Relationship between Bio12 (annual precipitation) and nucleotide diversity (π) of the East Asian (EA) genetic group across the east-west axis of Asia. Dot colors represent the annual precipitation of each population. Our proposed demographic history could be confounded by factors such as complex hybridization among groups. For example, SEA and CA might have independently originated from SA and later generated a hybrid population in EA (Figure 2—figure supplement 1A). Other possibilities are that either SEA or CA is the hybrid of other populations (Figure 2—figure supplement 1B and C). We examined these possibilities using f3 statistics for all possible trios among the four groups. None of the tests gave a significantly negative f3 value (Supplementary file 1c), suggesting the lack of a strong alternative model to our proposed relationship among these four groups. Based on the solid relationship among these genetic groups, we used fastsimcoal2 to model their divergence time, allowing population size change and gene flow at all time points (Figure 2—figure supplement 2A–D). According to this model, after initial domestication, the out-of-India event (when other groups diverged from SA) happened about 8.3 thousand generations ago (kga) with 75% parametric bootstrap range between 4.7 and 11.3 kga. Not until more than 5000 generations later (2.7 kga, 75% range 1.1–4.6 kga) did SEA diverge from the common ancestor of present-day EA and CA. CA diverged from EA only very recently (0.2 kga, 75% range 0.1–0.8 kga). Note that the divergence time was estimated in the number of generations, and the much longer growing seasons in the southern parts of Asia may allow more than one cropping season per year (Mishra et al., 2022; Vir et al., 2016). Our results suggest the non-SA accessions have a common origin out of India (otherwise these groups would branch off independently from the SA group). Given this, the phylogenetic relationship (Figure 2A) is consistent with the following hypotheses. (1) The east hypothesis: mungbean expanded eastward and gave rise to the SEA group. This group might initially occupy northeast South Asia and later expanded to Southeast Asia either through the land or maritime route (Castillo et al., 2016; Fuller et al., 2011). The group later expanded northward as EA. EA expanded westward into Central Asia and gave rise to the CA group. (2) The north hypothesis: the group leaving South Asia first entered Central Asia as the EA group. EA expanded eastward into East Asia through the Inner Asian Mountain Corridor (Stevens et al., 2016). The eastern population of EA expanded southward as the SEA group, and later the western population of EA diverged as the CA group. (3) The northeast hypothesis: the group leaving South Asia (through either of the above-mentioned routes) was first successfully cultivated in northern East Asia without previously being established in Southeast Asia or Central Asia. The EA group then diverged southward as SEA and later expanded westward, giving rise to CA. Consistent with this model, the genetic variation of the EA group gradually declines from east to west, accompanied by the gentlest decline of precipitation per unit geographic distance across Asia (Figure 2F). While all three hypotheses are consistent with the phylogeny (Figure 2A), the SEA group originated earlier than EA in the east hypothesis but later in the two other hypotheses. The former case predicts higher nucleotide diversity and faster LD decay in SEA than EA, which is supported by our results (Figure 2B and D). While populations that were established in a region for an extended time could accumulate genetic differentiation, generating patterns of isolation by distance, rapid-spreading populations in newly colonized regions could not (Lee et al., 2017; The 1001 1001 Genomes Consortium, 2016). Using this idea, Mantel’s test revealed a significantly positive correlation between genetic and geographic distances for the SA genetic group (r=0.466, P=0.010), followed by SEA (r=0.252, although not as significant, P=0.069). No such association was found for EA (r=0.030, P=0.142) or CA (r=0.087, P=0.172). In addition, the southern groups (SA and SEA) together (r=0.737, P=0.001) have a much stronger pattern of isolation by distance than the northern groups (EA and CA, r=0.311, P=0.001; Figure 2E). Using Q≥0.5 instead of Q≥0.7 to assign individuals into genetic groups generated results that are largely consistent (Supplementary file 1d). These results are again consistent with the ‘east hypothesis’ that local accessions from the SA and SEA groups were established much earlier than those from EA and CA. Finally, the genetic variation of the EA group is highest in the eastern end and declines westward (Figure 2F). This does not support the north hypothesis where EA first existed in Central Asia and expanded eastward. Environmental differentiation of the inferred genetic groups We further examined the possible causes governing the expansion of mungbean cultivation ranges. For a crop to be successfully cultivated in a new environment, dispersal and adaptation are both needed. Being a crop that has lost the ability of pod shattering, the spread of mungbean was governed by commerce or seed exchange. While barriers such as the Himalayas or Hindu Kush may limit human activity, South and Central Asia was already connected by a complex exchange network linking the north of Hindu Kush, Iran, and the Indus Valley as early as about 4 thousand years ago (kya; Dupuy, 2016; Kohl, 2007; Kohl and Lyonnet, 2008; Lamberg‐Karlovsky, 2002; Lombard, 2020; Lyonnet, 2005), and some sites contain diverse crops originated across Asia (Spengler et al., 2021). Similarly, other ancient land or maritime exchange routes existed among South, Southeast, East, and Central Asia (Stevens et al., 2016). This suggests that mungbean could have been transported from South to Central Asia, but our genetic evidence suggests that the present-day CA group did not descend directly from the SA group. Therefore, we investigated whether climatic adaptation, that is, the inability of mungbean to establish in a geographic region after human-mediated long-range expansion, could be a contributing factor. Multivariate ANOVA (MANOVA) of eight bioclimatic variables (after removing highly-correlated ones; Supplementary file 1e,f) indicated strong differentiation in the environmental niche space of the four genetic groups (Supplementary file 1g,h). PCA of climatic factors clearly reflects geographic structure, where the axis explaining most variation (PC1, 42%) separates north and south groups and is associated with both temperature- and precipitation-related factors (Figure 3A and Supplementary file 1i). Consistent with their geographic distribution, overlaps between EA and CA and between SA and SEA were observed. While these analyses were performed using bioclimatic variables from year-round data, we recognized that summer is the cropping season in the north. Parallel analyses using the temperature and precipitation of May, July, and September yielded similar results (Supplementary file 1j; Figure 3—figure supplement 1). Figure 3 with 5 supplements see all Download asset Open asset Environmental variation among genetic groups of mungbean. (A) Principal component analysis (PCA) of the eight bioclimatic variables. Samples are colored according to four inferred genetic groups as indicated in the legend. (B) Predicted distribution at current climate conditions. Red color indicates high suitability, and blue indicates low suitability. Values between pairs represent niche overlap measured using Schoener’s D, and higher values represent higher overlaps. Abbreviations: SAw: South Asia (west), SAe: South Asia (east); SEA: Southeast Asia; EAe: East Asia (east); EAw: East Asia (west), and CA: Central Asia. (C) Environmental gradient across potential directions of expansion. The value on each arrow indicates a change in annual precipitation per kilometer. The background map is colored according to annual precipitation (Bio12, in mm). Based on the Köppen climate classification (Köppen, 2011), we categorized the Asian mungbean cultivation range into six major climate zones (Figure 3—figure supplement 2): dry hot (BSh and BWh), dry cold (BSk and BWk), temperate dry summer (Csa), tropical savanna (Aw), continental (Dwb and Dfb), and temperate wet summer (Cfa and Cwa). The former three are relatively drier than the latter three zones. While SEA and CA are relatively homogeneous, SA and EA have about half of the samples in the dry and non-dry zones (Figure 3—figure supplement 2). We, therefore, separated SA into SAe and SAw and EA into EAe and EAw, corresponding to the wetter eastern and drier western regions within the SA and EA ranges. Environmental niche modeling revealed distinct suitable regions of these six groups except for CA and EAw, whose geographical ranges largely overlap (Figure 3B). Consistent with PCA, pairwise Schoener’s D values are smallest between the northern and southern groups while largest (suggesting overlaps of niche space) between the eastern and western subsets within north and south (Figure 3B), consistent with PCA that the major axis of climatic difference is between the northern and southern parts of Asia. Analyses using temperature and precipitation from May, July, and September yielded similar results (Figure 3—figure supplement 3). Given a single out-of-India event (Figure 2A), the results suggest it might be easier to first cultivate mungbean in Southeast rather than Central Asia, supporting the east hypothesis. While both temperature and precipitation variables differ strongly between north and south, one should note that these year-round temperature variables do not correctly reflect conditions in the growing seasons. In the north, mungbean is mostly grown in summer where the temperature is close to the south (Figure 3—figure supplement 4A–C). On the other hand, precipitation differs drastically between the north and south, especially for the CA group, where the summer-growing season is the driest of the year (Figure 3—figure supplement 4D). By estimating the regression slope of annual precipitation on geographical distance, we obtained a gradient of precipitation change per unit geographic distance between pairs of genetic groups (Figure 3C). Despite the SA-SEA transect having the steepest gradient (slope = 0.21), the spread from SA to SEA has been accompanied by an increase of precipitation and did not impose drought stress. However, the second highest slope (0.18) is associated with a strong precipitation decrease if the SA group were to disperse to Central Asia. Results from the precipitation of May, July, and September yielded similar conclusion (Figure 3—figure supplement 5). This likely explains why no direct historic spread is observed from South to Central Asia. Trait variation among genetic groups If environmental differences constrained the spread route of mungbean, the currently cultivated mungbean accessions occupying distinct environments should have locally adaptive traits for these environments. Indeed, PCA of four trait categories shows substantial differences among genetic groups (phenology, reproductive output, and size in field trials, as well as plant weight in lab hydroponic systems, Figure 4A). In the field, CA appears to have the shortest time to flowering, the lowest yield in terms of seed size and pod number, and the smallest leaf size (Figure 4B and Supplementary file 1k). On the other hand, SEA accessions maximize seed size, while SA accessions specialize in developing the largest number of pods (Figure 4B). These results suggest that CA has a shorter crop duration, smaller plant size, and less yield, consistent with drought escape phenotypes. This is consistent with the northern short-growing season constrained by temperature and daylength (below), as well as the low precipitation during the short season. Figure 4 with 1 supplement see all Download asset Open asset Quantitative trait differentiation among genetic groups. (A) Principal component analysis (PCA) of four trait categories. (B) Trait variability from common gardens in field experiments. Sample size of SA, SEA, and CA are 18, 17, and 14, respectively. (C) Comparison of QST-FST for four drought-related traits under two environments. FST values (mean, 5%, and 1%) were indicated by black dashed lines. The QST for each trait was colored according to treatment and was calculated as Equation 2 in Materials and methods. Abbreviations: RDW: root dry weight; SDW: shoot dry weight; TDW: total dry weight; RSRDW: root:shoot ratio dry weight; c: control; p: PEG6000. (D) Effect of PEG6000 (–0.6 MPa) on RDW, SDW, TDW, and RSRDW among genetic groups. Sampe size of SA, SEA, and CA are 20, 18, and 14, repectively. Data were expressed as the mean ± SE. Lowercase letters denote significant differences under Tukey’s honestly significant difference test in (B) and (D). In terms of seedling response to drought stress, the QST values of most traits (root, shoot, and whole plant dry weights under control and drought treatments) are higher than the tails of SNP FST, suggesting trait evolution driven by divergent selection (Figure 4C; Figure 4—figure supplement 1). Significant treatment, genetic group, and treatment by group interaction effects were observed except on a few occasions (Table 1). Consistent with field observation, SEA has the largest seedling dry weight (Figure 4D). While simulated drought significantly reduced shoot dry weight (SDW) for all groups, the effect on SEA is especially pronounced (treatment-by-group interaction effect, F2,575 = 23.55, P<0.001, Table 1 and Figure 4D), consistent with its native habitats with abundant water supply (Figure 3—figure supplement 4D and Supplementary file 1l). All groups react to drought in the same way by increasing root:shoot ratio (Figure 4D), suggesting such plastic change may be a strategy to reduce transpiration. Despite the lack of treatment-by-group interaction (F2,575 = 1.39, P>0.05), CA consistently exhibits a significantly higher root:shoot ratio, a phenotype that is potentially adaptive to its native environment of lower water supply (Figure 3—figure supplement 4D and Supplementary file 1l). Table 1 ANOVA F values for the dry weight (mg) of mungbean seedlings across three different genetic groups. Source of vari

Structural variation and DNA methylation shape the centromere-proximal meiotic crossover landscape in Arabidopsis

Abstract: Background Centromeres load kinetochore complexes onto chromosomes, which mediate spindle attachment and allow segregation during cell division. Although centromeres perform a conserved cellular function, their underlying DNA sequences are highly divergent within and between species. Despite variability in DNA sequence, centromeres are also universally suppressed for meiotic crossover recombination, across eukaryotes. However, the genetic and epigenetic factors responsible for suppression of centromeric crossovers remain to be completely defined. Results To explore the centromere-proximal recombination landscape, we mapped 14,397 crossovers against fully assembled Arabidopsis thaliana genomes. A. thaliana centromeres comprise megabase-scale satellite repeat arrays that load nucleosomes containing the CENH3 histone variant. Each chromosome possesses a structurally polymorphic 3-4 megabase region where crossovers were absent, that includes the satellite arrays, flanked by 1-2 megabase low-recombination zones. The recombination-suppressed regions are enriched for Gypsy/Ty3 retrotransposons, and additionally contain expressed genes with high genetic diversity that initiate meiotic recombination, yet do not crossover. We mapped crossovers at high-resolution in proximity to CEN3, which resolved punctate centromere-proximal hotspots that overlapped gene islands embedded in heterochromatin. Centromeres are densely DNA methylated and the recombination landscape was remodelled in DNA methylation mutants. We observed that the centromeric low-recombining zones decreased and increased crossovers in CG (met1) and non-CG (cmt3) mutants, respectively, whereas the core non recombining zones remained suppressed. Conclusion Our work relates the genetic and epigenetic organisation of the A. thaliana centromeres and flanking pericentromeric heterochromatin to the zones of crossover suppression that surround the CENH3-occupied satellite repeat arrays.

The genetic and physiological basis of Arabidopsis thaliana tolerance to Pseudomonas viridiflava

Abstract: The opportunistic pathogen Pseudomonas viridiflava colonizes more than fifty agricultural crop species and is the most common Pseudomonas in the phyllosphere of European Arabidopsis thaliana populations. Belonging to the P. syringae complex, it is genetically and phenotypically distinct from well-characterized P. syringae sensu stricto. Despite its prevalence, we lack knowledge of how A. thaliana responds to its native isolates at the molecular level. Here, we characterize the host response in an A. thaliana - P. viridiflava pathosystem. We measured host and pathogen growth in axenic infections, and used immune mutants, transcriptomics, and metabolomics to determine defense pathways influencing susceptibility to P. viridiflava infection. Infection with P. viridiflava increased jasmonic acid (JA) levels and the expression of ethylene defense pathway marker genes. The immune response in a susceptible host accession was delayed compared to a tolerant one. Mechanical injury rescued susceptibility, consistent with an involvement of JA. The JA/ethylene pathway is important for suppression of P. viridiflava, yet suppression capacity varies between accessions. Our results shed light on how A. thaliana can suppress the ever-present P. viridiflava, but further studies are needed to understand how P. viridiflava evades this suppression to spread broadly across A. thaliana populations.

Pervasive Under-Dominance in Gene Expression Underlying Emergent Growth Trajectories in Arabidopsis thaliana Hybrids

Abstract: Complex traits, such as growth and fitness, are typically controlled by a very large number of variants, which can interact in both additive and non-additive fashion. In an attempt to gauge the relative importance of both types of genetic interactions, we have turned to hybrids, which provide a facile means for creating many novel allele combinations. We focused on the interaction between alleles of the same locus and performed a transcriptomic study involving 141 random crosses between different accessions of the plant model species Arabidopsis thaliana. Additivity is rare, consistently observed for only about 300 genes enriched for roles in stress response and cell death. Regulatory rare-allele burden affects the expression level of these genes but does not correlate with F1 rosette size. Non-additive gene expression in F1 hybrids is much more common, with the vast majority of genes (over 90%) being expressed below parental average. Unlike in the additive genes, regulatory rare-allele burden in the non-additive gene set is strongly correlated with F1 rosette size, even though it only mildly covary with the expression level of these genes. Our study underscores under-dominance as the predominant gene action associated with emergence of rosette growth trajectories in the A. thaliana hybrid model. Our work lays the foundation for understanding molecular mechanisms and evolutionary forces that lead to dominance complementation of rare regulatory alleles.