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Rhizobial tRNA-derived small RNAs are signal molecules regulating plant nodulation

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Microbial tRNA pieces regulate nodulation To fix nitrogen, leguminous plants enter into a symbiotic relationship with nodulating bacteria. Ren et al. now reveal the bacteria as active regulators in this process (see the Perspective by Baldrich and Meyers). Small fragments cleaved from rhizobial tRNA molecules tap into the hosts' RNA interference machinery to silence key host genes. Thus, both host and microbe shape the symbiotic environment. Science , this issue p. 919 ; see also p. 868
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Cite as: B. Ren et al., Science
10.1126/science.aav8907 (2019).
REPORTS
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Symbiotic nitrogen fixation by the bacteria Rhizobia, which
occurs in specialized root organs known as nodules of leg-
umes, provides usable nitrogen to plants in agricultural and
natural eco-systems. The establishment of rhizobia-legume
symbiosis is dependent on recognition of signal molecules be-
tween the partners. Upon perception of plant flavonoids, rhi-
zobia secret lipo-chitooligosaccharidic nodulation factors,
which induce root hairs to curl around the bacteria and de-
velop infection treads that allow bacteria to penetrate into
the cortical cells of the roots to form nodules (1). As symbiotic
nitrogen fixation is resource intensive, legumes have evolved
a number of mechanisms to control nodule numbers (2).
Here we describe a mechanism by which the bacteria regulate
nodule numbers.
Transfer RNA (tRNA)-derived small RNA fragments
(tRFs) are found in both prokaryotes and eukaryotes. Origi-
nally thought to be random degradation products, tRFs are
specifically cleaved from mature tRNAs and often accumulate
in stressed or virally infected cells (3). Some tRFs, akin to mi-
croRNAs (miRNAs), are bound by Argonaute (AGO) proteins,
suggesting that they may employ an miRNA-like mechanism
to regulate gene expression (4). tRFs can target and repress
retrotransposons through an RNAi-mediated silencing path-
way (5). Here we ask whether tRFs are involved in cross-king-
dom communications.
We studied the soybean (Glycine max) and the rhizobium
(Bradyrhizobium japonicum) as symbiotic partners to ad-
dress this question. All 50 rhizobial tRNAs produced tRFs in
both the Rhizobium (strain USDA110) culture and the 10-d
and 20-d old soybean (cultivar Williams 82) nodules, most
were 18 to 24 nt in size, and abundance varied (Fig. 1A and
figs. S1 and S2). Overall, the tRFs in the nodules are more
abundant than those in the culture, with 21-nt tRFs, primarily
derived from the 3ends of the tRNAs, most abundant (figs.
S2 and S3 and table S1).
A total of 52 soybean genes in the soybean genome (6)
were predicted to be targets of 25 unique 21- or 22-nt rhizo-
bial tRFs with a relative abundance of >100 copies per million
rhizobial small RNA reads (table S1). These tRFs were neither
found in small RNA libraries from non-nodule soybean tis-
sues (table S2) (7) nor predicted to target rhizobial genes. Of
the 52 soybean genes, GmRHD3a/GmRHD3b,
GmHAM4a/GmHAM4b, and GmLRX5, which are orthologs of
the Arabidopsis Root Hair Defective 3 (RHD3), Hairy Meri-
stem 4 (HAM4), and Leucine-Rich Repeat Extensin-Like 5
(LRX5), respectively, attracted our attention, as these Ara-
bidopsis genes are important for root hair/plant development
(810). These soybean genes were predicted to be the targets
of three rhizobial tRFs, dubbed Bj-tRF001, Bj-tRF002, and Bj-
tRF003, the predominant products derived from three
tRNAs, Val-1-tRNA(CAC), Gly-1-tRNA(UCC), and Gln-1-
tRNA(CUG), respectively (Fig. 1A). Enrichment of the three
tRFs in the nodules compared with the rhizobium culture
was further validated by stem-loop qRT-PCR (Fig. 1B and fig.
S4), and reduced expression of the five soybean genes in the
nodules compared with the uninoculated roots was revealed
by qRT-PCR (Fig. 1C).
Rhizobial tRNA-derived small RNAs are signal molecules
regulating plant nodulation
Bo Ren1*, Xutong Wang1*, Jingbo Duan1, Jianxin Ma1,2
1Department of Agronomy, Purdue University, West Lafayette, IN 47907, USA. 2Center for Plant Biology, Purdue University, West Lafayette, IN 47907, USA.
*These authors contributed equally to this work.
†Corresponding author. Email: maj@purdue.edu
Rhizobial infection and root nodule formation in legumes requires recognition of signal molecules
produced by the bacteria and their hosts. Here we show that rhizobial tRNA-derived small RNA fragments
(tRFs) are signal molecules that modulate host nodulation. Three families of rhizobial tRFs were
confirmed to regulate host genes associated with nodule initiation and development via hijacking the host
RNAi machinery that involves ARGONAUTE 1. Silencing individual tRFs with the use of short tandem target
mimics or by overexpressing their targets represses root hair curling and nodule formation, whereas
repressing these targets with artificial miRNAs identical to the respective tRFs or mutating these targets
with CRISPR-Cas9 promotes nodulation. Our findings thus uncover a bacterial small RNA-mediated
mechanism for prokaryote-eukaryote interaction and may pave the way for enhancing nodulation
efficiency in legumes.
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Assuming that the reduced expression of these soybean genes
was caused by the rhizobial tRFs through miRNA-like post-
transcriptional regulation, cleavage of the mRNAs from these
genes at the predicted tRF target sites would have occurred.
Indeed, the mRNAs of these genes were predominantly
cleaved at the predicted tRF target sites in the 20-d nodules,
whereas none of these sites were cleaved in the uninoculated
roots (Fig. 1D and fig. S5). None of these sites are complemen-
tary to or were predicted to be targeted by previously identi-
fied soybean small RNAs (7) or newly produced ones in this
study. Soybean miR171k is the only small RNA predicted to
target GmHAM4a/GmHAM4b, but it was primarily expressed
in the uninoculated roots (9.38 counts per million reads, in-
stead of the nodules (0.27 counts per million reads), and thus
unlikely to be responsible for the observed repression of
GmHAM4a/GmHAM4b in the nodules.
To determine whether the repression of the
GmRHD3a/GmRHD3b, GmHAM4a/GmHAM4b, and
GmLRX5 expression in the nodules is associated with nodu-
lation, we created root mutants (fig. S6) for each of the five
genes and for both copies of each of the two duplicated gene
pairs by CRISPR-Cas9, which were inoculated with USDA110.
In all cases examined, expression of the edited genes was re-
duced (fig. S7), the roots with edited genes produced more
nodules than the empty-vector transgenic controls, and the
double mutants produced the greatest number of nodules
(Fig. 2, A and D). We also developed transgenic roots that
overexpress GmRHD3b, GmHAM4a, or GmLRX5 by the cau-
liflower mosaic virus (CaMV) 35S promoter, which exhibited
increased expression of these genes and reduced nodule num-
bers compared with the controls (Fig. 2, B and D, and fig.
S8A). Thus, these genes are negative regulators of nodulation.
To examine the effects of individual rhizobial tRFs on
nodulation, we generated transgenic short tandem target
mimic (STTM) soybean roots to silence each of the three rhi-
zobial tRFs (fig. S9). Nodule numbers in the STTM roots were
decreased compared with the empty-vector transgenic con-
trols (Fig. 2, C and D). As expected, relative abundance of the
three tRFs was decreased, and expression of their putative
targets was increased (figs. S8B and S10), suggesting that
these tRFs are positive regulators of nodulation and may
function through repressing their putative target genes.
To understand by which mechanism rhizobial tRFs regu-
late nodulation, two artificial miRNA precursors, aMIR-
tRF001 and aMIR-tRF003, were constructed by replacing the
miR172a and miR172a* sequences from the soybean miR172a
precursor MIR172a with rhizobial tRF001 and its comple-
mentary tRF001* or with tRF003 and its complementary
tRF003* (fig. S11). aMIR-tRF001 and aMIR-tRF003 were ex-
pressed separately in Williams 82 hairy roots, under the con-
trol of the 35S promoter, to produce artificial miRNAs amiR-
tFR001 and amiR-tFR-003 in the transgenic roots (Fig. 3A).
Expression of the putative amiR-tFR001 and amiR-tFR003
targets GmRHD3a/3b and GmLRX5 was reduced compared
with empty-vector transgenic controls (Fig. 3B), and more
nodules were produced in the aMIR-tRF001 and aMIR-
tRF003 transgenic roots than in respective controls (Fig. 3C).
These observations suggest that the artificial miRNA/tRF se-
quences directly repressed their putative targets to promote
nodulation.
To determine whether such sequence complementarity
was necessary for the amiRNA/tRF-mediated gene regula-
tion, two sets of fusion genes were made by adding each of
the 21-base pair (bp) of DNA fragments corresponding to the
three putative tRF target sites (wild type) and each of the 21-
bp of DNA fragments with 4-bp modification at the detected
cleavage site (mutation type) to the coding sequence of the
green fluorescence protein (GFP) gene. The fusion genes were
expressed under the control of the 35S promoter in Williams
82 hairy roots separately (fig. S12A). Reduction of the GFP
activity in the “wild-type” roots ~24-hours after inoculation
with USDA110 was detected, whereas no change of the GFP
activity in the “mutation type” roots was observed (Fig. 3D
and fig. S12B). The relative abundance of GFP transcripts was
consistent with the GFP activity (fig. S12C). These observa-
tions indicate that the “wild-type” fusion genes were nega-
tively regulated through base-pairing of their mRNAs at the
integrated “target sites” with the rhizobial tRFs.
In Arabidopsis, AGO1 is a component of the RNA-induced
silencing complexes that mediate miRNA-guided cleavage of
target mRNAs (11). To determine whether the rhizobial tRFs
act through the functional counterpart of AGO1 in soybean,
one (GmAGO1b) of the two soybean orthologs of the Ara-
bidopsis AGO1 (12), whose transcripts are relatively more
abundant than those of the other (GmAGO1a) in soybean root
nodules (13), was fused with the Myc epitope tag and ex-
pressed in the hairy roots of Williams 82. The fusion protein
was immunoprecipitated by the Myc antibody from the 20-d
nodules induced by USDA110. All three rhizobial tRFs were
detected in the GmAGO1b-Myc-associated fraction pulled
down by the Myc antibody but not detected in the nodule ly-
sate incubated without the antibody, suggesting that these
rhizobial tRFs hijacked the soybean AGO1 to catalyze tRF-
guided cleavage of target mRNAs in the host cells (Fig. 3E).
Actually, the tRF-mediated regulation of host gene expres-
sion was detected at early stages of rhizobial infection. At all
five time points from 6 to 72 hours post-inoculation with
USDA110, the abundance of the three tRFs was increased in
the inoculated root hairs compared with the uninoculated
root hairs (fig. S13A), whereas the expression of their targets
was decreased (fig. S13B). No differences in root hair number
and length were observed between the GmRHD3b,
GmHAM4a, and GmLRX5 overexpression roots and the con-
trols or between the tRF-silencing STTM roots and the
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controls (fig. S14), but the proportions of deformed/curled
root hairs were decreased in the overexpression and STTM
roots compared with respective controls (Fig. 4, A to C), sug-
gesting that rhizobial tRFs promote rhizobial infection.
To shed light on the evolutionary conservation and diver-
gence of rhizobial tRF-mediated host gene regulation, we an-
alyzed sequence data from four legumes, soybean, common
bean (Phaseolus vulgaris), Medicago trunctrula, and Lotus
japonica (6), and 12 rhizobium species (14), as well as the
GmRHD3a/GmRHD3b, GmHAM4a/GmHAM4b, and
GmLRX5 sequences from soybean populations (15, 16).
Among 699 soybean accessions, no sequence variation at the
three tRF target sites within the five genes was found (fig.
S15). Among eight B. japonicum strains, no sequence varia-
tion at the three tRF sites within respective rhizobial tRNAs
was detected (fig. S16). By contrast, sequences at the target
sites diverged among the four legumes (fig. S17). In particu-
lar, no orthologs of GmLRX5 were found in the other three
legumes (fig. S17). The counterparts of the three rhizobial tRF
sequences in respective tRNAs also showed interspecific di-
vergence (fig. S16). PvRHD3 in common bean, the ortholog of
GmRHD3a/3b, does have a tRF001 target site identical to that
of GmRHD3a/3b (fig. S17), but Rhizobium etli, a compatible
symbiotic partner of common bean (17), does not have the B.
japonicum Val-1-tRNA(CAC) from which tRF001 was derived.
Using the small RNA data from the common bean nodules
induced by a R. etli strain (17), 38 R. etli tRNAs were identi-
fied to have produced 21-nt tRFs. These tRFs were primarily
derived from the 3ends of the tRNAs (fig. S18). Ten unique
21-nt tRFs, each with a relative abundance of >100 counts per
million rhizobial small RNA reads in the common bean nod-
ules, were predicted to target 14 common bean genes, includ-
ing genes encoding a protein kinase, a GRAS transcription
factor, and an APETALA2-like transcription factor that may
be involved in nodulation regulation (table S3) (18). Never-
theless, none of these 14 putative R. etli tRF targets in com-
mon bean are orthologs of the 25 putative B. japonicum tRF
targets in soybean (table S1).
We demonstrate that rhizobial tRFs are positive regula-
tors of rhizobial infection and nodule formation in soybean,
thereby playing an important role in balancing plant growth
and symbiosis (fig. S19). In addition to the three rhizobial
tRFs we investigated, other rhizobial tRFs were predicted to
target soybean genes annotated to encode auxin receptors
and efflux carriers, RING/U-box proteins, and protein kinases
(table S1), which may also affect nodulation (19). Such cross-
kingdom communications may be common among symbiotic
partners, but the nodes of rhizobial tRFs-host gene interac-
tions appear to be diverse.
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ACKNOWLEDGMENTS
We thank D. Yu for the pSC1 vector, and B. C. Meyers for suggestions. Funding: This
work was partially supported by the Agriculture and Food Research Initiative of
the USDA National Institute of Food and Agriculture (grant nos. 2015-67013-
22811 and 2018-67013-27425), Purdue AgSEED program, North Central
Soybean Research Program, and Indiana Soybean Alliance. Author
contributions: B.R., X.W., and J.D. performed the research, B.R., X.W., and J.M.
analyzed the data, and J.M. designed the research and wrote the manuscript
with input from B.R., X.W., and J.D. Competing interests: This work has been
filed for a U.S. Provisional Patent Application. Data and materials availability:
All data are available in NCBI (accession no. SRR7986781 to SRR7986788, and
SRR7985373), main text, or supplementary materials.
SUPPLEMENTARY MATERIALS
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Materials and Methods
Figs. S1 to S19
Tables S1 to S4
References (2042)
30 October 2018; resubmitted 22 April 2019
Accepted 10 July 2019
Published online 25 July 2019
10.1126/science.aav8907
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Fig. 1. Rhizobial tRFs and their
putative target genes in soybean.
(
A
) Origins of three rhizobial tRFs.
Anticodons in corresponding tRNAs
are colored in blue. (
B
) Abundance of
the three tRFs, measured by stem-
loop-qRT-PCR, in free-living
Bradyrhizobium japonicum (B. j.)
USDA110 (1), and 10-d and 20-d post
inoculation (dpi) nodules (2 and 3,
respectively). (
C
) Expression of the
putative tRF target genes, measured
by qRT-PCR, in the 10-d and 20-d
nodules (2 and 4) and uninoculated
soybean roots (1 and 3). Values in (B)
and (C), with one set as “1” and the
others adjusted accordingly, are
shown as means ± standard errors
(s.e.) from three biological replicates.
Asterisks indicate the significance
level at P<0.01 (t-test). (
D
) The three
tRFs, their putative target transcripts,
and the cleavage sites and
frequencies (indicated by arrows and
ratios) detected in the 20-dpi
nodules.
on July 25, 2019 http://science.sciencemag.org/Downloaded from
First release: 25 July 2019 www.sciencemag.org (Page numbers not final at time of first release) 6
(
)
targets by CRISPR-
numbers. (
) Overexpression (OX)
of the putative tRF targets resulted
in decreased nodule numbers. (
)
Silencing of individual tRFs by STTM
numbers. (
) Nodule numbers, with
all data points represented by dots,
are shown as box and whisker plots
displaying 95%-
three biological replicates (12 plants
Controls are transgenic roots of
empty vectors used for the CRISPR-
Cas9 knockouts, the gene-
overexpression roots, and the STTM
tRF-
Asterisks indicate the significance
level of P < 0.01 (t-test).
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Fig. 3. Rhizobial tRF-guided gene regulation by hijacking the
host RNAi machinery.
(
A) Abundance of artificial miRNAs
measured by stem-loop-qRT-PCR in aMIR-tRF001 (2) and aMIR-
tRF003 transgenic roots (3) and respective empty-vector
transgenic roots (1) 28 dpi. (
B
) Expression of the putative
tRF/artificial miRNA targets measured by qRT-PCR in the same
samples as described in (A). Values in (A) and (B), with one set as
“1” and the others adjusted accordingly, are shown as means ± s.e.
from three biological replicates. Asterisks indicate the significance
level at P < 0.01 (t-test). (
C
) Nodule numbers in the same samples
as described in (A), with all data points represented by dots, are
shown as box and whisker plots displaying 95%-5% interval from
three biological replicates (12 plants per replicate). (
D
) GFP
activity in transgenic roots of “GFP-tRF target site” fusion genes
(W1-W3) and “GFP-mutated tRF target site” fusion genes (M1-M3)
24 hours post inoculation with USDA110. Bj- and Bj+ indicate
uninoculated and inoculated roots, respectively. (
E
) Association of
the three tRFs with soybean GmAGO1b in 28-dpi nodules detected
from three experimental replicates. “+” and “−” indicate the
GmAGO1b-Myc fusion protein-
associated fraction
immunoprecipitated by the Myc antibody and the nodule lysate
without Myc antibody incubation, respectively.
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Fig. 4. Modulation of early-stage
rhizobial infection by rhizobial tRFs
and their targets in soybean.
(
A
)
and (
B) Morphological differences
between the root hairs
overexpressing the rhizobial tRF
targets and the negative control, and
between the STTM root hairs
inhibiting the rhizobial tRF function
and the negative control. (
C
)
Quantitation of deformed root hairs
and curled root hairs with infection
foci in samples as exemplified in (A)
and (B). The values are shown as
means ± s.d. from three biological
replicates (n = 25 per replicates).
Asterisks indicate the significant level
at P < 0.05 (t-test).
on July 25, 2019 http://science.sciencemag.org/Downloaded from
Rhizobial tRNA-derived small RNAs are signal molecules regulating plant nodulation
Bo Ren, Xutong Wang, Jingbo Duan and Jianxin Ma
published online July 25, 2019
ARTICLE TOOLS http://science.sciencemag.org/content/early/2019/07/24/science.aav8907
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... This phenomenon has since been observed later in many different interacting organisms. For example, other plant fungal pathogens (such as Fusarium oxysporum, Verticillium dahliae), oomycete pathogens (such as Hyaloperonospora arabidopsidis), the parasitic plant Cuscuta campestris, and even the symbiotic ectomycorrhizal fungus Pisolithus microcarpus and the bacterial symbiont Rhizobium (Bradyrhizobium japonicum) can send a set of sRNAs into the host plant to silence the expression of host target genes (Dunker et al., 2020, Shahid et al., 2018, Ren et al., 2019, Wong-Bajracharya et al., 2022, Ji et al., 2021, Zhang et al., 2022. Furthermore, the mode of action of transferred microbial sRNAs seems also to be conserved. ...
... Furthermore, the mode of action of transferred microbial sRNAs seems also to be conserved. The sRNAs from F. oxysporum (Ji et al., 2021), V. dahliae (Wang et al., 2016), H. arabidopsidis (Dunker et al., 2020) and the Rhizobium (Ren et al., 2019) also utilize host AGO proteins for silencing host target genes. Excitingly, cross-kingdom or cross-species RNAi has also been observed in animal-pathogen or parasite interaction systems. ...
... Bc-siR3.2 and Bc-siR5 were detected by a stem-loop RT-PCR method. The same molecular mechanism was also found in plant pathogens F. oxysporum, V. dahliae, H. arabidopsidis, animal fungal pathogen Beauveria bassiana and even in beneficial bacterial symbiont Rhizobium during cross-kingdom RNAi with their hosts (Ji et al., 2021, Zhang et al., 2022, Dunker et al., 2020, Ren et al., 2019. The sRNAs from these microbes are loaded into host AGO proteins to silence host target genes. ...
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Cross-kingdom or cross-species RNA interference (RNAi) is broadly present in many interacting systems between microbes/parasites and their plant and animal hosts. Recent study by Qin et al. (2022) performed correlation analysis using global sRNA- and mRNA-deep sequencing data of cultured B. cinerea and B. cinerea-infected tomato leaves and claimed that cross kingdom RNAi may not occur in B. cinerea tomato interaction (Qin et al., 2022). In this response letter, we use experimental evidence and additional bioinformatics analysis of the datasets produced by Qin et al. (2022) to identify the key reasons why a discrepancy with previously published findings occurred. Here, we also provided additional experimental evidence to support the presence of cross-kingdom RNAi between tomato and B. cinerea. We believe it is important to clarify the basic concept and mechanism of cross-kingdom/cross-species sRNA trafficking and illustrate proper bioinformatics analyses in this regard for all the scientists and researchers in this field.
... The functional conservation of tsRNAs between plants and animals could be partially due to their similarity in biogenesis processes, inferring their key role in evolution. Interestingly, cross-kingdom regulation by tsRNAs has also been discovered in plant recently (Ren et al., 2019;Cao et al., 2022) (Figure 1). ...
... Remarkably, the crosskingdom communication of tsRNAs was observed between rhizobial and its host soybean. Rhizobial tRFs can transfer to soybean roots and hijack the host RNAi machinery to silence key host genes, thus enhancing nodulation in soybean (Ren et al., 2019). ...
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tRNA-derived small RNAs (tsRNAs) represent a novel category of small non-coding RNAs and serve as a new regulator of gene expression at both transcriptional and post-transcriptional levels. Growing evidence indicates that tsRNAs can be induced by diverse stimuli and regulate stress-responsive target genes, allowing plants to adapt to unfavorable environments. Here, we discuss the latest developments about the biogenesis and classification of tsRNAs and highlight the expression regulation and potential function of tsRNAs in plant biotic and abiotic stress responses. Of note, we also collect useful bioinformatics tools and resources for tsRNAs study in plants. Finally, we propose current limitations and future directions for plant tsRNAs research. These recent discoveries have refined our understanding of whether and how tsRNAs enhance plant stress tolerance.
... The expression of extracellular RNase T2 in response to stress correlates with the accumulation of tRFs (Alves et al., 2017;Megel et al., 2019), suggesting a regulatory role of extracellularly produced tRFs in this process. Like siRNAs and miRNAs, tRNA-derived fragments are also loaded into AGO proteins and regulate gene expression in plants, oomycetes and animals (Alves et al., 2017;Kumar et al., 2014;Loss-Morais et al., 2013;Ren et al., 2019;Wang et al., 2016b). For instance, tRFs have been shown to mediate trans-kingdom gene silencing between Rhizobia and soybean. ...
... For instance, tRFs have been shown to mediate trans-kingdom gene silencing between Rhizobia and soybean. Rhizobial tRFs produced by proccesing of tRNA Gly , tRNA Gln and tRNA Val associate with soybean AGO1 to catalyze tRF-guided cleavage of target mRNAs in soybean to promote nodulation (Ren et al., 2019). Although direct evidence of a role for plant extracellular tRFs in cross-kingdom gene silencing is lacking, the high accumulation of tRFs in the leaf apoplast tempt us to speculate that this is likely. ...
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Extracellular RNA (exRNA) has long been considered as cellular waste that plants can degrade and utilize to recycle nutrients. However, recent findings highlight the need to reconsider the biological significance of RNAs found outside of plant cells. A handful of studies suggest that the exRNA repertoire, which turns out to be an extremely heterogenous group of non-coding RNAs, comprises species as small as a dozen nucleotides to hundreds of nucleotides long. They are found mostly in free form or associated with RNA-binding proteins, while very few are found inside extracellular vesicles (EVs). Despite their low abundance, small RNAs associated with EVs have been a focus of exRNA research due to their putative role in mediating transkingdom RNA interference. Therefore, non-vesicular exRNAs have remained completely under the radar until very recently. Here we summarize our current knowledge of the RNA species that constitute the extracellular RNAome and discuss mechanisms that could explain the diversity of exRNAs, focusing not only on the potential mechanisms involved in RNA secretion but also on post-release processing of exRNAs. We will also share our thoughts on the putative roles of vesicular and extravesicular exRNAs in plant-pathogen interactions, intercellular communication, and other physiological processes in plants.
... Based on scattered genetic and molecular biological evidence, a general picture of extensive recruitment of core and accessory functions, in addition to key nodulation and nitrogen fixation genes, in optimizing symbiotic efficiency has been proposed earlier [16,17]. The list of core and accessory functions contributing to rhizobial fitness, from rhizosphere to rhizoplane to nodules, is ever-increasing (above 900 genes) and usually in a strain-host-dependent manner [52], e.g., motility and chemotaxis [124], surface polysaccharides [125][126][127][128][129], outer membrane vesicles [130], quorum sensing [131][132][133][134][135], T1SS, T3SS, T4SS and T6SS [136][137][138][139][140][141][142], dicarboxylate transport [143], poly-3-hydroxybutyrate [144][145][146], transporters of branched amino acids [147][148][149], uptake of ions (phosphorus [150][151][152], potassium [153,154], molybdenum [155], iron [156,157], sulfur [155], zinc [94] and manganese [158]), nitrate reduction [40], NO modulation [159,160], oxygen limitation responses [40,[161][162][163], cell cycle [164][165][166], peptide importers [167][168][169][170][171], regulatory non-coding RNAs (e.g., globally acting trans-small RNA AbcR1/2 and those fragments derived from transfer RNA) [172,173] and carbon-nitrogen metabolism coordination by nitrogen-related phosphotransferase system [153,174,175]. These efforts indicate that the successful integration of key nodulation and nitrogen fixation circuits in various bacterial recipients involves systematic and dynamic coordination with other functions during the establishment of symbiosis. ...
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... arabidopsidis 16 , an animal fungal pathogen Beauveria bassiana of mosqiuito 17 , a bacterial pathogen 19 and even symbiotic microbes, such as ectomycorrhizal fungus Pisolithus microcarpus 20 and Rhizobium (Bradyrhizobium japonicum) 21 , also utilize host Argonaute proteins for crosskingdom RNAi. The biogenesis of these pathogen sRNAs involved in cross-kingdom RNAi are also largely dependent on pathogen DCL proteins [7][8]10,15,[22][23][24][25][26] . ...
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... arabidopsidis 16 , an animal fungal pathogen Beauveria bassiana of mosqiuito 17 , a bacterial pathogen 19 and even symbiotic microbes, such as ectomycorrhizal fungus Pisolithus microcarpus 20 and Rhizobium (Bradyrhizobium japonicum) 21 , also utilize host Argonaute proteins for crosskingdom RNAi. The biogenesis of these pathogen sRNAs involved in cross-kingdom RNAi are also largely dependent on pathogen DCL proteins [7][8]10,15,[22][23][24][25][26] . ...
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Global demand to increase food production and simultaneously reduce synthetic nitrogen‐fertiliser inputs in agriculture are underpinning the need to intensify the use of legume crops. The symbiotic relationship that legume plants establish with nitrogen‐fixing rhizobia bacteria is central to their advantage. This plant‐microbe interaction results in newly developed root organs, called nodules, where the rhizobia convert atmospheric nitrogen gas into forms of nitrogen the plant can use. However, the process of developing and maintaining nodules is resource‐intensive; hence, the plant tightly controls the number of nodules forming. A variety of molecular mechanisms are used to regulate nodule numbers under both favourable and stressful growing conditions, enabling the plant to conserve resources and optimise development in response to a range of circumstances. Using genetic and genomic approaches, many components acting in the regulation of nodulation have now been identified. Discovering and functionally characterising these components can provide genetic targets and polymorphic markers that aid in the selection of superior legume cultivars and rhizobia strains that benefit agricultural sustainability and food security. This review addresses recent findings in nodulation control, presents detailed models of the molecular mechanisms driving these processes and identifies gaps in these processes that are not yet fully explained.
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