Natural Variation in Biogene

Current Biology 22, 166–170, January 24, 2012 ª2012 Elsevier Ltd All rights reserved DOI 10.1016/j.cub.2011.11.060

Reportsis

Efficiency of IndividualArabidopsis thaliana MicroRNAs

Marco Todesco,1 Sureshkumar Balasubramanian,1,4

Jun Cao,1 Felix Ott,1 Sridevi Sureshkumar,1,4

Korbinian Schneeberger,1,5 Rhonda Christiane Meyer,2,3

Thomas Altmann,2,3 and Detlef Weigel1,*1Department of Molecular Biology, Max Planck Institutefor Developmental Biology, 72076 Tubingen, Germany2Max-Planck Institute for Molecular Plant Physiology,14476 Potsdam-Golm, Germany3Leibniz-Institute of Plant Genetics and Crop Plant Research(IPK), 06466 Gatersleben, Germany

Summary

Like protein-coding genes, loci that produce microRNAs

(miRNAs) are generally considered to be under purifyingselection [1–3], consistent with miRNA polymorphisms

being able to cause disease [4]. Nevertheless, it has beenhypothesized that variation in miRNA genes may contribute

to phenotypic diversity [1, 3, 5, 6]. Here we demonstrate thata naturally occurring polymorphism in the MIR164A gene

affects leaf shape and shoot architecture in Arabidopsisthaliana, with the effects being modified by additional loci

in the genome. A single base pair substitution in the miRNAcomplementary sequence alters the predicted stability of the

miRNA:miRNA* duplex. It thereby greatly reduces miRNAaccumulation, probably because it interferes with precursor

processing. We demonstrate that this is not a rare exception

and that natural strains of Arabidopsis thaliana harbordozens of similar polymorphisms that affect processing

of a wide range of miRNA precursors. Our results suggestthat natural variation in miRNA biogenesis resulting from

cis mutations is a common contributor to phenotypic varia-tion in plants.

Results and Discussion

Allelic Variation at MIR164A Affects Leaf Development

and Shoot ArchitectureGenetic differences between individuals are sometimes re-vealed only in specific environments or genomic backgrounds.Such cryptic variation can determine the consequences ofboth deleterious and beneficial second-site mutations andaffects the success of breeding programs [7–9]. This type ofvariation is revealed when progeny show a wider phenotypicrange than their ancestors. A striking case of such trans-gressive segregation was observed in a recombinant inbredline (RIL) population obtained from a cross between theCol-0 and C24 strains of Arabidopsis thaliana [10]. The grand-parents had leaves with just a few indentations in their margins(Figure 1A), but the RIL population contained individuals with

4Present address: School of Biological Sciences, Monash University, VIC

3800, Australia5Present address: Department of Plant Developmental Biology, Max Planck

Institute for Plant Breeding Research, 50829 Cologne, Germany

*Correspondence: weigel@weigelworld.org

deeply serrated leaves, as well as ones with completelysmooth leaf margins. Quantitative trait locus (QTL) mappingidentified two major regions affecting this trait, on chromo-somes 2 and 4 (Figure 1B). Alleles at these loci had oppositeeffects, explaining the moderate levels of leaf serrationin either grandparent. Additional minor peaks suggested acomplex genetic architecture for this trait (Figure S1A; TableS1 available online).Several introgression lines (ILs) [11] confirmed both major

QTL. The chromosome 2 QTL was clearest, with ILs carryinga C24 segment introgressed into Col-0 having enhancedserration (Col-ILQTL2_C24), and the opposite type havingsmooth leaf margins (C24-ILQTL2_Col-0; Figures 1C and S1C).The location of the QTL was refined to a region of about 80genes. Among them wasMIR164A, one of three genes codingfor miR164, a miRNA targeting transcription factors of theCUP-SHAPED COTYLEDONS (CUC)/NO APICAL MERISTEM(NAM) family [12]. MIR164A suppresses CUC2, and inacti-vation of MIR164A in the Col-0 miR164a-4 allele causesdeep leaf serration [13] (Figure 1C). In test crosses, theMIR164AC24 allele did not complement the miR164a-4 muta-tion in Col-0, consistent with this allele being responsible forthe chromosome 2 QTL (Figures 1C and S1C). MIR164A alsosuppresses the production of normally dormant accessorybuds [14], which can elongate after the primary lateral shootin a leaf axil is removed [15] (Figure 1D). Col-ILQTL2_C24 lineshad more accessory buds than did Col-0, similar to themiR164a-4 mutant; conversely, C24-ILQTL2_Col-0 lines hadfewer accessory buds than did C24 (Figure 1E). Furthermore,only constitutive expression of MIR164ACol-0, but notMIR164AC24, conferred the known overexpression pheno-types of smooth leaf margins with occasional organ fusions[16, 17], thereby suppressing the miR164a-4 defects (Figures2A and S2A). Accordingly, CUC2 transcripts were more abun-dant inmiR164a-4 and Col-ILQTL2_C24 plants than in Col-0, andthey were strongly reduced only upon overexpression of theMIR164ACol-0 allele (Figure S2B). This further supports allelicdifferences at MIR164A as being causal for the chromosome2 QTL. A caveat to the overexpression experiments is thatthe miRNA processing machinery might become saturated,which could affect the rate of miRNA processing. However,the absence of shared pleiotropic effects from overexpressingdifferent miRNAs or overexpressing defective miRNA precur-sors argues against such a scenario (e.g., [18–22]).

A Causal Polymorphism in the Complement of the Mature

miRNAmiRNAs typically originate from primary MIRNA transcripts(pri-miRNA) that are processed by DICER-LIKE 1 (DCL1) [23].Constitutive expression of MIR164ACol-0 and MIR164AC24

resulted in similar levels of pri-miR164a but only plantsexpressing MIR164ACol-0 had increased levels of maturemiR164 (Figures 2B and 2C), independently of the geneticbackground (Figures S2C and S2D). These observationssuggest that the lower activity of MIR164AC24 is due toreduced accumulation of the miRNA. Sequencing of the smallRNA population of transgenic plants revealed that theMIR164AC24 and MIR164ACol-0 precursors produced a similar

A B

E

F

G

C

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Figure 2. Defective Processing of MIR164AC24

(A) miR164a-4 plants overexpressing the MIR164ACol-0 or MIR164AC24

allele.

(B) Pri-miR164a levels. The two transgenic lines in the miR164a-4 back-

ground are not significantly different (p = 0.88). Standard errors of the

mean are indicated.

(C) Mature miR164 inmiR164a-4 plants overexpressing theMIR164ACol-0 or

MIR164AC24 allele (four independent lines each). The effects of miR164a-4

are masked by expression from the MIR164B and MIR164C paralogs.

(D) Small RNA populations mapping to the transcribed strand of the

MIR164A locus in plants expressing MIR164ACol-0 orMIR164AC24, or plants

transformed with empty expression vector.

(E) Base pairing in the miR164a precursor, with miRNA in red and miRNA*

in blue. At position *2, the alternative C24 allele is shown in orange.

(F) Introduction of the C24 SNP intoMIR164ACol-0 (‘‘MIR164A*2U’’) abolishes

miRNA overproduction (RNA pooled from eight independent primary trans-

formants).

(G) miR164a-4 plant overexpressing MIR164A*2U.

Scale bars represent 1 cm. See also Figure S2 and Tables S2 and S3.

miR164a-4

C24Col-0

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ED

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X miR164a-4

0

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Figure 1. Identification of QTL Affecting Leaf Serration and Accessory Bud

Formation

(A) 6-week-old short-day grown plants. A representative adult leaf is out-

lined for each plant. Cumulative serration depth (‘‘Serr,’’ see Supplemental

Experimental Procedures and Figure S1B) averaged from ten leaves is re-

ported for each genotype.

(B) QTL map for leaf serration in Col-03 C24 RILs. Red line indicates signif-

icance threshold, and ticks genetic markers.

(C) Complementation test.

(D) Col-0 plants (left) often lack dormant buds in the axils of secondary

shoots. Such a bud is present in the SN33/2 NIL (right).

(E) Secondary shoots with accessory buds in long-day grown plants. Differ-

ences between the four groups are significant at p < 0.05.

Scale bars represent 1 cm. See also Figure S1 and Table S1.

Natural Variation in miRNA Biogenesis167

spectrum of small RNAs, but much less miR164 and miR164*were generated from the MIR164AC24 precursor (Figure 2D).One explanation is inefficient processing of the MIR164AC24

precursor by the DCL1 complex. Other scenarios are reducedstability or less efficient nuclear export of the miRNA:miRNA*complex, which may lead to enhanced degradation of theduplex before the miRNA becomes associated with AGO1.Similarly, less efficient incorporation of the miRNA into AGO1because of the altered miRNA:miRNA* structure may increasedegradation.

The experiments presented above indicated that changesin the MIR164AC24 precursor interfered with accumulationof mature miRNA and miRNA*. At the sequence level, theCol-0 and C24 alleles are differentiated by only a few single-nucleotide polymorphisms (SNPs; Table S2). One affects a Cin themiRNA* that is paired with a G at position 2 of the maturemiRNA (this position will henceforth be referred to as *2)(Figure 2E). The replacement of a G:C in MIR164ACol-0 witha non-Watson-Crick G:U pair inMIR164AC24 slightly increasesthe calculated free energy of the foldback from 265.3 to262.9 kcal/mol, but should notmodify the secondary structureof MIR164A (Figure S2E). Nevertheless, altered miRNA-miRNA* base pairing can affect miRNA processing in animalsand viruses [24–27] and has been associated with cancer

[28, 29], cardiomyopathy [30, 31], and schizophrenia [27].Consistent with this SNP being causal for the reduced activityof MIR164AC24, introducing it into MIR164ACol-0 greatlycompromised miR164 accumulation in overexpressors (Fig-ures 2F and 2G). In humans, a similar SNP in pre-miR146aleads to the production of two different miRNAs from thepassenger strand (miR146a*G and miR146a*C), which havebeen proposed to target different sets [32]. In the MIR164Acase, a role of the miRNA* itself is unlikely, because thephenotype conferred by MIR164AC24 matched that of themiR164a-4 mutant in Col-0. Moreover, miR164a* does notseem to be loaded into AGO1 protein [33], and the few low-confidence targets predicted for miR164a* would not begreatly affected by the C24 SNP (Table S3).Because the C24 mutation was predicted to have only a

subtle effect on pri-miRNA structure, we wanted to knowwhether it was in an unusually sensitive position. We replacedG:Cwith G:U pairs in other positions of pri-miR164A by individ-ually mutating all Cs paired to Gs in the mature miRNA. Allmutations strongly reduced miRNA production, and none of

A B

C

D

E F G

Figure 3. Effects of Partial and Complete Mismatches at Different Positions

and in Different miRNAs

(A) Diagram of G:C pairs changed to G:U wobble pairs inMIR164A and their

effects in a miR164a-4 background.

(B) Effects of introducing of a G:U pair at position *2 into MIR164B (RNA

pooled from eight independent primary transformants).

(C) miR164a-4 plants expressing different versions of MIR164B. Scale bar

represents 1 cm.

(D) miRNA expression in Col-0 plants transformed with different versions of

MIR156B, MIR172A, and MIR167A.

(E) Leaf initiation rate of plants expressing different versions of MIR156B.

Only MIR156BCol-0 plants are significantly different from the other lines at

p < 0.05 (n R 14).

(F) Flowering time of plants expressing different versions of MIR172A. All

differences but the one between MIR172A*2U and MIR172A*2A are signifi-

cant at p < 0.05 (n R 14).

(G) Classification of plants expressing different versions of MIR167A. Mild

symptoms are irregular, epinastic leaves; severe symptoms include delayed

flower anthesis. All differences but the one between Col-0 and MIR167A*2A

are significant at p < 0.05 (n R 14).

Standard errors of the mean are indicated. See also Figure S3 and Table S4.

Current Biology Vol 22 No 2168

the corresponding transgenes could suppress the miR164a-4phenotype, although miRNA activity seemed less affected bymutations closer to the center of the miRNA (Figure 3A). Wealso tested whether similar effects could be observed forother miRNAs. When the C24 mutation in MIR164A wasintroduced into MIR164B, much less miRNA accumulated inoverexpressors (Figure 3B), and the modified MIR164Btransgene no longer suppressed themiR164a-4 mutation (Fig-ure 3C). We then selected three unrelated MIRNA genes,MIR156B, MIR172A, and MIR167A, which produce distinctoverexpression phenotypes and the precursors of whichhave, like MIR164A, G:C pairs at position *2 (Figure S3A).Changing G:C to G:U pairs reduced miRNA accumulation inall cases. Compared to other mismatches, G:U wobble pairsare thermodynamically relatively stable and have unique

chemical properties [34]; consistent with this, introduction ofa fully mismatched G:A pair at position *2 further affectedmiRNA production (Figure 3D). The phenotypic effects werelargely proportional to the amount ofmaturemiRNAproduced,with the modified transgenes causing milder phenotypicalterations than the unmodified versions (Figures 3E–3G,S3B, and S3C; Table S4). Thus, both context and mismatchtype appear to be important for the consequences of alteredpairing in the miRNA precursor, consistent with previousobservations [19–22].

Effects of Polymorphisms in Other miRNA PrecursorsHow frequent are MIR164AC24-type polymorphisms in naturalstrains of A. thaliana? Analysis of 96 strains (accessions)from throughout the species range revealed that theMIR164AC24 polymorphism was unique, but a polymorphismat position *11 was found in 44 accessions. In this case,a G:U pair was replaced by a G:C pair (Figure 4A). Overexpres-sion of a natural allele with this polymorphism, MIR164ASha,indicated that it was at least as efficient in producing miR164as was the reference allele. Similar results were obtainedwhen this SNP was engineered into the Col-0 allele ofMIR164A. It could also partially suppress the negative effectof the C24 SNP when present in the same precursor (Figures4B and S4A).We then extended our analysis to other miRNA genes by

using whole-genome data for 80 accessions [35]. Of 190miRNA genes in miRBase [36], 65 were polymorphic, with105 SNPs in the sequence complementary to the maturemiRNA. The miRNA sequences themselves had 110 SNPs in60 genes (Figures 4C and S4B), in agreement with a previouscomparison of complex changes in miRNAs and their comple-ments [37]. These observations suggest similar functionalconstraints for miRNA and miRNA* sequences. Derived allelefrequencies are also similar, with SNPs being on average rarerthan polymorphisms in other portions of the miRNA precursor,indicative of stronger purifying selection in miRNAs andmiRNA*s (Figure 4D).Most of the 105 SNPs in the miRNA complementary

sequences, 94 in 60 genes, were predicted to modify basepairing in the miRNA foldback. We engineered several ofthese polymorphisms into the reference allele. In all cases,disrupting paired bases reducedmiRNAproduction in an over-expression assay, and improving base pairing increasedmiRNA accumulation, with corresponding effects on whole-plant phenotypes (Figures 4E and S4C–S4F). Although thiswas generally also the case when the complete natural alleleswere overexpressed, therewere exceptions. SNPs inMIR160BandMIR842 disrupt paired bases in themiRNA:miRNA* duplexand would thus be expected to reduce miRNA production, asobserved for the engineered alleles with single SNPs in thereference background. Instead, mature miRNAs accumulatedto higher levels. We conclude that additional SNPs and shortinsertions/deletions throughout the MIR160B and MIR842foldbacks can compensate for mutations affecting themiRNA:miRNA* duplex, consistent with such polymorphismsbeing able to affect MIRNA activity (J. Hu and J. de Meaux,personal communication).In conclusion, we have demonstrated that A. thaliana

miRNA:miRNA* duplexes feature a high number of naturalpolymorphisms that can affect base pairing and thus reduceaccumulation of mature miRNAs. In analogy with a case fromherpes virus [25], we favor impaired processability of themiRNA:miRNA* duplex as the most likely explanation,

Col

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IR84

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A BAUGUUGGAGAAG GGG ACGUGCAAA CA C

UACAACCUCUUC U C UGCACGUUU AA C

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Derived allele frequencies

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back

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stre

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own-

stre

am

+ ++

+ +

Figure 4. Natural Polymorphisms Affecting miRNA Processing

(A) Base pairing in the folded miR164a precursor. At position *11, the alter-

native Sha allele is shown in purple.

(B) miR164 expression. MIR164ASha plants are from the Sha strain.

MIR164A*11C is the reference allele with only the Sha SNP in the miRNA*,

whereas MIR164A*2U,11C includes the C24 SNP.

(C) SNP density across 196 MIRNA loci in 80 A. thaliana genomes [35]. The

miRNA and its complement are compared to the rest of the foldback and to

200 bp regions upstream or downstream. Black crosses represent means.

Differences between the three groups are significant at p < 0.05.

(D) Derived allele frequencies, assuming that the base in the reference

genome of A. lyrata reflects the ancestral state [39].

(E) miRNA levels in plants overexpressing either the reference alleles, the

reference alleles with individual SNPs introduced into the miRNA*, or the

naturally polymorphic alleles. For MIR169M, two modified Col-0 alleles

are shown. RNAwas pooled from eight independent primary transformants.

SNPs at positions indicated as red superscripts repair mismatches with

respect to the Col-0 reference allele.

See also Figure S4.

Natural Variation in miRNA Biogenesis169

although reduced stability after DCL1 processing is a possi-bility. The consequences at the level of the entire organismwill depend on the genetic background, as demonstratedfor MIR164A. There are many polymorphisms in maturemiRNA sequences as well; this variation can doubly impactmiRNA function, either by modifying base pairing andthus miRNA biogenesis or by modifying the targeting speci-ficity of the miRNA itself [24]. An additional level of miRNAregulation are expression differences, as recently revealedby interspecific comparison of the MIR163 gene betweenA. thaliana and its relative A. arenosa [38]. Together, thesefindings highlight the potential for sequence variation at plantmiRNA loci as raw material for phenotypic evolution andadaptation.

Accession Numbers

The EBI short read archive accession number for the small RNA libraries

sequencing data reported in this paper have been deposited in NCBI

GEO, accession number GSE32927.

Supplemental Information

Supplemental Information includes Supplemental Experimental Procedures

(details about growth conditions and phenotyping and information about

transgenic lines and RNA analysis), four figures, and four tables and can

be found with this article online at doi:10.1016/j.cub.2011.11.060.

Acknowledgments

We thank Felipe Fenselau de Felippes, Christa Lanz, and Sascha Laubinger

for help with small RNA sequencing and Juliette de Meaux and Pablo

Manavella for discussion and communication of unpublished results. This

work was supported by an EMBO long-term fellowship (S.B.), by European

Community FP6 IPs SIROCCO (contract LSHG-CT-2006-037900, D.W.)

and AGRON-OMICS (contract LSHG-CT-2006-037704, T.A. and D.W.),

a Gottfried Wilhelm Leibniz Award of the DFG, and the Max Planck Society

(D.W.).

Received: July 26, 2011

Revised: October 28, 2011

Accepted: November 29, 2011

Published online: December 29, 2011

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