Natural Variation in RNA m6A Methylation and Its ......Natural Variation in RNA m6A Methylation and Its Relationship with Translational Status1[OPEN] Jin-Hong Luo,a,b,2 Ye Wang,c,2

Natural Variation in RNA m6A Methylation and ItsRelationship with Translational Status1[OPEN]

Jin-Hong Luo,a,b,2 Ye Wang,c,2 Min Wang,b,2 Li-Yuan Zhang,d Hui-Ru Peng,d Yu-Yi Zhou,e,3 Gui-Fang Jia,c,3

and Yan Heb,3,4

aState Key Laboratory of Plant Physiology and Biochemistry, College of Biological Sciences, China AgriculturalUniversity, Beijing 100094, ChinabJoint Laboratory for International Cooperation in Crop Molecular Breeding, Ministry of Education, NationalMaize Improvement Center, China Agricultural University, Beijing 100094, ChinacSynthetic and Functional Biomolecules Center, Beijing National Laboratory for Molecular Sciences, KeyLaboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, College ofChemistry and Molecular Engineering, Peking University, Beijing 100871, ChinadBeijing Key Laboratory of Crop Genetic Improvement, Department of Plant Genetics and Breeding, ChinaAgricultural University, Beijing 100094, ChinaeState Key Laboratory of Plant Physiology and Biochemistry, College of Agronomy and Biotechnology, ChinaAgricultural University, Beijing 100094, China

ORCID IDs: 0000-0003-4475-8350 (Y.-Y.Z.); 0000-0002-4186-6922 (G.-F.J.); 0000-0003-3640-8502 (Y.H.).

N6-methyladenosine (m6A) is the most abundant modification of eukaryotic mRNA. Although m6A has been demonstrated toaffect almost all aspects of RNA metabolism, its global contribution to the post-transcriptional balancing of translational efficiencyremains elusive in plants. In this study, we performed a parallel analysis of the transcriptome-wide mRNA m6A distribution andpolysome profiling in two maize (Zea mays) inbred lines to assess the global correlation of m6A modification with translational status.m6A sites are widely distributed in thousands of protein-coding genes, confined to a consensus motif and primarily enriched in the 39untranslated regions, and highly coordinated with alternative polyadenylation usage, suggesting a role of m6A modification inregulating alternative polyadenylation site choice. More importantly, we identified that the m6A modification shows multifacetedcorrelations with the translational status depending on its strength and genic location. Moreover, we observed a substantialintraspecies variation in m6A modification, and this natural variation was shown to be partly driven by gene-specific expressionand alternative splicing. Together, these findings provide an invaluable resource for ascertaining transcripts that are subject to m6Amodification in maize and pave the way to a better understanding of natural m6A variation in mediating gene expression regulation.

N6-methyladenosine (m6A) is the most prevalent andphysiologically relevant mRNA modification and iscurrently the best example of a complete epitran-scriptomic system with known writer (Zhong et al.,2008; Liu et al., 2014; Ping et al., 2014; Schwartz et al.,

2014; Shen et al., 2016; Mendel et al., 2018; Yue et al.,2018, 2019), reader (Wang et al., 2014a, 2015; Xiao et al.,2016; Li et al., 2017; Shi et al., 2017; Arribas-Hernándezet al., 2018; Huang et al., 2018; Scutenaire et al., 2018;Wei et al., 2018; Wu et al., 2018), and eraser proteins (Jiaet al., 2011; Zheng et al., 2013; Duan et al., 2017) in bothplants andmammals.m6A has been demonstrated to beessential for the earliest stages of cell fate determinationand cell differentiation in plants (Bodi et al., 2012;Shen et al., 2016), metazoans (Yue et al., 2015;Haussmann et al., 2016; Lence et al., 2016), and mam-mals (Wang et al., 2014b; Geula et al., 2015; Hsu et al.,2017), and is linked with diseases in humans (Homosapiens) and other mammalian species (Jia et al., 2011;Zheng et al., 2013; Lin et al., 2016; Cui et al., 2017; Yoonet al., 2017; Zhang et al., 2017a; Wang et al., 2018) aswell as required for yeast (Saccharomyces cerevisiae) andmice (mus musculus) meiosis (Zheng et al., 2013; Bodiet al., 2015; Xu et al., 2017). Reduced levels of m6A alsoaffect the circadian period in mice (Fustin et al., 2013),and lead to partial infertility in Drosophila (Lence et al.,2016; Kan et al., 2017).

1This work was supported by the National Key Research and De-velopment Program of China (2016YFD0101201 and 2017YFD0101104to Y.H.).

2These authors contributed equally to this work.3Senior authors.4Author for contact: [email protected] author responsible for distribution of materials integral to the

findings presented in this article in accordance with the policy de-scribed in the Instructions for Authors (www.plantphysiol.org) is:Yan He ([email protected]).

Y.Y.Z., G.F.J., and Y.H. conceived and supervised the project;J.H.L., Y.W., and M.W. conducted experiments; J.H.L., L.Y.Z., andH.R.P. performed bioinformatics and statistical analyses; manuscriptwas prepared by J.H.L. and Y.H.; all authors read and approved thefinal manuscript.

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332 Plant Physiology�, January 2020, Vol. 182, pp. 332–344, www.plantphysiol.org � 2020 American Society of Plant Biologists. All Rights Reserved.

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m6Amediates its physiological effects by influencingthe fate of mRNA, and has been connected with a widerange of mRNA metabolism, including nuclear export(Fustin et al., 2013; Roundtree et al., 2017), secondarystructure (Liu et al., 2015; Liu et al., 2017), pre-mRNAsplicing (Zhao et al., 2014; Haussmann et al., 2016; Xiaoet al., 2016), alternative polyadenylation (APA) site choice(Ke et al., 2015; Molinie et al., 2016; Kasowitz et al., 2018;Yue et al., 2018), stability (Wang et al., 2014a; Shi et al.,2017; Huang et al., 2018), translatability (Meyer et al.,2015; Wang et al., 2015; Zhou et al., 2015; Li et al., 2017;Shi et al., 2017; Slobodin et al., 2017; Zhou et al., 2018), pri-microRNA processing (Alarcón et al., 2015), and othermechanisms accompanying RNAmaturation (Meyer andJaffrey, 2014; Yue et al., 2015; Yang et al., 2017).The impact of m6A on translation has been subjected

to substantial examinations in recent years (Meyer,2018). Several studies have reported stimulatory ef-fects of m6A on translation (Meyer et al., 2015; Wanget al., 2015; Coots et al., 2017; Li et al., 2017; Shi et al.,2017), whereas other studies have shown inhibitoryeffects (Choi et al., 2016; Qi et al., 2016; Slobodin et al.,2017). Current research has found that diverse effects ofm6A on translation regulation are dictated by many fac-tors, including its effect on RNA structures (Wang et al.,2014b; Liu et al., 2015; Roost et al., 2015; Spitale et al., 2015;Liu et al., 2017), the location within a transcript (Meyeret al., 2015; Qi et al., 2016), the proteins (readers) thatrecognize it (Wang et al., 2015; Li et al., 2017; Shi et al.,2017), and the cellular environment (Zhou et al., 2015;Zhou et al., 2018), among other factors (Han et al., 2017;Roignant and Soller, 2017; Meyer, 2018).Howm6A affects translation has not yet been studied

in any plant species. In this study, we illustrated thepatterns and features of mRNA m6A marks in twomaize (Zea mays) inbred lines, B73 and Mo17, andexamined the global extent of m6A correlating withtranslational status. By combining aparallel transcriptome-wide profiling of m6A distribution and polysome occu-pancy, we showed that m6A modification conferred anegative correlation with the translational status at aglobal scale. Meanwhile, the incidence of m6A modifi-cation near the start codon tended to enhance the trans-lational status. These results indicate that the involvementof m6A in affecting translational status is multifaceted,and varied in the context of its strength andgenic location.Furthermore, we identified that thousands of genes weresubject to natural variation in the specific modification ofm6A, which is at least partly associated with the intra-species variations in alternative splicing.

RESULTS

Features of the m6A Methylome in Maize

To obtain insight into the roles of m6A in affectingtranslational status, we conducted m6A RNA immu-noprecipitation sequencing (m6A-seq; Dominissini et al.,2012; Meyer et al., 2012), polysome profiling (Juntawong

et al., 2014; Zhang et al., 2017b), and input RNA se-quencing (RNA-seq) for the same samples collected fromtwo maize inbred lines, B73 and Mo17 (Fig. 1A). To de-termine the locations of m6A modifications throughoutthe transcriptome, we adapted an analytical algorithmfor identifying m6A peaks as described elsewhere(Dominissini et al., 2013; Yoon et al., 2017). m6A peakswere highly overlapped between two biologically inde-pendent replicates (Fig. 1B), and the concordant peaksfrom two replicates were used for subsequent bio-informatics analyses. In B73, m6A-seq revealed a total of11,185 peaks, including 8,265 protein-coding mRNAs(Supplemental Table S1), 76 long non-coding RNAs(Supplemental Table S2) and 140 transposable elementtranscripts (Supplemental Table S3). The majority ofprotein-coding genes (.90%) contain a single m6A resi-due (Supplemental Fig. S1). Using m6A reverse tran-scription quantitative PCR (RT-qPCR), all of the ninerandomly selected m6A peak-containing genes wereverified (Supplemental Fig. S2), implying a high authen-ticity of our data.Consistent with previous studies in both mammals

and plants (Meyer et al., 2012; Li et al., 2014; Luo et al.,2014; Wan et al., 2015), m6A peaks in protein-codinggenes were primarily enriched in the 39 untranslatedregion (UTR; ;69.2%) and in the vicinity of the stopcodon (;20.4%; defined as a 200-nt window centeredon the stop codon), while less present in coding se-quences (CDS; ;4.7%), near start codons (;0.6%; de-fined as a 200-nt window centered on the start codon),in the 59UTR (;0.7%), and in spliced intronic regions(;4.4%; Fig. 1, C andD; Supplemental Fig. S3). De novomotif analysis of m6A peaks using both the MEME(Bailey et al., 2009) and the HOMER software programs(Heinz et al., 2010) identified a UGUAMM sequencemotif (M5 A or C; Fig. 1, E–G) that is exactly the sameas the motif previously identified from a set of m6-A-methylated genes in rice (Oryza sativa; Li et al., 2014),and similar to a URUAY motif recently considered as aplant-specific m6A motif proven to be bound by them6A reader ECT2 in Arabidopsis (Arabidopsis thaliana;Wei et al., 2018); however, it is distinct from the ca-nonical RRACH motif reported in other organisms(Dominissini et al., 2012; Meyer et al., 2012).To predict the biological functions associated with

m6A-modified genes, we performed gene ontology(GO) enrichment analysis and found that proteinsencoded by genes with the highest level of m6A modi-fication (top 20%; see “Materials and Methods”) wereinvolved in a variety of cellular functions, includingRNA processing, ATP metabolism, transcription regu-lation, etc. Transcripts encoding mitotic cell cycle con-trol were identified as the most significantly enrichedgroup (Fig. 1H). Collectively, these results indicate thatthe high level of m6A modification tends to marktranscripts with regulatory functions.We performed all the analyses in Mo17 (Supplemental

Figs. S4–S6; Supplemental Tables S4 and S5), and all theresults about the m6A methylome in Mo17 were consis-tent with the findings in B73. Taken together, our analysis

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Relationship of RNA m6A and Translational Status

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revealed that thousands of transcripts were post-transcriptionally modified by m6A in maize, and theoverall topology of the m6A methylome showed bothconserved and unique features compared to other orga-nisms such as mammals (Dominissini et al., 2012; Meyeret al., 2012).

Possible Relation of m6A to the Choice of Poly(A) Sites

In mammals, the m6A modification has been dem-onstrated to play a role in choosing APA sites (Ke et al.,

2015; Molinie et al., 2016; Kasowitz et al., 2018; Yueet al., 2018). The strong enrichment of m6A peaks in39UTRs prompted us to investigatewhetherm6Amarksare correlated with APA usage in maize. From a total of18,676 expressed genes detected in our B73 RNA-seqdata set (Fig. 2A; Supplemental Table S6; and see“Materials and Methods”), we found that 67.6% ofgenes (n 5 8,549) containing at least two poly(A) siteswere m6A-methylated, which was remarkably higherthan 24.8% of genes (n 5 10,127) without APA sites(Fisher’s exact test, P value , 2.2 3 10216; Fig. 2, A, B,and D). Vice versa, 69.7% of m6A-modified genes

Figure 1. The m6A methylome in themaize inbred line B73. A, Schematicdiagram of m6A-seq and polysomeprofiling in parallel. NGS, next gener-ation sequencing. B, Overlap of m6Apeaks between two biological repli-cates (Rep1 and Rep2). C, Metageneprofile of m6A peak distribution along anormalized transcript composed ofthree rescaled nonoverlapping seg-ments, 59 UTR, CDS, and 39 UTR. D,Pie chart depicting the percentage ofm6A peaks within six transcript seg-ments. E, Sequence motif identifiedfrom the top 2,000 most significantm6A peaks by the software MEME. F,Sequence motif identified from the top2,000 most significant m6A peaks bythe software HOMER. G, A represen-tative Integrative Genomics Viewer(http://www.igv.org/) plot showing am6A motif sequence (highlighted inred) identified in (E) and (F) at thecenter of a peak within the 39 UTR ofZm00001d031318. The peak summit isindicated with a dashed rectangle box.H, GO enrichment analysis using thesoftware FuncAssociate 3.0 for fivegroups of genes ranked by m6A levels.The color bar stands for the 2log10(Pvalue) of each GO term. The size of thecircle indicates the number of genes ineach GO term.

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(n 5 8,291) were identified to harbor APA events,which was significantly higher than 26.7% of non-methylated genes (n 5 10,385; Fisher’s exact test, Pvalue, 2.23 10216; Fig. 2, A, C, and D). Moreover, theintimate association ofm6Amarkswith APAusagewasalso consistently observed in Mo17 (Supplemental Fig.S7; Supplemental Table S7). These results clearly indi-cate that the m6A modification may be associated withthe decision to choose poly(A) sites in maize.To further ascertain whether the effect of m6A on

APA usage is dependent on its location on 39UTRs, wedivided m6A-methylated genes into six categoriesaccording to m6A sites on different genic segments.Surprisingly, we found that besides m6A-methylatedsites on 39UTRs, it was evident that genes with m6A

marks on any other segments also exhibited a signifi-cant correlation with APA usage than genes withoutm6A modification (Supplemental Fig. S8), suggestingthat the effect of m6A modification on APA usage maybe a general output regardless of its genic location.

Effect of the m6A Modification on Translation

It has been reported in various species that the m6Astrength is negatively correlated with the transcript a-bundance, possibly by affecting mRNA decay (Li et al.,2014; Wang et al., 2014a; Wan et al., 2015; Martínez-Pérez et al., 2017; Anderson et al., 2018). Consis-tently, we revealed a significantly negative correlation

Figure 2. Association of m6Awith APAusage in B73. A, The number of genesdefined in each category in the corre-sponding analysis. B, Proportion ofm6A-modifed transcripts within tran-scripts with (left) or without APA usage(right). P values were calculated usingthe Fisher’s exact test. C, Proportion oftranscripts containing APA usagewithin m6A-methylated (left), andnonmethylated transcripts (right). Pvalues were calculated using theFisher’s exact test. D, Integrative Ge-nomics Viewer plots of two examplesrepresenting m6A located in the proxi-mal (left) or distal (right) APA. The ar-rows indicate the gene direction fromthe 59 to 39 end.



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(r520.66, P value, 2.23 10216 for B73 and r520.65,P value , 2.2 3 10216 for Mo17) between m6A and themRNA level in maize (Supplemental Fig. S9). Then, weperformed transcriptome-wide polysome profiling andcalculated the translational status of each expressedgene (ratio of the polysome-bound fraction to totalmRNA) to assess the effect of m6A on translation at aglobal scale (Supplemental Fig. S10). As shown inFigure 3A, although m6A-modified transcripts dis-played a tendency of a higher level of translationalstatus than transcripts without m6A marks, we ob-served that hypermethylated transcripts had the lowestdegree of translational status after ranking the genes

into five groups based on the m6A strength, suggestingthat the excessive extent of m6A modification maylikely attenuate the translational status. In contrast, thelevel of gene transcription showed a positive correla-tion with translational status (Supplemental Fig. S11).

We next examined the relationship between m6Amethylation and translational status by plotting thefraction of genes with m6A peaks in each genic seg-ment. Surprisingly, we found that although the overalllevel of m6A near the start codon was low (Fig. 1C),transcripts with m6A marks in the vicinity of the startcodon showed the highest translational status thanany other segments (Fig. 3B), raising an intriguing

Figure 3. Effect of the m6A modifica-tion on translation in B73. A, The m6Alevel and translational status shows anegative correlation. m6A-depletedand m6A-modified transcripts are dis-played in blue and deep red, respec-tively, and the P value was calculatedusing the Wilcoxon rank-sum test. TheP value among groups with differentm6A levels was calculated using theKruskal–Wallis test. B, Transcripts withm6A residues near the start codon (deepred) exhibit the highest level of trans-lational status. *P, 0.05, **P, 0.01,and ***P, 0.001. C, K-means cluster-ing analysis of all the m6A-modifiedtranscripts based on m6A intensity andtranslational status. Each level of m6Amethylation and translational statuswas converted to percentiles using theempirical cumulative distribution func-tion. The percentile indicates convertedm6A level and translational status. Thecolor indicates the relative m6A meth-ylation and translational status. A totalof four clusters were identified andthe number of genes in each cluster isshown. D, GO enrichment analysisfor Cluster 1 (left) and Cluster 3 (right)using the software FuncAssociate 3.0(permutation-based corrected P value ,0.05). All significantly enrichedGO termsare listed in Supplemental Table S8. Eachnode indicates an enriched GO termand the node size is proportional to thetotal number of genes in each pathway.


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possibility that the occurrence of m6A nearby the startcodon may have the ability to enhance mRNA trans-lation. Indeed, after we performed m6A methyl-ated RNA immunoprecipitation (MeRIP) toward thepolysome-mRNA fractions, we found that two ran-domly selected genes with m6A sites near the start co-don exhibited aggregated m6A strength relative to thatdetected from the total mRNA. In contrast, two geneswith m6A sites in the 39UTR did not show such regu-larity (Supplemental Fig. S12). These results suggestthat at least for the genes tested, the presence of them6Amark near the start codon in mRNA may facilitate theloading of mRNA onto the ribosomes. Moreover, weperformed GO term enrichment analysis for m6-A-methylated genes grouped according to m6A sites ondifferent genic segments. Interestingly, we found thatproteins encoded by transcripts with the m6A mark inthe vicinity of the start codon were enriched in thecategory of nucleosome (Supplemental Fig. S13).Meanwhile, the functional category of histone bindingwas enriched in proteins encoded by transcripts withm6A sites in the CDS (Supplemental Fig. S13). In con-trast, we could not detect any GO enrichment for all theother groups of genes.To further investigate whether m6A may coordinate

translational control in the context of distinct biologicalpathways, we performed the k-means clustering anal-ysis to group all the m6A-modified genes into fourclasses based on the levels of m6A and translationalstatus (Fig. 3C; Supplemental Fig. S14; see “Materialsand Methods”). We then conducted GO term enrich-ment analysis across the different clusters (SupplementalTable S8). In Cluster 1, which was signified by the lowlevel of m6A methylation but the high level of trans-lation efficiency, two of the most significant enrichedgroups were translation and RNA methylation pro-cesses (Fig. 3, C and D).Interestingly, the Cluster 1 group also showed

characteristics as the lowest proportion of APA us-ages (Supplemental Fig. S15A) and the highest pro-portion of transcripts with m6A near the start codon(Supplemental Fig. S15B). In contrast, genes involvedin purine metabolism were exceedingly enriched inCluster 3, which exhibited the highest level of m6Amodification but the lowest level of translationalstatus (Fig. 3, C and D), as well as the highest pro-portion of APA usages (Supplemental Fig. S15A) andthe lowest proportion of transcripts with m6A nearthe start codon (Supplemental Fig. S15B). As thespecific functional enrichment was identified for allfour clusters, it clearly indicates that genes partici-pating in distinct biological pathways may be subjectto m6A-mediated translational control in differentmanners.Notably, after investigating the correlation of m6A

modification and translational status in Mo17(Supplemental Figs. S16–S19; Supplemental Table S9),we saw the same pattern as we identified in B73. Al-together, these results suggest that m6A modificationmay play a role in bridging the transcription and

translation, hierarchically organized by its strength andgenic location in maize.

Natural Variation in m6A Modification between B73and Mo17

We next examined the extent of natural intraspeciesvariation in m6A modification. At the gene level, wefound that 6,237 genes (type I) were commonly modi-fied by m6A in both B73 and Mo17, while there were1,938 genes (type II) and 929 genes (type III) that wereonly modified in B73 or Mo17, respectively (Fig. 4, Aand B). As a post-transcriptional modification, thespecific appearance of m6A sites is conceivably decidedby gene-specific expression. However, we found thatthe inbred-specific expression could only explain asmall proportion of genes within both the type II and IIIgroups (Supplemental Fig. S20). In addition, we iden-tified hundreds of genes with differential levels ofm6Amodification between B73 andMo17 (SupplementalFig. S21). These results indicate that although theoverall topology of the m6A methylome is largelyconserved between B73 and Mo17, there is a sub-stantial number of genes with natural variation inm6A modification.We then searched for the relevant features associated

with or possibly responsible for inbred-specific m6Amodification. Interestingly, relative to type I, m6Apeaks in type II or type III showed a marked increase inthe proportion of the spliced intronic segment (Fisher’sexact test, P value, 0.001; Fig. 4C), suggesting that thealternative splicing of mRNA between two inbred linesmay at least in part be attributed to the inbred-specificm6A modification. In contrast, the proportion of geneswith APA usage in type II and type III turned out to beless compared to that in type I (Fig. 4D), suggesting thatthe specific m6A-modification in type II or type III wasnot driven by the alteration in APA usage. Moreover,the specific modification in type II occurred with higherprobability in the vicinity of the start codon (Fisher’sexact test, P value 5 0.03), but not for other genic seg-ments, when compared with the specific modificationin type III (Fig. 4C). However, the proportions of geneswith APA usage were comparable between type II andtype III (Fig. 4D). Furthermore, we did not observe theenrichment of any significant GO terms for genes be-longing to either type II or type III.To address whether such natural variation in m6A

modification had effects in gene expression regulation,we assessed the levels of translational status for genesin type II and type III, and made comparisons to type I.The results showed that the translational status wasstatistically lower for type II (Wilcoxon rank-sum test, Pvalue 5 6.9 3 1029) and type III (Wilcoxon rank-sumtest, P value5 1.13 1027) compared to type I (Fig. 4E),indicating that genes commonly modified by m6A inboth B73 and Mo17 may possess higher translationalstatus than genes specifically modified in either B73 orMo17. In contrast, there was no significant difference of



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Figure 4. Natural variation in the m6A modification between B73 and Mo17. A, Venn diagram showing the number of genescommonly (type I) and specifically modified by m6A in B73 (type II) and Mo17 (type III). B, Representative Integrative GenomicsViewer plots showing B73-specific (left), Mo17-specific (middle), and common (right) m6A modification. C, Pie charts depictingthe percentage of m6A peakswithin six transcript segments for three types of genes as indicated in (A). D, Proportion of transcripts


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the translational status between type II and type III at aglobal scale (Fig. 4E), or across each of the genic seg-ments (Supplemental Fig. S22). Taken together, theseresults indicate that the natural variation in m6A ac-tively occurs, and thereby may confer the other layer ofgene expression regulation within species.

DISCUSSION

Topology and Features of m6A Modification in Maize

Our transcriptome-wide m6A mapping revealed anextremely asymmetric distribution of mRNA m6Amethylation with the majority of m6A sites enriched inthe 39UTR in maize. In fact, a marked bias of m6A sitesin 39UTRs has been observed in nearly all species ex-amined to date, including rice (Li et al., 2014) andArabidopsis (Luo et al., 2014; Wan et al., 2015), sug-gesting that although the degree of this skewness seemsvariable, an evolutionary constraintmay target them6Adeposition to the 39UTR of genes regardless of genestructure or coding potential. This raises an intriguingquestion of what the underlying mechanisms of meth-ylation specificity are. In this study, we found thatm6A-methylated genes are highly likely to harbor APAevents in maize. Meanwhile, we extended the investi-gation of the relationship between m6A and APA siteselection in other plant species, including Arabidopsis(Col-0, Can-0, Hen-16) and rice, using published data(Li et al., 2014; Luo et al., 2014; Duan et al., 2017). Theresults revealed that the effect of m6A modification onAPA usage was conserved in all plant species investi-gated (Supplemental Fig. S23). APA is a widespreadphenomenon in eukaryotes, generating mRNAs withalternative 39ends (Elkon et al., 2013; Tian and Manley2017). The causative relation between m6A and APAwas demonstrated by a recent study in mouse, showingthat a nuclear m6A reader YTHDC1 plays a critical rolein m6A-dependent processing of pre-mRNA transcripts,and the loss of YTHDC1 altered the APA usage for morethan 800 genes (Kasowitz et al., 2018). In addition, it islikely that the involvement of m6A in APA usage mayoperate the otherway around inmaize, i.e. the occurrenceof APA in 39UTR marking transcripts with m6A sites.Alternatively, the bias of m6A methylation in the 39UTRmay be achieved by preferential recruitment of m6Amethylase to the 39UTR of genes by interacting with39UTR-binding proteins (Yue et al., 2018), or microRNAs,whichwere recently demonstrated to regulate the bindingof m6A methylase to mRNA in a sequence-dependentmanner (Chen et al., 2015).Early studies from numerous organisms have con-

firmed a RRACH sequence as the canonical m6A con-sensusmotif (Dominissini et al., 2012, 2013;Meyer et al.,

2012), whereas we found that maize may utilize a dis-tinct motif sequence (UGUAMM). The search using theUGUAMM sequence as the inquiry against all theexpressed genes yielded a total of 34,173 sites, indicat-ing that the majority of UGUAMM motifs in mRNAlack the m6A modification. Therefore, it remains un-clear how themethylationmachinery selectively targetsa subset of consensus motifs in the 39UTR. We suspectthat cis-elements such as the neighboring RNA se-quences or secondary structures may likely have ac-cessory roles in methylation specificity.

m6A-Mediated Translation Control in Maize

Although not explored in plants yet, the impact ofm6A on translation has been extensively studied inmany other organisms (Meyer et al., 2015; Wang et al.,2015; Choi et al., 2016; Qi et al., 2016; Coots et al., 2017;Li et al., 2017; Slobodin et al., 2017), leading to a para-doxical conclusion that m6A marks enable both stimu-latory and inhibitory effects on translation. In thisstudy, after integrating the analyses from the mRNAtranscriptome, m6A profiling, and polysome occu-pancy, we uncovered a general theme illustrating howm6A marks affect translational status in maize (Fig. 5):Transcripts with low m6A levels exhibit relativelyhigh translational status; however, the excessive de-position of m6Amarks on transcripts caused negativeeffects on translational status, indicating that thehypermethylated state of transcripts may inhibit theaccretion of ribosomes and lead to the decrease in thetranslational status. Compared to other genic seg-ments, the presence of m6A marks in the vicinity ofthe start codon may have the greatest effect on en-hancing the translational status. Based on these find-ings, we conclude that dependent on its strength andgenic location, the cotranscriptional m6A modificationon mRNAs has multidimensional effects on translationalstatus in maize.As an epitranscriptome mark, m6A would be pri-

marily recognized by reader proteins to fulfill its bio-logical functions. This raises an attractive question ofwhat the mechanistic connection between readers andm6A is, that influences the translational status. Al-though the translational regulation of m6A-modifiedmRNAs by m6A readers has not been reported in plantsyet, this fascinating field has emerged to be unveiled re-cently in mammalian cells. The YTHDF2 protein, for in-stance, decreases the amount of m6A-methylated mRNAin translatable fractions by sequestering m6A-containingmRNAs to processing bodies and eventually facilitat-ing their degradation (Wang et al., 2014a). In contrast,YTHDF1 and YTHDF3 recognizes m6A residues in

Figure 4. (Continued.)containing APA usage for three types of genes as indicated in (A). P values were calculated using the Fisher’s exact test. E,Comparison of translational status among three types of genes as indicated in (A). P values were calculated using the Wilcoxonrank-sum test.



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39UTRs and promotes translation through interactionwith initiation factors or ribosomal subunit proteins(Wang et al., 2014a, 2015; Li et al., 2017; Shi et al.,2017). Moreover, besides being conveyed by readerproteins, the effect of m6A residues on translationcould also be accomplished by its direct impact onsecondary and tertiary RNA structures (Wang et al.,2014b; Roost et al., 2015; Spitale et al., 2015; Liu et al.,2015, 2017; ), or its impairment on ribosome stallingor tRNA accommodation at methylation-affectingcodons, leading to the reduced translation kinetics(Choi et al., 2016).

How m6A sites near start codons enhance thetranslational status is also an important area of futurestudy. In principle, only the translating ribosomescan detect start codons, and this event occurs in thecytoplasm. However, m6A modification should takeplace primarily in the nucleus. Therefore, the startcodon itself is unlikely to be the cause of the m6Aenrichment near the start codon. This is distinct fromm6A-mediated regulation of cap-dependent or -in-dependent translation, both scenarios of which arerelated to m6A residues located in the 59UTR (Meyeret al., 2015).

In sum, we conducted a parallel analysis of thetranscriptome-wide m6A profiling and polysome oc-cupancy in two maize inbred lines. We found manyconserved and unique features of m6A localization inmaize when compared to other organisms, and dem-onstrated that m6A modification is involved in or-chestrating transcription and translation at a globalscale in maize. We further characterized the mode ofm6A methylation correlated with translational statusby its strength and location in transcripts. Lastly, wefound that thousands of genes exhibit distinctlyinbred-specific methylation, highlighting that m6A

modification confers a new dimension of naturalvariance in posttranscriptional gene regulation.

MATERIALS AND METHODS

Plant Materials

Seeds of maize (Zea mays) inbred lines B73 and Mo17 were sterilized by 70%ethanol for 1 min followed by 5% sodium hypochlorite solution for 5 min andrinsed five times with sterile water. Then seeds were sowed in pots containing amixture of vermiculite and soil (1:1, v/v) and grown in the growth chamber at28°C for 16 h in the light and 25°C for 8 h in the dark. After 14 d, aerial tissueswere harvested, immediately frozen in liquid nitrogen, and stored at 280°C.

m6A MeRIP

Total RNA was extracted using TRIzol reagent (cat. no. 15596-018; AmbionLife Technologies) according to the manufacturer’s protocol. PolyadenylatedRNA was isolated using the GenElute mRNA Miniprep Kit (Sigma-Aldrich)following the manufacturer’s instructions. Immunoprecipitation of m6A wasadapted from the protocol of the Magna MeRIP m6A Kit (Millipore). Briefly,mRNAwas adjusted to 27 mLwith the concentration of;1 mg/mL, followed byadding 3mL of 103RNA fragmentation buffer (CS220011) for 4min at 94°C andthen adding 3 mL of EDTA (0.5 M) to terminate the reaction. The fragmentedRNAwas purified by ethanol precipitation. Then, 30mL ofmagnetic A/G beads(CS203152) was preincubated with 10 mg of anti-m6A antibody (MABE1006) in13 immunoprecipitation (IP) buffer for 30 min at room temperature. A total of0.5-mg fragmented RNA was saved for RNA-seq as input control, and 20-mgfragmented mRNA was incubated with the antibody-beads mixture to a finalvolume of 500 mL for 2 h at 4°C with constant rotating. After washing 3 timeswith 13 IP buffer, RNAwas eluted with 100 mL of elution buffer two times andall elutes from the same samples were combined, and subsequently purifiedusing the RNA Clean & Concentrator Kit (ZYMO). Purified m6A-IP samplesand input RNAs were subjected to library construction.

Polysome Profiling

Polysome isolation bydifferential centrifugationwasperformedasdescribedin Zhang et al. (2017b). In brief, 2 g of tissue powder was homogenized in 5 mLof polysome extraction buffer (200 mM of Tris-HCl at pH 9.0, 200 mM of KCl,35 mM of MgCl2, 25 mM of EGTA, 1% [v/v] Triton X-100, 1% [v/v] TWEEN 20,

Figure 5. A general theme describingthe multidimensional correlations ofm6A marks on translational status. A,Transcripts with low m6A levels exhibithigh translational status. B, Moderatem6A marks are associated with themedian level of translational status. C,Excessive deposition of m6A marksdecreases the translational status. D,The deposition of m6A marks in thevicinity of the start codon may promotethe translational status.


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2% [v/v] polyoxyethylene, 5 mM of dithiothreitol, 0.5 mg/mL of heparin,100 mg/mL of chloramphenicol, and 25 mg/mL of cycloheximide). Crude celllysate was centrifuged at 13,200 g for 15 min at 4°C. The supernatants wereloaded on the top of a 1.7 M of Suc cushion and centrifuged at 45,000 rpm (modelno. SW 55 Ti Swinging Bucket Rotor in a model no. L-100XP Ultracentrifuge;Beckman Coulter) for 3 h at 4°C. The ribosome pellet was resuspended in200 mL of resuspension buffer (200 mM of Tris-HCl at pH 9.0, 200 mM of KCl,35 mM of MgCl2, 25 mM of EGTA, 100 mg/mL of chloramphenicol, and 25 mg/mL of cycloheximide). Then the solution was layered over a 20% to 60% Sucdensity gradient and centrifuged at 41,000 rpm (model no. SW 55 Ti SwingingBucket rotor; Beckman Coulter) for 2 h at 4°C. After ultracentrifugation, thegradients were monitored and fractionated into 14 fractions at an absorbance of254 nm using a Gradient Fractionator (Biocomp) including a UV detector. Thepolysome-RNA fractions were pooled and treated by 5% (w/v) SDS/0.2 M ofEDTA, and then extracted twice with an equal volume of phenol/chloroform/isoamyl alcohol (25:24:1; v/v/v). Themixture was centrifuged at 12,000 rpm for5 min at 10°C and RNA was precipitated by isopropanol followed by washedusing 70% (v/v) ethanol, and eventually resuspended for the libraryconstruction.

Library Construction and Sequencing

Libraries of RNA-seq, m6A-seq, and polysome profiling were generatedusing the NEBNext Ultra II RNA Library Prep Kit (model no. E7770S; NewEngland Biolabs) according to the manufacturer’s instructions. The librarieswere sequenced with 150-bp paired reads on a model no. HiSeq X Ten platform(Illumina).

m6A Peak Calling

Raw paired-end reads of m6A-seq and input RNA-seq were filtered andadapter sequences were trimmed out by the tool Trimmomatic v0.35 (Bolgeret al., 2014) with the parameters ILLUMINACLIP TruSeq3-PE-2.faMINLEN 30.Cleaned reads from B73 samples were aligned to the maize B73 reference ge-nome, AGPv4.38 (Jiao et al., 2017) and cleaned reads from Mo17 samples weremapped to the maize Mo17 reference genome, CAU-1.0 (Sun et al., 2018) usingthe software Hisat2 v2.1.0 (Kim et al., 2015) with the parameters25 123 1–dta.Reads matching to less than five places were retained for further analysis. m6Apeaks were identified using the MACS2 peak calling algorithm (Zhang et al.,2008) with the input as background and the parameter of effective genome sizewas adjusted to the transcriptome size (417272442) and the q value was set to0.01. Peaks that overlapped in at least 50% of their length between two bio-logical replicates were designated as high confidence m6A peaks using thesoftware package BedTools v2.17.0 (Quinlan and Hall 2010). The m6A intensitywas defined as fold changes of m6A peaks from MACS2 output.

The analysis of m6A peak enrichment based on six nonoverlapping tran-script segments was performed as follows: 59UTR [transcription start site, CDSstart codon 2 101 bp], start codon segment [CDS start codon 2 100 bp, CDS startcodon1 100 bp], CDS [CDS start codon1 101 bp, CDS stop codon2 101 bp], stopcodon segment [CDS stop codon2 100 bp, CDS stop codon1 100 bp], 39UTR [CDSstop codon1 101 bp, transcription termination site], and intron segment. Each of them6A sites is represented only once in the analysis. For genes with multiple mRNAtranscripts, the longest one was selected. Each high confidence peak was annotatedto one of these regions using BedTools (Quinlan and Hall 2010).

m6A Motif Analysis

All m6A peaks were sorted according to fold change and the top 2,000 peakswere chosen for the de novo motif analysis using the both of the two programsMEME v4.10.2 (Bailey et al., 2009) and HOMER v4.9 (Heinz et al., 2010). The101-nt–long sequences derived from the sense strand and centered around thepeak summit were extracted using the “fastaFromBed” function in BedTools(Quinlan and Hall 2010) and used as input for MEME (Bailey et al., 2009) andHOMER (Heinz et al., 2010). The meme script in MEME (Bailey et al., 2009) andthe findMotifs.pl script inHOMER (Heinz et al., 2010)were used for the de novomotif analysis.

APA Analysis

Genes withmultiple poly(A) sites were defined according tomaize B73 geneannotations (AGPv4.38; www.maizegdb.org).

RNA-Seq Analysis and Translational Status Calculation

Raw paired-end reads of polysome profiling and RNA-seq were processedand aligned the same as described above for m6A peak calling. Gene tran-scriptional and translational levels were estimated by calculating fragments perkilobase of transcript per million fragments (FPKM) by the software StringTiev1.3.3 (Pertea et al., 2015) with default parameters. The translational status wascalculated by “FPKM(translational level)/FPKM(transcriptional level)” as de-scribed in Lei et al. (2015). Inbred-specific expression was defined as genes withthe FPKM$ 1 of mRNA abundance in one in-bred, but FPKM, 1 in the other.

GO Analysis

K-means clustering was used to explore genes coordinated in the levels ofm6A methylation and translational status. On the basis of both the Elbow (thefactoextra function in the R package; https://www.r-project.org/) and Aver-age silhouette (the factoextra function in the R package) methods, four clusterswere determined as the optimal number of clusters. To avoid skewing distancecalculation due to difference in scale and variance of the expression measure-ments, each level of m6A methylation and translational status was firstly con-verted to percentiles using the empirical cumulative distribution function. Thesoftware FuncAssociate v3.0 (http://llama.mshri.on.ca/funcassociate/; Berrizet al., 2009) was used to assess enrichment of GO terms for each cluster. Thegene list for background input was explicitly defined as the set of genes in-cluded in all clusters. We defined significant enrichment as GO terms withadjusted P value , 0.05. Adjusted P value was the fraction (as percent) of1,000 null-hypothesis simulations having attributes with this single-hypothesisP value or smaller.

Enriched GO terms were visualized with the software Cytoscape 3.3.0(Shannon et al., 2003) installed with the Enrichment Map plugin (Merico et al.,2010). Within the enrichment maps, each node indicates an enriched GOpathway and the node size is proportional to the total number of genes in eachpathway.

RT-qPCR

RT-qPCR was performed as described in Duan et al. (2017). Briefly, 0.5-mgRNA from m6A-IP, input, and polysome profiling were used for reverse tran-scription using the Maxima H Minus cDNA Synthesis Master Mix with ds-DNase (Thermo Fisher Scientific). RT-qPCR was performed using TB GreenPremix Ex Taq (TaKaRa). Zm00001d019684was used as an internal control genefor the normalization. All primers used in this study are listed in SupplementalTable S10.

Analyses in Mo17

To reduce mapping bias, we built a Mo17 pseudogenome by substitutingsinglenucleotidepolymorphisms in themaizeB73 referencegenome (AGPv4.38)to Mo17 nucleotides. After that, reads of m6A-seq, RNA-seq, and polysomeprofiling fromMo17 sampleswere remapped to theMo17 pseudogenomes, andall the related analyses in Mo17 were conducted the same as for B73, asdescribed above.

Accession Numbers

The high-throughput sequencing data generated in this study have beendeposited at the National Center for Biotechnology Information’s Gene Ex-pression Omnibus database repository (http://www.ncbi.nlm.nih.gov/geo/)under the accession number GSE124543. All raw data in this study also wereconverted to bigWig files (https://genome.ucsc.edu/goldenpath/help/bigWig.html) and deposited in the web-based tool Comparative Genomics(https://genomevolution.org/coge/) for visualization. The accession numbersfor these bigwig files are listed in Supplemental Table S11.

Supplemental Material

The following supplemental materials are available.

Supplemental Figure S1. The number of methylated transcripts containingdifferent m6A sites in B73.



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Supplemental Figure S2. RT-qPCR validation for nine randomly selectedgenes containing m6A methylation.

Supplemental Figure S3. The number of methylated transcripts contain-ing various combinations of m6A sites within six transcript segmentsin B73.

Supplemental Figure S4. Distribution pattern of m6A sites in Mo17.

Supplemental Figure S5. The conserved m6A motif sequence in Mo17.

Supplemental Figure S6. GO enrichment analysis for m6A-methylatedgenes in Mo17.

Supplemental Figure S7. Association of m6A with APA usage in Mo17.

Supplemental Figure S8. The proportion of genes with APA usageaccording to the genic location of m6A in B73 (top) and Mo17(bottom).

Supplemental Figure S9. Correlation between m6A strength and mRNAabundance in B73 and Mo17.

Supplemental Figure S10. The repeatability between two biological repli-cates for both RNA-seq data (left) and polysome profiling data (right) inB73 (top) and Mo17 (bottom).

Supplemental Figure S11. Positive effect of RNA abundance on transla-tional status in B73.

Supplemental Figure S12. m6A-RT-qPCR of polysome-associated mRNAand total mRNA.

Supplemental Figure S13. GO analysis of genes with m6A marks at dif-ferent transcript segments in B73.

Supplemental Figure S14. “Elbow” and “Average silhouette” method forthe identification of the optimal number of clusters in B73.

Supplemental Figure S15. The relationship between clusters and m6-A-related characteristics in B73.

Supplemental Figure S16. Positive effect of RNA abundance on the trans-lational status in Mo17.

Supplemental Figure S17. Effect of the m6A modification on translationin Mo17.

Supplemental Figure S18. “Elbow” and “Average silhouette” method forthe identification of the optimal number of clusters in Mo17.

Supplemental Figure S19. Effect of the m6A modification on translationin Mo17.

Supplemental Figure S20. The specific expressed and modified genes inB73 and Mo17.

Supplemental Figure S21. Hundreds of genes with differential levels ofm6A modification between B73 and Mo17.

Supplemental Figure S22. Translational status between Type II and TypeIII across the different mRNA segments.

Supplemental Figure S23. Proportion of m6A-modified genes within tran-scripts with or without APA usage among different species.

Supplemental Table S1. The list of m6A-containing protein-coding genesshowing peak summit locations, m6A level, and translational statusin B73.

Supplemental Table S2. The list of m6A-containing long non-coding RNAsshowing peak summit locations and m6A level in B73.

Supplemental Table S3. The list of m6A-containing transposable elementsshowing peak summit locations and m6A level in B73.

Supplemental Table S4. The list of m6A-containing protein-coding genesshowing peak summit locations, m6A level, and translational statusin Mo17.

Supplemental Table S5. The list of m6A-containing transposable elementsshowing peak summit locations and m6A level in Mo17.

Supplemental Table S6. mRNA abundance of all expressed genes in twoindependent biological replicates in B73.

Supplemental Table S7. mRNA abundance of all expressed genes in twoindependent biological replicates in Mo17.

Supplemental Table S8. GO term enrichments for the clusters identified inFigure 3C.

Supplemental Table S9. GO term enrichments for the clusters identified inSupplemental Figure S19A.

Supplemental Table S10. The list of primers used in the study.

Supplemental Table S11. The list of accession numbers for “bigWig” filesin this study.

ACKNOWLEDGMENTS

We thank all the members of our laboratories for helpful discussions andassistance during this project.

Received August 13, 2019; accepted September 23, 2019; published October 7,2019.

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