The H3K4me1 histone mark recruits DNA repair to functionally constrained genomic regions in plants

The H3K4me1 histone mark recruits DNA repair to functionally

constrained genomic regions in plants

Daniela Quiroz

1,2

, Diego Lopez-Mateos

4,5

, Kehan Zhao

1,3

, Alice Pierce

1,3

, Lissandro Ortega

, Alissza Ali

, Pablo

Carbonell-Bejerano

, Vladimir Yarov-Yarovoy

4,5

, J. Grey Monroe

1,2,3,#

Department of Plant Sciences, University of California Davis, Davis, CA, USA 95616

Integrative Genetics and Genomics, University of California Davis, Davis, CA, USA 95616

Plant Biology Graduate Group, University of California Davis, Davis, CA, USA 95616

Department of Physiology and Membrane Biology, University of California Davis, Davis, CA, USA 95616

Biophysics Graduate Group, University of California Davis, Davis, California

Institute for Grape and Wine Sciences (ICVV, CSIC-CAR-UR), 26007 Logroño, La Rioja, Spain

Correspondence: gmonr[email protected]

Abstract

Mutation is the ultimate source of genetic variation. Mutation rate variability has been observed within plant

genomes, but the underlying mechanisms have been unclear. We previously found that mutations occur less often in

functionally constrained regions of the genome in Arabidopsis thaliana and that this mutation rate reduction is

predicted by H3K4me1, a histone modi

ﬁcation found in the gene bodies of actively expressed and evolutionarily

conserved genes in plants. We reanalyzed de novo germline single base substitutions in fast neutron irradiated

mutation accumulation lines in Kitaake rice (Oryza sativa) and found the same reduction in mutations associated with

H3K4me1, gene bodies, and constrained genes as in A. thaliana, suggesting conserved mechanisms for mutation

reduction in plants. Here, we characterize a model of targeted DNA repair to explain these observations; PDS5C and

MSH6 DNA repair-related proteins target H3K4me1 through their Tudor domains, resulting in nearby DNA

experiencing elevated repair. Experimental data and in-silico modeling support the high a

ﬃnity of the Tudor domain

for H3K4me1 in both proteins, and that this a

ﬃnity is conserved between plant species. ChIP-seq data from PDS5C

con

ﬁrms its localization to conserved and low mutation rate genome regions. Somatic and germline mutations

observed by deep sequencing of wild-type and MSH6 knockout lines con

ﬁrm that MSH6 preferentially repairs gene

bodies and H3K4me1-enriched regions. These ﬁ

ndings inspire further research to characterize the origins of

mechanisms of targeted DNA repair in eukaryotes and their consequences on tuning the evolutionary trajectories of

genomes.

Introduction

Mutations occur when DNA damage or replication

error goes unrepaired. Mechanisms that localize DNA repair

proteins to certain genome regions, such as by binding

certain histone modi

ﬁcations, reduce local mutation rates.

Interactions between DNA repair and histone modi

ﬁcations

are predicted to evolve if they promote repair in regions

prone to deleterious mutations, such as coding regions of

essential genes (Lynch, 2010; Martincorena and Luscombe,

2013; Lynch et al., 2016).

Associations between histone modi

ﬁcations and

mutation rates have been observed across diverse

organisms (Habig et al., 2021; de la Peña et al., 2022; Yang

et al., 2021; Yan et al., 2021; Monroe et al., 2022; Makova

and Hardison, 2015; Schuster-Böckler and Lehner, 2012).

The localization of DNA repair proteins responsible for such

mutation biases has been well-established in humans

(Supek and Lehner, 2015, 2017, 2019; Foster et al., 2015;

Katju et al., 2022). In vertebrates, H3K36me3 is targeted by

PWWP domains in proteins contributing to

homology-directed and mismatch repair, with H3K36me3

marking the gene bodies and exons of active genes (Li et

al., 2013; Huang et al., 2018; Fang et al., 2021; Aymard et

al., 2014; Sun et al., 2020). As predicted, reduced mutation

rates in active genes and gene bodies have been observed

in humans and other animals (Moore et al., 2021; Akdemir et

al., 2020; Li et al., 2021; Katju et al., 2022; Supek and

Lehner, 2017).

1The author(s) responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described

in the Instructions for Authors (https://academic.oup.com/plcell/pages/General-Instructions) is (are): Grey Monroe ([email protected]).

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Reduced mutation rates in gene bodies and active

genes have also been observed in some algae and land

plants, but the mechanism has been unclear (Bel

ﬁeld et al.,

2021; Lu et al., 2021; Zhu et al., 2021; Monroe et al., 2022;

Bel

ﬁeld et al., 2018; López-Cortegano et al., 2021; Yan et

al., 2021; Krasovec et al., 2017). Knockout lines of MSH2,

the mismatch repair protein that dimerizes with MSH6 to

form MutSα (Adé et al., 1999; Kolodner, 1996), indicate that

mismatch repair can preferentially target gene bodies in

plants. Yet, a speci

ﬁc mechanism of such targeting is

unresolved (Bel

ﬁeld et al., 2018).

In plants, H3K4me1 marks gene bodies of active

genes. Recent work has demonstrated that H3K4me1

enrichment is mediated by a combination of

transcription-coupled (ATXR7) and epigenome-guided

(ATX1, ATX2) methyltransferases (Oya et al., 2021). Once

established, H3K4me1 reading can occur by proteins

containing histone-reader domains such as “Royal family”

Tudor domains, which bind methylated lysine residues on

H3 histone tails (Kim et al., 2006; Lu and Wang, 2013;

Maurer-Stroh et al., 2003).

Recently, the Tudor domain of PDS5C was shown

to speci

ﬁcally bind H3K4me1 in A. thaliana (Niu et al., 2021).

This gene is also a cohesion cofactor that facilitates

homology-directed repair (Pradillo et al., 2015; Phipps and

Dubrana, 2022; Morales et al., 2020). Recent studies of

CRISPR-mediated mutation e

ﬃciency show that H3K4me1

is associated with lower mutation e

ﬃcacy (

R = -0.64),

supporting more e

ﬃcient repair (Weiss et al., 2022; Schep et

al., 2021; Zhu et al., 2021). These ﬁ

ndings are consistent

with analyses of mutation accumulation lines in A. thaliana,

which ﬁ

nd H3K4me1 associated with lower mutation rates

(Monroe et al., 2022). Still, the extent and consequences of

targeted DNA repair remain contentious (Liu and Zhang,

2022).

Here, we reanalyzed de novo mutations from

whole-genome-sequenced fast neutron mutation

accumulation lines in Kitaake Rice (O. sativa) (Li et al., 2017)

showing similar patterns of mutation reduction and

H3K4me1 association as A. thaliana. We then characterize a

mechanistic model to explain these observations, involving

PDS5C and MSH6 proteins targeting H3K4me1 via Tudor

domains.

Results and Discussion

Mutations in O. sativa FN-irradiated lines re

ﬂect no

selection on SBS mutations

Mutagenesis has been used extensively in the

generation and study of plant mutation. With single base

substitutions (SBS) in fast-neutron mutation accumulation

lines largely re

ﬂecting native mutational processes (Wyant et

al., 2022; Li et al., 2017), the distribution of these de novo

mutations could provide insights into mechanisms

underlying intragenomic heterogeneity in mutation rate.

We ﬁ

rst reanalyzed de novo mutations in a

population of 1,504 O. sativa lines that accumulated

mutations upon fast neutron radiation. These data were

previously described, and single base-pair substitutions

(SBS) were validated with a >99% true positive rate (Li et al.,

2017). In total, these data included 43,483 SBS, comprising

a combination of indistinguishable fast neutron-related and

“spontaneous” mutations (Fig. 1). We restricted our

analyses to SBS mutations to preclude selection that may

have occurred in the generation of these lines on insertions,

deletions, and structural variants (i.e., whole gene deletions).

To quantitatively evaluate whether selection on SBS

mutations occurred in these lines, we examined

non-synonymous and synonymous mutation rates. The ratio

of non-synonymous to synonymous mutations in mutation

accumulation lines was 2.33 (N/S=5,370/2,155), a 190%

increase over this ratio (Pn/Ps = 1.21) observed in

polymorphisms of 3,010 sequenced O. sativa accessions

(Wang et al., 2018) (X

= 670.63, p<2x10

-16

). The ratio of

non-synonymous to synonymous de novo mutations was

not higher in transposable elements (TE) (N/S=2.31) than in

non-TE protein-coding genes (N/S=2.34) (X

= 0.035, p =

0.85) nor was it less in coding genes than neutral

expectations (N/S=2.33) based on mutation spectra and

nucleotide composition of coding regions in the O. sativa

genome (X

= 0.029, df = 1, p = 0.86) (Fig. S1, methods). To

con

ﬁrm that this non-signiﬁcance was not simply due to a

lack of power, we tested how many non-synonymous

mutations would have to be “missing” because of selection

to explain the 29% reduction in mutation rate of coding

genes relative to non-genic (intergenic, TE) regions we

observed in downstream analyses. Given that coding

regions constitute only 37% of gene bodies (the rest being

intronic and untranslated exonic regions), we ﬁ

nd that 34%

of non-synonymous mutations would have to have been

missing due to selection, which would be readily detected

by a signi

ﬁcant deviation from the null expectation (X

224.4, df = 1, p < 2e-16). In conclusion, we detect no

evidence of selection on SBS mutations, providing an

opportunity to study de novo mutation rate heterogeneity

before selection.

We then compared SBS spectra in trinucleotide

contexts from these lines with de novo germline mutations

in A. thaliana (Weng et al., 2019; Monroe et al., 2022) and

found that they are signi

ﬁcantly correlated (Fig. 1A, r=0.8,

p<2x10

-16

). We cannot know how much of the residual

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ﬀerence in SBS spectra is due to the eﬀects of fast

neutron mutagenesis versus natural di

ﬀerences between O.

sativa and A. thaliana, as variations in the spectra of SBS

have been reported between related species and even

ﬀerent genotypes of the same species (Jiang et al., 2021;

Sasani et al., 2022; Cagan et al., 2022). Future work will

bene

ﬁt from the evaluation of de novo mutations arising in

ﬀerent species under diverse conditions to understand the

environmental and genetic controls of SBS mutational

spectra in plants.

H3K4me1 marks low mutation rate regions in O. sativa,

including gene bodies, and transcriptionally active and

evolutionarily conserved genes

To test whether the genome-wide distribution of

mutations in O. sativa is associated with histone

modi

ﬁcations, we used data from the riceENCODE

epigenomic database, which includes H3K4me1, H3K9me1,

H3K4me3, H3K36me3, H3K9me2, H3K27me3, H3K27ac,

H3K4ac, H3K12ac, H3K9ac, and RNA polymerase II (PII)

measured by chromatin immunoprecipitation sequencing

(ChIP-seq) (Xie et al., 2021). We then tested whether

mutation probabilities in 100bp windows in genic regions

(the probability of observing a mutation) were predicted by

epigenomic features and found a signi

ﬁcant reduction in

mutation probabilities in windows that overlapped with

H3K4me1 peaks (Fig. 1B). These data are consistent with

observations in other plant species where lower mutation

rates have been observed in regions marked by H3K4me1

(Monroe et al., 2022; Weiss et al., 2022). To further con

ﬁrm

that these patterns were not due to selection, we also

restricted our analyses to only those genes in which

loss-of-function mutations were found in the population (Li

et al., 2017) and observed similar results (Fig. S2). We

considered that mutation rate heterogeneity was possibly

caused by GC>AT mutations in transposable elements with

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elevated cytosine methylation in non-genic sequences

rather than histone-mediated mutation reduction. Therefore,

we restricted our analyses to exclude all such GC>AT

mutations and observed similar results.

H3K4me1-associated hypomutation was also the same

when analyses were restricted to only homozygous

mutations (Fig. S2). We further repeated analyses with other

regression approaches: single predictor binomial regression,

multiple linear regression, Poisson regression, and model

selection based on AIC. In all cases, H3K4me1 was found to

have the most signi

ﬁcant association with reduced mutation

rates (Fig. S4)

We calculated mutation rates in genes and their

neighboring sequences and observed a signi

ﬁcant reduction

in mutation rates in gene bodies (Fig. 1C), consistent with

lower mutation rates in gene bodies of other plants.

Mutation rates were lower both in and around H3K4me1

peaks, which could indicate the action of local recruitment

and targeting of DNA repair to H3K4me1 marked sequences

including gene bodies (Fig. 1D). That mutation rates were

also lower in sequences immediately neighboring H3K4me1

peaks could indicate a spatially distributed e

ﬀect on

mutation around H3K4me1, or the e

ﬀect of conservative

peak calling (Fig. 1D). Only 8.9% of H3K4me1 peaks were

found outside of non-TE protein-coding genes.

Nevertheless, we could use these instances of non-genic

H3K4me1 to test whether the reduction in mutation rates in

H3K4me1 peaks was due simply to selection against coding

region mutations a

ﬀecting results. When considering all

H3K4me1 peaks, we observed a 20.1% reduction in

mutation rates compared to regions within 2kb outside of

peaks (X

= 124.38, p < 2.2e-16 -). For non-genic H3K4me1

peaks, we observed the same reduction: -20.2% (X

= 9.88,

p = 0.00167). Together, these results suggested a role of

H3K4me1 in localized hypomutation, which could explain

reduced gene body mutation rates observed since gene

bodies are enriched for H3K4me1 (Fig. 1E,F).

We then compared mutation rates between

ﬀerent classes of genes, which proved consistent with the

expected e

ﬀects of increased DNA repair in functionally

constrained genes caused by H3K4me1-localized repair.

Mutation rates were signi

ﬁcantly lower in genes that

overlapped with H3K4me1 peaks, including when

considering only synonymous mutations (Fig S3). H3K4me1

peaks were enriched in genes annotated as expressed

compared with those not expressed (Kawahara et al., 2013)

= 2550961, p < 2x10

-16

). And, as predicted by their

enrichment for H3K4me1, mutation rates were 22% lower in

expressed genes (X

= 63.7, p = 1x10

-15

)(Fig. 1G). This result

was con

ﬁrmed in an analysis restricted to synonymous

mutations in coding regions only, rejecting the hypothesis

that these results are due to selection (Fig. S3). Indeed, the

ratio of non-synonymous to synonymous de novo mutations

in the data was not di

ﬀerent between expressed and

non-expressed genes (X

= 0.0007, p = 0.98) (Fig. S3).

Comparing genes that exhibit di

ﬀerent degrees of selection

in 3,010 natural accessions of O. sativa (Wang et al., 2018),

those under elevated purifying selection with low Pn/Ps

(non-synonymous/synonymous polymorphisms), were

enriched for H3K4me1 peaks (X

= 8045711, p < 2x10

-16

)

and experienced 19% lower mutation rates (X

= 188.5, p <

2x10

-16

) (Fig. 1H). These genes did not have a lower ratio of

non-synonymous to synonymous in de novo mutations (X

0.22, p=0.63) (Fig S3) and the reduction of mutation rates in

conserved genes was con

ﬁrmed by analysis of synonymous

mutations only (Fig S3). We, therefore, ﬁ

nd that mutation

rates are signi

ﬁcantly lower in functionally constrained

genes in O. sativa, which cannot be explained by selection

on non-synonymous mutations, consistent with what has

been previously shown in A. thaliana (Monroe et al., 2022).

PDS5C targets H3K4me1 and is associated with lower

mutation rates

These ﬁ

ndings in O. sativa are consistent with

reports of reduced mutation rates in gene bodies of

expressed and constrained genes in A. thaliana and other

species (Krasovec et al., 2017; Moore et al., 2021; Monroe

et al., 2022). While in humans, this is known to be mediated

by H3K36me3 targeting by DNA repair genes, our results

suggest that H3K4me1 may be a target of DNA repair in

plants. To examine this further, we considered genes with

known H3K4me1 targeting. PDS5C, a gene belonging to a

family of cohesion cofactors that facilitate

homology-directed repair (HDR), contains a Tudor domain

that was recently discovered to speci

ﬁcally bind H3K4me1

(Niu et al., 2021). Analyses of ChIP-seq data of PDS5C-Flag

from A. thaliana show PDS5C is targeted to gene bodies

(which are enriched for H3K4me1 in both O. sativa and A.

thaliana) (Fig. 2A). We also ﬁ

nd that PDS5C is increased in

regions of lower germline mutation rates in A. thaliana,

consistent with recruitment and its function in facilitating

DNA repair (Fig. 2B).

Evolutionary models predict that histone-mediated

repair mechanisms should evolve if they facilitate lower

mutation rates in sequences under purifying selection

(Lynch et al., 2016; Martincorena and Luscombe, 2013). As

predicted by this theory, we ﬁ

nd that PDS5C targeting

(ChIP-seq) is enriched in coding sequences, essential genes

(determined by experiments of knockout lines (Lloyd and

Meinke, 2012; Lloyd et al., 2015)), genes constitutively

expressed (detected in 100% of tissues sampled) (Mergner

et al., 2020), and genes under stronger purifying selection in

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natural populations of A. thaliana (lower Pn/Ps) (1001

Genomes Consortium, 2016) (Fig. 2C-F).

Visualizing the A. thaliana PDS5C protein full-length

model generated by Alphafold (Jumper et al., 2021) reveals

that the PDS5C active domain is separated from the Tudor

domain by unstructured, and potentially ﬂ

exible segments

(Fig. 3A), suggesting that the Tudor domain operates as an

anchor, localizing PDS5C to H3K4me1 and gene bodies of

active genes. PDS5C is a cohesion cofactor linked to

multiple DNA repair pathways. In its role in cohesion

between sister chromatids, it has been reported to promote

HDR (Pradillo et al., 2015). This is consistent with its known

interaction with repair proteins along with the direct

contribution of cohesion and PDS orthologs to the HDR

pathway (Morales et al., 2020; Phipps and Dubrana, 2022;

Hill et al., 2016; Ren et al., 2005; Bolaños-Villegas et al.,

2013; Schubert et al., 2009). The observation that mutation

rates are reduced at H3K4me1 peak regions (Fig. 1)

supports the hypothesis that Tudor domain-mediated

targeting in PDS5C, its orthologs (PDS5A, B, D, and E), or

other repair-related proteins contribute to targeted

hypomutation in the functionally important regions of the

genome. Still, additional experiments are needed to quantify

the precise local e

ﬀect of PDS5C on mutation rate. We

compared the PDS5C Tudor domain sequence between A.

thaliana and O. sativa and found that the critical amino acids

constituting the aromatic cage, where H3K4me1 binding

speci

ﬁcity is determined, are conserved (Fig. 3C),

suggesting a potential role of PDS5C in the mutation biases

observed here in O. sativa (Fig. 1).

Multiple DNA repair mechanisms with Tudor domains

could be in

ﬂuencing mutation biases

The discovery of the PDS5C Tudor domain as an

H3K4me1 targeting domain (Niu et al., 2021) provides an

opportunity to identify other proteins with potential for

H3K4me1-mediated gene body recruitment. We used blastp

to search the A. thaliana proteome for other proteins

containing Tudor domains similar to that of PDS5C. An

analysis of gene ontologies indicated that this gene set is

highly enriched for genes with DNA repair functions (9/29

genes, p=1x10

-11

)(Fig. S5A, Table S1). Five of these were

PDS5C homologs. We also found that MSH6, a DNA

mismatch repair protein, contains a Tudor domain similar to

that of PDS5C, which was an obvious candidate for further

consideration. That the MSH6 homologous protein in

vertebrates instead contains a PWWP that targets gene

bodies via H3K36me3 binding suggests a remarkable

example of convergent evolution between plants and

vertebrates (Li et al., 2013).

Structural modeling prediction of MSH6 structure

using AlphaFold (Jumper et al., 2021) indicates that its Tudor

domain may, like that in PDS5C, function as an anchor,

tethering it to H3K4me1 leading to local increases in DNA

repair (Fig. 3A-B, Fig. S5). Sequence comparison suggests

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that O. sativa MSH6, A. thaliana MSH6, and O. sativa

PDS5C Tudor domains may present a similar binding

preference for H3K4me1 as A. thaliana PDS5C Tudor

domain since key residues forming monomethylated lysine

binding site are conserved between all homologous

domains (Fig. 3C). To test this hypothesis, we modeled A.

thaliana MSH6 and O. sativa MSH6 and PDS5C Tudor

domains with AlphaFold and compared them with the

experimental structure of A. thaliana PDS5C Tudor domain

(PDB:7DE9) (Niu et al., 2021). Superimposition of the three

modeled Tudor domains onto the PDS5C Tudor domain

showed remarkably similar structures with backbone root

mean square deviation (RMSD) values below 1 Å (Fig. S6).

Subsequently, we modi

ﬁed the K4me1 from the H3

tail peptide bound to the PDS5C Tudor domain in ChimeraX

(Goddard et al., 2018) to obtain H3K4, H3K4me2, and

H3K4me3. Using Rosetta FlexPepDock (Raveh et al., 2010),

we modeled the docking of the di

ﬀerent methylation states

of H3K4 to the Tudor domains of PDS5C and MSH6 from A.

thaliana and O. sativa.

We analyzed the geometry of the binding site in the

top 10% of models based on Rosetta total score, by

measuring the distances of H3K4 nitrogen to the center of

the three aromatic rings forming the aromatic cage in the

Tudor domains (Fig 3D). The experimental structure of the

PDS5C Tudor domain bound to H3K4me1 (PDB:7DE9) (Niu

et al., 2021) provided a reference to analyze the geometry of

the aromatic cage. In this structure, the average distance

between H3K4 nitrogen and the aromatic rings is 4.6 Å (Fig.

3D). We calculated this average distance in the in silico

models generated by FlexPepDock and analyzed its

distributions per case (Fig. S7).

We found that by setting a distance threshold of

6Å, we were able to accurately calculate the proportion of

generated models with the H3K4 inside the aromatic cage.

For the A. thaliana PDS5C Tudor, the proportion of models

with H3K4 inside the aromatic cage was a near-perfect

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correlation (r=0.999) with the dissociation constant values

obtained experimentally by ITC (Figure 3E). Therefore, we

reasoned that we could apply this approach to predict the

binding preference of the Tudor domains of A. thaliana

MSH6 and O. sativa MSH6 and PDS5C to the di

ﬀerent

epigenetic marks. For all three cases, we observed that

H3K4me1 was the mark sampled more often inside the

aromatic cage (Fig. 3E), followed by H3K4me2, and

H3K4me3, aligning with the experimental results for the

Tudor domain of A. thaliana PDS5C. Interestingly, lack of

methylation resulted in almost no sampling of geometries

within the aromatic cage, which aligns with ITC experimental

results that show no detectable binding of H3 tail peptide by

the PDS5C Tudor domain when K4 was not methylated (Niu

et al., 2021). These results suggest that MSH6 and PDS5C

Tudor domains bind to H3K4 with more a

ﬃnity when it is in

the monomethylated state (H3K4me1). While binding to

H3K4me2 and me3 is possible, our results suggest a larger

energetic barrier to access the aromatic cage for these two

states and lower a

ﬃnity. However, binding experiments

must be conducted to obtain dissociation constant values,

thus determining the exact selectivity for H3K4me1 over

H3K4me2 and H3K4me3 of these Tudor domains.

Based on previous experimental data and our

computational analysis, we conclude that MSH6 and

PDS5C Tudor domains bind to H3K4 preferentially when it is

in the monomethylated state (H3K4me1). Interestingly,

in-silico predictions suggest di

ﬀerent levels of aﬃnity

between the Tudor domains, which could lead to di

ﬀerences

in their contribution to the H3K4me1-associated mutation

rate reduction. The similar binding preference of PDS5C and

MSH6 Tudor domains suggests that multiple repair

pathways could have evolved H3K4me1-targeting potential

in plants, motivating additional experiments and

investigations into the evolutionary origins of these

mechanisms. Because MSH6 operates as a dimer with

MSH2 to form the MutSα complex, which recognizes and

repairs small mismatches, its Tudor domain could explain

the previous observation that MSH2 preferentially targets

gene bodies to reduce mutation rates therein (Bel

ﬁeld et al.,

2018). These ﬁ

ndings are consistent with extensive work

showing that mutation rates can be lower in gene bodies of

active and conserved genes, but suggest that these

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mechanisms are independent of, while functionally

analogous to, similar mechanisms known in vertebrates

(H3K36me3 targeted repair described in the introduction).

Further experiments are needed - the reduced mutation

rates in gene bodies in active genes in plants may be

explained by multiple mechanisms collectively targeting

H3K4me1 or additional histone states via Tudor domains as

well as other histone modi

ﬁcations and readers (Davarinejad

et al., 2022; Liu et al., 2022).

de novo mutations in MSH6 knockout lines indicate

targeted repair of gene bodies and H3K4me1 marked

regions

To experimentally test the e

ﬀect of MSH6 in

targeted DNA repair and their potential consequence in the

reduction in mutation rates associated with H3K4me1 and

therefore gene bodies, we performed deep sequencing

(250x depth coverage) of 3-week old rosettes of A. thaliana

of 7 MSH6 knockout line SALK_037557 (msh6/msh6), 1

MSH6 knockout line SALK_089638 (msh6/msh6), 2

heterozygous SALK_089638 lines (WT/msh6), and 9

wildtypes (WT/WT) lines (Fig. 4A). Variant caller Strelka2 was

used in TUMOR-NORMAL mode to call SBS mutations for

each sample following a strict ﬁ

ltering process to call true

mutations. In summary, variants were kept if they were

called in only 1 sample, PASS for all 16 “NORMAL”

comparisons reported by Strelka2 (Kim et al., 2018), the

distance to nearest mutation >1000 bp, total read depth

>150, and alt read support > 5. Somatic vs de novo

germline mutations were distinguished based on deviation

from expected alternative variant frequencies (X

p<0.001,

alt reads < 50%) (Fig. S8B). As expected, the total number

of somatic mutations was higher in the MSH6 knockout

lines (mean±SE = 40.25±3.14 per sample) than in wild-type

and SALK_089638c heterozygous lines (14.1±2.31 per

sample). Mutations from heterozygotes were combined with

wild-type samples for further comparisons because

heterozygous lines exhibited the wild-type phenotypes (Fig.

S8A).

As expected due to mismatches arising from the

tendency for oxidized guanine (8-oxoG) to mispair with

adenine (Fig. 4D) (Kino et al., 2017), C>A and T>G

substitutions were proportionally higher in MSH6 knockout

lines (Fig. 4C), which is consistent with mutational

signatures observed in mismatch repair (MMR) de

ﬁcient

organisms (Sanders et al., 2021; Lujan et al., 2014). This

increase in C>A and T>G SBS was also found for the de

novo germline mutations (Fig. S6C). This result is consistent

with the high a

ﬃnity of MutSα for 8-oxoG:A mispairings

(Mazurek et al., 2002). In light of evidence that MSH6

physically binds MutY (Gu et al., 2002; Hahm et al., 2022)

and interacts synergistically with OGG1 (Ni et al., 1999;

Pavlov et al., 2003), both proteins responsible for 8-oxoG:A

base-excision repair (BER), we cannot exclude the

possibility that MSH6 promotes the local activity of multiple

(MMR and BER) repair pathways. MSH6 also in

ﬂuences

somatic recombination in A. thaliana (Li et al., 2006;

Gonzalez and Spampinato, 2020). Future studies should

also consider the potential e

ﬀects of somatic recombination

on local mutaiton rate.

To test whether MSH6 contributes to the reduction

in mutation rates in gene bodies and H3K4me1 marked

regions, we explored changes in the proportion of mutations

in MSH6 knockout and wild-type lines. The distribution of

mutations in wild-type plants around genes was consistent

with what has been previously reported (Monroe et al.,

2022), while in MSH6 knockout mutant lines gene body

mutation rates were increased, consistent with MSH6

targeting to gene bodies in wild-type plants (Fig. 4E). In

gene bodies, mutation rates were more than 4.5X higher in

MSH6 knockout lines than the wildtype and heterozygous

samples, while the increase of mutations in intergenic

regions and TEs was signi

ﬁcantly less, 2.4X and 1.7X,

respectively (Fig. 4F). We also estimated the mutation ratio

in relation to H3K4me1 ChIP-seq enrichment, and found

that MSH6 knockout lines contain ~5X more mutations in

genome regions most highly enriched for H3K4me1, with

regions containing less H3K4me1 experiencing signi

ﬁcantly

lower increase mutation rates in the knockout lines (Fig. 4G).

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(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made

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Quiroz et al., 2022, biorxiv H3K4me1-targeted DNA repair in plants

Experimental results are consistent with the

hypothesis that H3K4me1 marked genome regions

experience targeted DNA repair in plants, with the Tudor

domain of repair proteins providing a mechanistic basis for

this recruitment. These results inspire future functional

studies of this and other potential candidate genes

ﬂuencing targeted DNA repair and emergent mutation

biases.

Conclusions

We found evidence of mutation bias associated

with H3K4me1-mediated DNA repair in O. sativa and

examined potential mechanisms conserved in plants (Fig. 5).

Our observations here are derived from reanalyses of data

generated by independent research groups (Li et al., 2017;

Niu et al., 2021; Xie et al., 2021) and prove consistent with

previous reports of mutation biases in A. thaliana (Monroe et

al., 2022). The mechanisms revealed are aligned with

evolutionary models of evolved mutation bias, indicating

targeting of mismatch repair and homology-directed repair

pathways to regions of the genome functionally sensitive to

mutation: coding regions and genes under stronger

evolutionary constraints. Furthermore, we ﬁ

nd genetic

evidence that MSH6 regulates the reduced mutation rate in

gene bodies and H3K4me1-marked regions in A. thaliana.

Functional characterization of PDS5 proteins is still required

to estimate their in

ﬂuence over lower mutation rates in

H3K4me1-associated regions. These ﬁ

ndings provide a

plant-speci

ﬁc and higher-resolution mechanistic model of

hypomutation in gene bodies and essential genes,

motivating experimental investigations to further elucidate

the extent, evolutionary origins, and consequences of

chromatin-targeted DNA repair.

Acknowledgments

The research was conducted at the University of California

Davis, which is located on land which was the home of the

Patwin people for thousands of years. We thank Satoyo

Oya, Tetsuji Kakutani, and Soichi Inagaki for their feedback

and insights on H3K4me1. The Monroe Lab is supported by

FFAR grant ICRC20-0000000014, USDA-NIFA grant

108681-Z5327202, UC Davis STAIR grant, and CPRB grant

HG-2022-35.

Author Contributions

DQ, DL, and GM designed the research; DQ, DL, KZ, LO, AA

and GM performed research; DQ, DL, KZ, AP, VY, PC, and

GM contributed new analytic/computational/etc. tools; DQ,

DL, KZ VY, AP, PC, and GM analyzed data; and DQ, DL, KZ,

VY, PC, and GM wrote the paper.

Methods

Mutation dataset in O. sativa

Germline de novo mutations in 1,504 fast neutron

mutagenesis lines were downloaded from Kitbase at

kitbase.ucdavis.edu. These were independently called and

validated as previously described (Li et al., 2017). We

focused speci

ﬁcally on single base substitutions (SBS),

which were validated with a >99% accuracy by Li et al.

(2017). We annotated each SBS in coding regions as being

a synonymous or non-synonymous mutation based on the

ﬀect on the amino acid sequence. We compared

non-synonymous and synonymous ratios with values from

genomes of 3,010 natural accessions (Wang et al., 2018)

and neutral expectations based on mutation spectra, coding

region nucleotide composition, and codon table with the

Null_ns_s function from the polymorphology package in R

(https://github.com/greymonroe/polymorphology/blob/main/

R/Null_ns_s.R).

Epigenomic data collection

Epigenome features were accessed from the RiceENCODE

database (glab.hzau.edu.cn/RiceENCODE/), which has been

previously described (Xie et al., 2021). In brief, peaks were

called from ChIP-seq data with MACS2 (Zhang et al., 2008)

narrow-peak calling settings. We analyzed peak

distributions for H3K4me1, H3K9me1, H3K4me3,

H3K36me3, H3K9me2, H3K27me3, H3K27ac, H3K4ac,

H3K12ac, H3K9ac, and RNA polymerase II (PII) measured in

Nipponbare O. sativa plant seedlings, which constituted the

most complete set of histone modi

ﬁcations available. We

repeated analyses but with H3K4me1 measurements

derived from panicles and leaves (rather than seedlings) and

found essentially the same results.

For downstream analyses comparing changes in

mutation in MSH6 knockout mutant lines as a function of

H3K4me1, we accessed a collection of H3K4me1 ChIPseq

datasets from A. thaliana maintained by the Plant Chromatin

State Database (Liu et al., 2018). From these, we calculated

the normalized mean across all datasets in 200 bp sliding

(100 bp) windows across the entire genome.

Estimation of the relationship between mutation rates

and O. sativa epigenomic features

We divided the genome into 100 bp windows

surrounding genes (+- 3000 bp of genes). This allowed us

to, in later steps, restrict our analyses to only genes known

to have accumulated loss-of-function mutations, and thus

be less likely to be a

ﬀected by selection. We also divided

the genome into 100bp windows and repeated analyses, to

con

ﬁrm that results were generally the same. We calculated

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Quiroz et al., 2022, biorxiv H3K4me1-targeted DNA repair in plants

the number of single base-pair substitutions and peaks for

each epigenomic feature overlapping within each window.

We then estimated the relationships between epigenomic

features and mutation rates with a binomial generalized

linear model where the response was a binary state de

ﬁned

as whether a substitution occurred in that window,

predicted by all features, with predictors de

ﬁned as whether

that window overlapped with an epigenome peak. We also

repeated the analyses with a linear regression model where

the response was the number of mutations in a window and

found essentially the same results, so we show the binomial

regression results. To test whether ﬁ

ndings were driven

simply by GC>AT mutations in transposable elements, we

removed all GC>AT and repeated analyses. To further

control for any residual selection in the mutation

accumulation experiment, we also restricted our analyses to

genes harboring loss-of-function mutations in the

population and repeated the analyses. Finally, we restricted

analyses to homozygous SBS and repeated the analyses.

Mutation frequencies were plotted around genes in 100 bp

windows. Since gene bodies are di

ﬀerent lengths, the

position of the window was converted into a percent of

gene length. H3K4me1 peaks around gene bodies were

plotted similarly. We also visualized mutation frequencies

relative to H3K4me1 peaks in the same manner.

Analysis of ChIP-seq data of AtPDS5C

To study the distribution of PDS5C, we used ChIP-seq data

as described by Niu et al. (2021). PDS5C enrichment was

calculated as described by Niu et al. (2021) among regions

as log2[(1 + n_ChIP)/N_ChIP] – log2[(1 + n_Input)/N_Input)],

where n_ChIP and n_Input represent the total depth of

mapped ChIP and Input fragments in a region, and N_ChIP

and N_Input are the numbers total depths of mapped

unique fragments. We calculated PDS5C enrichment in

genic features (1000 bp upstream and downstream of

genes, UTRs, introns, coding regions) and gene bodies (TSS

to TTS) across the TAIR10 A. thaliana genome

(arabidopsis.org).

Relationship between AtPDS5C and functional

constraint

We analyzed the enrichment of the PDS5C ChIP-seq peaks

in A. thaliana in genetic features and estimated the

relationships between those regions and mutation rates,

H4K4me1, Pn/Ps, and tissue expression depth. Tissue

expression data are from (Mergner et al., 2020). H3K4me1 in

Arabidopsis is from the Plant Chromatin State Database (Liu

et al., 2018). Synonymous (Ps) and non-synonymous

polymorphism (Pn) data are from the 1001 Genomes project

(1001 Genomes Consortium, 2016). Essential genes were

based on ﬁ

ndings from (Lloyd and Meinke, 2012). Germline

mutation rates are from (Weng et al., 2019; Monroe et al.,

2022).

Blastp and protein structure prediction and visualization

We used blastp on Phytozome (Goodstein et al., 2012) to

search the O. sativa proteome for PDS5C and MHS6

orthologs and to search the A. thaliana proteome for genes

containing Tudor domains similar to that of PDS5C, which

was validated experimentally to bind H3K4me1 (Niu et al.,

2021). We submitted the resulting list of 29 genes with

putative Tudor domains to gene ontology analysis with

ShinyGO (bioinformatics.sdstate.edu/go/)(Ge et al., 2019).

Protein structure predictions were performed using

AlphaFold (Jumper et al., 2021) in Google Colab (Mirdita et

al., 2022) in no-template mode. All structures were

visualized, processed, and analyzed using UCSF ChimeraX

(Goddard et al., 2018).

Peptide docking

H3 tail peptides comprising 5 amino acids with the different

methylation states for K4 (none, mono, di or trimethylated)

were docked to the experimental structure of A. thaliana

PDS5C Tudor domain and to the models of A. thaliana and

O. sativa MSH6 and O. sativa PDS5C Tudor domains using

Rosetta FlexPepDock tool (Raveh et al., 2010) in re

ﬁnement

mode. We generated 10,000 docked models per case and

analyzed the top 10% based on Rosetta's total score.

Analysis of the outputs was conducted using PyRosetta

home-made scripts (Chaudhury et al., 2010) to measure the

average distance of lysine 4 nitrogen in histone 3 to the

center of the aromatic rings in the residues forming the

aromatic cage in Tudor domains.

Somatic mutations in MSH6 Knockout lines

To study the e

ﬀect of MSH6 in H3K4me1 targeted repair we

performed 250x coverage sequencing analyses of 17 A.

thaliana; 9 WT/WT, 7 msh6/msh6 (6 SALK_037557 and 1

SALK_089638) and 2 msh6/WT (2 heterozygous

SALK_089638). In brief, 3 week old plants were harvested,

stems and roots were removed and rosettes were stored at

-80 ºC. Whole rosettes were grinded using a mortar and

liquid nitrogen and Qiagen DNeasy Plant Mini Kit (Cat No:

69106) following the manufacturer's instructions. Illumina

library preparation and Whole-genome DNA sequencing

with NovaSeq (150-bp read length at high genomic

coverage ~250x) was performed by the UC Davis Genome

Center. Reads were trimmed with trimmomatic (Bolger et

al., 2014) and duplicates were marked with the samtools

markdup function (Li et al., 2009). Reads were mapped to

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(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made

The copyright holder for this preprintthis version posted November 11, 2022. ; https://doi.org/10.1101/2022.05.28.493846doi: bioRxiv preprint

Quiroz et al., 2022, biorxiv H3K4me1-targeted DNA repair in plants
the A. thaliana TAIR10 reference genome with bwa mem(Li
and Durbin, 2009). Strelka2 variant caller in
TUMOR-NORMAL mode (each sample was compared to all
other 16 samples as NORMALs) was used to call SBS in the
sequenced samples (Kim et al., 2018). Mutations found
were ﬁ
ltered by keeping variants called in only one sample,
given a PASS quality score in all 16 ”NORMAL”
comparisons. In addition to the built-in ﬁ
lters imposed by
Strelka2 for variants to receive a PASS, which “include (1)
the genotype probability computed by the core variant
probability model, (2) root-mean-square mapping quality, (3)
strand bias, (4) the fraction of reads consistent with locus
haplotype model, and (5) the complexity of the reference
context as measured by metrics such as homopolymer
length and compressibility” (Kim et al., 2018), we further
ﬁ
ltered to only include variants in which the distance to the
nearest mutation was >1000 bp, total read depth >150 and
alt read support > 5. To distinguish somatic mutations from
de novo heterozygous variants, read-depths between
alternative and reference alleles were compared with an X
2
test against the expected 50/50 ratio for heterozygous
variants. Mutations were considered somatic if the X
2
test
statistic p-value was less than 0.001 (to account for
multiple testing) and the alt read depth was < 50%
Homozygous de novo germline mutations were identi
ﬁed
when X
2
test statistic p-value was less than 0.001 and the
alt read depth was >50%. Complete code for variant calling,
post-processing, and analyses are maintained on
https://github.com/greymonroe/Quiroz_H3K4me1_mediated
_repair.
Code and data
Figures, code, and data are located on:
https://github.com/greymonroe/Quiroz_H3K4me1_mediated
_repair.
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Supplemental Table 1

Enrichment FDR

nGenes

Pathway Genes

Fold Enrichment

Pathway

URL

Genes

4.04E-16

483.49

Mitotic sister

chromatid

cohesion

http://amigo.gene

ontology.org/amig

o/term/GO:00070

AT1G15940

AT1G77600

AT1G80810

AT4G31880

AT4G32620

AT5G10950

AT5G47690

3.08E-14

251.817708

Sister chromatid

cohesion

http://amigo.gene

ontology.org/amig

o/term/GO:00070

AT1G15940

AT1G77600

AT1G80810

AT4G31880

AT4G32620

AT5G10950

AT5G47690

3.70E-06

199.240385

Microsporogenesi

http://amigo.gene

ontology.org/amig

o/term/GO:00095

AT1G15940

AT4G31880

AT5G47690

1.21E-12

138.933908

Sister chromatid

segregation

http://amigo.gene

ontology.org/amig

o/term/GO:00008

AT1G15940

AT1G77600

AT1G80810

AT4G31880

AT4G32620

AT5G10950

AT5G47690

4.08E-12

109

110.892202

Mitotic nuclear

division

http://amigo.gene

ontology.org/amig

o/term/GO:01400

AT1G15940

AT1G77600

AT1G80810

AT4G31880

AT4G32620

AT5G10950

AT5G47690

8.62E-12

126

95.9305556

Nuclear

chromosome

segregation

http://amigo.gene

ontology.org/amig

o/term/GO:00988

AT1G15940

AT1G77600

AT1G80810

AT4G31880

AT4G32620

AT5G10950

AT5G47690

1.97E-11

146

82.7893836

Chromosome

segregation

http://amigo.gene

ontology.org/amig

o/term/GO:00070

AT1G15940

AT1G77600

AT1G80810

AT4G31880

AT4G32620

AT5G10950

AT5G47690

2.95E-10

217

55.7016129

Nuclear division

http://amigo.gene

ontology.org/amig

o/term/GO:00002

AT1G15940

AT1G77600

AT1G80810

AT4G31880

AT4G32620

AT5G10950

AT5G47690

5.37E-10

242

49.947314

Mitotic cell cycle

proc.

http://amigo.gene

ontology.org/amig

o/term/GO:19030

AT1G15940

AT1G77600

AT1G80810

AT4G31880

AT4G32620

AT5G10950

AT5G47690

8.03E-10

259

46.6689189

Organelle fission

http://amigo.gene

ontology.org/amig

o/term/GO:00482

AT1G15940

AT1G77600

AT1G80810

AT4G31880

AT4G32620

AT5G10950

AT5G47690

6.42E-12

397

39.145466

DNA repair

http://amigo.gene

ontology.org/amig

o/term/GO:00062

AT1G15940

AT1G77600

AT1G80810

AT4G02070

AT4G31880

AT4G32620

AT4G32970

AT5G10950

AT5G47690

1.05E-11

431

36.0574246

Cellular response

to DNA damage

stimulus

http://amigo.gene

ontology.org/amig

o/term/GO:00069

AT1G15940

AT1G77600

AT1G80810

AT4G02070

AT4G31880

AT4G32620

AT4G32970

AT5G10950

AT5G47690

3.00E-12

564

30.6161348

Chromosome

organization

http://amigo.gene

ontology.org/amig

o/term/GO:00512

AT1G05830

AT1G15940

AT1G77600

AT1G80810

AT2G31650

AT4G02070

AT4G31880

AT4G32620

AT5G10950

AT5G47690

1.14E-09

484

28.5413223

Cell cycle proc.

http://amigo.gene

ontology.org/amig

o/term/GO:00224

AT1G15940

AT1G77600

AT1G80810

AT4G02070

AT4G31880

AT4G32620

AT5G10950

AT5G47690

4.51E-10

678

22.9214602

DNA metabolic

proc.

http://amigo.gene

ontology.org/amig

o/term/GO:00062

AT1G15940

AT1G77600

AT1G80810

AT4G02070

AT4G31880

AT4G32620

AT4G32970

AT5G10950

AT5G47690

7.35E-08

1265

12.2851779

Cellular response

to stress

http://amigo.gene

ontology.org/amig

o/term/GO:00335

AT1G15940

AT1G77600

AT1G80810

AT4G02070

AT4G31880

AT4G32620

AT4G32970

AT5G10950

AT5G47690

9.00E-08

1845

9.35907859

Organelle

organization

http://amigo.gene

ontology.org/amig

o/term/GO:00069

AT1G05830

AT1G15940

AT1G77600

AT1G80810

AT2G31650

AT4G02070

AT4G31880

AT4G32620

AT5G10950

AT5G47690

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