Paper
Mutation Rate Variation Across Genomic Regions in \textit{Arabidopsis thaliana}
Authors
Elisa Heinrich-Mora, Marcus W. Feldman
Abstract
In population genetics, mutation rate is often treated as a homogeneous parameter across the genome. Empirical evidence, however, shows systematic variation across genomic contexts associated with chromatin organization and epigenomic features. Using gene-level de novo mutation data from Arabidopsis thaliana, we test whether chromatin features predict not only the mean per-base mutation rate but also its variability across genes. To reduce heterogeneity in selective regime, we restrict analysis to essential and lethal loci subject to strong purifying selection. Across complementary multivariable models including heteroskedasticity-robust linear regression, length-weighted regression, and Poisson generalized linear models with exposure offsets, histone marks associated with active transcription (H3K4me1, H3K4me3, H3K36ac) are consistently associated with lower mean mutation rates and substantially reduced between-gene variance. GC content shows little association with the mean once chromatin predictors are controlled but is positively associated with mutation-rate variability. Estimates of skewness and kurtosis reveal no significant higher-order structure attributable to epigenomic predictors. A standardized Tajima's $D$ statistic yields directionally consistent but statistically underpowered associations with both the mean and variance of gene-level mutation rates. These results indicate that mutation rate is systematically structured by chromatin state within functionally constrained genes and suggest that evolutionary processes may act not only on expected mutation rate but also on its variability across loci.
Metadata
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Raw Data (Debug)
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"raw_xml": "<entry>\n <id>http://arxiv.org/abs/2603.03591v1</id>\n <title>Mutation Rate Variation Across Genomic Regions in \\textit{Arabidopsis thaliana}</title>\n <updated>2026-03-03T23:51:04Z</updated>\n <link href='https://arxiv.org/abs/2603.03591v1' rel='alternate' type='text/html'/>\n <link href='https://arxiv.org/pdf/2603.03591v1' rel='related' title='pdf' type='application/pdf'/>\n <summary>In population genetics, mutation rate is often treated as a homogeneous parameter across the genome. Empirical evidence, however, shows systematic variation across genomic contexts associated with chromatin organization and epigenomic features. Using gene-level de novo mutation data from Arabidopsis thaliana, we test whether chromatin features predict not only the mean per-base mutation rate but also its variability across genes. To reduce heterogeneity in selective regime, we restrict analysis to essential and lethal loci subject to strong purifying selection. Across complementary multivariable models including heteroskedasticity-robust linear regression, length-weighted regression, and Poisson generalized linear models with exposure offsets, histone marks associated with active transcription (H3K4me1, H3K4me3, H3K36ac) are consistently associated with lower mean mutation rates and substantially reduced between-gene variance. GC content shows little association with the mean once chromatin predictors are controlled but is positively associated with mutation-rate variability. Estimates of skewness and kurtosis reveal no significant higher-order structure attributable to epigenomic predictors. A standardized Tajima's $D$ statistic yields directionally consistent but statistically underpowered associations with both the mean and variance of gene-level mutation rates. These results indicate that mutation rate is systematically structured by chromatin state within functionally constrained genes and suggest that evolutionary processes may act not only on expected mutation rate but also on its variability across loci.</summary>\n <category scheme='http://arxiv.org/schemas/atom' term='q-bio.PE'/>\n <published>2026-03-03T23:51:04Z</published>\n <arxiv:comment>18 pages, 3 figures</arxiv:comment>\n <arxiv:primary_category term='q-bio.PE'/>\n <author>\n <name>Elisa Heinrich-Mora</name>\n </author>\n <author>\n <name>Marcus W. Feldman</name>\n </author>\n </entry>"
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