A genetic tradeoff for tolerance to moderate and severe heat stress in US hybrid maize.

Global climate change is increasing both average temperatures and the frequencies of extreme high temperatures. Past studies have documented a strong negative effect of exposures to temperatures >30°C on hybrid maize yields. However, these studies could not disentangle genetic adaptation via artificial selection from changes in agronomic practices. Because most of the earliest maize hybrids are no longer available, side-by-side comparisons with modern hybrids under current field conditions are generally impossible. Here, we report on the collection and curation of 81 years of public yield trial records covering 4,730 maize hybrids, which enabled us to model genetic variation for temperature responses among maize hybrids. We show that selection may have indirectly and inconsistently contributed to the genetic adaptation of maize to moderate heat stress over this time period while preserving genetic variance for continued adaptation. However, our results reveal the existence of a genetic tradeoff for tolerance to moderate and severe heat stress, leading to a decrease in tolerance to severe heat stress over the same time period. Both trends are particularly conspicuous since the mid-1970s. Such a tradeoff poses challenges to the continued adaptation of maize to warming climates due to a projected increase in the frequency of extreme heat events. Nevertheless, given recent advances in phenomics, enviromics, and physiological modeling, our results offer a degree of optimism for the capacity of plant breeders to adapt maize to warming climates, assuming appropriate levels of R&D investment.

KAT4IA: K-Means Assisted Training for Image Analysis of Field-Grown Plant Phenotypes.

High-throughput phenotyping enables the efficient collection of plant trait data at scale. One example involves using imaging systems over key phases of a crop growing season. Although the resulting images provide rich data for statistical analyses of plant phenotypes, image processing for trait extraction is required as a prerequisite. Current methods for trait extraction are mainly based on supervised learning with human labeled data or semisupervised learning with a mixture of human labeled data and unsupervised data. Unfortunately, preparing a sufficiently large training data is both time and labor-intensive. We describe a self-supervised pipeline (KAT4IA) that uses K-means clustering on greenhouse images to construct training data for extracting and analyzing plant traits from an image-based field phenotyping system. The KAT4IA pipeline includes these main steps: self-supervised training set construction, plant segmentation from images of field-grown plants, automatic separation of target plants, calculation of plant traits, and functional curve fitting of the extracted traits. To deal with the challenge of separating target plants from noisy backgrounds in field images, we describe a novel approach using row-cuts and column-cuts on images segmented by transform domain neural network learning, which utilizes plant pixels identified from greenhouse images to train a segmentation model for field images. This approach is efficient and does not require human intervention. Our results show that KAT4IA is able to accurately extract plant pixels and estimate plant heights.

Trajectories of Homoeolog-Specific Expression in Allotetraploid Tragopogon castellanus Populations of Independent Origins.

Polyploidization can have a significant ecological and evolutionary impact by providing substantially more genetic material that may result in novel phenotypes upon which selection may act. While the effects of polyploidization are broadly reviewed across the plant tree of life, the reproducibility of these effects within naturally occurring, independently formed polyploids is poorly characterized. The flowering plant genus Tragopogon (Asteraceae) offers a rare glimpse into the intricacies of repeated allopolyploid formation with both nascent (< 90 years old) and more ancient (mesopolyploids) formations. Neo- and mesopolyploids in Tragopogon have formed repeatedly and have extant diploid progenitors that facilitate the comparison of genome evolution after polyploidization across a broad span of evolutionary time. Here, we examine four independently formed lineages of the mesopolyploid Tragopogon castellanus for homoeolog expression changes and fractionation after polyploidization. We show that expression changes are remarkably similar among these independently formed polyploid populations with large convergence among expressed loci, moderate convergence among loci lost, and stochastic silencing. We further compare and contrast these results for T. castellanus with two nascent Tragopogon allopolyploids. While homoeolog expression bias was balanced in both nascent polyploids and T. castellanus, the degree of additive expression was significantly different, with the mesopolyploid populations demonstrating more non-additive expression. We suggest that gene dosage and expression noise minimization may play a prominent role in regulating gene expression patterns immediately after allopolyploidization as well as deeper into time, and these patterns are conserved across independent polyploid lineages.

Co-expression analysis aids in the identification of genes in the cuticular wax pathway in maize.

Epicuticular waxes provide a hydrophobic barrier that protects land plants from environmental stresses. To elucidate the molecular functions of maize glossy mutants that reduce the accumulation of epicuticular waxes, eight non-allelic glossy mutants were subjected to transcriptomic comparisons with their respective wild-type siblings. Transcriptomic comparisons identified 2279 differentially expressed (DE) genes. Other glossy genes tended to be down-regulated in glossy mutants; by contrast stress-responsive pathways were induced in mutants. Gene co-expression network (GCN) analysis found that glossy genes were clustered, suggestive of co-regulation. Genes that potentially regulate the accumulation of glossy gene transcripts were identified via a pathway level co-expression analysis. Expression data from diverse organs showed that maize glossy genes are generally active in young leaves, silks, and tassels, while largely inactive in seeds and roots. Through reverse genetics, a DE gene homologous to Arabidopsis CER8 and co-expressed with known glossy genes was confirmed to participate in epicuticular wax accumulation. GCN data-informed forward genetics approach enabled cloning of the gl14 gene, which encodes a putative membrane-associated protein. Our results deepen understanding of the transcriptional regulation of the genes involved in the accumulation of epicuticular wax, and provide two maize glossy genes and a number of candidate genes for further characterization.

Empirical Comparisons of Different Statistical Models To Identify and Validate Kernel Row Number-Associated Variants from Structured Multi-parent Mapping Populations of Maize.

Advances in next generation sequencing technologies and statistical approaches enable genome-wide dissection of phenotypic traits via genome-wide association studies (GWAS). Although multiple statistical approaches for conducting GWAS are available, the power and cross-validation rates of many approaches have been mostly tested using simulated data. Empirical comparisons of single variant (SV) and multi-variant (MV) GWAS approaches have not been conducted to test if a single approach or a combination of SV and MV is effective, through identification and cross-validation of trait-associated loci. In this study, kernel row number (KRN) data were collected from a set of 6,230 entries derived from the Nested Association Mapping (NAM) population and related populations. Three different types of GWAS analyses were performed: 1) single-variant (SV), 2) stepwise regression (STR) and 3) a Bayesian-based multi-variant (BMV) model. Using SV, STR, and BMV models, 257, 300, and 442 KRN-associated variants (KAVs) were identified in the initial GWAS analyses. Of these, 231 KAVs were subjected to genetic validation using three unrelated populations that were not included in the initial GWAS. Genetic validation results suggest that the three GWAS approaches are complementary. Interestingly, KAVs in low recombination regions were more likely to exhibit associations in independent populations than KAVs in recombinationally active regions, probably as a consequence of linkage disequilibrium. The KAVs identified in this study have the potential to enhance our understanding of the genetic basis of ear development.

Linked read technology for assembling large complex and polyploid genomes.

BACKGROUND: Short read DNA sequencing technologies have revolutionized genome assembly by providing high accuracy and throughput data at low cost. But it remains challenging to assemble short read data, particularly for large, complex and polyploid genomes. The linked read strategy has the potential to enhance the value of short reads for genome assembly because all reads originating from a single long molecule of DNA share a common barcode. However, the majority of studies to date that have employed linked reads were focused on human haplotype phasing and genome assembly. RESULTS: Here we describe a de novo maize B73 genome assembly generated via linked read technology which contains ~ 172,000 scaffolds with an N50 of 89 kb that cover 50% of the genome. Based on comparisons to the B73 reference genome, 91% of linked read contigs are accurately assembled. Because it was possible to identify errors with > 76% accuracy using machine learning, it may be possible to identify and potentially correct systematic errors. Complex polyploids represent one of the last grand challenges in genome assembly. Linked read technology was able to successfully resolve the two subgenomes of the recent allopolyploid, proso millet (Panicum miliaceum). Our assembly covers ~ 83% of the 1 Gb genome and consists of 30,819 scaffolds with an N50 of 912 kb. CONCLUSIONS: Our analysis provides a framework for future de novo genome assemblies using linked reads, and we suggest computational strategies that if implemented have the potential to further improve linked read assemblies, particularly for repetitive genomes.

Intragenic Meiotic Crossovers Generate Novel Alleles with Transgressive Expression Levels.

Meiotic recombination is an evolutionary force that generates new genetic diversity upon which selection can act. Whereas multiple studies have assessed genome-wide patterns of recombination and specific cases of intragenic recombination, few studies have assessed intragenic recombination genome-wide in higher eukaryotes. We identified recombination events within or near genes in a population of maize recombinant inbred lines (RILs) using RNA-sequencing data. Our results are consistent with case studies that have shown that intragenic crossovers cluster at the 5' ends of some genes. Further, we identified cases of intragenic crossovers that generate transgressive transcript accumulation patterns, that is, recombinant alleles displayed higher or lower levels of expression than did nonrecombinant alleles in any of ∼100 RILs, implicating intragenic recombination in the generation of new variants upon which selection can act. Thousands of apparent gene conversion events were identified, allowing us to estimate the genome-wide rate of gene conversion at SNP sites (4.9 × 10-5). The density of syntenic genes (i.e., those conserved at the same genomic locations since the divergence of maize and sorghum) exhibits a substantial correlation with crossover frequency, whereas the density of nonsyntenic genes (i.e., those which have transposed or been lost subsequent to the divergence of maize and sorghum) shows little correlation, suggesting that crossovers occur at higher rates in syntenic genes than in nonsyntenic genes. Increased rates of crossovers in syntenic genes could be either a consequence of the evolutionary conservation of synteny or a biological process that helps to maintain synteny.

Correction to: Genome-wide discovery and characterization of maize long non-coding RNAs.

The original version [1] of this article unfortunately contained a mistake. The additive effects of the eQTLs of lncRNAs were flipped, meaning that the base allele in the contrast to derive the additive effects should have been B73, rather than Mo17, due to the original coding of biallele SNPs as "0s" and "1s". Going through the entire analysis procedure, it was determined that the mistake was made while tabulating the eQTL results from QTL Cartographer.

Maize Genomes to Fields: 2014 and 2015 field season genotype, phenotype, environment, and inbred ear image datasets.

OBJECTIVES: Crop improvement relies on analysis of phenotypic, genotypic, and environmental data. Given large, well-integrated, multi-year datasets, diverse queries can be made: Which lines perform best in hot, dry environments? Which alleles of specific genes are required for optimal performance in each environment? Such datasets also can be leveraged to predict cultivar performance, even in uncharacterized environments. The maize Genomes to Fields (G2F) Initiative is a multi-institutional organization of scientists working to generate and analyze such datasets from existing, publicly available inbred lines and hybrids. G2F's genotype by environment project has released 2014 and 2015 datasets to the public, with 2016 and 2017 collected and soon to be made available. DATA DESCRIPTION: Datasets include DNA sequences; traditional phenotype descriptions, as well as detailed ear, cob, and kernel phenotypes quantified by image analysis; weather station measurements; and soil characterizations by site. Data are released as comma separated value spreadsheets accompanied by extensive README text descriptions. For genotypic and phenotypic data, both raw data and a version with outliers removed are reported. For weather data, two versions are reported: a full dataset calibrated against nearby National Weather Service sites and a second calibrated set with outliers and apparent artifacts removed.

Phenotypic Data from Inbred Parents Can Improve Genomic Prediction in Pearl Millet Hybrids.

Pearl millet is a non-model grain and fodder crop adapted to extremely hot and dry environments globally. In India, a great deal of public and private sectors' investment has focused on developing pearl millet single cross hybrids based on the cytoplasmic-genetic male sterility (CMS) system, while in Africa most pearl millet production relies on open pollinated varieties. Pearl millet lines were phenotyped for both the inbred parents and hybrids stage. Many breeding efforts focus on phenotypic selection of inbred parents to generate improved parental lines and hybrids. This study evaluated two genotyping techniques and four genomic selection schemes in pearl millet. Despite the fact that 6× more sequencing data were generated per sample for RAD-seq than for tGBS, tGBS yielded more than 2× as many informative SNPs (defined as those having MAF > 0.05) than RAD-seq. A genomic prediction scheme utilizing only data from hybrids generated prediction accuracies (median) ranging from 0.73-0.74 (1000-grain weight), 0.87-0.89 (days to flowering time), 0.48-0.51 (grain yield) and 0.72-0.73 (plant height). For traits with little to no heterosis, hybrid only and hybrid/inbred prediction schemes performed almost equivalently. For traits with significant mid-parent heterosis, the direct inclusion of phenotypic data from inbred lines significantly (P < 0.05) reduced prediction accuracy when all lines were analyzed together. However, when inbreds and hybrid trait values were both scored relative to the mean trait values for the respective populations, the inclusion of inbred phenotypic datasets moderately improved genomic predictions of the hybrid genomic estimated breeding values. Here we show that modern approaches to genotyping by sequencing can enable genomic selection in pearl millet. While historical pearl millet breeding records include a wealth of phenotypic data from inbred lines, we demonstrate that the naive incorporation of this data into a hybrid breeding program can reduce prediction accuracy, while controlling for the effects of heterosis per se allowed inbred genotype and trait data to improve the accuracy of genomic estimated breeding values for pearl millet hybrids.

tGBS® genotyping-by-sequencing enables reliable genotyping of heterozygous loci.

Conventional genotyping-by-sequencing (cGBS) strategies suffer from high rates of missing data and genotyping errors, particularly at heterozygous sites. tGBS® genotyping-by-sequencing is a novel method of genome reduction that employs two restriction enzymes to generate overhangs in opposite orientations to which (single-strand) oligos rather than (double-stranded) adaptors are ligated. This strategy ensures that only double-digested fragments are amplified and sequenced. The use of oligos avoids the necessity of preparing adaptors and the problems associated with inter-adaptor annealing/ligation. Hence, the tGBS protocol simplifies the preparation of high-quality GBS sequencing libraries. During polymerase chain reaction (PCR) amplification, selective nucleotides included at the 3'-end of the PCR primers result in additional genome reduction as compared to cGBS. By adjusting the number of selective bases, different numbers of genomic sites are targeted for sequencing. Therefore, for equivalent amounts of sequencing, more reads per site are available for SNP calling. Hence, as compared to cGBS, tGBS delivers higher SNP calling accuracy (>97-99%), even at heterozygous sites, less missing data per marker across a population of samples, and an enhanced ability to genotype rare alleles. tGBS is particularly well suited for genomic selection, which often requires the ability to genotype populations of individuals that are heterozygous at many loci.

A Comprehensive Analysis of Alternative Splicing in Paleopolyploid Maize.

Identifying and characterizing alternative splicing (AS) enables our understanding of the biological role of transcript isoform diversity. This study describes the use of publicly available RNA-Seq data to identify and characterize the global diversity of AS isoforms in maize using the inbred lines B73 and Mo17, and a related species, sorghum. Identification and characterization of AS within maize tissues revealed that genes expressed in seed exhibit the largest differential AS relative to other tissues examined. Additionally, differences in AS between the two genotypes B73 and Mo17 are greatest within genes expressed in seed. We demonstrate that changes in the level of alternatively spliced transcripts (intron retention and exon skipping) do not solely reflect differences in total transcript abundance, and we present evidence that intron retention may act to fine-tune gene expression across seed development stages. Furthermore, we have identified temperature sensitive AS in maize and demonstrate that drought-induced changes in AS involve distinct sets of genes in reproductive and vegetative tissues. Examining our identified AS isoforms within B73 × Mo17 recombinant inbred lines (RILs) identified splicing QTL (sQTL). The 43.3% of cis-sQTL regulated junctions are actually identified as alternatively spliced junctions in our analysis, while 10 Mb windows on each side of 48.2% of trans-sQTLs overlap with splicing related genes. Using sorghum as an out-group enabled direct examination of loss or conservation of AS between homeologous genes representing the two subgenomes of maize. We identify several instances where AS isoforms that are conserved between one maize homeolog and its sorghum ortholog are absent from the second maize homeolog, suggesting that these AS isoforms may have been lost after the maize whole genome duplication event. This comprehensive analysis provides new insights into the complexity of AS in maize.

Extreme-phenotype genome-wide association study (XP-GWAS): a method for identifying trait-associated variants by sequencing pools of individuals selected from a diversity panel.

Although approaches for performing genome-wide association studies (GWAS) are well developed, conventional GWAS requires high-density genotyping of large numbers of individuals from a diversity panel. Here we report a method for performing GWAS that does not require genotyping of large numbers of individuals. Instead XP-GWAS (extreme-phenotype GWAS) relies on genotyping pools of individuals from a diversity panel that have extreme phenotypes. This analysis measures allele frequencies in the extreme pools, enabling discovery of associations between genetic variants and traits of interest. This method was evaluated in maize (Zea mays) using the well-characterized kernel row number trait, which was selected to enable comparisons between the results of XP-GWAS and conventional GWAS. An exome-sequencing strategy was used to focus sequencing resources on genes and their flanking regions. A total of 0.94 million variants were identified and served as evaluation markers; comparisons among pools showed that 145 of these variants were statistically associated with the kernel row number phenotype. These trait-associated variants were significantly enriched in regions identified by conventional GWAS. XP-GWAS was able to resolve several linked QTL and detect trait-associated variants within a single gene under a QTL peak. XP-GWAS is expected to be particularly valuable for detecting genes or alleles responsible for quantitative variation in species for which extensive genotyping resources are not available, such as wild progenitors of crops, orphan crops, and other poorly characterized species such as those of ecological interest.

The maize brown midrib4 (bm4) gene encodes a functional folylpolyglutamate synthase.

Mutations in the brown midrib4 (bm4) gene affect the accumulation and composition of lignin in maize. Fine-mapping analysis of bm4 narrowed the candidate region to an approximately 105 kb interval on chromosome 9 containing six genes. Only one of these six genes, GRMZM2G393334, showed decreased expression in mutants. At least four of 10 Mu-induced bm4 mutant alleles contain a Mu insertion in the GRMZM2G393334 gene. Based on these results, we concluded that GRMZM2G393334 is the bm4 gene. GRMZM2G393334 encodes a putative folylpolyglutamate synthase (FPGS), which functions in one-carbon (C1) metabolism to polyglutamylate substrates of folate-dependent enzymes. Yeast complementation experiments demonstrated that expression of the maize bm4 gene in FPGS-deficient met7 yeast is able to rescue the yeast mutant phenotype, thus demonstrating that bm4 encodes a functional FPGS. Consistent with earlier studies, bm4 mutants exhibit a modest decrease in lignin concentration and an overall increase in the S:G lignin ratio relative to wild-type. Orthologs of bm4 include at least one paralogous gene in maize and various homologs in other grasses and dicots. Discovery of the gene underlying the bm4 maize phenotype illustrates a role for FPGS in lignin biosynthesis.

Nonsyntenic genes drive highly dynamic complementation of gene expression in maize hybrids.

Maize (Zea mays) displays an exceptional level of structural genomic diversity, which is likely unique among higher eukaryotes. In this study, we surveyed how the genetic divergence of two maize inbred lines affects the transcriptomic landscape in four different primary root tissues of their F1-hybrid progeny. An extreme instance of complementation was frequently observed: genes that were expressed in only one parent but in both reciprocal hybrids. This single-parent expression (SPE) pattern was detected for 2341 genes with up to 1287 SPE patterns per tissue. As a consequence, the number of active genes in hybrids exceeded that of their parents in each tissue by >400. SPE patterns are highly dynamic, as illustrated by their excessive degree of tissue specificity (80%). The biological significance of this type of complementation is underpinned by the observation that a disproportionally high number of SPE genes (75 to 82%) is nonsyntenic, as opposed to all expressed genes (36%). These genes likely evolved after the last whole-genome duplication and are therefore younger than the syntenic genes. In summary, SPE genes shape the remarkable gene expression plasticity between root tissues and complementation in maize hybrids, resulting in a tissue-specific increase of active genes in F1-hybrids compared with their inbred parents.

The Aux/IAA gene rum1 involved in seminal and lateral root formation controls vascular patterning in maize (Zea mays L.) primary roots.

The maize (Zea mays L.) Aux/IAA protein RUM1 (ROOTLESS WITH UNDETECTABLE MERISTEMS 1) controls seminal and lateral root initiation. To identify RUM1-dependent gene expression patterns, RNA-Seq of the differentiation zone of primary roots of rum1 mutants and the wild type was performed in four biological replicates. In total, 2 801 high-confidence maize genes displayed differential gene expression with Fc ≥2 and FDR ≤1%. The auxin signalling-related genes rum1, like-auxin1 (lax1), lax2, (nam ataf cuc 1 nac1), the plethora genes plt1 (plethora 1), bbm1 (baby boom 1), and hscf1 (heat shock complementing factor 1) and the auxin response factors arf8 and arf37 were down-regulated in the mutant rum1. All of these genes except nac1 were auxin-inducible. The maize arf8 and arf37 genes are orthologues of Arabidopsis MP/ARF5 (MONOPTEROS/ARF5), which controls the differentiation of vascular cells. Histological analyses of mutant rum1 roots revealed defects in xylem organization and the differentiation of pith cells around the xylem. Moreover, histochemical staining of enlarged pith cells surrounding late metaxylem elements demonstrated that their thickened cell walls displayed excessive lignin deposition. In line with this phenotype, rum1-dependent mis-expression of several lignin biosynthesis genes was observed. In summary, RNA-Seq of RUM1-dependent gene expression in maize primary roots, in combination with histological and histochemical analyses, revealed the specific regulation of auxin signal transduction components by RUM1 and novel functions of RUM1 in vascular development.

Genome-wide discovery and characterization of maize long non-coding RNAs.

BACKGROUND: Long non-coding RNAs (lncRNAs) are transcripts that are 200 bp or longer, do not encode proteins, and potentially play important roles in eukaryotic gene regulation. However, the number, characteristics and expression inheritance pattern of lncRNAs in maize are still largely unknown. RESULTS: By exploiting available public EST databases, maize whole genome sequence annotation and RNA-seq datasets from 30 different experiments, we identified 20,163 putative lncRNAs. Of these lncRNAs, more than 90% are predicted to be the precursors of small RNAs, while 1,704 are considered to be high-confidence lncRNAs. High confidence lncRNAs have an average transcript length of 463 bp and genes encoding them contain fewer exons than annotated genes. By analyzing the expression pattern of these lncRNAs in 13 distinct tissues and 105 maize recombinant inbred lines, we show that more than 50% of the high confidence lncRNAs are expressed in a tissue-specific manner, a result that is supported by epigenetic marks. Intriguingly, the inheritance of lncRNA expression patterns in 105 recombinant inbred lines reveals apparent transgressive segregation, and maize lncRNAs are less affected by cis- than by trans-genetic factors. CONCLUSIONS: We integrate all available transcriptomic datasets to identify a comprehensive set of maize lncRNAs, provide a unique annotation resource of the maize genome and a genome-wide characterization of maize lncRNAs, and explore the genetic control of their expression using expression quantitative trait locus mapping.

The maize brown midrib2 (bm2) gene encodes a methylenetetrahydrofolate reductase that contributes to lignin accumulation.

The midribs of maize brown midrib (bm) mutants exhibit a reddish-brown color associated with reductions in lignin concentration and alterations in lignin composition. Here, we report the mapping, cloning, and functional and biochemical analyses of the bm2 gene. The bm2 gene was mapped to a small region of chromosome 1 that contains a putative methylenetetrahydrofolate reductase (MTHFR) gene, which is down-regulated in bm2 mutant plants. Analyses of multiple Mu-induced bm2-Mu mutant alleles confirmed that this constitutively expressed gene is bm2. Yeast complementation experiments and a previously published biochemical characterization show that the bm2 gene encodes a functional MTHFR. Quantitative RT-PCR analyses demonstrated that the bm2 mutants accumulate substantially reduced levels of bm2 transcript. Alteration of MTHFR function is expected to influence accumulation of the methyl donor S-adenosyl-L-methionine (SAM). Because SAM is consumed by two methyltransferases in the lignin pathway (Ye et al., ), the finding that bm2 encodes a functional MTHFR is consistent with its lignin phenotype. Consistent with this functional assignment of bm2, the expression patterns of genes in a variety of SAM-dependent or -related pathways, including lignin biosynthesis, are altered in the bm2 mutant. Biochemical assays confirmed that bm2 mutants accumulate reduced levels of lignin with altered composition compared to wild-type. Hence, this study demonstrates a role for MTHFR in lignin biosynthesis.

Spreading of heterochromatin is limited to specific families of maize retrotransposons.

Transposable elements (TEs) have the potential to act as controlling elements to influence the expression of genes and are often subject to heterochromatic silencing. The current paradigm suggests that heterochromatic silencing can spread beyond the borders of TEs and influence the chromatin state of neighboring low-copy sequences. This would allow TEs to condition obligatory or facilitated epialleles and act as controlling elements. The maize genome contains numerous families of class I TEs (retrotransposons) that are present in moderate to high copy numbers, and many are found in regions near genes, which provides an opportunity to test whether the spreading of heterochromatin from retrotransposons is prevalent. We have investigated the extent of heterochromatin spreading into DNA flanking each family of retrotransposons by profiling DNA methylation and di-methylation of lysine 9 of histone 3 (H3K9me2) in low-copy regions of the maize genome. The effects of different retrotransposon families on local chromatin are highly variable. Some retrotransposon families exhibit enrichment of heterochromatic marks within 800-1,200 base pairs of insertion sites, while other families exhibit very little evidence for the spreading of heterochromatic marks. The analysis of chromatin state in genotypes that lack specific insertions suggests that the heterochromatin in low-copy DNA flanking retrotransposons often results from the spreading of silencing marks rather than insertion-site preferences. Genes located near TEs that exhibit spreading of heterochromatin tend to be expressed at lower levels than other genes. Our findings suggest that a subset of retrotransposon families may act as controlling elements influencing neighboring sequences, while the majority of retrotransposons have little effect on flanking sequences.