Biology subjects

Marand, A. P.

Publications and source records attributed to Marand, A. P..

At least 19 recordsLinked to original sources

bioRxiv2026

Empirical Estimation of Ambient Contamination in Combinatorial Single-Cell Methods Using Multi-Reference Mapping

Droplet-based microfluidics and combinatorial indexing (scifi-ATAC and scifi-RNA) have made single-cell experiments massively scalable. However, higher-order multiplexing complicates data quality, introduces noise, and affects the potential for biological discovery. Here, we show that ambient chromatin accumulates through the experimental workflow and distorts chromatin profiles, most drastically in low-depth nuclei and in minority populations. Standard cell calling relies heavily on read count thresholds, while existing decontamination methods generally operate on aggregated count matrices rather than the underlying reads. We introduce scifi-demux, for preprocessing scifi-ATAC libraries, and AmbientMapper, a generative model that maps reads competitively against multiple references, learns the ambient profile from empty and low-complexity barcodes, and separates nuclei from background and singlets from doublets by Bayesian Information Criterion. Using interspecies ground truth experiments, published multi-genotype libraries, and simulated read-level synthetic barcodes in which every contaminating read is traceable, we show that calls are robust to parameter variation and stable across designs, achieving a wrong-genome rate of 0.19% on a 26-genome reference panel. Finally, we evaluated the impact of removing contaminants, showcasing how AmbientMapper rescues low-depth nuclei discarded by standard pipelines and restores biological structure obscured by contamination.

bioinformatics↗

bioRxiv2026

Cell-type-specific regulatory variation shapes maize heterosis

Heterosis, the superior performance of hybrids over their parents, has been widely exploited to enhance crop productivity, but its underlying regulatory mechanisms remain incompletely understood. In particular, how cis-regulatory elements (CREs) vary between parents and hybrids, and how this variation is organized across cell types, remains largely unresolved. Here we profiled chromatin accessibility in 131,890 nuclei derived from seedlings of three Zea mays (maize) inbred lines and their reciprocal hybrids, resolving 14 major cell types. Parental haplotype comparisons showed that most accessible chromatin regions (ACRs) were sequence-conserved and have similar binarized chromatin accessibility status. At cellular resolution, hybridization broadly attenuated chromatin accessibility cell-type specificity, weakening parental cell-type bias and yielding a more even chromatin accessibility profile across cellular contexts. Chromatin inheritance was strongly cell-type dependent, with non-additive inheritance preferentially concentrated at cell-type-specific ACRs. Although cis effects were most prevalent overall, ACRs with attenuated cell-type specificity in hybrids were enriched for non-additive inheritance and trans effects. Attenuated ACRs were more prone to transcription factor (TF) footprint gains than loci retaining high cell-type specificity, with DNA-BINDING WITH ONE FINGER (DOF) and VASCULAR PLANT ONE ZINC FINGER (VOZ) among the motif families most enriched in high-confidence footprint-gaining events. ACRs with footprint gains were preferentially linked to genes involved in development, hormone responses and growth, including DOF-family gains at GOLDEN2-like (GLK2), where both the motif family and the locus have been implicated in bundle-sheath development and C4 photosynthetic specialization. Together, our findings reveal that parental chromatin accessibility patterns are reconfigured across cell types in maize hybrids, with attenuation of cell-type specificity offering a potential cellular mechanism underlying heterosis.

plant biology↗

bioRxiv2026

Sequence-based modeling of plant epigenomes reveals cell-type-specific cis-regulatory grammar

How cis-regulatory sequences and their genetic variation govern chromatin accessibility and gene expression to establish plant cell identities remains incompletely understood, despite their fundamental roles in development, environmental responses, and phenotypic diversity. Here we present PEAgent, a framework for training, evaluating and interpreting deep-learning models that predict single-cell chromatin accessibility directly from DNA sequence, packaged in an interactive web portal and toolkit. Models were trained on single-cell chromatin-accessibility atlases of soybean, maize and rice, together spanning over 355,000 cells and 320 cell types and [~]150 million years of evolution. We unraveled a lexicon of 243 cell-type-resolved regulatory patterns, half of them composite, with TCP and bHLH showing the greatest influence and strongest conservation across species. Co-occurrence and in silico synergy analyses, explicitly modeling motif orientation and spacing, revealed two distinct cooperative modes acting at short and nucleosome-scale distances. We further showed that model predictions distinguish grass-conserved from rice-specific regulatory sequences far more accurately than sequence conservation scores alone, and validated the models predicted variant effects against cell-type-level chromatin accessible QTLs. PEAgent provides a foundational resource for decoding cell-type-specific plant cis-regulatory logic and interpreting noncoding variation in plants. HighlightsO_LIPEAgent predicts single-cell chromatin accessibility directly from DNA sequence in soybean, rice and maize. C_LIO_LINearly half of cell-type-resolved patterns are composite, with TCP and bHLH motifs most influential and conserved across species. C_LIO_LICo-occurrence and synergy analysis reveals distinct cooperative grammar at short and nucleosome-scale distances. C_LIO_LIPEAgent distinguishes grass-conserved from lineage-specific regulatory sequences better than sequence conservation scores alone. C_LI

genetics↗

bioRxiv2026

Cell-specific dedifferentiation in Arabidopsis thaliana

Single somatic plant cells are capable of dedifferentiation and reversion to totipotency. However, understanding of dedifferentiation remains incomplete, limiting efforts to reprogram plant cell identities with engineered properties. Here, we describe the transcriptional dynamics of 125,091 Arabidopsis thaliana whole seedling protoplasts along a time course of dedifferentiation and varied chemical perturbations using single-cell RNA sequencing. We observed widespread cell-type-specific transcriptional reprogramming concomitant with cell wall digestion, including a guard cell-specific somatic embryogenic-like program initiated by ectopic LEC2 expression. Contrasting cell states between chemical perturbations across real time revealed that phytohormones antagonize cell aging, promote retention of transcriptional diversity, and selectively suppress wound responses. By dissecting time-resolved transcriptional dynamics, we discovered that dedifferentiation is accompanied by the activation of stem-cell and meristematic marker genes and associated with prevalent chromatin remodeling. Despite discovery of a shared regulatory program underlying early dedifferentiation, temporal modeling of diverse somatic cell types uncovered extensive bias in dedifferentiation potential, including epithem-derived dedifferentiated cells, variable dedifferentiation rates, and diversity in early reprogramming outcomes as a major source of in vitro heterogeneity. Taken together, these data showcase how initial somatic cell identity, phytohormone signaling, chromatin remodeling, and reprogramming heterogeneity combine to coordinate the early transcriptional events defining cellular dedifferentiation.

plant biology↗

bioRxiv2025

Hybrids reveal accessible chromatin trans genetic associations

Crosses between genetically distant Zea mays (Maize) inbreds cause hybrid vigour (heterosis): an over-dominant increase in vegetative growth and grain yield. Although the contributing loci are unknown, heterosis strength varies polygenically, with crosses between stiff stalk and non-stiff stalk lineages often producing the highly heterotic F1 seed used for agriculture. As F1 genomes conserve the parental cis-regulatory state, F1 trans-interactions between haplotypes underpin F1 trait over-dominance and heterotic gene expression. Gene expression relies upon transcription factors binding cis-regulatory elements in accessible chromatin regions (ACRs) and recruiting RNA POLYMERASE II. Here, assay for transposase accessible chromatin sequencing (ATAC-seq) examined cis-regulatory element chromatin accessibility inheritance in three different F1 parent-offspring pairs, including a representative stiff stalk-by-non-stiff stalk (B73xOh43) cross. Using concatenated reference alignment, we categorized ACR modes of inheritance (additive, dominant, under/over-dominant), revealing that ACRs are largely inherited additively, and, concordantly, that chromatin accessibility has strong narrow-sense heritability. However, mirroring other heterotic phenotypes, the B73xOh43 cross exhibited the most dominant and over-dominant inheritance. Comparing allele-specific parent-to-offspring chromatin accessibility, we identified F1 differentially trans-regulated ACRs. Using a matched chromatin accessible diversity panel, we found B73xOh43 SNPs with more ACR trans-associations than expected due to chance. These trans-regulatory variants revealed how cell-division and anabolism are elevated in heterotic F1 seedlings. This multiple discovery filtering (MDF) approach to trans-regulatory variant detection is genomic modality agnostic and stands to empower trans-relationship dissection in diverse genetic models.

genetics↗

bioRxiv2025

Polymer-derived distance penalties improve chromatin interaction predictions from single-cell data across crop genomes

Scalable proxies for 3D genome contacts - such as single-cell co-accessibility and deep learning predictions - have emerged as powerful alternatives to chromatin capture-based methods, but predictions systematically overestimate long-range interactions. Here we show how to correct this bias using distance-based penalty functions informed by Gaussian mixture modeling and polymer-physics scaling. Using Hi-C datasets from maize, rice, and soybean, we derive tissue-specific and global consensus penalties parameterized by multi-regime power-law exponents. Applying these corrections to scATAC-seq co-accessibility scores improves their distance profiles in concordance with Hi-C and reduces long-range false positives by an average of 73% with tissue-specific penalties and 66% with the global consensus. We provide open-source code and fitted parameters to support adoption in maize, rice, and soybean.

bioinformatics↗

bioRxiv2025

Extensive modulation of a conserved cis-regulatory code across 589 grass species

The growing availability of genomes from non-model organisms offers new opportunities to identify functional loci underlying trait variation through comparative genomics. While cis-regulatory regions drive much of phenotypic evolution, linking them to specific functions remains challenging. We identified 514 cis-regulatory motifs enriched in regulatory regions of five diverse grass species, with 73% consistently enriched across all, suggesting a deeply conserved regulatory code. We then quantified conservation of specific motif instances across 589 grass species, revealing widespread gain and loss over evolutionary time. Conservation declined rapidly over the first few million years of divergence, yet [~]50% of motif instances were conserved back to the origin of grasses [~]100 million years ago. Conservation patterns varied by gene class, with modestly higher conservation at transcription factor genes. To test for adaptive cis-regulatory changes, we used phylogenetic mixed models to identify motif gains and losses associated with ecological niche transitions. Our models revealed polygenic adaptation across 810 motif-orthogroup combinations, including convergent gains of HSF/GARP motifs at an Alpha-N-acetylglucosaminidase gene associated with adaptation to temperate environments. Our results support a "stable code, variable sites" model in which cis-regulatory evolution involves extensive turnover of individual binding site instances while largely preserving transcription factors binding preferences. Cis-regulatory changes at hundreds to thousands of genes appear to contribute to environmental adaptation. Our results highlight the potential of comparative genomics and phylogenetic mixed models to reveal the genetic basis of complex traits.

genomics↗

bioRxiv2024

The genetic architecture of cell-type-specific cis-regulation

AbstractGene expression and complex phenotypes are determined by the activity of cis-regulatory elements. However, an understanding of how extant genetic variants affect cis regulation remains limited. Here, we investigated the consequences of cis-regulatory diversity using single-cell genomics of >0.7 million nuclei across 172 Zea mays (maize) inbreds. Our analyses pinpointed cis-regulatory elements distinct to domesticated maize and revealed how historical transposon activity has shaped the cis-regulatory landscape. Leveraging population genetics principles, we fine-mapped [~]22,000 chromatin accessibility-associated genetic variants with widespread cell-type-specific effects. Variants in TEOSINTE BRANCHED1/CYCLOIDEA/PROLIFERATING CELL FACTOR binding sites were the most prevalent determinants of chromatin accessibility. Finally, integrating chromatin accessibility-associated variants, organismal trait variation, and population differentiation revealed how local adaptation has rewired regulatory networks in unique cellular context to alter maize flowering.

genetics↗

bioRxiv2024

A spatially resolved multiomic single-cell atlas of soybean development

Cis-regulatory elements (CREs) precisely control spatiotemporal gene expression in cells. Using a spatially resolved single-cell atlas of gene expression with chromatin accessibility across ten soybean tissues, we identified 103 distinct cell types and 303,199 accessible chromatin regions (ACRs). Nearly 40% of the ACRs showed cell-type-specific patterns and were enriched for transcription factor (TF) motifs defining diverse cell identities. We identified de novo enriched TF motifs and explored conservation of gene regulatory networks underpinning legume symbiotic nitrogen fixation. With comprehensive developmental trajectories for endosperm and embryo, we uncovered the functional transition of the three sub-cell types of endosperm, identified 13 sucrose transporters sharing the DOF11 motif that were co-up-regulated in late peripheral endosperm and identified key embryo cell-type specification regulators during embryogenesis, including a homeobox TF that promotes cotyledon parenchyma identity. This resource provides a valuable foundation for analyzing gene regulatory programs in soybean cell types across tissues and life stages.

plant biology↗

bioRxiv2024

GenomicLinks: Deep learning predictions of 3Dchromatin loops in the maize genome

Gene regulation in eukaryotes is partly shaped by the 3D organization of chro]matin within the cell nucleus. Distal interactions between cis-regulatory elements and their target genes are widespread and many causal loci underlying heritable agricultural traits have been mapped to distal non-coding elements. The biology underlying chromatin loop formation in plants is poorly understood. Dissecting the sequence features that mediate distal interactions is an important step toward identifying putative molecular mechanisms. Here, we trained GenomicLinks, a deep learning model, to identify DNA sequence features predictive of 3D chromatin interactions in maize. We found that the presence of binding motifs of specific Transcription Factor classes, especially bHLH, are predictive of chromatin interaction specificities. Using an in silico mutagenesis approach we show the removal of these motifs from loop anchors leads to reduced interaction probabilities. We were able to validate these predictions with single-cell co-accessibility data from different maize genotypes that harbor natural substitutions in these TF binding motifs. GenomicLinks is currently implemented as an open-source web tool, which should facilitate its wider use in the plant research community.

genomics↗

bioRxiv2024

Evolution of cell-type-specific accessible chromatin regions and the cis-regulatory elements that drive lineage-specific innovation

Cis-regulatory elements (CREs) are critical in regulating gene expression, and yet understanding of CRE evolution remains challenging. Here, we constructed a comprehensive single-cell atlas of chromatin accessibility in Oryza sativa, integrating data from 103,911 nuclei representing 126 discrete cell states across nine distinct organs. We used comparative genomics to compare cell-type resolved chromatin accessibility between O. sativa and 57,552 nuclei from four additional grass species (Zea mays, Sorghum bicolor, Panicum miliaceum, and Urochloa fusca). Accessible chromatin regions (ACRs) had different levels of conservation depending on the degree of cell-type specificity. We found a complex relationship between ACRs with conserved noncoding sequences, cell-type specificity, conservation, and tissue-specific switching. Additionally, we found that epidermal ACRs were less conserved compared to other cell types, potentially indicating that more rapid regulatory evolution has occurred in the L1-derived epidermal layer of these species. Finally, we identified and characterized a conserved subset of ACRs that overlapped the repressive histone modification H3K27me3, implicating them as potentially silencer-like CREs maintained by evolution. Collectively, this comparative genomics approach highlights the dynamics of plant cell-type-specific CRE evolution.

plant biology↗

bioRxiv2023

Massive-scale single-cell chromatin accessibility sequencing using combinatorial fluidic indexing

Single-cell ATAC-seq has emerged as a powerful approach for revealing candidate cis-regulatory elements genome-wide at cell-type resolution. However, current single-cell methods suffer from limited throughput and high costs. Here, we present a novel technique called single-cell combinatorial fluidic indexing ATAC-sequencing ("scifi-ATAC-seq"), which combines a barcoded Tn5 pre-indexing step with droplet-based single-cell ATAC-seq using a widely commercialized microfluidics platform (10X Genomics). With scifi-ATAC-seq, up to 200,000 nuclei across multiple samples in a single emulsion reaction can be indexed, representing a [~]20-fold increase in throughput compared to the standard 10X Genomics workflow.

genomics↗

bioRxiv2023

Computational Analysis of Maize Enhancer Regulatory Elements Using ATAC-STARR-seq

The blueprints to development, response to the environment, and cellular function are largely the manifestation of distinct gene expression programs controlled by the spatiotemporal activity of cis-regulatory elements. Although biochemical methods for identifying accessible chromatin - a hallmark of active cis-regulatory elements - have been developed, approaches capable of measuring and quantifying cis-regulatory activity are only beginning to be realized. Massively Parallel Reporter Assays coupled to chromatin accessibility profiling present a high-throughput solution for testing the transcription-activating capacity of millions of putatively regulatory DNA sequences in parallel. However, clear computational pipelines for analyzing these high-throughput sequencing-based reporter assays are lacking. In this protocol, I layout and rationalize a computational framework for the processing and analysis of Assay for Transposase Accessible Chromatin profiling followed by Self-Transcribed Active Regulatory Region sequencing (ATAC-STARR-seq) data from a recent study in Zea mays. The approach described herein can be adapted to other sequencing-based reporter assays and is largely agnostic to the model organism with the appropriate input substitutions.

genomics↗

bioRxiv2022

Machine learning reveals conserved chromatin patterns determining meiotic recombination sites in plants

Distribution of meiotic recombination events in plants has been associated with local chromatin and DNA characteristics, chromosome landmark proximity, and other features1-7. However, relative importance of these characteristics is unclear and it is unknown if they are sufficient to unambiguously determine recombination landscape8. Here, we analyzed over 40 DNA sequence, chromatin, and chromosome location features of maize and Arabidopsis recombination sites using machine learning9,10. We discovered that a combination of just three features, CG methylation, CHG methylation, and nucleosome occupancy, enabled identification of exact crossover site with 90% accuracy. These results imply redundancy of most recombination site characteristics. Recombination takes place in a small fraction of the genome with chromatin features distinct from those of genome at large. Surprisingly, crossover sites show elevated heterochromatin histone marks despite low DNA methylation. Crossover site features show broad evolutionary conservation, which will enable creating genetic maps in species where conventional mapping is unfeasible.

plant biology↗

bioRxiv2021

Modeling chromatin state from sequence across angiosperms using recurrent convolutional neural networks

Accessible chromatin regions are critical components of gene regulation but modeling them directly from sequence remains challenging, especially within plants, whose mechanisms of chromatin remodeling are less understood than in animals. We trained an existing deep learning architecture, DanQ, on leaf ATAC-seq data from 12 angiosperm species to predict the chromatin accessibility of sequence windows within and across species. We also trained DanQ on DNA methylation data from 10 angiosperms, because unmethylated regions have been shown to overlap significantly with accessible chromatin regions in some plants. The across-species models have comparable or even superior performance to a model trained within species, suggesting strong conservation of chromatin mechanisms across angiosperms. Testing a maize held out model on a multi-tissue scATAC panel revealed our models are best at predicting constitutively-accessible chromatin regions, with diminishing performance as cell-type specificity increases. Using a combination of interpretation methods, we ranked JASPAR motifs by their importance to each model and saw that the TCP and AP2/ ERF transcription factor families consistently ranked highly. We embedded the top three JASPAR motifs for each model at all possible positions on both strands in our sequence window and observed position- and strand-specific patterns in their importance to the model. With our cross-species "a2z" model it is now feasible to predict the chromatin accessibility and methylation landscape of any angiosperm genome.

bioinformatics↗

bioRxiv2021

A combinatorial indexing strategy for epigenomic profiling of plant single cells

Understanding how cis-regulatory elements facilitate gene expression is a key question in biology. Recent advances in single-cell genomics have led to the discovery of cell-specific chromatin landscapes that underlie transcription programs. However, the high equipment and reagent costs of commercial systems limit their applications for many laboratories. In this study, we profiled the Arabidopsis root single-cell epigenome using a combinatorial index and dual PCR barcode strategy without the need of any specialized equipment. We generated chromatin accessibility profiles for 13,576 Arabidopsis thaliana root nuclei with an average of 12,784 unique Tn5 integrations per cell and 85% of the Tn5 insertions localizing to discrete accessible chromatin regions. Comparison with data generated from a commercial microfluidic platform revealed that our method is capable of unbiased identification of cell type-specific chromatin accessibility with improved throughput, quality, and efficiency. We anticipate that by removing cost, instrument, and other technical obstacles, this combinatorial indexing method will be a valuable tool for routine investigation of single-cell epigenomes and usher new insight into plant growth, development and their interactions with the environment.

genomics↗

bioRxiv2021

Stability of DNA methylation and chromatin accessibility in structurally diverse maize genomes

Accessible chromatin and unmethylated DNA are associated with many genes and cis-regulatory elements. Attempts to understand natural variation for accessible chromatin regions (ACRs) and unmethylated regions (UMRs) often rely upon alignments to a single reference genome. This limits the ability to assess regions that are absent in the reference genome assembly and monitor how nearby structural variants influence variation in chromatin state. In this study, de novo genome assemblies for four maize inbreds (B73, Mo17, Oh43 and W22) are utilized to assess chromatin accessibility and DNA methylation patterns in a pan-genome context. The number of UMRs and ACRs that can be identified is more accurate when chromatin data is aligned to the matched genome rather than a single reference genome. While there are UMRs and ACRs present within genomic regions that are not shared between genotypes, these features are substantially enriched within shared regions, as determined by chromosomal alignments. Characterization of UMRs present within shared genomic regions reveals that most UMRs maintain the unmethylated state in other genotypes with only a small number being polymorphic between genotypes. However, the majority of UMRs between genotypes only exhibit partial overlaps suggesting that the boundaries between methylated and unmethylated DNA are dynamic. This instability is not solely due to sequence variation as these partially overlapping UMRs are frequently found within genomic regions that lack sequence variation. The ability to compare chromatin properties among individuals with structural variation enables pan-epigenome analyses to study the sources of variation for accessible chromatin and unmethylated DNA. Article summaryRegions of the genome that have accessible chromatin or unmethylated DNA are often associated with cis-regulatory elements. We assessed chromatin accessibility and DNA methylation in four structurally diverse maize genomes. There are accessible or unmethylated regions within the non-shared portions of the genomes but these features are depleted within these regions. Evaluating the dynamics of methylation and accessibility between genotypes reveals conservation of features, albeit with variable boundaries suggesting some instability of the precise edges of unmethylated regions.

plant biology↗

bioRxiv2021

De novo assembly, annotation, and comparative analysis of 26 diverse maize genomes

We report de novo genome assemblies, transcriptomes, annotations, and methylomes for the 26 inbreds that serve as the founders for the maize nested association mapping population. The data indicate that the number of pan-genes exceeds 103,000 and that the ancient tetraploid character of maize continues to degrade by fractionation to the present day. Excellent contiguity over repeat arrays and complete annotation of centromeres further reveal the locations and internal structures of major cytological landmarks. We show that combining structural variation with SNPs can improve the power of quantitative mapping studies. Finally, we document variation at the level of DNA methylation, and demonstrate that unmethylated regions are enriched for cis-regulatory elements that overlap QTL and contribute to changes in gene expression. One sentence summaryA multi-genome analysis of maize reveals previously unknown variation in gene content, genome structure, and methylation.

genomics↗