Biology subjects

Buckler, E. S.

Publications and source records attributed to Buckler, E. S..

At least 19 recordsLinked to original sources

bioRxiv2026

An open field phenomics resource for multimodal maize yield prediction across divergent environments

Temporal drone phenotyping captures crop development, but irregular flight schedules complicate comparisons across environments. We release curated imagery from 356 flights across 19 Genomes to Fields environments containing 1,180 maize (Zea mays L.) hybrids. To evaluate its utility, we integrated functional principal components of vegetation index and weather trajectories with genomic information. Combinined genomic and phenomic kernels improved yield prediction, reaching correlations up to r = 0.501 for held-out hybrids in environments represented in training and 0.408 when environments were also withheld. Accumulated growing degree days offered no consistent predictive advantage over days after planting, and weather contributed modest, task-dependent gains. A transformer neural process learned directly from irregular observations, serving as a novel application of neural process models in agriculture. Mapping vegetation index functional principal components identified recurrent quantitative trait loci on chromosomes 3 and 7. This resource and its reproducible analyses guide the use of temporal spectral data for crop prediction and genetic discovery.

plant biology↗

bioRxiv2026

Convergent genome- and gene-level constraints shape repeated environmental adaptation in grasses

Grasses (Poaceae) dominate terrestrial ecosystems and sustain global food security, yet the genomic principles enabling their repeated adaptation to extreme environments remain unresolved. Combining dense phylogenomic sampling, global environmental data, and genomic large language models (gLLMs), we characterize the mutational targets underlying environmental adaptation across 707 genomes from 569 species spanning 17 climate zones. We identify 19-30 phylogenetically independent transitions into extreme temperature, water, and soil environments, accompanied by convergent shifts in genome-scale molecular properties, including the Nitrogen-to-Carbon balance and the biosynthetic cost of the proteome. Our gLLMs-informed phylogenetic mixed modeling framework identifies 330 genes that repeatedly underlie distinct axes of environmental adaptation, highlighting the importance of protein modification and localization within extracellular and organellar compartments. Overlaying independent convergent adaptation tests identifies 17 high-confidence candidates for further characterization. Together, our results show that grass adaptation is canalized by layered constraints at genome-wide and gene-specific scales, producing predictable evolutionary trajectories.

evolutionary biology↗

bioRxiv2026

A transcriptomic atlas of grass senescence reveals divergent underground sink networks limit nitrogen recycling in annuals

Senescence enables plants to remobilize and recycle nutrients from aging organs to support growth, reproduction, and survival. In annual crops like maize, nitrogen remobilization from leaves to grain is incomplete, with 30-50% of nitrogen stranded in aboveground tissues and subject to environmental loss. Mitigating nitrogen loss in annual crops could be achieved by leveraging the physiological strategies of perennial grasses, which remobilize nitrogen and other nutrients into underground organs at the end of the growing season, thereby preventing environmental leakage. To uncover the molecular basis of perennial nitrogen recycling to underground organs, we built a transcriptomic atlas from field-grown plants, comprising 2,685 RNA-seq libraries from 14 grass species within the Panicoideae (Poaceae), utilizing maize and sorghum as annual references for comparative analyses. The atlas spans leaves, roots, stalks, and rhizomes across two seasons, from mid-growing season to senescence. Using a photosynthetic index to align the leafs transition from nitrogen sink to source across species, co-expression network analysis revealed that the subnetworks driving leaf nitrogen recycling are preserved across annuals and perennials. However, we discovered that the subnetworks associated with underground sink establishment, specifically those associated with seed-like dormancy and desiccation tolerance pathways, have diverged among annual crop accessions. Our work identifies conserved gene candidates and networks that could be used to reintroduce perennial-like nutrient recycling into annual crops to enhance long-term nutrient retention in the field.

plant biology↗

bioRxiv2026

Inter-variety competition dynamics in US inbred and hybrid maize

Variety mixtures provide a potential avenue in US cropping systems to improve yield stability and disease resistance. However, implementation of variety mixtures requires an understanding of the competitive dynamics of the crop. In this study, we examine the effects of plant competition both between and within plots through five unique experiments: 1) 5,000 diverse inbred lines in single-row plots, 2) hybrids in two-row plots developed from the above inbred lines, 3) over 4,000 hybrids measured in 141 locations in two-row plots as part of Genomes to Fields, 4) mixtures of two hybrids within a two-row plot planted across two years and five locations, and 5) mixtures of up to twenty hybrids in four-row plots in three locations. Across all experiments, we find that competitive interactions are extremely limited. Within inbred lines, height of the neighboring plot accounts for 1.2% of the variance in focal plot height. Similarly, neighbor height explains 1.7% of the variance in focal plot yield in hybrids developed from the inbred lines. The genetics of neighboring plots explains 1.55% of the variation in yield across 141 location-year environments, reinforcing the generally modest impacts of neighbor competition. In evaluating mixtures of hybrids in both two and four-row plots, we observe no yield penalty compared to conventional single hybrid plots, even with large height differentials of the hybrids included in the mixture or in mixtures of up to 20 hybrids within a plot. Finally, we observe that mixtures have more yield stability compared to conventional plots, highlighting a new avenue for increased stability in higher risk environments. The lack of yield penalty and stability benefits are promising for future investigations of mixtures that may complement each other in disease resistance or abiotic stress tolerance and increase overall yield stability in the field.

plant biology↗

bioRxiv2025

Identification of Freezing Tolerance QTLs in Tripsacum dactyloides Using Open-Pollinated Bulk Segregant Analysis

This study investigates the genetic basis of freezing tolerance in Tripsacum dactyloides and related subspecies as a potential source of valuable traits for improving maize agriculture. Recognizing the significant economic losses in corn yields due to frost damage, we hypothesized that northern populations of T. dactyloides are enriched for freezing tolerance alleles. 40 diverse Tripsacum accessions were collected from natural populations and long-established field collections and used to generate F1 hybrids and open-pollinated F2 families. F2 seedlings were germinated then screened within a growth chamber for freezing tolerance by exposure to freezing temperatures. Seedlings were then phenotyped by tissue survival, and extremes were pooled to create tolerant and susceptible bulks. DNA sequencing was performed on founders, F1s, and tolerant/susceptible F2 bulks. To overcome challenges in traditional SNP calling in bulked samples, we developed a regression-based approach to estimate gamete frequencies and impute allele frequencies in pooled populations. The results showed genetic diversity among Tripsacum accessions, with divergence between northern and southern populations. We tracked segregation of alleles across genomic loci, and performed a joint bulk segregant analysis, identifying 9 QTLs significantly associated with freezing tolerance. These findings highlight potential loci for freezing tolerance that could inform genetic engineering of maize. Central HypothesisNorthern populations of Tripsacum dactyloides, a wild relative of maize, are enriched for freezing tolerance alleles which can be identified by mapping.

genomics↗

bioRxiv2025

The origins and adaptive consequences of polyploidy in a dominant prairie grass

Polyploidy is ubiquitous across North American prairies, which provide essential ecosystem services and rich soil for agriculture. Yet the mechanism driving polyploid abundance is unclear. Multiple hypotheses have been proposed including polyploid abundance is proportional to the opportunity for whole genome duplication (WGD), and WGD alters phenotypes that may increase fitness. We tested these two hypotheses together in the mixed-ploidy species Andropogon gerardi, a dominant grass species in endangered North American tallgrass prairies. Leveraging a novel, phased allopolyploid reference genome, we found the A. gerardi hexaploid arose after the C4 grassland expansion in the early Pleistocene, when glacial cycles likely increased secondary contact between the diploid progenitors. We sequenced A. gerardi from 25 popula-tions and examined cytotype performance and morphology in a controlled environment to investigate the consequences of the contemporary mixed-ploidy populations. We found the 9x A. gerardi cytotype is a neopolyploid and a result of recurrent WGD events. Further, we demonstrate the 9x neopolyploids have greater growth and a decreased stomatal pore index, which is adaptive in xeric climates where the 9x cy-totype is most common. Together, our results support both hypotheses for polyploid abundance in North America: WGD is a product of opportunity and can have immediate fitness consequences. Although the changes to fitness may provide an advantage to 9x A. gerardi, the establishment of 9x may lower overall population fitness due to the lower reproductive viability of 9x individuals. Significance statementPolyploid species are abundant in North American prairies and make up many of the dominant species in the ecosystem. This prominence could be a result of whole genome duplication conferring an advantage that increases the frequency of polyploids or could simply indicate that the opportunity for whole genome duplication is higher in this ecosystem, or both. Through examining three polyploidization events in A. gerardi, the dominant species in endangered tallgrass North American prairies, we found whole genome duplication is both surprisingly common and confers traits that are beneficial in some environments.

plant biology↗

bioRxiv2025

GeneCAD: Plant Genome Annotation with a DNA Foundation Model

Accurate genome annotation is fundamental to biological discovery, yet identifying gene structures directly from DNA sequence remains a major challenge in complex genomes. We introduce GeneCAD, a sequence-only framework that predicts biologically coherent gene models without requiring species-matched transcriptomic or proteomic evidence. GeneCAD integrates lineage-specific DNA representations from the PlantCAD2 foundation model with a transformer encoder and a chromosome-scale conditional random field (CRF) to enforce structural constraints, such as splice-phase and feature order. To ensure high-quality supervision, we implement a curation strategy using a sequence-based masked-motif score to filter reference transcripts. As a primary validation across diverse angiosperms, including a complex allotetraploid, GeneCAD improves transcript F1 by approximately 9% over current tools like Helixer and BRAKER3, while sharpening boundary precision and achieving a best-in-class recovery of 86% of classical coding sequences. Furthermore, we demonstrate the frameworks modularity by adapting it to animal lineages through the substitution of the underlying DNA foundation model. While the long introns of vertebrates challenge full transcript reconstruction, the model remains highly effective at identifying individual exons. By connecting evolutionary signals with structured decoding, GeneCAD provides a versatile and scalable solution for high-fidelity genome annotation across the Tree of Life. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=102 SRC="FIGDIR/small/685877v3_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@5dd348org.highwire.dtl.DTLVardef@1da37daorg.highwire.dtl.DTLVardef@188ef17org.highwire.dtl.DTLVardef@108da0c_HPS_FORMAT_FIGEXP M_FIG C_FIG Lay SummaryIdentifying where genes are located within a genome is a major challenge in biology, especially in plants with large and repetitive DNA. Current methods often rely on expensive laboratory data or struggle to find genes in "noisy" regions. We developed GeneCAD, a deep-learning tool that identifies genes using only the raw DNA sequence. By using AI models that recognize patterns shaped by millions of years of evolution, GeneCAD predicts gene structures with high accuracy and consistency. Our tests show that GeneCAD outperforms existing tools in plants and can be easily adapted for use in other species, including animals. By removing the need for costly lab experiments, GeneCAD provides an affordable way for researchers to quickly map the genomes of everything from rare wild plants to essential food crops.

bioinformatics↗

bioRxiv2025

High-Quality Draft Genome Assemblies and Comparative Genomics of Three Bouteloua Species (Poaceae: Chloridoideae)

Bouteloua is a PACMAD grass genus that dominates much of the central and southern North American prairies and plains, where species such as sideoats grama (B. curtipendula), blue grama (B. gracilis), and black grama (B. eriopoda) are both ecologically dominant and among the most valuable forage grasses of arid rangelands. Yet, genomic resources for the genus remain limited. We generated PacBio HiFi draft assemblies for B. curtipendula (653 Mb, N50 25.5 Mb), B. gracilis (808 Mb, N50 4.1 Mb), and B. eriopoda (1.67 Gb, N50 1.0 Mb). All assemblies showed >98.5% BUSCO completeness. Helixer predicted 83,877-215,536 gene models per assembly. However, syntenic copy numbers (2 in B. curtipendula, 3 in B. gracilis, and 6 in B. eriopoda) indicate that at least two species are polyploid, and the inflated gene model counts likely reflect homeologous copies and fragmented predictions rather than true gene numbers. panEDTA identified 25-40% transposable-element content, dominated by LTR retrotransposons. These assemblies provide foundational genomic references for Bouteloua and support comparative studies across PACMAD grasses.

plant biology↗

bioRxiv2025

PlantCAD2: A Long-Context DNA Language Model for Cross-Species Functional Annotation in Angiosperms

Understanding how DNA sequence encodes biological function remains a fundamental challenge in biology. Flowering plants (angiosperms), the dominant terrestrial clade, exhibit maximal biochemical complexity, extraordinary species diversity (over 100,000 species), relatively recent origins ([~]160 million years), [~]200-fold variation in genome size and relative compact coding regions compared with other eukaryotes. These features present both a unique challenge and opportunity for pre-training DNA language models to understand plant-specific evolutionary conservation, regulatory architectures and genomic functions. Here, we introduce PlantCAD2, an extended context, plant-specific DNA language model with single-nucleotide resolution, pre-trained on 65 angiosperm genomes, together with a series of public benchmarks for evaluation. Comprehensive zero-shot testing shows that PlantCAD2 (676 million parameters) efficiently captures evolutionary conservation, surpassing the 7-billion-parameter Evo2 model in 10 of 12 tasks. With parameter-efficient fine-tuning, PlantCAD2 also outperforms the 1-billion-parameter AgroNT across seven cross-species tasks including chromatin accessible region, gene expression and protein translation. Moreover, its 8,192bp context window substantially improves accessible chromatin prediction in large genomes such as maize (AUPRC increasing from 0.587 to 0.711), underscoring the importance of long-range context for modeling distal regulation. Together, these results establish PlantCAD2 as a powerful, efficient, and versatile foundation model for plant genomics, enabling accurate genome annotation across diverse species.

bioinformatics↗

bioRxiv2025

Grass Rhizome Proteomics Reveals Convergent Freezing-Tolerance Strategies

O_LIGrasses in the PACMAD clade independently colonized cold environments from warm-climate ancestors, but whether their molecular responses to freezing reflect shared evolutionary solutions or lineage-specific innovations remains unknown. We used comparative proteomics to test whether protein-level cold responses show stronger cross-species conservation than previously observed at the transcript level. C_LIO_LIWe quantified seasonal rhizome proteomes (winter vs summer) from five PACMAD species grown in a common garden exposed to sustained sub-zero temperatures, identified differentially abundant proteins, and compared fold-change magnitudes across species using orthogroup-based correlation analyses. We further examined LEA3 protein structure through hydropathy profiling and motif analysis. C_LIO_LIShared cold-responsive proteins showed higher cross-species fold-change correlation ({rho} = 0.80) than background proteins ({rho} = 0.45), despite greater divergence in baseline abundance. LEA3 was the only ortholog elevated across all five species. Cold-tolerant species contained more tandem 11-mer repeats than the cold-sensitive maize, and two species accumulated multiple LEA3 paralogs, increasing total LEA3 abundance. C_LIO_LIIndependent evolution of freezing tolerance in PACMAD grasses is governed by evolutionary constraints on protein-level response magnitude, reflecting the retention of an ancestral protective capacity. Structural divergence of LEA3 in maize suggests that transcriptional induction alone does not ensure freezing tolerance; functional protection likely requires intact motif architecture. C_LI

evolutionary biology↗

bioRxiv2025

Phylogenetic Analysis and Machine Learning Identify Signatures of Selection and Predict Deleterious Mutations in Common Bean

Mutations are continuous source of new alleles and genetic diversity in populations. Domestication and selection influence the accumulation of alleles occurring across a range of deleteriousness. Evidence suggests that mildly deleterious mutations (DelMut) can be purged out of breeding populations, increasing favorable allele accumulation. We used phylogeny-based analyses among 36 legume genomes to identify selection signatures and predict DelMut in common bean. We also developed a multiparent advanced generation intercrossed (MAGIC) population of black beans to characterize DelMut. Genes involved in nitrogen metabolism showed signs of positive selection in the Middle American genome, whereas genes related to phosphorylation were positively selected in the Andean genome. By combining conservation and protein information with machine learning (ML) for high-dimensional feature analysis, we characterized 82,442 sites in the MAGIC founders (36,558 polymorphic) and 4,753 sites evenly sequenced among RILs that could be potentially deleterious. Variation in the number of highly DelMut (high predicted deleterious scores) among lines was observed and later correlated with agronomic traits. Phenotypic analyses showed that calculated genetic load (and number of highly DelMut) was negatively correlated with flowering time, maturity, and yield. A detailed in-silico analysis of predicted mutations showed presence in highly conserved protein regions, which is likely to affect protein functionality. Our results show that variation in genetic load can be observed in breeding populations and potentially impact plant performance. These results contribute to understanding the genome-wide accumulation patterns of DelMut in breeding populations. Our study supports future development of strategies to reduce genetic load in promising germplasm and accelerate breeding programs. Key messages- Genome-wide highly deleterious mutations were predicted in conserved protein domains potentially affecting protein functionality. - Variation in the genetic load and number of highly deleterious mutations can be observed in artificial breeding populations. - Nitrogen- and phosphorous-related genes are under positive selection in Middle American and Andean beans respectively.

plant biology↗

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↗

bioRxiv2025

Higher order repeat structures reflect diverging evolutionary paths in maize centromeres and knobs

BackgroundHighly repetitive tandem repeat arrays, known as satellite DNAs, are enriched in low-recombination regions such as centromeres. Satellite arrays often contain complex internal structures called higher-order repeats (HORs), which may have functional significance. Maize is unusual in that its satellites occur in two distinct genomic contexts: centromeres, which interact with kinetochore proteins, and knobs, which undergo meiotic drive in the presence of Abnormal chromosome 10. Whether maize centromeres or knobs contain HOR patterns, and how such patterns relate to function, remains unclear. ResultsHere, we generate 13 repeat-sensitive genome assemblies of maize and its recent ancestor, teosinte. We develop a new graph-based pipeline, HiReNET, to classify HORs and demonstrate its utility in both Arabidopsis and maize. We find that HORs are ubiquitous in maize satellites but are typically low-frequency with small patterns, unlike the large, continuous HOR blocks characteristic of human centromeres. Approximately 38% of centromeric CentC monomers occur in HORs; however, no specific HOR class dominates any functional centromere as marked by centromeric histone H3. Arabidopsis centromeres have a similar HOR landscape. In contrast, maize knobs exhibit a more structured HOR distribution. Large knobs contain megabase-scale similarity blocks with repeated HOR patterns. These repeat units likely promote unequal crossing over, enabling rapid knob expansion, and may harbor motifs recognized by trans-acting factors involved in meiotic drive. ConclusionsHORs occur in all major maize satellite arrays. Specific HORs are not associated with centromere function, but knobs contain conserved HOR patterns within similarity blocks that may facilitate meiotic drive.

genomics↗

bioRxiv2025

Extensive genome evolution distinguishes maize within a stable tribe of grasses

Over the last 20 million years, the Andropogoneae tribe of grasses has evolved to dominate 17% of global land area. Domestication of these grasses in the last 10,000 years has yielded our most productive crops, including maize, sugarcane, and sorghum. The majority of Andropogoneae species, including maize, show a history of polyploidy - a condition that, while offering the evolutionary advantage of multiple gene copies, poses challenges to basic cellular processes, gene expression, and epigenetic regulation. Genomic studies of polyploidy have been limited by sparse sampling of taxa in groups with multiple polyploidy events. Here, we present 33 genome assemblies from 27 species, including chromosome-scale assemblies of maize relatives Zea and Tripsacum. In maize, the after-effects of polyploidy have been widely studied, showing reduced chromosome number, biased fractionation of duplicate genes, and transposable element (TE) expansions. While we observe these patterns within the genus Zea, 12 other polyploidy events deviate significantly. Those tetraploids and hexaploids retain elevated chromosome number, maintain nearly complete complements of duplicate genes, and have only stochastic TE amplifications. These genomes reveal variable outcomes of polyploidy, challenging simple predictions and providing a foundation for understanding its evolutionary implications in an ecologically and economically important clade.

evolutionary biology↗

bioRxiv2024

Maize inbreds show allelic variation for diel transcription patterns

Circadian entrainment and external cues can cause gene transcript abundance to oscillate throughout the day, and these patterns of diel transcript oscillation vary across genes and plant species. Less is known about within-species allelic variation for diel patterns of transcript oscillation, or about how regulatory sequence variation influences diel transcription patterns. In this study, we evaluated diel transcript abundance for 24 diverse maize inbred lines. We observed extensive natural variation in diel transcription patterns, with two-fold variation in the number of genes that oscillate over the course of the day. A convolutional neural network trained to predict oscillation from promoter sequence identified sequences previously reported as binding motifs for known circadian clock genes in other plant systems. Genes showing diel transcription patterns that cosegregate with promoter sequence haplotypes are enriched for associations with photoperiod sensitivity and may have been indirect targets of selection as maize was adapted to longer day lengths at higher latitudes. These findings support the idea that cis-regulatory sequence variation influences patterns of gene expression, which in turn can have effects on phenotypic plasticity and local adaptation.

plant biology↗

bioRxiv2024

The maize recombination landscape evolved during domestication.

Meiotic recombination is an important evolutionary process because it can increase the amount of genetic variation within populations through the breakage of unfavorable linkages and creation of novel allelic combinations. Despite the plethora of knowledge about population-level benefits of recombination and numerous theoretical studies examining how recombination rates can evolve over time, there is a lack of empirical evidence for any hypotheses that have been put forward. To alleviate this gap in knowledge, we characterized the evolution of the recombination landscape in Zea mays ssp. mays (maize) during its domestication from Zea mays ssp. parviglumis (teosinte), explored hypotheses that permitted the evolution of the maize recombination landscape and tied these alterations to changes in the genetic basis of recombination. Using experimental populations and the population genomics approach of ancestral recombination graph (ARG) inference, our data demonstrated that maize had a 12% increase in its genome-wide recombination rate during domestication. Although the maize and teosinte recombination landscapes are highly correlated, r = 0.85 at 1Mb resolution, maize has evolved to have higher recombining regions in interstitial chromosome regions, compared to teosinte which only harbors high recombining regions sub-telomerically. Our data show that the re-patterning of COs towards interstitial chromosome regions came from reduced CO interference levels within maize. Supporting the idea that CO interference is reduced within maize, we found evidence for selection acting on trans-acting recombination-modifiers that participate in the class I CO pathway or CO interference directly. Lastly, we showed that the re-patterning of COs was beneficial to maize evolution because regions that significantly increased in recombination were targeted to gene-rich regions harboring domestication related loci. Because we found regions with significant increases in recombination had a lower deleterious mutation load, compared to regions with decreases in recombination, we concluded that the domestication-related variation in these regions, in which selection acted upon during domestication, was shielded from the Hill-Robertson effect. In conclusion, the re-patterning of CO events during domestication allowed maize to adapt and evolve at a faster rate than previously understood.

evolutionary biology↗

bioRxiv2024

The utility of environmental data from traditionalvarieties for climate-adaptive maize breeding

Maintaining crop yields in the face of climate change is a major challenge facing plant breeding today. Considerable genetic variation exists in ex-situ collections of traditional crop varieties, but identifying adaptive loci and testing their agronomic performance in large populations in field trials is costly. Here, we study the utility of climate and genomic data for identifying promising traditional varieties to incorporate into maize breeding programs. To do so, we use phenotypic data from more than 4,000 traditional maize varieties grown in 13 trial environments. First, we used genotype data to predict environmental characteristics of germplasm collections to identify varieties that may be locally adapted to target environments. Second, we used environmental GWAS (envGWAS) to identify genetic loci associated with historical divergence along climatic gradients, such as the putative heat shock protein hsftf9 and the large-scale adaptive inversion Inv4m. Finally, we compared the value of environmental data and envGWAS-prioritized loci to genomic data for prioritizing traditional varieties. We find that maize yield traits are best predicted by genomic data, and that envGWAS-identified variants provide little direct predictive information over patterns of population structure. We also find that adding environment-of-origin variables does not improve yield component prediction over kinship or population structure alone, but could be a useful selection proxy in the absence of sequencing data. While our results suggest little utility of environmental data for selecting traditional varieties to incorporate in breeding programs, environmental GWAS is nonetheless a potentially powerful approach to identify individual novel loci for maize improvement, especially when coupled with high density genotyping.

evolutionary biology↗

bioRxiv2024

Cross-species plant genomes modeling at single nucleotide resolution using a pre-trained DNA language model

Interpreting function and fitness effects in diverse plant genomes requires transferable models. Language models (LMs) pre-trained on large-scale biological sequences can learn evolutionary conservation and offer cross-species prediction better than supervised models through fine-tuning limited labeled data. We introduce PlantCaduceus, a plant DNA LM based on the Caduceus and Mamba architectures, pre-trained on a curated dataset of 16 Angiosperm genomes. Fine-tuning PlantCaduceus on limited labeled Arabidopsis data for four tasks, including predicting translation initiation/termination sites and splice donor and acceptor sites, demonstrated high transferability to 160 million year diverged maize, outperforming the best existing DNA LM by 1.45 to 7.23-fold. PlantCaduceus is competitive to state-of-the-art protein LMs in terms of deleterious mutation identification, and is threefold better than PhyloP. Additionally, PlantCaduceus successfully identifies well-known causal variants in both Arabidopsis and maize. Overall, PlantCaduceus is a versatile DNA LM that can accelerate plant genomics and crop breeding applications.

bioinformatics↗