Chromosome-Scale Assembly of Wheat Cultivar Sumai 3, a Major Germplasm Source for Fusarium Head Blight Resistance

Chromosome-Scale Assembly of Wheat Cultivar Sumai 3, a Major Germplasm Source for Fusarium Head Blight Resistance | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 9 February 2026 V1 Latest version Share on Chromosome-Scale Assembly of Wheat Cultivar Sumai 3, a Major Germplasm Source for Fusarium Head Blight Resistance Authors : Rubylyn Mijan 0009-0004-5450-2695 , Bikash Poudel , Sittal Thapa , Oluwatayo Ajayi-Moses 0000-0002-7215-1209 , Thomas Lux , Raz Avni , Steven Xu 0000-0001-7000-2034 , Manuel Spannagl , Martin Mascher 0000-0001-6373-6013 , Peter Maughan 0000-0003-3714-3411 , and Jason Fiedler 0000-0001-7736-4484 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.177067351.16721183/v1 408 views 131 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Fusarium head blight (FHB) is a devastating disease that severely impacts global wheat production. Sumai 3, a wheat cultivar widely used in breeding programs for its strong FHB resistance, has not been fully resolved at the chromosome level. Here, we present a high-quality chromosome-scale assembly of Sumai 3 using PacBio HiFi reads, and chromosome conformation capture sequencing. The 14.6 Gb assembly consists of 832 contigs, with the longest contig being 245.2 Mb and a contig N50 of 41.90 Mb, which were scaffolded into 21 pseudomolecules. De novo annotation identified 104,620 high-confidence protein-coding genes and found 92.67% of the genome to consist of repetitive sequences. Synteny analysis showed strong collinearity between Sumai 3 and the wheat reference sequence Chinese Spring (CS). Structural variant analysis identified chromosome 2A with the highest number of deletions (5,980) and insertions (4,545), while chromosome 3B had the most inversions (466). Duplications were most frequent on 2A (320), and contractions on 2B (235). The gene content of the major resistance quantitative trait loci on 3B, Fhb1, largely validates previous annotations for CS, although we discovered two new genes at approximately 12.4 Mb, including an additional copy of a terpene synthase, further suggesting homology with CS 3D over 3B. Differential expression analysis highlighted up-regulation of three genes coding pore forming-toxin like protein, sina superfamily protein, and plastid-lipid associated proteins potentially involved in FHB resistance. This assembly provides critical insights into FHB resistance and offers a valuable genomic resource for wheat breeding programs. 1 INTRODUCTION Bread wheat ( Triticum aestivum L.) is one of the most widely grown and important staple crops, providing a significant source of calories and nutrients to the global population (Shiferaw, 2020). However, wheat production faces numerous challenges, including the threat of Fusarium head blight (FHB), also known as scab, caused by the fungal pathogen Fusarium graminearum Schwabe (Dweba et al., 2017; Lilleboe & Roth, 2011; McMullen et al., 2012; Salgado et al., 2015). FHB is disease of wheat spikes that severely reduces grain quality and leads to substantial yield losses (Rojas et al., 2020). Spring grain crops are especially susceptible to FHB since their flowering usually occurs during warm and humid environmental conditions that favor the growth, infection, and spread of the fungus (Birr et al., 2020; Doohan et al., 2003; Parry et al., 1995; Xu et al., 2008). A major FHB epidemic in 1993 severely impacted wheat production in the northern United States hard red spring wheat growing areas of Minnesota, North Dakota, and South Dakota, resulting in a yield loss of 4.8 million tons and causing an economic loss of approximately 704 million US dollars (Beard and Hamlin, 1995). This epidemic underscored the urgent need for the development of wheat varieties with enhanced resistance to FHB to ensure the sustainability and profitability of wheat production in the region. Resistance to FHB in wheat is a complex trait that is inherited quantitatively and involves multiple genetic loci and environmental interactions (Mesterhazy et al., 2020). The resistance is classified into four major types: type I, which confers resistance to initial infection, type II, which limits the spread of the fungus within the spike, type III, which is resistance to kernel infection, and type IV, which is resistance to mycotoxin accumulation (Mesterhazy, 1995; Miller & Amison, 1986; Schroeder & Christensen, 1963). Genetic studies have identified numerous quantitative trait loci (QTL), and genes associated with disease resistance, with Fhb1 (Cuthbert et al., 2006; Liu et al., 2006 and Fhb7 (Guo et al., 2015; Wang et al., 2020) being among the most significant loci controlling type II resistance. The Fhb1 gene, located on the short arm of chromosome 3B, has been “cloned” by three different groups identifying two different genes as the causative agent. Rawat et al. (2016) described the Fhb1 gene as a gene coding pore-forming toxin-like (PFT) protein, suggesting a direct antimicrobial role in FHB resistance. In contrast, Su et al. (2019) later identified Fhb1 as the nearby gene encoding a putative nuclear-localized, histidine-rich calcium-binding protein, working through a susceptibility mode of action where resistance results from a loss-of-function mutation. Building on this, Li et al. (2019) fine-mapped Fhb1 to a 23.8-kb interval and pinpointed TaHRC as the sole candidate gene within that region. However, unlike Su et al., Li et al. interpreted the resistance-conferring allele as a functional variant rather than a knockout, emphasizing the complexity of Fhb1 ’s molecular nature. Over the years, Fhb1 has been extensively incorporated into more than 20 modern cultivars used for wheat production (Zhu et al., 2019). However, this locus has shown inconsistent effectiveness when introgressed into many different genetic backgrounds (Shaobin Zhong, personal communication). Durum wheat is especially vulnerable to this variable efficacy, and it has been postulated that accessory genes on other chromosomes interact with Fhb1 to promote or limit its function (Zhu et al., 2022; 2016). Despite extensive investment in research, the complete set of genes conferring resistance or tolerance to FHB has eluded complete characterization for decades. This challenge has largely been due to the complex genetic architecture of wheat, combined with the lack of comprehensive sequence information in the reference genome (Walkowiak et al., 2020; IWGSC et al., 2018). The lack of detailed genetic maps has confounded efforts to pinpoint the specific interacting loci and resistance haplotypes associated with FHB resistance (Bai and Shaner, 2004). Traditional mapping techniques have often fallen short in resolving the intricate network of QTLs that govern this resistance, leading to a significant gap in our understanding of the genetic basis of FHB resistance (Buerstmayr et al., 2009). The multi-genic nature of FHB resistance, coupled with environmental interactions, further complicates the identification and functional validation of resistance genes (Mesterhazy, 1995). Recent advancements in genomic technologies have begun to overcome these hurdles. The advent of high-throughput sequencing methods, including short-read sequencing (IWGSC et al., 2018), third generation long-read sequencing (Pucker et al., 2022), and high-resolution genotyping platforms (Geethanjali et al., 2024), have revolutionized our ability to dissect the wheat genome. These technologies provide the resolution necessary to identify small polymorphisms, structural variations, and presence-absence variations that determine FHB resistance. For instance, the development of long-read sequencing platforms such as PacBio and Nanopore has enabled the rapid assembly of contiguous genome sequences, revealing previously hidden genetic elements that contribute to disease resistance (Murigneux et al., 2020). Moreover, the integration of Hi-C sequencing data has facilitated the scaffolding of these contigs into chromosomal pseudomolecules, allowing for the production of many new wheat genomes (Akpinar et al., 2022; Athiyannan et al., 2022; Aury et al., 2022; Kale et al., 2022; Liu et al., 2024; Liu et al., 2025; Sato et al., 2021; Zhu et al., 2021) and more accurate mapping of resistance loci (Ghurye et al., 2019). Here, we report the utilization of these technologies to generate a high-quality de novo assembly of the Sumai 3 cultivar for use as a robust foundation to build genomics research upon and better understand this disease. 2 MATERIALS AND METHODS 2.1 Plant materials, library preparation, and sequencing T. aestivum cv Sumai 3, used to generate a chromosome-level genome assembly, was developed in China by crossing two moderately susceptible parents, ‘Funo’ and ‘Taiwanxiaomai’ and was found to exhibit high-level FHB resistance and other important agronomic traits (Bai and Shaner 1994). Seedlings of Sumai 3 were grown in a controlled hydroponic growth chamber adjusted with 12 h photoperiod and day/night temperature set to 20°/18 °C. The growth solution was made using MaxiBloom Hydroponics Plant Food (General Hydroponics, Sevastopol, CA, United States) at a concentration of 1.7 g/L. In preparation for PacBio HiFi sequencing, high-molecular weight (HMW) DNA was extracted from 2-week-old young leaf tissues after 72-h dark-treatment using a CTAB-Qiagen Genomic-tip protocol as described previously (Vaillancourt and Buell, 2019). DNA quantity and quality was checked using Qubit double-stranded DNA high sensitivity (dsDNA HS) assay and Nanodrop spectrophotometer respectively. HMW genomic DNA was sheared to 17 kb on a Diagenode Megaruptor and then processed into SMRTbell adapted libraries using SMRTbell Express Template Prep Kit 2.0. Size selection was performed using a Sage BluePippin to select fragments greater than 15 kb and then sequenced at the Brigham Young University DNA Sequencing Center (Provo, UT, USA) using Sequel II Sequencing Kit 2.0 with Sequencing Primer v5 and Sequel Binding kit 2.2 for 30 h with adaptive loading using PacBio SMRT Link recommendations. In total 21 cells were run resulting in 397 Gb of circular consensus (HiFi CCS) data which is approximately 25.6x genome coverage. For chromosomal conformational capture (Hi-C) sequencing, two independent libraries were prepared by a Phase Genomic, Inc using the 4-base restriction endonuclease DPNII and sequenced on the Illumina NovaSeq platform (Illumina, San Diego, CA, USA) with a total output of 45x coverage. Total RNA was extracted from stem, leaf, spikelet, and rachis tissues with a Qiagen RNA Easy Plant Kit, pooled at equimolar concentrations, and converted into a single IsoSeq library. This library was sequenced with one PacBio HiFi cell, resulting in 7.3 Gb of data. Total RNA was also extracted from spikelet tissues collected 5 days post-inoculation with water (treated as mock) and F. graminearum conidia spores under three replications. High-quality RNA (RIN ≥ 8) was converted to RNA_Seq libraries and sequenced (NovogeneUSA), yielding ~10 Gb raw reads per individual samples. Raw reads were trimmed using Trimmomatic (Bolger et al., 2014), and quality were checked using FASTQC (Andrews, 2010). Clean reads (Q ≥ 30) were mapped to a de novo high-quality Sumai 3 genome using HISAT2, and differentially expressed genes were identified using Hisat2-featurecounts-DESeq2 pipeline. Differential gene expression analysis was performed using DESeq2 (Love et al., 2014), applying a stringent cutoff of FDR 1 to identify significantly regulated genes. 2.2 Genome assembly and scaffolding Primary assembly contigs were generated by assembling PacBio HiFi reads with Hifiasm v0.16.1 using default parameters and option –l0 (disable duplicate purging). The TRITEX pipeline (Monat et al., 2019) was used to inspect and curate the contig sequences and scaffold primary contigs into pseudomolecules with Hi-C proximity. Briefly, Hi-C reads were aligned to the primary contigs and only uniquely aligned paired-end reads were retained for downstream analyses. The resulting files were plotted using a custom script to visualize the Hi-C map (Figure S1b) and to facilitate manual curation in cases where the Hi-C map showed a dis-contiguous sequence. The final assembly consisted of 21 pseudomolecules and 4,362 unanchored contigs that were concatenated into a ChrUn pseudomolecule. NCBI Foreign Contamination Screen (FCS) (Astashyn et al., 2024) was employed to detect and eliminate contaminant sequences. The FCS identified 67 contaminant fragments, including 66 adaptor fragments and one mitochondrial fragment across 21 pseudomolecules, totaling 3,898 (0.03%) contaminant nucleotides that were subsequently hard-masked. 2.3 Genome assembly quality and annotation of repetitive and non-coding elements Genome completeness of Sumai 3 was assessed relative to conserved orthologous genes with the poales_odb10 database using BUSCO v5.7.1 (Manni et al., 2021). Transposable elements (TEs) were annotated using a homology-based approach implemented in RepeatMasker v4.2.0 (Smit et al., 2015). A custom repeat library was constructed by combining wheat TE sequences from ClariTeReP (https://github.com/jdaron/CLARI-TE) and 801 Triticum aestivum TE elements (http://botserv2.uzh.ch/kelldata/trep-db/TREP_species_index.php?db=TREP_main). Long terminal repeats (LTRs) were initially identified using LTR_FINDER v1.06 (Xu & Wang, 2007). To enhance detection efficiency and accuracy for estimating LTR Assembly Index (LAI), LTR_FINDER_parallel v1.2 (Ou & Jiang, 2019) was employed. Non-coding RNAs (ncRNAs), including miRNAs, snRNAs, rRNAs, and other regulatory elements, were annotated using Infernal v1.1.2 (Nawrocki et al., 2009) against the Rfam database v14.8 (Grifths-Jones et al., 2005). Further identification of ribosomal and transfer RNAs, RNAmmer v1.2 (Lagesen et al., 2007) and tRNAscan-SE v1.3.1 (Lowe and Eddy, 1997) were used, respectively, identifying functional RNA elements across the genome. 2.4 Gene prediction, functional annotation, and comparative gene analysis Gene structure prediction was conducted using a combination of ab initio and homology-based prediction to ensure comprehensive genome annotation. Initially, ab initio gene prediction was performed using Augustus v3.4.0 (Stanke et al., 2006) with default parameters to identify potential coding regions within the Sumai 3 genome. To complement this, an alternative ab initio prediction was carried out using Helixer (Stiehler et al., 2020), providing an additional layer of annotation refinement. For evidence-based annotation, RNA-seq and Iso-seq datasets were integrated to enhance gene model accuracy, supporting the identification of transcript-supported gene structures. The gene models derived from both ab initio predictions and RNA-seq/Iso-seq evidence were subsequently refined through annotation integration, improving the confidence and completeness of the final gene set. To assess gene conservation and classification, a comparative analysis of high-confidence and low-confidence genes were conducted using CS as reference and Sumai 3 as the query. 2.5 Whole-genome alignment and structural variation analysis Whole-genome alignments between CS and Sumai 3 genomes were performed using Minimap2 v2.24 (Li, 2018) to generate pairwise alignments and assess large-scale genome structure and conservation. Dot plots visualizing the alignments were generated with a custom R script with the ggplot2 package to illustrate overall syntenic relationships. Structural variations including insertion, deletion, duplication, translocation, inversion, and contraction were detected between the reference CS and the query Sumai 3 with MUM&Co (v 3.8) using default parameters, including a minimum alignment length of 50 bp (O’Donnell and Fisher, 2020), enabling identification of genome-wide differences contributing to structural divergence. 2.6 Fhb1 region synteny analysis For the synteny analysis of the Fhb1 region, coding sequences of annotated genes within the known Fhb1 locus were aligned to Sumai 3 chromosome 3BS BAC sequence (GenBank Accession KX907434.1) and the Chinese Spring IWGSC RefSeq v2.1 3BS and 3DS chromosomes using BLAST v2.16.0 (Altschul et al., 1990) to assess sequence similarity and identify homologous regions. This alignment-based comparison enabled quantification of coding sequence conservation and identification of potential homologs across wheat subgenomes. Gene collinearity and syntenic relationships within Fhb1 region were visualized using JBrowse2 (Diesh et al., 2023) and the interactive web-based platform SynVisio (Bandi and Gutwin, 2020) (http://synvisio.github.io/), facilitating detailed examination of gene orientation, and structural conservation (Figure S3). To complement the structural comparison, RNA-seq data from Sumai 3 plants inoculated with F. graminearum spores were analyzed to evaluate expression patterns of genes annotated within Fhb1 region, enabling integration of transcriptomics evidence with structural comparisons. 3 RESULTS AND DISCUSSION 3.1 Chromosome-scale genome assembly of Sumai 3 Using PacBio HiFi CCS and chromosomal conformation Hi-C reads, the final assembly of Sumai 3 genome (Figure 1; Figure S1b) was compared against five other wheat varieties, including Fielder (Sato et al., 2021), Kariega (Athiyannan et al., 2022), Attraktion (Kale et al., 2022), Renan (Aury et al., 2022), and Chinese Spring IWGSC RefSeq v2.1 (Zhu et al., 2021). The total genome sizes across all varieties remain comparable, ranging from 14.26 Gb (Renan) to 14.7 Gb (Fielder). Sumai 3’s genome spans 14.6 Gb, slightly larger than the reference genome CS (14.57 Gb) and similar to the other cultivars. The longest contig length in Sumai 3 (254.2 Mb) is markedly larger than any of the other genomes, with the next highest being 171.22 Mb in Fielder and 158.43 Mb in Kariega. CS, being assembled from short read sequences, exhibits the most fragmented assembly, with its longest contig being only 3.53 Mb. Similarly, contig N50, which represents the contig length at which 50% of the genome is contained in contigs of at least that size, is 41.9 Mb in Sumai 3, double that of Fielder (20.69 Mb) and Kariega (26.66 Mb), and significantly higher than CS (0.34 Mb). The contig count further highlights the fragmentation of CS (306,274 contigs) compared to Sumai 3 (832 contigs), suggesting a more contiguous and high-quality assembly in Sumai 3. Across all assemblies, BUSCO completeness remains high, with Sumai 3 at 99.7% (Table 1; Figure S1a), slightly surpassing CS (99.3%) and other cultivars (99.2-99.4%). In terms of high-confidence (HC) genes, Sumai 3 contains 104,620 genes, which is fewer than CS (106,913 genes) and other varieties such as Fielder (116,480 genes) and Kariega (116,838 genes), likely due to the limited number of tissues that were used in the IsoSeq library preparation. While Sumai 3 has a slightly lower number of annotated genes (Table 1), its high contiguity and assembly quality suggests improved structural integrity and accuracy in gene localization (Michael and VanBuren, 2020). Figure 1. Overview of Sumai 3 chromosome-scale assembly. (a) Distribution of the A. tauschii clone A6-10 subtelomeric tandem repeat sequence (GenBank Accession AY249980.1). (b) Distribution of the A. tauschii clone 6C6-3 (GenBank Accession AY249981.1) and 6C6-4 (GenBank Accession AY249982.1) and T. monococcum ssp. aegilopoides clone BAC TbBAC5 (GenBank Accession DQ904440.1) and TbBAC30 (GenBank Accession EF624064.1) centromere-specific tandem repeat sequences. (c) Distribution of the noncoding gene density. (d) Distribution of tandem repeat density (e) Distribution of the long terminal repeat density. (f) the high-confidence protein-coding gene density. (g) Distribution percentage of GC content. Links between chromosomes are collinearity blocks, which are colored according to the homeologous group. Table 1. The summary results of genome assemblies of wheat cultivars Sumai 3, Fielder, Kariega, Attraktion, Renan, and Chinese Spring IWGSC RefSeq v2.1. Genome features Sumai 3 Fielder Kariega Attraktion Renan CS Total size (Gb) 14.60 14.70 14.68 14.68 14.26 14.57 Longest contig (Mb) 245.2 171.22 158.43 113.94 15.12 3.53 # Contigs 832 1,428 717 1,553 12,982 306,348 Contig N50 (Mb) 41.90 20.69 26.66 16.70 2.16 0.34 BUSCO completeness (%) 99.70 99.30 99.30 99.40 99.20 99.30 # High confidence genes 104,620 116,480 116,838 NA 109,543 106,913 The total chromosome lengths for Sumai 3 range from 502.62 Mb (Chr1D) to 858.38 Mb (Chr3B), closely aligned with CS, where the smallest chromosome (Chr1D) measures 498.64 Mb and the largest (Chr3B) is 851.93 Mb. The D-genome chromosomes (Chr1D, Chr4D, Chr6D) tend to be the smallest on all the assemblies (Athiyannan et al., 2022; Aury et al., 2022; Kale et al., 2022; Sato et al., 2021; Zhu et al., 2021). In Sumai 3, Chr1D (502.62 Mb) is slightly longer than CS (498.64 Mb), while Chr6D (506.59 Mb) and Chr4D (532.53 Mb) remain equivalent in size to their CS counterparts (495.38 Mb and 518.33 Mb, respectively). This suggests a relatively stable D-genome structure across cultivars. The largest chromosome across all cultivars belong to the B and A subgenomes, particularly Chr3B, Chr2B, and Chr3A. Chr3B in Sumai 3 (858.38 Mb) is the largest chromosome, slightly longer than CS (851.93 Mb), and close to Kariega (864.62 Mb) and Fielder (861.14 Mb). Chr2B in Sumai 3 (806.05 Mb) is slightly smaller than CS (812.76 Mb) but aligns closely with other cultivars. Chr3A (757.92 Mb) is nearly identical to CS (754.13 Mb), suggesting strong conservation across cultivars (Table 2). Table 2. Chromosome lengths of genome assemblies of wheat cultivars Sumai 3, Fielder, Kariega, Attraktion, Renan, and Chinese Spring IWGSC RefSeq v2.1. Chromosomes Sumai 3 Fielder Kariega Attraktion Renan CS Chr1A 603,896,264 608,979,116 613,662,638 605,966,608 593,930,347 598,660,471 Chr1B 710,210,752 720,972,993 717,109,572 703,076,930 702,775,664 700,547,350 Chr1D 502,615,715 501,257,520 504,659,958 495,911,329 494,594,617 498,638,509 Chr2A 784,543,660 804,602,427 794,474,755 796,169,439 792,837,209 787,782,082 Chr2B 806,047,704 808,121,247 817,712,742 779,372,321 812,232,696 812,755,788 Chr2D 660,513,740 649,118,519 662,526,948 665,561,653 661,835,603 656,544,405 Chr3A 757,918,164 758,906,661 760,111,594 757,165,295 750,337,041 754,128,162 Chr3B 858,377,832 861,141,126 864,624,966 852,704,148 854,463,248 851,934,019 Chr3D 641,972,620 642,382,296 633,282,846 623,698,249 623,248,023 619,618,552 Chr4A 754,339,051 759,893,476 769,810,128 745,048,881 749,950,614 754,227,511 Chr4B 701,046,972 689,766,370 701,857,263 677,947,850 673,746,810 673,810,255 Chr4D 532,528,736 531,462,149 534,651,777 524,289,323 520,815,567 518,332,611 Chr5A 721,986,879 714,517,032 715,684,684 726,838,826 712,547,961 713,360,525 Chr5B 737,472,575 717,288,350 726,425,509 701,430,346 703,299,309 714,805,278 Chr5D 583,195,916 586,345,039 584,285,409 584,133,940 569,771,178 569,951,140 Chr6A 623,167,309 626,266,972 623,890,083 622,677,745 620,176,429 622,669,697 Chr6B 748,983,441 738,085,275 738,041,677 745,712,656 717,542,863 731,188,232 Chr6D 506,597,824 505,809,789 507,261,758 490,622,797 493,761,083 495,380,293 Chr7A 753,959,795 759,124,079 755,457,679 748,850,018 746,502,734 744,491,536 Chr7B 765,635,790 751,612,808 767,912,069 753,856,519 752,612,656 764,081,788 Chr7D 653,597,169 653,055,523 659,687,352 643,890,519 648,661,963 642,921,167 The long terminal repeat (LTR) Assembly Index (LAI) values provide an estimate of genome assembly quality and the completeness of repetitive elements, varied across chromosomes of Sumai 3, ranging from 22.42 (Chr3D) to 25.61 (Chr5A) indicating a high-quality assembly, particularly for the A and B subgenomes, which generally have higher LAI values than the D subgenome. The A subgenome exhibited the highest LAI values, ranging from 24,52 (Chr7A) to 25.61 (Chr5A), suggesting a more complete representation of repetitive sequences in these chromosomes, consistent with previous findings associating higher LAI scores with extensive retention and continuity of LTR elements (Ou et al., 2018). The B subgenome generally had slightly lower LAI values, with Chr3B (22.89) and Chr7B (23.14) among the lowest in this subgenome. The D subgenome had the lowest LAI scores, with Chr3D (22.42) and Chr7D (22.44) being the least repetitive in terms of LTR assembly. The number of contigs for B subgenome has the highest contig counts, with Chr3B containing 92 contigs. Chr5B had the highest contig density relative to chromosome size, making it the most fragmented chromosome in the Sumai 3 assembly. In contrast, the D subgenome chromosomes tend to have fewer contigs, with Chr4D (13 contigs) and Chr5D (14 contigs). Chr5D exhibited the lowest contig density, indicating the least fragmented and the most contiguous chromosome in the Sumai 3 assembly. MicroRNAs (miRNAs) were most abundant in the B subgenome, with Chr2B (5,948) and Chr3B (5,733) showing the highest count. Conversely, Chr4D (1,817) contained the fewest. Ribosomal RNA (rRNA) content was highest in Chr1B (284) and Chr5D (182), while the lowest counts were found in Chr4B (12). Small nucleolar RNAs (snoRNAs) and small nuclear RNAs (snRNAs) were unevenly distributed, with Chr5B (201) and Chr6D (146) exhibiting highest counts (Table 3). Table 3. Statistics of number of contigs, LAI, and non-coding RNAs on each chromosome in Sumai 3. Chromosomes # contigs LAI miRNA rRNA snoRNA snRNA tRNA Chr1A 15 25.5 2,830 78 151 13 475 Chr1B 73 23.53 4,833 284 164 23 530 Chr1D 19 23.31 2,129 28 140 21 495 Chr2A 25 25.06 3,611 27 99 38 495 Chr2B 62 23.65 5,948 42 98 53 509 Chr2D 16 23.13 2,922 28 64 41 476 Chr3A 21 25.05 3,313 35 60 33 555 Chr3B 92 22.89 5,753 44 118 37 678 Chr3D 21 22.42 2,457 23 58 44 560 Chr4A 40 23.93 3,396 52 81 156 535 Chr4B 70 23.8 4,270 12 121 16 370 Chr4D 13 22.75 1,817 29 86 14 411 Chr5A 20 25.61 3,171 16 164 29 485 Chr5B 89 23.45 5,610 30 201 78 458 Chr5D 14 23.86 2,340 182 107 92 518 Chr6A 20 25.57 2,574 24 128 56 344 Chr6B 86 24.18 4,784 179 151 71 509 Chr6D 16 22.81 1,876 24 146 59 388 Chr7A 20 24.25 3,609 25 96 59 543 Chr7B 74 23.14 5,558 30 138 81 473 Chr7D 26 22.44 2,538 79 73 59 522 Total 832 500.33 75,339 1,271 2,444 1,073 10,329 3.2 Transposable element composition and repeats in the Sumai 3 genome Transposable elements (TEs) play a significant role in genome structure, evolution, and regulation by contributing to genome expansion and genetic diversity. In the Sumai 3 genome, TEs constitute a large proportion of the genome across the A, B, and D subgenomes, with an overall TE content of 84.88%. Among the subgenomes, the A genome harbors the highest proportion (86.14%), followed by B (84.58%), and D (83.93%) (Table 5). Retrotransposons (Class I TEs) are the most abundant class of TEs in the Sumai 3 genome, comprising 71.12% of the genome-wide TE content, consistent with previous findings in wheat, including 67.6% in Chinese Spring v1.0 (IWGSC RefSeq v1.0 ; The International Wheat Genome Sequencing Consortium et al., 2018), 66.9% in Chinese Spring (IWGSC RefSeq v2.1 ; Zhu et al., 2021), 67.7% in Fielder (Sato et al., 2021), and 66.6% in Renan (Aury et al., 2022). The long terminal repeat (LTR) retrotransposons account for the largest portion (70.23% of all TEs), with Copia (15.73%) and Gypsy (52.58%) elements being the most dominant superfamilies. The A genome harbors the highest percentage of LTR retrotransposons (67.90%) reflecting extensive TE expansion with minimal subsequent elimination, indicative of reduced TE turnover, compared to the D genome (67.90%), which shows the lowest percentage of LTR elements. This lower percentage in the D genome may reflect higher rates of recombination, TE removal, or differential accumulation of other repeat types (Tiley and Burleigh, 2015; Kent et al., 2017). The B genome (70.93%) remains intermediate between A and D in LTR content, consistent with previous observations that the B genome tends to have lower repeat content and more streamlined organization compared to the A and D genomes (Zhu et al., 2021). Table 5. Statistics for the repeats in Sumai 3 genomes. Only the repeat types with percentages larger than 0.01% were listed. The bold text indicates the class, the regular text indicates the superfamily, while the italic text indicates family. Repeat types A (%) B (%) D (%) A + B + D (%) Genome size (bp) 4,999,811,122 5,327,775,066 4,081,021,720 14,408,607,908 All TEs (bps) 4,320,075,983 4,546,426,983 3,438,302,525 12,304,805,491 All TEs (%) 86.14 84.58 83.93 84.88 Retrotransposons 72.68 71.89 68.80 71.12 LTR 71.87 70.93 67.90 70.23 Copia (RLC) 15.97 14.99 16.24 15.73 Gypsy (RLG) 54.41 54.10 49.23 52.58 Unknown (RLX) 1.48 1.84 2.43 1.92 LINE (RIX) 0.82 0.95 0.90 0.89 DNA-transposons 8.92 9.58 11.95 10.15 CACTA (DTC) 7.75 8.26 10.52 8.84 Mutator (DTM) 0.28 0.33 0.39 0.33 Harbinger (DTH) 0.27 0.29 0.30 0.29 Mariner (DTT) 0.33 0.38 0.47 0.39 hAT (DTA) 0.02 0.03 0.02 0.02 Helitron (DHH) 0.09 0.11 0.08 0.10 Unknown (DTX) 0.175 0.177 0.182 0.178 Tandem Repeats 3.40 1.25 1.95 2.20 Unknown 1.14 1.87 1.23 1.41 Unlike LTR retrotransposons, DNA transposons (Class II TEs) constitute a minor fraction of the Sumai 3 genome, accounting for only 10.15% of the total genome. The most prevalent DNA transposon families include CACTA elements (8.84%). Other superfamilies such as Mutator (DTM), Harbinger (DTH), Mariner (DTT), hAT (DTA), and Helitron (DHH) were present at lower frequencies (<1% each). These findings are consistent with previous wheat genome assemblies (Athiyannan et al., 2022; Aury et al., 2022; Kale et al., 2022; Sato et al., 2021; Zhu et al., 2021), where DNA transposons are typically present in low copy numbers compared to retrotransposons. The low proportion of DNA transposons suggests that they have undergone limited amplification or have been subject to genomic purging over time. Tandem repeats, which consist of repeated DNA sequences arranged in a head-to-tail fashion, make up 2.20% of the Sumai 3 genome, with A (3.40%) having the highest proportion. These sequences may play structural roles in centromere and telomere formation or contribute to genomic instability. Additionally, unclassified repeats (including unknown and misannotated elements) accounted for 1.41%, which may represent novel or highly diverged transposable elements that are not categorized into known repeat families. 3.3 Synteny analysis and structural variations between Sumai 3 and Chinese Spring IWGSC RefSeq v2.1. A synteny analysis was conducted between CS and Sumai 3. The comparison confirmed strong collinearity between the homoeologous chromosomes of the two cultivars, as evidenced by the prominent diagonal line spanning the plot, consistent with previous wheat studies (Liu et al., 2024; Aury et al., 2022; Athiyannan et al., 2022). Each chromosome pair demonstrated a high degree of synteny, with minimal structural rearrangements observed. However, minor deviations from perfect collinearity, visible as scattered points outside the diagonal, may indicate small-scale structural variations or potential assembly or annotation differences between the genomes (Figure 2; Figure S2). Comprehensive structural variant (SV) analysis identified deletions, insertions, duplications, contractions, inversions, and translocations across all chromosomes. Structural variation analysis between Sumai 3 and CS revealed deletions and insertions as the most dominant variant types, with the majority (56.6%) being less than 500 bp. Chromosome 2A exhibits the highest number of deletions (5,980) and insertions (4,545), with a net increase of 1.70 Mb compared to CS. In contrast, chromosome 4D had the lowest deletion (4,035) and insertion (2,687) counts, with a net decrease in 430 kb compared to CS. Among inversions, chromosome 3B showed the highest frequency (466), while chromosome 4D had the fewest (48), reflecting localized chromosomal rearrangements that could impact gene regulation and recombination. Duplications were most frequent in chromosome 2A (320), while chromosome 3D had the least (124). Similarly, contractions followed a similar pattern, with chromosome 2B having the most (235) and chromosome 3D the least (135). Interestingly, no translocations were detected, suggesting that interchromosomal rearrangements between Sumai 3 and CS are minimal. The structural variants identified here, particularly the inversions and duplications likely influence gene expression and functional diversity, which impacts key agronomic traits such as disease resistance and stress tolerance (Maccaferri et al., 2019) (Table 6; Figure 3). These results highlight the overall genomic stability and conservation between CS and Sumai 3 but also identify regions of variation that may contribute to phenotypic and functional differences between the two cultivars. Figure 2. Whole genome comparison of Sumai 3 with Chinese Spring (IWGSC RefSeq v2.1). Table 6. Structural variant summary of Sumai 3 compared to Chinese Spring IWGSC RefSeq v2.1. Chromosomes Deletions Insertions Duplications Contractions Inversions Translocations Chr1A 4370 3055 173 145 286 0 Chr1B 5075 3479 198 207 309 0 Chr1D 4197 2804 125 148 95 0 Chr2A 5980 4545 320 162 456 0 Chr2B 5797 3859 208 235 299 0 Chr2D 5341 3517 131 149 128 0 Chr3A 5377 3625 181 203 327 0 Chr3B 6033 4424 252 185 466 0 Chr3D 5435 3460 124 135 92 0 Chr4A 4581 3248 198 205 261 0 Chr4B 4535 3288 180 191 267 0 Chr4D 4035 2687 115 146 48 0 Chr5A 4462 2836 152 198 185 0 Chr5B 5201 3894 270 176 351 0 Chr5D 4699 3175 138 188 103 0 Chr6A 4080 2520 128 169 165 0 Chr6B 5228 3687 217 222 372 0 Chr6D 3951 2739 123 148 69 0 Chr7A 5297 3870 217 155 346 0 Chr7B 5468 3821 203 227 258 0 Chr7D 5432 3561 145 143 97 0 Figure 3. Characterization of SVs in Sumai 3 compared to Chinese Spring IWGSC RefSeq v2.1 across all chromosomes. (a) Number of SVs: deletion; insertion; inversion; contraction; duplications. (b) Percentage among five types of SVs. 3.4 Comparative analysis of the Fhb1 region of Sumai 3 on chromosome 3BS with the equivalent regions on CS chromosomes 3BS and 3DS To evaluate gene conservation and variation at the Fhb1 locus, we compared the annotated genes in chromosome 3BS of our chromosome-scale Sumai 3 assembly to the previously published Sumai 3 BAC sequence (Rawat et al., 2016), and the Chinese spring (CS) reference genome, focusing on homoeologous regions on chromosomes 3BS and 3DS (IWGSC RefSeq v2.1; Su et al., 2019). This comparison focuses on an approximately 377 kb sized interval located at 12.4 Mb containing the Fhb1 locus (Figure 4a), which allowed us to assess coding sequence identity and to contextualize the annotation within previously published resources. In the chromosome-scale Sumai 3 assembly, we annotated a total of 15 genes spanning the Fhb1 interval. These included functionally characterized or predicted genes such as alanyl-tRNA synthetase (Ala-RNA), hypothetical protein-A (Hyp-A), plastid-lipid associated proteins (PAP), tRNA methyltransferase (MT), polygalacturonase (PG), oxidoreductase NAD-binding (NAD), terpene synthase (TS), hypothetical protein-D (Hyp-D), histidine-rich calcium-binding protein (His), pore forming-toxin like protein (PFT), sina superfamily protein (Sin), two copies of serine-glycine-asparagine-histidine plant lipase-like protein (SG), cystatin (Cys), and F-box domain containing protein (FB) (Figure 4b). Several genes, including Ala-RNA, Hyp-A, PAP, MT, PG, and His, showed high coding sequence (CDS) identity (>90%) and full or near-full alignment lengths when aligned to the Sumai 3 BAC (Figure 4c; Table S3), CS 3BS (Figure 4d; Table S3), and CS 3DS (Figure 4e; Table S3), indicating strong conservation across B-genome and D-genome. NAD aligned well to BAC and CS 3BS sequences, with 100.0% and 97.0% identity across 805 bp, respectively. Alignment to CS 3DS showed slightly lower identity at 96.6% over a shorter 675 bp region, reflecting typical divergence between B and D subgenomes. For TS, two tandem copies were previously annotated in CS 3DS. The Sumai 3 annotation aligned with high identity (98.2%) to the first of the CS 3DS TS copy, whereas the Sumai 3 BAC and CS 3BS annotations aligned to the second TS copy in CS 3DS, with 94.2% and 94.9% identity and alignment lengths of 1546 bp and 1000 bp, respectively. Importantly, the TS copy present in the Sumai 3 annotation, along with Hyp-D, was located within the ~76 kb physical gap previously reported in the Sumai 3 BAC sequence (Rawat et al., 2016). Hyp-D did not align to the BAC, CS 3BS, or CS 3DS, further supporting its position within the BAC gap. BLAST analysis revealed that Hyp-D encodes a protein with a zf-RVT (zinc finger-reverse transcriptase) domain and an RNase H-like domain, suggesting it is derived from a retrotransposon. While its function remains unclear, the specific localization within previously missing regions may indicate a structural or regulatory role in genome evolution or disease response. The Sumai 3 PFT gene showed 100% identity to the BAC gene, reinforcing annotation consistency in this region. The gene Sin revealed an interesting divergence pattern, while the CDS in Sumai 3 aligned with high identity to BAC sequence (99.7% over 338 bp), CS 3BS (93.6% over 484 bp) and CS 3DS (94.6% over 573 bp), only the CS 3DS alignment covered over 95% of the full gene length (605 bp), compared to ~80% for CS 3BS and ~56% for the BAC sequence. To investigate transcription relevance of these genes, RNA-seq analysis was performed using Sumai 3 samples inoculated with F. graminareum . Differential expression analysis revealed that PAP, PFT, and Sin were upregulated, suggesting their potential involvement in the defense response at the Fhb1 locus. Figure 4. Synteny analysis of Fhb1 region. (a) Chromosome location of the Fhb1 region on 3BS of Sumai 3; (b) Fhb1 region of Sumai 3, containing 15 open reading frames (arrows) and their respective positions within the interval; (c) (d) Comparison of homologous interval in Sumai 3 3BS (Rawat et al., 2016) and CS 3BS (Su et al., 2019); (e) Comparison of homoeologous region in CS 3DS. Arrows represent gene orientation. Genes highlighted in orange were found to be upregulated in Sumai 3 based on RNA-seq analysis. Solid lines connecting orthologs indicate sequence identity > 90%. Genes without connecting lines were not detected or did not meet alignment thresholds in the corresponding genome. Together, this comparative analysis of the Fhb1 region on chromosome 3BS demonstrates strong conservation of gene content between our chromosome-scale assembly, the Sumai 3 BAC, and the Chinese Spring reference genome. The resolution of previously missing genes (TS and Hyp-D) within the ~76 kb BAC gap highlights the improved completeness of our assembly. While most genes exhibited high sequence similarity, moderate divergence in TS, Sin, and NAD underscores the importance of subgenome-specific variation. Notable, the upregulation of PAP, PFT, and Sin in response to F. graminearum infection suggests functional relevance of these genes in host defense. Overall, our integration of structural and transcriptomic data provides a refined view of the Fhb1 locus and strengthens the utility of the Sumai 3 reference for understanding fusarium head blight resistance. ACKNOWLEDGEMENTS We would like to acknowledge Mary Osenga and Terrance Peterson at the North Central Small Grains Genotyping Lab for technical assistance. We also thank Steven Xu, Shaobin Zhong, Xiwen Cai, and Andrew Green, and for seed lots of the Sumai 3 cultivar. This research used resources provided by the USDA-ARS SCINet project 0201-88888-003-000D. This work was supported in part by funding from the U.S. Wheat and Barley Scab Initiative (USWBSI) through USDA-ARS project number 3060-21000-046-000-D. CONFLICT OF INTEREST The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture. USDA is an equal opportunity provider and employer. ORCID Rubylyn D. Mijan https://orcid.org/0009-0004-5450-2695 Jason D. Fiedler https://orcid.org/0000-0001-7736-4484 DATA AVAILABIILTY The assembled genome has been deposited in NCBI under BioProject accession number PRJNA1247523 and is available on Graingenes ( https://wheat.pw.usda.gov). SUPPLEMENTAL MATERIAL Supplemental files include additional figures and tables supporting the genome assembly and annotation of Triticum aestivum cv Sumai 3. These include: Supplementary Figure S1. (a) BUSCO assessment results of assembled Sumai 3 genome; (b) Hi-C contact map showing the intrachromosomal interaction heatmap in the assembled chromosomes of Sumai 3 Supplementary Figure S2. Comparison of Sumai 3 with Chinese Spring IWGSC RefSeq v2.1 across 21 chromosomes Supplementary Figure S3. Syntenic relationship of Sumai 3 (Ta) with Chinese Spring IWGSC RefSeq v2.1 (Cs), including (a) genome-wide; and (b) sub-genome (A, B, and D chromosomes) comparisons Supplementary Table S1. 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Keywords agricultural genome sequencing plant disease rna-seq wheat Authors Affiliations Rubylyn Mijan 0009-0004-5450-2695 North Dakota State University View all articles by this author Bikash Poudel North Dakota State University View all articles by this author Sittal Thapa North Dakota State University View all articles by this author Oluwatayo Ajayi-Moses 0000-0002-7215-1209 North Dakota State University View all articles by this author Thomas Lux Helmholtz Center Munich German Research Center for Environmental Health View all articles by this author Raz Avni Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) View all articles by this author Steven Xu 0000-0001-7000-2034 USDA-ARS Pacific West Area View all articles by this author Manuel Spannagl Helmholtz Center Munich German Research Center for Environmental Health View all articles by this author Martin Mascher 0000-0001-6373-6013 Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) View all articles by this author Peter Maughan 0000-0003-3714-3411 Brigham Young University View all articles by this author Jason Fiedler 0000-0001-7736-4484 [email protected] USDA ARS ETSARC View all articles by this author Metrics & Citations Metrics Article Usage 408 views 131 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Rubylyn Mijan, Bikash Poudel, Sittal Thapa, et al. 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