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Advancing crop genomics requires efficient genetic systems enabled by high-quality personalized genome assemblies. Here, we introduce RagTag, a toolset for automating assembly scaffolding and patching, and we establish chromosome-scale reference genomes for the widely used tomato genotype M82 along with Sweet-100, a new rapid-cycling genotype that we developed to accelerate functional genomics and genome editing in tomato. This work outlines strategies to rapidly expand genetic systems and genomic resources in other plant species.

 

Abstract Motivation As genomic data becomes more abundant, efficient algorithms and data structures for sequence alignment become increasingly important. The suffix array is a widely used data structure to accelerate alignment, but the binary search algorithm used to query, it requires widespread memory accesses, causing a large number of cache misses on large datasets. Results Here, we present Sapling, an algorithm for sequence alignment, which uses a learned data model to augment the suffix array and enable faster queries. We investigate different types of data models, providing an analysis of different neural network models as well as providing an open-source aligner with a compact, practical piecewise linear model. We show that Sapling outperforms both an optimized binary search approach and multiple widely used read aligners on a diverse collection of genomes, including human, bacteria and plants, speeding up the algorithm by more than a factor of two while adding <1% to the suffix array’s memory footprint. Availability and implementation The source code and tutorial are available open-source at https://github.com/mkirsche/sapling. Supplementary information Supplementary data are available at Bioinformatics online. 

INTRODUCTION One of the central applications of the human reference genome has been to serve as a baseline for comparison in nearly all human genomic studies. Unfortunately, many difficult regions of the reference genome have remained unresolved for decades and are affected by collapsed duplications, missing sequences, and other issues. Relative to the current human reference genome, GRCh38, the Telomere-to-Telomere CHM13 (T2T-CHM13) genome closes all remaining gaps, adds nearly 200 million base pairs (Mbp) of sequence, corrects thousands of structural errors, and unlocks the most complex regions of the human genome for scientific inquiry. RATIONALE We demonstrate how the T2T-CHM13 reference genome universally improves read mapping and variant identification in a globally diverse cohort. This cohort includes all 3202 samples from the expanded 1000 Genomes Project (1KGP), sequenced with short reads, as well as 17 globally diverse samples sequenced with long reads. By applying state-of-the-art methods for calling single-nucleotide variants (SNVs) and structural variants (SVs), we document the strengths and limitations of T2T-CHM13 relative to its predecessors and highlight its promise for revealing new biological insights within technically challenging regions of the genome. RESULTS Across the 1KGP samples, we found more than 1 million additional high-quality variants genome-wide using T2T-CHM13 than with GRCh38. Within previously unresolved regions of the genome, we identified hundreds of thousands of variants per sample—a promising opportunity for evolutionary and biomedical discovery. T2T-CHM13 improves the Mendelian concordance rate among trios and eliminates tens of thousands of spurious SNVs per sample, including a reduction of false positives in 269 challenging, medically relevant genes by up to a factor of 12. These corrections are in large part due to improvements to 70 protein-coding genes in >9 Mbp of inaccurate sequence caused by falsely collapsed or duplicated regions in GRCh38. Using the T2T-CHM13 genome also yields a more comprehensive view of SVs genome-wide, with a greatly improved balance of insertions and deletions. Finally, by providing numerous resources for T2T-CHM13 (including 1KGP genotypes, accessibility masks, and prominent annotation databases), our work will facilitate the transition to T2T-CHM13 from the current reference genome. CONCLUSION The vast improvements in variant discovery across samples of diverse ancestries position T2T-CHM13 to succeed as the next prevailing reference for human genetics. T2T-CHM13 thus offers a model for the construction and study of high-quality reference genomes from globally diverse individuals, such as is now being pursued through collaboration with the Human Pangenome Reference Consortium. As a foundation, our work underscores the benefits of an accurate and complete reference genome for revealing diversity across human populations. Genomic features and resources available for T2T-CHM13. Comparisons to GRCh38 reveal broad improvements in SNVs, indels, and SVs discovered across diverse human populations by means of short-read (1KGP) and long-read sequencing (LRS). These improvements are due to resolution of complex genomic loci (nonsyntenic and previously unresolved), duplication errors, and discordant haplotypes, including those in medically relevant genes. 

Abstract The current human reference genome, GRCh38, represents over 20 years of effort to generate a high-quality assembly, which has benefitted society 1,2 . However, it still has many gaps and errors, and does not represent a biological genome as it is a blend of multiple individuals 3,4 . Recently, a high-quality telomere-to-telomere reference, CHM13, was generated with the latest long-read technologies, but it was derived from a hydatidiform mole cell line with a nearly homozygous genome 5 . To address these limitations, the Human Pangenome Reference Consortium formed with the goal of creating high-quality, cost-effective, diploid genome assemblies for a pangenome reference that represents human genetic diversity 6 . Here, in our first scientific report, we determined which combination of current genome sequencing and assembly approaches yield the most complete and accurate diploid genome assembly with minimal manual curation. Approaches that used highly accurate long reads and parent–child data with graph-based haplotype phasing during assembly outperformed those that did not. Developing a combination of the top-performing methods, we generated our first high-quality diploid reference assembly, containing only approximately four gaps per chromosome on average, with most chromosomes within ±1% of the length of CHM13. Nearly 48% of protein-coding genes have non-synonymous amino acid changes between haplotypes, and centromeric regions showed the highest diversity. Our findings serve as a foundation for assembling near-complete diploid human genomes at scale for a pangenome reference to capture global genetic variation from single nucleotides to structural rearrangements. 

Since its initial release in 2000, the human reference genome has covered only the euchromatic fraction of the genome, leaving important heterochromatic regions unfinished. Addressing the remaining 8% of the genome, the Telomere-to-Telomere (T2T) Consortium presents a complete 3.055 billion–base pair sequence of a human genome, T2T-CHM13, that includes gapless assemblies for all chromosomes except Y, corrects errors in the prior references, and introduces nearly 200 million base pairs of sequence containing 1956 gene predictions, 99 of which are predicted to be protein coding. The completed regions include all centromeric satellite arrays, recent segmental duplications, and the short arms of all five acrocentric chromosomes, unlocking these complex regions of the genome to variational and functional studies.