Highly accurate long-read HiFi sequencing data for five complex genomes

Techniques for assessing telomere length: A methodological review

Telomeres are located at the ends of chromosomes and have specific sequences with a distinctive structure that safeguards genes. They possess capping structures that protect chromosome ends from fusion events and ensure chromosome stability. Telomeres shorten in length during each cycle of cell division. When this length reaches a certain threshold, it can lead to genomic instability, thus being implicated in various diseases, including cancer and neurodegenerative disorders. The possibility of telomeres serving as a biomarker for aging and age-related disease is being explored, and their significance is still under study. This is because post-mitotic cells, which are mature cells that do not undergo mitosis, do not experience telomere shortening due to age. Instead, other causes, for example, exposure to oxidative stress, can directly damage the telomeres, causing genomic instability. Nonetheless, a general agreement has been established that measuring telomere length offers valuable insights and forms a crucial foundation for analyzing gene expression and epigenetic data. Numerous approaches have been developed to accurately measure telomere lengths. In this review, we summarize various methods and their advantages and limitations for assessing telomere length.

Biparental graph strategy to represent and analyze hybrid plant genomes

Hybrid plants are found extensively in the wild, and they often demonstrate superior performance of complex traits over their parents and other selfing plants. This phenomenon, known as heterosis, has been extensively applied in plant breeding for decades. However, the process of decoding hybrid plant genomes has seriously lagged due to the challenges associated with genome assembly and the lack of appropriate methodologies for their subsequent representation and analysis. Here, we present the assembly and analysis of 2 hybrids, an intraspecific hybrid between 2 maize (Zea mays ssp. mays) inbred lines and an interspecific hybrid between maize and its wild relative teosinte (Z. mays ssp. parviglumis), utilizing a combination of PacBio High Fidelity sequencing and chromatin conformation capture sequencing data. The haplotypic assemblies are well phased at chromosomal scale, successfully resolving the complex loci with extensive parental structural variations (SVs). By integrating into a biparental genome graph, the haplotypic assemblies can facilitate downstream short-read-based SV calling and allele-specific gene expression analysis, demonstrating outstanding advantages over a single linear genome. Our work offers a comprehensive workflow that aims to facilitate the decoding of numerous hybrid plant genomes, particularly those with unknown or inaccessible parentage, thereby enhancing our understanding of genome evolution and heterosis.

FindCSV: a long-read based method for detecting complex structural variations

BACKGROUND

Structural variations play a significant role in genetic diseases and evolutionary mechanisms. Extensive research has been conducted over the past decade to detect simple structural variations, leading to the development of well-established detection methods. However, recent studies have highlighted the potentially greater impact of complex structural variations on individuals compared to simple structural variations. Despite this, the field still lacks precise detection methods specifically designed for complex structural variations. Therefore, the development of a highly efficient and accurate detection method is of utmost importance.

RESULT

In response to this need, we propose a novel method called FindCSV, which leverages deep learning techniques and consensus sequences to enhance the detection of SVs using long-read sequencing data. Compared to current methods, FindCSV performs better in detecting complex and simple structural variations.

CONCLUSIONS

FindCSV is a new method to detect complex and simple structural variations with reasonable accuracy in real and simulated data. The source code for the program is available at https://github.com/nwpuzhengyan/FindCSV .

Streamlining of Simple Sequence Repeat Data Mining Methodologies and Pipelines for Crop Scanning

Genetic markers are powerful tools for understanding genetic diversity and the molecular basis of traits, ushering in a new era of molecular breeding in crops. Over the past 50 years, DNA markers have rapidly changed, moving from hybridization-based and second-generation-based to sequence-based markers. Simple sequence repeats (SSRs) are the ideal markers in plant breeding, and they have numerous desirable properties, including their repeatability, codominance, multi-allelic nature, and locus specificity. They can be generated from any species, which requires prior sequence knowledge. SSRs may serve as evolutionary tuning knobs, allowing for rapid identification and adaptation to new circumstances. The evaluations published thus far have mostly ignored SSR polymorphism and gene evolution due to a lack of data regarding the precise placements of SSRs on chromosomes. However, NGS technologies have made it possible to produce high-throughput SSRs for any species using massive volumes of genomic sequence data that can be generated fast and at a minimal cost. Though SNP markers are gradually replacing the erstwhile DNA marker systems, SSRs remain the markers of choice in orphan crops due to the lack of genomic resources at the reference level and their adaptability to resource-limited labor. Several bioinformatic approaches and tools have evolved to handle genomic sequences to identify SSRs and generate primers for genotyping applications in plant breeding projects. This paper includes the currently available methodologies for producing SSR markers, genomic resource databases, and computational tools/pipelines for SSR data mining and primer generation. This review aims to provide a 'one-stop shop' of information to help each new user carefully select tools for identifying and utilizing SSRs in genetic research and breeding programs.

Problems with Paralogs: The Promise and Challenges of Gene Duplicates in Evo-Devo Research

Gene duplicates, or paralogs, serve as a major source of new genetic material and comprise seeds for evolutionary innovation. While originally thought to be quickly lost or nonfunctionalized following duplication, now a vast number of paralogs are known to be retained in a functional state. Daughter paralogs can provide robustness through redundancy, specialize via sub-functionalization, or neo-functionalize to play new roles. Indeed, the duplication and divergence of developmental genes have played a monumental role in the evolution of animal forms (e.g., Hox genes). Still, despite their prevalence and evolutionary importance, the precise detection of gene duplicates in newly sequenced genomes remains technically challenging and often overlooked. This presents an especially pertinent problem for evolutionary developmental biology, where hypothesis testing requires accurate detection of changes in gene expression and function, often in nontraditional model species. Frequently, these analyses rely on molecular reagents designed within coding sequences that may be highly similar in recently duplicated paralogs, leading to cross-reactivity and spurious results. Thus, care is needed to avoid erroneously assigning diverged functions of paralogs to a single gene, and potentially misinterpreting evolutionary history. This perspective aims to overview the prevalence and importance of paralogs and to shed light on the difficulty of their detection and analysis while offering potential solutions.

Wheat improvement through advances in single nucleotide polymorphism (SNP) detection and genotyping with a special emphasis on rust resistance

KEY MESSAGE

Single nucleotide polymorphism (SNP) markers in wheat and their prospects in breeding with special reference to rust resistance. Single nucleotide polymorphism (SNP)-based markers are increasingly gaining momentum for screening and utilizing vital agronomic traits in wheat. To date, more than 260 million SNPs have been detected in modern cultivars and landraces of wheat. This rapid SNP discovery was made possible through the release of near-complete reference and pan-genome assemblies of wheat and its wild relatives, coupled with whole genome sequencing (WGS) of thousands of wheat accessions. Further, genotyping customized SNP sites were facilitated by a series of arrays (9 to 820Ks), a cost effective substitute WGS. Lately, germplasm-specific SNP arrays have been introduced to characterize novel traits and detect closely linked SNPs for marker-assisted breeding. Subsequently, the kompetitive allele-specific PCR (KASP) assay was introduced for rapid and large-scale screening of specific SNP markers. Moreover, with the advances and reduction in sequencing costs, ample opportunities arise for generating SNPs artificially through mutations and in combination with next-generation sequencing and comparative genomic analyses. In this review, we provide historical developments and prospects of SNP markers in wheat breeding with special reference to rust resistance where over 50 genetic loci have been characterized through SNP markers. Rust resistance is one of the most essential traits for wheat breeding as new strains of the Puccinia fungus, responsible for rust diseases, evolve frequently and globally.

Insertions and Deletions: Computational Methods, Evolutionary Dynamics, and Biological Applications

Insertions and deletions constitute the second most important source of natural genomic variation. Insertions and deletions make up to 25% of genomic variants in humans and are involved in complex evolutionary processes including genomic rearrangements, adaptation, and speciation. Recent advances in long-read sequencing technologies allow detailed inference of insertions and deletion variation in species and populations. Yet, despite their importance, evolutionary studies have traditionally ignored or mishandled insertions and deletions due to a lack of comprehensive methodologies and statistical models of insertions and deletion dynamics. Here, we discuss methods for describing insertions and deletion variation and modeling insertions and deletions over evolutionary time. We provide practical advice for tackling insertions and deletions in genomic sequences and illustrate our discussion with examples of insertions and deletion-induced effects in human and other natural populations and their contribution to evolutionary processes. We outline promising directions for future developments in statistical methodologies that would allow researchers to analyze insertions and deletion variation and their effects in large genomic data sets and to incorporate insertions and deletions in evolutionary inference.

De Novo Genome Assemblies From Two Indigenous Americans from Arizona Identify New Polymorphisms in Non-Reference Sequences

There is a collective push to diversify human genetic studies by including underrepresented populations. However, analyzing DNA sequence reads involves the initial step of aligning the reads to the GRCh38/hg38 reference genome which is inadequate for non-European ancestries. In this study, using long-read sequencing technology, we constructed de novo genome assemblies from two indigenous Americans from Arizona (IAZ). Each assembly included ∼17 Mb of DNA sequence not present [nonreference sequence (NRS)] in hg38, which consists mostly of repeat elements. Forty NRSs totaling 240 kb were uniquely anchored to the hg38 primary assembly generating a modified hg38-NRS reference genome. DNA sequence alignment and variant calling were then conducted with whole-genome sequencing (WGS) sequencing data from 387 IAZ using both the hg38 and modified hg38-NRS reference maps. Variant calling with the hg38-NRS map identified ∼50,000 single-nucleotide variants present in at least 5% of the WGS samples which were not detected with the hg38 reference map. We also directly assessed the NRSs positioned within genes. Seventeen NRSs anchored to regions including an identical 187 bp NRS found in both de novo assemblies. The NRS is located in HCN2 79 bp downstream of Exon 3 and contains several putative transcriptional regulatory elements. Genotyping of the HCN2-NRS revealed that the insertion is enriched in IAZ (minor allele frequency = 0.45) compared to other reference populations tested. This study shows that inclusion of population-specific NRSs can dramatically change the variant profile in an underrepresented ethnic groups and thereby lead to the discovery of previously missed common variations.

Chromosome-Scale Genome Assembly and Characterization of Top-Quality Japanese Green Tea Cultivar 'Seimei'

Japanese green tea, an essential beverage in Japanese culture, is characterized by the initial steaming of freshly harvested leaves during production. This process efficiently inactivates endogenous enzymes such as polyphenol oxidases, resulting in the production of sencha, gyokuro and matcha that preserves the vibrant green color of young leaves. Although genome sequences of several tea cultivars and germplasms have been published, no reference genome sequences are available for Japanese green tea cultivars. Here, we constructed a reference genome sequence of the cultivar 'Seimei', which is used to produce high-quality Japanese green tea. Using the PacBio HiFi and Hi-C technologies for chromosome-scale genome assembly, we obtained 15 chromosome sequences with a total genome size of 3.1 Gb and an N50 of 214.9 Mb. By analyzing the genomic diversity of 23 Japanese tea cultivars and lines, including the leading green tea cultivars 'Yabukita' and 'Saemidori', it was revealed that several candidate genes could be related to the characteristics of Japanese green tea. The reference genome of 'Seimei' and information on genomic diversity of Japanese green tea cultivars should provide crucial information for effective breeding of such cultivars in the future.

Recent progress in DNA data storage based on high-throughput DNA synthesis

DNA data storage has emerged as a solution for storing massive volumes of data by utilizing nucleic acids as a digital information medium. DNA offers exceptionally high storage density, long durability, and low maintenance costs compared to conventional storage media such as flash memory and hard disk drives. DNA data storage consists of the following steps: encoding, DNA synthesis (i.e., writing), preservation, retrieval, DNA sequencing (i.e., reading), and decoding. Out of these steps, DNA synthesis presents a bottleneck due to imperfect coupling efficiency, low throughput, and excessive use of organic solvents. Overcoming these challenges is essential to establish DNA as a viable data storage medium. In this review, we provide the overall process of DNA data storage, presenting the recent progress of each step. Next, we examine a detailed overview of DNA synthesis methods with an emphasis on their limitations. Lastly, we discuss the efforts to overcome the constraints of each method and their prospects.

High-quality metagenome assembly from long accurate reads with metaMDBG

We introduce metaMDBG, a metagenomics assembler for PacBio HiFi reads. MetaMDBG combines a de Bruijn graph assembly in a minimizer space with an iterative assembly over sequences of minimizers to address variations in genome coverage depth and an abundance-based filtering strategy to simplify strain complexity. For complex communities, we obtained up to twice as many high-quality circularized prokaryotic metagenome-assembled genomes as existing methods and had better recovery of viruses and plasmids.

Limitations of current high-throughput sequencing technologies lead to biased expression estimates of endogenous retroviral elements

Human endogenous retroviruses (HERVs), the remnants of ancient germline retroviral integrations, comprise almost 8% of the human genome. The elucidation of their biological roles is hampered by our inability to link HERV mRNA and protein production with specific HERV loci. To solve the riddle of the integration-specific RNA expression of HERVs, several bioinformatics approaches have been proposed; however, no single process seems to yield optimal results due to the repetitiveness of HERV integrations. The performance of existing data-bioinformatics pipelines has been evaluated against real world datasets whose true expression profile is unknown, thus the accuracy of widely-used approaches remains unclear. Here, we simulated mRNA production from specific HERV integrations to evaluate second and third generation sequencing technologies along with widely used bioinformatic approaches to estimate the accuracy in describing integration-specific expression. We demonstrate that, while a HERV-family approach offers accurate results, per-integration analyses of HERV expression suffer from substantial expression bias, which is only partially mitigated by algorithms developed for calculating the per-integration HERV expression, and is more pronounced in recent integrations. Hence, this bias could erroneously result into biologically meaningful inferences. Finally, we demonstrate the merits of accurate long-read high-throughput sequencing technologies in the resolution of per-locus HERV expression.

Whole-genome sequencing and identification of antimicrobial peptide coding genes in parsley (Petroselinum crispum), an important culinary and medicinal Apiaceae species

Parsley is a commonly cultivated Apiaceae species of culinary and medicinal importance. Parsley has several recognized health benefits and the species has been utilized in traditional medicine since ancient times. Although parsley is among the most commonly cultivated members of Apiaceae, no systematic genomic research has been conducted on parsley. In the present work, parsley genome was sequenced using the long-read HiFi (high fidelity) sequencing technology and a draft contig assembly of 1.57 Gb that represents 80.9% of the estimated genome size was produced. The assembly was highly repeat-rich with a repetitive DNA content of 81%. The assembly was phased into a primary and alternate assembly in order to minimize redundant contigs. Scaffolds were constructed with the primary assembly contigs, which were used for the identification of AMP (antimicrobial peptide) genes. Characteristic AMP domains and 3D structures were used to detect and verify antimicrobial peptides. As a result, 23 genes (PcAMP1-23) representing defensin, snakin, thionin, lipid transfer protein and vicilin-like AMP classes were identified. Bioinformatic analyses for the characterization of peptide physicochemical properties indicated that parsley AMPs are extracellular peptides, therefore, plausibly exert their antimicrobial effects through the most commonly described AMP action mechanism of membrane attack. AMPs are attracting increasing attention since they display their fast antimicrobial effects in small doses on both plant and animal pathogens with a significantly reduced risk of resistance development. Therefore, identification and characterization of AMPs is important for their incorporation into plant disease management protocols as well as medicinal research for the treatment of multi-drug resistant infections.

Advancing long-read nanopore genome assembly and accurate variant calling for rare disease detection

More than 50% of families with suspected rare monogenic diseases remain unsolved after whole genome analysis by short read sequencing (SRS). Long-read sequencing (LRS) could help bridge this diagnostic gap by capturing variants inaccessible to SRS, facilitating long-range mapping and phasing, and providing haplotype-resolved methylation profiling. To evaluate LRS's additional diagnostic yield, we sequenced a rare disease cohort of 98 samples, including 41 probands and some family members, using nanopore sequencing, achieving per sample ∼36x average coverage and 32 kilobase (kb) read N50 from a single flow cell. Our Napu pipeline generated assemblies, phased variants, and methylation calls. LRS covered, on average, coding exons in ∼280 genes and ∼5 known Mendelian disease genes that were not covered by SRS. In comparison to SRS, LRS detected additional rare, functionally annotated variants, including SVs and tandem repeats, and completely phased 87% of protein-coding genes. LRS detected additional de novo variants, and could be used to distinguish postzygotic mosaic variants from prezygotic de novos . Eleven probands were solved, with diverse underlying genetic causes including de novo and compound heterozygous variants, large-scale SVs, and epigenetic modifications. Our study demonstrates LRS's potential to enhance diagnostic yield for rare monogenic diseases, implying utility in future clinical genomics workflows.

Maptcha: an efficient parallel workflow for hybrid genome scaffolding

BACKGROUND

Genome assembly, which involves reconstructing a target genome, relies on scaffolding methods to organize and link partially assembled fragments. The rapid evolution of long read sequencing technologies toward more accurate long reads, coupled with the continued use of short read technologies, has created a unique need for hybrid assembly workflows. The construction of accurate genomic scaffolds in hybrid workflows is complicated due to scale, sequencing technology diversity (e.g., short vs. long reads, contigs or partial assemblies), and repetitive regions within a target genome.

RESULTS

In this paper, we present a new parallel workflow for hybrid genome scaffolding that would allow combining pre-constructed partial assemblies with newly sequenced long reads toward an improved assembly. More specifically, the workflow, called Maptcha, is aimed at generating long scaffolds of a target genome, from two sets of input sequences-an already constructed partial assembly of contigs, and a set of newly sequenced long reads. Our scaffolding approach internally uses an alignment-free mapping step to build a ⟨ contig,contig ⟩ graph using long reads as linking information. Subsequently, this graph is used to generate scaffolds. We present and evaluate a graph-theoretic "wiring" heuristic to perform this scaffolding step. To enable efficient workload management in a parallel setting, we use a batching technique that partitions the scaffolding tasks so that the more expensive alignment-based assembly step at the end can be efficiently parallelized. This step also allows the use of any standalone assembler for generating the final scaffolds.

CONCLUSIONS

Our experiments with Maptcha on a variety of input genomes, and comparison against two state-of-the-art hybrid scaffolders demonstrate that Maptcha is able to generate longer and more accurate scaffolds substantially faster. In almost all cases, the scaffolds produced by Maptcha are at least an order of magnitude longer (in some cases two orders) than the scaffolds produced by state-of-the-art tools. Maptcha runs significantly faster too, reducing time-to-solution from hours to minutes for most input cases. We also performed a coverage experiment by varying the sequencing coverage depth for long reads, which demonstrated the potential of Maptcha to generate significantly longer scaffolds in low coverage settings ( 1 × - 10 × ).

Establishing African genomics and bioinformatics programs through annual regional workshops

The African BioGenome Project (AfricaBP) Open Institute for Genomics and Bioinformatics aims to overcome barriers to capacity building through its distributed African regional workshops and prioritizes the exchange of grassroots knowledge and innovation in biodiversity genomics and bioinformatics. In 2023, we implemented 28 workshops on biodiversity genomics and bioinformatics, covering 11 African countries across the 5 African geographical regions. These regional workshops trained 408 African scientists in hands-on molecular biology, genomics and bioinformatics techniques as well as the ethical, legal and social issues associated with acquiring genetic resources. Here, we discuss the implementation of transformative strategies, such as expanding the regional workshop model of AfricaBP to involve multiple countries, institutions and partners, including the proposed creation of an African digital database with sequence information relating to both biodiversity and agriculture. This will ultimately help create a critical mass of skilled genomics and bioinformatics scientists across Africa.

A roadmap of phylogenomic methods for studying polyploid plant genera

Phylogenetic inference of polyploid species is the first step towards understanding their patterns of diversification. In this paper, we review the challenges and limitations of inferring species relationships of polyploid plants using traditional phylogenetic sequencing approaches, as well as the mischaracterization of the species tree from single or multiple gene trees. We provide a roadmap to infer interspecific relationships among polyploid lineages by comparing and evaluating the application of current phylogenetic, phylogenomic, transcriptomic, and whole-genome approaches using different sequencing platforms. For polyploid species tree reconstruction, we assess the following criteria: (1) the amount of prior information or tools required to capture the genetic region(s) of interest; (2) the probability of recovering homeologs for polyploid species; and (3) the time efficiency of downstream data analysis. Moreover, we discuss bioinformatic pipelines that can reconstruct networks of polyploid species relationships. In summary, although current phylogenomic approaches have improved our understanding of reticulate species relationships in polyploid-rich genera, the difficulties of recovering reliable orthologous genes and sorting all homeologous copies for allopolyploids remain a challenge. In the future, assembled long-read sequencing data will assist the recovery and identification of multiple gene copies, which can be particularly useful for reconstructing the multiple independent origins of polyploids.

GALEON: a comprehensive bioinformatic tool to analyse and visualize gene clusters in complete genomes

MOTIVATION

Gene clusters, defined as a set of genes encoding functionally related proteins, are abundant in eukaryotic genomes. Despite the increasing availability of chromosome-level genomes, the comprehensive analysis of gene family evolution remains largely unexplored, particularly for large and highly dynamic gene families or those including very recent family members. These challenges stem from limitations in genome assembly contiguity, particularly in repetitive regions such as large gene clusters. Recent advancements in sequencing technology, such as long reads and chromatin contact mapping, hold promise in addressing these challenges.

RESULTS

To facilitate the identification, analysis, and visualization of physically clustered gene family members within chromosome-level genomes, we introduce GALEON, a user-friendly bioinformatic tool. GALEON identifies gene clusters by studying the spatial distribution of pairwise physical distances among gene family members along with the genome-wide gene density. The pipeline also enables the simultaneous analysis and comparison of two gene families and allows the exploration of the relationship between physical and evolutionary distances. This tool offers a novel approach for studying the origin and evolution of gene families.

AVAILABILITY AND IMPLEMENTATION

GALEON is freely available from https://www.ub.edu/softevol/galeon and https://github.com/molevol-ub/galeon.

mtDNA analysis using Mitopore

Mitochondrial DNA (mtDNA) analysis is crucial for the diagnosis of mitochondrial disorders, forensic investigations, and basic research. Existing pipelines are complex, expensive, and require specialized personnel. In many cases, including the diagnosis of detrimental single nucleotide variants (SNVs), mtDNA analysis is still carried out using Sanger sequencing. Here, we developed a simple workflow and a publicly available webserver named Mitopore that allows the detection of mtDNA SNVs, indels, and haplogroups. To simplify mtDNA analysis, we tailored our workflow to process noisy long-read sequencing data for mtDNA analysis, focusing on sequence alignment and parameter optimization. We implemented Mitopore with eliBQ (eliminate bad quality reads), an innovative quality enhancement that permits the increase of per-base quality of over 20% for low-quality data. The whole Mitopore workflow and webserver were validated using patient-derived and induced pluripotent stem cells harboring mtDNA mutations. Mitopore streamlines mtDNA analysis as an easy-to-use fast, reliable, and cost-effective analysis method for both long- and short-read sequencing data. This significantly enhances the accessibility of mtDNA analysis and reduces the cost per sample, contributing to the progress of mtDNA-related research and diagnosis.

Probing RNA structure and dynamics using nanopore and next generation sequencing

It has become increasingly evident that the structures RNAs adopt are conformationally dynamic; the various structured states that RNAs sample govern their interactions with other nucleic acids, proteins, and ligands to regulate a myriad of biological processes. Although several biophysical approaches have been developed and used to study the dynamic landscape of structured RNAs, technical limitations have limited their application to all classes of RNA due to variable size and flexibility. Recent advances combining chemical probing experiments with next-generation- and direct sequencing have emerged as an alternative approach to exploring the conformational dynamics of RNA. In this review, we provide a methodological overview of the sequencing-based techniques used to study RNA conformational dynamics. We discuss how different techniques have enabled us to better understand the propensity of RNAs from a variety of different classes to sample multiple conformational states. Finally, we present examples of the ways these techniques have reshaped how we think about RNA structure.

Complete genome assembly provides a high-quality skeleton for pan-NLRome construction in melon

Melon (Cucumis melo L.), being under intensive domestication and selective breeding, displays an abundant phenotypic diversity. Wild germplasm with tolerance to stress represents an untapped genetic resource for discovery of disease-resistance genes. To comprehensively characterize resistance genes in melon, we generate a telomere-to-telomere (T2T) and gap-free genome of wild melon accession PI511890 (C. melo var. chito) with a total length of 375.0 Mb and a contig N50 of 31.24 Mb. The complete genome allows us to dissect genome architecture and identify resistance gene analogs. We construct a pan-NLRome using seven melon genomes, which include 208 variable and 18 core nucleotide-binding leucine-rich repeat receptors (NLRs). Multiple disease-related transcriptome analyses indicate that most up-regulated NLRs induced by pathogens are shell or cloud NLRs. The T2T gap-free assembly and the pan-NLRome not only serve as essential resources for genomic studies and molecular breeding of melon but also provide insights into the genome architecture and NLR diversity.

Mapping structural variants to rare disease genes using long-read whole genome sequencing and trait-relevant polygenic scores

Recent studies have revealed the pervasive landscape of rare structural variants (rSVs) present in human genomes. rSVs can have extreme effects on the expression of proximal genes and, in a rare disease context, have been implicated in patient cases where no diagnostic single nucleotide variant (SNV) was found. Approaches for integrating rSVs to date have focused on targeted approaches in known Mendelian rare disease genes. This approach is intractable for rare diseases with many causal loci or patients with complex, multi-phenotype syndromes. We hypothesized that integrating trait-relevant polygenic scores (PGS) would provide a substantial reduction in the number of candidate disease genes in which to assess rSV effects. We further implemented a method for ranking PGS genes to define a set of core/key genes where a rSV has the potential to exert relatively larger effects on disease risk. Among a subset of patients enrolled in the Genomic Answers for Kids (GA4K) rare disease program (N=497), we used PacBio HiFi long-read whole genome sequencing (lrWGS) to identify rSVs intersecting genes in trait-relevant PGSs. Illustrating our approach in Autism (N=54 cases), we identified 22, 019 deletions, 2,041 duplications, 87,826 insertions, and 214 inversions overlapping putative core/key PGS genes. Additionally, by integrating genomic constraint annotations from gnomAD, we observed that rare duplications overlapping putative core/key PGS genes were frequently in higher constraint regions compared to controls (P = 1×10-03). This difference was not observed in the lowest-ranked gene set (P = 0.15). Overall, our study provides a framework for the annotation of long-read rSVs from lrWGS data and prioritization of disease-linked genomic regions for downstream functional validation of rSV impacts. To enable reuse by other researchers, we have made SV allele frequencies and gene associations freely available.

A fully haplotype-resolved and nearly gap-free genome assembly of wheat stripe rust fungus

Stripe rust fungus Puccinia striiformis f. sp. tritici (Pst) is a destructive pathogen of wheat worldwide. Pst has a macrocyclic-heteroecious lifecycle, in which one-celled urediniospores are dikaryotic, each nucleus containing one haploid genome. We successfully generated the first fully haplotype-resolved and nearly gap-free chromosome-scale genome assembly of Pst by combining PacBio HiFi sequencing and trio-binning strategy. The genome size of the two haploid assemblies was 75.59 Mb and 75.91 Mb with contig N50 of 4.17 Mb and 4.60 Mb, and both had 18 pseudochromosomes. The high consensus quality values of 55.57 and 59.02 for both haplotypes confirmed the correctness of the assembly. Of the total 18 chromosomes, 15 and 16 were gapless while there were only five and two gaps for the remaining chromosomes of the two haplotypes, respectively. In total, 15,046 and 15,050 protein-coding genes were predicted for the two haplotypes, and the complete BUSCO scores achieved 97.7% and 97.9%, respectively. The genome will lay the foundation for further research on genetic variations and the evolution of rust fungi.

Integration of hybrid and self-correction method improves the quality of long-read sequencing data

Third-generation sequencing (TGS) technologies have revolutionized genome science in the past decade. However, the long-read data produced by TGS platforms suffer from a much higher error rate than that of the previous technologies, thus complicating the downstream analysis. Several error correction tools for long-read data have been developed; these tools can be categorized into hybrid and self-correction tools. So far, these two types of tools are separately investigated, and their interplay remains understudied. Here, we integrate hybrid and self-correction methods for high-quality error correction. Our procedure leverages the inter-similarity between long-read data and high-accuracy information from short reads. We compare the performance of our method and state-of-the-art error correction tools on Escherichia coli and Arabidopsis thaliana datasets. The result shows that the integration approach outperformed the existing error correction methods and holds promise for improving the quality of downstream analyses in genomic research.

New insights into functional divergence and adaptive evolution of uncultured bacteria in anammox community by complete genome-centric analysis

Anaerobic ammonium-oxidation (anammox) bacteria play a crucial role in global nitrogen cycling and wastewater nitrogen removal, but they share symbiotic relationships with various other microorganisms. Functional divergence and adaptive evolution of uncultured bacteria in anammox community remain underexplored. Although shotgun metagenomics based on short reads has been widely used in anammox research, metagenome-assembled genomes (MAGs) are often discontinuous and highly contaminated, which limits in-depth analyses of anammox communities. Here, for the first time, we performed Pacific Biosciences high-fidelity (HiFi) long-read sequencing on the anammox granule sludge sample from a lab-scale bioreactor, and obtained 30 accurate and complete metagenome-assembled genomes (cMAGs). These cMAGs were obtained by selecting high-quality circular contigs from initial assemblies of long reads generated by HiFi sequencing, eliminating the need for Illumina short reads, binning, and reassembly. One new anammox species affiliated with Candidatus Jettenia and three species affiliated with novel families were found in this anammox community. cMAG-centric analysis revealed functional divergence in general and nitrogen metabolism among the anammox community members, and they might adopt a cross-feeding strategy in organic matter, cofactors, and vitamins. Furthermore, we identified 63 mobile genetic elements (MGEs) and 50 putative horizontal gene transfer (HGT) events within these cMAGs. The results suggest that HGT events and MGEs related to phage and integration or excision, particularly transposons containing tnpA in anammox bacteria, might play important roles in the adaptive evolution of this anammox community. The cMAGs generated in the present study could be used to establish of a comprehensive database for anammox bacteria and associated microorganisms. These findings highlight the advantages of HiFi sequencing for the studies of complex mixed cultures and advance the understanding of anammox communities.

A new long-read mitochondrial-genome protocol (PacBio HiFi) for haemosporidian parasites: a tool for population and biodiversity studies

BACKGROUND

Studies on haemosporidian diversity, including origin of human malaria parasites, malaria's zoonotic dynamic, and regional biodiversity patterns, have used target gene approaches. However, current methods have a trade-off between scalability and data quality. Here, a long-read Next-Generation Sequencing protocol using PacBio HiFi is presented. The data processing is supported by a pipeline that uses machine-learning for analysing the reads.

METHODS

A set of primers was designed to target approximately 6 kb, almost the entire length of the haemosporidian mitochondrial genome. Amplicons from different samples were multiplexed in an SMRTbell® library preparation. A pipeline (HmtG-PacBio Pipeline) to process the reads is also provided; it integrates multiple sequence alignments, a machine-learning algorithm that uses modified variational autoencoders, and a clustering method to identify the mitochondrial haplotypes/species in a sample. Although 192 specimens could be studied simultaneously, a pilot experiment with 15 specimens is presented, including in silico experiments where multiple data combinations were tested.

RESULTS

The primers amplified various haemosporidian parasite genomes and yielded high-quality mt genome sequences. This new protocol allowed the detection and characterization of mixed infections and co-infections in the samples. The machine-learning approach converged into reproducible haplotypes with a low error rate, averaging 0.2% per read (minimum of 0.03% and maximum of 0.46%). The minimum recommended coverage per haplotype is 30X based on the detected error rates. The pipeline facilitates inspecting the data, including a local blast against a file of provided mitochondrial sequences that the researcher can customize.

CONCLUSIONS

This is not a diagnostic approach but a high-throughput method to study haemosporidian sequence assemblages and perform genotyping by targeting the mitochondrial genome. Accordingly, the methodology allowed for examining specimens with multiple infections and co-infections of different haemosporidian parasites. The pipeline enables data quality assessment and comparison of the haplotypes obtained to those from previous studies. Although a single locus approach, whole mitochondrial data provide high-quality information to characterize species pools of haemosporidian parasites.

ESKEMAP: exact sketch-based read mapping

BACKGROUND

Given a sequencing read, the broad goal of read mapping is to find the location(s) in the reference genome that have a "similar sequence". Traditionally, "similar sequence" was defined as having a high alignment score and read mappers were viewed as heuristic solutions to this well-defined problem. For sketch-based mappers, however, there has not been a problem formulation to capture what problem an exact sketch-based mapping algorithm should solve. Moreover, there is no sketch-based method that can find all possible mapping positions for a read above a certain score threshold.

RESULTS

In this paper, we formulate the problem of read mapping at the level of sequence sketches. We give an exact dynamic programming algorithm that finds all hits above a given similarity threshold. It runs in O ( | t | + | p | + ℓ 2 ) time and O ( ℓ log ℓ ) space, where |t| is the number of k -mers inside the sketch of the reference, |p| is the number of k -mers inside the read's sketch and ℓ is the number of times that k -mers from the pattern sketch occur in the sketch of the text. We evaluate our algorithm's performance in mapping long reads to the T2T assembly of human chromosome Y, where ampliconic regions make it desirable to find all good mapping positions. For an equivalent level of precision as minimap2, the recall of our algorithm is 0.88, compared to only 0.76 of minimap2.

PacBio Hi-Fi genome assembly of Sipha maydis, a model for the study of multipartite mutualism in insects

Dependence on multiple nutritional endosymbionts has evolved repeatedly in insects feeding on unbalanced diets. However, reference genomes for species hosting multi-symbiotic nutritional systems are lacking, even though they are essential for deciphering the processes governing cooperative life between insects and anatomically integrated symbionts. The cereal aphid Sipha maydis is a promising model for addressing these issues, as it has evolved a nutritional dependence on two bacterial endosymbionts that complement each other. In this study, we used PacBio High fidelity (HiFi) long-read sequencing to generate a highly contiguous genome assembly of S. maydis with a length of 410 Mb, 3,570 contigs with a contig N50 length of 187 kb, and BUSCO completeness of 95.5%. We identified 117 Mb of repetitive sequences, accounting for 29% of the genome assembly, and predicted 24,453 protein-coding genes, of which 2,541 were predicted enzymes included in an integrated metabolic network with the two aphid-associated endosymbionts. These resources provide valuable genetic and metabolic information for understanding the evolution and functioning of multi-symbiotic systems in insects.

Single-cell and spatial transcriptomics: Bridging current technologies with long-read sequencing

Single-cell technologies have transformed biomedical research over the last decade, opening up new possibilities for understanding cellular heterogeneity, both at the genomic and transcriptomic level. In addition, more recent developments of spatial transcriptomics technologies have made it possible to profile cells in their tissue context. In parallel, there have been substantial advances in sequencing technologies, and the third generation of methods are able to produce reads that are tens of kilobases long, with error rates matching the second generation short reads. Long reads technologies make it possible to better map large genome rearrangements and quantify isoform specific abundances. This further improves our ability to characterize functionally relevant heterogeneity. Here, we show how researchers have begun to combine single-cell, spatial transcriptomics, and long-read technologies, and how this is resulting in powerful new approaches to profiling both the genome and the transcriptome. We discuss the achievements so far, and we highlight remaining challenges and opportunities.

Technology-enabled great leap in deciphering plant genomes

Plant genomes provide essential and vital basic resources for studying many aspects of plant biology and applications (for example, breeding). From 2000 to 2020, 1,144 genomes of 782 plant species were sequenced. In the past three years (2021-2023), 2,373 genomes of 1,031 plant species, including 793 newly sequenced species, have been assembled, representing a great leap. The 2,373 newly assembled genomes, of which 63 are telomere-to-telomere assemblies and 921 have been generated in pan-genome projects, cover the major phylogenetic clades. Substantial advances in read length, throughput, accuracy and cost-effectiveness have notably simplified the achievement of high-quality assemblies. Moreover, the development of multiple software tools using different algorithms offers the opportunity to generate more complete and complex assemblies. A database named N3: plants, genomes, technologies has been developed to accommodate the metadata associated with the 3,517 genomes that have been sequenced from 1,575 plant species since 2000. We also provide an outlook for emerging opportunities in plant genome sequencing.

The Application of Long-Read Sequencing to Cancer

Cancer is a multifaceted disease arising from numerous genomic aberrations that have been identified as a result of advancements in sequencing technologies. While next-generation sequencing (NGS), which uses short reads, has transformed cancer research and diagnostics, it is limited by read length. Third-generation sequencing (TGS), led by the Pacific Biosciences and Oxford Nanopore Technologies platforms, employs long-read sequences, which have marked a paradigm shift in cancer research. Cancer genomes often harbour complex events, and TGS, with its ability to span large genomic regions, has facilitated their characterisation, providing a better understanding of how complex rearrangements affect cancer initiation and progression. TGS has also characterised the entire transcriptome of various cancers, revealing cancer-associated isoforms that could serve as biomarkers or therapeutic targets. Furthermore, TGS has advanced cancer research by improving genome assemblies, detecting complex variants, and providing a more complete picture of transcriptomes and epigenomes. This review focuses on TGS and its growing role in cancer research. We investigate its advantages and limitations, providing a rigorous scientific analysis of its use in detecting previously hidden aberrations missed by NGS. This promising technology holds immense potential for both research and clinical applications, with far-reaching implications for cancer diagnosis and treatment.

Finding divergent sequences of homomorphic sex chromosomes via diploidized nanopore-based assembly from a single male

Although homomorphic sex chromosomes can have non-recombining regions with elevated sequence divergence between its complements, such divergence signals can be difficult to detect bioinformatically. If found in genomes of e.g. insect pests, these sequences could be targeted by the engineered genetic sexing and control systems. Here, we report an approach that can leverage long-read nanopore sequencing of a single XY male to identify divergent regions of homomorphic sex chromosomes. Long-read data are used for de novo genome assembly that is diploidized in a way that maximizes sex-specific differences between its haploid complements. We show that the correct assembly phasing is supported by the mapping of nanopore reads from the male's haploid Y-bearing sperm cells. The approach revealed a highly divergent region (HDR) near the centromere of the homomorphic sex chromosome of Aedes aegypti, the most important arboviral vector, for which there is a great interest in creating new genetic control tools. HDR is located ~5Mb downstream of the known male-determining locus on chromosome 1 and is significantly enriched for ovary-biased genes. While recombination in HDR ceased relatively recently (~1.4 MYA), HDR gametologs have divergent exons and introns of protein coding genes, and most lncRNA genes became X-specific. Megabases of previously invisible sex-linked sequences provide new putative targets for engineering the genetic systems to control this deadly mosquito. Broadly, our approach expands the toolbox for studying cryptic structure of sex chromosomes.

The Complex Landscape of Structural Divergence Between the Drosophila pseudoobscura and D. persimilis Genomes

Structural genomic variants are key drivers of phenotypic evolution. They can span hundreds to millions of base pairs and can thus affect large numbers of genetic elements. Although structural variation is quite common within and between species, its characterization depends upon the quality of genome assemblies and the proportion of repetitive elements. Using new high-quality genome assemblies, we report a complex and previously hidden landscape of structural divergence between the genomes of Drosophila persimilis and D. pseudoobscura, two classic species in speciation research, and study the relationships among structural variants, transposable elements, and gene expression divergence. The new assemblies confirm the already known fixed inversion differences between these species. Consistent with previous studies showing higher levels of nucleotide divergence between fixed inversions relative to collinear regions of the genome, we also find a significant overrepresentation of INDELs inside the inversions. We find that transposable elements accumulate in regions with low levels of recombination, and spatial correlation analyses reveal a strong association between transposable elements and structural variants. We also report a strong association between differentially expressed (DE) genes and structural variants and an overrepresentation of DE genes inside the fixed chromosomal inversions that separate this species pair. Interestingly, species-specific structural variants are overrepresented in DE genes involved in neural development, spermatogenesis, and oocyte-to-embryo transition. Overall, our results highlight the association of transposable elements with structural variants and their importance in driving evolutionary divergence.

Cutting edge tools in the field of soil microbiology

The study of the whole of the genetic material contained within the microbial populations found in a certain environment is made possible by metagenomics. This technique enables a thorough knowledge of the variety, function, and interactions of microbial communities that are notoriously difficult to research. Due to the limitations of conventional techniques such as culturing and PCR-based methodologies, soil microbiology is a particularly challenging field. Metagenomics has emerged as an effective technique for overcoming these obstacles and shedding light on the dynamic nature of the microbial communities in soil. This review focuses on the principle of metagenomics techniques, their potential applications and limitations in soil microbial diversity analysis. The effectiveness of target-based metagenomics in determining the function of individual genes and microorganisms in soil ecosystems is also highlighted. Targeted metagenomics, including high-throughput sequencing and stable-isotope probing, is essential for studying microbial taxa and genes in complex ecosystems. Shotgun metagenomics may reveal the diversity of soil bacteria, composition, and function impacted by land use and soil management. Sanger, Next Generation Sequencing, Illumina, and Ion Torrent sequencing revolutionise soil microbiome research. Oxford Nanopore Technology (ONT) and Pacific Biosciences (PacBio)'s third and fourth generation sequencing systems revolutionise long-read technology. GeoChip, clone libraries, metagenomics, and metabarcoding help comprehend soil microbial communities. The article indicates that metagenomics may improve environmental management and agriculture despite existing limitations.Metagenomics has revolutionised soil microbiology research by revealing the complete diversity, function, and interactions of microorganisms in soil. Metagenomics is anticipated to continue defining the future of soil microbiology research despite some limitations, such as the difficulty of locating the appropriate sequencing method for specific genes.

DNA satellite and chromatin organization at mouse centromeres and pericentromeres

BACKGROUND

Centromeres are essential for faithful chromosome segregation during mitosis and meiosis. However, the organization of satellite DNA and chromatin at mouse centromeres and pericentromeres is poorly understood due to the challenges of assembling repetitive genomic regions.

RESULTS

Using recently available PacBio long-read sequencing data from the C57BL/6 strain, we find that contrary to the previous reports of their homogeneous nature, both centromeric minor satellites and pericentromeric major satellites exhibit a high degree of variation in sequence and organization within and between arrays. While most arrays are continuous, a significant fraction is interspersed with non-satellite sequences, including transposable elements. Using chromatin immunoprecipitation sequencing (ChIP-seq), we find that the occupancy of CENP-A and H3K9me3 chromatin at centromeric and pericentric regions, respectively, is associated with increased sequence enrichment and homogeneity at these regions. The transposable elements at centromeric regions are not part of functional centromeres as they lack significant CENP-A enrichment. Furthermore, both CENP-A and H3K9me3 nucleosomes occupy minor and major satellites spanning centromeric-pericentric junctions and a low yet significant amount of CENP-A spreads locally at centromere junctions on both pericentric and telocentric sides. Finally, while H3K9me3 nucleosomes display a well-phased organization on major satellite arrays, CENP-A nucleosomes on minor satellite arrays are poorly phased. Interestingly, the homogeneous class of major satellites also phase CENP-A and H3K27me3 nucleosomes, indicating that the nucleosome phasing is an inherent property of homogeneous major satellites.

CONCLUSIONS

Our findings reveal that mouse centromeres and pericentromeres display a high diversity in satellite sequence, organization, and chromatin structure.

MarkerScan: Separation and assembly of cobionts sequenced alongside target species in biodiversity genomics projects

Contamination of public databases by mislabelled sequences has been highlighted for many years and the avalanche of novel sequencing data now being deposited has the potential to make databases difficult to use effectively. It is therefore crucial that sequencing projects and database curators perform pre-submission checks to remove obvious contamination and avoid propagating erroneous taxonomic relationships. However, it is important also to recognise that biological contamination of a target sample with unexpected species' DNA can also lead to the discovery of fascinating biological phenomena through the identification of environmental organisms or endosymbionts. Here, we present a novel, integrated method for detection and generation of high-quality genomes of all non-target genomes co-sequenced in eukaryotic genome sequencing projects. After performing taxonomic profiling of an assembly from the raw data, and leveraging the identity of small rRNA sequences discovered therein as markers, a targeted classification approach retrieves and assembles high-quality genomes. The genomes of these cobionts are then not only removed from the target species' genome but also available for further interrogation. Source code is available from https://github.com/CobiontID/MarkerScan. MarkerScan is written in Python and is deployed as a Docker container.

The long and short of it: benchmarking viromics using Illumina, Nanopore and PacBio sequencing technologies

Viral metagenomics has fuelled a rapid change in our understanding of global viral diversity and ecology. Long-read sequencing and hybrid assembly approaches that combine long- and short-read technologies are now being widely implemented in bacterial genomics and metagenomics. However, the use of long-read sequencing to investigate viral communities is still in its infancy. While Nanopore and PacBio technologies have been applied to viral metagenomics, it is not known to what extent different technologies will impact the reconstruction of the viral community. Thus, we constructed a mock bacteriophage community of previously sequenced phage genomes and sequenced them using Illumina, Nanopore and PacBio sequencing technologies and tested a number of different assembly approaches. When using a single sequencing technology, Illumina assemblies were the best at recovering phage genomes. Nanopore- and PacBio-only assemblies performed poorly in comparison to Illumina in both genome recovery and error rates, which both varied with the assembler used. The best Nanopore assembly had errors that manifested as SNPs and INDELs at frequencies 41 and 157 % higher than found in Illumina only assemblies, respectively. While the best PacBio assemblies had SNPs at frequencies 12 and 78 % higher than found in Illumina-only assemblies, respectively. Despite high-read coverage, long-read-only assemblies recovered a maximum of one complete genome from any assembly, unless reads were down-sampled prior to assembly. Overall the best approach was assembly by a combination of Illumina and Nanopore reads, which reduced error rates to levels comparable with short-read-only assemblies. When using a single technology, Illumina only was the best approach. The differences in genome recovery and error rates between technology and assembler had downstream impacts on gene prediction, viral prediction, and subsequent estimates of diversity within a sample. These findings will provide a starting point for others in the choice of reads and assembly algorithms for the analysis of viromes.

Unraveling metagenomics through long-read sequencing: a comprehensive review

The study of microbial communities has undergone significant advancements, starting from the initial use of 16S rRNA sequencing to the adoption of shotgun metagenomics. However, a new era has emerged with the advent of long-read sequencing (LRS), which offers substantial improvements over its predecessor, short-read sequencing (SRS). LRS produces reads that are several kilobases long, enabling researchers to obtain more complete and contiguous genomic information, characterize structural variations, and study epigenetic modifications. The current leaders in LRS technologies are Pacific Biotechnologies (PacBio) and Oxford Nanopore Technologies (ONT), each offering a distinct set of advantages. This review covers the workflow of long-read metagenomics sequencing, including sample preparation (sample collection, sample extraction, and library preparation), sequencing, processing (quality control, assembly, and binning), and analysis (taxonomic annotation and functional annotation). Each section provides a concise outline of the key concept of the methodology, presenting the original concept as well as how it is challenged or modified in the context of LRS. Additionally, the section introduces a range of tools that are compatible with LRS and can be utilized to execute the LRS process. This review aims to present the workflow of metagenomics, highlight the transformative impact of LRS, and provide researchers with a selection of tools suitable for this task.

MicroAnnot: A Dedicated Workflow for Accurate Microsporidian Genome Annotation

With nearly 1700 species, Microsporidia represent a group of obligate intracellular eukaryotes with veterinary, economic and medical impacts. To help understand the biological functions of these microorganisms, complete genome sequencing is routinely used. Nevertheless, the proper prediction of their gene catalogue is challenging due to their taxon-specific evolutionary features. As innovative genome annotation strategies are needed to obtain a representative snapshot of the overall lifestyle of these parasites, the MicroAnnot tool, a dedicated workflow for microsporidian sequence annotation using data from curated databases of accurately annotated microsporidian genes, has been developed. Furthermore, specific modules have been implemented to perform small gene (<300 bp) and transposable element identification. Finally, functional annotation was performed using the signature-based InterProScan software. MicroAnnot's accuracy has been verified by the re-annotation of four microsporidian genomes for which structural annotation had previously been validated. With its comparative approach and transcriptional signal identification method, MicroAnnot provides an accurate prediction of translation initiation sites, an efficient identification of transposable elements, as well as high specificity and sensitivity for microsporidian genes, including those under 300 bp.

Sample and Library Preparation for PacBio Long-Read Sequencing in Grapevine

PacBio long-read sequencing is a third-generation technology that generates long reads up to 20 kilobases (kb), unlike short-read sequencing instruments that produce up to 600 bases. Long-read sequencing is particularly advantageous in higher organisms, such as humans and plants, where repetitive regions in the genome are more abundant. The PacBio long-read sequencing uses a single molecule, real-time approach where the SMRT cells contain several zero-mode waveguides (ZMWs). Each ZMW contains a single DNA molecule bound by a DNA polymerase. All ZMWs are flushed with deoxy nucleotides with a fluorophore specific to each nucleotide. As the sequencing proceeds, the detector detects the wavelength of the fluorescence and the nucleotides are read in real-time. This chapter describes the sample and library preparation for PacBio long-read sequencing for grapevine.

Comparative Evolutionary Genomics in Insects

Genome sequencing quality, in terms of both read length and accuracy, is constantly improving. By combining long-read sequencing technologies with various scaffolding techniques, chromosome-level genome assemblies are now achievable at an affordable price for non-model organisms. Insects represent an exciting taxon for studying the genomic underpinnings of evolutionary innovations, due to ancient origins, immense species-richness, and broad phenotypic diversity. Here we summarize some of the most important methods for carrying out a comparative genomics study on insects. We describe available tools and offer concrete tips on all stages of such an endeavor from DNA extraction through genome sequencing, annotation, and several evolutionary analyses. Along the way we describe important insect-specific aspects, such as DNA extraction difficulties or gene families that are particularly difficult to annotate, and offer solutions. We describe results from several examples of comparative genomics analyses on insects to illustrate the fascinating questions that can now be addressed in this new age of genomics research.

Salmonella Typhimurium with Eight Tandem Copies of blaNDM-1 on a HI2 Plasmid

Carbapenem-resistant Salmonella has recently aroused increasing attention. In this study, a total of four sequence type 36 Salmonella enterica subsp. enterica serovar Typhimurium (S. Typhimurium) isolates were consecutively isolated from an 11-month-old female patient with a gastrointestinal infection, of which one was sensitive to carbapenems and three were resistant to carbapenems. Via antibiotic susceptibility testing, a carbapenemases screening test, plasmid conjugation experiments, Illumina short-reads, and PacBio HiFi sequencing, we found that all four S. Typhimurium isolates contained a blaCTX-M-14-positive IncI1 plasmid. One carbapenem-sensitive S. Typhimurium isolate then obtained an IncHI2 plasmid carrying blaNDM-1 and an IncP plasmid without any resistance genes during the disease progression. The blaNDM-1 gene was located on a new 30 kb multiple drug resistance region, which is flanked by IS26 and TnAs2, respectively. In addition, the ST_F0903R isolate contained eight tandem copies of the ISCR1 unit (ISCR1-dsbD-trpF-ble-blaNDM-1-ISAba125Δ1), but an increase in MICs to carbapenems was not observed. Our work further provided evidence of the rapid spread and amplification of blaNDM-1 through plasmid. Prompting the recognition of carbapenem-resistant Enterobacterales and the initiation of appropriate infection control measures are essential to avoid the spread of these organisms.

Haplotype-resolved genome of heterozygous African cassava cultivar TMEB117 (Manihot esculenta)

Cassava (Manihot esculenta Crantz) is a vital tropical root crop providing essential dietary energy to over 800 million people in tropical and subtropical regions. As a climate-resilient crop, its significance grows as the human population expands. However, yield improvement faces challenges from biotic and abiotic stress and limited breeding. Advanced sequencing and assembly techniques enabled the generation of a highly accurate, nearly complete, haplotype-resolved genome of the African cassava cultivar TMEB117. It is the most accurate cassava genome sequence to date with a base-level accuracy of QV > 64, N50 > 35 Mbp, and 98.9% BUSCO completeness. Over 60% of the genome comprises repetitive elements. We predicted over 45,000 gene models for both haplotypes. This achievement offers valuable insights into the heterozygosity genome organization of the cassava genome, with improved accuracy, completeness, and phased genomes. Due to its high susceptibility to African Cassava Mosaic Virus (ACMV) infections compared to other cassava varieties, TMEB117 provides an ideal reference for studying virus resistance mechanisms, including epigenetic variations and smallRNA expressions.

A near-complete assembly of asparagus bean provides insights into anthocyanin accumulation in pods

Asparagus bean (Vigna unguiculata ssp. sesquipedialis), a subspecies of V. unguiculata, is a vital legume crop widely cultivated in Asia for its tender pods consumed as vegetables. However, the existing asparagus bean assemblies still contain numerous gaps and unanchored sequences, which presents challenges to functional genomics research. Here, we present an improved reference genome sequence of an elite asparagus bean variety, Fengchan 6, achieved through the integration of nanopore ultra-long reads, PacBio high-fidelity reads, and Hi-C technology. The improved assembly is 521.3 Mb in length and demonstrates several enhancements, including a higher N50 length (46.4 Mb), an anchor ratio of 99.8%, and the presence of only one gap. Furthermore, we successfully assembled 14 telomeres and all 11 centromeres, including four telomere-to-telomere chromosomes. Remarkably, the centromeric regions cover a total length of 38.1 Mb, providing valuable insights into the complex architecture of centromeres. Among the 30 594 predicted protein-coding genes, we identified 2356 genes that are tandemly duplicated in segmental duplication regions. These findings have implications for defence responses and may contribute to evolutionary processes. By utilizing the reference genome, we were able to effectively identify the presence of the gene VuMYB114, which regulates the accumulation of anthocyanins, thereby controlling the purple coloration of the pods. This discovery holds significant implications for understanding the underlying mechanisms of color determination and the breeding process. Overall, the highly improved reference genome serves as crucial resource and lays a solid foundation for asparagus bean genomic studies and genetic improvement efforts.

Experimental and Computational Approaches to Measure Telomere Length: Recent Advances and Future Directions

PURPOSE OF REVIEW

The length of telomeres, protective structures at the chromosome ends, is a well-established biomarker for pathological conditions including multisystemic syndromes called telomere biology disorders. Approaches to measure telomere length (TL) differ on whether they estimate average, distribution, or chromosome-specific TL, and each presents their own advantages and limitations.

RECENT FINDINGS

The development of long-read sequencing and publication of the telomere-to-telomere human genome reference has allowed for scalable and high-resolution TL estimation in pre-existing sequencing datasets but is still impractical as a dedicated TL test. As sequencing costs continue to fall and strategies for selectively enriching telomere regions prior to sequencing improve, these approaches may become a promising alternative to classic methods. Measurement methods rely on probe hybridization, qPCR or more recently, computational methods using sequencing data. Refinements of existing techniques and new approaches have been recently developed but a test that is accurate, simple, and scalable is still lacking.

De novo reconstruction of satellite repeat units from sequence data

Satellite DNA are long tandemly repeating sequences in a genome and may be organized as high-order repeats (HORs). They are enriched in centromeres and are challenging to assemble. Existing algorithms for identifying satellite repeats either require the complete assembly of satellites or only work for simple repeat structures without HORs. Here we describe Satellite Repeat Finder (SRF), a new algorithm for reconstructing satellite repeat units and HORs from accurate reads or assemblies without prior knowledge on repeat structures. Applying SRF to real sequence data, we show that SRF could reconstruct known satellites in human and well-studied model organisms. We also find satellite repeats are pervasive in various other species, accounting for up to 12% of their genome contents but are often underrepresented in assemblies. With the rapid progress in genome sequencing, SRF will help the annotation of new genomes and the study of satellite DNA evolution even if such repeats are not fully assembled.

Metagenomic binning of PacBio HiFi data prior to assembly reveals a complete genome of Cosmopolites sordidus (Germar) (Coleopterea: Curculionidae, Dryophthorinae) the most damaging arthropod pest of bananas and plantains

PacBio HiFi sequencing was employed in combination with metagenomic binning to produce a high-quality reference genome of Cosmopolites sordidus. We compared k-mer and alignment reference based pre-binning and post-binning approaches to remove contamination. We were also interested to know if the post-binning approach had interspersed bacterial contamination within intragenic regions of Arthropoda binned contigs. Our analyses identified 3,433 genes that were composed with reads identified as of putative bacterial origins. The pre-binning approach yielded a C. sordidus genome of 1.07 Gb genome composed of 3,089 contigs with 98.6% and 97.1% complete and single copy genome and protein BUSCO scores respectively. In this article we demonstrate that in this case the pre-binning approach does not sacrifice assembly quality for more stringent metagenomic filtering. We also determine post-binning allows for increased intragenic contamination increased with increasing coverage, but the frequency of gene contamination increased with lower coverage. Future work should focus on developing reference free pre-binning approaches for HiFi reads produced from eukaryotic based metagenomic samples.

Local and Environmental Reservoirs of Salmonella enterica After Hurricane Florence Flooding

In many regions of the world, including the United States, human and animal fecal genetic markers have been found in flood waters. In this study, we use high-resolution whole genomic sequencing to examine the origin and distribution of Salmonella enterica after the 2018 Hurricane Florence flooding. We specifically asked whether S. enterica isolated from water samples collected near swine farms in North Carolina shortly after Hurricane Florence had evidence of swine origin. To investigate this, we isolated and fully sequenced 18 independent S. enterica strains from 10 locations (five flooded and five unflooded). We found that all strains have extremely similar chromosomes with only five single nucleotide polymorphisms (SNPs) and possessed two plasmids assigned bioinformatically to the incompatibility groups IncFIB and IncFII. The chromosomal core genome and the IncFIB plasmid are most closely related to environmental Salmonella strains isolated previously from the southeastern US. In contrast, the IncFII plasmid was found in environmental S. enterica strains whose genomes were more divergent, suggesting the IncFII plasmid is more promiscuous than the IncFIB type. We identified 65 antibiotic resistance genes (ARGs) in each of our 18 S. enterica isolates. All ARGs were located on the Salmonella chromosome, similar to other previously characterized environmental isolates. All isolates with different SNPs were resistant to a panel of commonly used antibiotics. These results highlight the importance of environmental sources of antibiotic-resistant S. enterica after extreme flood events.

Deciphering the genetic architecture of fruit color in strawberry

Fruits of Fragaria species usually have an appealing bright red color due to the accumulation of anthocyanins, water-soluble flavonoid pigments. Octoploid cultivated strawberry (Fragaria × ananassa) is a major horticultural crop for which fruit color and associated nutritional value are main breeding targets. Great diversity in fruit color intensity and pattern is observed not only in cultivated strawberry but also in wild relatives such as its octoploid progenitor F. chiloensis or the diploid woodland strawberry F. vesca, a model for fruit species in the Rosaceae. This review examines our understanding of fruit color formation in strawberry and how ongoing developments will advance it. Natural variations of fruit color as well as color changes during fruit development or in response to several cues have been used to explore the anthocyanin biosynthetic pathway and its regulation. So far, the successful identification of causal genetic variants has been largely driven by the availability of high-throughput genotyping tools and high-quality reference genomes of F. vesca and F. × ananassa. The current completion of haplotype-resolved genomes of F. × ananassa combined with QTL mapping will accelerate the exploitation of the untapped genetic diversity of fruit color and help translate the findings into strawberry improvement.