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Population genomics using short‐read resequencing captures single‐nucleotide polymorphisms and small insertions and deletions but struggles with structural variants, leading to a loss of heritability in genome‐wide association studies. In recent years, long‐read sequencing has improved pangenome construction for diverse eukaryotic species, including humans, crops, and other organisms of ecological and economic importance, addressing this issue to some extent. Sufficient‐coverage high‐fidelity data for population genomics is often prohibitively expensive, limiting its use in large‐scale populations and broader eukaryotic species and creating an urgent need for robust low‐coverage assemblies. However, current assemblers underperform in such conditions. To address this, HiFiCCL is proposed, the first assembly framework specifically designed for low‐coverage high‐fidelity reads, using a reference‐guided, chromosome‐by‐chromosome assembly approach. This study demonstrates that HiFiCCL improves low‐coverage assembly performance of existing assemblers and outperforms the state‐of‐the‐art assemblers on human and plant datasets. Tested on 45 human datasets (∼5× coverage), HiFiCCL combined with hifiasm reduces the length of misassembled contigs relative to hifiasm by an average of 21.19% and up to 38.58%. These improved assemblies excel in detecting large germline structural variants, minimize inter‐chromosome mis‐scaffolding, and improve the detection of specific germline and tumor somatic structural variants based on the pangenome graph. HiFiCCL, as the first assembly framework specifically designed for low‐coverage high‐fidelity reads, improves the assembly quality of existing assemblers and also enhances downstream applications such as large structural variant (SV) detection (>10 000 bp), synteny analysis, pangenome graph construction, and graph‐based individual‐specific germline SVs and tumor somatic SVs detection, thereby advancing the field of population genomics.

Andrographis paniculata is an important medicinal plant containing various bioactive terpenoids and flavonoids. Despite its importance in herbal medicine, no ready-to-use transcript sequence information of this plant is made available in the public data base, this study mainly deals with the sequencing of RNA from A. paniculata leaf using Illumina HiSeq™ 2000 platform followed by the de novo transcriptome assembly. A total of 189.22 million high quality paired reads were generated and 1,70,724 transcripts were predicted in the primary assembly. Secondary assembly generated a transcriptome size of ~88 Mb with 83,800 clustered transcripts. Based on the similarity searches against plant non-redundant protein database, gene ontology, and eukaryotic orthologous groups, 49,363 transcripts were annotated constituting upto 58.91% of the identified unigenes. Annotation of transcripts-using kyoto encyclopedia of genes and genomes database-revealed 5606 transcripts plausibly involved in 140 pathways including biosynthesis of terpenoids and other secondary metabolites. Transcription factor analysis showed 6767 unique transcripts belonging to 97 different transcription factor families. A total number of 124 CYP450 transcripts belonging to seven divergent clans have been identified. Transcriptome revealed 146 different transcripts coding for enzymes involved in the biosynthesis of terpenoids of which 35 contained terpene synthase motifs. This study also revealed 32,341 simple sequence repeats (SSRs) in 23,168 transcripts. Assembled sequences of transcriptome of A. paniculata generated in this study are made available, for the first time, in the TSA database, which provides useful information for functional and comparative genomic analysis besides identification of key enzymes involved in the various pathways of secondary metabolism.

Long-read de novo genome assembly continues to advance rapidly. However, there is a lack of effective tools to accurately evaluate the assembly results, especially for structural errors. We present Inspector, a reference-free long-read de novo assembly evaluator which faithfully reports types of errors and their precise locations. Notably, Inspector can correct the assembly errors based on consensus sequences derived from raw reads covering erroneous regions. Based on in silico and long-read assembly results from multiple long-read data and assemblers, we demonstrate that in addition to providing generic metrics, Inspector can accurately identify both large-scale and small-scale assembly errors.

Several fruit flies species of the Anastrepha fraterculus group are of great economic importance for the damage they cause to a variety of fleshy fruits. Some species in this group have diverged recently, with evidence of introgression, showing similar morphological attributes that render their identification difficult, reinforcing the relevance of identifying new molecular markers that may differentiate species. We investigated genes expressed in head tissues from two closely related species: A. obliqua and A. fraterculus, aiming to identify fixed single nucleotide polymorphisms (SNPs) and highly differentiated transcripts, which, considering that these species still experience some level of gene flow, could indicate potential candidate genes involved in their differentiation process. We generated multiple libraries from head tissues of these two species, at different reproductive stages, for both sexes. Our analyses indicate that the de novo transcriptome assemblies are fairly complete. We also produced a hybrid assembly to map each species’ reads, and identified 67,470 SNPs in A. fraterculus, 39,252 in A. obliqua, and 6386 that were common to both species. We identified 164 highly differentiated unigenes that had a mean interspecific index (D¯) of at least 0.94. We selected unigenes that had Ka/Ks higher than 0.5, or had at least three or more highly differentiated SNPs as potential candidate genes for species differentiation. Among these candidates, we identified proteases, regulators of redox homeostasis, and an odorant-binding protein (Obp99c), among other genes. The head transcriptomes described here enabled the identification of thousands of genes hitherto unavailable for these species, and generated a set of candidate genes that are potentially important to genetically identify species and understand the speciation process in the presence of gene flow of A. obliqua and A. fraterculus.

Recent research into structural variants (SVs) has established their importance to medicine and molecular biology, elucidating their role in various diseases, regulation of gene expression, ethnic diversity, and large-scale chromosome evolution—giving rise to the differences within populations and among species. Nevertheless, characterizing SVs and determining the optimal approach for a given experimental design remains a computational and scientific challenge. Multiple approaches have emerged to target various SV classes, zygosities, and size ranges. Here, we review these approaches with respect to their ability to infer SVs across the full spectrum of large, complex variations and present computational methods for each approach.

SKESA is a DeBruijn graph-based de-novo assembler designed for assembling reads of microbial genomes sequenced using Illumina. Comparison with SPAdes and MegaHit shows that SKESA produces assemblies that have high sequence quality and contiguity, handles low-level contamination in reads, is fast, and produces an identical assembly for the same input when assembled multiple times with the same or different compute resources. SKESA has been used for assembling over 272,000 read sets in the Sequence Read Archive at NCBI and for real-time pathogen detection. Source code for SKESA is freely available at https://github.com/ncbi/SKESA/releases .

Genomic structural variants (SVs) can play important roles in adaptation and speciation. Yet the overall fitness effects of SVs are poorly understood, partly because accurate population-level identification of SVs requires multiple high-quality genome assemblies. Here, we use 31 chromosome-scale, haplotype-resolved genome assemblies of Theobroma cacao—an outcrossing, long-lived tree species that is the source of chocolate—to investigate the fitness consequences of SVs in natural populations. Among the 31 accessions, we find over 160,000 SVs, which together cover eight times more of the genome than single-nucleotide polymorphisms and short indels (125 versus 15 Mb). Our results indicate that a vast majority of these SVs are deleterious: they segregate at low frequencies and are depleted from functional regions of the genome. We show that SVs influence gene expression, which likely impairs gene function and contributes to the detrimental effects of SVs. We also provide empirical support for a theoretical prediction that SVs, particularly inversions, increase genetic load through the accumulation of deleterious nucleotide variants as a result of suppressed recombination. Despite the overall detrimental effects, we identify individual SVs bearing signatures of local adaptation, several of which are associated with genes differentially expressed between populations. Genes involved in pathogen resistance are strongly enriched among these candidates, highlighting the contribution of SVs to this important local adaptation trait. Beyond revealing empirical evidence for the evolutionary importance of SVs, these 31 de novo assemblies provide a valuable resource for genetic and breeding studies in T. cacao.

Summary Studies on structural variation in plants have revealed the inadequacy of a single reference genome for an entire species and suggest that it is necessary to build a species‐representative genome called a pan‐genome to better capture the extent of both structural and nucleotide variation. Here, we present a pan‐genome of cultivated soybean (Glycine max), termed PanSoy, constructed using the de novo genome assembly of 204 phylogenetically and geographically representative improved accessions selected from the larger GmHapMap collection. PanSoy uncovers 108 Mb (˜11%) of novel nonreference sequences encompassing 3621 protein‐coding genes (including 1659 novel genes) absent from the soybean ‘Williams 82’ reference genome. Nonetheless, the core genome represents an exceptionally large proportion of the genome, with >90.6% of genes being shared by >99% of the accessions. A majority of PAVs encompassing genes could be confirmed with long‐read sequencing on a subset of accessions. The PanSoy is a major step towards capturing the extent of genetic variation in cultivated soybean and provides a resource for soybean genomics research and breeding.

Resequencing or reference-based assemblies reveal large parts of the small-scale sequence variation. However, they typically fail to separate such local variation into colinear and rearranged variation, because they usually do not recover the complement of large-scale rearrangements, including transpositions and inversions. Besides the availability of hundreds of genomes of diverse Arabidopsis thaliana accessions, there is so far only one full-length assembled genome: the reference sequence. We have assembled 117 Mb of the A. thaliana Landsberg erecta (Ler) genome into five chromosome-equivalent sequences using a combination of short Illumina reads, long PacBio reads, and linkage information. Whole-genome comparison against the reference sequence revealed 564 transpositions and 47 inversions comprising ∼3.6 Mb, in addition to 4.1 Mb of nonreference sequence, mostly originating from duplications. Although rearranged regions are not different in local divergence from colinear regions, they are drastically depleted for meiotic recombination in heterozygotes. Using a 1.2-Mb inversion as an example, we show that such rearrangement-mediated reduction of meiotic recombination can lead to genetically isolated haplotypes in the worldwide population of A. thaliana. Moreover, we found 105 single-copy genes, which were only present in the reference sequence or the Ler assembly, and 334 single-copy orthologs, which showed an additional copy in only one of the genomes. To our knowledge, this work gives first insights into the degree and type of variation, which will be revealed once complete assemblies will replace resequencing or other reference-dependent methods.

Background The recent introduction of the Pacific Biosciences RS single molecule sequencing technology has opened new doors to scaffolding genome assemblies in a cost-effective manner. The long read sequence information is promised to enhance the quality of incomplete and inaccurate draft assemblies constructed from Next Generation Sequencing (NGS) data. Results Here we propose a novel hybrid assembly methodology that aims to scaffold pre-assembled contigs in an iterative manner using PacBio RS long read information as a backbone. On a test set comprising six bacterial draft genomes, assembled using either a single Illumina MiSeq or Roche 454 library, we show that even a 50× coverage of uncorrected PacBio RS long reads is sufficient to drastically reduce the number of contigs. Comparisons to the AHA scaffolder indicate our strategy is better capable of producing (nearly) complete bacterial genomes. Conclusions The current work describes our SSPACE-LongRead software which is designed to upgrade incomplete draft genomes using single molecule sequences. We conclude that the recent advances of the PacBio sequencing technology and chemistry, in combination with the limited computational resources required to run our program, allow to scaffold genomes in a fast and reliable manner.