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Background: Given the demonstrated utility of Third Generation Sequencing [Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT)] long reads in many studies, a comprehensive analysis and comparison of their data quality and applications is in high demand. Methods: Based on the transcriptome sequencing data from human embryonic stem cells, we analyzed multiple data features of PacBio and ONT, including error pattern, length, mappability and technical improvements over previous platforms. We also evaluated their application to transcriptome analyses, such as isoform identification and quantification and characterization of transcriptome complexity, by comparing the performance of size-selected PacBio, non-size-selected ONT and their corresponding Hybrid-Seq strategies (PacBio+Illumina and ONT+Illumina). Results: PacBio shows overall better data quality, while ONT provides a higher yield. As with data quality, PacBio performs marginally better than ONT in most aspects for both long reads only and Hybrid-Seq strategies in transcriptome analysis. In addition, Hybrid-Seq shows superior performance over long reads only in most transcriptome analyses. Conclusions: Both PacBio and ONT sequencing are suitable for full-length single-molecule transcriptome analysis. As this first use of ONT reads in a Hybrid-Seq analysis has shown, both PacBio and ONT can benefit from a combined Illumina strategy. The tools and analytical methods developed here provide a resource for future applications and evaluations of these rapidly-changing technologies.

Summary The Populus shoot undergoes primary growth (longitudinal growth) followed by secondary growth (radial growth), which produces biomass that is an important source of energy worldwide. We adopted joint PacBio Iso‐Seq and RNA‐seq analysis to identify differentially expressed transcripts along a developmental gradient from the shoot apex to the fifth internode of Populus Nanlin895. We obtained 87 150 full‐length transcripts, including 2081 new isoforms and 62 058 new alternatively spliced isoforms, most of which were produced by intron retention, that were used to update the Populus annotation. Among these novel isoforms, there are 1187 long non‐coding RNAs and 356 fusion genes. Using this annotation, we found 15 838 differentially expressed transcripts along the shoot developmental gradient, of which 1216 were transcription factors (TFs). Only a few of these genes were reported previously. The differential expression of these TFs suggests that they may play important roles in primary and secondary growth. AP2, ARF, YABBY and GRF TFs are highly expressed in the apex, whereas NAC, bZIP, PLATZ and HSF TFs are likely to be important for secondary growth. Overall, our findings provide evidence that long‐read sequencing can complement short‐read sequencing for cataloguing and quantifying eukaryotic transcripts and increase our understanding of the vital and dynamic process of shoot development.

Cotton is an agriculturally important crop. Because of its importance, a genome sequence of a diploid cotton species (Gossypium raimondii, D-genome) was first assembled using Sanger sequencing data in 2012. Improvements to DNA sequencing technology have improved accuracy and correctness of assembled genome sequences. Here we report a new de novo genome assembly of G. raimondii and its close relative G. turneri. The two genomes were assembled to a chromosome level using PacBio long-read technology, HiC, and Bionano optical mapping. This report corrects some minor assembly errors found in the Sanger assembly of G. raimondii. We also compare the genome sequences of these two species for gene composition, repetitive element composition, and collinearity. Most of the identified structural rearrangements between these two species are due to intra-chromosomal inversions. More inversions were found in the G. turneri genome sequence than the G. raimondii genome sequence. These findings and updates to the D-genome sequence will improve accuracy and translation of genomics to cotton breeding and genetics.

Long-read technologies are overcoming early limitations in accuracy and throughput, broadening their application domains in genomics. Dedicated analysis tools that take into account the characteristics of long-read data are thus required, but the fast pace of development of such tools can be overwhelming. To assist in the design and analysis of long-read sequencing projects, we review the current landscape of available tools and present an online interactive database, long-read-tools.org, to facilitate their browsing. We further focus on the principles of error correction, base modification detection, and long-read transcriptomics analysis and highlight the challenges that remain.

The advent of next-generation sequencing (NGS) has brought about a paradigm shift in genomics research, offering unparalleled capabilities for analyzing DNA and RNA molecules in a high-throughput and cost-effective manner. This transformative technology has swiftly propelled genomics advancements across diverse domains. NGS allows for the rapid sequencing of millions of DNA fragments simultaneously, providing comprehensive insights into genome structure, genetic variations, gene expression profiles, and epigenetic modifications. The versatility of NGS platforms has expanded the scope of genomics research, facilitating studies on rare genetic diseases, cancer genomics, microbiome analysis, infectious diseases, and population genetics. Moreover, NGS has enabled the development of targeted therapies, precision medicine approaches, and improved diagnostic methods. This review provides an insightful overview of the current trends and recent advancements in NGS technology, highlighting its potential impact on diverse areas of genomic research. Moreover, the review delves into the challenges encountered and future directions of NGS technology, including endeavors to enhance the accuracy and sensitivity of sequencing data, the development of novel algorithms for data analysis, and the pursuit of more efficient, scalable, and cost-effective solutions that lie ahead.

Background Pacific Biosciences HiFi read technology is currently the industry standard for high accuracy long-read sequencing that has been widely adopted by large sequencing and assembly initiatives for generation of de novo assemblies in non-model organisms. Though adapter contamination filtering is routine in traditional short-read analysis pipelines, it has not been widely adopted for HiFi workflows. Results Analysis of 55 publicly available HiFi datasets revealed that a read-sanitation step to remove sequence artifacts derived from PacBio library preparation from read pools is necessary as adapter sequences can be erroneously integrated into assemblies. Conclusions Here we describe the nature of adapter contaminated reads, their consequences in assembly, and present HiFiAdapterFilt, a simple and memory efficient solution for removing adapter contaminated reads prior to assembly.

Sequencing of the low-complexity ORF15 exon of RPGR, a gene correlated with retinitis pigmentosa and cone dystrophy, is difficult to achieve with NGS and Sanger sequencing. False results could lead to the inaccurate annotation of genetic variants in dbSNP and ClinVar databases, tools on which HGMD and Ensembl rely, finally resulting in incorrect genetic variants interpretation. This paper aims to propose PacBio sequencing as a feasible method to correctly detect genetic variants in low-complexity regions, such as the ORF15 exon of RPGR, and interpret their pathogenicity by structural studies. Biological samples from 75 patients affected by retinitis pigmentosa or cone dystrophy were analyzed with NGS and repeated with PacBio. The results showed that NGS has a low coverage of the ORF15 region, while PacBio was able to sequence the region of interest and detect eight genetic variants, of which four are likely pathogenic. Furthermore, molecular modeling and dynamics of the RPGR Glu-Gly repeats binding to TTLL5 allowed for the structural evaluation of the variants, providing a way to predict their pathogenicity. Therefore, we propose PacBio sequencing as a standard procedure in diagnostic research for sequencing low-complexity regions such as RPGR[sup.ORF15], aiding in the correct annotation of genetic variants in online databases.

ABSTRACT True fungi ( Fungi ) and fungus-like organisms (e.g. Mycetozoa , Oomycota ) constitute the second largest group of organisms based on global richness estimates, with around 3 million predicted species. Compared to plants and animals, fungi have simple body plans with often morphologically and ecologically obscure structures. This poses challenges for accurate and precise identifications. Here we provide a conceptual framework for the identification of fungi, encouraging the approach of integrative (polyphasic) taxonomy for species delimitation, i.e. the combination of genealogy (phylogeny), phenotype (including autecology), and reproductive biology (when feasible). This allows objective evaluation of diagnostic characters, either phenotypic or molecular or both. Verification of identifications is crucial but often neglected. Because of clade-specific evolutionary histories, there is currently no single tool for the identification of fungi, although DNA barcoding using the internal transcribed spacer (ITS) remains a first diagnosis, particularly in metabarcoding studies. Secondary DNA barcodes are increasingly implemented for groups where ITS does not provide sufficient precision. Issues of pairwise sequence similarity-based identifications and OTU clustering are discussed, and multiple sequence alignment-based phylogenetic approaches with subsequent verification are recommended as more accurate alternatives. In metabarcoding approaches, the trade-off between speed and accuracy and precision of molecular identifications must be carefully considered. Intragenomic variation of the ITS and other barcoding markers should be properly documented, as phylotype diversity is not necessarily a proxy of species richness. Important strategies to improve molecular identification of fungi are: (1) broadly document intraspecific and intragenomic variation of barcoding markers; (2) substantially expand sequence repositories, focusing on undersampled clades and missing taxa; (3) improve curation of sequence labels in primary repositories and substantially increase the number of sequences based on verified material; (4) link sequence data to digital information of voucher specimens including imagery. In parallel, technological improvements to genome sequencing offer promising alternatives to DNA barcoding in the future. Despite the prevalence of DNA-based fungal taxonomy, phenotype-based approaches remain an important strategy to catalog the global diversity of fungi and establish initial species hypotheses.

DNA barcoding is a powerful taxonomic tool to identify and discover species. DNA barcoding utilizes one or more standardized short DNA regions for taxon identification. With the emergence of new sequencing techniques, such as Next-generation sequencing (NGS), ONT MinION nanopore sequencing, and Pac Bio sequencing, DNA barcoding has become more accurate, fast, and reliable. Rapid species identification by DNA barcodes has been used in a variety of fields, including forensic science, control of the food supply chain, and disease understanding. The Consortium for Barcode of Life (CBOL) presents various working groups to identify the universal barcode gene, such as COI in metazoans; rbcL, matK, and ITS in plants; ITS in fungi; 16S rRNA gene in bacteria and archaea, and creating a reference DNA barcode library. In this article, an attempt has been made to analyze the various proposed DNA barcode for different organisms, strengths & limitations, recent advancements in DNA barcoding, and methods to speed up the DNA barcode reference library construction. This study concludes that constructing a reference library with high species coverage would be a major step toward identifying species by DNA barcodes. This can be achieved in a short period of time by using advanced sequencing and data analysis methods.

We propose LongQC as an easy and automated quality control tool for genomic datasets generated by third generation sequencing (TGS) technologies such as Oxford Nanopore technologies (ONT) and SMRT sequencing from Pacific Bioscience (PacBio). Key statistics were optimized for long read data, and LongQC covers all major TGS platforms. LongQC processes and visualizes those statistics automatically and quickly.