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This study deals with an on-line method for turn-to-turn short-circuit fault detection in low-voltage permanent-magnet synchronous machine drives. Owing to the closed-loop control, the fault effects are reflected in the voltage. Therefore an appropriate diagnostic index is proposed, which is derived from the positive- and negative-sequences of the voltage references. These sequences are obtained in the time domain via adaptive filters, which require only a few calculations. To increase the sensitivity to the fault, the algorithm is only applied to a part of the voltage references, that is, the output of the proportional–integral controllers. Furthermore, the cumulative-sum algorithm is introduced to cope with changes of small magnitudes. This algorithm allows a change of a fault index to be detected and can be used as a decision system. The resulting fault detection scheme is computationally cheap and can be embedded in the control unit. Simulations and experimental results validate the proposed method in steady state and the performances under non-stationary operating conditions are also investigated.

High‐throughput sequencing has the potential to describe biological communities with high efficiency yet comprehensive assessment of diversity with species‐level resolution remains one of the most challenging aspects of metabarcoding studies. We investigated the utility of curated ribosomal and mitochondrial nematode reference sequence databases for determining phylum‐specific species‐level clustering thresholds. We compiled 438 ribosomal and 290 mitochondrial sequences which identified 99% and 94% as the species delineation clustering threshold, respectively. These thresholds were evaluated in HTS data from mock communities containing 39 nematode species as well as environmental samples from Vietnam. We compared the taxonomic description of the mocks generated by two read‐merging and two clustering algorithms and the cluster‐free Dada2 pipeline. Taxonomic assignment with the RDP classifier was assessed under different training sets. Our results showed that 36/39 mock nematode species were identified across the molecular markers (18S: 32, JB2: 19, JB3: 21) in UClust_ref OTUs at their respective clustering thresholds, outperforming UParse_denovo and the commonly used 97% similarity. Dada2 generated the most realistic number of ASVs (18S: 83, JB2: 75, JB3: 82), collectively identifying 30/39 mock species. The ribosomal marker outperformed the mitochondrial markers in terms of species and genus‐level detections for both OTUs and ASVs. The number of taxonomic assignments of OTUs/ASVs was highest when the smallest reference database containing only nematode sequences was used and when sequences were truncated to the respective amplicon length. Overall, OTUs generated more species‐level detections, which were, however, associated with higher error rates compared to ASVs. Genus‐level assignments using ASVs exhibited higher accuracy and lower error rates compared to species‐level assignments, suggesting that this is the most reliable pipeline for rapid assessment of alpha diversity from environmental samples. Curated DNA barcode data were used to delineate nematode‐specific inter‐specific operational taxonomic unit (OTUs) clustering thresholds, which were subsequently tested on a artificial nematode community and environmental samples. Open‐reference clustering (UClust_ref) at these empirically derived thresholds outperformed denovo (UParse) as well as cluster‐free approaches (DADA2), resulting in the most accurate description of the nematode community.

Background The emergence of HIV drug resistance is a challenge in controlling the acquired immunodeficiency syndrome (AIDS) pandemic caused by human immunodeficiency virus-1 (HIV-1) infection. Detection of drug resistance variants at minor frequencies can help to formulate successful antiretroviral therapy (ART) regimens for people living with HIV (PLWH) and reduce the emergence of drug resistance. Therefore, a pipeline which can accurately produce consensus nucleotide sequences and identify drug resistance mutations (DRMs) at defined frequency thresholds will be helpful in the treatment of PLWH, analysis of virus evolution, and the control of the pandemic. Results We have developed a pipeline, HIVGenoPipe, to determine HIV drug resistance variants within the gag-pol region above user-defined frequencies for HIV-1 samples sequenced using Illumina technology. The pipeline has been validated by comparing its results with the results generated by a widely used pipeline, HyDRA, which is limited to the pol region, and with the results generated by Sanger sequencing technology using the same set of 30 samples. The variant frequency used to generate ambiguous consensus sequences in HIVGenoPipe is more accurate than other pipelines because a sample-specific reference, which is generated in real-time with a novel hybrid strategy of de novo and reference-based assembly, is used for the frequency calculation, leading to more accurate drug resistance calls for use by clinicians. In addition, since Nextflow is used as the pipeline platform, HIVGenoPipe inherently has great portability, scalability and reproducibility; and the components can be updated or replaced independently if required. Conclusions We developed HIVGenoPipe for the detection of HIV-1 drug resistance. It constructs more accurate gag-pol consensus sequences, leading to improved detection of DRMs. HIVGenoPipe is open source and freely available under the MIT license at https://github.com/LHRI-Bioinformatics/HIVGenoPipe . The current release (v1.0.1) is archived and available at https://doi.org/ https://doi.org/10.5281/zenodo.15528502 .

Species of the dinoflagellate genus  Tripos  have attracted extensive attention not only because they play a crucial role in marine ecosystems as primary producers, but also because many Tripos species can cause harmful algal blooms (HABs) with significant negative impact on marine ecosystems. The common molecular marker 18S rDNA V4-based metabarcoding analysis has been demonstrated to be effective for identifying species of the dinoflagellate genus Tripos that could not be unambiguously identified according to morphological features. However, the number of Tripos species whose reference 18S rDNA V4 sequences have been resolved is currently very limited, severely hindering the accurate annotation of Tripos species in metabarcoding analysis. In this project, we attempted to expand the 18S rDNA V4 reference sequences by retrieving and analyzing sequences for 81 Tripos species described in AlgaeBase from the NCBI NT database, successfully identifying reference sequences for 59 Tripos species, including 41 known and 18 yet undescribed Tripos species. In addition, phylogenetic analysis of the reference sequences revealed many groups of Tripos species shared identical sequences, indicating that the resolution of the common molecular marker 18S rDNA V4 for Tripos species is limited. Our findings reaffirm that the common molecular marker 18S rDNA V4 does not have adequate resolution for distinguishing many Tripos species, underscore the necessity and importance of selecting molecular markers with higher resolution to improve species identification capacity and the necessity to enhance reference databases to include more Tripos species for better identification of Tripos species in metabarcoding analysis.

Potato (Solanum tuberosum L.) is one of the most important crops with a worldwide production of 370 million metric tons. The objectives of this study were (1) to create a high-quality consensus sequence across the two haplotypes of a diploid clone derived from a tetraploid elite variety and assess the sequence divergence from the available potato genome assemblies, as well as among the two haplotypes; (2) to evaluate the new assembly’s usefulness for various genomic methods; and (3) to assess the performance of phasing in diploid and tetraploid clones, using linked-read sequencing technology. We used PacBio long reads coupled with 10x Genomics reads and proximity ligation scaffolding to create the dAg1_v1.0 reference genome sequence. With a final assembly size of 812 Mb, where 750 Mb are anchored to 12 chromosomes, our assembly is larger than other available potato reference sequences and high proportions of properly paired reads were observed for clones unrelated by pedigree to dAg1. Comparisons of the new dAg1_v1.0 sequence to other potato genome sequences point out the high divergence between the different potato varieties and illustrate the potential of using dAg1_v1.0 sequence in breeding applications.

Background Chromosomal variants play important roles in crop breeding and genetic research. The development of single-stranded oligonucleotide (oligo) probes simplifies the process of fluorescence in situ hybridization (FISH) and facilitates chromosomal identification in many species. Genome sequencing provides rich resources for the development of oligo probes. However, little progress has been made in peanut due to the lack of efficient chromosomal markers. Until now, the identification of chromosomal variants in peanut has remained a challenge. Results A total of 114 new oligo probes were developed based on the genome-wide tandem repeats (TRs) identified from the reference sequences of the peanut variety Tifrunner (AABB, 2 n =  4x = 40) and the diploid species Arachis ipaensis (BB, 2 n =  2x = 20). These oligo probes were classified into 28 types based on their positions and overlapping signals in chromosomes. For each type, a representative oligo was selected and modified with green fluorescein 6-carboxyfluorescein (FAM) or red fluorescein 6-carboxytetramethylrhodamine (TAMRA). Two cocktails, Multiplex #3 and Multiplex #4, were developed by pooling the fluorophore conjugated probes. Multiplex #3 included FAM-modified oligo TIF-439, oligo TIF-185-1, oligo TIF-134-3 and oligo TIF-165. Multiplex #4 included TAMRA-modified oligo Ipa-1162, oligo Ipa-1137, oligo DP-1 and oligo DP-5. Each cocktail enabled the establishment of a genome map-based karyotype after sequential FISH/genomic in situ hybridization (GISH) and in silico mapping. Furthermore, we identified 14 chromosomal variants of the peanut induced by radiation exposure. A total of 28 representative probes were further chromosomally mapped onto the new karyotype. Among the probes, eight were mapped in the secondary constrictions, intercalary and terminal regions; four were B genome-specific; one was chromosome-specific; and the remaining 15 were extensively mapped in the pericentric regions of the chromosomes. Conclusions The development of new oligo probes provides an effective set of tools which can be used to distinguish the various chromosomes of the peanut. Physical mapping by FISH reveals the genomic organization of repetitive oligos in peanut chromosomes. A genome map-based karyotype was established and used for the identification of chromosome variations in peanut following comparisons with their reference sequence positions.

The Bermuda Principles for DNA sequence data sharing are an enduring legacy of the Human Genome Project (HGP). They were adopted by the HGP at a strategy meeting in Bermuda in February of 1996 and implemented in formal policies by early 1998, mandating daily release of HGP-funded DNA sequences into the public domain. The idea of daily sharing, we argue, emanated directly from strategies for large, goal-directed molecular biology projects first tested within the \"community\" of C. elegans researchers, and were introduced and defended for the HGP by the nematode biologists John Sulston and Robert Waterston. In the C. elegans community, and subsequently in the HGP, daily sharing served the pragmatic goals of quality control and project coordination. Yet in the HGP human genome, we also argue, the Bermuda Principles addressed concerns about gene patents impeding scientific advancement, and were aspirational and flexible in implementation and justification. They endured as an archetype for how rapid data sharing could be realized and rationalized, and permitted adaptation to the needs of various scientific communities. Yet in addition to the support of Sulston and Waterston, their adoption also depended on the clout of administrators at the US National Institutes of Health (NIH) and the UK nonprofit charity the Wellcome Trust, which together funded 90% of the HGP human sequencing effort. The other nations wishing to remain in the HGP consortium had to accommodate to the Bermuda Principles, requiring exceptions from incompatible existing or pending data access policies for publicly funded research in Germany, Japan, and France. We begin this story in 1963, with the biologist Sydney Brenner's proposal for a nematode research program at the Laboratory of Molecular Biology (LMB) at the University of Cambridge. We continue through 2003, with the completion of the HGP human reference genome, and conclude with observations about policy and the historiography of molecular biology.

Background Reference sequences play a vital role in next-generation sequencing (NGS), impacting mapping quality during genome analyses. However, reference genomes usually do not represent the full range of genetic diversity of a species as a result of geographical divergence and independent demographic events of different populations. For the mitochondrial genome (mitogenome), which occurs in high copy numbers in cells and is strictly maternally inherited, an optimal reference sequence has the potential to make mitogenome alignment both more accurate and more efficient. In this study, we used three different types of reference sequences for mitogenome mapping, i.e., the commonly used reference sequence (CU-ref), the breed-specific reference sequence (BS-ref) and the sample-specific reference sequence (SS-ref), respectively, and compared the accuracy of mitogenome alignment and SNP calling among them, for the purpose of proposing the optimal reference sequence for mitochondrial DNA (mtDNA) analyses of specific populations Results Four pigs, representing three different breeds, were high-throughput sequenced, subsequently mapping reads to the reference sequences mentioned above, resulting in a largest mapping ratio and a deepest coverage without increased running time when aligning reads to a BS-ref. Next, single nucleotide polymorphism (SNP) calling was carried out by 18 detection strategies with the three tools SAMtools, VarScan and GATK with different parameters, using the bam results mapping to BS-ref. The results showed that all eighteen strategies achieved the same high specificity and sensitivity, which suggested a high accuracy of mitogenome alignment by the BS-ref because of a low requirement for SNP calling tools and parameter choices. Conclusions This study showed that different reference sequences representing different genetic relationships to sample reads influenced mitogenome alignment, with the breed-specific reference sequences being optimal for mitogenome analyses, which provides a refined processing perspective for NGS data.

With increasing utilization of eDNA metabarcoding for fish community assessment, it is critical to identify, address, and communicate its capabilities and limitations. One limitation of great concern is the reliability of taxonomic coverage. Taxonomic blind spots, defined as consistent false negatives for specific taxa despite known presence, reduce corroboration with conventional surveys and can limit the uptake of eDNA metabarcoding for biomonitoring. These blind spots result from gaps in reference sequence libraries, issues with taxonomic resolution, inefficient binding of universal primers to the DNA of certain species, and ineffective collection during the sampling of eDNA. To explore this, a multiproject empirical dataset was compiled and analyzed to evaluate the taxonomic coverage of eDNA metabarcoding for a subset of Canadian freshwater fishes using a standardized workflow for two genetic markers: 12S MiFish‐U and Vertebrate COI. The compiled dataset consists of species lists generated by eDNA surveys, paired conventional surveys, and historical records. In total, 59 fish species across 15 families were evaluated of which approximately 40% were unable to be consistently detected by either marker because of a blind spot. The 12S and COI markers also differed in which kinds of blind spots were most frequently observed, with 12S markers exhibiting more reference and resolution blind spots and the COI marker exhibiting more unclassified blind spots. Additionally, in silico primer testing exhibited inconsistent predictions for amplification when using multiple software packages, suggesting the need for further in vitro analysis to troubleshoot primer‐related blind spots. This study highlights the impact of these blind spots in taxonomic coverage on eDNA metabarcoding studies of Canadian freshwater fishes. The limitations imposed by taxonomic blind spots should be addressed in future optimization efforts as eDNA metabarcoding sees broader acceptance as an applied method for fish biomonitoring. Taxonomic blind spots, defined as consistent false negatives for specific taxa despite known presence, reduce corroboration with conventional surveys and can limit the uptake of eDNA metabarcoding for biomonitoring. To explore current taxonomic blind spots, a multiproject empirical dataset was compiled to evaluate the taxonomic coverage of eDNA metabarcoding for a subset of Canadian freshwater fishes for two genetic markers and of the 59 fish species (across 15 families) evaluated, approximately 40% were unable to be consistently detected by either marker because of a blind spot. This study highlights the impact of these blind spots in taxonomic coverage on eDNA metabarcoding studies of Canadian freshwater fishes and provides a framework for exploring them to improve future research.

Biodiversity assessments relying on DNA have increased rapidly over the last decade. However, the reliability of taxonomic assignments in metabarcoding studies is variable and affected by the reference databases and the assignment methods used. Species level assignments are usually considered as reliable using regional libraries but unreliable using public repositories. In this study, we aimed to test this assumption for metazoan species detected in the Gulf of St. Lawrence in the Northwest Atlantic. We first created a regional library (GSL-rl) by data mining COI barcode sequences from BOLD, and included a reliability ranking system for species assignments. We then estimated 1) the accuracy and precision of the public repository NCBI-nt for species assignments using sequences from the regional library and 2) compared the detection and reliability of species assignments of a metabarcoding dataset using either NCBI-nt or the regional library and popular assignment methods. With NCBI-nt and sequences from the regional library, the BLAST-LCA (least common ancestor) method was the most precise method for species assignments, but the accuracy was higher with the BLAST-TopHit method (>80% over all taxa, between 70% and 90% amongst taxonomic groups). With the metabarcoding dataset, the reliability of species assignments was greater using GSL-rl compared to NCBI-nt. However, we also observed that the total number of reliable species assignments could be maximized using both GSL-rl and NCBI-nt with different optimized assignment methods. The use of a two-step approach for species assignments, i.e., using a regional library and a public repository, could improve the reliability and the number of detected species in metabarcoding studies.