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Abstract Long-read sequencing technology has enabled variant detection in difficult-to-map regions of the genome and enabled rapid genetic diagnosis in clinical settings. Rapidly evolving third-generation sequencing platforms like Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT) are introducing newer platforms and data types. It has been demonstrated that variant calling methods based on deep neural networks can use local haplotyping information with long-reads to improve the genotyping accuracy. However, using local haplotype information creates an overhead as variant calling needs to be performed multiple times which ultimately makes it difficult to extend to new data types and platforms as they get introduced. In this work, we have developed a local haplotype approximate method that enables state-of-the-art variant calling performance with multiple sequencing platforms including PacBio Revio system, ONT R10.4 simplex and duplex data. This addition of local haplotype approximation simplifies long-read variant calling with DeepVariant.

Here the Human Pangenome Reference Consortium presents a first draft of the human pangenome reference. The pangenome contains 47 phased, diploid assemblies from a cohort of genetically diverse individuals1. These assemblies cover more than 99% of the expected sequence in each genome and are more than 99% accurate at the structural and base pair levels. Based on alignments of the assemblies, we generate a draft pangenome that captures known variants and haplotypes and reveals new alleles at structurally complex loci. We also add 119 million base pairs of euchromatic polymorphic sequences and 1,115 gene duplications relative to the existing reference GRCh38. Roughly 90 million of the additional base pairs are derived from structural variation. Using our draft pangenome to analyse short-read data reduced small variant discovery errors by 34% and increased the number of structural variants detected per haplotype by 104% compared with GRCh38-based workflows, which enabled the typing of the vast majority of structural variant alleles per sample.

There has been tremendous progress in phased genome assembly production by combining long-read data with parental information or linked-read data. Nevertheless, a typical phased genome assembly generated by trio-hifiasm still generates more than 140 gaps. We perform a detailed analysis of gaps, assembly breaks, and misorientations from 182 haploid assemblies obtained from a diversity panel of 77 unique human samples. Although trio-based approaches using HiFi are the current gold standard, chromosome-wide phasing accuracy is comparable when using Strand-seq instead of parental data. Importantly, the majority of assembly gaps cluster near the largest and most identical repeats (including segmental duplications [35.4%], satellite DNA [22.3%], or regions enriched in GA/AT-rich DNA [27.4%]). Consequently, 1513 protein-coding genes overlap assembly gaps in at least one haplotype, and 231 are recurrently disrupted or missing from five or more haplotypes. Furthermore, we estimate that 6-7 Mbp of DNA are misorientated per haplotype irrespective of whether trio-free or trio-based approaches are used. Of these misorientations, 81% correspond to bona fide large inversion polymorphisms in the human species, most of which are flanked by large segmental duplications. We also identify large-scale alignment discontinuities consistent with 11.9 Mbp of deletions and 161.4 Mbp of insertions per haploid genome. Although 99% of this variation corresponds to satellite DNA, we identify 230 regions of euchromatic DNA with frequent expansions and contractions, nearly half of which overlap with 197 protein-coding genes. Such variable and incompletely assembled regions are important targets for future algorithmic development and pangenome representation.

Long-read sequencing has the potential to transform variant detection by reaching currently difficult-to-map regions and routinely linking together adjacent variations to enable read-based phasing. Third-generation nanopore sequence data have demonstrated a long read length, but current interpretation methods for their novel pore-based signal have unique error profiles, making accurate analysis challenging. Here, we introduce a haplotype-aware variant calling pipeline, PEPPER-Margin-DeepVariant, that produces state-of-the-art variant calling results with nanopore data. We show that our nanopore-based method outperforms the short-read-based single-nucleotide-variant identification method at the whole-genome scale and produces high-quality single-nucleotide variants in segmental duplications and low-mappability regions where short-read-based genotyping fails. We show that our pipeline can provide highly contiguous phase blocks across the genome with nanopore reads, contiguously spanning between 85% and 92% of annotated genes across six samples. We also extend PEPPER-Margin-DeepVariant to PacBio HiFi data, providing an efficient solution with superior performance over the current WhatsHap-DeepVariant standard. Finally, we demonstrate de novo assembly polishing methods that use nanopore and PacBio HiFi reads to produce diploid assemblies with high accuracy (Q35+ nanopore-polished and Q40+ PacBio HiFi-polished).

The SK-BR-3 cell line is one of the most important models for HER2+ breast cancers, which affect one in five breast cancer patients. SK-BR-3 is known to be highly rearranged, although much of the variation is in complex and repetitive regions that may be underreported. Addressing this, we sequenced SK-BR-3 using long-read single molecule sequencing from Pacific Biosciences and develop one of the most detailed maps of structural variations (SVs) in a cancer genome available, with nearly 20,000 variants present, most of which were missed by short-read sequencing. Surrounding the important ERBB2 oncogene (also known as HER2), we discover a complex sequence of nested duplications and translocations, suggesting a punctuated progression. Full-length transcriptome sequencing further revealed several novel gene fusions within the nested genomic variants. Combining long-read genome and transcriptome sequencing enables an in-depth analysis of how SVs disrupt the genome and sheds new light on the complex mechanisms involved in cancer genome evolution.

Many researchers working on the development of dye-sensitized solar cells (DSCs) continue to focus on the synthesis of photoanode materials with high surface area, along with high light scattering ability to enhance light harvesting efficiency (LHE). Meanwhile, dye packing density, which also impacts the LHE significantly, is often overlooked. Solvothermally synthesized anatase TiO2 nanoparticles (SANP) were obtained by a new and simple approach using a mixed solvent, ethanol and acetic acid. SANP were applied in photoanodes of DSCs using either metal-free organic dye (D149) or organometallic (N719) dyes. Dye loading (packing density) was correlated with the isoelectric point (IEP) in addition to light scattering effects were shown to determine the devices photovoltaic efficiency (PCE); specifically when compared with ones employing commercially available TiO2 nanoparticles. SANP photoanodes sensitized with D149 dye were found to be optimised at 10 µm, yielding a PCE of 6.9%, superior to for transparent or transparent + scattering films from the commercial source (5.6% and 5.9%, respectively). Furthermore, a 7.7% PCE was achieved using a SANP photoanode sensitized with N719 dye, with 7.2% seen for the transparent photoanode and 7.9% with a scattering layer. The high PCEs of of SANP devices are attributed to the high dye loading capability in addition to light scattering. A further point of interest is that even with the increased reactivity of the surface towards dye adsorption, we did not observe any significant increase in recombination with the redox mediator, presumably due to the increased dye loading providing better shielding.

While genome assembly projects have been successful in many haploid and inbred species, the assembly of noninbred or rearranged heterozygous genomes remains a major challenge. To address this challenge, we introduce the open-source FALCON and FALCON-Unzip algorithms (https://github.com/PacificBiosciences/FALCON/) to assemble long-read sequencing data into highly accurate, contiguous, and correctly phased diploid genomes. We generate new reference sequences for heterozygous samples including an F1 hybrid of Arabidopsis thaliana, the widely cultivated Vitis vinifera cv. Cabernet Sauvignon, and the coral fungus Clavicorona pyxidata, samples that have challenged short-read assembly approaches. The FALCON-based assemblies are substantially more contiguous and complete than alternate short- or long-read approaches. The phased diploid assembly enabled the study of haplotype structure and heterozygosities between homologous chromosomes, including the identification of widespread heterozygous structural variation within coding sequences.

Professions exist to serve the needs of society and, in the case of the dental profession, patients. Academic dental institutions strive to help meet these needs by educating and developing future practitioners, educators, researchers, and citizen leaders who serve the community and shape the changing environment in which they provide care. As patient needs, practice patterns, scientific evidence, and economic conditions evolve, dental education must respond with self-assessment and innovation. Guiding any institution through authentic reform requires a number of strategies. Lee Bolman and Terrance Deal suggest four organizational constructs, or frames, through which to observe and navigate a complex organization: Structural, Human Resource, Political and Symbolic. This qualitative case study examines a major curricular reform initiative in a North American school of dentistry through Bolman and Deal's organizational frames.

Abstract Background Genome-wide association studies (GWAS) are typically visualized using a two-dimensional Manhattan plot, displaying chromosomal location of SNPs along the x-axis and the negative log-10 of their p-value on the y-axis. This traditional plot provides a broad overview of the results, but offers little opportunity for interaction or expansion of specific regions, and is unable to show additional dimensions of the dataset. Results We created BigTop, a visualization framework in virtual reality (VR), designed to render a Manhattan plot in three dimensions, wrapping the graph around the user in a simulated cylindrical room. BigTop uses the z-axis to display minor allele frequency of each SNP, allowing for the identification of allelic variants of genes. BigTop also offers additional interactivity, allowing users to select any individual SNP and receive expanded information, including SNP name, exact values, and gene location, if applicable. BigTop is built in JavaScript using the React and A-Frame frameworks, and can be rendered using commercially available VR headsets or in a two-dimensional web browser such as Google Chrome. Data is read into BigTop in JSON format, and can be provided as either JSON or a tab-separated text file. Conclusions Using additional dimensions and interactivity options offered through VR, we provide a new, interactive, three-dimensional representation of the traditional Manhattan plot for displaying and exploring GWAS data.

Turbidity is one of the primary metrics to determine water quality in terms of health and environmental concerns, however analysis typically takes place in centralized facilities, with samples periodically collected and transported there. Large scale autonomous deployments (WSNs) are impeded by both initial and per measurement costs. In this study we employ a Paired Emitter-Detector Diode (PEDD) technique to quantitatively measure turbidity using analytical grade calibration standards. Our PEDD approach compares favorably against more conventional photodiode-LED arrangements in terms of spectral sensitivity, cost, power use, sensitivity, limit of detection, and physical arrangement as per the ISO 7027 turbidity sensing standard. The findings show that the PEDD technique was superior in all aforementioned aspects. It is therefore more ideal for low-cost, low-power, IoT deployed sensors. The significance of these findings can lead to environmental deployments that greatly lower the device and per-measurement costs.

Photovoltaic energy conversion is one of the best alternatives to fossil fuel combustion. Petroleum resources are now close to depletion and their combustion is known to be responsible for the release of a considerable amount of greenhouse gases and carcinogenic airborne particles. Novel third-generation solar cells include a vast range of device designs and materials aiming to overcome the factors limiting the current technologies. Among them, quantum dot-based devices showed promising potential both as sensitizers and as colloidal nanoparticle films. A good example is the p-type PbS colloidal quantum dots (CQDs) forming a heterojunction with a n-type wide-band-gap semiconductor such as TiO2 or ZnO. The confinement in these nanostructures is also expected to result in marginal mechanisms, such as the collection of hot carriers and generation of multiple excitons, which would increase the theoretical conversion efficiency limit. Ultimately, this technology could also lead to the assembly of a tandem-type cell with CQD films absorbing in different regions of the solar spectrum.

To date, a number of photon up-conversion (UC) systems with high quantum efficiencies have been demonstrated, including at non-concentrated solar illumination intensities. These are, however, yet to be successfully combined with photovoltaic devices in order to provide substantial increases in photocurrent, as compared with devices without UC. In the present work, we perform simple calculations, based on the optical properties of an UC + solar cell system, specifically a dye-sensitized solar cell and sensitized-triplet-triplet annihilation based UC system, in line with our previous experimentally realized proof-of-concept devices. This model is then used to more specifically identify the limitations and losses, thereby providing a pathway toward improvements, based on either real or hypothetical materials. This model highlights that only a fraction of the benefit may be realized without substantial improvements being made in terms of various transmission losses, coupled with the fact that UC emission typically scales quadratically in this flux regime. The model presented can help identify where research efforts should be focused as well as where there may be little utility, with these lessons also being valuable in the future as even more efficient UC systems are developed. Furthermore, a spreadsheet is provided in the supplementary material to assist other researchers in their efforts. [ABSTRACT FROM AUTHOR]

Abstract The creation of composite structures is a commonly employed approach towards enhanced photocatalytic performance, with one of the key rationales for doing this being to separate photoexcited charges, affording them longer lifetimes in which to react with adsorbed species. Here we examine three composite photocatalysts using either WO3, TiO2 or CeO2 with BiVO4 for the degradation of model dyes Methylene Blue and Rhodamine B. Each of these materials (WO3, TiO2 or CeO2) has a different band edge energy offset with respect to BiVO4, allowing for a systematic comparison of these different arrangements. It is seen that while these offsets can afford beneficial charge transfer (CT) processes, they can also result in the deactivation of certain reactions. We also observed the importance of localized dye concentrations, resulting from a strong affinity between it and the surface, in attaining high overall photocatalytic performance, a factor not often acknowledged. It is hoped in the future that these observations will assist in the judicious selection of semiconductors for use as composite photocatalysts.