bluuebunny/crossref_metadata_2025_split huggingface dataset:
Overexpression of the violaxanthin de-epoxidase confers faster NPQ and photosynthesis induction in rice
Authors: Xin Duanfeng , Chen Faming , Zhou Pengfei , Shi Zai , Tang Qiming , Zhu Xin-Guang 
Published: April 2023

AbstractPlants in the field experience fluctuations in light conditions. Plants with swift responses to dynamic light conditions usually gain competitive advantage in the field. The dynamic photosynthesis can be reflected in dynamic changes in almost all processes in photosynthesis, with dominant factors being dynamic changes in non-photochemical quenching, Rubisco activation and stomatal dynamics. Each of these dynamic responses is controlled by defined mechanisms. In this study, we showed that overexpression of VDE, an enzyme involved in the xanthophyll cycle and non-photochemical quenching, in rice resulted in faster NPQ induction, less photoinhibition, and faster photosynthesis induction, which together caused increased biomass production by about 11∼16%. This study, demonstrating a previously unnoticed role of VDE in altering the dynamics of photosynthesis induction besides decreasing photoinhibition, offers a potential strategy to improve canopy photosynthesis through capitalizing the ability of plants to use dynamic light.HighlightThe overexpression of VDE in rice resulted in faster NPQ induction, less photoinhibition, and faster photosynthesis induction, which together caused increased biomass in field.
Emerging viruses are an underestimated cause of undiagnosed febrile illness in Uganda
Authors: Ashraf Shirin , Jerome Hanna , Bugembe Daniel Lule , Ssemwanga Deogratius , Byaruhanga Timothy , Kayiwa John Timothy , Downing Robert , Salazar-Gonzalez Jesus F. , Salazar Maria G. , Shepherd James G. , Davis Chris , Logan Nicola , Vattipally Sreenu B. , Wilkie Gavin S. , da Silva Filipe Ana , Ssekagiri Alfred , Namuwulya Prossy , Bukenya Henry , Kigozi Brian K. , McConnell Weronika Witkowska , Willett Brian J. , Balinandi Stephen , Lutwama Julius , Kaleebu Pontiano , Bwogi Josephine , Thomson Emma C. 
Published: April 2023

SUMMARYBackgroundViruses that cause acute febrile illness (AFI) in sub-Saharan Africa cause a spectrum of disease from mild to life-threatening. Viral infection is often undiagnosed, as routine diagnostics are insufficient to capture the diversity of circulating pathogens.Methods1281 patients with fever of 2-7 days were prospectively recruited from three sites in Uganda as part of the CDC-UVRI AFI Study and screened with enhanced diagnostics. Plasma from 233 undiagnosed patients was analysed using metagenomic next-generation sequencing (mNGS). Confirmatory testing was carried out by PCR and serology.FindingsThirty-eight viral pathogens were identified by mNGS in 35/233 (15%) undiagnosed patients including Measles, Hepatitis A/B/E viruses, Human immunodeficiency virus-1, Rhinovirus, Rotavirus-like virus, Human herpesvirus 6B, Human parainfluenza virus 3 and Enteroviruses. Four high-consequence arboviruses were found in six patients; Crimean-Congo haemorrhagic fever virus, Rift Valley fever virus, dengue virus and yellow fever virus. Le Dantec virus, last reported in 1969, was detected and confirmed by serology in one patient (and a contact of that patient). The majority of patients (23/30; 76%) diagnosed with an acute viral infection were treated with antibiotics and/or (12/30; 40%) antimalarials.InterpretationAFI in Uganda is commonly associated with undiagnosed viral infection, including high-consequence and rarely reported viruses. This highlights an ongoing risk to public health and the need for improved vigilance. MNGS alongside diagnostic serology is a powerful method for clinical surveillance to investigate circulating viral pathogens. Cost-effective diagnostic assays should be adapted according to regional needs for testing.FundingMedical Research Council and Wellcome Trust
Accurate phenotypic classification and exome sequencing allow identification of novel genes and variants associated with adult-onset hearing loss
Authors: Lewis Morag A. , Schulte Jennifer , Matthews Lois , Vaden Kenneth I. , Steves Claire J. , Williams Frances M.K. , Schulte Bradley A. , Dubno Judy R. , Steel Karen P. 
Published: April 2023

Adult-onset progressive hearing loss is a common, complex disease with a strong genetic component. Although to date over 150 genes have been identified as contributing to human hearing loss, many more remain to be discovered, as does most of the underlying genetic diversity. Many different variants have been found to underlie adult-onset hearing loss, but they tend to be rare variants with a high impact upon the gene product. It is likely that combinations of more common, lower impact variants also play a role in the prevalence of the disease.Here we present our exome study of hearing loss in a cohort of 532 older adult volunteers with extensive phenotypic data, including 99 older adults with normal hearing, an important control set. Firstly, we carried out an outlier analysis to identify genes with a high variant load in older adults with hearing loss compared to those with normal hearing. Secondly, we used audiometric threshold data to identify individual variants which appear to contribute to different threshold values. We followed up these analyses in a second cohort. Using these approaches, we identified genes and variants linked to better hearing as well as those linked to worse hearing.These analyses identified some known deafness genes, demonstrating proof of principle of our approach. However, most of the candidate genes are novel associations with hearing loss. While the results support the suggestion that genes responsible for severe deafness may also be involved in milder hearing loss, they also suggest that there are many more genes involved in hearing which remain to be identified. Our candidate gene lists may provide useful starting points for improved diagnosis and drug development.
Fossil calibrations for molecular analyses and divergence time estimation for true crabs (Decapoda: Brachyura)
Authors: Luque Javier , Bracken-Grissom Heather D. , Ortega-Hernández Javier , Wolfe Joanna M. 
Published: April 2023

ABSTRACTTrue crabs, or Brachyura, comprise over 7,600 known species and are among the most ecologically dominant, economically significant, and popularly recognized group of extant crustaceans. There are over 3,000 fossil brachyuran species known from mid and upper Jurassic, Cretaceous, and Cenozoic deposits across the globe, many of them preserved in exquisite detail, but the origins and early evolution of true crabs remain unresolved. This uncertainty hinders the identification of the stratigraphically earliest occurrence of major brachyuran groups in the fossil record, obscuring our understanding of their phylogenetic relationships and thus the ability to estimate divergence times to answer large scale macroevolutionary questions. Here, we present 36 vetted fossil node calibration points for molecular phylogenetic analysis of crabs (one Anomura and 35 Brachyura) and reassess the earliest occurrences of several key clades based on recent fossil discoveries or re-examination of previous studies. For each calibrated node, we provide the minimum and tip maximum ages for the stratigraphically oldest fossil that can be reliably assigned to the group. Disentangling the anatomical disparity of fossil forms and their phylogenetic relationships is crucial to recognize the earliest branching members among brachyuran groups. This represents a critical first step understanding the evolution of carcinization and decarcinization in true crabs, the appearance of key adaptations, and the transition from sea to land and freshwater. The identification of reliable fossils for deep time calibrations, both as tips and nodes, is pivotal to ensure not only precise but more accurate divergence time estimations when reconstructing the crab tree of life.PLAIN LANGUAGE SUMMARYWe present 36 vetted fossil calibration points for molecular phylogenetic analysis of crabs (one Anomura and 35 Brachyura) and reassess the earliest occurrences of several key groups based on recent fossil discoveries or re-examination of previous studies, together with discussions for each taxon. We also provide some general observations and recommendations on fossil age selection and stratigraphic considerations. The identification of reliable fossils for deep time calibrations, both as tips and nodes, is pivotal to ensure not only precise but more accurate divergence time estimations when reconstructing phylogenetic trees.
Plasma-free samples for transcriptomic analysis: a potential alternative to whole blood samples
Authors: Chen Qingwang , Guo Xiaorou , Wang Haiyan , Sun Shanyue , Jiang He , Zhang Peipei , Shang Erfei , Zhang Ruolan , Cao Zehui , Niu Quanne , Zhang Chao , Liu Yaqing , Zheng Yuanting , Yu Ying , Hou Wanwan , Shi Leming 
Published: April 2023

AbstractRNA sequencing (RNAseq) technology has become increasingly important in precision medicine and clinical diagnostics and emerged as a powerful tool for identifying protein-coding genes, performing differential gene analysis, and inferring immune cell composition. Human peripheral blood samples are widely used for RNAseq, providing valuable insights into individual biomolecular information. Blood samples can be classified as whole blood (WB), plasma, serum, and remaining sediment samples, including plasma-free blood (PFB) and serum-free blood (SFB) samples. However, the feasibility of using PFB and SFB samples for transcriptome analysis remains unclear. In this study, we aimed to assess the viability of employing PFB or SFB samples as substitute RNA sources in transcriptomic analysis and performed a comparative analysis of WB, PFB, and SFB samples for different applications. Our results revealed that PFB samples exhibit greater similarity to WB samples in terms of protein-coding gene expression patterns, differential expression gene profiling, and immunological characterizations, suggesting that PFB can be a viable alternative for transcriptomic analysis. This contributes to the optimization of blood sample utilization and the advancement of precision medicine research.
A benchmark study on current GWAS models in admixed populations
Authors: Yang Zikun , Huaman Basilio Cieza , Reyes-Dumeyer Dolly , Montesinos Rosa , Soto-Añari Marcio , Custodio Nilton , Tosto Giuseppe 
Published: April 2023

AbstractObjectiveThe performances of popular Genome-wide association study (GWAS) models haven’t been examined yet in a consistent manner under the scenario of genetic admixture, which introduces several challenging aspects such as heterogeneity of minor allele frequency (MAF), a wide spectrum of case-control ratio, and varying effect sizes etc.MethodsWe generated a cohort of synthetic individuals (N=19,234) that simulates 1) a large sample size; 2) two-way admixture [Native American-European ancestry] and 3) a binary phenotype. We then examined the inflation factors produced by three popular GWAS tools: GMMAT, SAIGE, and Tractor. We also computed power calculations under different MAFs, case-control ratios, and varying ancestry percentages. Then, we employed a cohort of Peruvians (N=249) to further examine the performances of the testing models on 1) real genetic data and 2) small sample sizes. Finally, we validated these findings using an independent Peruvian cohort (N=109) included in 1000 Genome project (1000G).ResultIn the synthetic cohort, SAIGE performed better than GMMAT and Tractor in terms of type-I error rate, especially under severe unbalanced case-control ratio. On the contrary, power analysis identified Tractor as the best method to pinpoint ancestry-specific causal variants, but showed decreased power when no adequate heterogeneity of the true effect sizes was simulated between ancestries. The real Peruvian data showed that Tractor is severely affected by small sample sizes, and produced severely inflated statistics, which we replicated in the 1000G Peruvian cohort.DiscussionThe current study illustrates the limitations of available GWAS tools under different scenarios of genetic admixture. We urge caution when interpreting results under complex population scenarios.
Disentangling genetic effects on transcriptional and post-transcriptional gene regulation through integrating exon and intron expression QTLs
Authors: Brümmer Anneke , Bergmann Sven 
Published: April 2023

AbstractExpression quantitative trait loci (eQTL) studies typically consider exon expression of genes and discard intronic RNA sequencing reads despite their information on RNA metabolism. Here, we quantified genetic effects on exon and intron levels of genes and their ratio in lymphoblastoid cell lines, revealing thousands of cis-QTLs of each type. Genetic effects were often shared between cis-QTL types, but 6084 (41%) were not detectable at exon levels. We show that exon levels preferentially capture genetic effects on transcriptional regulation, while exon-intron-ratios better detect those on co- and post-transcriptional processes. Considering all cis-QTL types substantially increased the number of colocalizing GWAS variants (by 61%). It further allowed dissecting the potential gene regulatory processes underlying GWAS associations, suggesting comparable contributions by transcriptional (48%) and co- and post-transcriptional regulation (42%) to complex traits. Overall, integrating intronic RNA sequencing reads in eQTL studies expands our understanding of genetic effects on gene regulatory processes.
5-hydroxymethylcytosine profiling of cell-free DNA identifies bivalent genes that are prognostic of survival in high-risk neuroblastoma
Authors: Chennakesavalu Mohansrinivas , Moore Kelley , Chaves Gepoliano , Veeravalli Sahil , TerHaar Rachel , Wu Tong , Lyu Ruitu , Chlenski Alexandre , He Chuan , Piunti Andrea , Applebaum Mark A. 
Published: April 2023

ABSTRACTNeuroblastoma is the most common extra-cranial solid tumor in childhood and epigenetic dysregulation is a key driver of this embryonal disease. In cell-free DNA from neuroblastoma patients with high-risk disease, we found increased 5-hydroxymethylcytosine (5-hmC) deposition on Polycomb Repressive Complex 2 (PRC2) target genes, a finding previously described in the context of bivalent genes. As bivalent genes, defined as genes bearing both activating (H3K4me3) and repressive (H3K27me3) chromatin modifications, have been shown to play an important role in development and cancer, we investigated the potential role of bivalent genes in maintaining a de-differentiated state in neuroblastoma and their potential use as a biomarker. We identified 313 genes that bore bivalent chromatin marks, were enriched for mediators of neuronal differentiation, and were transcriptionally repressed across a panel of heterogenous neuroblastoma cell lines. Through gene set variance analysis, we developed a clinically implementable bivalent signature. In three distinct clinical cohorts, low bivalent signature was significantly and independently associated with worse clinical outcome in high-risk neuroblastoma patients. Thus, low expression of bivalent genes is a biomarker of ultra-high-risk disease and may represent a therapeutic opportunity in neuroblastoma.
Identification of disease mechanisms and novel disease genes using clinical concept embeddings learned from massive amounts of biomedical data
Authors: Bugrim Andrej 
Published: April 2023

AbstractMotivationKnowledge of relationship and similarity among human diseases can be leveraged in many biomedical applications such as drug repositioning, biomarker discovery, differential diagnostics, and understanding of disease mechanisms. Recently developedcui2vecresource provides embeddings of approximately 109 thousand biomedical terms and allows computing novel measures of disease similarity, directly related to patterns in real-world data. We investigate whether disease embeddings fromcui2veccan be utilized to identify functional relations among diseases, to uncover their molecular mechanisms, and to generate hypotheses about novel gene-disease associations and potential drug targets.Methods and resultsWe focus on a subset of 3,568cui2vecterms corresponding to human diseases annotated in DisGeNET database. Disease-disease distance matrix is computed for this set of diseases based on their embedding vectors. Clustering of this matrix reveals a well-defined structure with good correspondence between disease clusters and the top MeSH disease categories. Using pulmonary embolism as an example we show how disease clustering is related to known mechanistic relations among diseases. Next, we combine disease embeddings with annotated gene-disease associations from DisGeNET to generate joint gene-disease co-embeddings. From these we identify molecular pathways most characteristic for each disease group and show that they are highly relevant to known disease physiology. Finally, we leverage disease similarity to generate and rank hypothesis for gene-disease associations and demonstrate that this method generates highly accurate results and can suggest relevant drug targets.ConclusionsWe show that combination of disease embeddings learned from massive amounts of biomedical records with curated data on gene-disease associations can reliably reveal groups of functionally related diseases and their molecular mechanisms and predict novel gene-disease associations. Importantly, our analysis does not require knowledge of associated genes for every disease to identify patterns in the embedding space, therefore it can be used to suggest mechanisms for conditions that have not been functionally understood. In this respect our analysis can be applied to identify potential markers and drug targets for poorly characterized orphan and rare diseases. It can also reveal unexpected novel connections among diseases and between diseases and molecular pathways.
Inference of population genetics parameters using discriminator neural networks: an adversarial Monte Carlo approach
Authors: Gower Graham , Picazo Pablo Iáñez , Lindgren Finn , Racimo Fernando 
Published: April 2023

AbstractAccurately estimating biological variables of interest, such as parameters of demographic models, is a key problem in evolutionary genetics. Likelihood-based and likelihood-free methods both typically use only limited genetic information, such as carefully chosen summary statistics. Deep convolutional neural networks (CNNs) trained on genotype matrices can incorporate a great deal more information, and have been shown to have high accuracy for inferring parameters such as recombination rates and population sizes, when evaluated using simulations. However these methods are typically framed as regression or classification problems, and it is not straightforward to ensure that the training data adequately model the empirical data on which they are subsequently applied. It has recently been shown that generative adversarial networks (GANs) can be used to iteratively tune parameter values until simulations match a given target dataset. Here, we investigate an adversarial architecture for discriminator-based inference, which iteratively improves the sampling distribution for training the discriminator CNN via Monte Carlo density estimation. We show that this method produces parameter estimates with excellent agreement to simulated data. We developeddinf, a modular Python package for discriminator-based inference that incorporates this method, and is available fromhttps://github.com/RacimoLab/dinf/.
BRCA2-HSF2BP Oligomeric Ring Disassembly by BRME1 Promotes Homologous Recombination
Authors: Ghouil Rania , Miron Simona , Sato Koichi , Ristic Dejan , van Rossum-Fikkert Sari E. , Legrand Pierre , Ouldali Malika , Winter Jean-Marie , Ropars Virginie , David Gabriel , Arteni Ana-Andreea , Wyman Claire , Knipscheer Puck , Kanaar Roland , Zelensky Alex N. , Zinn-Justin Sophie 
Published: April 2023

ABSTRACTIn meiotic homologous recombination (HR), BRCA2 facilitates loading of the recombinases RAD51 and DMC1 at the sites of double-strand breaks. The HSF2BP-BRME1 complex interacts with BRCA2 to support its function in meiotic HR. In somatic cancer cells ectopically producing HSF2BP, DNA damage can trigger HSF2BP-dependent degradation of BRCA2, which prevents HR. Here we show that, upon binding to BRCA2, HSF2BP assembles into a large ring-shaped 24-mer consisting of three interlocked octameric rings. Addition of BRME1 leads to dissociation of this ring structure, and cancels the disruptive effect of HSF2BP on cancer cell resistance to DNA damage. It also prevents BRCA2 degradation during inter-strand DNA crosslink repair inXenopusegg extracts. We propose that the control of HSF2BP-BRCA2 oligomerization by BRME1 ensures timely assembly of the ring complex that concentrates BRCA2 and controls its turnover, thus promoting meiotic HR.
Comparative mitogenomic analysis of subterranean and surface amphipods (Crustacea, Amphipoda) with special reference to the family Crangonyctidae
Authors: Benito Joseph B. , Porter Megan L. , Niemiller Matthew L. 
Published: April 2023

AbstractMitochondrial genomes play important roles in studying genome evolution, phylogenetic analyses, and species identification. Amphipods (Class Malacostraca, Order Amphipoda) are one of the most ecologically diverse crustacean groups occurring in a diverse array of aquatic and terrestrial environments globally, from freshwater streams and lakes to groundwater aquifers and the deep sea, but we have a limited understanding of how habitat influences the molecular evolution of mitochondrial energy metabolism. Subterranean amphipods likely experience different evolutionary pressures on energy management compared to surface-dwelling taxa that generally encounter higher levels of predation and energy resources and live in more variable environments. In this study, we compared the mitogenomes, including the 13 protein-coding genes involved in the oxidative phosphorylation (OXPHOS) pathway, of surface and subterranean amphipods to uncover potentially different molecular signals of energy metabolism between surface and subterranean environments in this diverse crustacean group. We compared base composition, codon usage, gene order rearrangement, conducted comparative mitogenomic and phylogenomic analyses, and examined evolutionary signals of 35 amphipod mitogenomes representing 13 families, with an emphasis on Crangonyctidae. Mitogenome size, AT content, GC-skew, gene order, uncommon start codons, location of putative control region (CR), length ofrrnLand intergenic spacers differed between surface and subterranean amphipods. Among crangonyctid amphipods, the spring-dwellingCrangonyx forbesiexhibited a unique gene order, a longnad5locus, longerrrnLandrrnSloci, and unconventional start codons. Evidence of directional selection was detected in several protein-encoding genes of the OXPHOS pathway in the mitogenomes of surface amphipods, while a signal of purifying selection was more prominent in subterranean species, which is consistent with the hypothesis that the mitogenome of surface-adapted species has evolved in response to a more energy demanding environment compared to subterranean amphipods. Overall, gene order, locations of non-coding regions, and base-substitution rates points to habitat as an important factor influencing the evolution of amphipod mitogenomes.