bluuebunny/crossref_metadata_2025_split huggingface dataset:
Patient-specific functional genomics and disease modeling suggest a role for LRP2 in hypoplastic left heart syndrome
Authors: Theis Jeanne L. , Vogler Georg , Missinato Maria A. , Li Xing , Martinez-Fernandez Almudena , Nielsen Tanja , Walls Stanley M. , Kervadec Anais , Zeng Xin-Xin I , Kezos James N. , Birker Katja , Evans Jared M. , O’Byrne Megan M. , Fogarty Zachary C. , Terzic André , Grossfeld Paul , Ocorr Karen , Nelson Timothy J. , Olson Timothy M. , Colas Alexandre R. , Bodmer Rolf 
Published: November 2019

ABSTRACTCongenital heart diseases (CHD), such as hypoplastic left heart syndrome (HLHS), are considered to have complex genetic underpinnings that are poorly understood. Here, an integrated multi-disciplinary approach was applied to identify novel genes and underlying mechanisms associated with HLHS. A family-based strategy was employed that coupled whole genome sequencing (WGS) with RNA sequencing of patient-derived induced pluripotent stem cells (iPSCs) from a sporadic HLHS proband-parent trio to identify, prioritize and functionally evaluate candidate genes in model systems. Consistent with the hypoplastic phenotype, the proband’s iPSCs had reduced proliferation capacity. Filtering WGS for rare de novo, recessive, and loss-of-function variants revealed 10 candidate genes with recessive variants and altered expression compared to the parents’ iPSCs. siRNA/RNAi-mediated knockdown in generic human iPSC-derived cardiac progenitors and in thein vivo Drosophilaheart model revealed that LDL receptor related proteinLRP2and apolipoproteinAPOBare required for robust hiPSC-derived cardiomyocyte proliferation and normal hear structure and function, possibly involving an oligogenic mechanism via growth-promoting WNT and SHH signaling.LRP2was further validated as a CHD gene in a zebrafish heart model and rare variant burden testing in an HLHS cohort. Collectively, this cross-functional genetic approach to complex congenital heart disease revealed LRP2 dysfunction as a likely novel genetic driver of HLHS, and hereby established a scalable approach to decipher the oligogenic underpinnings of maladaptive left heart development.One sentence summaryWhole genome sequencing and a multi-model system candidate gene validation - human iPSC-derived cardiomyocytes andDrosophilaand zebrafish hearts - identified lipoproteinLRP2as a new potential driver in congenital heart disease and suggests a deficit in proliferation as a hallmark of hypoplastic left heart syndrome.
Mutation severity spectrum of rare alleles in the human genome is predictive of disease type
Authors: Pei Jimin , Kinch Lisa , Grishin Nick V. 
Published: November 2019

AbstractThe human genome harbors a variety of genetic variations. Single-nucleotide changes that alter amino acids in protein-coding regions are one of the major causes of human phenotypic variation and diseases. These single-amino acid variations (SAVs) are routinely found in whole genome and exome sequencing. Evaluating the functional impact of such genomic alterations is crucial for diagnosis of genetic disorders. We developed DeepSAV, a deep-learning convolutional neural network to differentiate disease-causing and benign SAVs based on a variety of protein sequence, structural and functional properties. Our method outperforms most stand-alone programs and has similar predictive power as some of the best available. We transformed DeepSAV scores of rare SAVs observed in the general population into a mutation severity measure of protein-coding genes. This measure reflects a gene’s tolerance to deleterious missense mutations and serves as a useful tool to study gene-disease associations. Genes implicated in cancer, autism, and viral interaction are found by this measure as intolerant to mutations, while genes associated with a number of other diseases are scored as tolerant. Among known disease-associated genes, those that are mutation-intolerant are likely to function in development and signal transduction pathways, while those that are mutation-tolerant tend to encode metabolic and mitochondrial proteins.
A generalizable multivariate brain pattern for interpersonal guilt
Authors: Yu Hongbo , Koban Leonie , Chang Luke J. , Wagner Ullrich , Krishnan Anjali , Vuilleumier Patrik , Zhou Xiaolin , Wager Tor D. 
Published: November 2019

AbstractFeeling guilty when we have wronged another is a crucial aspect of prosociality, but its neurobiological bases are elusive. Although multivariate patterns of brain activity show promise for developing brain measures linked to specific emotions, it is less clear whether brain activity can be trained to detect more complex social emotional states such as guilt. Here, we identified a distributed Guilt-Related Brain Signature (GRBS) across two independent neuroimaging datasets that used interpersonal interactions to evoke guilt. This signature discriminated conditions associated with interpersonal guilt from closely matched control conditions in a cross-validated training sample (N = 24; Chinese population) and in an independent test sample (N = 19; Swiss population). However, it did not respond to observed or experienced pain, or recalled guilt. Moreover, the GRBS only exhibited weak spatial similarity with other brain signatures of social affective processes, further indicating the specificity of the brain state it represents. These findings provide a step towards developing biological markers of social emotions, which could serve as important tools to investigate guilt-related brain processes in both healthy and clinical populations.
FastMulRFS: Fast and accurate species tree estimation under generic gene duplication and loss models
Authors: Molloy Erin K. , Warnow Tandy 
Published: November 2019

AbstractMotivationSpecies tree estimation is a basic part of biological research but can be challenging because of gene duplication and loss (GDL), which results in genes that can appear more than once in a given genome. All common approaches in phylogenomic studies either reduce available data or are error-prone, and thus, scalable methods that do not discard data and have high accuracy on large heterogeneous datasets are needed.ResultsWe present FastMulRFS, a polynomial-time method for estimating species trees without knowledge of orthology. We prove that FastMulRFS is statistically consistent under a generic model of GDL when adversarial GDL does not occur. Our extensive simulation study shows that FastMulRFS matches the accuracy of MulRF (which tries to solve the same optimization problem) and has better accuracy than prior methods, including ASTRAL-multi (the only method to date that has been proven statistically consistent under GDL), while being much faster than both methods.AvailabilityFastMulRFS is available on Github (https://github.com/ekmolloy/fastmulrfs).
Human HMGN1 and HMGN2 are not required for transcription-coupled DNA repair
Authors: Apelt Katja , Zoutendijk Iris , Gout Dennis Y. , van den Heuvel Diana , Luijsterburg Martijn S. 
Published: November 2019

SummaryTranscription-coupled repair (TCR) removes DNA lesions from the transcribed strand of active genes. Stalling of RNA polymerase II (RNAPII) at DNA lesions initiates TCR through the recruitment of the CSB and CSA proteins. The full repertoire of proteins required for human TCR – particularly in a chromatin context - remains to be determined. Studies in mice have revealed that the nucleosome-binding protein HMGN1 is required to enhance the repair of UV-induced lesions in transcribed genes. However, whether HMGN1 is required for human TCR remains unaddressed. Here, we show that knockout or knockdown of HMGN1, either alone or in combination with HMGN2, does not render human cells sensitive to UV light or Illudin S-induced transcription-blocking DNA lesions. Moreover, transcription restart after UV irradiation was not impaired in HMGN-deficient cells. In contrast, TCR-deficient cells were highly sensitive to DNA damage and failed to restart transcription. Furthermore, GFP-tagged HMGN1 was not recruited to sites of UV-induced DNA damage under conditions were GFP-CSB readily accumulated. In line with this, HMGN1 did not associate with the TCR complex, nor did TCR proteins require HMGN1 to associate with DNA damage-stalled RNAPII. Together, our findings suggest that HMGN1 and HMGN2 are not required for human TCR.
On species delimitation, hybridization and population structure of cassava whitefly in Africa
Authors: Elfekih S , Tay WT , Polaszek A , Gordon KHJ , Kunz D , Macfadyen S , Walsh TK , Vyskočilová S , Colvin J , De Barro PJ 
Published: November 2019

AbstractThe Bemisia cassava whitefly complex includes species that cause severe crop damage through vectoring cassava viruses in eastern Africa. Currently, the cassava whitefly complex is divided into species and subgroups based on very limited molecular markers that did not allow clear definition of species and population structure. Based on 14,358 genome-wide SNPs from 63 cassava whitefly individuals belonging to sub-Saharan African (SSA1, SSA2 and SSA4) species, and using a well-curated mtCOI gene database, we show clear incongruities in previous taxonomic approaches underpinned by effects from pseudogenes. We show that the SSA4 species is part of the SSA2 species, and that populations of the SSA1 species comprise of south-eastern (Madagascar, Tanzania) and north-western (Nigeria, Democratic Republic of Congo and Burundi) sub-species that show signatures of allopatric incipient speciation, with a hybrid zone separating these adjacent sub-species. These findings provide the first genomic insights into the evolution and molecular ecology of a highly cryptic hemipteran insect complex in African, and allow the systematic use of genomic data in management and control strategies for this important cassava pest.
An assessment of environmental metabarcoding protocols aiming at favouring contemporary biodiversity in inventories of deep-sea communities
Authors: Brandt Miriam I. , Trouche Blandine , Henry Nicolas , Liautard-Haag Cathy , Maignien Lois , de Vargas Colomban , Wincker Patrick , Poulain Julie , Zeppilli Daniela , Arnaud-Haond Sophie 
Published: November 2019

ABSTRACTThe abyssal seafloor covers more than 50% of planet Earth and is a large reservoir of still mostly undescribed biodiversity. It is increasingly under target of resource-extraction industries although being drastically understudied. In such remote and hard-to-access ecosystems, environmental DNA (eDNA) metabarcoding is a useful and efficient tool for studying biodiversity and implementing environmental impact assessments. Yet, eDNA analysis outcomes may be biased towards describing past rather than present communities as sediments contain both contemporary and ancient DNA.Using commercially available kits, we investigated the impacts of five molecular processing methods on DNA metabarcoding biodiversity inventories targeting prokaryotes (16S-V4V5), unicellular eukaryotes (18S-V4), and metazoans (18S-V1, COI). As the size distribution of ancient DNA is skewed towards small fragments, we evaluated the effect of removing short DNA fragments via size-selection and ethanol reconcentration using DNA extracted from 10 g of sediment at five deep-sea sites. We also compare communities revealed by DNA and RNA co-extracted from 2 g of sediment at the same sites.Results show that removing short DNA fragments does not affect alpha and beta diversity estimates in any of the biological compartments investigated. Results also confirm doubts regarding the possibility to better describe live communities using environmental RNA (eRNA). With ribosomal loci, RNA, while resolving similar spatial patterns than co-extracted DNA, resulted in significantly higher richness estimates, supporting hypotheses of increased persistence of ribosomal RNA (rRNA) in the environment and unmeasured bias due to over-abundance of rRNA and RNA release. With the mitochondrial locus, RNA detected lower metazoan richness and resolved less spatial patterns than co-extracted DNA, reflecting high messenger RNA lability. Results also highlight the importance of using large amounts of sediment (≥10 g) for accurately surveying eukaryotic diversity.We conclude that DNA should be favoured over RNA for logistically realistic, repeatable, and reliable surveys, and confirm that large sediment samples (≥10 g) deliver more complete and accurate assessments of benthic eukaryotic biodiversity and that increasing the number of biological rather than technical replicates is important to infer robust ecological patterns.
Correcting reference bias from the Illumina Isaac aligner enables analysis of cancer genomes
Authors: Cornish Alex J. , Chubb Daniel , Frangou Anna , Hoang Phuc H. , Kaiser Martin , Wedge David C. , Houlston Richard S. 
Published: November 2019

ABSTRACTEstimating the fraction of cancer cells with individual somatic mutations is central to many analyses in cancer genomics, including characterisation of clonal architecture and timing of mutational events. Estimation of these cancer cell fractions (CCFs) is contingent on unbiased assessment of the fraction of reads supporting variant alleles (VAFs). We demonstrate that VAFs computed by the Illumina Isaac pipeline, used in many large-scale sequencing projects including The 100,000 Genomes Project, are biased by the preferential soft clipping of reads supporting non-reference alleles (semi-aligned reads). We show that these biased VAFs can have deleterious effects on downstream analyses reliant on unbiased CCF estimates. While Isaac bias can be corrected through realignment with alternative parameters, this is computationally intensive. We therefore developed FixVAF, a tool for removing bias introduced by soft clipping of semi-aligned reads, facilitating downstream analyses without the need for realignment. FixVAF is freely available at https://github.com/danchubb/FixVAF.Contactalex.cornish@icr.ac.uk or daniel.chubb@icr.ac.uk.
PPanGGOLiN: depicting microbial diversity via a partitioned pangenome graph
Authors: Gautreau Guillaume , Bazin Adelme , Gachet Mathieu , Planel Rémi , Burlot Laura , Dubois Mathieu , Perrin Amandine , Médigue Claudine , Calteau Alexandra , Cruveiller Stéphane , Matias Catherine , Ambroise Christophe , Rocha Eduardo PC , Vallenet David 
Published: November 2019

AbstractThe use of comparative genomics for functional, evolutionary, and epidemiological studies requires methods to classify gene families in terms of occurrence in a given species. These methods usually lack multivariate statistical models to infer the partitions and the optimal number of classes and don’t account for genome organization. We introduce a graph structure to model pangenomes in which nodes represent gene families and edges represent genomic neighborhood. Our method, named PPanGGOLiN, partitions nodes using an Expectation-Maximization algorithm based on multivariate Bernoulli Mixture Model coupled with a Markov Random Field. This approach takes into account the topology of the graph and the presence/absence of genes in pangenomes to classify gene families into persistent, cloud, and one or several shell partitions. By analyzing the partitioned pangenome graphs of isolate genomes from 439 species and metagenome-assembled genomes from 78 species, we demonstrate that our method is effective in estimating the persistent genome. Interestingly, it shows that the shell genome is a key element to understand genome dynamics, presumably because it reflects how genes present at intermediate frequencies drive adaptation of species, and its proportion in genomes is independent of genome size. The graph-based approach proposed by PPanGGOLiN is useful to depict the overall genomic diversity of thousands of strains in a compact structure and provides an effective basis for very large scale comparative genomics. The software is freely available athttps://github.com/labgem/PPanGGOLiN.Author summaryMicroorganisms have the greatest biodiversity and evolutionary history on earth. At the genomic level, it is reflected by a highly variable gene content even among organisms from the same species which explains the ability of microbes to be pathogenic or to grow in specific environments. We developed a new method called PPanGGOLiN which accurately represent the genomic diversity of a species (i.e. its pangenome) using a compact graph structure. Based on this pangenome graph, we classify genes by a statistical method according to their occurrence in the genomes. This method allowed us to build pangenomes even for uncultivated species at an unprecedented scale. We applied our method on all available genomes in databanks in order to depict the overall diversity of hundreds of species. Overall, our work enables microbiologists to explore and visualize pangenomes alike a subway map.
CenH3-independent kinetochore assembly in Lepidoptera requires CENP-T
Authors: Cortes-Silva N , Ulmer J , Kiuchi T , Hsieh E , Cornilleau G , Ladid I , Dingli F , Loew D , Katsuma S , Drinnenberg IA 
Published: November 2019

AbstractAccurate chromosome segregation requires assembly of the multiprotein kinetochore complex at centromeres. In most eukaryotes, kinetochore assembly is primed by the histone H3 variant CenH3, which physically interacts with components of the inner kinetochore constitutive-centromere-associated-network (CCAN). Unexpected to its critical function, previous work identified that select eukaryotic lineages, including several insects, have lost CenH3, while having retained homologs of the CCAN. These findings imply alternative CCAN assembly pathways in these organisms that function in CenH3-independent manners. Here, we study the composition and assembly of CenH3-deficient kinetochores of Lepidoptera (butterflies and moths). We show that lepidopteran kinetochores consist of previously identified CCAN homologs as well as additional components including a divergent CENP-T homolog, which are required for accurate mitotic progression. Our study focuses on CENP-T that we find both necessary and sufficient to recruit the Mis12 outer kinetochore complex. In addition, CRISPR-mediated gene editing inBombyx moriestablishes an essential function of CENP-Tin vivo. Finally, the retention of CENP-T homologs in other independently-derived CenH3-deficient insects indicates a conserved mechanism of kinetochore assembly between these lineages. Our study provides the first functional insights into CCAN-based kinetochore assembly pathways that function independently of CenH3, thus contributing to the emerging picture of an unexpected plasticity to build a kinetochore.
Inhibiting the prostaglandin transporter PGT induces non-canonical thermogenesis at thermoneutrality
Authors: Pai Victor J , Lu Run , Wu Licheng , Macia Marina Garcia , Koba Wade R , Chi Yuling , Singh Rajat , Schwartz Gary J , Schuster Victor L 
Published: November 2019

ABSTRACT / SUMMARYProstaglandins play fundamental roles in adipose tissue function. While prostaglandin F2α inhibits adipogenesis, prostaglandin E2 promotes adipose beiging. PGF2α and PGE2 are both inactivated through uptake by the plasma membrane transporter (PGT). We hypothesized that inhibiting PGT would increase PGF2α and PGE2 levels, thereby reducing white fat expansion and inducing beiging. Consistent with this hypothesis, inhibiting PGT in mice on high fat diet via genetic knockout or pharmacological blockade reduced body fat stores and induced thermogenesis at thermoneutrality. Inguinal white adipose tissue (iWAT) of these mice exhibited robust UCP1-independent thermogenesis characterized by mitochondrial expansion, coupling of O2 consumption to ATP synthesis, and induction of the creatine pathway. Enhanced coupled respiration persisted in PGT-KO iWAT adipocytes in a creatine shuttle-dependent manner. Thus, inhibiting PGT increases mitochondrial biogenesis and coupled respiration—each supported by the creatine pathway in a system lacking UCP1 expression—revealing PGT as a promising drug target against obesity.
Heme synthesis inhibition blocks angiogenesis via mitochondrial dysfunction
Authors: Shetty Trupti , Sishtla Kamakshi , Park Bomina , Repass Matthew J. , Corson Timothy W. 
Published: November 2019

AbstractThe relationship between heme metabolism and angiogenesis is poorly understood. The final synthesis of heme occurs in mitochondria, where ferrochelatase (FECH) inserts Fe2+ into protoporphyrin IX to produce proto-heme IX. We previously showed that FECH inhibition is antiangiogenic in human retinal microvascular endothelial cells (HRECs) and in animal models of ocular neovascularization. In the present study, we sought to understand the mechanism of how FECH and thus heme is involved in endothelial cell function. Mitochondria in endothelial cells had several defects in function after heme inhibition. FECH loss changed the shape and mass of mitochondria and led to significant oxidative stress. Oxidative phosphorylation and mitochondrial Complex IV were decreased in HRECs and in murine retina ex vivo after heme depletion. Supplementation with heme partially rescued phenotypes of FECH blockade. These findings provide an unexpected link between mitochondrial heme metabolism and angiogenesis.Abstract FigureHighlightsHeme synthesis inhibition changes mitochondrial morphology in endothelial cellsLoss of heme causes a buildup of mitochondrial ROS and depolarized membrane potentialEndothelial cells have defective oxidative phosphorylation and glycolysis on loss of hemeMitochondrial damage is caused by loss of functional heme-containing Complex IV and partially restored by exogenous heme