bluuebunny/crossref_metadata_2025_split huggingface dataset:
Single Molecule Sequencing of Cell-free DNA from Maternal Plasma for Noninvasive Trisomy Detection
Authors: Dong Minyue , Deng Liwei , Jin Huan , Cai Jinsen , Shang Huan , Zhang Shuo , Zhang Yueping , Qin Jinzhou , Zhang Dikai , Long Feng , Zhang Renli , Chen Runsheng , Deem Michael W. , Yu Jun , He Jiankui 
Published: October 2017

AbstractThe demand of non-invasive prenatal testing for autosomal aneuploidy using cell-free fetal DNA (cffDNA) in maternal plasma is a highly sought-after diagnostic, with a rapidly growing market. Current approaches developed by next generation sequencing (NGS) need PCR amplifcation during sample preparation, which results in amplification bias in GC-rich areas of the human genome. With these approaches, the minimum fetal fraction in maternal plasma is 4% for the small differences in circulating cfDNA between trisomic and disomic pregnancies to be detectable. In this paper, we performed single molecule sequencing of cell-free DNA from maternal plasma for noninvasive trisomy 13, 18 and 21 detections using the GenoCare platform. We found that single molecule sequencing is sensitive enough to detect these chromosome abnormalities when the fetal DNA fraction is as low as 2%. Compared to the Hiseq2500 platform, no significant GC bias was observed. The improved sensitivity and unbiased GC readout make GenoCare a promising platform for autosomal aneuploidy detections, even in the very early stage of pregnancy.
Molecular insights into the pathways underlying naked mole-rat eusociality
Authors: Mulugeta Eskeatnaf , Marion-Poll Lucile , Gentien David , Ganswindt Stefanie B. , Ganswindt André , Bennett Nigel C. , Blackburn Elizabeth H. , Faulkes Chris G. , Heard Edith 
Published: October 2017

AbstractBackgroundEusociality is the highest level of social organization and naked mole-rats (NMR)s are amongst the few mammals showing this unique social behavior; nevertheless, little is known about the molecular mechanisms underlying the eusociality of NMRs.ResultsGene expression profiling of NMR brain and gonads (ovary and testis), from animals belonging to different reproductive castes, revealed robust gene expression differences between reproductive and non-reproductive members of NMR colonies. In the brain, dopaminergic pathways appear to be potential players in NMR eusocial behaviour. Breeding animals (queens and breeding males) showed increased expression of genes involved in dopamine metabolism. Using immunohistochemistry, we notably found these differences to be in dopaminergic hypothalamic areas, which provide inhibitory control over the secretion of prolactin, amongst other regions. Furthermore, plasma prolactin concentrations were elevated in many non-breeders (of both sexes), often reaching levels exceeding that of pregnant or lactating queens, suggesting a role for hyperprolactinaemia in socially-induced reproductive suppression. We also found that the ovaries of non-breeding females are arrested at pre-pubertal stage. They contained fewer supporting stromal cells compared to queens, and had very low expression of the aromatase geneCyp19A1(a key enzyme in estrogen synthesis) compared to non-breeding females. In the testes, genes involved in post meiosis spermatogenesis and sperm maturation (Prm1, Prm2, Odf3andAkap4) were highly expressed in breeding males compared to non-breeders, explaining the low sperm number and impaired sperm motility characteristic of non-breeding males.ConclusionsOur study suggests that extreme reproductive skew, one of the defining features of eusociality, is associated with changes in expression of key components of dopamine pathways, which could lead to hypogonadism and a lifetime of socially-induced sterility for most NMRs.
A first global phylogeny ofMaize chlorotic mottle virus
Authors: Braidwood Luke A , Quito-Avila Diego F , Cabanas Darlene , Bressan Alberto , Wangai Anne , Baulcombe David C. 
Published: October 2017

ABSTRACTMaize chlorotic mottle virushas been rapidly spreading around the globe over the past decade. The interactions ofMaize chlorotic mottle viruswith potyviridae viruses causes an aggressive synergistic viral condition - maize lethal necrosis, which can cause total yield loss. Maize production in sub-Saharan Africa, where it is the most important cereal, is threatened by the arrival of maize lethal necrosis. We obtainedMaize chlorotic mottle virusgenome sequences from across East Africa and for the first time from Ecuador and Hawaii, and constructed a phylogeny which highlights the similarity of Chinese to African isolates, and Ecuadorian to Hawaiian isolates. We used a measure of clustering, the adjusted Rand index, to extract region-specific SNPs and coding variation that can be used for diagnostics. The population genetics analysis we performed shows that the majority of sequence diversity is partitioned between populations, with diversity extremely low within China and East Africa.
Automated microuidic cell culture of stem cell derived dopaminergic neurons in Parkinson’s disease
Authors: Kane Khalid I.W. , Moreno Edinson Lucumi , Hachi Siham , Walter Moriz , Jarazo Javier , Hankemeier Thomas , Vulto Paul , Schwamborn Jens , Thoma Martin , Fleming Ronan M.T. 
Published: October 2017

AbstractParkinson’s disease is a slowly progressive neurodegenerative disease characterised by dysfunction and death of selectively vulnerable midbrain dopaminergic neurons leading mainly to motor dysfunction, but also other non-motor symptoms. The development of human in vitro cellular models with similar phenotypic characteristics to selectively vulnerable neurons is a major challenge in Parkinson’s disease research. We constructed a fully automated cell culture platform optimised for long-term maintenance and monitoring of induced pluripotent stem cell derived neurons in three dimensional microfluidic cell culture devices. The system can be flexibly adapted to various experimental protocols and features time-lapse imaging microscopy for quality control and electrophysiology monitoring to assess neuronal activity. Using this system, we continuously monitored the differentiation of Parkinson’s disease patient derived human neuroepithelial stem cells into midbrain specific dopaminergic neurons. Calcium imaging confirmed the electrophysiological activity of differentiated neurons and immunostaining confirmed the efficiency of the differentiation protocol. This system is the first example of a fully automated Organ-on-a-Chip culture and enables a versatile array of in vitro experiments for patient-specific disease modelling.
DiscoSnp++: de novo detection of small variants from raw unassembled read set(s)
Authors: Peterlongo Pierre , Riou Chloé , Drezen Erwan , Lemaitre Claire 
Published: October 2017

AbstractMotivationNext Generation Sequencing (NGS) data provide an unprecedented access to life mechanisms. In particular, these data enable to detect polymorphisms such as SNPs and indels. As these polymorphisms represent a fundamental source of information in agronomy, environment or medicine, their detection in NGS data is now a routine task. The main methods for their prediction usually need a reference genome. However, non-model organisms and highly divergent genomes such as in cancer studies are extensively investigated.ResultsWe propose DiscoSnp++, in which we revisit the DiscoSnp algorithm. DiscoSnp++ is designed for detecting and ranking all kinds of SNPs and small indels from raw read set(s). It outputs files in fasta and VCF formats. In particular, predicted variants can be automatically localized afterwards on a reference genome if available. Its usage is extremely simple and its low resource requirements make it usable on common desktop computers. Results show that DiscoSnp++ performs better than state-of-the-art methods in terms of computational resources and in terms of results quality. An important novelty is the de novo detection of indels, for which we obtained 99% precision when calling indels on simulated human datasets and 90% recall on high confident indels from the Platinum dataset.LicenseGNU Affero general public licenseAvailabilityhttps://github.com/GATB/DiscoSnpContactpierre.peterlongo@inria.fr
Fossilized Microbial Forms in Baltic and Goan Amber-A Comparative Pioneer Study
Authors: Sujata Dabolkar , Nandkumar Kamat 
Published: October 2017

AbstractThis paper is based on surveys, exploration and standardization of techniques to recover rare amber samples from sands in Goa and identify specimens embedded with distinct microbial fossils based on studies on reference samples of imported Baltic amber. We developed techniques to locate, detect and identify amber samples in local sand. In this pioneer study, we report presumptive microbial forms such as actinobacteria and fungi in amber samples of Goa throwing light on microbial paleobiodiversity. Baltic amber (Succinate) is fossilized resin belonging to the Eocene period (44-49 million years old) derived from the Araucariaceae and Leguminoseae families of trees containing up to 8% of Succinic acid and compounds such as terpenoids and phenolic derivatives. Sooty moulds in the amber fossils have been studied (Schmidt et al., 2014). Samples of imported Baltic amber were validated, studied and used as reference for identification and characterization of amber found in sand of Goa. FTIR Spectroscopic tests diagnostic of presence of Succinate proved that both samples meet the criteria as plant derived Succinate containing products. Fossil fungi in Baltic amber were observed, and compared with similar forms in rare amber fragments of Goa. These samples were subjected to microscopic examination. Actinobacterial and fungal forms embedded in local amber were compared with similar forms found in imported Baltic amber and those published in literature. Detection of fossilized actinobacterial and fungal forms has shown us the potential for further studies for comprehensive collection and microscopic examination of such paleomicrobial forms in rare local amber samples.
Partial selfing eliminates inbreeding depression while maintaining genetic diversity
Authors: Chelo Ivo M. , Afonso Bruno , Carvalho Sara , Theologidis Ioannis , Goy Christine , Pino-Querido Ania , Proulx Stephen R. , Teotónio Henrique 
Published: October 2017

AbstractClassical theory on the origin and evolution of selfing and outcrossing relies on the role of inbreeding depression created by unlinked partially-deleterious recessive alleles to predict that individuals from natural populations predominantly self or outcross. Comparative data indicates, however, that maintenance of partial selfing and outcrossing at intermediate frequencies is common in nature. In part to explain the presence of mixed reproductive modes within populations, several hypotheses regarding the evolution of inbreeding depression have been put forward based on the complex interaction of linkage and identity disequilibrium among fitness loci, together with Hill-Robertson effects. We here ask what is the genetic basis of inbreeding depression so that populations with intermediate selfing rates can eliminate it while maintain potentially adaptive genetic diversity. For this, we use experimental evolution in the nematodeC. elegansunder partial selfing and compare it to the experimental evolution of populations evolved under exclusive selfing and predominant outcrossing. We find that the ancestral risk of extinction upon enforced inbreeding by selfing is maintained when populations evolve under predominant outcrossing, but reduced when populations evolve under partial or exclusive selfing. Analysis of genome-wide single-nucleotide polymorphism (SNP) during experimental evolution and after enforced inbreeding suggests that, under partial selfing, populations were purged of unlinked deleterious recessive alleles that segregate in the ancestral population, which in turn allowed the expression of unlinked overdominant fitness loci. Taken together, these observations indicate that populations evolving under partial selfing gain the short-term benefits of selfing, in purging deleterious recessive alleles, but also the long-term benefits of outcrossing, in maintaining genetic diversity that may important for future adaptation.
Evolution of cold acclimation in temperate grasses (Pooideae)
Authors: Schubert Marian , Grønvold Lars , Sandve Simen R. , Hvidsten Torgeir R. , Fjellheim Siri 
Published: October 2017

AbstractIn the past 50 million years climate cooling has triggered the expansion of temperate biomes. During this period, many extant plant lineages in temperate biomes evolved from tropical ancestors and adapted to seasonality and cool conditions. Among the Poaceae (grass family), one of the subfamilies that successfully shifted from tropical to temperate biomes is the Pooideae (temperate grasses). Subfamily Pooideae contains the most important crops cultivated in the temperate regions including wheat (Triticum aestivum) and barley (Hordeum vulgare). Due to the need of well-adapted cultivars, extensive research has produced a large body of knowledge about the mechanisms underlying cold adaptation in cultivated Pooideae species. Especially cold acclimation, a process which increases the frost tolerance during a period of non-freezing cold, plays an important role. Because cold adaptation is largely unexplored in lineages that diverged early in the evolution of the Pooideae, little is known about the evolutionary history of cold acclimation in the Pooideae. Here we test if several species of early diverging lineages exhibit increased frost tolerance after a period of cold acclimation. We further investigate the conservation of five well-studied gene families that are known to be involved in the cold acclimation of Pooideae crop species. Our results indicate that cold acclimation exists in early diverging lineages, but that genes involved in regulation of cold acclimation are not conserved. The investigated gene families show signs of lineage-specific evolution and support the hypothesis that gene family expansion is an important mechanism in adaptive evolution.
Assigning enzyme sequences to orphan and novel reactions using knowledge of substrate reactive sites
Authors: Hadadi Noushin , MohamadiPeyhani Homa , Miskovic Ljubisa , Seijo Marianne , Hatzimanikatis Vassily 
Published: October 2017

ABSTRACTThousands of biochemical reactions with characterized activities are orphan, meaning they cannot be assigned to a specific enzyme, leaving gaps in metabolic pathways. Novel reactions predicted by pathway-generation tools also lack associated sequences, limiting protein engineering applications. Associating orphan and novel reactions with known biochemistry and suggesting enzymes to catalyze them is a daunting problem. We propose a new method, BridgIT, to identify candidate genes and protein sequences for these reactions, and this method introduces, for the first time, information about the enzyme binding pocket into reaction similarity comparisons. BridgIT assesses the similarity of two reactions, one orphan and one well-characterized, nonorphan reaction, using their substrate reactive sites, their surrounding structures, and the structures of the generated products to suggest protein sequences and genes that catalyze the most similar non-orphan reactions as candidates for also catalyzing the orphan ones.We performed two large-scale validation studies to test BridgIT predictions against experimental biochemical evidence. For the 234 orphan reactions from KEGG 2011 (a comprehensive enzymatic reaction database) that became non-orphan in KEGG 2018, BridgIT predicted the exact or a highly related enzyme for 211 of them. Moreover, for 334 out of 379 novel reactions in 2014 that were later catalogued in KEGG 2018, BridgIT predicted the exact or highly similar enzyme sequences.BridgIT requires knowledge about only three connecting bonds around the atoms of the reactive sites to correctly identify protein sequences for 93% of analyzed enzymatic reactions. Increasing to six connecting bonds allowed for the accurate identification of a sequence for nearly all known enzymatic reactions.SIGNIFICANCE STATEMENTRecent advances in synthetic biochemistry have resulted in a wealth of novel hypothetical enzymatic reactions that are not matched to protein-encoding genes, deeming them “orphan”. Nearly half of known metabolic enzymes are also orphan, leaving important gaps in metabolic network maps. Proposing genes for the catalysis of orphan reactions is critical for applications ranging from biotechnology to medicine. In this work, a novel computational method, BridgIT, identified a potential enzyme sequence to orphan reactions and nearly all theoretically possible biochemical transformations, providing candidate genes to catalyze these reactions to the research community. BridgIT online tool will allow researchers to fill the knowledge gaps in metabolic networks and will act as a starting point for designing novel enzymes to catalyze non-natural transformations.
Modeling the growth and decline of pathogen effective population size provides insight into epidemic dynamics and drivers of antimicrobial resistance
Authors: Volz Erik M. , Didelot Xavier 
Published: October 2017

AbstractNon-parametric population genetic modeling provides a simple and flexible approach for studying demographic history and epidemic dynamics using pathogen sequence data. Existing Bayesian approaches are premised on stationary stochastic processes which may provide an unrealistic prior for epidemic histories which feature extended period of exponential growth or decline. We show that non-parametric models defined in terms of the growth rate of the effective population size can provide a more realistic prior for epidemic history. We propose a non-parametric autoregressive model on the growth rate as a prior for effective population size, which corresponds to the dynamics expected under many epidemic situations. We demonstrate the use of this model within a Bayesian phylodynamic inference framework. Our method correctly reconstructs trends of epidemic growth and decline from pathogen genealogies even when genealogical data is sparse and conventional skyline estimators erroneously predict stable population size. We also propose a regression approach for relating growth rates of pathogen effective population size and time-varying variables that may impact the replicative fitness of a pathogen. The model is applied to real data from rabies virus andStaphylococcus aureusepidemics. We find a close correspondence between the estimated growth rates of a lineage of methicillin-resistantS. aureusand population-level prescription rates ofβ-lactam antibiotics. The new models are implemented in an open source R package calledskygrowthwhich is available athttps://mrc-ide.github.io/skygrowth/.
Forest Dormouse (Dryomys nitedula) populations in southern Italy belong to a deeply divergent evolutionary lineage
Authors: Bisconti R. , Aloise G. , Siclari A. , Fava V. , Provenzano M , Arduino P. , Chiocchio A. , Nascetti G. , Canestrelli D. 
Published: October 2017

AbstractThe Forest Dormouse (Dryomys nitedula) is a small rodent with a wide, albeit severely fragmented distribution, ranging from central Europe to central Asia. Within the Italian region,D. nitedulapopulations are restricted to forested mountain areas of two largely disconnected regions, the eastern Alps and the Calabria region, where two distinct subspecies (D. nitedula intermediusandD. nitedula aspromontis, respectively) have been described on the basis of phenotypic characters (i.e., fur colour). Here we analysedD. nitedulasamples from both regions, to investigate patterns of genetic divergence and phylogenetic relationship among these two populations. Genetic variation was studied at the level of one mitochondrial (cytochrome b gene) and three nuclear gene fragments (exon1 of the interstitial retinoid-binding protein, exon 10 of the growth hormone receptor, and recombination activating gene 1). Phylogenetic analyses were performed using Maximum Likelihood and Bayesian inference methods.D. n. aspromontisandD. n. intermediuswere found to be reciprocally monophyletic in all the phylogenetic analyses, and the genetic divergence observed between them at the mitochondrialCYTBgene was conspicuous (HKY: 0.044) when compared to previously observed values among many sister species of rodents. Our results clearly show thatD. nitedula aspromontisis a deeply divergent, narrow endemic evolutionary lineage, and its conservation needs should be carefully evaluated in the near future. Moreover, such deep genetic divergence, together with phenotypic differentiation betweenD. n. intermediusandD. n. aspromontis,suggest thatD. nitedulapopulations in southern Italy might belong to a distinct, previously unrecognized species.
Spatial sorting as the spatial analogue of natural selection
Authors: Phillips Ben L. , Perkins T. Alex 
Published: October 2017

AbstractIn most systems, dispersal occurs despite clear fitness costs to dispersing individuals. Theory posits that spatial heterogeneity in habitat quality pushes dispersal rates to evolve towards zero, while temporal heterogeneity in habitat quality favours non-zero dispersal rates. One aspect of dispersal evolution that has received a great deal of recent attention is a process known as spatial sorting, which has been referred to as a “shy younger sibling” of natural selection. More precisely, spatial sorting is the process whereby variation in dispersal ability is sorted along density clines and will, in nature, often be a transient phenomenon. Despite this transience, spatial sorting is likely a general mechanism behind non-zero dispersal in spatiotemporally varying environments. While generally transient, spatial sorting is persistent on invasion fronts, where its effect cannot be ignored, causing rapid evolution of traits related to dispersal. Spatial sorting is described in several elegant models, yet these models require a high level of mathematical sophistication and are not accessible to most evolutionary biologists or their students. Here, we frame spatial sorting in terms of the classic haploid and diploid models of natural selection. We show that, on an invasion front, spatial sorting can be conceptualized precisely as selection operating through space rather than (as with natural selection) time, and that genotypes can be viewed as having both spatial and temporal aspects of fitness. The resultant model is strikingly similar to classic models of natural selection. This similarity renders the model easy to understand (and to teach), but also suggests that many established theoretical results around natural selection could apply equally to spatial sorting.