Down syndrome-recent progress and future prospects

Down syndrome (DS) is caused by trisomy of chromosome 21 (Hsa21) and is associated with a number of deleterious phenotypes, including learning disability, heart defects, early-onset Alzheimer's disease and childhood leukaemia. Individuals with DS are affected by these phenotypes to a variable extent; understanding the cause of this variation is a key challenge. Here, we review recent research progress in DS, both in patients and relevant animal models. In particular, we highlight exciting advances in therapy to improve cognitive function in people with DS and the significant developments in understanding the gene content of Hsa21. Moreover, we discuss future research directions in light of new technologies. In particular, the use of chromosome engineering to generate new trisomic mouse models and large-scale studies of genotype-phenotype relationships in patients are likely to significantly contribute to the future understanding of DS

Spatial correlations in attribute communities

Community detection is an important tool for exploring and classifying the properties of large complex networks and should be of great help for spatial networks. Indeed, in addition to their location, nodes in spatial networks can have attributes such as the language for individuals, or any other socio-economical feature that we would like to identify in communities. We discuss in this paper a crucial aspect which was not considered in previous studies which is the possible existence of correlations between space and attributes. Introducing a simple toy model in which both space and node attributes are considered, we discuss the effect of space-attribute correlations on the results of various community detection methods proposed for spatial networks in this paper and in previous studies. When space is irrelevant, our model is equivalent to the stochastic block model which has been shown to display a detectability-non detectability transition. In the regime where space dominates the link formation process, most methods can fail to recover the communities, an effect which is particularly marked when space-attributes correlations are strong. In this latter case, community detection methods which remove the spatial component of the network can miss a large part of the community structure and can lead to incorrect results.Comment: 10 pages and 7 figure

Comprehensive comparative analysis of strand-specific RNA sequencing methods

Strand-specific, massively parallel cDNA sequencing (RNA-seq) is a powerful tool for transcript discovery, genome annotation and expression profiling. There are multiple published methods for strand-specific RNA-seq, but no consensus exists as to how to choose between them. Here we developed a comprehensive computational pipeline to compare library quality metrics from any RNA-seq method. Using the well-annotated Saccharomyces cerevisiae transcriptome as a benchmark, we compared seven library-construction protocols, including both published and our own methods. We found marked differences in strand specificity, library complexity, evenness and continuity of coverage, agreement with known annotations and accuracy for expression profiling. Weighing each method's performance and ease, we identified the dUTP second-strand marking and the Illumina RNA ligation methods as the leading protocols, with the former benefitting from the current availability of paired-end sequencing. Our analysis provides a comprehensive benchmark, and our computational pipeline is applicable for assessment of future protocols in other organisms.Howard Hughes Medical InstituteUnited States-Israel Binational Science Foundatio

Prominent use of distal 5′ transcription start sites and discovery of a large number of additional exons in ENCODE regions

This report presents systematic empirical annotation of transcript products from 399 annotated protein-coding loci across the 1% of the human genome targeted by the Encyclopedia of DNA elements (ENCODE) pilot project using a combination of 5′ rapid amplification of cDNA ends (RACE) and high-density resolution tiling arrays. We identified previously unannotated and often tissue- or cell-line-specific transcribed fragments (RACEfrags), both 5′ distal to the annotated 5′ terminus and internal to the annotated gene bounds for the vast majority (81.5%) of the tested genes. Half of the distal RACEfrags span large segments of genomic sequences away from the main portion of the coding transcript and often overlap with the upstream-annotated gene(s). Notably, at least 20% of the resultant novel transcripts have changes in their open reading frames (ORFs), most of them fusing ORFs of adjacent transcripts. A significant fraction of distal RACEfrags show expression levels comparable to those of known exons of the same locus, suggesting that they are not part of very minority splice forms. These results have significant implications concerning (1) our current understanding of the architecture of protein-coding genes; (2) our views on locations of regulatory regions in the genome; and (3) the interpretation of sequence polymorphisms mapping to regions hitherto considered to be "noncoding," ultimately relating to the identification of disease-related sequence alterations. ©2007 by Cold Spring Harbor Laboratory Press

Methods to study splicing from high-throughput RNA Sequencing data

The development of novel high-throughput sequencing (HTS) methods for RNA (RNA-Seq) has provided a very powerful mean to study splicing under multiple conditions at unprecedented depth. However, the complexity of the information to be analyzed has turned this into a challenging task. In the last few years, a plethora of tools have been developed, allowing researchers to process RNA-Seq data to study the expression of isoforms and splicing events, and their relative changes under different conditions. We provide an overview of the methods available to study splicing from short RNA-Seq data. We group the methods according to the different questions they address: 1) Assignment of the sequencing reads to their likely gene of origin. This is addressed by methods that map reads to the genome and/or to the available gene annotations. 2) Recovering the sequence of splicing events and isoforms. This is addressed by transcript reconstruction and de novo assembly methods. 3) Quantification of events and isoforms. Either after reconstructing transcripts or using an annotation, many methods estimate the expression level or the relative usage of isoforms and/or events. 4) Providing an isoform or event view of differential splicing or expression. These include methods that compare relative event/isoform abundance or isoform expression across two or more conditions. 5) Visualizing splicing regulation. Various tools facilitate the visualization of the RNA-Seq data in the context of alternative splicing. In this review, we do not describe the specific mathematical models behind each method. Our aim is rather to provide an overview that could serve as an entry point for users who need to decide on a suitable tool for a specific analysis. We also attempt to propose a classification of the tools according to the operations they do, to facilitate the comparison and choice of methods.Comment: 31 pages, 1 figure, 9 tables. Small corrections adde

Early biting and insecticide resistance in the malaria vector Anopheles might compromise the effectiveness of vector control intervention in Southwestern Uganda.

BACKGROUND: Southwestern Uganda has high malaria heterogeneity despite moderate vector control and other interventions. Moreover, the early biting transmission and increased resistance to insecticides might compromise strategies relying on vector control. Consequently, monitoring of vector behaviour and insecticide efficacy is needed to assess the effectiveness of strategies aiming at malaria control. This eventually led to an entomological survey in two villages with high malaria prevalence in this region. METHODS: During rainy, 2011 and dry season 2012, mosquitoes were collected in Engari and Kigorogoro, Kazo subcounty, using human landing collection, morning indoor resting collection, pyrethrum spray collection and larval collection. Circumsporozoite protein of Plasmodium falciparum sporozoites in female Anopheles mosquitoes was detected using ELISA assay. Bioassays to monitor Anopheles resistance to insecticides were performed. RESULTS: Of the 1,021 female Anopheles species captured, 62% (632) were Anopheles funestus and 36% (371) were Anopheles gambiae s.l. The most common species were Anopheles gambiae s.l. in Engari (75%) and A. funestus in Kigorogoro (83%). Overall, P. falciparum prevalence was 2.9% by ELISA. The daily entomological inoculation rates were estimated at 0.17 and 0.58 infected bites/person/night during rainy and dry season respectively in Engari, and 0.81 infected bites/person/night in Kigorogoro during dry season. In both areas and seasons, an unusually early evening biting peak was observed between 6 - 8 p.m. In Engari, insecticide bioassays showed 85%, 34% and 12% resistance to DDT during the rainy season, dry season and to deltamethrin during the dry season, respectively. In Kigorogoro, 13% resistance to DDT and to deltamethrin was recorded. There was no resistance observed to bendiocarb and pirimiphos methyl. CONCLUSIONS: The heterogeneity of mosquito distribution, entomological indicators and resistance to insecticides in villages with high malaria prevalence highlight the need for a long-term vector control programme and monitoring of insecticide resistance in Uganda. The early evening biting habits of Anopheles combined with resistance to DDT and deltamethrin observed in this study suggest that use of impregnated bed nets alone is insufficient as a malaria control strategy, urging the need for additional interventions in this area of high transmission

Population genomics of marine zooplankton

Author Posting. © The Author(s), 2017. This is the author's version of the work. It is posted here for personal use, not for redistribution. The definitive version was published in Bucklin, Ann et al. "Population Genomics of Marine Zooplankton." Population Genomics: Marine Organisms. Ed. Om P. Rajora and Marjorie Oleksiak. Springer, 2018. doi:10.1007/13836_2017_9.The exceptionally large population size and cosmopolitan biogeographic distribution that distinguish many – but not all – marine zooplankton species generate similarly exceptional patterns of population genetic and genomic diversity and structure. The phylogenetic diversity of zooplankton has slowed the application of population genomic approaches, due to lack of genomic resources for closelyrelated species and diversity of genomic architecture, including highly-replicated genomes of many crustaceans. Use of numerous genomic markers, especially single nucleotide polymorphisms (SNPs), is transforming our ability to analyze population genetics and connectivity of marine zooplankton, and providing new understanding and different answers than earlier analyses, which typically used mitochondrial DNA and microsatellite markers. Population genomic approaches have confirmed that, despite high dispersal potential, many zooplankton species exhibit genetic structuring among geographic populations, especially at large ocean-basin scales, and have revealed patterns and pathways of population connectivity that do not always track ocean circulation. Genomic and transcriptomic resources are critically needed to allow further examination of micro-evolution and local adaptation, including identification of genes that show evidence of selection. These new tools will also enable further examination of the significance of small-scale genetic heterogeneity of marine zooplankton, to discriminate genetic “noise” in large and patchy populations from local adaptation to environmental conditions and change.Support was provided by the US National Science Foundation to AB and RJO (PLR-1044982) and to RJO (MCB-1613856); support to IS and MC was provided by Nord University (Norway)

Drug Resistance in Eukaryotic Microorganisms

Eukaryotic microbial pathogens are major contributors to illness and death globally. Although much of their impact can be controlled by drug therapy as with prokaryotic microorganisms, the emergence of drug resistance has threatened these treatment efforts. Here, we discuss the challenges posed by eukaryotic microbial pathogens and how these are similar to, or differ from, the challenges of prokaryotic antibiotic resistance. The therapies used for several major eukaryotic microorganisms are then detailed, and the mechanisms that they have evolved to overcome these therapies are described. The rapid emergence of resistance and the restricted pipeline of new drug therapies pose considerable risks to global health and are particularly acute in the developing world. Nonetheless, we detail how the integration of new technology, biological understanding, epidemiology and evolutionary analysis can help sustain existing therapies, anticipate the emergence of resistance or optimize the deployment of new therapies

Extreme Ultraviolet Beam Enhancement by Relativistic Surface Plasmons

The emission of high-order harmonics in the extreme ultraviolet range from the interaction of a short, intense laser pulse with a grating target is investigated experimentally. When resonantly exciting a surface plasmon, both the intensity and the highest order observed for the harmonic emission along the grating surface increase with respect to a flat target. Harmonics are obtained when a suitable density gradient is preformed at the target surface, demonstrating the possibility to manipulate the grating profile on a nanometric scale without preventing the surface plasmon excitation. In support of this, the harmonic emission is spatiotemporally correlated to the acceleration of multi-MeV electron bunches along the grating surface. Particle-in-cell simulations reproduce the experimental results and give insight on the mechanism of high harmonic generation in the presence of surface plasmons