<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Peña-Chilet, Maria</style></author><author><style face="normal" font="default" size="100%">Roldán, Gema</style></author><author><style face="normal" font="default" size="100%">Perez-Florido, Javier</style></author><author><style face="normal" font="default" size="100%">Ortuno, Francisco M</style></author><author><style face="normal" font="default" size="100%">Carmona, Rosario</style></author><author><style face="normal" font="default" size="100%">Aquino, Virginia</style></author><author><style face="normal" font="default" size="100%">López-López, Daniel</style></author><author><style face="normal" font="default" size="100%">Loucera, Carlos</style></author><author><style face="normal" font="default" size="100%">Fernandez-Rueda, Jose L</style></author><author><style face="normal" font="default" size="100%">Gallego, Asunción</style></author><author><style face="normal" font="default" size="100%">Garcia-Garcia, Francisco</style></author><author><style face="normal" font="default" size="100%">González-Neira, Anna</style></author><author><style face="normal" font="default" size="100%">Pita, Guillermo</style></author><author><style face="normal" font="default" size="100%">Núñez-Torres, Rocío</style></author><author><style face="normal" font="default" size="100%">Santoyo-López, Javier</style></author><author><style face="normal" font="default" size="100%">Ayuso, Carmen</style></author><author><style face="normal" font="default" size="100%">Minguez, Pablo</style></author><author><style face="normal" font="default" size="100%">Avila-Fernandez, Almudena</style></author><author><style face="normal" font="default" size="100%">Corton, Marta</style></author><author><style face="normal" font="default" size="100%">Moreno-Pelayo, Miguel Ángel</style></author><author><style face="normal" font="default" size="100%">Morin, Matías</style></author><author><style face="normal" font="default" size="100%">Gallego-Martinez, Alvaro</style></author><author><style face="normal" font="default" size="100%">Lopez-Escamez, Jose A</style></author><author><style face="normal" font="default" size="100%">Borrego, Salud</style></author><author><style face="normal" font="default" size="100%">Antiňolo, Guillermo</style></author><author><style face="normal" font="default" size="100%">Amigo, Jorge</style></author><author><style face="normal" font="default" size="100%">Salgado-Garrido, Josefa</style></author><author><style face="normal" font="default" size="100%">Pasalodos-Sanchez, Sara</style></author><author><style face="normal" font="default" size="100%">Morte, Beatriz</style></author><author><style face="normal" font="default" size="100%">Carracedo, Ángel</style></author><author><style face="normal" font="default" size="100%">Alonso, Ángel</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">Spanish Exome Crowdsourcing Consortium</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">CSVS, a crowdsourcing database of the Spanish population genetic variability.</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Alleles</style></keyword><keyword><style  face="normal" font="default" size="100%">Chromosome Mapping</style></keyword><keyword><style  face="normal" font="default" size="100%">Crowdsourcing</style></keyword><keyword><style  face="normal" font="default" size="100%">Databases, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Exome</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Frequency</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetics, Population</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">Genomics</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Internet</style></keyword><keyword><style  face="normal" font="default" size="100%">Precision Medicine</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword><keyword><style  face="normal" font="default" size="100%">Spain</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2021 01 08</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">49</style></volume><pages><style face="normal" font="default" size="100%">D1130-D1137</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The knowledge of the genetic variability of the local population is of utmost importance in personalized medicine and has been revealed as a critical factor for the discovery of new disease variants. Here, we present the Collaborative Spanish Variability Server (CSVS), which currently contains more than 2000 genomes and exomes of unrelated Spanish individuals. This database has been generated in a collaborative crowdsourcing effort collecting sequencing data produced by local genomic projects and for other purposes. Sequences have been grouped by ICD10 upper categories. A web interface allows querying the database removing one or more ICD10 categories. In this way, aggregated counts of allele frequencies of the pseudo-control Spanish population can be obtained for diseases belonging to the category removed. Interestingly, in addition to pseudo-control studies, some population studies can be made, as, for example, prevalence of pharmacogenomic variants, etc. In addition, this genomic data has been used to define the first Spanish Genome Reference Panel (SGRP1.0) for imputation. This is the first local repository of variability entirely produced by a crowdsourcing effort and constitutes an example for future initiatives to characterize local variability worldwide. CSVS is also part of the GA4GH Beacon network. CSVS can be accessed at: http://csvs.babelomics.org/.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">D1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32990755?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Joaquín Dopazo</style></author><author><style face="normal" font="default" size="100%">Amadoz, Alicia</style></author><author><style face="normal" font="default" size="100%">Bleda, Marta</style></author><author><style face="normal" font="default" size="100%">García-Alonso, Luz</style></author><author><style face="normal" font="default" size="100%">Alemán, Alejandro</style></author><author><style face="normal" font="default" size="100%">Garcia-Garcia, Francisco</style></author><author><style face="normal" font="default" size="100%">Rodriguez, Juan A</style></author><author><style face="normal" font="default" size="100%">Daub, Josephine T</style></author><author><style face="normal" font="default" size="100%">Muntané, Gerard</style></author><author><style face="normal" font="default" size="100%">Antonio Rueda</style></author><author><style face="normal" font="default" size="100%">Vela-Boza, Alicia</style></author><author><style face="normal" font="default" size="100%">López-Domingo, Francisco J</style></author><author><style face="normal" font="default" size="100%">Florido, Javier P</style></author><author><style face="normal" font="default" size="100%">Arce, Pablo</style></author><author><style face="normal" font="default" size="100%">Ruiz-Ferrer, Macarena</style></author><author><style face="normal" font="default" size="100%">Méndez-Vidal, Cristina</style></author><author><style face="normal" font="default" size="100%">Arnold, Todd E</style></author><author><style face="normal" font="default" size="100%">Spleiss, Olivia</style></author><author><style face="normal" font="default" size="100%">Alvarez-Tejado, Miguel</style></author><author><style face="normal" font="default" size="100%">Navarro, Arcadi</style></author><author><style face="normal" font="default" size="100%">Bhattacharya, Shomi S</style></author><author><style face="normal" font="default" size="100%">Borrego, Salud</style></author><author><style face="normal" font="default" size="100%">Santoyo-López, Javier</style></author><author><style face="normal" font="default" size="100%">Antiňolo, Guillermo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">267 Spanish exomes reveal population-specific differences in disease-related genetic variation.</style></title><secondary-title><style face="normal" font="default" size="100%">Molecular biology and evolution</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">disease</style></keyword><keyword><style  face="normal" font="default" size="100%">NGS</style></keyword><keyword><style  face="normal" font="default" size="100%">polymorphisms</style></keyword><keyword><style  face="normal" font="default" size="100%">Population genomics</style></keyword><keyword><style  face="normal" font="default" size="100%">prioritization</style></keyword><keyword><style  face="normal" font="default" size="100%">SNP</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2016 Jan 13</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://mbe.oxfordjournals.org/content/early/2016/02/17/molbev.msw005.full</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Recent results from large-scale genomic projects suggest that allele frequencies, which are highly relevant for medical purposes, differ considerably across different populations. The need for a detailed catalogue of local variability motivated the whole exome sequencing of 267 unrelated individuals, representative of the healthy Spanish population. Like in other studies, a considerable number of rare variants were found (almost one third of the described variants). There were also relevant differences in allelic frequencies in polymorphic variants, including about 10,000 polymorphisms private to the Spanish population. The allelic frequencies of variants conferring susceptibility to complex diseases (including cancer, schizophrenia, Alzheimer disease, type 2 diabetes and other pathologies) were overall similar to those of other populations. However, the trend is the opposite for variants linked to Mendelian and rare diseases (including several retinal degenerative dystrophies and cardiomyopathies) that show marked frequency differences between populations. Interestingly, a correspondence between differences in allelic frequencies and disease prevalence was found, highlighting the relevance of frequency differences in disease risk. These differences are also observed in variants that disrupt known drug binding sites, suggesting an important role for local variability in population-specific drug resistances or adverse effects. We have made the Spanish population variant server web page that contains population frequency information for the complete list of 170,888 variant positions we found publicly available (http://spv.babelomics.org/), We show that it if fundamental to determine population-specific variant frequencies in order to distinguish real disease associations from population-specific polymorphisms.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lagarde, Julien</style></author><author><style face="normal" font="default" size="100%">Uszczynska-Ratajczak, Barbara</style></author><author><style face="normal" font="default" size="100%">Santoyo-López, Javier</style></author><author><style face="normal" font="default" size="100%">Gonzalez, Jose Manuel</style></author><author><style face="normal" font="default" size="100%">Tapanari, Electra</style></author><author><style face="normal" font="default" size="100%">Mudge, Jonathan M</style></author><author><style face="normal" font="default" size="100%">Steward, Charles A</style></author><author><style face="normal" font="default" size="100%">Wilming, Laurens</style></author><author><style face="normal" font="default" size="100%">Tanzer, Andrea</style></author><author><style face="normal" font="default" size="100%">Howald, Cédric</style></author><author><style face="normal" font="default" size="100%">Chrast, Jacqueline</style></author><author><style face="normal" font="default" size="100%">Vela-Boza, Alicia</style></author><author><style face="normal" font="default" size="100%">Antonio Rueda</style></author><author><style face="normal" font="default" size="100%">López-Domingo, Francisco J</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Reymond, Alexandre</style></author><author><style face="normal" font="default" size="100%">Guigó, Roderic</style></author><author><style face="normal" font="default" size="100%">Harrow, Jennifer</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Extension of human lncRNA transcripts by RACE coupled with long-read high-throughput sequencing (RACE-Seq).</style></title><secondary-title><style face="normal" font="default" size="100%">Nature communications</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2016</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.nature.com/articles/ncomms12339</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">7</style></volume><pages><style face="normal" font="default" size="100%">12339</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Long non-coding RNAs (lncRNAs) constitute a large, yet mostly uncharacterized fraction of the mammalian transcriptome. Such characterization requires a comprehensive, high-quality annotation of their gene structure and boundaries, which is currently lacking. Here we describe RACE-Seq, an experimental workflow designed to address this based on RACE (rapid amplification of cDNA ends) and long-read RNA sequencing. We apply RACE-Seq to 398 human lncRNA genes in seven tissues, leading to the discovery of 2,556 on-target, novel transcripts. About 60% of the targeted loci are extended in either 5’ or 3’, often reaching genomic hallmarks of gene boundaries. Analysis of the novel transcripts suggests that lncRNAs are as long, have as many exons and undergo as much alternative splicing as protein-coding genes, contrary to current assumptions. Overall, we show that RACE-Seq is an effective tool to annotate an organism’s deep transcriptome, and compares favourably to other targeted sequencing techniques.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lagarde, Julien</style></author><author><style face="normal" font="default" size="100%">Uszczynska-Ratajczak, Barbara</style></author><author><style face="normal" font="default" size="100%">Santoyo-López, Javier</style></author><author><style face="normal" font="default" size="100%">Gonzalez, Jose Manuel</style></author><author><style face="normal" font="default" size="100%">Tapanari, Electra</style></author><author><style face="normal" font="default" size="100%">Mudge, Jonathan M.</style></author><author><style face="normal" font="default" size="100%">Steward, Charles A.</style></author><author><style face="normal" font="default" size="100%">Wilming, Laurens</style></author><author><style face="normal" font="default" size="100%">Tanzer, Andrea</style></author><author><style face="normal" font="default" size="100%">Howald, Cédric</style></author><author><style face="normal" font="default" size="100%">Chrast, Jacqueline</style></author><author><style face="normal" font="default" size="100%">Vela-Boza, Alicia</style></author><author><style face="normal" font="default" size="100%">Rueda, Antonio</style></author><author><style face="normal" font="default" size="100%">Lopez-Domingo, Francisco J.</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Reymond, Alexandre</style></author><author><style face="normal" font="default" size="100%">Guigó, Roderic</style></author><author><style face="normal" font="default" size="100%">Harrow, Jennifer</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Extension of human lncRNA transcripts by RACE coupled with long-read high-throughput sequencing (RACE-Seq)</style></title><secondary-title><style face="normal" font="default" size="100%">Nature Communications</style></secondary-title><short-title><style face="normal" font="default" size="100%">Nat Commun</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan-11-2016</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.nature.com/articles/ncomms12339http://www.nature.com/articles/ncomms12339.pdfhttp://www.nature.com/articles/ncomms12339.pdfhttp://www.nature.com/articles/ncomms12339</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">7</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">1</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Munro, Sarah A</style></author><author><style face="normal" font="default" size="100%">Lund, Steven P</style></author><author><style face="normal" font="default" size="100%">Pine, P Scott</style></author><author><style face="normal" font="default" size="100%">Binder, Hans</style></author><author><style face="normal" font="default" size="100%">Clevert, Djork-Arné</style></author><author><style face="normal" font="default" size="100%">Ana Conesa</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Fasold, Mario</style></author><author><style face="normal" font="default" size="100%">Hochreiter, Sepp</style></author><author><style face="normal" font="default" size="100%">Hong, Huixiao</style></author><author><style face="normal" font="default" size="100%">Jafari, Nadereh</style></author><author><style face="normal" font="default" size="100%">Kreil, David P</style></author><author><style face="normal" font="default" size="100%">Labaj, Paweł P</style></author><author><style face="normal" font="default" size="100%">Li, Sheng</style></author><author><style face="normal" font="default" size="100%">Liao, Yang</style></author><author><style face="normal" font="default" size="100%">Lin, Simon M</style></author><author><style face="normal" font="default" size="100%">Meehan, Joseph</style></author><author><style face="normal" font="default" size="100%">Mason, Christopher E</style></author><author><style face="normal" font="default" size="100%">Santoyo-López, Javier</style></author><author><style face="normal" font="default" size="100%">Setterquist, Robert A</style></author><author><style face="normal" font="default" size="100%">Shi, Leming</style></author><author><style face="normal" font="default" size="100%">Shi, Wei</style></author><author><style face="normal" font="default" size="100%">Smyth, Gordon K</style></author><author><style face="normal" font="default" size="100%">Stralis-Pavese, Nancy</style></author><author><style face="normal" font="default" size="100%">Su, Zhenqiang</style></author><author><style face="normal" font="default" size="100%">Tong, Weida</style></author><author><style face="normal" font="default" size="100%">Wang, Charles</style></author><author><style face="normal" font="default" size="100%">Wang, Jian</style></author><author><style face="normal" font="default" size="100%">Xu, Joshua</style></author><author><style face="normal" font="default" size="100%">Ye, Zhan</style></author><author><style face="normal" font="default" size="100%">Yang, Yong</style></author><author><style face="normal" font="default" size="100%">Yu, Ying</style></author><author><style face="normal" font="default" size="100%">Salit, Marc</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Assessing technical performance in differential gene expression experiments with external spike-in RNA control ratio mixtures.</style></title><secondary-title><style face="normal" font="default" size="100%">Nature communications</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">RNA-seq</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2014</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.nature.com/ncomms/2014/140925/ncomms6125/full/ncomms6125.html</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">5</style></volume><pages><style face="normal" font="default" size="100%">5125</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">There is a critical need for standard approaches to assess, report and compare the technical performance of genome-scale differential gene expression experiments. Here we assess technical performance with a proposed standard ’dashboard’ of metrics derived from analysis of external spike-in RNA control ratio mixtures. These control ratio mixtures with defined abundance ratios enable assessment of diagnostic performance of differentially expressed transcript lists, limit of detection of ratio (LODR) estimates and expression ratio variability and measurement bias. The performance metrics suite is applicable to analysis of a typical experiment, and here we also apply these metrics to evaluate technical performance among laboratories. An interlaboratory study using identical samples shared among 12 laboratories with three different measurement processes demonstrates generally consistent diagnostic power across 11 laboratories. Ratio measurement variability and bias are also comparable among laboratories for the same measurement process. We observe different biases for measurement processes using different mRNA-enrichment protocols.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">González-del Pozo, María</style></author><author><style face="normal" font="default" size="100%">Méndez-Vidal, Cristina</style></author><author><style face="normal" font="default" size="100%">Santoyo-López, Javier</style></author><author><style face="normal" font="default" size="100%">Vela-Boza, Alicia</style></author><author><style face="normal" font="default" size="100%">Nereida Bravo-Gil</style></author><author><style face="normal" font="default" size="100%">Antonio Rueda</style></author><author><style face="normal" font="default" size="100%">García-Alonso, Luz</style></author><author><style face="normal" font="default" size="100%">Vázquez-Marouschek, Carmen</style></author><author><style face="normal" font="default" size="100%">Joaquín Dopazo</style></author><author><style face="normal" font="default" size="100%">Borrego, Salud</style></author><author><style face="normal" font="default" size="100%">Antiňolo, Guillermo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Deciphering intrafamilial phenotypic variability by exome sequencing in a Bardet–Biedl family</style></title><secondary-title><style face="normal" font="default" size="100%">Molecular Genetics &amp; Genomic Medicine</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://onlinelibrary.wiley.com/doi/10.1002/mgg3.50/full</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">2</style></volume><pages><style face="normal" font="default" size="100%">124-133</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Bardet–Biedl syndrome (BBS) is a model ciliopathy characterized by a wide range of clinical variability. The heterogeneity of this condition is reflected in the number of underlying gene defects and the epistatic interactions between the proteins encoded. BBS is generally inherited in an autosomal recessive trait. However, in some families, mutations across different loci interact to modulate the expressivity of the phenotype. In order to investigate the magnitude of epistasis in one BBS family with remarkable intrafamilial phenotypic variability, we designed an exome sequencing–based approach using SOLID 5500xl platform. This strategy allowed the reliable detection of the primary causal mutations in our family consisting of two novel compound heterozygous mutations in McKusick–Kaufman syndrome (MKKS) gene (p.D90G and p.V396F). Additionally, exome sequencing enabled the detection of one novel heterozygous NPHP4 variant which is predicted to activate a cryptic acceptor splice site and is only present in the most severely affected patient. Here, we provide an exome sequencing analysis of a BBS family and show the potential utility of this tool, in combination with network analysis, to detect disease-causing mutations and second-site modifiers. Our data demonstrate how next-generation sequencing (NGS) can facilitate the dissection of epistatic phenomena, and shed light on the genetic basis of phenotypic variability.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">González-del Pozo, María</style></author><author><style face="normal" font="default" size="100%">Méndez-Vidal, Cristina</style></author><author><style face="normal" font="default" size="100%">Santoyo-López, Javier</style></author><author><style face="normal" font="default" size="100%">Vela-Boza, Alicia</style></author><author><style face="normal" font="default" size="100%">Bravo-Gil, Nereida</style></author><author><style face="normal" font="default" size="100%">Rueda, Antonio</style></author><author><style face="normal" font="default" size="100%">García-Alonso, Luz</style></author><author><style face="normal" font="default" size="100%">Vázquez-Marouschek, Carmen</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Borrego, Salud</style></author><author><style face="normal" font="default" size="100%">Antiňolo, Guillermo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Deciphering intrafamilial phenotypic variability by exome sequencing in a Bardet-Biedl family.</style></title><secondary-title><style face="normal" font="default" size="100%">Mol Genet Genomic Med</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Mol Genet Genomic Med</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2014 Mar</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">2</style></volume><pages><style face="normal" font="default" size="100%">124-33</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Bardet-Biedl syndrome (BBS) is a model ciliopathy characterized by a wide range of clinical variability. The heterogeneity of this condition is reflected in the number of underlying gene defects and the epistatic interactions between the proteins encoded. BBS is generally inherited in an autosomal recessive trait. However, in some families, mutations across different loci interact to modulate the expressivity of the phenotype. In order to investigate the magnitude of epistasis in one BBS family with remarkable intrafamilial phenotypic variability, we designed an exome sequencing-based approach using SOLID 5500xl platform. This strategy allowed the reliable detection of the primary causal mutations in our family consisting of two novel compound heterozygous mutations in McKusick-Kaufman syndrome (MKKS) gene (p.D90G and p.V396F). Additionally, exome sequencing enabled the detection of one novel heterozygous NPHP4 variant which is predicted to activate a cryptic acceptor splice site and is only present in the most severely affected patient. Here, we provide an exome sequencing analysis of a BBS family and show the potential utility of this tool, in combination with network analysis, to detect disease-causing mutations and second-site modifiers. Our data demonstrate how next-generation sequencing (NGS) can facilitate the dissection of epistatic phenomena, and shed light on the genetic basis of phenotypic variability. &lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/24689075?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">López-Domingo, Francisco J</style></author><author><style face="normal" font="default" size="100%">Florido, Javier P</style></author><author><style face="normal" font="default" size="100%">Rueda, Antonio</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Santoyo-López, Javier</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">ngsCAT: a tool to assess the efficiency of targeted enrichment sequencing.</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Bioinformatics</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Exome</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">High-Throughput Nucleotide Sequencing</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, DNA</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2014 Jun 15</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">30</style></volume><pages><style face="normal" font="default" size="100%">1767-8</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;MOTIVATION: &lt;/b&gt;Targeted enrichment sequencing by next-generation sequencing is a common approach to interrogate specific loci or the whole exome in the human genome. The efficiency and the lack of bias in the enrichment process need to be assessed as a quality control step before performing downstream analysis of the sequence data. Tools that can report on the sensitivity, specificity, uniformity and other enrichment-specific features are needed.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;We have implemented the next-generation sequencing data Capture Assessment Tool (ngsCAT), a tool that takes the information of the mapped reads and the coordinates of the targeted regions as input files, and generates a report with metrics and figures that allows the evaluation of the efficiency of the enrichment process. The tool can also take as input the information of two samples allowing the comparison of two different experiments.&lt;/p&gt;&lt;p&gt;&lt;b&gt;AVAILABILITY AND IMPLEMENTATION: &lt;/b&gt;Documentation and downloads for ngsCAT can be found at http://www.bioinfomgp.org/ngscat.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">12</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/24578402?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">García-Alonso, Luz</style></author><author><style face="normal" font="default" size="100%">Jiménez-Almazán, Jorge</style></author><author><style face="normal" font="default" size="100%">Carbonell-Caballero, José</style></author><author><style face="normal" font="default" size="100%">Vela-Boza, Alicia</style></author><author><style face="normal" font="default" size="100%">Santoyo-López, Javier</style></author><author><style face="normal" font="default" size="100%">Antiňolo, Guillermo</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The role of the interactome in the maintenance of deleterious variability in human populations.</style></title><secondary-title><style face="normal" font="default" size="100%">Mol Syst Biol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Mol Syst Biol</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Alleles</style></keyword><keyword><style  face="normal" font="default" size="100%">Exome</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Library</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetics, Population</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">Genomics</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">Phenotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Conformation</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Interaction Maps</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, DNA</style></keyword><keyword><style  face="normal" font="default" size="100%">Whites</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2014 Sep 26</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">10</style></volume><pages><style face="normal" font="default" size="100%">752</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Recent genomic projects have revealed the existence of an unexpectedly large amount of deleterious variability in the human genome. Several hypotheses have been proposed to explain such an apparently high mutational load. However, the mechanisms by which deleterious mutations in some genes cause a pathological effect but are apparently innocuous in other genes remain largely unknown. This study searched for deleterious variants in the 1,000 genomes populations, as well as in a newly sequenced population of 252 healthy Spanish individuals. In addition, variants causative of monogenic diseases and somatic variants from 41 chronic lymphocytic leukaemia patients were analysed. The deleterious variants found were analysed in the context of the interactome to understand the role of network topology in the maintenance of the observed mutational load. Our results suggest that one of the mechanisms whereby the effect of these deleterious variants on the phenotype is suppressed could be related to the configuration of the protein interaction network. Most of the deleterious variants observed in healthy individuals are concentrated in peripheral regions of the interactome, in combinations that preserve their connectivity, and have a marginal effect on interactome integrity. On the contrary, likely pathogenic cancer somatic deleterious variants tend to occur in internal regions of the interactome, often with associated structural consequences. Finally, variants causative of monogenic diseases seem to occupy an intermediate position. Our observations suggest that the real pathological potential of a variant might be more a systems property rather than an intrinsic property of individual proteins. &lt;/p&gt;</style></abstract><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/25261458?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Méndez-Vidal, Cristina</style></author><author><style face="normal" font="default" size="100%">González-del Pozo, María</style></author><author><style face="normal" font="default" size="100%">Vela-Boza, Alicia</style></author><author><style face="normal" font="default" size="100%">Santoyo-López, Javier</style></author><author><style face="normal" font="default" size="100%">López-Domingo, Francisco J</style></author><author><style face="normal" font="default" size="100%">Vázquez-Marouschek, Carmen</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Borrego, Salud</style></author><author><style face="normal" font="default" size="100%">Antiňolo, Guillermo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Whole-exome sequencing identifies novel compound heterozygous mutations in USH2A in Spanish patients with autosomal recessive retinitis pigmentosa.</style></title><secondary-title><style face="normal" font="default" size="100%">Molecular vision</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2013</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.molvis.org/molvis/v19/2187/</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">19</style></volume><pages><style face="normal" font="default" size="100%">2187-95</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">PURPOSE: Retinitis pigmentosa (RP) is an inherited retinal dystrophy characterized by extreme genetic and clinical heterogeneity. Thus, the diagnosis is not always easily performed due to phenotypic and genetic overlap. Current clinical practices have focused on the systematic evaluation of a set of known genes for each phenotype, but this approach may fail in patients with inaccurate diagnosis or infrequent genetic cause. In the present study, we investigated the genetic cause of autosomal recessive RP (arRP) in a Spanish family in which the causal mutation has not yet been identified with primer extension technology and resequencing. METHODS: We designed a whole-exome sequencing (WES)-based approach using NimbleGen SeqCap EZ Exome V3 sample preparation kit and the SOLiD 5500×l next-generation sequencing platform. We sequenced the exomes of both unaffected parents and two affected siblings. Exome analysis resulted in the identification of 43,204 variants in the index patient. All variants passing filter criteria were validated with Sanger sequencing to confirm familial segregation and absence in the control population. In silico prediction tools were used to determine mutational impact on protein function and the structure of the identified variants. RESULTS: Novel Usher syndrome type 2A (USH2A) compound heterozygous mutations, c.4325T&gt;C (p.F1442S) and c.15188T&gt;G (p.L5063R), located in exons 20 and 70, respectively, were identified as probable causative mutations for RP in this family. Family segregation of the variants showed the presence of both mutations in all affected members and in two siblings who were apparently asymptomatic at the time of family ascertainment. Clinical reassessment confirmed the diagnosis of RP in these patients. CONCLUSIONS: Using WES, we identified two heterozygous novel mutations in USH2A as the most likely disease-causing variants in a Spanish family diagnosed with arRP in which the cause of the disease had not yet been identified with commonly used techniques. Our data reinforce the clinical role of WES in the molecular diagnosis of highly heterogeneous genetic diseases where conventional genetic approaches have previously failed in achieving a proper diagnosis.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Németh, Attila</style></author><author><style face="normal" font="default" size="100%">Ana Conesa</style></author><author><style face="normal" font="default" size="100%">Santoyo-López, Javier</style></author><author><style face="normal" font="default" size="100%">Medina, Ignacio</style></author><author><style face="normal" font="default" size="100%">Montaner, David</style></author><author><style face="normal" font="default" size="100%">Péterfia, Bálint</style></author><author><style face="normal" font="default" size="100%">Solovei, Irina</style></author><author><style face="normal" font="default" size="100%">Cremer, Thomas</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Längst, Gernot</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Initial genomics of the human nucleolus.</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS genetics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">NGS</style></keyword><keyword><style  face="normal" font="default" size="100%">nucleolus</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2010</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.plosgenetics.org/article/info%3Adoi%2F10.1371%2Fjournal.pgen.1000889</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">6</style></volume><pages><style face="normal" font="default" size="100%">e1000889</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We report for the first time the genomics of a nuclear compartment of the eukaryotic cell. 454 sequencing and microarray analysis revealed the pattern of nucleolus-associated chromatin domains (NADs) in the linear human genome and identified different gene families and certain satellite repeats as the major building blocks of NADs, which constitute about 4% of the genome. Bioinformatic evaluation showed that NAD-localized genes take part in specific biological processes, like the response to other organisms, odor perception, and tissue development. 3D FISH and immunofluorescence experiments illustrated the spatial distribution of NAD-specific chromatin within interphase nuclei and its alteration upon transcriptional changes. Altogether, our findings describe the nature of DNA sequences associated with the human nucleolus and provide insights into the function of the nucleolus in genome organization and establishment of nuclear architecture.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Andrew R Jones</style></author><author><style face="normal" font="default" size="100%">Allyson L Lister</style></author><author><style face="normal" font="default" size="100%">Leandro Hermida</style></author><author><style face="normal" font="default" size="100%">Peter Wilkinson</style></author><author><style face="normal" font="default" size="100%">Martin Eisenacher</style></author><author><style face="normal" font="default" size="100%">Khalid Belhajjame</style></author><author><style face="normal" font="default" size="100%">Frank Gibson</style></author><author><style face="normal" font="default" size="100%">Phil Lord</style></author><author><style face="normal" font="default" size="100%">Matthew Pocock</style></author><author><style face="normal" font="default" size="100%">Heiko Rosenfelder</style></author><author><style face="normal" font="default" size="100%">Santoyo-López, Javier</style></author><author><style face="normal" font="default" size="100%">Anil Wipat</style></author><author><style face="normal" font="default" size="100%">Norman W Paton</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Modeling and managing experimental data using FuGE.</style></title><secondary-title><style face="normal" font="default" size="100%">OMICS</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">13</style></volume><pages><style face="normal" font="default" size="100%">239-51</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Birmingham, Amanda</style></author><author><style face="normal" font="default" size="100%">Selfors, Laura M</style></author><author><style face="normal" font="default" size="100%">Forster, Thorsten</style></author><author><style face="normal" font="default" size="100%">Wrobel, David</style></author><author><style face="normal" font="default" size="100%">Kennedy, Caleb J</style></author><author><style face="normal" font="default" size="100%">Shanks, Emma</style></author><author><style face="normal" font="default" size="100%">Santoyo-López, Javier</style></author><author><style face="normal" font="default" size="100%">Dunican, Dara J</style></author><author><style face="normal" font="default" size="100%">Long, Aideen</style></author><author><style face="normal" font="default" size="100%">Kelleher, Dermot</style></author><author><style face="normal" font="default" size="100%">Smith, Queta</style></author><author><style face="normal" font="default" size="100%">Beijersbergen, Roderick L</style></author><author><style face="normal" font="default" size="100%">Ghazal, Peter</style></author><author><style face="normal" font="default" size="100%">Shamu, Caroline E</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Statistical methods for analysis of high-throughput RNA interference screens</style></title><secondary-title><style face="normal" font="default" size="100%">Nature Methods</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">gene silencing</style></keyword><keyword><style  face="normal" font="default" size="100%">regulation</style></keyword><keyword><style  face="normal" font="default" size="100%">siRNA</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2009/08//print</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1038/nmeth.1351</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Nature Publishing Group</style></publisher><volume><style face="normal" font="default" size="100%">6</style></volume><pages><style face="normal" font="default" size="100%">569 - 575</style></pages><isbn><style face="normal" font="default" size="100%">1548-7091</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><notes><style face="normal" font="default" size="100%">&lt;p&gt;10.1038/nmeth.1351&lt;/p&gt;</style></notes></record></records></xml>