Bioinformatic characterization and analysis of polymorphic inversions in the human genome

Within the great interest in the characterization of genomic structural variants (SVs) in the human genome, inversions present unique challenges and have been little studied. This thesis has developed "GRIAL", a new algorithm focused specifically in detect and map accurately inversions from paired-end mapping (PEM) data, which is the most widely used method to detect SVs. GRIAL is based on geometrical rules to cluster, merge and refine both breakpoints of putative inversions. That way, we have been able to predict hundreds of inversions in the human genome. In addition, thanks to the different GRIAL quality scores, we have been able to identify spurious PEM-patterns and their causes, and discard a big fraction of the predicted inversions as false positives. Furthermore, we have created â ˘ AIJInvFESTâ˘A˙I, the first database of human polymorphic inversions, which represents the most reliable catalogue of inversions and integrates all the associated information from multiple sources. Currently, InvFEST combines information from 30 different studies and contains 1092 candidate inversions, which are categorized based on internal scores and manual curation. Finally, the analysis of all the data generated has provided information on the genomic patterns of inversions, contributing decisively to the understanding of the map of human polymorphic inversions.Dentro del estudio de las variantes estructurales en el genoma humano, las inversiones han sido las menos han consolidado sus resultados y constituye uno de los principales retos en la actualidad. Esta tesis aborda el tema a través de la implementación de "GRIAL" un nuevo algoritmo específicamente diseñado para la detección más precisa posible de las inversiones usando el mapeo de secuencias apareadas (del inglés PEM) que es el método más utilizado para estudiar la variación estructural. GRIAL se basa en reglas geométricas para agrupar los patrones de PEM que señalan un posible punto de rotura (del inglés breakpoint) de inversión, además une cada breakpoint correspondientes a inversiones independientes y refina lo más exacto posible su localización. Su uso nos permitió predecir cientos de inversiones. Un gran aporte de nuestro método es la creación de índices (del inglés score) de fiabilidad para las predicciones mediante los cuales identificamos patrones de inversión incorrectos y sus causas. Esto nos permitió filtrar nuestro resultado eliminando un gran número de predicciones posiblemente falsas. Además se creó "InvFEST", la primera base de datos especialmente dedicada a inversiones polimórficas en el genoma humano la cual representa el catálogo más fiable de inversiones, integrando además a cada inversión conocida la información asociada disponible. Actualmente InvFEST contiene (y mantiene la clasificación según el nivel de certeza) un catálogo de 1092 inversiones clasificadas, a partir de datos de 30 estudios diferentes. Finalmente el análisis de toda la información generada nos permitió describir algunos patrones de las inversiones polimórficas en el genoma humano contribuyendo de este modo a la comprensión de esta variante estructural y el estado de su información en los estudios del genoma humano.Inversió genòmic

Bioinformatic characterization and analysis of polymorphic inversions in the human genome

Within the great interest in the characterization of genomic structural variants (SVs) in the human genome, inversions present unique challenges and have been little studied. This thesis has developed "GRIAL", a new algorithm focused specifically in detect and map accurately inversions from paired-end mapping (PEM) data, which is the most widely used method to detect SVs. GRIAL is based on geometrical rules to cluster, merge and refine both breakpoints of putative inversions. That way, we have been able to predict hundreds of inversions in the human genome. In addition, thanks to the different GRIAL quality scores, we have been able to identify spurious PEM-patterns and their causes, and discard a big fraction of the predicted inversions as false positives. Furthermore, we have created â ˘ AIJInvFESTâ˘A˙I, the first database of human polymorphic inversions, which represents the most reliable catalogue of inversions and integrates all the associated information from multiple sources. Currently, InvFEST combines information from 30 different studies and contains 1092 candidate inversions, which are categorized based on internal scores and manual curation. Finally, the analysis of all the data generated has provided information on the genomic patterns of inversions, contributing decisively to the understanding of the map of human polymorphic inversions.Dentro del estudio de las variantes estructurales en el genoma humano, las inversiones han sido las menos han consolidado sus resultados y constituye uno de los principales retos en la actualidad. Esta tesis aborda el tema a través de la implementación de "GRIAL" un nuevo algoritmo específicamente diseñado para la detección más precisa posible de las inversiones usando el mapeo de secuencias apareadas (del inglés PEM) que es el método más utilizado para estudiar la variación estructural. GRIAL se basa en reglas geométricas para agrupar los patrones de PEM que señalan un posible punto de rotura (del inglés breakpoint) de inversión, además une cada breakpoint correspondientes a inversiones independientes y refina lo más exacto posible su localización. Su uso nos permitió predecir cientos de inversiones. Un gran aporte de nuestro método es la creación de índices (del inglés score) de fiabilidad para las predicciones mediante los cuales identificamos patrones de inversión incorrectos y sus causas. Esto nos permitió filtrar nuestro resultado eliminando un gran número de predicciones posiblemente falsas. Además se creó "InvFEST", la primera base de datos especialmente dedicada a inversiones polimórficas en el genoma humano la cual representa el catálogo más fiable de inversiones, integrando además a cada inversión conocida la información asociada disponible. Actualmente InvFEST contiene (y mantiene la clasificación según el nivel de certeza) un catálogo de 1092 inversiones clasificadas, a partir de datos de 30 estudios diferentes. Finalmente el análisis de toda la información generada nos permitió describir algunos patrones de las inversiones polimórficas en el genoma humano contribuyendo de este modo a la comprensión de esta variante estructural y el estado de su información en los estudios del genoma humano.Inversió genòmic

InvFEST, a database integrating information of polymorphic inversions in the human genome

The newest genomic advances have uncovered an unprecedented degree of structural variation throughout genomes, with great amounts of data accumulating rapidly. Here we introduce InvFEST (http://invfestdb.uab.cat), a database combining multiple sources of information to generate a complete catalogue of non-redundant human polymorphic inversions. Due to the complexity of this type of changes and the underlying high false-positive discovery rate, it is necessary to integrate all the available data to get a reliable estimate of the real number of inversions. InvFEST automatically merges predictions into different inversions, refines the breakpoint locations, and finds associations with genes and segmental duplications. In addition, it includes data on experimental validation, population frequency, functional effects and evolutionary history. All this information is readily accessible through a complete and user-friendly web report for each inversion. In its current version, InvFEST combines information from 34 different studies and contains 1092 candidate inversions, which are categorized based on internal scores and manual curation. Therefore, InvFEST aims to represent the most reliable set of human inversions and become a central repository to share information, guide future studies and contribute to the analysis of the functional and evolutionary impact of inversions on the human genome.This work was supported by The European Research Council under the European Union Seventh Research Framework Programme [Starting Grant 243212 (INVFEST) to M.C.]; Ministerio de Asuntos Exteriores y Cooperación (Spain) [MAECAECI doctoral fellowship to A.M.F.]; Ministerio de Ciencia e Innovación (Spain) [BFU2007-60930 to M.C. and BFU2009-09504 to A.B.]. Funding for open access/ncharge: European Research Counci

InvFEST, a database integrating information of polymorphic inversions in the human genome

The newest genomic advances have uncovered an unprecedented degree of structural variation throughout genomes, with great amounts of data accumulating rapidly. Here we introduce InvFEST (http://invfestdb.uab.cat), a database combining multiple sources of information to generate a complete catalogue of non-redundant human polymorphic inversions. Due to the complexity of this type of changes and the underlying high false-positive discovery rate, it is necessary to integrate all the available data to get a reliable estimate of the real number of inversions. InvFEST automatically merges predictions into different inversions, refines the breakpoint locations, and finds associations with genes and segmental duplications. In addition, it includes data on experimental validation, population frequency, functional effects and evolutionary history. All this information is readily accessible through a complete and user-friendly web report for each inversion. In its current version, InvFEST combines information from 34 different studies and contains 1092 candidate inversions, which are categorized based on internal scores and manual curation. Therefore, InvFEST aims to represent the most reliable set of human inversions and become a central repository to share information, guide future studies and contribute to the analysis of the functional and evolutionary impact of inversions on the human genome.This work was supported by The European Research Council under the European Union Seventh Research Framework Programme [Starting Grant 243212 (INVFEST) to M.C.]; Ministerio de Asuntos Exteriores y Cooperación (Spain) [MAECAECI doctoral fellowship to A.M.F.]; Ministerio de Ciencia e Innovación (Spain) [BFU2007-60930 to M.C. and BFU2009-09504 to A.B.]. Funding for open access/ncharge: European Research Counci

PeSV-fisher : identification of somatic and non-somatic structural variants using next generation sequencing data

Next-generation sequencing technologies expedited research to develop efficient computational tools for the identification of structural variants (SVs) and their use to study human diseases. As deeper data is obtained, the existence of higher complexity SVs in some genomes becomes more evident, but the detection and definition of most of these complex rearrangements is still in its infancy. The full characterization of SVs is a key aspect for discovering their biological implications. Here we present a pipeline (PeSV-Fisher) for the detection of deletions, gains, intra- and inter-chromosomal translocations, and inversions, at very reasonable computational costs. We further provide comprehensive information on co-localization of SVs in the genome, a crucial aspect for studying their biological consequences. The algorithm uses a combination of methods based on paired-reads and read-depth strategies. PeSV-Fisher has been designed with the aim to facilitate identification of somatic variation, and, as such, it is capable of analysing two or more samples simultaneously, producing a list of non-shared variants between samples. We tested PeSV-Fisher on available sequencing data, and compared its behaviour to that of frequently deployed tools (BreakDancer and VariationHunter). We have also tested this algorithm on our own sequencing data, obtained from a tumour and a normal blood sample of a patient with chronic lymphocytic leukaemia, on which we have also validated the results by targeted re-sequencing of different kinds of predictions. This allowed us to determine confidence parameters that influence the reliability of breakpoint predictions.Availability:PeSV-Fisher is available at http://gd.crg.eu/tools

InvFEST, a database integrating information of polymorphic inversions in the human genome

The newest genomic advances have uncovered an unprecedented degree of structural variation throughout genomes, with great amounts of data accumulating rapidly. Here we introduce InvFEST (), a database combining multiple sources of information to generate a complete catalogue of non-redundant human polymorphic inversions. Due to the complexity of this type of changes and the underlying high false-positive discovery rate, it is necessary to integrate all the available data to get a reliable estimate of the real number of inversions. InvFEST automatically merges predictions into different inversions, refines the breakpoint locations, and finds associations with genes and segmental duplications. In addition, it includes data on experimental validation, population frequency, functional effects and evolutionary history. All this information is readily accessible through a complete and user-friendly web report for each inversion. In its current version, InvFEST combines information from 34 different studies and contains 1092 candidate inversions, which are categorized based on internal scores and manual curation. Therefore, InvFEST aims to represent the most reliable set of human inversions and become a central repository to share information, guide future studies and contribute to the analysis of the functional and evolutionary impact of inversions on the human genome

PeSV-Fisher: identification of somatic and non-somatic structural variants using nextgeneration sequencing data

Next-generation sequencing technologies expedited research to develop efficient computational tools for the identification of structural variants (SVs) and their use to study human diseases. As deeper data is obtained, the existence of higher complexity SVs in some genomes becomes more evident, but the detection and definition of most of these complex rearrangements is still in its infancy. The full characterization of SVs is a key aspect for discovering their biological implications. Here we present a pipeline (PeSV-Fisher) for the detection of deletions, gains, intra- and inter-chromosomal translocations, and inversions, at very reasonable computational costs. We further provide comprehensive information on co-localization of SVs in the genome, a crucial aspect for studying their biological consequences. The algorithm uses a combination of methods based on paired-reads and read-depth strategies. PeSV-Fisher has been designed with the aim to facilitate identification of somatic variation, and, as such, it is capable of analysing two or more samples simultaneously, producing a list of non-shared variants between samples. We tested PeSV-Fisher on available sequencing data, and compared its behaviour to that of frequently deployed tools (BreakDancer and VariationHunter). We have also tested this algorithm on our own sequencing data, obtained from a tumour and a normal blood sample of a patient with chronic lymphocytic leukaemia, on which we have also validated the results by targeted re-sequencing of different kinds of predictions. This allowed us to determine confidence parameters that influence the reliability of breakpoint predictions.This work was supported by AGAUR (Generalitat de Catalunya, 2009 SGR 1502) (X.E.); CIBERESP (Instituto de Salud Carlos III) (G.E.); ESGI (European Commission, 262055_ESGI) (R.R., X.E.), ENGAGE (European Commission, ENGAGE_201413), TECHGENE (European Commission, TECHGENE_223143), and GEUVADIS (European Commission, 261123_GEUVADIS) (X.E.); NOVADIS (Ministerio de Ciencia y Technologia, SAF2008-00357) (X.E.); Galicia Government Xunta de Galicia (Spain) through the project number 10PXIB918057 (J.M.C.T.); MAEC-AEC1 Predoctoral Fellowship (Ministerio de Asuntos Exteriores y Cooperación, Spain) (A.M.F.); and Ramón y Cajal position and grant BFU2007-60930 (Ministerio de Educación y Ciencia) (M.C.)

Validation and Genotyping of Multiple Human Polymorphic Inversions Mediated by Inverted Repeats Reveals a High Degree of Recurrence

In recent years different types of structural variants (SVs) have been discovered in the human genome and their functional impact has become increasingly clear. Inversions, however, are poorly characterized and more difficult to study, especially those mediated by inverted repeats or segmental duplications. Here, we describe the results of a simple and fast inverse PCR (iPCR) protocol for high-throughput genotyping of a wide variety of inversions using a small amount of DNA. In particular, we analyzed 22 inversions predicted in humans ranging from 5.1 kb to 226 kb and mediated by inverted repeat sequences of 1.6-24 kb. First, we validated 17 of the 22 inversions in a panel of nine HapMap individuals from different populations, and we genotyped them in 68 additional individuals of European origin, with correct genetic transmission in ∼12 mother-father-child trios. Global inversion minor allele frequency varied between 1% and 49% and inversion genotypes were consistent with Hardy-Weinberg equilibrium. By analyzing the nucleotide variation and the haplotypes in these regions, we found that only four inversions have linked tag-SNPs and that in many cases there are multiple shared SNPs between standard and inverted chromosomes, suggesting an unexpected high degree of inversion recurrence during human evolution. iPCR was also used to check 16 of these inversions in four chimpanzees and two gorillas, and 10 showed both orientations either within or between species, providing additional support for their multiple origin. Finally, we have identified several inversions that include genes in the inverted or breakpoint regions, and at least one disrupts a potential coding gene. Thus, these results represent a significant advance in our understanding of inversion polymorphism in human populations and challenge the common view of a single origin of inversions, with important implications for inversion analysis in SNP-based studies

Validation and genotyping of multiple human polymorphic inversions mediated by inverted repeats reveals a high degree of recurrence

In recent years different types of structural variants (SVs) have been discovered in the human genome and their functional impact has become increasingly clear. Inversions, however, are poorly characterized and more difficult to study, especially those mediated by inverted repeats or segmental duplications. Here, we describe the results of a simple and fast inverse PCR (iPCR) protocol for high-throughput genotyping of a wide variety of inversions using a small amount of DNA. In particular, we analyzed 22 inversions predicted in humans ranging from 5.1 kb to 226 kb and mediated by inverted repeat sequences of 1.6-24 kb. First, we validated 17 of the 22 inversions in a panel of nine HapMap individuals from different populations, and we genotyped them in 68 additional individuals of European origin, with correct genetic transmission in ∼ 12 mother-father-child trios. Global inversion minor allele frequency varied between 1% and 49% and inversion genotypes were consistent with Hardy-Weinberg equilibrium. By analyzing the nucleotide variation and the haplotypes in these regions, we found that only four inversions have linked tag-SNPs and that in many cases there are multiple shared SNPs between standard and inverted chromosomes, suggesting an unexpected high degree of inversion recurrence during human evolution. iPCR was also used to check 16 of these inversions in four chimpanzees and two gorillas, and 10 showed both orientations either within or between species, providing additional support for their multiple origin. Finally, we have identified several inversions that include genes in the inverted or breakpoint regions, and at least one disrupts a potential coding gene. Thus, these results represent a significant advance in our understanding of inversion polymorphism in human populations and challenge the common view of a single origin of inversions, with important implications for inversion analysis in SNP-based studies.This work was supported by the European Research Council (ERC) Starting Grant 243212 (INVFEST) under the European Union Seventh Research Framework Programme (FP7) to MC, a FPI PhD fellowship from the Ministerio de Educación y Ciencia (Spain) to MO, a PIF PhD fellowship from the Universitat Autònoma de Barcelona (Spain) to CGD, a MAEC-AECI PhD fellowship from the Ministerio de Asuntos Exteriores y Cooperación (Spain) to AMF, and a research PRIC grant from the Barcelona Zoo (Ajuntament de Barcelona, Spain) to ARH