scholarly journals Large-scale objective association of mouse phenotypes with human symptoms through structural variation identified in patients with developmental disorders

2012 ◽  
Vol 33 (5) ◽  
pp. 874-883 ◽  
Author(s):  
Hannah Boulding ◽  
Caleb Webber
Keyword(s):  
Developmental Disorders ◽  
Large Scale ◽  
Structural Variation

CONTRIBUTION OF DNA COPY-NUMBER VARIATION (CNV) TO CANCER SUSCEPTIBILITY AND LARGE-SCALE GENOME ALTERATIONS IN OSTEOSARCOMA (OS)

2008 ◽  
Vol 31 (4) ◽  
pp. 19
Author(s):  
I Pasic ◽  
A Shlien ◽  
A Novokmet ◽  
C Zhang ◽  
U Tabori ◽  
...  
Keyword(s):  
Genomic Instability ◽  
Large Scale ◽  
Structural Variation ◽  
Age Of Onset ◽  
Cancer Susceptibility ◽  
Small Sample Size ◽  
Snp Array ◽  
Tumour Suppressor Gene ◽  
Small Sample ◽  
International Hapmap Project

Introduction: OS, a common Li-Fraumeni syndrome (LFS)-associated neoplasm, is a common bone malignancy of children and adolescents. Sporadic OS is also characterized by young age of onset and high genomic instability, suggesting a genetic contribution to disease. This study examined the contribution of novel DNA structural variation elements, CNVs, to OS susceptibility. Given our finding of excessive constitutional DNA CNV in LFS patients, which often coincide with cancer-related genes, we hypothesized that constitutional CNV may also provide clues about the aetiology of LFS-related sporadic neoplasms like OS. Methods: CNV in blood DNA of 26 patients with sporadic OS was compared to that of 263 normal control samples from the International HapMap project, as well as 62 local controls. Analysis was performed on DNA hybridized to Affymetrix genome-wide human SNP array 6.0 by Partek Genomic Suite. Results: There was no detectable difference in average number of CNVs, CNV length, and total structural variation (product of average CNV number and length) between individuals with OS and controls. While this data is preliminary (small sample size), it argues against the presence of constitutional genomic instability in individuals with sporadic OS. Conclusion: We found that the majority of tumours from patients with sporadic OS show CN loss at chr3q13.31, raising the possibility that chr3q13.31 may represent a “driver” region in OS aetiology. In at least one OS tumour, which displays CN loss at chr3q13.31, we demonstrate decreased expression of a known tumour suppressor gene located at chr3q13.31. We are investigating the role ofchr3q13.31 in development of OS.

scholarly journals svtools: population-scale analysis of structural variation

2019 ◽  
Vol 35 (22) ◽  
pp. 4782-4787 ◽  
Author(s):  
David E Larson ◽  
Haley J Abel ◽  
Colby Chiang ◽  
Abhijit Badve ◽  
Indraniel Das ◽  
...  
Keyword(s):  
Large Scale ◽  
Structural Variation ◽  
Human Genetics ◽  
Mobile Element ◽  
Supplementary Information ◽  
Joint Analysis ◽  
Human Populations ◽  
Scale Analysis ◽  
Human Genomes ◽  
Variant Detection

Abstract Summary Large-scale human genetics studies are now employing whole genome sequencing with the goal of conducting comprehensive trait mapping analyses of all forms of genome variation. However, methods for structural variation (SV) analysis have lagged far behind those for smaller scale variants, and there is an urgent need to develop more efficient tools that scale to the size of human populations. Here, we present a fast and highly scalable software toolkit (svtools) and cloud-based pipeline for assembling high quality SV maps—including deletions, duplications, mobile element insertions, inversions and other rearrangements—in many thousands of human genomes. We show that this pipeline achieves similar variant detection performance to established per-sample methods (e.g. LUMPY), while providing fast and affordable joint analysis at the scale of ≥100 000 genomes. These tools will help enable the next generation of human genetics studies. Availability and implementation svtools is implemented in Python and freely available (MIT) from https://github.com/hall-lab/svtools. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Single-molecule analysis reveals widespread structural variation in multiple myeloma

2015 ◽  
Vol 112 (25) ◽  
pp. 7689-7694 ◽  
Author(s):  
Aditya Gupta ◽  
Michael Place ◽  
Steven Goldstein ◽  
Deepayan Sarkar ◽  
Shiguo Zhou ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Tumor Progression ◽  
Single Molecule ◽  
Large Scale ◽  
Structural Variation ◽  
Plasma Cells ◽  
Optical Mapping ◽  
Genome Structure ◽  
Genomic Analysis ◽  
Whole Genome Analysis

Multiple myeloma (MM), a malignancy of plasma cells, is characterized by widespread genomic heterogeneity and, consequently, differences in disease progression and drug response. Although recent large-scale sequencing studies have greatly improved our understanding of MM genomes, our knowledge about genomic structural variation in MM is attenuated due to the limitations of commonly used sequencing approaches. In this study, we present the application of optical mapping, a single-molecule, whole-genome analysis system, to discover new structural variants in a primary MM genome. Through our analysis, we have identified and characterized widespread structural variation in this tumor genome. Additionally, we describe our efforts toward comprehensive characterization of genome structure and variation by integrating our findings from optical mapping with those from DNA sequencing-based genomic analysis. Finally, by studying this MM genome at two time points during tumor progression, we have demonstrated an increase in mutational burden with tumor progression at all length scales of variation.

scholarly journals Expectations and blind spots for structural variation detection from short-read alignment and long-read assembly

2020 ◽  
Author(s):  
Xuefang Zhao ◽  
Ryan L. Collins ◽  
Wan-Ping Lee ◽  
Alexandra M. Weber ◽  
Yukyung Jun ◽  
...  
Keyword(s):  
Single Molecule ◽  
Large Scale ◽  
Structural Variation ◽  
Human Genetics ◽  
Clinical Diagnostics ◽  
Added Value ◽  
Mendelian Disease ◽  
Segmental Duplications ◽  
Genomic Context ◽  
Long Read

AbstractVirtually all genome sequencing efforts in national biobanks, complex and Mendelian disease programs, and emerging clinical diagnostic approaches utilize short-reads (srWGS), which present constraints for genome-wide discovery of structural variants (SVs). Alternative long-read single molecule technologies (lrWGS) offer significant advantages for genome assembly and SV detection, while these technologies are currently cost prohibitive for large-scale disease studies and clinical diagnostics (∼5-12X higher cost than comparable coverage srWGS). Moreover, only dozens of such genomes are currently publicly accessible by comparison to millions of srWGS genomes that have been commissioned for international initiatives. Given this ubiquitous reliance on srWGS in human genetics and genomics, we sought to characterize and quantify the properties of SVs accessible to both srWGS and lrWGS to establish benchmarks and expectations in ongoing medical and population genetic studies, and to project the added value of SVs uniquely accessible to each technology. In analyses of three trios with matched srWGS and lrWGS from the Human Genome Structural Variation Consortium (HGSVC), srWGS captured ∼11,000 SVs per genome using reference-based algorithms, while haplotype-resolved assembly from lrWGS identified ∼25,000 SVs per genome. Detection power and precision for SV discovery varied dramatically by genomic context and variant class: 9.7% of the current GRCh38 reference is defined by segmental duplications (SD) and simple repeats (SR), yet 91.4% of deletions that were specifically discovered by lrWGS localized to these regions. Across the remaining 90.3% of the human reference, we observed extremely high concordance (93.8%) for deletions discovered by srWGS and lrWGS after error correction using the raw lrWGS reads. Conversely, lrWGS was superior for detection of insertions across all genomic contexts. Given that the non-SD/SR sequences span 90.3% of the GRCh38 reference, and encompass 95.9% of coding exons in currently annotated disease associated genes, improved sensitivity from lrWGS to discover novel and interpretable pathogenic deletions not already accessible to srWGS is likely to be incremental. However, these analyses highlight the added value of assembly-based lrWGS to create new catalogues of functional insertions and transposable elements, as well as disease associated repeat expansions in genomic regions previously recalcitrant to routine assessment.

scholarly journals A synthesis of mapping experiments reveals extensive genomic structural diversity in the Mimulus guttatus species complex

2018 ◽  
Author(s):  
Lex Flagel ◽  
Benjamin K. Blackman ◽  
Lila Fishman ◽  
Patrick J. Monnahan ◽  
Andrea Sweigart ◽  
...  
Keyword(s):  
Genetic Mapping ◽  
Species Complex ◽  
Large Scale ◽  
Structural Variation ◽  
Reference Genome ◽  
Genetic Research ◽  
Evolutionary Genetics ◽  
Flowering Plant ◽  
Mimulus Guttatus ◽  
Trait Mapping

ABSTRACTUnderstanding genomic structural variation such as inversions and translocations is a key challenge in evolutionary genetics. In this paper, we tackle this challenge by developing a novel statistical approach to comparative genetic mapping. The procedure couples a Hidden Markov Model with a Genetic Algorithm to detect large-scale structural variation using low-level sequencing data from multiple genetic mapping populations. We demonstrate the method using five distinct crosses within the flowering plant genus Mimulus. The synthesis of data from these experiments is first used to correct numerous errors (misplaced sequences) in the M. guttatus reference genome. Second, we confirm and/or detect eight large inversions polymorphic within the M. guttatus species complex. Finally, we show how this method can be applied in genomic scans to improve the accuracy and resolution of Quantitative Trait Locus (QTL) mapping.AUTHOR SUMMARYGenome sequences have proved to be a critical experimental resource for genetic research in many species. However, in some species there is considerable variation in genomic organization, making a single reference genome sequence inadequate. This variation can cause issues in interpreting genomic signals, such as those coming from trait mapping. We introduce a new statistical method and computational tools that use linkage information to reorganize a single reference genome to 1) repair genome assembly errors, and 2) identify variation between individuals or populations of the same species. Using this method we can create a new genome order that improves upon the reference genome. We apply this method to five crosses among plants in the Mimulus guttatus species complex. In this system we detect eight large chromosomal inversions and improve the resolution of a trait mapping study. This work highlights the utility of our method, and indicates how others studying diverse species might use them to improve their own research.

scholarly journals Multi-platform discovery of haplotype-resolved structural variation in human genomes

2017 ◽  
Author(s):  
Mark J.P. Chaisson ◽  
Ashley D. Sanders ◽  
Xuefang Zhao ◽  
Ankit Malhotra ◽  
David Porubsky ◽  
...  
Keyword(s):  
Genome Sequencing ◽  
Large Scale ◽  
Structural Variation ◽  
High Throughput Sequencing ◽  
Whole Genome Sequencing Data ◽  
Sequencing Data ◽  
Full Spectrum ◽  
Variant Discovery ◽  
Sequencing Technologies ◽  
Sequencing Studies

ABSTRACTThe incomplete identification of structural variants (SVs) from whole-genome sequencing data limits studies of human genetic diversity and disease association. Here, we apply a suite of long-read, short-read, and strand-specific sequencing technologies, optical mapping, and variant discovery algorithms to comprehensively analyze three human parent–child trios to define the full spectrum of human genetic variation in a haplotype-resolved manner. We identify 818,054 indel variants (<50 bp) and 27,622 SVs (≥50 bp) per human genome. We also discover 156 inversions per genome—most of which previously escaped detection. Fifty-eight of the inversions we discovered intersect with the critical regions of recurrent microdeletion and microduplication syndromes. Taken together, our SV callsets represent a sevenfold increase in SV detection compared to most standard high-throughput sequencing studies, including those from the 1000 Genomes Project. The method and the dataset serve as a gold standard for the scientific community and we make specific recommendations for maximizing structural variation sensitivity for future large-scale genome sequencing studies.

Load and Order in Rapid Automatized Naming: A Large-Scale Prospective Study of Toddlers With Brain Injury

2010 ◽  
Vol 9 (2) ◽  
pp. 166-182 ◽  
Author(s):  
Ronny Geva ◽  
Judith M. Gardner ◽  
Bernard Z. Karmel
Keyword(s):  
Learning Disabilities ◽  
Developmental Disorders ◽  
Large Scale ◽  
Learning Difficulties ◽  
Naming Task ◽  
Rapid Automatized Naming ◽  
Information Load ◽  
Developmental Risk ◽  
Factors Affecting ◽  
Potential Use

The rapid automatized naming task (RAN) is a well-established tool to evaluate risk of developmental disorders. Its potential use with 3-year-olds who are at risk for learning difficulties and factors affecting its dependent measures are not yet understood. This study investigated the effects of neonatal central nervous system compromise grouping (five levels, N = 617) on RAN task adapted for 3-year-olds, using two levels of information load and two presentation orders. Results showed that increased errors and slowed speed in toddlers are expected subsequent to severe neonatal CNS compromise. Furthermore, collaborative information may have a beneficial effect on processing speeds of toddlers born with severe, but not with moderate, neonatal CNS compromise. Finally, the study highlights the feasability of evaluating RAN performance in toddlers who are at a developmental risk for learning disabilities and the conditions of RAN that may facilitate performance of severely affected participants.

Sign in / Sign up

Export Citation Format

Share Document