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Search Results: 1 - 10 of 176832 matches for " Matthew E Hurles "
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Gene conversion homogenizes the CMT1A paralogous repeats
Matthew E Hurles
BMC Genomics , 2001, DOI: 10.1186/1471-2164-2-11
Abstract: Here, a statistical test to detect gene conversion between pairs of non-coding sequences is presented. It is shown that the 24 kb Charcot-Marie-Tooth type 1A paralogous repeats (CMT1A-REPs) exhibit the imprint of gene conversion processes whilst control orthologous sequences do not. In addition, Monte Carlo simulations of the evolutionary divergence of the CMT1A-REPs, incorporating two alternative models for gene conversion, generate repeats that are statistically indistinguishable from the observed repeats. Bounds are placed on the rate of these conversion processes, with central values of 1.3 × 10-4 and 5.1 × 10-5 per generation for the alternative models.This evidence presented here suggests that gene conversion may have played an important role in the evolution of the CMT1A-REP paralogous repeats. The rates of these processes are such that it is probable that homogenized CMT1A-REPs are polymorphic within modern populations. Gene conversion processes are similarly likely to play an important role in the evolution of other segmental duplications and may influence the rate of non-allelic homologous recombination between them.There is a rapidly growing literature describing pathogenic rearrangements caused by illegitimate recombination between non-allelic homologous sequences [1-3]. These paralogous repeats can cause inversions which disrupt coding sequences, and microdeletions and microduplications that result in pathogenic changes in the copy number of intervening genes.The peripheral neuropathy Charcot-Marie-Tooth disease type 1A (CMT1A) is caused by a microduplication of a 1.5 Mb region on chromosome 17 that lies between 24 kb paralogous direct repeats known as CMT1A-REPs [4]. The reciprocal product, a microdeletion, causes hereditary neuropathy with liability to pressure palsies (HNPP) [5]. Similarly the SMS-REP direct paralogous repeats on chromosome 17 cause both pathogenic microdeletions (causing Smith-Magenis Syndrome) and microduplications [6]. Inverted pa
Characterising and Predicting Haploinsufficiency in the Human Genome
Ni Huang,Insuk Lee,Edward M. Marcotte,Matthew E. Hurles
PLOS Genetics , 2010, DOI: 10.1371/journal.pgen.1001154
Abstract: Haploinsufficiency, wherein a single functional copy of a gene is insufficient to maintain normal function, is a major cause of dominant disease. Human disease studies have identified several hundred haploinsufficient (HI) genes. We have compiled a map of 1,079 haplosufficient (HS) genes by systematic identification of genes unambiguously and repeatedly compromised by copy number variation among 8,458 apparently healthy individuals and contrasted the genomic, evolutionary, functional, and network properties between these HS genes and known HI genes. We found that HI genes are typically longer and have more conserved coding sequences and promoters than HS genes. HI genes exhibit higher levels of expression during early development and greater tissue specificity. Moreover, within a probabilistic human functional interaction network HI genes have more interaction partners and greater network proximity to other known HI genes. We built a predictive model on the basis of these differences and annotated 12,443 genes with their predicted probability of being haploinsufficient. We validated these predictions of haploinsufficiency by demonstrating that genes with a high predicted probability of exhibiting haploinsufficiency are enriched among genes implicated in human dominant diseases and among genes causing abnormal phenotypes in heterozygous knockout mice. We have transformed these gene-based haploinsufficiency predictions into haploinsufficiency scores for genic deletions, which we demonstrate to better discriminate between pathogenic and benign deletions than consideration of the deletion size or numbers of genes deleted. These robust predictions of haploinsufficiency support clinical interpretation of novel loss-of-function variants and prioritization of variants and genes for follow-up studies.
Origins of chromosomal rearrangement hotspots in the human genome: evidence from the AZFa deletion hotspots
Matthew E Hurles, David Willey, Lucy Matthews, Syed Hussain
Genome Biology , 2004, DOI: 10.1186/gb-2004-5-8-r55
Abstract: These recombination hotspots are characterized by signatures of concerted evolution, which indicate that gene conversion between paralogs has been predominant in shaping their recent evolution. By contrast, the paralogous sequences that surround the hotspots exhibit little evidence of gene conversion. A second feature of these rearrangement hotspots is the extreme interspecific sequence divergence (around 2.5%) that places them among the most divergent orthologous sequences between humans and chimpanzees.Several hominid-specific gene conversion events have rendered these hotspots better substrates for chromosomal rearrangements in humans than in chimpanzees or gorillas. Monte Carlo simulations of sequence evolution suggest that extreme sequence divergence is a direct consequence of gene conversion between paralogs. We propose that the coincidence of signatures of concerted evolution and recurrent breakpoints of chromosomal rearrangement (mapped at the sequence level) may enable the identification of putative rearrangement hotspots from analysis of comparative sequences from great apes.The pattern of meiotic homologous recombination is not homogeneous throughout the human genome. Hotspots of recombination activity - short genomic regions defined at the sequence level that exhibit higher levels of recombination than their surrounding sequence - have been identified in both the generation of haplotypic diversity by allelic homologous recombination (AHR) and the production of chromosomal rearrangements by non-allelic homologous recombination (NAHR) [1,2]. The evolution and determinants of these recombination hotspots are poorly understood.NAHR between duplicated sequences sponsors a wide variety of pathogenic chromosomal rearrangements, giving rise to phenotypes known collectively as 'genomic disorders' (reviewed in [3]). While some of these disorders result from the intermediates of NAHR being resolved as crossovers (that is, rearrangements such as deletions, duplicati
Gene Duplication: The Genomic Trade in Spare Parts
Matthew Hurles
PLOS Biology , 2012, DOI: 10.1371/journal.pbio.0020206
Abstract:
How homologous recombination generates a mutable genome
Matthew Hurles
Human Genomics , 2005, DOI: 10.1186/1479-7364-2-3-179
Abstract:
Gene Duplication: The Genomic Trade in Spare Parts
Matthew Hurles
PLOS Biology , 2004, DOI: 10.1371/journal.pbio.0020206
Abstract:
The Rate of Nonallelic Homologous Recombination in Males Is Highly Variable, Correlated between Monozygotic Twins and Independent of Age
Jacqueline A. L. MacArthur,Timothy D. Spector,Sarah J. Lindsay,Massimo Mangino,Raj Gill,Kerrin S. Small,Matthew E. Hurles
PLOS Genetics , 2014, DOI: doi/10.1371/journal.pgen.1004195
Abstract: Nonallelic homologous recombination (NAHR) between highly similar duplicated sequences generates chromosomal deletions, duplications and inversions, which can cause diverse genetic disorders. Little is known about interindividual variation in NAHR rates and the factors that influence this. We estimated the rate of deletion at the CMT1A-REP NAHR hotspot in sperm DNA from 34 male donors, including 16 monozygotic (MZ) co-twins (8 twin pairs) aged 24 to 67 years old. The average NAHR rate was 3.5×10?5 with a seven-fold variation across individuals. Despite good statistical power to detect even a subtle correlation, we observed no relationship between age of unrelated individuals and the rate of NAHR in their sperm, likely reflecting the meiotic-specific origin of these events. We then estimated the heritability of deletion rate by calculating the intraclass correlation (ICC) within MZ co-twins, revealing a significant correlation between MZ co-twins (ICC = 0.784, p = 0.0039), with MZ co-twins being significantly more correlated than unrelated pairs. We showed that this heritability cannot be explained by variation in PRDM9, a known regulator of NAHR, or variation within the NAHR hotspot itself. We also did not detect any correlation between Body Mass Index (BMI), smoking status or alcohol intake and rate of NAHR. Our results suggest that other, as yet unidentified, genetic or environmental factors play a significant role in the regulation of NAHR and are responsible for the extensive variation in the population for the probability of fathering a child with a genomic disorder resulting from a pathogenic deletion.
Fast-evolving noncoding sequences in the human genome
Christine P Bird, Barbara E Stranger, Maureen Liu, Daryl J Thomas, Catherine E Ingle, Claude Beazley, Webb Miller, Matthew E Hurles, Emmanouil T Dermitzakis
Genome Biology , 2007, DOI: 10.1186/gb-2007-8-6-r118
Abstract: Here we identify 1,356 CNC sequences that appear to have undergone dramatic human-specific changes in selective pressures, at least 15% of which have substitution rates significantly above that expected under neutrality. The 1,356 'accelerated CNC' (ANC) sequences are enriched in recent segmental duplications, suggesting a recent change in selective constraint following duplication. In addition, single nucleotide polymorphisms within ANC sequences have a significant excess of high frequency derived alleles and high FSTvalues relative to controls, indicating that acceleration and positive selection are recent in human populations. Finally, a significant number of single nucleotide polymorphisms within ANC sequences are associated with changes in gene expression. The probability of variation in an ANC sequence being associated with a gene expression phenotype is fivefold higher than variation in a control CNC sequence.Our analysis suggests that ANC sequences have until very recently played a role in human evolution, potentially through lineage-specific changes in gene regulation.The manner in which the expression of genes is regulated defines and determines many of the cellular and developmental processes in an organism. It has been hypothesized that variation in gene regulation is responsible for much of the phenotypic diversity within and between species [1]. In particular, it was proposed a few decades ago that the phenotypic divergence between human and chimpanzees is largely due to changes in gene regulation rather than changes in the protein-coding sequences of genes [2]. Although it has been long recognized that regulatory sequences play an important role in genome function, the fine structure and evolutionary patterns of such sequences are not well understood [3], mainly because such sequences have a much more complex functional code and appear not to be restricted to particular sequence motifs. One of the most powerful approaches with which to identify regula
A Genome-Wide Assessment of the Role of Untagged Copy Number Variants in Type 1 Diabetes
Manuela Zanda,Suna Onengut-Gumuscu,Neil Walker,Corina Shtir,Daniel Gallo,Chris Wallace,Deborah Smyth,John A. Todd,Matthew E. Hurles,Vincent Plagnol ,Stephen S. Rich
PLOS Genetics , 2014, DOI: doi/10.1371/journal.pgen.1004367
Abstract: Genome-wide association studies (GWAS) for type 1 diabetes (T1D) have successfully identified more than 40 independent T1D associated tagging single nucleotide polymorphisms (SNPs). However, owing to technical limitations of copy number variants (CNVs) genotyping assays, the assessment of the role of CNVs has been limited to the subset of these in high linkage disequilibrium with tag SNPs. The contribution of untagged CNVs, often multi-allelic and difficult to genotype using existing assays, to the heritability of T1D remains an open question. To investigate this issue, we designed a custom comparative genetic hybridization array (aCGH) specifically designed to assay untagged CNV loci identified from a variety of sources. To overcome the technical limitations of the case control design for this class of CNVs, we genotyped the Type 1 Diabetes Genetics Consortium (T1DGC) family resource (representing 3,903 transmissions from parents to affected offspring) and used an association testing strategy that does not necessitate obtaining discrete genotypes. Our design targeted 4,309 CNVs, of which 3,410 passed stringent quality control filters. As a positive control, the scan confirmed the known T1D association at the INS locus by direct typing of the 5′ variable number of tandem repeat (VNTR) locus. Our results clarify the fact that the disease association is indistinguishable from the two main polymorphic allele classes of the INS VNTR, class I-and class III. We also identified novel technical artifacts resulting into spurious associations at the somatically rearranging loci, T cell receptor, TCRA/TCRD and TCRB, and Immunoglobulin heavy chain, IGH, loci on chromosomes 14q11.2, 7q34 and 14q32.33, respectively. However, our data did not identify novel T1D loci. Our results do not support a major role of untagged CNVs in T1D heritability.
Breaking the waves: improved detection of copy number variation from microarray-based comparative genomic hybridization
John C Marioni, Natalie P Thorne, Armand Valsesia, Tomas Fitzgerald, Richard Redon, Heike Fiegler, T Daniel Andrews, Barbara E Stranger, Andrew G Lynch, Emmanouil T Dermitzakis, Nigel P Carter, Simon Tavaré, Matthew E Hurles
Genome Biology , 2007, DOI: 10.1186/gb-2007-8-10-r228
Abstract: We describe the presence of a genome-wide technical artifact, spatial autocorrelation or 'wave', which occurs in a large dataset used to determine the location of CNV across the genome. By removing this artifact we are able to obtain both a more biologically meaningful clustering of the data and an increase in the number of CNVs identified by current calling methods without a major increase in the number of false positives detected. Moreover, removing this artifact is critical for the development of a novel model-based CNV calling algorithm - CNVmix - that uses cross-sample information to identify regions of the genome where CNVs occur. For regions of CNV that are identified by both CNVmix and current methods, we demonstrate that CNVmix is better able to categorize samples into groups that represent copy number gains or losses.Removing artifactual 'waves' (which appear to be a general feature of array comparative genomic hybridization (aCGH) datasets) and using cross-sample information when identifying CNVs enables more biological information to be extracted from aCGH experiments designed to investigate copy number variation in normal individuals.Copy number variation (CNV) throughout the human genome has recently been the focus of much interest and array comparative genomic hybridization (aCGH) technology has been instrumental in identifying regions of the genome where CNVs occur. It is believed that such variation may explain the presence and development of adverse phenotypes ranging from HIV-1 infection to Alzheimer's and Parkinson's disease [1]. To analyze the experimental aCGH data and to identify the location of CNVs, specific statistical tools for normalization and CNV calling (segmentation) are undergoing continual refinement and development.There are many algorithms [2,3] for segmenting aCGH data into classes with differing numbers of copies. The vast majority of these algorithms identify CNVs by identifying outlier regions within a single genome (cross-gen
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