Dataset Information

Identification of both copy number variation-type and constant-type core elements in a large segmental duplication region of the mouse genome.

ABSTRACT:

Background

Copy number variation (CNV), an important source of diversity in genomic structure, is frequently found in clusters called CNV regions (CNVRs). CNVRs are strongly associated with segmental duplications (SDs), but the composition of these complex repetitive structures remains unclear.

Results

We conducted self-comparative-plot analysis of all mouse chromosomes using the high-speed and large-scale-homology search algorithm SHEAP. For eight chromosomes, we identified various types of large SD as tartan-checked patterns within the self-comparative plots. A complex arrangement of diagonal split lines in the self-comparative-plots indicated the presence of large homologous repetitive sequences. We focused on one SD on chromosome 13 (SD13M), and developed SHEPHERD, a stepwise ab initio method, to extract longer repetitive elements and to characterize repetitive structures in this region. Analysis using SHEPHERD showed the existence of 60 core elements, which were expected to be the basic units that form SDs within the repetitive structure of SD13M. The demonstration that sequences homologous to the core elements (>70% homology) covered approximately 90% of the SD13M region indicated that our method can characterize the repetitive structure of SD13M effectively. Core elements were composed largely of fragmented repeats of a previously identified type, such as long interspersed nuclear elements (LINEs), together with partial genic regions. Comparative genome hybridization array analysis showed that whereas 42 core elements were components of CNVR that varied among mouse strains, 8 did not vary among strains (constant type), and the status of the others could not be determined. The CNV-type core elements contained significantly larger proportions of long terminal repeat (LTR) types of retrotransposon than the constant-type core elements, which had no CNV. The higher divergence rates observed in the CNV-type core elements than in the constant type indicate that the CNV-type core elements have a longer evolutionary history than constant-type core elements in SD13M.

Conclusions

Our methodology for the identification of repetitive core sequences simplifies characterization of the structures of large SDs and detailed analysis of CNV. The results of detailed structural and quantitative analyses in this study might help to elucidate the biological role of one of the SDs on chromosome 13.

SUBMITTER: Umemori J

PROVIDER: S-EPMC3722088 | biostudies-literature | 2013 Jul

REPOSITORIES: biostudies-literature

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Publications

Identification of both copy number variation-type and constant-type core elements in a large segmental duplication region of the mouse genome.

Umemori Juzoh J Mori Akihiro A Ichiyanagi Kenji K Uno Takeaki T Koide Tsuyoshi T

BMC genomics 20130708

<h4>Background</h4>Copy number variation (CNV), an important source of diversity in genomic structure, is frequently found in clusters called CNV regions (CNVRs). CNVRs are strongly associated with segmental duplications (SDs), but the composition of these complex repetitive structures remains unclear.<h4>Results</h4>We conducted self-comparative-plot analysis of all mouse chromosomes using the high-speed and large-scale-homology search algorithm SHEAP. For eight chromosomes, we identified vario ...[more]

PMID: 23834397

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Project description:BackgroundSegmental duplications (SD) have been found in genomes of various organisms, often accumulated at the ends of chromosomes. It has been assumed that the sequence homology in-between the SDs allow for ectopic interactions that may contribute to the emergence of new genes or gene variants through recombinatorial events.MethodsIn silico analysis of the 3D7 Plasmodium falciparum genome, conducted to investigate the subtelomeric compartments, led to the identification of subtelomeric SDs. Sequence variation and copy number polymorphisms of the SDs were studied by DNA sequencing, real-time quantitative PCR (qPCR) and fluorescent in situ hybridization (FISH). The levels of transcription and the developmental expression of copy number variant genes were investigated by qPCR.ResultsA block of six genes of >10 kilobases in size, including var, rif, pfmc-2tm and three hypothetical genes (n-, o- and q-gene), was found duplicated in the subtelomeric regions of chromosomes 1, 2, 3, 6, 7, 10 and 11 (SD1). The number of SD1 per genome was found to vary from 4 to 8 copies in between different parasites. The intragenic regions of SD1 were found to be highly conserved across ten distinct fresh and long-term cultivated P. falciparum. Sequence variation was detected in a approximately 23 amino-acid long hypervariable region of a surface-exposed loop of PFMC-2TM. A hypothetical gene within SD1, the n-gene, encoding a PEXEL/VTS-containing two-transmembrane protein was found expressed in ring stage parasites. The n-gene transcription levels were found to correlate to the number of n-gene copies. Fragments of SD1 harbouring two or three of the SD1-genes (o-gene, pfmc-2tm, q-gene) were also found in the 3D7 genome. In addition a related second SD, SD2, of approximately 55% sequence identity to SD1 was found duplicated in a fresh clinical isolate but was only present in a single copy in 3D7 and in other P. falciparum lines or clones.ConclusionPlasmodium falciparum carries multiple sequence conserved SDs in the otherwise highly variable subtelomeres of its chromosomes. The uniqueness of the SDs amongst plasmodium species, and the conserved nature of the genes within, is intriguing and suggests an important role of the SD to P. falciparum.

Project description:The human genome contains numerous blocks of highly homologous duplicated sequence. This higher-order architecture provides a substrate for recombination and recurrent chromosomal rearrangement associated with genomic disease. However, an assessment of the role of segmental duplications in normal variation has not yet been made. On the basis of the duplication architecture of the human genome, we defined a set of 130 potential rearrangement hotspots and constructed a targeted bacterial artificial chromosome (BAC) microarray (with 2,194 BACs) to assess copy-number variation in these regions by array comparative genomic hybridization. Using our segmental duplication BAC microarray, we screened a panel of 47 normal individuals, who represented populations from four continents, and we identified 119 regions of copy-number polymorphism (CNP), 73 of which were previously unreported. We observed an equal frequency of duplications and deletions, as well as a 4-fold enrichment of CNPs within hotspot regions, compared with control BACs (P < .000001), which suggests that segmental duplications are a major catalyst of large-scale variation in the human genome. Importantly, segmental duplications themselves were also significantly enriched >4-fold within regions of CNP. Almost without exception, CNPs were not confined to a single population, suggesting that these either are recurrent events, having occurred independently in multiple founders, or were present in early human populations. Our study demonstrates that segmental duplications define hotspots of chromosomal rearrangement, likely acting as mediators of normal variation as well as genomic disease, and it suggests that the consideration of genomic architecture can significantly improve the ascertainment of large-scale rearrangements. Our specialized segmental duplication BAC microarray and associated database of structural polymorphisms will provide an important resource for the future characterization of human genomic disorders.

Dataset Information

Identification of both copy number variation-type and constant-type core elements in a large segmental duplication region of the mouse genome.

Background

Results

Conclusions

Publications

Identification of both copy number variation-type and constant-type core elements in a large segmental duplication region of the mouse genome.

Similar Datasets

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