4.2 Article

An algorithm for determining the origin of trisomy and the positions of chiasmata from SNP genotype data

期刊

CHROMOSOME RESEARCH
卷 19, 期 2, 页码 155-163

出版社

SPRINGER
DOI: 10.1007/s10577-010-9181-4

关键词

aneuploidy; recombination; trisomy; meiosis; SNP

资金

  1. BBSRC [BB/E024211/1]
  2. NIH [HD21341]
  3. Biotechnology and Biological Sciences Research Council [BB/E024211/1] Funding Source: researchfish
  4. BBSRC [BB/E024211/1] Funding Source: UKRI

向作者/读者索取更多资源

Trisomy causes mental retardation, pregnancy loss, IVF failure, uniparental disomy and several other pathologies, and its accurate detection is thus clinically essential. Most trisomies arise at meiosis I and are associated with increasing maternal age and reduction or alteration in recombination patterns. Investigations into the relationship between trisomy and meiotic recombination have used short tandem repeat markers; however, this approach is limited by the resolution with which the position of crossovers can identified. As cytogenetics enters the post-genomic era, recent work has used array comparative genomic hybridisation (aCGH) to screen for trisomy of all 24 chromosomes, determining chromosome copy number by dosage analysis. However, aCGH has a fundamental drawback for studying the aetiology of trisomy since neither the parent and phase of origin nor uniparental disomy can be ascertained. The development of SNP microarrays has made it possible to analyse multiple loci for sequence variation, and the proprietary software provided can determine the presence of aneuploidy by algorithms based on fluorescence intensity. To the best of our knowledge, however, such software is not equipped to determine the phase of origin of the error or the position of any chiasmata. In this study, therefore, we present an algorithm to determine the parent of origin, the phase of origin and the location of chiasmata in a series of nine trisomy triplets (i.e. samples derived from father, mother and their trisomic foetus). Novel adaptations of well-established principles are applied along with a simple algorithm written in Microsoft Excel for visualisation of the results. Such analysis has a range of applications in preimplantation and prenatal diagnosis.

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