Literature DB >> 9149943

Low frequency of microsatellites in the avian genome.

C R Primmer1, T Raudsepp, B P Chowdhary, A P Møller, H Ellegren.   

Abstract

A better insight into the occurrence of microsatellites in a range of taxa may help to understand the evolution of simple repeats. Previous studies have found the relative abundance of several repeat motifs to differ among mammals, invertebrates, and plants. Absolute numbers of microsatellites also tend to correlate positively with genome size. We analyzed the occurrence, frequency, and distribution of microsatellites in birds, a taxon with one of the smallest known genome sizes among vertebrates. Dot-blot hybridization revealed that about half of 22 different di-, tri-, and tetranucleotide repeat motifs were clearly more common in human than in three species of birds: chicken, woodpecker, and swallow. For the remaining motifs no clear difference was found. From searching avian database sequences we estimated there to be 30,000-70,000 microsatellites longer than 20 bp in the avian genome. The number of (CA) > or = 10 would be around 7000-9000 and the number of (CA) > or = 14 about 3000. The calculated density of avian microsatellites (total, one every 20-39 kb; (CA) > or = 10, one every 136-150 kb) is much lower than that estimated for the human genome (one every 6 and 30 kb, respectively). This may be explained by the fact that the avian genome contains relatively less noncoding DNA than most mammals and that avian SINE/LINE elements do not terminate in poly(A) tails, which are known to provide a resource for the evolution of simple repeats in mammals. We found no association between microsatellites and SINEs in birds. Primed in situ labeling suggested fairly even distribution of (CA)n repeats over chicken macrochromosomes and intermediate chromosomes, whereas the microchromosomes, a large part of the Z and W chromosomes, and most telomeres and centromeres had very low concentrations of (CA)n microsatellites. The scarcity of microsatellites on the microchromosomes is compatible to these regions likely being unusually rich in coding sequences. The low microsatellite density in the genome in general and on the microchromosomes in particular imposes an obstacle for the development of marker-rich genetic maps of chicken and other birds, and for the localization of quantitative trait genes.

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Year:  1997        PMID: 9149943     DOI: 10.1101/gr.7.5.471

Source DB:  PubMed          Journal:  Genome Res        ISSN: 1088-9051            Impact factor:   9.043


  46 in total

1.  A consensus linkage map of the chicken genome.

Authors:  M A Groenen; H H Cheng; N Bumstead; B F Benkel; W E Briles; T Burke; D W Burt; L B Crittenden; J Dodgson; J Hillel; S Lamont; A P de Leon; M Soller; H Takahashi; A Vignal
Journal:  Genome Res       Date:  2000-01       Impact factor: 9.043

2.  Arrangements of macro- and microchromosomes in chicken cells.

Authors:  F A Habermann; M Cremer; J Walter; G Kreth; J von Hase; K Bauer; J Wienberg; C Cremer; T Cremer; I Solovei
Journal:  Chromosome Res       Date:  2001       Impact factor: 5.239

3.  Addressing fluorogenic real-time qPCR inhibition using the novel custom Excel file system 'FocusField2-6GallupqPCRSet-upTool-001' to attain consistently high fidelity qPCR reactions.

Authors:  Jack M Gallup; Mark R Ackermann
Journal:  Biol Proced Online       Date:  2006-09-15       Impact factor: 3.244

4.  Phylogenomics of nonavian reptiles and the structure of the ancestral amniote genome.

Authors:  Andrew M Shedlock; Christopher W Botka; Shaying Zhao; Jyoti Shetty; Tingting Zhang; Jun S Liu; Patrick J Deschavanne; Scott V Edwards
Journal:  Proc Natl Acad Sci U S A       Date:  2007-02-16       Impact factor: 11.205

Review 5.  Mutational dynamics of microsatellites.

Authors:  Atul Bhargava; F F Fuentes
Journal:  Mol Biotechnol       Date:  2010-03       Impact factor: 2.695

6.  Characterization and chromosomal distribution of novel satellite DNA sequences of the lesser rhea (Pterocnemia pennata) and the greater rhea (Rhea americana).

Authors:  Kazuhiko Yamada; Chizuko Nishida-Umehara; Yoichi Matsuda
Journal:  Chromosome Res       Date:  2002       Impact factor: 5.239

Review 7.  Rapid and cost-effective screening of newly identified microsatellite loci by high-resolution melting analysis.

Authors:  Wolfgang Arthofer; Florian M Steiner; Birgit C Schlick-Steiner
Journal:  Mol Genet Genomics       Date:  2011-08-17       Impact factor: 3.291

8.  The 'PREXCEL-Q Method' for qPCR.

Authors:  Jack M Gallup; Mark R Ackermann
Journal:  Int J Biomed Sci       Date:  2008-12-15

9.  Rapid microsatellite isolation from a butterfly by de novo transcriptome sequencing: performance and a comparison with AFLP-derived distances.

Authors:  Alexander S Mikheyev; Tanya Vo; Brian Wee; Michael C Singer; Camille Parmesan
Journal:  PLoS One       Date:  2010-06-18       Impact factor: 3.240

10.  A first-generation microsatellite-based genetic linkage map of the Siberian jay (Perisoreus infaustus): insights into avian genome evolution.

Authors:  Sonja Jaari; Meng-Hua Li; Juha Merilä
Journal:  BMC Genomics       Date:  2009-01-03       Impact factor: 3.969

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