Blog
About

19
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Characterization of the ovine ribosomal protein SA gene and its pseudogenes

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          The ribosomal protein SA (RPSA), previously named 37-kDa laminin receptor precursor/67-kDa laminin receptor (LRP/LR) is a multifunctional protein that plays a role in a number of pathological processes, such as cancer and prion diseases. In all investigated species, RPSA is a member of a multicopy gene family consisting of one full length functional gene and several pseudogenes. Therefore, for studies on RPSA related pathways/pathologies, it is important to characterize the whole family and to address the possible function of the other RPSA family members. The present work aims at deciphering the RPSA family in sheep.

          Results

          In addition to the full length functional ovine RPSA gene, 11 other members of this multicopy gene family, all processed pseudogenes, were identified. Comparison between the RPSA transcript and these pseudogenes shows a large variety in sequence identities ranging from 99% to 74%. Only one of the 11 pseudogenes, i.e. RPSAP7, shares the same open reading frame (ORF) of 295 amino acids with the RPSA gene, differing in only one amino acid. All members of the RPSA family were annotated by comparative mapping and fluorescence in situ hybridization (FISH) localization. Transcription was investigated in the cerebrum, cerebellum, spleen, muscle, lymph node, duodenum and blood, and transcripts were detected for 6 of the 11 pseudogenes in some of these tissues.

          Conclusions

          In the present work we have characterized the ovine RPSA family. Our results have revealed the existence of 11 ovine RPSA pseudogenes and provide new data on their structure and sequence. Such information will facilitate molecular studies of the functional RPSA gene taking into account the existence of these pseudogenes in the design of experiments. It remains to be investigated if the transcribed members are functional as regulatory non-coding RNA or as functional proteins.

          Related collections

          Most cited references 41

          • Record: found
          • Abstract: found
          • Article: not found

          Basic local alignment search tool.

          A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score. Recent mathematical results on the stochastic properties of MSP scores allow an analysis of the performance of this method as well as the statistical significance of alignments it generates. The basic algorithm is simple and robust; it can be implemented in a number of ways and applied in a variety of contexts including straightforward DNA and protein sequence database searches, motif searches, gene identification searches, and in the analysis of multiple regions of similarity in long DNA sequences. In addition to its flexibility and tractability to mathematical analysis, BLAST is an order of magnitude faster than existing sequence comparison tools of comparable sensitivity.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Primer3 on the WWW for general users and for biologist programmers.

             H Skaletsky,  S Rozen (1999)
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              CAP3: A DNA sequence assembly program.

               X. Huang (1999)
              We describe the third generation of the CAP sequence assembly program. The CAP3 program includes a number of improvements and new features. The program has a capability to clip 5' and 3' low-quality regions of reads. It uses base quality values in computation of overlaps between reads, construction of multiple sequence alignments of reads, and generation of consensus sequences. The program also uses forward-reverse constraints to correct assembly errors and link contigs. Results of CAP3 on four BAC data sets are presented. The performance of CAP3 was compared with that of PHRAP on a number of BAC data sets. PHRAP often produces longer contigs than CAP3 whereas CAP3 often produces fewer errors in consensus sequences than PHRAP. It is easier to construct scaffolds with CAP3 than with PHRAP on low-pass data with forward-reverse constraints.
                Bookmark

                Author and article information

                Journal
                BMC Genomics
                BMC Genomics
                BioMed Central
                1471-2164
                2010
                16 March 2010
                : 11
                : 179
                Affiliations
                [1 ]Department of Nutrition, Genetics and Ethology, Faculty of Veterinary Medicine, Ghent University, Heidestraat 19, B-9820 Merelbeke, Belgium
                [2 ]Departamento de Mejora Genética Animal, INIA, Ctra La Coruña Km 7.5, Madrid 28040, Spain
                [3 ]INRA, UMR 1313 Génétique Animale et Biologie Intégrative, F78350 Jouy-en-Josas, France
                1471-2164-11-179
                10.1186/1471-2164-11-179
                2850357
                20233419
                Copyright ©2010 Van den Broeke et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                Categories
                Research Article

                Genetics

                Comments

                Comment on this article