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Theoretical and Applied Genetics

, Volume 110, Issue 3, pp 492–510 | Cite as

Construction of BAC and BIBAC libraries and their applications for generation of SSR markers for genome analysis of chickpea, Cicer arietinum L.

  • J. Lichtenzveig
  • C. Scheuring
  • J. Dodge
  • S. Abbo
  • H.-B. Zhang
Original Paper

Abstract

Large-insert bacterial artificial chromosome (BAC) libraries, plant-transformation-competent binary BAC (BIBAC) libraries, and simple sequence repeat (SSR) markers are essential for many aspects of genomics research. We constructed a BAC library and a BIBAC library from the nuclear DNA of chickpea, Cicer arietinum L., cv. Hadas, partially digested with HindIII and BamHI, respectively. The BAC library has 14,976 clones, with an average insert size of 121 kb, and the BIBAC library consists of 23,040 clones, with an average insert size of 145 kb. The combined libraries collectively cover ca. 7.0× genomes of chickpea. We screened the BAC library with eight synthetic SSR oligos, (GA)10, (GAA)7, (AT)10, (TAA)7, (TGA)7, (CA)10, (CAA)7, and (CCA)7. Positive BACs were selected, subcloned, and sequenced for SSR marker development. Two hundred and thirty-three new chickpea SSR markers were developed and characterized by PCR, using chickpea DNA as template. These results have demonstrated that BACs are an excellent source for SSR marker development in chickpea. We also estimated the distribution of the SSR loci in the chickpea genome. The SSR motifs (TAA) n and (GA) n were much more abundant than the others, and the distribution of the SSR loci appeared non-random. The BAC and BIBAC libraries and new SSR markers will provide valuable resources for chickpea genomics research and breeding (the libraries and their filters are available to the public at http://hbz.tamu.edu).

Keywords

Bacterial Artificial Chromosome Simple Sequence Repeat Marker Bacterial Artificial Chromosome Clone Bacterial Artificial Chromosome Library Simple Sequence Repeat Locus 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

This research was supported by Research Grant Award No. US-3034-98R from BARD, the United States–Israel Binational Agricultural Research and Development Fund. The authors would like to thank the Texas A&M University GENE finder Genomic Resources for their assistance in preparing the library filters, and Haddassa VanOss, the Hebrew University in Jerusalem, for her assistance in evaluating the SSR primers.

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Copyright information

© Springer-Verlag 2004

Authors and Affiliations

  • J. Lichtenzveig
    • 1
    • 3
    • 4
  • C. Scheuring
    • 2
  • J. Dodge
    • 2
  • S. Abbo
    • 1
  • H.-B. Zhang
    • 2
  1. 1.Institute of Plant Science and Genetics in AgricultureThe Hebrew University of JerusalemRehovotIsrael
  2. 2.Department of Soil and Crop Sciences and Institute for Plant Genomics and BiotechnologyTexas A&M UniversityCollege StationUSA
  3. 3.ACNFP at Murdoch UniversityMurdochAustralia
  4. 4.CSIRO Plant IndustryWembleyAustralia

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