Computational Mining and Genome Wide Distribution of Microsatellite in Fusarium oxysporum f. sp. lycopersici

Authors

  • Sudheer KUMAR National Bureau of Agriculturally Important Microorganisms (IN)
  • Deepak MAURYA National Bureau of Agriculturally Important Microorganisms (NBAIM), Mau, Uttar Pradesh, 275101 (IN)
  • Shalini RAI National Bureau of Agriculturally Important Microorganisms (NBAIM), Mau, Uttar Pradesh, 275101 (IN)
  • Prem Lal KASHYAP National Bureau of Agriculturally Important Microorganisms (NBAIM), Mau, Uttar Pradesh, 275101 (IN)
  • Alok Kumar SRIVASTAVA National Bureau of Agriculturally Important Microorganisms (NBAIM), Mau, Uttar Pradesh, 275101 (IN)

DOI:

https://doi.org/10.15835/nsb448271

Abstract

Simple sequence repeat (SSR) is currently the most preferred molecular marker system owing to their highly desirable properties viz., abundance, hyper-variability, and suitability for high-throughput analysis. Hence, in present study an attempt was made to mine and analyze microsatellite dynamics in whole genome of Fusarium oxysporum f. sp. lycopersici. The distribution pattern of different SSR motifs provides the evidence of greater accumulation of tetra-nucleotide (3837) repeats followed by tri-nucleotide (3367) repeats. Maximum frequency distribution in coding region was shown by mono-nucleotide SSR motifs (34.8%), where as minimum frequency is observed for penta-nucleotide SSR (0.87%). Highest relative abundance (1023 SSR/Mb) and density of SSRs (114.46 bp/Mb) were observed on chromosome 1, while least density of SSR motifs was recorded on chromosome 11 (7.40 bp/Mb) and 12 (7.41 bp/Mb), respectively. Maximum trinucleotide (34.24%) motifs code for glutamic acid (GAA) while GT/CT were the most frequent repeat of dinucleotide SSRs. Most common and highly repeated SSR motifs were identified as (A)64, (T)48, (GT)24, (GAA)31, (TTTC)24, (TTTCT)28 and (AACCAG)27. Overall, the generated information may serve as baseline information for developing SSR markers that could find applications in genomic analysis of F. oxysporum f. sp. lycopersici for better understanding of evolution, diversity analysis, population genetics, race identification and acquisition of new virulence.

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Author Biography

Sudheer KUMAR, National Bureau of Agriculturally Important Microorganisms

National Bureau of Agriculturally Important Microorganisms (NBAIM), Mau, Uttar Pradesh, India 275101

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Published

2012-11-06

How to Cite

KUMAR, S., MAURYA, D., RAI, S., KASHYAP, P. L., & SRIVASTAVA, A. K. (2012). Computational Mining and Genome Wide Distribution of Microsatellite in Fusarium oxysporum f. sp. lycopersici. Notulae Scientia Biologicae, 4(4), 127–131. https://doi.org/10.15835/nsb448271

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Section

Research articles
CITATION
DOI: 10.15835/nsb448271

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