Mining of microsatellites in mitochondrial genomes of order Hypnales (Bryopsida)

Authors

  • Khushbu Anand 1) Department of Bioinformatics, Central University of South Bihar, Gaya 824236, Bihar, India; 2) Department of Bioscience and Biotechnology, Banasthali Vidyapith, Tonk 304022, Rajasthan, India
  • Sonu Kumar Department of Bioinformatics, Central University of South Bihar, Gaya 824236, Bihar, India
  • Afroz Alam Department of Bioscience and Biotechnology, Banasthali Vidyapith, Tonk 304022, Rajasthan, India
  • Asheesh Shankar Department of Bioinformatics, Central University of South Bihar, Gaya 824236, Bihar, India

DOI:

https://doi.org/10.14719/pst.2019.6.sp1.697

Keywords:

Bryophytes, Hypnales, Microsatellites, Simple Sequence Repeats

Abstract

Microsatellites or SSRs are the markers of selection due to their reproducibility, degree of polymorphism, distribution throughout the genome and co-dominant nature. Microsatellites are used primarily to study the genetic variability in various species and marker aided selection. Since microsatellites can be readily amplified by PCR, they have been utilized most extensively. To reduce time and cost to a great extent, the computational approach for identifying and developing microsatellite markers by mining nucleotide sequences is preferred over the conventional methods. In the present analysis, an in-silico method was used to detect microsatellites effectively in mitochondrial genomes of Anomodon rugelii (Müll. Hal.) Keissl., Anomodon attenuatus (Hedw.) Hueb., Climacium americanum (Renauld & Cardot) Kindberg, and Hypnum imponens Hedw. (Bryopsida; Hypnales). A total of 101 perfect microsatellites were mined with an average density of 1 microsatellite/4.21 kb. The hexa-nucleotide repeats were not detected in mitochondrial genomes of studied taxa. Di-nucleotides were seen to be the most frequent repeats followed by tetra-nucleotides. The identified microsatellites were also checked for variability in length between species. The mined microsatellites will be used for gene tagging, species identification and population genetic studies.

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References

1. Kabra R, Kapil A, Attarwala K, Rai PK, Shanker A. Identification of common, unique and polymorphic microsatellites among 73 cyanobacterial genomes. World J Microbiol Biotechnol. 2016;32:71. https://doi.org/10.1007/s11274-016-2061-0

2. Srivastava D, Shanker A. Identification of simple sequence repeats in chloroplast genomes of Magnoliids through bioinformatics approach. Interdiscip Sci. 2016;8(4):327-36. https://doi.org/10.1007/s12539-015-0129-4

3. Shanker A. Combined data from chloroplast and mitochondrial genome sequences showed paraphyly of bryophytes. Arch Bryol. 2013;171:1-9.

4. Shanker A. Comparison of mitochondrial genomes of bryophytes. Arch Bryol. 2014;142:1-5.

5. Kapil A, Rai PK, Shanker A. ChloroSSRdb: a repository of perfect and imperfect chloroplastic simple sequence repeats (cpSSRs) of green plants. Database (Oxford). 2014;7. https://doi.org/10.1093/database/bau107

6. Kumar M, Kapil A, Shanker A. MitoSatPlant: mitochondrial microsatellites database of Viridiplantae. Mitochondrion. 2014; 19 Pt B: 334-7. https://doi.org/10.1016/j.mito.2014.02.002

7. Shanker A. Combined data from chloroplast and mitochondrial genome sequences showed paraphyly of bryophytes. Arch Bryol. 2013;171:1-9.

8. Shanker A. Computational mining of microsatellites in the chloroplast genome of Ptilidium pulcherrimum, a liverwort. Int J Environment. 2014;3:50-58.

9. Shanker A. Sequenced mitochondrial genomes of bryophytes. Arch Bryol. 2014;146:1-6.

10. Shanker A. Computationally mined microsatellites in chloroplast genome of Pellia endiviifolia. Arch Bryol. 2014;199:1-5.

11. Zhao CX, Zhu RL, Liu Y. Simple sequence repeats in bryophyte mitochondrial genomes. Mitochondrial DNA Pt A. 2016;27:1917. http://doi.org/10.3109/19401736.2014.880889

12. Kumar S, Shanker A. Common, unique and polymorphic simple sequence repeats in chloroplast genomes of genus Arabidopsis. Vegetos. 2018;31(special):125-31. http://doi.org/10.5958/2229-4473.2018.00043.5

13. Tambarussi EV, Melotto-Passarin DM, Gonzalez SG, Brigati JB, de Jesus FA, Barbosa AL, Dressano K, Carrer H. In silico analysis of simple sequence repeats from chloroplast genomes of Solanaceae species. CBAB. 2009;9(4):344-52.

14. Kapil A, Jha CK, Shanker A. Data mining to detect common, unique and polymorphic simple sequence repeats. In Bioinformatics: Sequences, Structures, Phylogeny. A. Shanker (ed.), Springer Singapore; 2018, pp. 141-54. https://doi.org/10.1007/978-981-13-1562-6.7

15. Liu Y, Medina R, Goffinet B. 350 my of mitochondrial genome stasis in mosses, an early land plant lineage. Mol Biol Evol. 2014;31(10):2586-91. https://doi.org/10.1093/molbev/msu199

16. Liu Y, Xue JY, Wang B, Li L, Qiu YL. The mitochondrial genomes of the early land plants Treubia lacunosa and Anomodon rugelii: dynamic and conservative evolution. PLoS One. 2011;6(10):e25836. https://doi.org/10.1371/journal.pone.0025836

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Published

31-12-2019

How to Cite

1.
Anand K, Kumar S, Alam A, Shankar A. Mining of microsatellites in mitochondrial genomes of order Hypnales (Bryopsida). Plant Sci. Today [Internet]. 2019 Dec. 31 [cited 2024 May 4];6(sp1):635-8. Available from: https://horizonepublishing.com/journals/index.php/PST/article/view/697

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