Genassemblage 2.0 as a tool in optimization and management of genetic variation resources deposited in banks of cryopreserved fish gametes
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1
University of Warmia and Mazury in Olsztyn, Poland
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2
Stanisław Sakowicz Inland Fisheries Institute, Poland
Introduction
Cryopreservation of gametes is used to protect the genetic resources of a fish population (FAO 2012) and to safeguard the level of genetic variability (Yang and Tiersch 2009) in the event of a catastrophe resulting in the extinction of the population. It is used for both endangered fish species and economically valuable breeds and breeding lines (Zhang 2004, Cabrita et al. 2010).
The potential usefulness of cryopreserved gametes in protecting the genetic variability of fish population depends on the genetic diversity of the individuals from which the gametes were collected (FAO 2012). The genetic diversity of a gamete bank can be managed if the genetic profiles of the gamete donors are known and a tool is available to process this information (Kaczmarczyk 2019). To address this problem, we developed a tool that enables management of genetic variation in a gamete bank and added it as a new module for Genassemblage 2.0 software.
Materials
Genassemblage 2.0 is free-of-charge Windows-based program. It is an improved version of Genassemblage 1.0 (Kaczmarczyk 2015) with expanded functionality. Its installer and a detailed user guide can be downloaded from the author’s website. The software requires MS Excel, version 2003 or newer.
The module “Management of genetic variation in gamete bank” is based on allelic diversity across all loci included in genetic profiles. It calculates the overall number of alleles across all loci and indicates which samples should be used to obtain a target percentage of allelic diversity while using as few samples as possible. The input file for this module should include data such as sample name or name of individual, and a list of alleles identified at investigated loci (Fig. 1).
After the user chooses this module and loads the input file, the program will automatically calculate the number of alleles across all samples. In the line “minimum level of genetic variation”, the user should enter the percentage of total genetic variation deposited across all samples and loci that should be in the group of samples chosen by the software. In the example presented below, this value is 100%; as a result, all alleles included in the input file are included in the group of selected samples. Next, the user clicks the “generate output file” button, and the program asks for the name of the output file, then starts calculations.
Results
In the input data presented in Figure 1, Genassemblage 2.0 identified 31 alleles. The output file lists the alleles at each locus, and the alleles across all samples and loci. Transferring 100% of the allelic diversity detected in this group of samples can be done by using 5 out the 24 samples. The names of those samples (A09, A10, A15, A21 and A22) and their genotypes are given below the line with “selected sample” in bold (Fig. 2). Below that, the alleles detected at each locus in these five selected samples are given.
Summary
As these calculations show, it is possible to use a fraction of the samples stored in a gamete bank and transfer the same number of detected alleles as when using all the samples. In this way, Genassemblage 2.0 can be used with the genetic profiles of gamete donors to manage the genetic variation resources deposited in a gamete bank. This method is especially valuable when working with populations of fish in which genetic variation is low and only a small number of individuals differ from the others to a relatively large extent, such as populations of lake minnow, Eupallasella percnurus, one of the most endangered fish species in Poland (Kaczmarczyk and Wolnicki 2016). The method and software presented above can be recommended for conservation of fish populations, including gamete banking, restocking extinct populations and supplementation of populations where genetic variation has decreased as a result of inbreeding or bottleneck.
Acknowledgements
The present studies were carried out within the project No. 2014/15/B/NZ9/05240 granted by the National Science Centre (Poland) for years 2015-2019.
References
Cabrita E., Sarasquete C., Martinez-Paramo S., Robles V., Beirao J., Perez-Cerezales S., Herraez M.P. 2010. Cryopreservation of fish sperm: applications and perspectives. J. Appl. Ichthyol. 26: 623-635.
FAO 2012. Cryoconservation of animal genetic resources. FAO Animal Production and Health Guidelines No. 12, Rome.
Kaczmarczyk D. 2015. Genassemblage software, a tool for management of genetic diversity in human dependent population. Conserv. Gen. Res. 7: 49-51.
Kaczmarczyk D. 2019. Techniques based on the polymorphism of microsatellite DNA as tools for conservation of endangered populations. Appl. Ecol. Env. Res. 17: 1599-1615.
Kaczmarczyk D., Wolnicki J. 2016. Genetic diversity of the endangered cyprinid fish lake minnow Eupallasella percnurus in Poland and its implications for conservation. PLoS One 12: 1-16.
Yang H., Tiersch T. 2009. Current status of sperm cryopreservation in biomedical research fish models: zebrafish, medaka, and xiphophorus. Comp. Biochem. Physiol. 149: 224-232.
Zhang T. 2004. Cryopreservation of gametes and embryos of aquatic species. In: Life in the Frozen State, (Eds) Fuller B., Lane N., Benson E., pp. 415-435. Boca Rosa: CRC Press.
Keywords:
Bioinformatics tool,
Active Protection,
gamete banks,
conservation biology,
Genetic profiles
Conference:
XVI European Congress of Ichthyology, Lausanne, Switzerland, 2 Sep - 6 Sep, 2019.
Presentation Type:
Oral
Topic:
THREATS AND CONSERVATION
Citation:
Kaczmarczyk
D and
Wolnicki
J
(2019). Genassemblage 2.0 as a tool in optimization and management of genetic variation resources deposited in banks of cryopreserved fish gametes.
Front. Mar. Sci.
Conference Abstract:
XVI European Congress of Ichthyology.
doi: 10.3389/conf.fmars.2019.07.00162
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Received:
29 Jul 2019;
Published Online:
30 Jul 2019.
*
Correspondence:
Dr. Dariusz Kaczmarczyk, University of Warmia and Mazury in Olsztyn, Olsztyn, Poland, d.kaczmarczyk@uwm.edu.pl