Activities

The major activities of the Centre of Excellence for Biodiversity and Molecular Plant Breeding are the following:

(1) Conservation of Plant Genetic Resources

In last five decades many efforts have been made with the aim of conservation of plant genetic resources in Croatia. The activities including collection, characterization, maintenance and regeneration of plant genetic resources are implemented in the National Programme for the Conservation and Sustainable Use of Plant Genetic Resources for Food and Agriculture. However, due to limited budget and numerous collections, the financial support for characterization and evaluation of accessions at agronomic, biochemical and genetic level is far from being sufficient. Thus, the utilization of accessions in plant breeding is limited. The Centre of Excellence for Biodiversity and Molecular Plant Breeding aims at creating a strong link between germplasm collections, scientific research and breeding programs.

Major objectives of the activities that will be carried are the following:

  1. Further characterization and evaluation of plant genetic resources
  2. Increase of benefits arising out of use of plant genetic resources for food and agriculture

 

 

(2) Phenotyping

Plant phenotyping presents one of the most important bottlenecks in plant science and plant breeding, and their further progress demands interdisciplinary approach and integration of transdisciplinary activities from different fields such as plant physiology, sensorics and bioinformatics. Realized progress in high-throughput and high-defining plant genotyping provides the genomic information in very short time and at reasonable costs, which at the end enables development of a larger number of mapping populations and inbred lines for phenotyping. However, our understanding of the relationship between genotype and phenotype progresses very slowly due to limitations that exist in plant phenotyping thus decreasing our capabilities in dissecting heritability and genetic architecture of quantitative traits.

It is well-known fact that soil heterogeneity and our inability to control climatic factors makes difficult to interpret the experimental results. Moreover, information acquired from controlled environments is not readily comparable with those from field. Thus, it would not be possible without efficient platforms and methods for fast, high-throughput, simple and cheap phenotyping neither better biological understanding of the links between genotype and phenotype nor further increase of rate of genetic gain in plant breeding.

We can expect that further improvements in phenotyping and good laboratory practice will be directed toward increase in precision and pyramiding the information from all levels (different traits measured at different time and variable space, environmental and genomic information). Besides the use of different devices for phenotyping different key traits and designs of experiments with the purpose of controlling soil heterogeneity it is necessary to have the adequate integration of different types of data and their simple, quick and robust statistical analysis.

Major objectives of the activities that will be carried out are the following:

  1. Identify and analyse key traits of eight model plant species through field experiments and laboratory analysis,
  2. Optimize protocols from phenotyping procedures and good laboratory practice to experimental designs including interpretation of results,
  3. Establish links with key institutions from EU possessing infrastructure for a high-throughput phenotyping (HTP) platforms, and
  4. Compare results from the experiments from high-throughput phenotyping (HTP) controlled environments with those from field experiments with the purpose of evaluating the genotype (G), the environment (E) and their interaction (G×E) effects.

 

(3) Genotyping

Genotyping techniques are improved tremendously in the past decade, although there are still substantial differences in developing of genotyping procedures across the plant species. Nevertheless, high-throughput genotyping has revolutionized genetic analyses covering genomes with high resolution, generally switching from microsatellite (simple sequence repeats; SSRs) marker system to DArT and SNP marker systems. SSRs found the widest application in assessing the variability and genetic structure of populations in a variety of plants. The traditional method of developing SSRs requires considerable resources, but it is still commonly used in most laboratories worldwide. Genotyping facilities in Croatia used also mostly SSRs as a technically non-demanding marker system. The genotyping labs in Croatia are not interconnected and there is no continuous cooperation among them where strengths, weaknesses, opportunities and threats of each genotyping facility are not known.

Compared to other marker systems, SNPs are less labour intensive and less time-consuming, and the associated costs allow performing high-throughput genotyping. SNPs markers are biallelic, have lower information content than polyallelic SSR markers, but they occur at much higher density in genome, and have lower genotyping error rate. Recently, SNPs are being used to design genotyping arrays containing thousands and tens of thousands of markers spread over the entire genome to analyse large numbers of samples. Array-based SNP genotyping facilitates the detection of associations between the markers and phenotypes representing a powerful tool for dissecting complex traits via genome-wide association studies (GWAS) or quantitative trait locus (QTL) analysis as well as for fine mapping genes of interest which are largely used in plant breeding for germplasm characterization and marker assisted selection. Although array-based genotyping is becoming an advanced genotyping method of choice in major crops, novel genotyping by sequencing (GBS) method makes use of ultra high-throughput, short-read sequencing to provide lower cost genotyping with much higher information content. Several genotyping platforms appeared in the last years for crop genotyping which had been developed in the EU and the USA using SNPs for both array-based and GBS genotyping offering reliable high-density genotyping solutions in biodiversity studies and molecular plant breeding.

Major objectives of the activities that will be carried out are the following:

  1. To optimize genotyping protocols introducing common standardized lab and analysis procedures,
  2. To connect with the key genotyping facilities in the EU which design and develop state-of-the-art genotyping platforms, and
  3. To evaluate and compare new genotyping platforms to eventually utilize them routinely according to the specific developments in each of the species.

 

(4) Bioinformatics

In the past, common strategy to deal with the large data sets was the acquisition of powerful servers with high processing capacity. In a present day, due to rapid development of technology, any server will soon become dwarfed by just an ordinary PC. Therefore, the approach to this problem is shifted towards connecting a mass of standard computers into cluster whose performance is superior to a single powerful computer. Constant and rapid development of molecular genetic technology causes frequent shift in the approach to the research in the field of life sciences. Among other, development of new techniques speeds up data generation, thus setting up challenging demands in data processing, regards the quality control and analysis of big data sets. Meeting these ever-increasing demands requires the application of robust, efficient and fast-operating statistical tools. In order to achieve a successful collaboration between five self-contained institutions, dislocated resources will be connected by establishing the collaborative repository for data storage and information exchange. High computational demands have already created the need to relocate more demanding data processing operations to the “statistical” server acquired by University of Zagreb, Faculty of Agriculture, and recently, to University Computing Centre (SRCE) “Isabella” computational cluster. For further improvement of communication and information exchange, it is necessary to develop the user-friendly interface, as a gateway for an easy access to data queries and result reports. The main platform for data processing will be the “Isabella” cluster, because its availability and continuous expansion guarantee the full coverage of our needs.

Major objectives of the activities that will be carried out are the following:

  1. Set up a cloud storage as a collaborative repository for data collection and information exchange between five institutions involved in the project,
  2. Relocate the data management and analysis processes from servers and PCs to computer clusters, in order to comply with the increasing demands for computing power when handling big data sets.
  3. Implement novel statistical methodology.

 

(5) Dissemination

The goal is to communicate the activities of the CoE with scientific and other groups. The different channels will be used to share the information according to planned activities. The partners involved in the CoE represent a multidisciplinary group including universities and research institutes, therefore, the mutual communication and dissemination of the achievements is essential. That will be accomplished by organization of annual meetings with intention to present obtained results and discuss the next goals to be accomplished. Overall activities will be presented by creating and maintaining web page at the host institution.

The target groups that we plan to communicate with are: TG1 Academia (scientific community, students), TG2 Farmers and entrepreneurs in agriculture, and TG3 General public.

 

(6) Management

Major objectives of the activities that will be carried out are the following:

  1. To coordinate initiatives and activities among the Working Groups in order to optimally use existing capacities and thus avoiding unnecessary additional costs,
  2. To facilitate the transfer of ideas, information and knowledge among all collaborators,

3. To analyse strengths, weaknesses, opportunities and threats of each available phenotyping and genotyping facility within the CoE.