Biology subjects

Bancic, J.

Publications and source records attributed to Bancic, J..

3 recordsLinked to original sources

bioRxiv2023

Plant breeding simulations with AlphaSimR

Plant breeding plays a crucial role in the development of high-performing crop varieties that meet the demands of society. Emerging breeding techniques offer the potential to improve the precision and efficiency of plant breeding programs; however, their optimal implementation requires refinement of existing breeding programs or the design of new ones. Stochastic simulations are a cost-effective solution for testing and optimizing new breeding strategies. The aim of this paper is to provide an introduction to stochastic simulation with software AlphaSimR for plant breeding students, researchers, and experienced breeders. We present an overview of how to use the software and provide an introductory AlphaSimR vignette as well as complete AlphaSimR scripts of breeding programs for self-pollinated, clonal, and cross-pollinated plants, including relevant breeding techniques, such as backcrossing, speed breeding, genomic selection, index selection, and others. Our objective is to provide a foundation for understanding and utilizing simulation software, enabling readers to adapt the provided scripts for their own use or even develop completely new plant breeding programs. By incorporating simulation software into plant breeding education and practice, the next generation of plant breeders will have a valuable tool in their quest to provide sustainable and nutritious food sources for a growing population.

genetics↗

bioRxiv2021

Genomic and phenotypic characterization of finger millet indicates a complex diversification history

Advances in sequencing technologies mean that insights into crop diversification aiding future breeding can now be explored in crops beyond major staples. For the first time, we use a genome assembly of finger millet, an allotetraploid orphan crop, to analyze DArTseq single nucleotide polymorphisms (SNPs) at the sub-genome level. A set of 8,778 SNPs and 13 agronomic traits characterizing a broad panel of 423 landrace accessions from Africa and Asia suggested the crop has undergone complex, context-specific diversification consistent with a long domestication history. Both Principal Component Analysis and Discriminant Analysis of Principal Components of SNPs indicated four groups of accessions that coincided with the principal geographic areas of finger millet cultivation. East Africa, the considered origin of the crop, appeared the least genetically diverse. A Principal Component Analysis of phenotypic data also indicated clear geographic differentiation, but different relationships among geographic areas than genomic data. Neighbour-joining trees of sub-genomes A and B showed different features which further supported the crops complex evolutionary history. Our genome-wide association study indicated only a small number of significant marker-trait associations. We applied then clustering to marker effects from a ridge regression model for each trait which revealed two clusters of different trait complexity, with days to flowering and threshing percentage among simple traits, and finger length and grain yield among more complex traits. Our study provides comprehensive new knowledge on the distribution of genomic and phenotypic variation in finger millet, supporting future breeding intra- and inter-regionally across its major cultivation range. Core ideasO_LI8,778 SNPs and 13 agronomic traits characterized a panel of 423 finger millet landraces. C_LIO_LI4 clusters of accessions coincided with major geographic areas of finger millet cultivation. C_LIO_LIA comparison of phenotypic and genomic data indicated a complex diversification history. C_LIO_LIThis was confirmed by the analysis of allotetraploid finger millets separate sub-genomes. C_LIO_LIComprehensive new knowledge for intra- and inter-regional breeding is provided. C_LI

genetics↗

bioRxiv2020

Modelling illustrates that genomic selection provides new opportunities for intercrop breeding

Intercrop breeding programs using genomic selection can produce faster genetic gain than intercrop breeding programs using phenotypic selection. Intercropping is an agricultural practice in which two or more component crops are grown together. It can lead to enhanced soil structure and fertility, improved weed suppression, and better control of pests and diseases. Especially in subsistence agriculture, intercropping has great potential to optimise farming and increase profitability. However, breeding for intercrop varieties is complex as it requires simultaneous improvement of two or more component crops that combine well in the field. We hypothesize that genomic selection can significantly simplify and accelerate the process of breeding crops for intercropping. Therefore, we used stochastic simulation to compare four different intercrop breeding programs implementing genomic selection and an intercrop breeding program entirely based on phenotypic selection. We assumed three different levels of genetic correlation between monocrop grain yield and intercrop grain yield to investigate how the different breeding strategies are impacted by this factor. We found that all four simulated breeding programs using genomic selection produced significantly more intercrop genetic gain than the phenotypic selection program regardless of the genetic correlation with monocrop yield. We suggest a genomic selection strategy which combines monocrop and intercrop trait information to predict general intercropping ability to increase selection accuracy in early stages of a breeding program and to minimize the generation interval.

genetics↗