Biology subjects

Zwart, A. B.

Publications and source records attributed to Zwart, A. B..

3 recordsLinked to original sources

bioRxiv2020

Genetics of phosphorus use efficiency in a MAGIC wheat population grown in the field

Phosphorus (P) is an essential plant nutrient and regular applications are essential in most farming systems to maintain high yields. Yet the P fertilizers applied to crops and pastures are derived from non-renewable resources. It is therefore important to find agronomic and genetic strategies for using this resource efficiently, especially since only a proportion of the applied P is absorbed by crops. The aim of this study was to identify Quantitative Trait Loci (QTL) for P use efficiency (PUE) in wheat using a Multiparent Advanced Generation InterCross (MAGIC) population grown in the field. The 357 genotypes were arranged in paired plots with and without P fertilization. Yield and biomass were measured and PUE was calculated as either the performance of the genotype relative to the average response to fertilization, or the performance of the genotype relative to the average resilience in the absence of fertilization. Five trials were conducted over three years in Australia at three sites with contrasting clay and sandy soil types. Genotypic variation for response and resilience were identified in all trials with moderate to strong correlation with productivity with and without P between trials. Multiparent Whole Genome Average Interval Mapping (WGAIM) QTL analyses were conducted on the four traits (Biomass / Yield x P Response / Resilience) across the five trials and identified 130 QTL in total. QTL within 10 cM of each other were clustered into 56 groups that were likely to represent identical or linked loci. Of the clusters 27 (48%) contained only a single QTL but 17 (31%) contained 3 or more in different trials or traits. This suggests multiple biological mechanisms driving PUE in different environments. Eight of the 56 groups collocated with QTL for seedling root hair length identified in the same MAGIC population in an earlier study. HighlightIdentification of genetic loci for phosphorus use efficiency in a multigenic population of Australian wheats grown on contrasting soils.

plant biology↗

bioRxiv2019

A versatile high throughput screening platform for plant metabolic engineering highlights the major role of ABI3 in lipid metabolism regulation

Traditional functional genetic studies in crops are time-consuming, complicated and cannot be readily scaled up. The reason is that mutant or transformed crops need to be generated to study the effect of gene modifications on specific traits of interest. However, many crop species have a complex genome and a long generation time. As a result, it usually takes several months to over a year to obtain desired mutants or transgenic plants, which represents a significant bottleneck in the development of new crop varieties. To overcome this major issue, we are currently establishing a versatile plant genetic screening platform, amenable to high throughput screening in almost any crop species, with a unique workflow. This platform combines protoplast transformation and fluorescence-activated cell sorting. Here we show that tobacco protoplasts can accumulate high levels of lipids if transiently transformed with genes involved in lipid biosynthesis and can be sorted based on lipid content. Hence, protoplasts can be used as a predictive tool for plant lipid engineering. Using this newly established strategy, we demonstrate the major role of ABI3 in plant lipid accumulation. We anticipate that this workflow can be applied to numerous highly valuable metabolic traits other than storage lipid accumulation. This new strategy represents a significant step towards screening complex genetic libraries, in a single experiment and in a matter of days, as opposed to years by conventional means.

plant biology↗

bioRxiv2016

Rooting density differentiates wheat genotypes through Bayesian modeling

Wheat pre-breeders use soil coring and core-break counts to phenotype root architecture traits, with data collected on rooting density for hundreds of genotypes in small increments of depth. The measured densities are both large datasets and highly variable even within the same genotype, hence, any rigorous, comprehensive statistical analysis of such complex field data would be technically challenging. Traditionally, most attributes of the field data are therefore discarded in favor of simple numerical summary descriptors which retain much of the high variability exhibited by the raw data. This poses practical challenges: although plant scientists have established that root traits do drive resource capture in crops, traits that are more randomly (rather than genetically) determined are difficult to breed for. In this paper we develop a Bayesian hierarchical nonlinear modeling approach that utilizes the complete field data for wheat genotypes to fit an idealized relative intensity function for the root distribution over depth. Our approach was used to determine heritability: how much of the variation between field samples was purely random versus being mechanistically driven by the plant genetics? Based on the genotypic intensity functions, the overall heritability estimate was 0.62 (95% Bayesian confidence interval was 0.52 to 0.71). Despite root count profiles that were statistically very noisy, our Bayesian analysis led to denoised profiles which exhibited rigorously discernible phenotypic traits. The profile-specific traits could be representative of a genotype and thus can be used as a quantitative tool to associate phenotypic traits with specific genotypes.

plant biology↗