Biology subjects

Lister, C.

Publications and source records attributed to Lister, C..

4 recordsLinked to original sources

bioRxiv2025

Controlling GRF4-GIF1 Expression for Efficient, Genotype-Independent Transformation Across Wheat Cultivars

Bread wheat (Triticum aestivum L.) plays a vital role in global food security, and its continuous genetic improvement is essential to meet the demands of a rapidly growing world population. Advances in genome sequencing and assembly have positioned wheat as a model crop for functional genomics and have increased the demand for highly efficient, genotype-independent transformation systems. A fusion technology involving a GROWTH-REGULATING FACTOR (GRF) and a GRF-INTERACTING FACTOR (GIF) has emerged as a powerful tool to enhance regeneration efficiency and expand the range of transformable genotypes. In this study, we present an optimized and robust Agrobacterium-mediated wheat transformation protocol incorporating GRF4-GIF1, tested across multiple wheat varieties. Across all tested wheat cultivars, GRF4-GIF1 containing constructs consistently enabled successful transformation, with varied efficiencies depending on the genotype and promotors used to drive the gene fusion. Our method significantly improves transformation efficiency while minimizing GRF4-GIF1 pleiotropic effects, providing a versatile platform for gene function analysis and gene editing. This work represents a critical step toward efficient, genotype-independent transformation in wheat, supporting both research and breeding applications aimed at improving crop resilience, nutritional value, and productivity.

plant biology↗

bioRxiv2023

Harnessing Landrace Diversity Empowers Wheat Breeding for Climate Resilience

Breeding crops resilient to climate change is urgently needed to help ensure food security. A key challenge is to harness genetic diversity to optimise adaptation, yield, stress resilience and nutrition. We examined the genetic and phenotypic diversity of the A.E. Watkins landrace collection of bread wheat (Triticum aestivum), a major global cereal, through whole-genome re-sequencing (827 Watkins landraces and 208 modern cultivars) and in-depth field evaluation spanning a decade. We discovered that modern cultivars are derived from just two of the seven ancestral groups of wheat, leaving five groups as previously untapped sources for breeding. This provides access to landrace-specific functional variations using structured germplasm, genotyping and informatics resources. Employing complementary genetic populations and approaches, we identified thousands of high-resolution quantitative trait loci (QTL) and significant marker-trait associations for major traits, revealing many Watkins-unique loci that can confer superior traits in modern wheat. Furthermore, we identified and functionally verified causative genes for climate-change adaptation, nutritional enhancement and resistance to wheat blast. Finally, we assessed the phenotypic effects of 44,338 Watkins-unique haplotypes, introgressed from 143 prioritised QTL in the context of modern cultivars, bridging the gap between landrace diversity and current breeding. This study establishes a framework for systematically utilising genetic diversity in crop improvement to achieve sustainable food security.

plant biology↗

bioRxiv2020

Resolving a QTL complex for height, heading, and grain yield on chromosome 3A in bread wheat

Crop height (Ht), heading date (Hd), and grain yield (GY) are interrelated traits in wheat. Independent manipulation of each is important for adaptation and performance. Validated QTL for all three collocate on chromosome 3A in the Avalon x Cadenza population. We asked if these are linked or pleiotropic effects. The region was dissected using recombinants derived from Near Isogenic Lines. It was shown that Ht and Hd are controlled by independent genes. The newly defined Ht QTL interval contained a gene cluster involved in cell wall growth and displaying high levels of differential transcript expression. The Hd locus is much larger and rearranged compared to the reference genome but FT2 is a candidate of particular interest. The Hd effect was shown to act independently of photoperiod and vernalization but did exhibit genotype x environment interaction suggesting a role in ambient temperature sensitivity. It was the Hd locus that was most associated with increased GY of Cadenza alleles, supporting physiological studies proposing that late alleles at this locus increase spike fertility and grain number. The work has uncoupled height from heading and yield and shown that one of very few validated GY QTL in wheat is probably mediated by phenological variation. HighlightThere only are three validated wheat yield QTL. Here, one of them was genetically dissected. This showed that the physiological basis of the yield effect is likely to be phenological.

genetics↗

bioRxiv2017

CropQuant: An automated and scalable field phenotyping platform for crop monitoring and trait measurements to facilitate breeding and digital agriculture

Automated phenotyping technologies are capable of providing continuous and precise measurements of traits that are key to todays crop research, breeding and agronomic practices. In additional to monitoring developmental changes, high-frequency and high-precision phenotypic analysis can enable both accurate delineation of the genotype-to-phenotype pathway and the identification of genetic variation influencing environmental adaptation and yield potential. Here, we present an automated and scalable field phenotyping platform called CropQuant, designed for easy and cost-effective deployment in different environments. To manage infield experiments and crop-climate data collection, we have also developed a web-based control system called CropMonitor to provide a unified graphical user interface (GUI) to enable realtime interactions between users and their experiments. Furthermore, we established a high-throughput trait analysis pipeline for phenotypic analyses so that lightweight machine-learning modelling can be executed on CropQuant workstations to study the dynamic interactions between genotypes (G), phenotypes (P), and environmental factors (E). We have used these technologies since 2015 and reported results generated in 2015 and 2016 field experiments, including developmental profiles of five wheat genotypes, performance-related traits analyses, and new biological insights emerged from the application of the CropQuant platform.

plant biology↗