Search bioRxiv⌕ Search

Biology subjects

Van Haeften, S.

Publications and source records attributed to Van Haeften, S..

3 recordsLinked to original sources

Trait stability of diverse kabuli chickpea germplasm from delayed sowing in a rainfed environment

Structured AbstractO_ST_ABSContext and ObjectiveC_ST_ABSDelayed sowing can expose chickpea crops to stress during the critical period for yield determination, but the effect of yield components and phenology to grain yield variation is not well characterised in diverse germplasm under rainfed conditions. Identifying genetic resources for grain yield improvement requires integration of multi-environment trial and genomic analyses to disentangle direct yield effects from indirect effects of phenology. This study aimed to (1) characterise genotype by environment interaction patterns for grain yield, yield components and phenology across times of sowing and seasons, and (2) identify genomic regions associated with improved grain yield that are present in genebank accessions but absent from current Australian commercial cultivars. MethodsA diversity panel of 141 kabuli chickpea genotypes, including six commercial Australian cultivars and 135 genebank accessions, was evaluated across six rainfed trials at Narrabri, New South Wales over three seasons (2018 to 2020) under typical (MAIN) and delayed (LATE) sowing. Multi-environment trial analyses with factor analytic models partitioned genotype by environment interactions for grain yield, 100-seed weight, seed number, and thermal time to flowering, podding, and maturity. Haplotype block analysis identified high variance blocks associated with seed number, classified by their overlap with high variance thermal time to flowering blocks, to distinguish from effects mediated by phenology. Results and ConclusionsDelayed sowing reduced grain yield by up to 1.04 t ha-{superscript 1}, driven primarily by reductions in seed number rather than 100-seed weight. Accelerated phenology was a key component of adaptation among commercial cultivars. Four haploblocks with high block variance for seed number were identified across all six trials. SignificanceSeed number was the dominant driver of grain yield variation in this diverse kabuli chickpea panel. Targeted introgression of rare superior haplotypes from genebank accessions provides an opportunity to broaden the genetic base of Australian kabuli chickpea and improve yield through higher seed number, with relevance to chickpea production systems facing similar climate variability. HighlightsDelayed sowing reduced grain yield in diverse kabuli chickpea germplasm by up to 1.04 t ha-1 across three years and six trials in northern New South Wales. Seed number, not seed weight, was the dominant driver of grain yield variation, and a shorter phenological duration was associated with higher seed number. Across all six trials, haplotype block analysis identified four genomic regions in high linkage disequilibrium with high variance for seed number and low variance for flowering time. The accession FLIP 94 62C uniquely carried rare superior haplotypes at two chromosome 4 blocks, the haplotype at the 17.0 Mb block was the most superior haplotype in all trials while the haplotype at the 8.5Mb block was most superior only in the most heat stressed environment.

plant biology↗

Identifying water stress response haplotypes in barley using latent environmental covariates

PurposeGenotype-by-environment (G x E) interactions represent a major obstacle to increasing genetic gain in crop breeding, with the underlying physiological drivers often remaining obscured within conventional statistical models. This case study presents a novel framework that transforms the latent factors from Factor Analytic (FA) multi-environment trial (MET) models into heritable quantitative traits, enabling the genetic dissection of adaptive response patterns. MethodsA Factor Analytical Linear Mixed Model (FA-LMM) was fit to plot-level yield data for 1,036 barley genotypes across eight Australian trials. ResultsCorrelation of the factor loadings with APSIM-simulated environmental covariates demonstrated that the second latent factor FA2 was strongly correlated with the Water Stress Index (r = -0.83) during the critical flowering period, establishing water availability as the main biological axis of crossover Gx E. Genotypic scores for the derived traits, Overall Performance (OP) and Water Stress Response (WSR), were subjected to high-resolution haplotype-based mapping using local Genomic Estimated Breeding Values (GEBV). ConclusionThis analysis successfully identified major genomic regions that accounted for a substantial proportion of the additive genetic variance. Gene Ontology enrichment of candidate genes within the top haploblocks implicated fundamental pathways related to energy homeostasis, root development, and stress response, with notable candidates including FTsH11, BPS1, and TDP1. The distribution of favourable Haplotypes of Interest (HOI) in elite cultivars suggested a historical signature of inadvertent selection for these adaptive mechanisms. This framework provides an explicit bridge between statistical modelling and functional genomics, offering breeders actionable genetic targets for accelerated development of climate-resilient cereals.

plant biology↗

The potential to breed for genetic legacy effects in sustainable farming systems

Legume crops provide protein-rich food, critical disease breaks in cereal rotations, and contribute to soil fertility through symbiotic nitrogen fixation. However, crop improvement programs typically focus on within-crop performance rather than system-level benefits. We hypothesise that legacy effects (the influence of one crops genotype on subsequent crop performance) are under genetic control and could be leveraged in breeding programs. To test this, we evaluated how 309 genetically diverse mungbean genotypes influence subsequent wheat performance. The mungbean panel was grown, followed by a single wheat cultivar sown in the same plot locations. Remarkably, wheat yield varied by nearly 1 t ha{square}{superscript 1} (2.52-3.49 t ha{square}{superscript 1}) depending solely on the preceding mungbean genotype, with legacy traits displaying moderate heritability (H{superscript 2}: 0.43-0.65), demonstrating untapped genetic potential for breeding. Analyses of mungbean traits, soil properties, and volatile organic compounds implicated root architecture, symbiotic nitrogen fixation and soil microbiome as potential biological drivers of legacy effects. Haplotype mapping identified genomic regions in mungbean associated with wheat yield and protein, revealing trade-offs between within-crop and legacy performance. Genetic simulations using empirically derived marker effects compared genomic selection strategies targeting mungbean yield, wheat yield, or both simultaneously. Balanced selection (50:50 weighting) achieved simultaneous gains in both crops (19.5% and 7.6%), highlighting the opportunity to breed for system-level productivity with reduced input requirements.

plant biology↗