A GWAS study highlights significant associations between a series of indels in a FLOWERING LOCUS T gene promoter and flowering time in white lupin (Lupinus albus L.).

BACKGROUND: White lupin (Lupinus albus L.) is a high-protein Old World grain legume with remarkable food and feed production interest. It is sown in autumn or early spring, depending on the local agroclimatic conditions. This study aimed to identify allelic variants associated with vernalization responsiveness, in order to improve our knowledge of legume flowering regulatory pathways and develop molecular selection tools for the desired phenology as required for current breeding and adaptation to the changing climate. RESULTS: Some 120 white lupin accessions originating from a wide range of environments of Europe, Africa, and Asia were phenotyped under field conditions in three environments with different intensities of vernalization, namely, a Mediterranean and a subcontinental climate sites of Italy under autumn sowing, and a suboceanic climate site of France under spring sowing. Two hundred sixty-two individual genotypes extracted from them were phenotyped in a greenhouse under long-day photoperiod without vernalization. Phenology data, and marker data generated by Diversity Arrays Technology sequencing (DArT-seq) and by PCR-based screening targeting published quantitative trait loci (QTLs) from linkage map and newly identified insertion/deletion polymorphisms in the promoter region of the FLOWERING LOCUS T homolog, LalbFTc1 gene (Lalb_Chr14g0364281), were subjected to a genome-wide association study (GWAS). Population structure followed differences in phenology and isolation by distance pattern. The GWAS highlighted numerous loci significantly associated with flowering time, including four LalbFTc1 gene promoter deletions: 2388 bp and 2126 bp deletions at the 5' end, a 264 bp deletion in the middle and a 28 bp deletion at the 3' end of the promoter. Besides LalbFTc1 deletions, this set contained DArT-seq markers that matched previously published major QTLs in chromosomes Lalb_Chr02, Lalb_Chr13 and Lalb_Chr16, and newly discovered QTLs in other chromosomes. CONCLUSIONS: This study highlighted novel QTLs for flowering time and validated those already published, thereby providing novel evidence on the convergence of FTc1 gene functional evolution into the vernalization pathway in Old World lupin species. Moreover, this research provided the set of loci specific for extreme phenotypes (the earliest or the latest) awaiting further implementation in marker-assisted selection for spring- or winter sowing.

The Effect of Genome Parametrization and SNP Marker Subsetting on Genomic Selection in Autotetraploid Alfalfa.

BACKGROUND: Alfalfa, the most economically important forage legume worldwide, features modest genetic progress due to long selection cycles and the extent of the non-additive genetic variance associated with its autotetraploid genome. METHODS: To improve the efficiency of genomic selection in alfalfa, we explored the effects of genome parametrization (as tetraploid and diploid dosages, plus allele ratios) and SNP marker subsetting (all available SNPs, only genic regions, and only non-genic regions) on genomic regressions, together with various levels of filtering on reading depth and missing rates. We used genotyping by sequencing-generated data and focused on traits of different genetic complexity, i.e., dry biomass yield in moisture-favorable (FE) and drought stress (SE) environments, leaf size, and the onset of flowering, which were assessed in 143 genotyped plants from a genetically broad European reference population and their phenotyped half-sib progenies. RESULTS: On average, the allele ratio improved the predictive ability compared with other genome parametrizations (+7.9% vs. tetraploid dosage, +12.6% vs. diploid dosage), while using all the SNPs offered an advantage compared with any specific SNP subsetting (+3.7% vs. genic regions, +7.6% vs. non-genic regions). However, when focusing on specific traits, different combinations of genome parametrization and subsetting achieved better performances. We also released Legpipe2, an SNP calling pipeline tailored for reduced representation (GBS, RAD) in medium-sized genotyping experiments.

Genomic prediction for rust resistance in pea.

Genomic selection (GS) has become an indispensable tool in modern plant breeding, particularly for complex traits. This study aimed to assess the efficacy of GS in predicting rust (Uromyces pisi) resistance in pea (Pisum sativum), using a panel of 320 pea accessions and a set of 26,045 Silico-Diversity Arrays Technology (Silico-DArT) markers. We compared the prediction abilities of different GS models and explored the impact of incorporating marker × environment (M×E) interaction as a covariate in the GBLUP (genomic best linear unbiased prediction) model. The analysis included phenotyping data from both field and controlled conditions. We assessed the predictive accuracies of different cross-validation strategies and compared the efficiency of using single traits versus a multi-trait index, based on factor analysis and ideotype-design (FAI-BLUP), which combines traits from controlled conditions. The GBLUP model, particularly when modified to include M×E interactions, consistently outperformed other models, demonstrating its suitability for traits affected by complex genotype-environment interactions (GEI). The best predictive ability (0.635) was achieved using the FAI-BLUP approach within the Bayesian Lasso (BL) model. The inclusion of M×E interactions significantly enhanced prediction accuracy across diverse environments in GBLUP models, although it did not markedly improve predictions for non-phenotyped lines. These findings underscore the variability of predictive abilities due to GEI and the effectiveness of multi-trait approaches in addressing complex traits. Overall, our study illustrates the potential of GS, especially when employing a multi-trait index like FAI-BLUP and accounting for M×E interactions, in pea breeding programs focused on rust resistance.

Improved Ultrasound-Guided Balloon-Assisted Maturation Angioplasty Using Drug-Eluting Balloons in the First Autogenous Arteriovenous Fistula Procedure: Early Experience.

In patients with end-stage renal failure requiring hemodialysis, autogenous arteriovenous fistula (AVF) is preferred over tunneled dialysis catheters due to lower complications and costs. However, AVF maturation failure remains a common issue due to small vein size, multiple venipunctures, and other factors. Guidelines recommend using vessels of >2 mm for forearm AVFs and >3 mm for upper arm AVFs. This study investigates the use of intraoperative Doppler ultrasound (DUS)-guided Balloon-Assisted Maturation (BAM) with drug-eluting balloons (DEB) during initial AVF creation. Data from 114 AVF procedures, of which 27.2% underwent BAM, were analyzed. BAM was performed in 25 distal radio-cephalic and 6 proximal brachio-cephalic AVFs. With DUS guidance, vein stenosis was identified and treated using DEB. Technical success was achieved in all cases, with no early mortality. Early BAM-related complications were minimal, and no AVF thrombosis occurred. AVF maturation time was 15 days (SD: 3), and no further complications were reported during a mean follow-up of 10.38 months. Using BAM with DEB during AVF creation led to successful maturation and dialysis use without the need for secondary procedures. This study emphasizes the importance of identifying AVF failure risk early and utilizing DUS-guided procedures to enhance AVF outcomes. A more liberal use of intraoperative BAM could limit reinterventions in patients undergoing AVFs.

Discovering new genes for alfalfa (Medicago sativa) growth and biomass resilience in combined salinity and Phoma medicaginis infection through GWAS.

Salinity and Phoma medicaginis infection represent significant challenges for alfalfa cultivation in South Africa, Europe, Australia, and, particularly, Tunisia. These constraints have a severe impact on both yield and quality. The primary aim of this study was to establish the genetic basis of traits associated with biomass and growth of 129 Medicago sativa genotypes through genome-wide association studies (GWAS) under combined salt and P. medicaginis infection stresses. The results of the analysis of variance (ANOVA) indicated that the variation in these traits could be primarily attributed to genotype effects. Among the test genotypes, the length of the main stem, the number of ramifications, the number of chlorotic leaves, and the aerial fresh weight exhibited the most significant variation. The broad-sense heritability (H²) was relatively high for most of the assessed traits, primarily due to genetic factors. Cluster analysis, applied to morpho-physiological traits under the combined stresses, revealed three major groups of accessions. Subsequently, a GWAS analysis was conducted to validate significant associations between 54,866 SNP-filtered single-nucleotide polymorphisms (SNPs) and seven traits. The study identified 27 SNPs that were significantly associated with the following traits: number of healthy leaves (two SNPs), number of chlorotic leaves (five SNPs), number of infected necrotic leaves (three SNPs), aerial fresh weight (six SNPs), aerial dry weight (nine SNPs), number of ramifications (one SNP), and length of the main stem (one SNP). Some of these markers are related to the ionic transporters, cell membrane rigidity (related to salinity tolerance), and the NBS_LRR gene family (associated with disease resistance). These findings underscore the potential for selecting alfalfa genotypes with tolerance to the combined constraints of salinity and P. medicaginis infection.

European soybean to benefit people and the environment.

Europe imports large amounts of soybean that are predominantly used for livestock feed, mainly sourced from Brazil, USA and Argentina. In addition, the demand for GM-free soybean for human consumption is project to increase. Soybean has higher protein quality and digestibility than other legumes, along with high concentrations of isoflavones, phytosterols and minerals that enhance the nutritional value as a human food ingredient. Here, we examine the potential to increase soybean production across Europe for livestock feed and direct human consumption, and review possible effects on the environment and human health. Simulations and field data indicate rainfed soybean yields of 3.1 ± 1.2 t ha-1 from southern UK through to southern Europe (compared to a 3.5 t ha-1 average from North America). Drought-prone southern regions and cooler northern regions require breeding to incorporate stress-tolerance traits. Literature synthesized in this work evidenced soybean properties important to human nutrition, health, and traits related to food processing compared to alternative protein sources. While acknowledging the uncertainties inherent in any modelling exercise, our findings suggest that further integrating soybean into European agriculture could reduce GHG emissions by 37-291 Mt CO2e year-1 and fertiliser N use by 0.6-1.2 Mt year-1, concurrently improving human health and nutrition.

Genomic prediction and allele mining of agronomic and morphological traits in pea (Pisum sativum) germplasm collections.

Well-performing genomic prediction (GP) models for polygenic traits and molecular marker sets for oligogenic traits could be useful for identifying promising genetic resources in germplasm collections, setting core collections, and establishing molecular variety distinction. This study aimed at (i) defining GP models and key marker sets for predicting 15 agronomic or morphological traits in germplasm collections, (ii) verifying the GP model usefulness also for selection in breeding programs, (iii) investigating the consistency between molecular and phenotypic diversity patterns, and (iv) identifying genomic regions associated with to the target traits. The study was based on phenotyping data and over 41,000 genotyping-by-sequencing-generated SNP markers of 220 landraces or old cultivars belonging to a world germplasm collection and 11 modern cultivars. Non-metric multi-dimensional scaling (NMDS) and an analysis of population genetic structure indicated a high level of genetic differentiation of material from Western Asia, a major West-East diversity gradient, and quite limited genetic diversity of the improved germplasm. Mantel's test revealed a low correlation (r = 0.12) between phenotypic and molecular diversity, which increased (r = 0.45) when considering only the molecular diversity relative to significant SNPs from genome-wide association analyses. These analyses identified, inter alia, several areas of chromosome 6 involved in a largely pleiotropic control of vegetative or reproductive organ pigmentation. We found various significant SNPs for grain and straw yield under severe drought and onset of flowering, and one SNP on chromosome 5 for grain protein content. GP models displayed moderately high predictive ability (0.43 to 0.61) for protein content, grain and straw yield, and onset of flowering, and high predictive ability (0.76) for individual seed weight, based on intra-population, intra-environment cross-validations. The inter-population, inter-environment assessment of the models trained on the germplasm collection for breeding material of three recombinant inbred line (RIL) populations, which was challenged by much narrower diversity of the material, over eight-fold less available markers and quite different test environments, led to an overall loss of predictive ability of about 40% for seed weight, 50% for protein content and straw yield, and 60% for onset of flowering, and no prediction for grain yield. Within-RIL population predictive ability differed among populations.