Biology subjects

Bauland, C.

Publications and source records attributed to Bauland, C..

10 recordsLinked to original sources

bioRxiv2026

Phenomic selection enables nursery screening for field performance in maize and pea

Due to economical constraints, breeding programs eliminate most selection candidates at early stages, before their productivity can be evaluated in field trials. Genomic selection partially overcomes this limitation by enabling early prediction of field performance, but its implementation requires large-scale recurrent genotyping that remains inaccessible for many species and breeding programs. Phenomic selection offers a promising alternative by replacing genotyping with inexpensive high-dimensional phenotyping data. However, previous applications have focused on predicting genotypes already evaluated in field trials. We investigated whether phenomic data acquired by unoccupied aerial vehicles (UAVs) from nursery-grown genotypes can be used to predict their performance in field trials. We validated this nursery-screening approach in maize and pea, two species with contrasting biology and canopy structures, supporting its potential transferability to other species. In the most challenging scenarios, average accuracies for yield-related traits were between 0.36 for maize and 0.40 for pea. Simulations indicated that these accuracies can support substantial nursery culling while limiting the risk of discarding superior genotypes. This proof of concept demonstrates that UAV-based phenomic selection can predict the field performance of nursery-grown genotypes without genotyping the selection candidates.

genetics↗

bioRxiv2026

Dissecting the phenotypic and genetic determinants of maize-bean interactions in intercropping

O_LICereal-legume intercropping is a cornerstone of agroecological systems because interactions between species can enhance agroecosystem resilience. Yet, the mechanisms underlying these interactions remain poorly understood. To address this gap, we investigated the maize-bean association under low-input conditions. C_LIO_LIWe conducted a two-year intercropping experiment with 200 climbing bean lines grown alongside three maize landraces in France and Romania. We evaluated bean phenotypic responses above- and below-ground to 3 maize landraces, treated as distinct biotic environments (E). Direct and indirect genetic effects were assessed by mapping bean and maize phenotypic traits onto the bean genome (G), with G x E interactions tested using contrasts among maize landraces. C_LIO_LICompetitive interactions dominated, maize acting as the stronger competitor. Maize landraces created distinct biotic environments affecting bean traits. Best-performing partners varied across experimental fields, with no evidence of bean local adaptation. The most productive and balanced mixtures were obtained with the traditionally intercropped maize landrace. Genome-wide association analyses identified loci underlying direct and indirect genetic effects, including candidate genes associated with neighbor perception. C_LIO_LIThese findings reveal the genetic complexity of maize-bean interactions and highlight competitive tolerance in bean and reduced aggressiveness in maize as key traits for improving cereal-legume intercrop performance. C_LI

genetics↗

bioRxiv2026

Predicting agronomic performance of maize landraces in various and future environments by combining genomic prediction and ecogenetics

Forecasting vulnerability of cultivated and wild species to climate changes is highly challenging. Evolutionary genomic models enable the prediction of mal-adaptation (genomic offset - GO) across environments and future climates under the assumption that populations are currently locally adapted but do not predict but the resulting phenotypic changes. To do so, we developed a new genomic prediction model (GP) integrating both genomic offset (GO) and within-population gene diversity (Hs) to capture genotype by environment interaction and inbreeding effects, respectively (GP-HO-Hs). As proof of concept, we applied this GP-GO-Hs model to a collection of 397 maize populations (landraces) evaluated across 25 environments in Europe using high-throughput DNA pool genotyping. GP-GO-Hs model accurately predicted yield, plant height and flowering time. It increased by 13% the predictive abilities of GP model for predicting yield of new landraces in new environments. GP-GO-Hs model also predicted that the more diverse the landrace, the more stable its agronomic performance across environments. GP-GO-Hs model generated phenotypic adaptive landscapes for each landrace in future climatic scenarios, enabling the identification of landraces with enhanced potential to adapt to future or emerging cultivation conditions. This GP-GO-Hs model could be easily applied to other wild and cultivated species. TeaserIdentify promising landrace adapted to new and future environments by combining genomic selection and offset

genomics↗

bioRxiv2024

A multidisciplinary on-farm survey of maize-bean intercropping shows that revival of traditionalagricultural systems requires careful consideration of partner varieties and agronomic practices.

O_LICereal-legume intercropping is a promising strategy for sustainable agroecosystems. The traditional intercropping of maize and bean is experiencing a revival in some modern agricultural settings, such as in southwestern France, where maize hybrids are intercropped with the commercialized Tarbais bean. We conducted on-farm surveys and a field assay to address the following questions: How does the cropping system impact yield, nutrient uptake, and rhizosphere bacterial assemblages? Do positive or negative interactions between maize and beans dominate in intercropping? What is the effect of intercropping on plant transcriptomics? C_LIO_LIWe recorded farming practices, conducted yield and nutrient measurements, and characterized soil bacterial assemblages to compare sole-cropped maize and beans with intercropped plants. A controlled field assay was also established to extend this comparison to plant gene expression differences. C_LIO_LIIntercropping was associated with a trend towards increased bacterial diversity. The cropping system significantly influenced agronomic traits, with frequent farm-by-cropping system interactions underscoring the critical role of farming practices. Competition dominated maize-bean intercropping, with 34 negative correlations among the 47 significant ones between maize and bean traits. This competition affected yield and nutrition, but primarily impacted beans, which produced fewer but bigger/heavier seeds. Transcriptomic results concurred with these findings, revealing no differentially expressed genes in maize but 5,070 in beans under competition. C_LIO_LIOverall, our findings suggest that beneficial interactions between the two crops are hindered under current field conditions, underscoring the importance of carefully considering partner varieties and farming practices to revive traditional agricultural systems. C_LI Societal Impact StatementCereal-legume intercropping is a promising strategy for sustainable agroecosystems that leverages the biological complementarities between plant species, reducing the need for chemical inputs while enhancing field biodiversity. Here, we focused on maize-bean intercropping, which is experiencing a revival in modern conventional agricultural settings. We found a trend towards an increased soil bacterial diversity in intercropping. However, competition between the two crops dominated and primarily impacted yield and gene expression in beans. Despite lower yield, bean seeds exhibited greater size. Our study indicates that implementing variety selection of both species and adapting farming practices is essential to fully harness the potential of intercropping.

plant biology↗

bioRxiv2024

Effects of maize development and phenology on the field infestation dynamics of the European Corn Borer

Phenological match/mismatch between cultivated plants and their pest could impact pest infestastion dynamics in the field. To explore how such match/mismatch of plant and pest phenologies may interact with plant defense dynamics, we studied the infestation dynamics of maize by one of its main pests in Europe, the European Corn Borer (Ostrinia nubilalis; Lepidoptera: Crambidae). A two-year field experiment was carried out on a collection of 23 maize inbred lines contrasted for their earliness. Each inbred line was sown at three different dates in order to expose different developmental stages of maize to natural European corn borer infestation. The effect of the sowing date depended on the inbred line, the pest generation and the year. In 2021, the final pest incidence ranged from 36% to 91% depending on inbred lines and sowing date. In 2022, it ranged from 2% to 77%. This variability in final pest incidence can be related to variations in plant development during plant exposure to pest infestation. However, this relationship was not straightforward. Indeed, the shape and intensity of the relationship depended on the timing of the onset of the pest infestation. When infestation occurred while plants were in a vegetative stage, a non-linear relationship between development and pest incidence was observed with the least and most developed plants being the most infested. When infestation occurred when all plants were in the mature phase, the most developed plants were the least infested. Our results highlight the effect of plant-pest phenological match/mismatch on pest infestation dynamics and underline the importance of taking plant-pest interactions into account to propose relevant control strategies.

ecology↗

bioRxiv2023

Large genetic variability of maize leaf palatability to european corn borer : metabolic insights

Maize is the most-produced cereal in the world, but its production faces constraints such as parasitic attacks from stemborers. We evaluated the resistance of a core-collection of 18 maize lines by measuring their palatability to European Corn Borer (ECB) larvae fed on maize leaf discs. Using an original consumption test device that takes into account the variability of larvae behaviour, we were able to phenotype the resistance of the 18 maize lines. We matched consumption data to existing enzymatic and metabolomic data that characterized the maize core-collection and identified some metabolites such as caffeoyl-lquinate, trocopherol, digalactosylglycerol and tyrosine that are positively or negatively correlated with the palatability to ECB larvae. Altogether, our results confirm the metabolic complexity involved in the establishment of plant defenses. Metabolic changes associated to leaf palatability mostly concern membrane and cell wall composition. Some of them, pointing-out to the phenylpropanoids pathway, were observed independently of plant developmental pace and plant earliness.

genetics↗

bioRxiv2020

Genome-wide SNP genotyping of DNA pools identifies untapped landraces and genomic regions that could enrich the maize breeding pool

Maize landraces preserved in genebanks have a large genetic diversity that is still poorly characterized and underexploited in modern breeding programs. Here, we genotyped DNA pools from 156 American and European landraces with a 50K SNP Illumina array to study the effect of both human selection and environmental adaptation on the genome-wide diversity of maize landraces. Genomic diversity of landraces varied strongly in different parts of the genome and with geographic origin. We detected selective footprints between landraces of different geographic origin in genes involved in the starch pathway (Su1, Waxy1), flowering time (Zcn8, Vgt3, ZmCCT9) and tolerance to abiotic and biotic stress (ZmASR, NAC and dkg genes). Landrace diversity was compared to that of (i) 327 inbred lines representing American and European diversity ("CK lines) and (ii) 103 new lines derived directly from landraces ("DH-SSD lines"). We observed limited diversity loss or selective sweep between landraces and CK lines, except in peri-centromeric regions. However, analysis of modified Rogers distance between landraces and the CK lines showed that most landraces were not closely related to CK lines. Assignment of CK lines to landraces using supervised analysis showed that only a few landraces, such as Reids Yellow Dent, Lancaster Surecrop and Lacaune, strongly contributed to modern European and American breeding pools. Haplotype diversity of CK lines was more enriched by DH-SSD lines that derived from the landraces with no related lines and the lowest contribution to CK lines. Our approach opens an avenue for the identification of promising landraces for pre-breeding. SIGNIFICANCE STATEMENTSMaize landraces are a valuable source of genetic diversity for addressing the challenges of climate change and the requirements of low input agriculture as they have been long selected to be well adapted to local agro-climatic conditions and human uses. However, they are underutilized in modern breeding programs because they are poorly characterized, genetically heterogeneous and exhibit poor agronomic performance compared to elite hybrid material. In this study, we developed a high-throughput approach to identify landraces that could potentially enlarge the genetic diversity of modern breeding pools. We genotyped DNA pools from landraces using 50K array technology, which is widely used by breeders to characterize the genetic diversity of inbred lines. To identify landraces that could enrich the modern maize germplasm, we estimated their contribution to inbred lines using supervised analysis and a new measurement of genetic distance.

genetics↗

bioRxiv2020

Deciphering the genetic diversity of landraces with high-throughput SNP genotyping of DNA bulks: methodology and application to the maize 50k array

Genebanks harbor original landraces carrying many original favorable alleles for mitigating biotic and abiotic stresses. Their genetic diversity remains however poorly characterized due to their large within genetic diversity. We developed a high-throughput, cheap and labor saving DNA bulk approach based on SNP Illumina Infinium HD array to genotype landraces. Samples were gathered for each landrace by mixing equal weights from young leaves, from which DNA was extracted. We then estimated allelic frequencies in each DNA bulk based on fluorescent intensity ratio (FIR) between two alleles at each SNP using a two step-approach. We first tested either whether the DNA bulk was monomorphic or polymorphic according to the two FIR distributions of individuals homozygous for allele A or B, respectively. If the DNA bulk was polymorphic, we estimated its allelic frequency by using a predictive equation calibrated on FIR from DNA bulks with known allelic frequencies. Our approach: (i) gives accurate allelic frequency estimations that are highly reproducible across laboratories, (ii) protects against false detection of allele fixation within landraces. We estimated allelic frequencies of 23,412 SNPs in 156 landraces representing American and European maize diversity. Modified Rogers genetic Distance between 156 landraces estimated from 23,412 SNPs and 17 SSRs using the same DNA bulks were highly correlated, suggesting that the ascertainment bias is low. Our approach is affordable, easy to implement and does not require specific bioinformatics support and laboratory equipment, and therefore should be highly relevant for large-scale characterization of genebanks for a wide range of species.

genetics↗

bioRxiv2019

Disentangling group specific QTL allele effects from genetic background epistasis using admixed individuals in GWAS: an application to maize flowering

When handling a structured population in association mapping, group-specific allele effects may be observed at quantitative trait loci (QTLs) for several reasons: (i) a different linkage disequilibrium (LD) between SNPs and QTLs across groups, (ii) group-specific genetic mutations in QTL regions, and/or (iii) epistatic interactions between QTLs and other loci that have differentiated allele frequencies between groups. We present here a new genome-wide association (GWAS) approach to identify QTLs exhibiting such group-specific allele effects. We developed genetic materials including admixed progeny from different genetic groups with known genome-wide ancestries (local admixture). A dedicated statistical methodology was developed to analyze pure and admixed individuals jointly, allowing one to disentangle the factors causing the heterogeneity of allele effects across groups. This approach was applied to maize by developing an inbred \"Flint-Dent\" panel including admixed individuals that was evaluated for flowering time. Several associations were detected revealing a wide range of configurations of allele effects, both at known flowering QTLs (Vgt1, Vgt2 and Vgt3) and new loci. We found several QTLs whose effect depended on the group ancestry of alleles while others interacted with the genetic background. The existence of directional epistasis was highlighted by comparing admixed with pure individuals and was consistent with epistatic interactions identified at the level of QTLs. Our GWAS approach provides useful information on the stability of QTL effects across genetic groups and can be applied to a wide range of species.\n\nAuthor summaryIdentification of genomic regions involved in genetic architecture of traits has become commonplace in quantitative genetics studies. Genetic structure is a common feature in human, animal and plant species and most current methods target genomic regions whose effects on traits are conserved between genetic groups. However, a heterogeneity of allele effects may be observed due to different factors: a group-specific correlation between the alleles of the tagged marker and those of the causal variant, a group-specific mutation at the causal variant or an epistatic interaction between the causal variant and the genetic background. We propose a new method adapted to structured populations including admixed individuals, which aims to identify these genomic regions and to unravel the previous factors. method was applied to a maize inbred diversity panel including lines from the dent and the flint genetic groups, as well as admixed lines, evaluated for flowering time. Several genomic regions were detected with various configurations of allele effects, with evidence of epistatic interactions between some of the loci and the genetic background.

genetics↗

bioRxiv2018

Genotyping-by-sequencing and microarrays are complementary for detecting quantitative trait loci by tagging different haplotypes in association studies

BackgroundSingle Nucleotide Polymorphism (SNP) array and re-sequencing technologies have different properties (e.g. calling rate, minor allele frequency profile) and drawback (e.g. ascertainment bias), which lead us to study the complementarity and consequences of using them separately or combined in diversity analyses and Genome-Wide Association Studies (GWAS). We performed GWAS on three traits (grain yield, plant height and male flowering time) measured in 22 environments on a panel of 247 diverse dent maize inbred lines using three genotyping technologies (Genotyping-By-Sequencing, Illumina Infinium 50K and Affymetrix Axiom 600K arrays).\n\nResultsThe effects of ascertainment bias of both arrays were negligible for deciphering global genetic trends of diversity in this panel and for estimating relatedness. We developed an original approach based on linkage disequilibrium (LD) extent in order to determine whether SNPs significantly associated with a trait and that are physically linked should be considered as a single QTL or several independent QTLs. Using this approach, we showed that the combination of the three technologies, which have different SNP distribution and density, allowed us to detect more Quantitative Trait Loci (QTLs, gain in power) and potentially refine the localization of the causal polymorphisms (gain in position).\n\nConclusionsConceptually different technologies are complementary for detecting QTLs by tagging different haplotypes in association studies. Considering LD, marker density and the combination of different technologies (arrays and re-sequencing), the genotypic data presently available were most likely enough to well represent polymorphisms in the centromeric regions, whereas using more markers would be beneficial for telomeric regions.

genomics↗