Biology subjects

Madur, D.

Publications and source records attributed to Madur, D..

7 recordsLinked to original sources

bioRxiv2026

A major chromosome 4 region modulates early vigor under chilling through brassinosteroid signaling associated genes in maize

AbstractEarly sowing is a key strategy to improve maize productivity and resilience under climate change, but it exposes plants to prolonged chilling stress that can severely compromise seedling establishment. While previous genetic studies have focused on germination or very early stages, tolerance to long-term chilling during the autotrophic transition remains poorly characterized. Here, we combined genome-wide association studies (GWAS) and transcriptome analysis on QTL near-isogenic lines (NILs) to dissect the genetic architecture of early vigor under chilling in maize. We identified a major genomic region on chromosome 4 (LD_COL4), harboring two QTLs within a 2.7 Mb interval, that were consistently associated with early vigor under long-term chilling conditions. Transcriptomic analysis of contrasted NILs revealed a cluster of differentially expressed genes co-localizing with LD_COL4, pointing to two strong candidate genes, Zm00001d048582, an ortholog of the Arabidopsis OPS gene that regulates the brassinosteroid (BR) signaling pathway upstream of the key transcription factors BES1 and BZR1, and Zm00001d048612, a brassinosteroid-signaling kinase (BSK). Multiple orthologs of BES1/BZR1 modulators were differentially expressed between genotypes under chilling, supporting the involvment of brassinosteroid signaling in this response. These findings highlight both genes as promising targets for marker-assisted breeding and gene editing to improve maize adaptation to early sowing.

plant biology↗

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↗

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

Genetic diversity of maize landraces from the South-West of France

From the 17th century until the arrival of hybrids in 1960s, maize landraces were cultivated in the South-West of France, a traditional region for maize cultivation. A set of landraces were collected in this region between the 1950s and 1980s and were then conserved ex situ in a germplam collection. Previous studies using molecular markers on approx. twenty landraces fo this region showed that they belonged to a Pyrenees-Galicia Flint genetic group and originated from hybridization between Caribbean and Northern Flint germplasms introduced in Europe. In this study, we assessed the structure and genetic diversity of 194 SWF maize landraces to elucidate their origin, using a 50K SNP array and a bulk DNA approach. We identified two weakly differentiated genetic groups, one in the Western part and the other in the Eastern part. We highlighted the existence of a longitudinal gradient along the SWF area that was probably maintained through the interplay between genetic drifts and restricted gene flows, rather than through differential climatic adaptation. The contact zone between the two groups observed near the Garonne valley may be the result of these evolutionnary forces. We found only few significant cases of hybridization between Caribbean and Northern Flint germplasms in the region. We also found gene flows from various maize genetic groups to SWF landraces. Thus, we assumed that SWF landraces had a multiple origin with a slightly higher influence of Tropical germplasm in the West and preponderance of Northern Flint germplasm in the East.

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↗

bioRxiv2018

High throughput genotyping of structural variations in a complex plant genome using an original Affymetrix(R) Axiom(R) array

BackgroundInsertions/deletions (InDels) and more specifically presence/absence variations (PAVs) are pervasive in several species and have strong functional and phenotypic effect by removing or drastically modifying genes. Genotyping of such variants on large panels remains poorly addressed, while necessary for approaches such as association mapping or genomic selection.\n\nResultsWe have developed, as a proof of concept, a new high-throughput and affordable approach to genotype InDels. We first identified 141,000 InDels by aligning reads from the B73 line against the genome of three temperate maize inbred lines (F2, PH207, and C103) and reciprocally. Next, we designed an Affymetrix(R) Axiom(R) array to target these InDels, with a combination of probes selected at breakpoint sites (13%) or within the InDel sequence, either at polymorphic (25%) or non-polymorphic sites (63%) sites. The final array design is composed of 662,772 probes and targets 105,927 InDels, including PAVs ranging from 35bp to 129kbp. After Affymetrix(R) quality control, we successfully genotyped 86,648 polymorphic InDels (82% of all InDels interrogated by the array) on 445 maize DNA samples with 422,369 probes. Genotyping InDels using this approach produced a highly reliable dataset, with low genotyping error (~3%), high call rate (~98%), and high reproducibility (>95%). This reliability can be further increased by combining genotyping of several probes calling the same InDels (<0.1% error rate and >99.9% of call rate for 5 probes). This \"proof of concept\" tool was used to estimate the kinship matrix between 362 maize lines with 57,824 polymorphic InDels. This InDels kinship matrix was highly correlated with kinship estimated using SNPs from Illumina 50K SNP arrays.\n\nConclusionsWe efficiently genotyped thousands of small to large InDels on a sizeable number of individuals using a new Affymetrix(R) Axiom(R) array. This powerful approach opens the way to studying the contribution of InDels to trait variation and heterosis in maize. The approach is easily extendable to other species and should contribute to decipher the biological impact of InDels at a larger scale.

genomics↗

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↗