Biology subjects

Felderhoff, T.

Publications and source records attributed to Felderhoff, T..

9 recordsLinked to original sources

bioRxiv2026

Flywheel Genomics: Simultaneous trait discovery and genetic gain in plant breeding

Genomic mapping has yielded extensive catalogs of quantitative trait loci underlying agronomic traits, yet translating these discoveries into breeding gains remains inefficient. Here, we introduce Flywheel Genomics, a framework that integrates trait discovery directly within rapid cycling breeding populations. Using empirical data from a smallholder-oriented sorghum breeding program, we demonstrate that recurrent intermating and selection maintain genetic diversity, effective population size, and recombination while reducing confounding from plant height and maturity. Within this population, we resolve loci underlying simple adaptive and complex environmentally responsive traits and generate large segregating populations for mapping and near-isogenic lines for locus validation. We further demonstrate applicability in a public wheat breeding program, where known agronomic loci were readily detected. Simulations show that rapid cycling better preserves the population genetic properties required for Flywheel Genomics than conventional pure line development. By integrating discovery with improvement, Flywheel Genomics reframes breeding programs as engines of both crop improvement and genetic insight.

genetics↗

bioRxiv2026

Field and lab phenomics facilitate detection of genetic variation for iron deficiency chlorosis tolerance in sorghum

Bioavailability of iron, an essential micronutrient to plants, is low in alkaline or calcareous soils, which are prevalent across semi-arid production regions. Breeding efforts to increase tolerance to iron deficiency chlorosis (IDC) in sorghum, a major crop of semi-arid regions, are confounded by spatial variation of stress severity in field trials. Here we developed and validated two high-throughput phenotyping approaches to address this challenge, with multi-spectral aerial imaging in the field and a controlled-environment assay to isolate the effects of iron bioavailability. In the field, severity and uniformity of stress are highly predictive of genetic signals for IDC tolerance (R2 > 0.6 for soil pH metrics and H2). Plot-level data filtering for stress conditions based on control genotypes successfully addresses field spatial variation (unfiltered H2 = 0.18 vs. filtered H2 = 0.4). The controlled-environment assay proxies field stress using iron sources with differential bioavailability, evidenced by high heritability ( H2 = 0.98) and phenotypic differential for hybrid control genotypes that matches field performance. Finally, we show that assay phenotypes are suitable for genome-wide association studies in global germplasm. Together, these field and lab phenomic approaches can be deployed to understand genetics of IDC tolerance and develop crops resilient to alkaline soils. HIGHLIGHTStress severity and uniformity greatly impact detection of genetic signals underlying iron deficiency chlorosis tolerance in sorghum. A controlled-environment assay reduces spatial heterogeneity and improves assessment of tolerance genetics.

genetics↗

bioRxiv2026

A stable genomic variant for photoperiodic flowering plasticity to enhance grain mold escape and yield stability in sorghum

Grain mold severely constrains sorghum [Sorghum bicolor (L.) Moench] productivity and grain quality in subhumid environments. Photoperiod-sensitive flowering plays a key role in mold avoidance and yield stability along north-south rainfall gradients. In response to the high susceptibility of elite cultivars in subhumid zones of Senegal, we developed and characterized a recombinant inbred line (RIL) population derived from Nganda (grain mold-susceptible) and Grinkan (photoperiod-sensitive) varieties. The population was evaluated across three distinct agro-ecological zones over two years. Environmental indices derived from genotype-environmental interactions, together with defined growth windows, strongly influenced flag leaf appearance (FLA), a photoperiodic flowering trait. Plasticity parameters (intercept and slope) for environmental indices, FLA, grain mold severity, and yield enabled identification of loci contributing to flowering response, mold resistance, and yield stability. The maturity gene Ma1 and two QTLs for FLA, qFLA6.2 and qFLA6.3, were identified, stable across environments, and colocalized with grain mold and yield QTLs. The wild-type Ma1 allele from Grinkan delayed FLA and reduced grain mold damage but was not associated with increased yield. The Ma1 effect was confirmed using the developed breeder-friendly KASP marker, Sbv3.1_06_40312464K, in 174 F3 three-way cross families. Photoperiod-sensitive lines with intermediate-to-late FLA alleles showed strong negative associations with mold damage. Overall, the identified stable loci and candidate lines provide foundations for effective molecular breeding of climate-resilient varieties. PLAIN LANGUAGE SUMMARYGrain mold is a fungal disease that reduces sorghum grain yield and quality, particularly in subhumid climates. With the limited number of resistant elite varieties, photoperiod-sensitive flowering to day length variation can contribute to grain mold escape at the end of rainy seasons. We characterized 286 sorghum recombinant inbred lines across three contrasting environments over two years along rainfall gradients in Senegal. Using flag leaf appearance (FLA), which is a photoperiodic flowering trait, strong genotype-environment interactions for FLA and genotypic plasticity were revealed. We identified and validated the common genomic locus associated with FLA variation and its plasticity across environments, the canonical maturity gene Ma1, which was influenced by temperature variation across environments. The presence of Ma1 in the background of photoperiod-sensitive lines enhances grain mold avoidance and yield stability along rainfall gradients in Senegal. CORE IDEASO_LIWe investigated photoperiodic flowering plasticity in sorghum as a contributor to grain mold resistance and yield stability along rainfall gradients. C_LIO_LIThe Maturity locus Ma1 (qFLA6.1) is the major contributor of photoperiodic flowering and its plasticity across semi-arid and subhumid environments. C_LIO_LIHybrid genotypes carrying two stable loci qFLA6.1 and qFLA6.2 sustain high grain mold avoidance in diverse environments. C_LIO_LIPhotoperiod-sensitive lines with medium to late flowering times are effective in avoiding grain mold, while maintaining yield stability in subhumid regions. C_LI

genetics↗

bioRxiv2025

Deep Learning for Sorghum Yield Forecasting using Uncrewed Aerial Systems and Lab-Derived Imagery

The AI revolution, advanced Graphics Processing Units (GPUs), and open-source platforms have enabled Machine Learning (ML) and Deep Learning (DL) algorithms to rapidly and accurately extract phenotypic features from Uncrewed Aerial System (UAS)-derived imagery. Such advancement leads to phenotypic digitization and sorghum yield forecasting. Yield analytics are critical for breeding programs to assess the genetics and breeding potential of genotypes to enhance cultivar development. This trial followed a three-replicated Randomized Complete Block Design (RCBD) with 36 diverse sorghum genotypes in 2023 at Ashland Bottoms, Kansas. The field images were captured 6 meters above using a DJI M300 drone equipped with the P1 sensor at 90{degrees}nadir and 45{degrees} oblique angles. This research trained YOLO and the Faster R-CNN (Detectron2) models to harness yield attributes from UAS field and lab images. The YOLO models outperformed the Faster R-CNN model in detecting sorghum panicles, achieving a mean average precision at 50% IoU (mAP@0.50) ranging from 0.92 to 0.98, compared to 0.61 to 0.89. Panicle detection from field imagery correlated at 0.86 with ground truth. Lab imagery analyses measured panicle size, seed counts, and seed area with correlation coefficients of 0.71, 0.95, and 0.25, respectively. Three machine learning models: Support Vector Regression (SVR), Decision Tree Regression (DTR), and Random Forest Regression (RFR) are used to predict yield with correlation coefficients of 0.58, 0.76, and 0.70, respectively. We observed that YOLO models are well-suited for extracting yield-attributing traits from images, which are then incorporated into ML regression models to improve yield prediction performance.

plant biology↗

bioRxiv2023

Globally-deployed sorghum aphid resistance gene RMES1 is vulnerable to biotype shifts but being bolstered by RMES2

Durable host plant resistance (HPR) to insect pests is critical for sustainable agriculture. Natural variation exists for aphid HPR in sorghum (Sorghum bicolor) but the genetic architecture and phenotype has not been clarified for most sources. To assess the threat of a sorghum aphid (Melanaphis sorghi) biotype shift, we characterized the phenotype of Resistance to Melanaphis sorghi 1 (RMES1) and contributing HPR architecture in globally-admixed populations selected under severe aphid infestation in Haiti. We found RMES1 reduces sorghum aphid fecundity but not bird cherry-oat aphid (Rhopalosiphum padi) fecundity, suggesting a discriminant HPR response typical of gene-for-gene interaction. A second resistant gene, RMES2, were more frequent than RMES1 resistant alleles in landraces and historic breeding lines. RMES2 contributes early and mid-season aphid resistance in a segregating F2 population, however RMES1 was only significant with mid-season fitness. In a fixed population with high aphid resistance, RMES1 and RMES2 were selected for demonstrating a lack of significant antagonistic pleiotropy. Associations with resistance co-located with cyanogenic glucoside biosynthesis genes support additional HPR sources. Globally, therefore, a vulnerable HPR source (RMES1) is bolstered by a second common source of resistance in breeding programs (RMES2) which may be staving off a biotype shift. HIGHLIGHTThe globally-deployed sorghum aphid resistance gene, RMES1, reduces aphid reproduction and therefore is vulnerable to a biotype shift. A second major gene, RMES2, and cyanogenesis may increase global durability of resistance.

plant biology↗

bioRxiv2023

Field phenomics reveals genetic variation for transpiration response to vapor pressure deficit in sorghum

Drought adaptation for water-limited environments relies on traits that optimize plant water budgets. Limited transpiration (LT) reduces water demand under high vapor pressure deficit (VPD) (i.e., dry air condition), conserving water for efficient use during the reproductive stage. Although studies in controlled environments report genetic variation for LT, confirming its replicability in field conditions is critical for developing water-resilient crops. Here we test the existence of genetic variation for LT in sorghum in field trials and whether canopy temperature (TC) is a surrogate method to discriminate this trait. We phenotyped transpiration response to VPD (TR-VPD) via stomatal conductance (gs), canopy temperature (TC) from fixed IRT sensors (TCirt), and unoccupied aerial system thermal imagery (TCimg) in 11 genotypes. Replicability among phenomic approaches for three genotypes revealed genetic variability for TR-VPD. Genotypes BTx2752 and SC979 carry the LT trait, while genotype DKS54-00 has the non-LT trait. TC can determine differences in TR-VPD. However, the broad sense heritability (H2) and correlations suggest that canopy architecture and stand count hampers TCirt and TCimg measurement. Unexpectedly, observations of gs and VPD showed non-linear patterns for genotypes with LT and non-LT traits. Our findings provide further insights into the genetics of plant water dynamics.

genetics↗

bioRxiv2022

Genomics and Phenomics Enabled Prebreeding Improved Early-Season Chilling Tolerance in Sorghum

In temperate climates, earlier planting of tropical-origin crops can provide longer growing seasons, reduce water loss, suppress weeds, and escape post-flowering drought stress. However, chilling sensitivity of sorghum, a tropical-origin cereal crop, limits early planting and over 50 years of conventional breeding has been stymied by coinheritance of chilling tolerance (CT) loci with undesirable tannin and dwarfing alleles. In this study, phenomics and genomics-enabled approaches were used for prebreeding of sorghum early-season CT. Uncrewed aircraft systems (UAS) high-throughput phenotyping platform tested for improving scalability showed moderate correlation between manual and UAS phenotyping. UAS normalized difference vegetation index (NDVI) values from the chilling nested association mapping population detected CT QTL that colocialized with manual phenotyping CT QTL. Two of the four first-generation KASP molecular markers, generated using the peak QTL SNPs, failed to function in an independent breeding program as the CT allele was common in diverse breeding lines. Population genomic FST analysis identified SNP CT alleles that were globally rare but common to the CT donors. Second-generation markers, generated using population genomics, were successful in tracking the donor CT allele in diverse breeding lines from two independent sorghum breeding programs. Marker-assisted breeding, effective in introgressing CT allele from Chinese sorghums into chilling-sensitive US elite sorghums, improved early-planted seedling performance ratings in lines with CT alleles by up to 13-24% compared to the negative control under natural chilling stress. These findings directly demonstrate the effectiveness of high-throughput phenotyping and population genomics in molecular breeding of complex adaptive traits.

genetics↗

bioRxiv2021

The recent evolutionary rescue of a staple crop depended on over half a century of global germplasm exchange

Rapid environmental change can lead to extinction of populations or evolutionary rescue via genetic adaptation. In the past several years, smallholder and commercial cultivation of sorghum (Sorghum bicolor), a global cereal and forage crop, has been threatened by a global outbreak of an aggressive new biotype of sugarcane aphid (SCA; Melanaphis sacchari). Here we characterized genomic signatures of adaptation in a Haitian sorghum breeding population, which had been recently founded from admixed global germplasm, extensively intercrossed, and subjected to intense selection under SCA infestation. We conducted evolutionary population genomics analyses of 296 post-selection Haitian lines compared to 767 global accessions at 159,683 single nucleotide polymorphisms. Despite intense selection, the Haitian population retains high nucleotide diversity through much of the genome due to diverse founders and an intercrossing strategy. A genome-wide fixation (FST) scan and geographic analyses suggests that adaptation to SCA in Haiti is conferred by a globally-rare East African allele of RMES1, which has also spread to other breeding programs in Africa, Asia, and the Americas. De novo genome sequencing data for SCA resistant and susceptible lines revealed putative causative variants at RMES1. Convenient low-cost markers were developed from the RMES1 selective sweep and successfully predicted resistance in independent U.S. x African breeding lines and eight U.S. commercial and public breeding programs, demonstrating the global relevance of the findings. Together, the findings highlight the potential of evolutionary genomics to develop adaptive trait breeding technology and the value of global germplasm exchange to facilitate evolutionary rescue.

evolutionary biology↗

bioRxiv2019

Genetic Architecture of Chilling Tolerance in Sorghum Dissected with a Nested Association Mapping Population

Dissecting the genetic architecture of stress tolerance in crops is critical to understand and improve adaptation. In temperate climates, early planting of chilling-tolerant varieties could provide longer growing seasons and drought escape, but chilling tolerance (<15{degrees}) is generally lacking in tropical-origin crops. Here we developed a nested association mapping (NAM) population to dissect the genetic architecture of early-season chilling tolerance in the tropical-origin cereal sorghum (Sorghum bicolor [L.] Moench). The NAM resource, developed from reference line BTx623 and three chilling-tolerant Chinese lines, is comprised of 771 recombinant inbred lines genotyped by sequencing at 43,320 single nucleotide polymorphisms. We phenotyped the NAM population for emergence, seedling vigor, and agronomic traits (>75,000 data points from [~]16,000 plots) in multi-environment field trials in Kansas under natural chilling stress (sown 30-45 days early) and normal growing conditions. Joint linkage mapping with early-planted field phenotypes revealed an oligogenic architecture, with 5-10 chilling tolerance loci explaining 20-41% of variation. Surprisingly, several of the major chilling tolerance loci co-localize precisely with the classical grain tannin (Tan1 and Tan2) and dwarfing genes (Dw1 and Dw3) that were under strong directional selection in the US during the 20th century. These findings suggest that chilling sensitivity was inadvertently selected due to coinheritance with desired nontannin and dwarfing alleles. The characterization of genetic architecture with NAM reveals why past chilling tolerance breeding was stymied and provides a path for genomics-enabled breeding of chilling tolerance.\n\nArticle SummaryChilling sensitivity limits productivity of tropical-origin crops in temperate climates, and remains poorly understood at a genetic level. We developed a nested association mapping resource in sorghum, a tropical-origin cereal, to understand the genetic architecture of chilling tolerance. Linkage mapping of growth traits from early-planted field trials revealed several major chilling tolerance loci, including some colocalized with genes that were selected in the origin of US grain sorghum. These findings suggest chilling sensitivity was inadvertently selected during 20th century breeding, but can be bypassed using a better understanding of the underlying genetic architecture.\n\nDisclaimerMention of a trademark, warranty, proprietary product, or vendor does not constitute a guarantee by the USDA and does not imply approval or recommendation of the product to the exclusion of others that may be suitable. USDA is an equal opportunity provider and employer.

genetics↗