Biology subjects

Parker, T. A.

Publications and source records attributed to Parker, T. A..

5 recordsLinked to original sources

bioRxiv2026

Genotypic and multi-environment phenotypic evaluation of the lima bean USDA National Plant Germplasm System collection

Lima bean (Phaseolus lunatus L.) is an economically and agronomically important grain legume. Lima beans (or limas) show a range of climatic adaptations with independent domestications in the Andes (large-seeded) and Mesoamerica (small- or medium-seeded). We generated and integrated genotypic and comprehensive field- and laboratory-based phenotypic information for the available accessions in the USDA National Plant Germplasm System collection across multiple environments to inform germplasm utilization in breeding. A total of 810 accessions were genotyped using short-read, low-coverage sequencing. Accession geographic origin and domestication explained population structure. A partially overlapping subset of the panel (n=141-308) was field-evaluated across two years in each of Davis, CA, Central Ferry, WA, and Coachella Valley, CA (the latter was fall-planted for evaluation of photoperiod-sensitive accessions) to assess trait performance in contrasting environments. Agronomic traits such as determinacy and flowering time, and seed traits such as seed coat color and hundred-seed weight, were scored. Macronutrient traits (protein, starch, fat, and ash content) were measured on dry (mature) harvested grain via near-infrared spectroscopy. Genome-wide association analyses identified loci significantly associated with descriptive, agronomic, and seed traits, including orthologs of known genes in common bean and novel candidate regions. Genomic predictive abilities were moderate to high for key traits. Finally, we established a conditional core collection that was constrained to include 211 extensively phenotyped accessions and for which 91 supplemental accessions were selected to maximize genetic diversity from among the genotyped accessions. Overall, these resources provide a foundation to support genomics-assisted breeding of limas.

plant biology↗

bioRxiv2026

Genotypic and environmental effects on seed coat patterning and nutritional composition in common bean (Phaseolus vulgaris L.)

Common bean (Phaseolus vulgaris L.) is the leading grain legume consumed directly by humans and a primary source of nutrients in many communities. This study utilized common bean genotypes with diverse seed coat phenotypes to investigate genotypic and environmental effects on pigmented seed coat area and seed macronutrient (protein, starch, fat, ash, moisture), anti-nutrient (phytate), and mineral nutrient (iron, zinc, calcium, phosphorus, magnesium, potassium, sodium) profiles. Recombinant inbred lines (RILs) that comprise six phenotypic classes for seed coat patterning and nine commercial cultivars were field-evaluated for multiple years across inland, coastal, and intermountain environments in California. A custom near-infrared spectroscopy calibration improved macronutrient prediction accuracy relative to a pre-existing calibration. Environmental effects on macronutrients were pronounced; the 2022 coastal growing environment was the most distinct, characterized by significantly higher starch and moisture content and significantly lower protein content in the RILs relative to any other environments. Across growing years in the RILs, greater consistency was observed at the inland site, where only protein was significantly different; all macronutrient traits significantly differed within the intermountain site. Certain commercial cultivars largely maintained their relative rank for protein content across environments, indicating consistency of genotypic performance, and Black Nightfall ranked among the highest for iron, zinc, phosphorus, and magnesium. Percent pigmented seed coat area was significantly negatively correlated with both calcium and magnesium concentrations. These results underscore the importance of genotype-by-environment field trials for seed coat patterning, seed nutritional composition, and their interplay, to support breeding of common bean among other grain legumes. HighlightsO_LICustom near-infrared spectroscopy (NIRS) calibration improved prediction accuracies C_LIO_LIEnvironmental effects significantly influenced common bean macronutrient composition C_LIO_LICertain cultivars ranked consistently for macronutrient traits across environments C_LIO_LISeed coat pattern was significantly associated with mineral nutrient concentrations C_LI

plant biology↗

bioRxiv2025

Drone methods and educational resources for plant science and agriculture

Technological advances have made drones (UAVs) increasingly important tools for the collection of trait data in plant science. Many costs for the analysis of plant populations have dropped precipitously in recent decades, particularly for genetic sequencing. Similarly, hardware advances have made it increasingly simple and practical to capture drone imagery of plant populations.However, converting this imagery into high-precision and high-throughput tabular data has become a major bottleneck in plant science. Here, we describe high-throughput phenotyping methods for the analysis of numerous plant traits based on imagery from diverse sensor types. Methods can be flexibly combined to extract data related to canopy temperature, area, height, volume, vegetation indices, and summary statistics derived from complex segmentations and classifications. We then describe educational and training resources for these methods, including a web page (PlantScienceDroneMethods.github.io) and an educational YouTube channel (https://www.youtube.com/@travisparkerplantscience) with step-by-step protocols, example data, and example scripts for the whole drone data processing pipeline. These resources facilitate the extraction of high-throughput and high-precision phenomic data, removing barriers to the phenomic analysis of large plant populations.

plant biology↗

bioRxiv2025

Developing a model to implement marker-assisted selection for root-knot nematode resistance in common bean

Common bean (Phaseolus vulgaris L.) is a vital crop for direct human consumption, with essential nutrients and valuable protein that provides food security in developing countries. However, its cultivation faces significant threats from Meloidogyne incognita, a root-knot nematode (RKN), resulting in considerable yield loss. Developing crop resistance remains a key strategy for mitigating nematode infections. To investigate the genetic architecture of common bean responses to RKN (specifically, race 3 of M. incognita), we performed controlled crosses between the genotypes IAC-Tybata and Branquinho with contrasting resistance. The resulting segregating population (F2) of 333 individuals was genotyped using GBS (genotyping-by-sequencing). We used a phenotyping approach, already optimized in the lab, to collect trait data for a subset of 200 F2:3 families. Evaluations of egg mass (EM), root-galling index (GI), and root dry mass (RM) were conducted 30 days after RKN inoculation under greenhouse conditions, in a completely randomized design with ten replicates. Linkage and quantitative trait loci (QTL) mapping were performed, while functional mapping of associated regions facilitated identification of candidate genes. A linkage map encompassing 954 SNPs assigned to 11 linkage groups totaling 1,687 cM formed the basis for Interval Mapping (IM), Composite Interval Mapping (CIM), and Multiple Interval Mapping (MIM), revealing four major QTLs (on Pv03, Pv05, Pv08, and Pv10) and epistasis between QTL on Pv08 and on Pv10 associated with the GI trait. No significant QTL were identified for EM and RM. The model enabled calculation of genotypic values through marker-assisted selection (MAS). The high correlation between observed and predicted values (0.72) underscores the models significance. Candidate genes previously associated with nematode resistance were also identified within the QTL interval on chromosome Pv10. Our results will be valuable for future selection of varieties resistant to this important crop disease.

genetics↗

bioRxiv2024

QTL Mapping for Pod Quality and Yield Traits in Snap Bean (Phaseolus vulgaris L.)

Pod quality and yield traits in snap bean (Phaseolus vulgaris L.) influence consumer preferences, crop adoption by farmers, and the ability of the product to be commercially competitive locally and globally. The objective of the study was to identify the quantitative trait loci (QTL) for pod quality and yield traits in a snap x dry bean recombinant inbred line (RIL) population. A total of 184 F6 RILs derived from a cross between Vanilla (snap bean) and MCM5001 (dry bean) were grown in three field sites in Kenya and one greenhouse environment in Davis, CA, USA. They were genotyped at 5,951 single nucleotide polymorphisms (SNPs), and composite interval mapping was conducted to identify QTL for 16 pod quality and yield traits, including pod wall fiber, pod string, pod size, and harvest metrics. A combined total of 44 QTL were identified in field and greenhouse trials. The QTL for pod quality were identified on chromosomes Pv01, Pv02, Pv03, Pv04, Pv06, and Pv07, and for pod yield were identified on Pv08. Co-localization of QTL was observed for pod quality and yield traits. Some identified QTL overlapped with previously mapped QTL for pod quality and yield traits, with several others identified as novel. The identified QTL can be used in future marker-assisted selection in snap bean.

plant biology↗