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1. Protein, weight, and oil prediction by single‐seed near‐infrared spectroscopy for selection of seed quality and yield traits in pea ( Pisum sativum )

   https://doi.org/10.1002/jsfa.10389  

   Hacisalihoglu, Gokhan ; Freeman, Jelani ; Armstrong, Paul R. ; Seabourn, Brad W. ; Porter, Lyndon D. ; Settles, A. Mark ; Gustin, Jeffery L. ( April 2020 , Journal of the Science of Food and Agriculture)

   Pea (Pisum sativum) is a prevalent cool‐season crop that produces seeds valued for their high protein content. Modern cultivars have incorporated several traits that improved harvested yield. However, progress toward improving seed quality has received less emphasis, in part due to the lack of tools for easily and rapidly measuring seed traits. In this study we evaluated the accuracy of single‐seed near‐infrared spectroscopy (NIRS) for measuring pea‐seed weight, protein, and oil content. A total of 96 diverse pea accessions were analyzed using both single‐seed NIRS and wet chemistry methods. To demonstrate field relevance, the single‐seed NIRS protein prediction model was used to determine the impact of seed treatments and foliar fungicides on the protein content of harvested dry peas in a field trial.

   External validation of partial least squares (PLS) regression models showed high prediction accuracy for protein and weight (R²= 0.94 for both) and less accuracy for oil (R²= 0.74). Single‐seed weight was weakly correlated with protein and oil content in contrast with previous reports. In the field study, the single‐seed NIRS predicted protein values were within 10 mg g⁻¹of an independent analytical reference measurement and were sufficiently precise to detect small treatment effects.

   The high accuracy of protein and weight estimation show that single‐seed NIRS could be used in the dual selection of high‐protein, high‐weight peas early in the breeding cycle, allowing for faster genetic advancement toward improved pea nutritional quality. © 2020 Society of Chemical Industry

    

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2. Harnessing Genetic Diversity in the USDA Pea Germplasm Collection Through Genomic Prediction

   https://doi.org/10.3389/fgene.2021.707754  

   Bari, Md. Abdullah ; Zheng, Ping ; Viera, Indalecio ; Worral, Hannah ; Szwiec, Stephen ; Ma, Yu ; Main, Dorrie ; Coyne, Clarice J. ; McGee, Rebecca J. ; Bandillo, Nonoy ( December 2021 , Frontiers in Genetics)

   Phenotypic evaluation and efficient utilization of germplasm collections can be time-intensive, laborious, and expensive. However, with the plummeting costs of next-generation sequencing and the addition of genomic selection to the plant breeder’s toolbox, we now can more efficiently tap the genetic diversity within large germplasm collections. In this study, we applied and evaluated genomic prediction’s potential to a set of 482 pea ( Pisum sativum L.) accessions—genotyped with 30,600 single nucleotide polymorphic (SNP) markers and phenotyped for seed yield and yield-related components—for enhancing selection of accessions from the USDA Pea Germplasm Collection. Genomic prediction models and several factors affecting predictive ability were evaluated in a series of cross-validation schemes across complex traits. Different genomic prediction models gave similar results, with predictive ability across traits ranging from 0.23 to 0.60, with no model working best across all traits. Increasing the training population size improved the predictive ability of most traits, including seed yield. Predictive abilities increased and reached a plateau with increasing number of markers presumably due to extensive linkage disequilibrium in the pea genome. Accounting for population structure effects did not significantly boost predictive ability, but we observed a slight improvement in seed yield. By applying the best genomic prediction model (e.g., RR-BLUP), we then examined the distribution of genotyped but nonphenotyped accessions and the reliability of genomic estimated breeding values (GEBV). The distribution of GEBV suggested that none of the nonphenotyped accessions were expected to perform outside the range of the phenotyped accessions. Desirable breeding values with higher reliability can be used to identify and screen favorable germplasm accessions. Expanding the training set and incorporating additional orthogonal information (e.g., transcriptomics, metabolomics, physiological traits, etc.) into the genomic prediction framework can enhance prediction accuracy. 

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3. Evidence for divergence of response in Indica , Japonica , and wild rice to high CO 2 × temperature interaction

   https://doi.org/10.1111/gcb.13279  

   Wang, Diane R. ; Bunce, James A. ; Tomecek, Martha B. ; Gealy, David ; McClung, Anna ; McCouch, Susan R. ; Ziska, Lewis H. ( April 2016 , Global Change Biology)

   HighCO₂and high temperature have an antagonistic interaction effect on rice yield potential and present a unique challenge to adapting rice to projected future climates. Understanding how the differences in response to these two abiotic variables are partitioned across rice germplasm accessions may be key to identifying potentially useful sources of resilient alleles for adapting rice to climate change. In this study, we evaluated eleven globally diverse rice accessions under controlled conditions at two carbon dioxide concentrations (400 and 600 ppm) and four temperature environments (29 °C day/21 °C night; 29 °C day/21 °C night with additional heat stress at anthesis; 34 °C day/26 °C night; and 34 °C day/26 °C night with additional heat stress at anthesis) for a suite of traits including five yield components, five growth characteristics, one phenological trait, and four photosynthesis‐related measurements. Multivariate analyses of mean trait data from these eight treatments divide our rice panel into two primary groups consistent with the genetic classification ofINDICA/INDICA‐like andJAPONICApopulations. Overall, we find that the productivity of plants grown under elevated [CO₂] was more sensitive (negative response) to high temperature stress compared with that of plants grown under ambient [CO₂] across this diversity panel. We report differential response toCO₂× temperature interaction forINDICA/INDICA‐like andJAPONICArice accessions and find preliminary evidence for the beneficial introduction of exotic alleles into cultivated rice genomic background. Overall, these results support the idea of using wild or currently unadapted gene pools in rice to enhance breeding efforts to secure future climate change adaptation.

    

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4. Direct and indirect selection on flowering time, water‐use efficiency ( WUE , δ 13 C), and WUE plasticity to drought in Arabidopsis thaliana

   https://doi.org/10.1002/ece3.1270  

   Kenney, Amanda M. ; McKay, John K. ; Richards, James H. ; Juenger, Thomas E. ( November 2014 , Ecology and Evolution)

   Flowering time and water‐use efficiency (WUE) are two ecological traits that are important for plant drought response. To understand the evolutionary significance of natural genetic variation in flowering time,WUE, andWUEplasticity to drought inArabidopsis thaliana, we addressed the following questions: (1) How are ecophysiological traits genetically correlated within and between different soil moisture environments? (2) Does terminal drought select for early flowering and drought escape? (3) IsWUEplasticity to drought adaptive and/or costly? We measured a suite of ecophysiological and reproductive traits on 234 spring flowering accessions ofA. thalianagrown in well‐watered and season‐ending soil drying treatments, and quantified patterns of genetic variation, correlation, and selection within each treatment.WUEand flowering time were consistently positively genetically correlated.WUEwas correlated withWUEplasticity, but the direction changed between treatments. Selection generally favored early flowering and lowWUE, with drought favoring earlier flowering significantly more than well‐watered conditions. Selection for lowerWUEwas marginally stronger under drought. There were no net fitness costs ofWUEplasticity.WUEplasticity (per se) was globally neutral, but locally favored under drought. Strong genetic correlation betweenWUEand flowering time may facilitate the evolution of drought escape, or constrain independent evolution of these traits. Terminal drought favored drought escape in these spring flowering accessions ofA. thaliana.WUEplasticity may be favored over completely fixed development in environments with periodic drought.

    

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5. Patterns of genetic variation in a prairie wildflower, Silphium integrifolium , suggest a non‐prairie origin and locally adaptive variation

   https://doi.org/10.1002/ajb2.1603  

   Raduski, Andrew R. ; Herman, Adam ; Pogoda, Cloe ; Dorn, Kevin M. ; Van Tassel, David L. ; Kane, Nolan ; Brandvain, Yaniv ( January 2021 , American Journal of Botany)

   Understanding the relationship between genetic structure and geography provides information about a species’ history and can be used for breeding and conservation goals. The North American prairie is interesting because of its recent origin and subsequent fragmentation.Silphium integrifolium, an iconic perennial American prairie wildflower, is targeted for domestication, having undergone a few generations of improvement. We present the first application of population genetic data in this species to address the following goals: (1) improve breeding by characterizing genetic structure and (2) identify the species geographic origin and potential targets and drivers of selection during range expansion.

   We developed a reference transcriptome as a genotyping reference for samples from throughout the species range. Population genetic analyses were used to describe patterns of genetic variation, and demographic modeling was used to characterize potential processes that shaped variation. Outlier scans for selection and associations with environmental variables were used to identify loci linked to putative targets and drivers of selection.

   Genetic variation partitioned samples into three geographic clusters. Patterns of variation and demographic modeling suggest that the species origin is in the American Southeast. Breeding program accessions are from the region with lowest observed genetic variation.

   This prairie species did not originate within the prairie. Breeding may be improved by including accessions from outside of the germplasm founding region. The geographic structuring and the identified targets and drivers of adaptation can guide collecting efforts toward populations with beneficial agronomic traits.

    

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