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Murphy, J. P.

Publications and source records attributed to Murphy, J. P..

7 recordsLinked to original sources

Environmentally-mediated yield effects of vernalization and photoperiod alleles in historic winter wheat trials

In common wheat (Triticum aestivum L.), variation at the Vrn1 and Ppd1 loci changes plant phenology, resulting in differential adaptation useful to breeders. Because the effects of phenology on grain yield are conditional on environmental factors, the incorporation of markers for Vrn1 and Ppd1 alleles into breeding approaches has proven difficult. Historic phenotypic, genotypic, and environmental data can provide insight into the relationship between major phenology alleles and grain yield as mediated by environmental variables. Analyses of eight years of breeding trials (1,038 lines at 219 site-years) determined that weak vrn1 alleles and Ppd1 insensitivity alleles have variable effects. These effects change depending on an environment's winter temperature and latitude, respectively, but the environmentally-driven changes in effect of vrn1 alleles are much more variable than effects of Ppd1 alleles. Mediation analyses showed phenologically-dependent environmental variables are one mechanism through which phenological changes created by vrn1 and Ppd1 variants alter yield across multiple developmental stages. Environmentally-driven relationships between flowering time and yield were modeled to estimate yield allele effects as a function of effects on phenology and environmental variables. Weak winter alleles at vrn1 may play a stabilizing role on yield, due to the correlation of winter conditions that drive larger effects with later-season warm temperatures that penalize later maturity. A better mechanistic understanding of how these loci drive environment-specific yield effects may facilitate utilization of markers for these alleles and improve predictive modeling of yield.

genetics↗

Promoter hijacking by primate LINC00473 disrupts an ancestral CREB-PDE10A feedback loop

Thousands of human long noncoding RNAs (lncRNAs) evolved in primates, although much remains unknown about how these lncRNAs shaped human gene regulatory networks. The primate-specific lncRNA gene LINC00473 has a CREB-inducible promoter that is conserved beyond primates and the gene is located upstream of PDE10A, which encodes an inhibitor of CREB. To gain insight into the regulatory consequences of LINC00473 acquisition, we tested the cellular function of the conserved mouse promoter. We found that the homologous mouse promoter is induced by CREB and regulates the downstream Pde10a gene in C2C12 myoblast-like cells and neurons. Activation of this promoter by CRISPRa increased Pde10a transcript and protein levels, and proteomics revealed that elevated Pde10a promoted C2C12 differentiation at the expense of proliferation. Activation of Pde10a by CRISPRa also impaired CREB-dependent gene expression, suggesting that the mouse homolog of the LINC00473 promoter drives a CREB-Pde10a feedback loop. In contrast to the mouse homolog, human LINC00473 promoter activation by CRISPRa increased LINC00473 expression with either no change in PDE10A or delayed induction compared to mice. Our findings suggest that the newly evolved LINC00473 gene hijacked an ancestral CREB-inducible Pde10a promoter, thereby disrupting a negative feedback loop that may otherwise constrain CREB-dependent gene expression. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=87 SRC="FIGDIR/small/680088v1_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@1862846org.highwire.dtl.DTLVardef@be3ca8org.highwire.dtl.DTLVardef@1806b36org.highwire.dtl.DTLVardef@1fedc56_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

Bearded or Smooth? Awns Improve Yield when Wheat Experiences Heat Stress During Grain Fill

The presence or absence of awns - whether wheat heads are "bearded" or "smooth"- is the most visible phenotype distinguishing wheat cultivars. Previous studies suggest that awns may improve yields in heat or water-stressed environments, but the exact contribution of awns to yield differences remains unclear. Here we leverage historical phenotypic, genotypic, and climate data to estimate the yield effects of awns under different environmental conditions over a 12-year period in the Southeast US. Lines were classified as awned or awnless based on sequence data, and observed heading dates were used to associate grain fill periods of each line in each environment with climatic data and grain yield. In most environments, awn suppression was associated with higher yields, but awns were associated with better performance in heat-stressed environments more common at southern locations. Wheat breeders in environments where awns are only beneficial in some years may consider selection for awned lines to reduce year-to-year yield variability, and with an eye towards future climates.

genetics↗

UTILIZATION OF A PUBLICLY AVAILABLE DIVERSITY PANEL IN GENOMIC PREDICTION OF FUSARIUM HEAD BLIGHT RESISTANCE TRAITS IN WHEAT

Fusarium head blight (FHB) is an economically and environmentally concerning disease of wheat (Triticum aestivum L). A two-pronged approach of marker assisted selection (MAS) coupled with genomic selection (GS) has been suggested when breeding for FHB resistance. An historical dataset comprised of entries in the Southern Uniform Winter Wheat Scab Nursery (SUWWSN) from 2011-2021 was partitioned and used in genomic prediction. Two traits were curated from 2011-2021 in the SUWWSN: percent Fusarium damaged kernels (FDK) and Deoxynivalenol (DON) content. Heritability was estimated for each trait-by-environment combination. A consistent set of check lines was drawn from each year in the SUWWSN, and K-means clustering was performed across environments to assign environments into clusters. Two clusters were identified for FDK and three for DON. Cross-validation on SUWWSN data from 2011-2019 indicated no outperforming training population in comparison to the combined dataset. Forward validation for FDK on the SUWWSN 2020 and 2021 data indicated a predictive accuracy r {approx} 0.58 and r {approx} 0.53, respectively. Forward validation for DON indicated a predictive accuracy of r {approx} 0.57 and r {approx} 0.45, respectively. Forward validation using environments in cluster one for FDK indicated a predictive accuracy of r {approx} 0.65 and r {approx} 0.60, respectively. Forward validation using environments in cluster one for DON indicated a predictive accuracy of r {approx} 0.67 and r {approx} 0.60, respectively. These results indicated that selecting environments based on check performance may produce higher forward prediction accuracies. This work may be used as a model to create a public resource for genomic prediction of FHB resistance traits across public wheat breeding programs. CORE IDEASO_LIThe data from the Southern Uniform Winter Wheat Nursery may be used for genomic prediction. C_LIO_LICreating training populations based on like-check performance improves forward genomic predictive accuracies. C_LIO_LIFiltering out locations with low genomic, per-plot, narrow-sense heritability may improve predictive accuracies. C_LI

plant biology↗

Discovery of Potent Pyrazoline-Based Covalent SARS-CoV-2 Main Protease Inhibitors

While vaccines and antivirals are now being deployed for the current SARS-CoV-2 pandemic, we require additional antiviral therapeutics to not only effectively combat SARS-CoV-2 and its variants, but also future coronaviruses. All coronaviruses have relatively similar genomes that provide a potential exploitable opening to develop antiviral therapies that will be effective against all coronaviruses. Among the various genes and proteins encoded by all coronaviruses, one particularly "druggable" or relatively easy-to-drug target is the coronavirus Main Protease (3CLpro or Mpro), an enzyme that is involved in cleaving a long peptide translated by the viral genome into its individual protein components that are then assembled into the virus to enable viral replication in the cell. Inhibiting Mpro with a small-molecule antiviral would effectively stop the ability of the virus to replicate, providing therapeutic benefit. In this study, we have utilized activity-based protein profiling (ABPP)-based chemoproteomic approaches to discover and further optimize cysteine-reactive pyrazoline-based covalent inhibitors for the SARS-CoV-2 Mpro. Structure-guided medicinal chemistry and modular synthesis of di- and tri-substituted pyrazolines bearing either chloroacetamide or vinyl sulfonamide cysteine-reactive warheads enabled the expedient exploration of structure-activity relationships (SAR), yielding nanomolar potency inhibitors against Mpro from not only SARS-CoV-2, but across many other coronaviruses. Our studies highlight promising chemical scaffolds that may contribute to future pan-coronavirus inhibitors.

biochemistry↗

Genetic variation for plant growth traits in a common wheat population is dominated by known variants and novel QTL

Genetic variation in growth over the course of the season is a major source of grain yield variation in wheat, and for this reason variants controlling heading date and plant height are among the best-characterized in wheat genetics. While the major variants for these traits have been cloned, the importance of these variants in contributing to genetic variation for plant growth over time is not fully understood. Here we develop a biparental population segregating for major variants for both plant height and flowering time to characterize the genetic architecture of the traits and identify additional novel QTL. We find that additive genetic variation for both traits is almost entirely associated with major and moderate-effect QTL, including four novel heading date QTL and four novel plant height QTL. FT2 and Vrn-A3 are proposed as candidate genes underlying QTL on chromosomes 3A and 7A, while Rht8 is mapped to chromosome 2D. These mapped QTL also underlie genetic variation in a longitudinal analysis of plant growth over time. The oligogenic architecture of these traits is further demonstrated by the superior trait prediction accuracy of QTL-based prediction models compared to polygenic genomic selection models. In a population constructed from two modern wheat cultivars adapted to the southeast U.S., almost all additive genetic variation in plant growth traits is associated with known major variants or novel moderate-effect QTL. Major transgressive segregation was observed in this population despite the similar plant height and heading date characters of the parental lines. This segregation is being driven primarily by a small number of mapped QTL, instead of by many small-effect, undetected QTL. As most breeding populations in the southeast U.S. segregate for known QTL for these traits, genetic variation in plant height and heading date in these populations likely emerges from similar combinations of major and moderate effect QTL. We can make more accurate and cost-effective prediction models by targeted genotyping of key SNPs.

genetics↗

Sequence based mapping identifies AWNS1, a candidate transcription repressor underlying awn suppression at the B1 locus in wheat

Awns are stiff, hair-like structures that grow from the spikelets of wheat (Triticum aestivum L.) and other grasses. In wild wheat relatives, awns play a role in seed dispersal. Awn suppression in domesticated wheat, where awns are shortened or even eliminated entirely, is variably adaptive with both awned and awnless types under widespread cultivation. Although the B1 locus on the long arm of chromosome 5A is a major determinant of awn suppression, no underlying gene or mechanism of action has been identified. Using association mapping, we identified a SNP marker located on the distal end of 5AL (5A28417) predictive of awn status in a panel of 640 U.S. winter wheat breeding lines, indicating that B1 was the determinant of awn suppression in this germplasm. Analysis of historical data available for the panel determined 5A28417 was also significantly associated with grain test weight. Evaluation of spike morphology and kernel traits was undertaken in a 341 RIL population developed from a cross between awned soft winter wheat cultivar LA95135 and awnless cultivar SS-MPV57. Awn suppression in the population co-segregated with 5A28417 and was co-located with QTL for number of spikelets per spike, kernel weight and kernel length. Fine-mapping located B1 to a region containing only two predicted genes, including a C2H2 zinc finger transcription factor 219 bp from 5A28417 that we named AWNS-A1. Deletions encompassing both genes were present in awned mutants of the awnless cultivar Brundage. Polymorphisms in the AWNS-A1 coding region were not observed in diverse wheat germplasm. However, sequencing of wheat lines representing different marker haplotypes in the surrounding region identified a deletion 3 kb downstream of AWNS-A1. A marker for this deletion was highly predictive of awn suppression in a collection of diverse wheat accessions, and indicates that AWNS-A1 is likely the major determinant of awn suppression in global wheat germplasm. AWNS-A1 is more highly expressed in developing spikes of awnless individuals, suggesting a mechanism for awn suppression.

genetics↗