Bearded or smooth? Awns improve yield when wheat experiences heat stress during grain fill in the southeastern United States.

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 for wheat (Triticum aestivum) to estimate the yield effects of awns under different environmental conditions over a 12-year period in the southeastern USA. 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.

Genome-wide association mapping of the 'super-soft' kernel texture in white winter wheat.

KEY MESSAGE: The novel super-soft kernel phenotype has the potential to improve wheat processing and flour quality. We identified genomic regions associated with this kernel texture in white winter wheat. Grain hardness is a key determinant of wheat milling and baking quality. The recently discovered 'super-soft' kernel phenotype has the potential to improve wheat processing and flour quality. However, the genetic basis underlying the super-soft trait in wheat is not yet well understood. In this study, we investigated the phenotypic and genotypic structure of the super-soft trait in a collection of 172 advanced soft white winter wheat breeding lines and cultivars adapted to the Pacific Northwest region of the USA. This collection had a continuous distribution for grain hardness index (single-kernel characterization system). Ten super-soft genotypes showed hardness index ≤ 12 including the cultivar Jasper. Over 98,000 SNP markers from genotyping-by-sequencing were used for association mapping (GWAS). The GWAS identified 20 significant markers associated with grain hardness. These significant SNPs corresponded to seven QTL on chromosomes 2B, 3A, 3B, 5A, 6B,7A, and one unaligned chromosome. Two of these QTL, QSKhard.wql-3A and QSKhard.wql-5A, had large effects and distinguished between the normal soft and the super-soft classes. QSKhard.wql-3A and QSKhard.wql-5A reduced the hardness index by 11.7 and 13.1 on average, respectively. The remaining QTL had small effects and reduced grain hardness within the normal soft range. QSKhard.wql-2B, QSKhard.wql-3A, QSKhard.wql-3B, and QSKhard.wql-6B were not previously reported to be in genomic regions of grain hardness-related genes/QTL. The identified super-soft genotypes as well as the SNPs associated with lower grain hardness will be useful to assist breeding for this grain texture trait.

Genomic Prediction and Indirect Selection for Grain Yield in US Pacific Northwest Winter Wheat Using Spectral Reflectance Indices from High-Throughput Phenotyping.

Secondary traits from high-throughput phenotyping could be used to select for complex target traits to accelerate plant breeding and increase genetic gains. This study aimed to evaluate the potential of using spectral reflectance indices (SRI) for indirect selection of winter-wheat lines with high yield potential and to assess the effects of including secondary traits on the prediction accuracy for yield. A total of five SRIs were measured in a diversity panel, and F5 and doubled haploid wheat breeding populations planted between 2015 and 2018 in Lind and Pullman, WA. The winter-wheat panels were genotyped with 11,089 genotyping-by-sequencing derived markers. Spectral traits showed moderate to high phenotypic and genetic correlations, indicating their potential for indirect selection of lines with high yield potential. Inclusion of correlated spectral traits in genomic prediction models resulted in significant (p < 0.001) improvement in prediction accuracy for yield. Relatedness between training and test populations and heritability were among the principal factors affecting accuracy. Our results demonstrate the potential of using spectral indices as proxy measurements for selecting lines with increased yield potential and for improving prediction accuracy to increase genetic gains for complex traits in US Pacific Northwest winter wheat.

Evaluating the thermostability of commercial fast real-time PCR master mixes.

There is an increasing need for affordable, thermostable PCR reagents that can be used for diagnostic testing in resource limited settings. The development of point-of-care devices in such settings is highly dependent on the availability and efficacy of thermostable reagents. Here, we assess the thermostability of commercial, intercalating dye-based real-time PCR master mixes. We show that several of these master mixes have thermostability and robust performance at 20°C, 40°C, and 45°C for 6, 4 and 2 weeks, respectively. However, none of the master mixes that we evaluated was able to withstand more than 1 month at 45°C incubation. Our findings have implications for clinical diagnostics in the developing world where cold-chain delivery of diagnostic assays is difficult to guarantee.

MicroRNAs in chronic lymphocytic leukemia.

Chronic lymphocytic leukemia (CLL) is the most common leukemia in the western world. Recent research, conducted primarily in basic science laboratories, has indicated a role for microRNAs (miRNAs) in the pathogenesis and prognosis of this disease. MiRNAs are small, non-coding, functional RNAs, that mediate post-transcriptional inhibition of messenger RNAs. Because miRNA expression levels in CLL patients differ from that of normal patients, there may be a role for these novel small molecules as biomarkers in this disease.

Predicting Fusarium Head Blight Resistance for Advanced Trials in a Soft Red Winter Wheat Breeding Program With Genomic Selection.

Many studies have evaluated the effectiveness of genomic selection (GS) using cross-validation within training populations; however, few have looked at its performance for forward prediction within a breeding program. The objectives for this study were to compare the performance of naïve GS (NGS) models without covariates and multi-trait GS (MTGS) models by predicting two years of F4: 7 advanced breeding lines for three Fusarium head blight (FHB) resistance traits, deoxynivalenol (DON) accumulation, Fusarium damaged kernels (FDK), and severity (SEV) in soft red winter wheat and comparing predictions with phenotypic performance over two years of selection based on selection accuracy and response to selection. On average, for DON, the NGS model correctly selected 69.2% of elite genotypes, while the MTGS model correctly selected 70.1% of elite genotypes compared with 33.0% based on phenotypic selection from the advanced generation. During the 2018 breeding cycle, GS models had the greatest response to selection for DON, FDK, and SEV compared with phenotypic selection. The MTGS model performed better than NGS during the 2019 breeding cycle for all three traits, whereas NGS outperformed MTGS during the 2018 breeding cycle for all traits except for SEV. Overall, GS models were comparable, if not better than phenotypic selection for FHB resistance traits. This is particularly helpful when adverse environmental conditions prohibit accurate phenotyping. This study also shows that MTGS models can be effective for forward prediction when there are strong correlations between traits of interest and covariates in both training and validation populations.

Analysis of the primary sources of quantitative adult plant resistance to stripe rust in U.S. soft red winter wheat germplasm.

Stripe rust, or yellow rust (Puccinia striiformis Westend. f. sp. tritic), is a disease of wheat (Triticum aestivum L.) historically causing significant economic losses in cooler growing regions. Novel isolates of stripe rust with increased tolerance for high temperatures were detected in the United States circa 2000. This increased heat tolerance puts geographic regions, such as the soft red winter wheat (SRWW) growing region of the southeastern United States, at greater risk of stripe rust induced losses. In order to identify sources of stripe rust resistance in contemporary germplasm, we conducted genome-wide association (GWA) studies on stripe rust severity measured in two panels. The first consisted of 273 older varieties, landraces, and some modern elite breeding lines and was evaluated in environments in the U.S. Pacific Northwest and the southeastern United States. The second panel consisted of 588 modern, elite SRWW breeding lines and was evaluated in four environments in Arkansas and Georgia. The analyses identified three major resistance loci on chromosomes: 2AS (presumably the 2NS:2AS alien introgression from Aegilops ventricosa Tausch; syn. Ae. caudata L.), 3BS, and 4BL. The 4BL locus explained a greater portion of variance in resistance than either the 2AS or 3BS loci in southeastern environments. However, its effects were unstable across different environments and sets of germplasm, possibly a result of its involvement in epistatic interactions. Relatively few lines carry resistance alleles at all three loci, suggesting that there is a pre-existing reservoir of enhanced stripe rust resistance that may be further exploited by regional breeding programs.

Gains through selection for grain yield in a winter wheat breeding program.

Increased genetic gain for complex traits in plant breeding programs can be achieved through different selection strategies. The objective of this study was to compare potential gains for grain yield in a winter wheat breeding program through estimating response to selection R values across several selection approaches including phenotypic (PS), marker-based (MS), genomic (GS), and a combination of PS and GS (PS+GS). Ten populations of Washington State University (WSU) winter wheat breeding lines including a diversity panel and F5 and double haploid lines evaluated from 2015 to 2019 growing seasons for grain yield in Lind and Pullman, WA, USA were used in the study. Selection was conducted by selecting the top 20% of lines based on observed yield (PS strategy), genomic estimated breeding values (GS), presence of yield "enhancing" alleles of the most significant single nucleotide polymorphism (SNP) markers identified from genome-wide association mapping (MS), and high observed yield and estimated breeding values (PS+GS). Overall, PS compared to other individual selection strategies (MS and GS) showed the highest mean response (R = 0.61) within the same environment. When combined with GS, a 23% improvement in R for yield was observed, indicating that gains could be improved by complementing traditional PS with GS within the same environment. Validating selection strategies in different environments resulted in low to negative R values indicating the effects of genotype-by-environment interactions for grain yield. MS was not successful in terms of R relative to the other selection approaches; using this strategy resulted in a significant (P < 0.05) decrease in response to selection compared with the other approaches. An integrated PS+GS approach could result in optimal genetic gain within the same environment, whereas a PS strategy might be a viable option for grain yield validated in different environments. Altogether, we demonstrated that gains through increased response to selection for yield could be achieved in the WSU winter wheat breeding program by implementing different selection strategies either exclusively or in combination.

Unnatural amino acid substitution as a probe of the allosteric coupling pathway in a mycobacterial Cu(I) sensor.

The Cu(I) sensor Mycobacterium tuberculosis CsoR is a founding member of a new metalloregulatory protein family. Here we show that two "atom" substitutions of the Nepsilon2 face of a Cu(I) coordinating histidine-61 allosterically uncouple Cu(I) and DNA binding, with no effect on Cu(I) binding affinity and coordination structure. A model analogous to the allosteric switch mechanism in Staphylococcus aureus CzrA, a zinc sensor protein with a completely different fold, is proposed.

Genetic Dissection of Snow Mold Tolerance in US Pacific Northwest Winter Wheat Through Genome-Wide Association Study and Genomic Selection.

Snow mold is a yield-limiting disease of wheat in the Pacific Northwest (PNW) region of the US, where there is prolonged snow cover. The objectives of this study were to identify genomic regions associated with snow mold tolerance in a diverse panel of PNW winter wheat lines in a genome-wide association study (GWAS) and to evaluate the usefulness of genomic selection (GS) for snow mold tolerance. An association mapping panel (AMP; N = 458 lines) was planted in Mansfield and Waterville, WA in 2017 and 2018 and genotyped using the Illumina® 90K single nucleotide polymorphism (SNP) array. GWAS identified 100 significant markers across 17 chromosomes, where SNPs on chromosomes 5A and 5B coincided with major freezing tolerance and vernalization loci. Increased number of favorable alleles was related to improved snow mold tolerance. Independent predictions using the AMP as a training population (TP) to predict snow mold tolerance of breeding lines evaluated between 2015 and 2018 resulted in a mean accuracy of 0.36 across models and marker sets. Modeling nonadditive effects improved accuracy even in the absence of a close genetic relatedness between the TP and selection candidates. Selecting lines based on genomic estimated breeding values and tolerance scores resulted in a 24% increase in tolerance. The identified genomic regions associated with snow mold tolerance demonstrated the genetic complexity of this trait and the difficulty in selecting tolerant lines using markers. GS was validated and showed potential for use in PNW winter wheat for selecting on complex traits such tolerance to snow mold.

Genome-wide association studies for yield-related traits in soft red winter wheat grown in Virginia.

Grain yield is a trait of paramount importance in the breeding of all cereals. In wheat (Triticum aestivum L.), yield has steadily increased since the Green Revolution, though the current rate of increase is not forecasted to keep pace with demand due to growing world population and increasing affluence. While several genome-wide association studies (GWAS) on yield and related component traits have been performed in wheat, the previous lack of a reference genome has made comparisons between studies difficult. In this study, a GWAS for yield and yield-related traits was carried out on a population of 322 soft red winter wheat lines across a total of four rain-fed environments in the state of Virginia using single-nucleotide polymorphism (SNP) marker data generated by a genotyping-by-sequencing (GBS) protocol. Two separate mixed linear models were used to identify significant marker-trait associations (MTAs). The first was a single-locus model utilizing a leave-one-chromosome-out approach to estimating kinship. The second was a sub-setting kinship estimation multi-locus method (FarmCPU). The single-locus model identified nine significant MTAs for various yield-related traits, while the FarmCPU model identified 74 significant MTAs. The availability of the wheat reference genome allowed for the description of MTAs in terms of both genetic and physical positions, and enabled more extensive post-GWAS characterization of significant MTAs. The results indicate a number of promising candidate genes contributing to grain yield, including an ortholog of the rice aberrant panicle organization (APO1) protein and a gibberellin oxidase protein (GA2ox-A1) affecting the trait grains per square meter, an ortholog of the Arabidopsis thaliana mother of flowering time and terminal flowering 1 (MFT) gene affecting the trait seeds per square meter, and a B2 heat stress response protein affecting the trait seeds per head.

Peptide lipidation stabilizes structure to enhance biological function.

Medicines that decrease body weight and restore nutrient tolerance could improve human diabetes and obesity treatment outcomes. We developed lipid-acylated glucagon analogs that are co-agonists for the glucagon and glucagon-like peptide 1 receptors, and stimulate weight loss and plasma glucose lowering in pre-diabetic obese mice. Our studies identified lipid acylation (lipidation) can increase and balance in vitro potencies of select glucagon analogs for the two aforementioned receptors in a lipidation site-dependent manner. A general capacity for lipidation to enhance the secondary structure of glucagon analogs was recognized, and the energetics of this effect quantified. The molecular structure of a lipid-acylated glucagon analog in water was also characterized. These results support that lipidation can modify biological activity through thermodynamically-favorable intramolecular interactions which stabilize structure. This establishes use of lipidation to achieve specific pharmacology and implicates similar endogenous post-translational modifications as physiological tools capable of refining biological action in means previously underappreciated.

Allosteric inhibition of a zinc-sensing transcriptional repressor: insights into the arsenic repressor (ArsR) family.

The molecular basis of allosteric regulation remains a subject of intense interest. Staphylococcus aureus CzrA is a member of the ubiquitous arsenic repressor (ArsR) family of bacterial homodimeric metal-sensing proteins and has emerged as a model system for understanding allosteric regulation of operator DNA binding by transition metal ions. Using unnatural amino acid substitution and a standard linkage analysis, we show that a His97' NH(ε2)...O=C His67 quaternary structural hydrogen bond is an energetically significant contributor to the magnitude of the allosteric coupling free energy, ∆Gc. A "cavity" introduced just beneath this hydrogen bond in V66A/L68V CzrA results in a significant reduction in regulation by Zn(II) despite adopting a wild-type global structure and Zn(II) binding and DNA binding affinities only minimally affected from wild type. The energetics of Zn(II) binding and heterotropic coupling free energies (∆Hc, -T∆Sc) of the double mutant are also radically altered and suggest that increased internal dynamics leads to poorer allosteric negative regulation in V66A/L68V CzrA. A statistical coupling analysis of 3000 ArsR proteins reveals a sector that links the DNA-binding determinants and the α5 Zn(II)-sensing sites through V66/L68 in CzrA. We propose that distinct regulatory sites uniquely characteristic of individual ArsR proteins result from evolution of distinct connectivities to this sector, each capable of driving the same biological outcome, transcriptional derepression.

KRAS detection in colonic tumors by DNA extraction from FTA paper: the molecular touch-prep.

DNA isolated from formalin-fixed paraffin-embedded (FFPE) tissue is usually more degraded and contains more polymerase chain reaction (PCR) inhibitors than DNA isolated from nonfixed tissue. In addition, the tumor size and cellular heterogeneity found in tissue sections can often impact testing for molecular biomarkers. As a potential remedy to this situation, we evaluated the use of Whatman FTA paper cards for collection of colorectal tumor samples before tissue fixation and for isolation of DNA for use in a real-time PCR-based KRAS mutation assay. Eleven colon tumor samples were collected by making a cut into the fresh tumor and applying the Whatman FTA paper to the cut surface. Matched FFPE tissue blocks from these tumors were also collected for comparison. KRAS mutation analysis was carried out using the Applied Biosystems 7500 Fast Real-time PCR System using 7 independent custom TaqMan PCR assays. Of the 11 colon tumors sampled, 6 were positive for KRAS mutations in both the Whatman FTA paper preparations and corresponding FFPE samples. Whatman FTA paper cards for collection of colorectal tumor samples before tissue fixation and for isolation of DNA have many advantages including ease of use, intrinsic antimicrobial properties, long storage potential (stability of DNA over time), and a faster turnaround time for results. Extracted DNA should be suitable for most molecular diagnostic assays that use PCR techniques. This novel means of DNA preservation from surgical specimens would benefit from additional study and validation as a dependable and practical technique to preserve specimens for molecular testing.