With the rapid generation and preservation of both genomic and phenotypic information for many genotypes within crops and across locations, emerging breeding programs have a valuable opportunity to ...leverage these resources to 1) establish the most appropriate genetic foundation at program inception and 2) implement robust genomic prediction platforms that can effectively select future breeding lines. Integrating genomics-enabled
1
breeding into cultivar development can save costs and allow resources to be reallocated towards advanced (i.e., later) stages of field evaluation, which can facilitate an increased number of testing locations and replicates within locations. In this context, a reestablished winter wheat breeding program was used as a case study to understand best practices to leverage and tailor existing genomic and phenotypic resources to determine optimal genetics for a specific target population of environments. First, historical multi-environment phenotype data, representing 1,285 advanced breeding lines, were compiled from multi-institutional testing as part of the SunGrains cooperative and used to produce GGE biplots and PCA for yield. Locations were clustered based on highly correlated line performance among the target population of environments into 22 subsets. For each of the subsets generated, EMMs and BLUPs were calculated using linear models with the
‘lme4’
R package. Second, for each subset, TPs representative of the new SC breeding lines were determined based on genetic relatedness using the
‘STPGA’
R package. Third, for each TP, phenotypic values and SNP data were incorporated into the
‘rrBLUP’
mixed models for generation of GEBVs of YLD, TW, HD and PH. Using a five-fold cross-validation strategy, an average accuracy of
r
= 0.42 was obtained for yield between all TPs. The validation performed with 58 SC elite breeding lines resulted in an accuracy of
r
= 0.62 when the TP included complete historical data. Lastly, QTL-by-environment interaction for 18 major effect genes across three geographic regions was examined. Lines harboring major QTL in the absence of disease could potentially underperform (e.g., Fhb1 R-gene), whereas it is advantageous to express a major QTL under biotic pressure (e.g., stripe rust R-gene). This study highlights the importance of genomics-enabled breeding and multi-institutional partnerships to accelerate cultivar development.
Key message
Marker-assisted selection is important for cultivar development. We propose a system where a training population genotyped for QTL and genome-wide markers may predict QTL haplotypes in ...early development germplasm.
Breeders screen germplasm with molecular markers to identify and select individuals that have desirable haplotypes. The objective of this research was to investigate whether QTL haplotypes can be accurately predicted using SNPs derived by genotyping-by-sequencing (GBS). In the SunGrains program during 2020 (SG20) and 2021 (SG21), 1,536 and 2,352 lines submitted for GBS were genotyped with markers linked to the
Fusarium
head blight QTL:
Qfhb.nc-1A, Qfhb.vt-1B
,
Fhb1
, and
Qfhb.nc-4A
. In parallel, data were compiled from the 2011–2020 Southern Uniform Winter Wheat Scab Nursery (SUWWSN), which had been screened for the same QTL, sequenced via GBS, and phenotyped for: visual
Fusarium
severity rating (SEV), percent
Fusarium
damaged kernels (FDK), deoxynivalenol content (DON), plant height, and heading date. Three machine learning models were evaluated: random forest, k-nearest neighbors, and gradient boosting machine. Data were randomly partitioned into training–testing splits. The QTL haplotype and 100 most correlated GBS SNPs were used for training and tuning of each model. Trained machine learning models were used to predict QTL haplotypes in the testing partition of SG20, SG21, and the total SUWWSN. Mean disease ratings for the observed and predicted QTL haplotypes were compared in the SUWWSN. For all models trained using the SG20 and SG21, the observed
Fhb1
haplotype estimated group means for SEV, FDK, DON, plant height, and heading date in the SUWWSN were not significantly different from any of the predicted
Fhb1
calls. This indicated that machine learning may be utilized in breeding programs to accurately predict QTL haplotypes in earlier generations.
Key message
The optimization of training populations and the use of diagnostic markers as fixed effects increase the predictive ability of genomic prediction models in a cooperative wheat breeding ...panel.
Plant breeding programs often have access to a large amount of historical data that is highly unbalanced, particularly across years. This study examined approaches to utilize these data sets as training populations to integrate genomic selection into existing pipelines. We used cross-validation to evaluate predictive ability in an unbalanced data set of 467 winter wheat (
Triticum aestivum
L.) genotypes evaluated in the Gulf Atlantic Wheat Nursery from 2008 to 2016. We evaluated the impact of different training population sizes and training population selection methods (Random, Clustering, PEVmean and PEVmean1) on predictive ability. We also evaluated inclusion of markers associated with major genes as fixed effects in prediction models for heading date, plant height, and resistance to powdery mildew (caused by
Blumeria graminis
f. sp.
tritici)
. Increases in predictive ability as the size of the training population increased were more evident for Random and Clustering training population selection methods than for PEVmean and PEVmean1. The selection methods based on minimization of the prediction error variance (PEV) outperformed the Random and Clustering methods across all the population sizes. Major genes added as fixed effects always improved model predictive ability, with the greatest gains coming from combinations of multiple genes. Maximum predictabilities among all prediction methods were 0.64 for grain yield, 0.56 for test weight, 0.71 for heading date, 0.73 for plant height, and 0.60 for powdery mildew resistance. Our results demonstrate the utility of combining unbalanced phenotypic records with genome-wide SNP marker data for predicting the performance of untested genotypes.
This study sought to evaluate the effects of empagliflozin on extracellular volume (ECV) in individuals with type 2 diabetes mellitus (T2DM) and coronary artery disease (CAD).
Empagliflozin has been ...shown to reduce left ventricular mass index (LVMi) in patients with T2DM and CAD. The effects on myocardial ECV are unknown.
This was a prespecified substudy of the EMPA-HEART (Effects of Empagliflozin on Cardiac Structure in Patients with Type 2 Diabetes) CardioLink-6 trial in which 97 participants were randomized to receive empagliflozin 10 mg daily or placebo for 6 months. Data from 74 participants were included: 39 from the empagliflozin group and 35 from the placebo group. The main outcome was change in left ventricular ECV from baseline to 6 months determined by cardiac magnetic resonance (CMR). Other outcomes included change in LVMi, indexed intracellular compartment volume (iICV) and indexed extracellular compartment volume (iECV), and the fibrosis biomarkers soluble suppressor of tumorgenicity (sST2) and matrix metalloproteinase (MMP)-2.
Baseline ECV was elevated in the empagliflozin group (29.6 ± 4.6%) and placebo group (30.6 ± 4.8%). Six months of empagliflozin therapy reduced ECV compared with placebo (adjusted difference: –1.40%; 95% confidence interval CI: –2.60 to –0.14%; p = 0.03). Empagliflozin therapy reduced iECV (adjusted difference: –1.5 ml/m2; 95% CI: –2.6 to –0.5 ml/m2; p = 0.006), with a trend toward reduction in iICV (adjusted difference: –1.7 ml/m2; 95% CI: –3.8 to 0.3 ml/m2; p = 0.09). Empagliflozin had no impact on MMP-2 or sST2.
In individuals with T2DM and CAD, 6 months of empagliflozin reduced ECV, iECV, and LVMi. No changes in MMP-2 and sST2 were seen. Further investigation into the mechanisms by which empagliflozin causes reverse remodeling is required. (Effects of Empagliflozin on Cardiac Structure in Patients With Type 2 Diabetes EMPA-HEART; NCT02998970)
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Chronic massive rotator cuff tears heal poorly and often retear. This study investigated the effect of adipose-derived stem cells (ADSCs) and transforming growth factor-β3 (TGF-β3) delivered in 1 of ...2 hydrogels (fibrin or gelatin methacrylate GelMA) on enthesis healing after repair of acute or chronic massive rotator cuff tears in rats.
Adult male Lewis rats underwent bilateral transection of the supraspinatus and infraspinatus tendons with intramuscular injection of botulinum toxin A (n = 48 rats). After 8 weeks, animals received 1 of 8 interventions (n = 12 shoulders/group): (1) no repair, (2) repair only, or repair augmented with (3) fibrin, (4) GelMA, (5) fibrin + ADSCs, (6) GelMA + ADSCs, (7) fibrin + ADSCs + TGF-β3, or (8) GelMA + ADSCs + TGF-β3. An equal number of animals underwent acute tendon transection and immediate application of 1 of 8 interventions. Enthesis healing was evaluated 4 weeks after the repair by microcomputed tomography, histology, and mechanical testing.
Increased bone loss and reduced structural properties were seen in chronic compared with acute tears. Bone mineral density of the proximal humerus was higher in repairs of chronic tears augmented with fibrin + ADSCs and GelMA + ADSCs than in unrepaired chronic tears. Similar improvement was not seen in acute tears. No intervention enhanced histologic appearance or structural properties in acute or chronic tears.
Surgical repair augmented with ADSCs may provide more benefit in chronic tears compared with acute tears, although there was no added benefit to supplementing ADSCs with TGF-β3.
The Radiotracer 11COMAR was developed for positron emission tomography (PET) imaging of cannabinoid type-1 receptors (CB1R). The objectives of the present study were to evaluate kinetic analysis ...methods, determine test–retest reliability, and assess gender differences in receptor availability. Dynamic PET data were acquired in 10 human subjects, and analyzed with one-tissue (1T) and two-tissue (2T) compartment models and by the Logan and multilinear analysis (MA1) methods to estimate regional volume of distribution (VT). The 2T model inclusive of a vascular component (2TV) and MA1 were the preferred techniques. Test–retest reliability of VT was good (mean absolute deviation ~ 9%; intraclass correlation coefficient ~ 0.7). Tracer parent fraction in plasma was lower in women (P < 0.0001). Cerebral uptake normalized by body weight and injected dose was higher in men by 17% (P < 0.0001), but VT was significantly greater in women by 23% (P < 0.0001). These findings show that 11COMAR binding can be reliably quantified by the 2T model or MA1 method and demonstrate the utility of this tracer for in vivo imaging of CB1R. In addition, results from the present study indicate that gender difference in receptor binding should be taken into consideration when 11COMAR is used to quantify CB1R availability in neuropsychiatric disorders.
In this work we present evidence that the heat stress induced kernel abortion and suppression of grain maturation in a representative heat susceptible hard red winter wheat (
Triticum aestivum L.) ...cultivar is regulated by heat stress induced ethylene production. Exposure to heat stress (38
°C) during early kernel development (10 DAP) resulted in a 6-fold increase in ethylene production in developing kernels of the heat susceptible hard red winter wheat cultivar ‘Karl 92’. A similar 7-fold increase in ethylene production in embryos and 12-fold increase in ethylene production in the flag leaf of heat stressed plants of ‘Karl 92’ was also found. In contrast, no change in ethylene production was observed in the heat tolerant hard white spring wheat cultivar ‘Halberd’. In an effort to link the heat stress induced ethylene production to the observed increase in kernel abortion and reduced kernel weight in the heat susceptible ‘Karl 92’, plants were treated with the ethylene receptor inhibitor 1-methylcyclopropane (1-MCP) prior to exposure to heat stress. Inhibiting ethylene perception in the heat susceptible ‘Karl 92’ in this manner blocked heat stress induced kernel abortion and reduction in kernel weight and demonstrated a clear link between ethylene in regulating susceptibility to heat stress or perception of high temperatures as a timing signal for transitioning to developmental arrest and senescence in certain wheat genotype classes.
Rodent experiments have emphasized a role of central fatty acid (FA) species, such as oleic acid, in regulating peripheral glucose and energy metabolism. Thus, we hypothesized that central FAs are ...related to peripheral glucose regulation and energy expenditure in humans. To test this we measured FA species profiles in cerebrospinal fluid (CSF) and plasma of 32 individuals who stayed in our clinical inpatient unit for 6 days. Body composition was measured by dual energy X-ray absorptiometry and glucose regulation by an oral glucose test (OGTT) followed by measurements of 24 hour (24EE) and sleep energy expenditure (SLEEP) as well as respiratory quotient (RQ) in a respiratory chamber. CSF was obtained via lumbar punctures; FA concentrations were measured by liquid chromatography/mass spectrometry. As expected, FA concentrations were higher in plasma compared to CSF. Individuals with high concentrations of CSF very-long-chain saturated FAs had lower rates of SLEEP. In the plasma moderate associations of these FAs with higher 24EE were observed. Moreover, CSF monounsaturated long-chain FA (palmitoleic and oleic acid) concentrations were associated with lower RQs and lower glucose area under the curve during the OGTT. Thus, FAs in the CSF strongly correlated with peripheral metabolic traits. These physiological parameters were most specific to long-chain monounsaturated (C16:1, C18:1) and very-long-chain saturated (C24:0, C26:0) FAs.
Together with previous animal experiments these initial cross-sectional human data indicate that central FA species are linked to peripheral glucose and energy homeostasis.
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