The ability to predict the agronomic performance of single-crosses with high precision is essential for selecting superior candidates for hybrid breeding. With recent technological advances, ...thousands of new parent lines, and, consequently, millions of new hybrid combinations are possible in each breeding cycle, yet only a few hundred can be produced and phenotyped in multi-environment yield trials. Well established prediction approaches such as best linear unbiased prediction (BLUP) using pedigree data and whole-genome prediction using genomic data are limited in capturing epistasis and interactions occurring within and among downstream biological strata such as transcriptome and metabolome. Because mRNA and small RNA (sRNA) sequences are involved in transcriptional, translational and post-translational processes, we expect them to provide information influencing several biological strata. However, using sRNA data of parent lines to predict hybrid performance has not yet been addressed. Here, we gathered genomic, transcriptomic (mRNA and sRNA) and metabolomic data of parent lines to evaluate the ability of the data to predict the performance of untested hybrids for important agronomic traits in grain maize. We found a considerable interaction for predictive ability between predictor and trait, with mRNA data being a superior predictor for grain yield and genomic data for grain dry matter content, while sRNA performed relatively poorly for both traits. Combining mRNA and genomic data as predictors resulted in high predictive abilities across both traits and combining other predictors improved prediction over that of the individual predictors alone. We conclude that downstream "omics" can complement genomics for hybrid prediction, and, thereby, contribute to more efficient selection of hybrid candidates.
Information about the genetic diversity and population structure in elite breeding material is of fundamental importance for the improvement of crops. The objectives of our study were to (a) examine ...the population structure and the genetic diversity in elite maize germplasm based on simple sequence repeat (SSR) markers, (b) compare these results with those obtained from single nucleotide polymorphism (SNP) markers, and (c) compare the coancestry coefficient calculated from pedigree records with genetic distance estimates calculated from SSR and SNP markers. Our study was based on 1,537 elite maize inbred lines genotyped with 359 SSR and 8,244 SNP markers. The average number of alleles per locus, of group specific alleles, and the gene diversity (D) were higher for SSRs than for SNPs. Modified Roger's distance (MRD) estimates and membership probabilities of the STRUCTURE matrices were higher for SSR than for SNP markers but the germplasm organization in four heterotic pools was consistent with STRUCTURE results based on SSRs and SNPs. MRD estimates calculated for the two marker systems were highly correlated (0.87). Our results suggested that the same conclusions regarding the structure and the diversity of heterotic pools could be drawn from both markers types. Furthermore, although our results suggested that the ratio of the number of SSRs and SNPs required to obtain MRD or D estimates with similar precision is not constant across the various precision levels, we propose that between 7 and 11 times more SNPs than SSRs should be used for analyzing population structure and genetic diversity.
There is increasing empirical evidence that whole-genome prediction (WGP) is a powerful tool for predicting line and hybrid performance in maize. However, there is a lack of knowledge about the ...sensitivity of WGP models towards the genetic architecture of the trait. Whereas previous studies exclusively focused on highly polygenic traits, important agronomic traits such as disease resistances, nutrifunctional or climate adaptational traits have a genetic architecture which is either much less complex or unknown. For such cases, information about model robustness and guidelines for model selection are lacking. Here, we compared five WGP models with different assumptions about the distribution of the underlying genetic effects. As contrasting model traits, we chose three highly polygenic agronomic traits and three metabolites each with a major QTL explaining 22 to 30% of the genetic variance in a panel of 289 diverse maize inbred lines genotyped with 56,110 SNPs.
We found the five WGP models to be remarkable robust towards trait architecture with the largest differences in prediction accuracies ranging between 0.05 and 0.14 for the same trait, most likely as the result of the high level of linkage disequilibrium prevailing in elite maize germplasm. Whereas RR-BLUP performed best for the agronomic traits, it was inferior to LASSO or elastic net for the three metabolites. We found the approach of genome partitioning of genetic variance, first applied in human genetics, as useful in guiding the breeder which model to choose, if prior knowledge of the trait architecture is lacking.
Our results suggest that in diverse germplasm of elite maize inbred lines with a high level of LD, WGP models differ only slightly in their accuracies, irrespective of the number and effects of QTL found in previous linkage or association mapping studies. However, small gains in prediction accuracies can be achieved if the WGP model is selected according to the genetic architecture of the trait. If the trait architecture is unknown e.g. for novel traits which only recently received attention in breeding, we suggest to inspect the distribution of the genetic variance explained by each chromosome for guiding model selection in WGP.
Abstract
Direct removal of
99
TcO
4
−
from the highly acidic solution of used nuclear fuel is highly beneficial for the recovery of uranium and plutonium and more importantly aids in the elimination ...of
99
Tc discharge into the environment. However, this task represents a huge challenge given the combined extreme conditions of super acidity, high ionic strength, and strong radiation field. Here we overcome this challenge using a cationic polymeric network with significant TcO
4
−
uptake capabilities in four aspects: the fastest sorption kinetics, the highest sorption capacity, the most promising uptake performance from highly acidic solutions, and excellent radiation-resistance and hydrolytic stability among all anion sorbent materials reported. In addition, this material is fully recyclable for multiple sorption/desorption trials, making it extremely attractive for waste partitioning and emergency remediation. The excellent TcO
4
−
uptake capability is elucidated by X-ray absorption spectroscopy, solid-state NMR measurement, and density functional theory analysis on anion coordination and bonding.
High external pressure is found to induce a non-coordinated water molecule to bond to cerium in a previously studied mellitate coordination polymer, as determined by high-pressure single-crystal ...X-ray diffraction, resulting in a coordination number transition at 3.85 GPa from 9 to 9.5 where half the cerium ions are 10-coordinate. Also, bond length changes due to increased pressure are experimentally measured, whereas the cerium–carboxylate bond lengths overall change by −0.004(9) Å/GPa, the cerium–water bonds by −0.016(3) Å/GPa, and cerium–oxygen bonds overall by −0.010(6) Å/GPa, which corresponds well with theoretical bond length decreases determined for similar compounds. The high-pressure absorbance spectra of the analogous neodymium mellitate are examined and compared with the structural changes observed.
Selective crystallization offers new opportunities for separating neodymium and dysprosium, which are considerably important in permanent magnets. Two water-soluble nitrogen-rich tetrazolate-based ...ligands, dtp2– (H2dtp = 2,3-di-1H-tetrazol-5-ylpyrazine) and H2ibt– H3ibt = 4,5-bis(tetrazol-5-yl)imidazole, allow the separation of Nd3+ and Dy3+ through selective crystallization. The reactions of Ln3+ with the ligand Na2(dtp)·2H2O lead to two distinct phases, NaLn(dtp)(H2O)8(dtp)·H2O (Lndtp1; Ln = La–Pr) and Ln(H2O)8(Hdtp)(dtp)·H2O (Lndtp2; Ln = Nd and Sm–Lu). Three different compound types, Ln(H2ibt)2(H2O)6(H2ibt)·3(H2O) (Lnibt1; Ln = La or Ce), Ln(H2ibt)(H2O)7(H2ibt)2·4(H2O) (Lnibt2; Ln = Pr or Nd), and Ln(Hibt)(H2ibt)(H2O)4·4+x(H2O) (Lnibt3; Ln = Sm–Lu), are obtained from reacting Ln3+ and Na(H2ibt)·3(H2O). Two different phases are observed for Nd(Lnibt2) and Dy(Lnibt3) in the system of H2ibt–, which leads to crystallization-based separation of Nd/Dy with a separation factor of 32 ± 0.7, 10 times higher than that of dtp2–, and a short separation time of 20 s (1 day for dtp2–). The higher performance of H2ibt– compared to that of dtp2– provides guidance for the rational design of water-soluble tetrazolate-derived ligands for selective crystallization.
Key message
Training sets produced by maximizing the number of parent lines, each involved in one cross, had the highest prediction accuracy for H0 hybrids, but lowest for H1 and H2 hybrids.
Genomic ...prediction holds great promise for hybrid breeding but optimum composition of the training set (TS) as determined by the number of parents (
n
TS
) and crosses per parent (
c
) has received little attention. Our objective was to examine prediction accuracy (
r
a
) of GCA for lines used as parents of the TS (I1 lines) or not (I0 lines), and H0, H1 and H2 hybrids, comprising crosses of type I0 × I0, I1 × I0 and I1 × I1, respectively, as function of
n
TS
and
c
. In the theory, we developed estimates for
r
a
of GBLUPs for hybrids: (i)
r
^
a
based on the expected prediction accuracy, and (ii)
r
~
a
based on
r
a
of GBLUPs of GCA and SCA effects. In the simulation part, hybrid populations were generated using molecular data from two experimental maize data sets. Additive and dominance effects of QTL borrowed from literature were used to simulate six scenarios of traits differing in the proportion (
τ
SCA
= 1%, 6%, 22%) of SCA variance in
σ
G
2
and heritability (
h
2
= 0.4, 0.8). Values of
r
~
a
and
r
^
a
closely agreed with
r
a
for hybrids. For given size
N
TS
=
n
TS
×
c
of TS,
r
a
of H0 hybrids and GCA of I0 lines was highest for
c
= 1. Conversely, for GCA of I1 lines and H1 and H2 hybrids,
c
= 1 yielded lowest
r
a
with concordant results across all scenarios for both data sets. In view of these opposite trends, the optimum choice of
c
for maximizing selection response across all types of hybrids depends on the size and resources of the breeding program.
Abstract
Genetic variation is of crucial importance for crop improvement. Landraces are valuable sources of diversity, but for quantitative traits efficient strategies for their targeted utilization ...are lacking. Here, we map haplotype-trait associations at high resolution in ~1000 doubled-haploid lines derived from three maize landraces to make their native diversity for early development traits accessible for elite germplasm improvement. A comparative genomic analysis of the discovered haplotypes in the landrace-derived lines and a panel of 65 breeding lines, both genotyped with 600k SNPs, points to untapped beneficial variation for target traits in the landraces. The superior phenotypic performance of lines carrying favorable landrace haplotypes as compared to breeding lines with alternative haplotypes confirms these findings. Stability of haplotype effects across populations and environments as well as their limited effects on undesired traits indicate that our strategy has high potential for harnessing beneficial haplotype variation for quantitative traits from genetic resources.
Key message
Mating designs determine the realized additive genetic variance in a population sample. Deflated or inflated variances can lead to reduced or overly optimistic assessment of future ...selection gains.
The additive genetic variance
V
A
inherent to a breeding population is a major determinant of short- and long-term genetic gain. When estimated from experimental data, it is not only the additive variances at individual loci (QTL) but also covariances between QTL pairs that contribute to estimates of
V
A
. Thus, estimates of
V
A
depend on the genetic structure of the data source and vary between population samples. Here, we provide a theoretical framework for calculating the expectation and variance of
V
A
from genotypic data of a given population sample. In addition, we simulated breeding populations derived from different numbers of parents (
P
= 2, 4, 8, 16) and crossed according to three different mating designs (disjoint, factorial and half-diallel crosses). We calculated the variance of
V
A
and of the parameter
b
reflecting the covariance component in
V
A
,
standardized by the genic variance. Our results show that mating designs resulting in large biparental families derived from few disjoint crosses carry a high risk of generating progenies exhibiting strong covariances between QTL pairs on different chromosomes. We discuss the consequences of the resulting deflated or inflated
V
A
estimates for phenotypic and genome-based selection as well as for applying the usefulness criterion in selection. We show that already one round of recombination can effectively break negative and positive covariances between QTL pairs induced by the mating design. We suggest to obtain reliable estimates of
V
A
and its components in a population sample by applying statistical methods differing in their treatment of QTL covariances.
Summary
Intravenous magnesium has been reported to improve postoperative pain; however, the evidence is inconsistent. The objective of this quantitative systematic review is to evaluate whether or ...not the peri‐operative administration of intravenous magnesium can reduce postoperative pain. Twenty‐five trials comparing magnesium with placebo were identified. Independent of the mode of administration (bolus or continuous infusion), peri‐operative magnesium reduced cumulative intravenous morphine consumption by 24.4% (mean difference: 7.6 mg, 95% CI −9.5 to −5.8 mg; p < 0.00001) at 24 h postoperatively. Numeric pain scores at rest and on movement at 24 h postoperatively were reduced by 4.2 (95% CI −6.3 to −2.1; p < 0.0001) and 9.2 (95% CI −16.1 to −2.3; p = 0.009) out of 100, respectively. We conclude that peri‐operative intravenous magnesium reduces opioid consumption, and to a lesser extent, pain scores, in the first 24 h postoperatively, without any reported serious adverse effects.
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