Euphytica最新文献

Soybean [Glycine max (L.) Merr.] is an important seed crop with agricultural sustainability that can be used to meet the growing demand for plant-based oil and protein worldwide. Expanding the cultivation of soybean to high-latitude regions could be an effective strategy for enhancing soybean production. Low temperatures in these regions can inhibit seed germination during the planting season. Despite their importance, many cold tolerance-related genes in soybean remain unidentified. Here, we carried out a genome-wide association study (GWAS) in a diverse soybean population with large variations in cold tolerance-related germination traits. The analyses led to the identification of a total of 46 single-nucleotide polymorphisms (SNPs) that were significantly associated with cold tolerance-related traits. We identified a new locus on chromosome 18, qCold-18–3, that was associated with both the low-temperature germination rate and potential. Furthermore, Abscisic Acid-Deficient4 (GmABA4) was prioritized as the most promising candidate gene. In addition, GmABA4 was strongly induced in a cold-tolerant accession by cold stress during germination, and it contains cis-acting elements associated with low temperature in its promoter region. Haplotype analysis revealed that the accessions harboring Hap3 of GmABA4 were more tolerant to low temperature than those harboring the other haplotypes. In this study, a new cold tolerance-related candidate gene, GmABA4, was identified through GWAS, and further study could advance our understanding of the underlying genetic mechanisms and facilitate the breeding of soybean with improved cold tolerance.

Fruit neck length (FNL) is one of the important commercial characteristics of bottle gourd (Lagenaria siceraria), which is usually desirable by consumers based on their preferences. At present, there has not been extensive research on the genetics of bottle gourd FNL. In this study, an F₂ segregating population was constructed using the long fruit neck material H16 and the short fruit neck material H06. Bulked segregant analysis and kompetitive allele-specific PCR techniques were used to identify candidate regions regulating FNL in bottle gourd. InDel markers were used to narrow the final candidate region interval to 0.16 Mb, which contained 8 genes. A combined analysis using a gene annotation library, real-time fluorescence quantitative expression, and sequence analysis of candidate genes in the region indicated that the HG_GLEAN_10011965 gene might be involved in the regulation of bottle gourd FNL and was named LsFNL1.1. Based on the most narrowed candidate gene interval, an InDel marker was developed for molecular marker assisted breeding of bottle gourd FNL. The phenotypic-genotype association rate of this InDel marker was 83%. This study provides a theoretical basis for further exploring the molecular mechanisms underlying bottle gourd fruit traits and can accelerate the breeding of varieties with desirable characteristics.

Identification of maize germplasm with dual resistance to Striga hermonthica (Sh) and S. asiatica (Sa), could lead to the development of cultivars with stable resistance. 130 tropical and sub-tropical maize germplasms, including checks, were evaluated in a controlled environment for their reaction to Sh and Sa infestations using a 13 × 10 alpha lattice design with two replications over two seasons. Significant differences (P < 0.05) were detected among the assessed genotypes for all the recorded traits in Sh and Sa-infested treatments. Under Sa-infested conditions, mean Striga emergence counts 8 weeks after planting (SEC8) and 10 weeks after planting (SEC10) were 5.00 and 45.50, respectively, while the mean Striga damage rate 8 weeks after planting (SDR8) and 10 weeks after planting (SDR10) were 3.35 and 3.07, respectively. Under Sh-infested conditions, SEC8 and SEC10 mean values were 3.66 and 3.77, respectively, while the SDR8 and SDR10 values were 5.25 and 2.75 respectively. Positive and significant (P < 0.05) correlations were found between anthesis-silking interval (ASI) and SDR8 (r = 0.18) and SDR10 (0.32) under Sa-infested conditions. Negative and significant correlations were recorded between ear per plant (EPP) and SEC8, SDR8, and SDR10, with r = − 0.18, r = − 0.27, and r = − 0.24, respectively. Under Sh-infested conditions, significant and negative correlations were recorded between SDR8 and EPP (r = − 0. 20), EHT and SEC8 (r = − 0.22), EHT and SDR8 (r = − 0.36), PLHT and SDR8 (− 0.48), and PLHT and SDR10 (− 0.22). The results suggest that dual resistance to the two Striga species exists in some tropical and sub-tropical maize lines. The following genotypes have dual resistance to Sa and Sh: CML440, CML566, CML540, CML539, CLHP0343, CLHP0326, TZISTR1248, TZSTRI115, TZISTR25, TZISTR1205, TZSTRI113, TZISTR1119, TZISTR1174 and the OPVs B.King/1421, Shesha/1421, ZM1421, DTSTR-W SYN13, DTSTR-Y SYN14, and 2*TZECOMP3DT/WhiteDTSTRSYN) C2. The identified genotypes are suitable for use as parents in developing high-performing maize varieties with Striga resistance and improved grain yield.

Jatropha curcas (known as jatropha and physic nut) can be used as an alternative source for biodiesel and biomass production. However, conventional breeding of J. curcas needs time, labor and land for characterization and evaluation of the progenies owing to its perennial growth habit. Quantitative trait loci (QTL) mapping can help identifying marker-trait association and accelerate breeding process of perennial crops through marker-assisted selection. However, the genetic basis for woody biomass improvement in jatropha has not yet been studied. In this manuscript, we report the construction of a SNP-based linkage map and detection of QTLs for woody-biomass-related traits using an F₂ population of the interspecific cross between J. curcas and Jatropha integerrima. A high-density genetic linkage map containing 2,179 SNPs was constructed. As high as 89.26% of the SNP markers developed from these interspecific progenies expressed significant segregation distortion. Most of the distorted markers showed neither gametophytic nor zygotic selection, except those on linkage groups 3, 5 and 6 which showed gametophytic and zygotic selection. The F₂ population showed high variation and transgressive segregation for plant height, canopy width and wood density. QTL analyses detected 5, 8, and 7 loci for plant height, canopy width, and wood density, respectively. The SNPs linked to these QTLs could be incorporated into marker-assisted breeding to maximize the selection gain in jatropha biomass breeding.

Abstract

In clonal progenies tests, using experiments with one single tree plot, the number of repetitions (cloned plants of each individual of the progenies under evaluation) must be smaller than the traditionally employed. This is because obtaining clones of each individual from the progenies must be carried out in the shortest possible time and, thus, contribute to the greatest advantage of clonal progenies test, which is to identify new clones earlier than other selection alternatives. With the objective of obtaining the minimum number of repetitions necessary in one single tree plot for use in clonal progenies tests, without significantly affecting the selection accuracy, this work was carried out. To estimate the minimum number of repetitions (number of plants of each clone), data obtained from the evaluation of 60 eucalyptus clones, with 30 repetitions in one single tree plot, conducted in six sites, were used. In these experiments, the mean annual increment (cubic meter per hectare per year) was evaluated. Through 1000 resamplings, without replacement, experimental data were obtained with the number of repetitions ranging from 2 to 29. The estimates of the general mean, genetic variance between clones and the selection accuracy obtained showed that, the estimates of general mean, genetic variance between clones and selection accuracy in means were very similar. It was inferred that for clonal progenies tests, in which the experiments will certainly be carried out in more sites, it is feasible to use five repetitions per experiment.

A stable back cross introgression line IL65 (IET22161) (Swarna/O. nivara-BC₂F₆) of rice was used to map flag leaf related traits in F₂ and F₃ populations. A total of 12 QTLs were mapped on two chromosomes with each QTL explaining 3 to 21% phenotypic variance (PV). Interestingly, a novel 12 Mb QTL cluster (RM8094—RM9) that controls 7 traits was identified on long arm of chromosome 1 where QTLs qSPAD1.2, qSPAD1.3 for SPAD, qFLL1.1, qFLL1.2 for flag leaf length, qFLW1.1, qFLW1.2 for flag leaf width, qFLA1.1, qFLA1.2 for flag leaf area, qPH1.1, qPH1.2 for plant height, qDTF1.2, qDTF1.3 for days to flowering and qHI1.2, qHI1.3 for harvest index were co-located. Among these, one major effect QTL qFLA1.1 for flag leaf area explaining 12.7% PV was identified in a 9 Mb region between RM8094 and RM5638. There was an adjacent minor effect QTL qFLA1.2 with 7% PV in a 3 Mb region between RM5638 and RM9. Together, these two QTLs from O. nivara explained 19.7% PV of leaf area. The QTL for flag leaf related traits can be fine mapped and considered for breeding rice varieties with higher flag leaf area, photosynthetic rate and grain yield.

By accounting for many traits, phenotyping sweet corn is a costly practice, making complementary strategies necessary. Thus, predictive methods present as an excellent alternative for the prediction and selection of the traits. The accuracy of the prediction is highly influenced by characteristics such as phenotypic data quality and marker density, which impact on project costs. Several studies have been carried out to verify minimum densities without the significant loss in prediction accuracies, but none with sweet corn. In this study, the objectives were to test, assess and validate different strategies to pre-select markers for genomic selection and to find the minimum density in a prediction of yield traits in sweet corn. Initially, the prediction was performed with a high-density chip and then, using a pre-selection strategy of clustering markers into haplotype blocks. Furthermore, a third strategy was tested, where markers were selected evenly across the genome. In general, all traits showed a significant reduction in accuracy as the number of markers decreased. However, the relationship between marker’s increment and accuracy did not remain constant and reached a plateau after a certain point. Applying marker pre-selection can be a good option for a cost-efficient implementation of genomic selection in sweet corn for yield traits, as they can be predicted with a significant accuracy using a panel of ~ 8k quality markers that are evenly across the genome. Furthermore, using one marker per haplotype block appears to be a better cost-effective strategy for carrying out genomic selection in sweet corn, for yield traits.

This study was conducted to investigate the variability of Ethiopian black cumin genotypes by using morpho-agronomic traits. Sixty-four genotypes were tested at Debre Zeit and Kulumsa Agricultural Research center in 2021 using an 8 × 8 simple lattice design with two replications. Analysis of variance revealed significant (p ≤ 0.001 or p ≤ 0.01) differences among the genotypes for all traits studied, except the number of primary branches per plant. The effect of location was significant (p ≤ 0.001 or p ≤ 0.05) for all traits except the number of primary branches per plant. It is expected to improve all phenological traits as well as seed yield and yield-related qualitative traits by 4–41% over improved varieties by the selection of the top 5% landraces. Thus, through selection, it would also be possible to shorten the flowering and maturity periods of the genotypes. High broad sense heritability values coupled with high to moderate genetic advance as a percentage of mean values were shown by the number of capsules per plant and plant height which indicates possibilities for improvement of these traits through selection. Plant height, number of primary branches per plant, number of seeds per capsule and thousand seeds weight had a positive and significant phenotypic and genotypic association with seed yield per hectare. Plant height and seed yield per plant had a positive direct effect on seed yield per hectare phenotypically and genotypically. This would be a direct selection criterion for further improvement of the genotypes. The principal component analysis of 12 quantitative traits exhibited 81.5% of the total variance captured by the first four principal components (PCs). Days to 50% flowering, days to full blooming, days to maturity, number of seeds per plant, and seed yield per plant were the main contributor traits for the variation in the first and second PCs. The genotypes were grouped into three different clusters (C-I = 35.93%, C-II = 9.38%, and C-III = 54.69%) based on 12 quantitative traits with significant inter-cluster distances. This clearly showed that there was sufficient diversity among the genotypes which can be exploited for the future black cumin improvement program.

The flag leaf size of wheat is an “ideotypic” morphological trait that plays a critical role in plant architecture and grain yield by providing photosynthetic assimilates in wheat. Although many of the genomics research studies covered the flag leaf traits, including flag leaf length (FLL), width (FLW), area (FLA), thickness (FLT), and volume (FLV), for a better understanding, this research used a recombinant inbred line (RIL) population derived from a cross between DH118 and Jinmai 919 to evaluate the genetic regions across six environments, including BLUP under both drought stress (DS) and well-watered (WW) conditions and analyze their correlation with traits related to grain yield. A total of 40 (QTL) quantitative trait loci controlling the five traits were detected across all environments, with phenotypic variance explaining (PVE) 5.09%-15.26%. Among them, 12 QTL were identified as stable, including two QTL for FLL, two for FLW, three for FLA, two for FLT and three for FLV, in which nine QTL were found to be validated in more than three environments through a double haploid (DH) population Jinchun 7 × Jinmai 919. The Qflw.saw-2A, Qfla.saw-2A, Qflv.saw-2A, Qflt.saw-2B, and Qflt.saw-3B were stated as novel due to not being reported by any of the previous research studies related to flag leaf traits. In addition, traits related to flag-leaf and grain yield were significantly correlated in both water regimes. These results provide a better understanding of the genetic basis underlying flag leaf traits. Also, target regions for fine mapping and marker-assisted selection (MAS) were identified and will be valuable for breeding high-yielding bread wheat.

Abstract

Phenotypic uniformity and tuber yield are fundamental concerns in diploid inbred-based F₁ hybrid breeding in potatoes. We evaluated the agronomic traits of 22 hybrid families grown in small and large pots and the field. These families were derived from crosses of heterozygous × heterozygous, homozygous × heterozygous, and homozygous × homozygous parents using highly homozygous plants of Solanum phureja, S. chacoense, and tenth selfed generation plants derived from an interspecific hybrid. Genetic variability was estimated using genome-wide single nucleotide polymorphism (SNP) markers. Hybrid populations from homozygous × homozygous parents exhibited the highest phenotypic and genetic uniformity levels. Hybrid vigor in hybrids of homozygous × homozygous parents was tremendously enormous for fecundity and growth (up to 2877.5% and 8153.6%, respectively) and moderately large for tuber yield (158.2 to 230.7%). SNP-based genome-wide percent heterozygosity ranged from 28.7 to 44.3% for heterozygous parents and 14.4 to 44.8% for hybrid populations. The heterozygosity was correlated most highly with tuber size (r = 0.691–0.684) and negatively with tuber number (r = − 0.518), resulting in a positive correlation with tuber yield (r = 0.498). Since the heterozygosity of 2x Atlantic was the second highest (44.3%), its hybrid population produced a high yield in the field (925.6 g/plant) close to the yield of tetraploid potatoes. Thus, yield potential can be predicted by the genome-wide percent heterozygosity, possibly because many genetic factors collectively contributing to yield are located across the potato genome, and their accumulated heterotic effects can be represented as the genome-wide percent heterozygosity.