Nazareno, Eric S.Fiedler, JasonMiller, Marisa E.Figueroa, Melania...
15页
查看更多>>摘要：Key message We mapped three adult plant resistance (APR) loci on oat chromosomes 4D and 6C and developed flanking KASP/PACE markers for marker-assisted selection and gene pyramiding. Using sequence orthology search and the available oat genomic and transcriptomic data, we surveyed these genomic regions for genes that may control disease resistance. Sources of durable disease resistance are needed to minimize yield losses in cultivated oat caused by crown rust (Puccinia coronata f. sp. avenae). In this study, we developed five oat recombinant inbred line mapping populations to identify sources of adult plant resistance from crosses between five APR donors and Otana, a susceptible variety. The preliminary bulk segregant mapping based on allele frequencies showed two regions in linkage group Mrg21 (Chr4D) that are associated with the APR phenotype in all five populations. Six markers from these regions in Chr4D were converted to high-throughput allele specific PCR assays and were used to genotype all individuals in each population. Simple interval mapping showed two peaks in Chr4D, named QPc.APR-4D.1 and QPc.APR-4D.2, which were detected in the OtanaA/CI4706-2 and OtanaA/CI9416-2 and in the Otana/PI189733, OtanaD/PI260616, and OtanaA/CI8000-4 populations, respectively. These results were validated by mapping two entire populations, Otana/PI189733 and OtanaA/CI9416, genotyped using Illumina HiSeq, in which polymorphisms were called against the OT3098 oat reference genome. Composite interval mapping results confirmed the presence of the two quantitative trait loci (QTL) located on oat chromosome 4D and an additional QTL with a smaller effect located on chromosome 6C. This mapping approach also narrowed down the physical intervals to between 5 and 19 Mb, and indicated that QPc.APR-4D.1, QPc.APR-4D.2, and QPc.APR-6C explained 43.4%, 38.5%, and 21.5% of the phenotypic variation, respectively. In a survey of the gene content of each QTL, several clusters of disease resistance genes that may contribute to APR were found. The allele specific PCR markers developed for these QTL regions would be beneficial for marker-assisted breeding, gene pyramiding, and future cloning of resistance genes from oat.
查看更多>>摘要：Key message MutMap and KASP analyses revealed that the BrGGL7 gene is responsible for the male-sterile trait of ftms1 in Chinese cabbage, with functional verification in Arabidopsis. The application of a male-sterile line is an ideal approach of hybrid seed production in Chinese cabbage. In this study, we obtained a male-sterile mutant (ftms1) from the double haploid line 'FT' using ethyl methane sulfonate (EMS) mutagenesis. The mutant was completely sterile due to abnormal enlargement and vacuolization of the tapetum cells. A single recessive nuclear gene was found to control male sterility in the mutant, while MutMap and KASP analyses identified BraA05g022470.3C (BrGGL7), which encodes a GDSL esterase / lipase, as the candidate mutant gene. A single nucleotide substitution from C to T occurred within the domain of BrGGL7 in ftms1, resulting in premature translation termination in the fourth exon. Meanwhile, qRT-PCR analysis indicated that BrGGL7 was prominently expressed in the anothers, and expression was greater in the wild-type 'FT' than ftms1. Genetic complementation of the orthologous Arabidopsis ggl7 mutant further confirmed the role of BrGGL7 in pollen development. These findings suggest that BrGGL7 plays a fundamental role in pollen formation, providing important insight into the molecular mechanisms underlying male sterility in Chinese cabbage.
查看更多>>摘要：Key message Phenomic prediction of wheat grain yield and heading date in different multi-environmental trial scenarios is accurate. Modelling the genotype-by-environment interaction effect using phenomic data is a potentially low-cost complement to genomic prediction. The performance of wheat cultivars in multi-environmental trials (MET) is difficult to predict because of the genotype-by-environment interactions (G x E). Phenomic selection is supposed to be efficient for modelling the G x E effect because it accounts for non-additive effects. Here, phenomic data are near-infrared (NIR) spectra obtained from plant material. While phenomic selection has recently been shown to accurately predict wheat grain yield in single environments, its accuracy needs to be investigated for MET. We used four datasets from two winter wheat breeding programs to test and compare the predictive abilities of phenomic and genomic models for grain yield and heading date in different MET scenarios. We also compared different methods to model the G x E using different covariance matrices based on spectra. On average, phenomic and genomic prediction abilities are similar in all different MET scenarios. Better predictive abilities were obtained when G x E effects were modelled with NIR spectra than without them, and it was better to use all the spectra of all genotypes in all environments for modelling the G x E. To facilitate the implementation of phenomic prediction, we tested MET designs where the NIR spectra were measured only on the genotype-environment combinations phenotyped for the target trait. Missing spectra were predicted with a weighted multivariate ridge regression. Intermediate predictive abilities for grain yield were obtained in a sparse testing scenario and for new genotypes, which shows that phenomic selection is an efficient and practicable prediction method for dealing with G x E.
Malangisha, Guy KatetaMa, YuyuanZhang, KejiaZhou, Yimei...
17页
查看更多>>摘要：Key message Gene mining in a C. lanatus x C. amarus population revealed one gene, ACS7, linked to primary root elongation in watermelon. Watermelon is a xerophytic crop characterized by a long primary root and robust lateral roots. Therefore, watermelon serves as an excellent model for studying root elongation and development. However, the genetic mechanism underlying the primary root elongation in watermelon remains unknown. Herein, through bulk segregant analysis we identified a genetic locus, qPRL.Chr03, controlling primary root length (PRL) using two different watermelon species (Citrullus lanatus and Citrullus amarus) that differ in their root architecture. Fine mapping revealed that xaa-Pro dipeptidase and 1-aminocyclopropane-1-carboxylate synthase 7 (ACS7) are candidate regulators of the primary root growth. Allelic variation in the delimited region among 193 watermelon accessions indicated that the long-root alleles might only exist in C. amarus. Interestingly, the discrepancy in PRL among the C. amarus accessions was clearly associated with a nonsynonymous single nucleotide polymorphism variant within the ACS7 gene. The ACS7 expression and ethylene levels in the primary root tips suggested that ethylene is a negative regulator of root elongation in watermelon, as supported by the application of 1-aminocyclopropane-1-carboxylate (ACC, the ethylene precursor) or 2-aminoethoxyvinyl glycine (AVG, an ACS inhibitor). To the best of our knowledge, these findings provide the first description of the genetic basis of root elongation in watermelon. The detected markers of the ACS7 gene will facilitate marker-assisted selection for the PRL trait to improve water and nutrient use efficacy in watermelon and beyond.
查看更多>>摘要：In order to understand the molecular mechanism of cotton's response to drought during the flowering and boll stage, transcriptomics and metabolomics were carried out for two introgression lines (drought-tolerant line: T307; drought-sensitive line: S48) which were screened from Gossypium hirsutum cv. 'Emian22' with some gene fragments imported from Gossypiumbarbadense acc. 3-79, under drought stress by withdrawing water at flowering and boll stage. Results showed that the basic drought response in cotton included a series of broad-spectrum responses, such as amino acid synthesis, hormone (abscisic acid, ABA) signal transduction, and mitogen-activated protein kinases signal transduction pathway, which activated in both drought-tolerant and drought-sensitive lines. However, the difference of their imported fragments and diminished sequences triggers endoplasmic reticulum (ER) protein processing, photosynthetic-related pathways (in leaves), and membrane solute transport (in roots) in drought-tolerant line T307, while these are missed or not activated in drought-sensitive line S48, reflecting the different drought tolerance of the two genotypes. Virus-induced gene silencing assay of drought-tolerant differentially expressed heat shock protein (HSP) genes (mainly in leaf) and ATP-binding cassette (ABC) transporter genes (mainly in roots) indicated that those genes play important role in cotton drought tolerant. Combined analysis of transcriptomics and metabolomics highlighted the important roles of ER-stress-related HSP genes and root-specific ABC transporter genes in plants drought tolerance. These results provide new insights into the molecular mechanisms underlying the drought stress adaptation in cotton.
Tolhurst, Daniel J.Gaynor, R. ChrisGardunia, BrianHickey, John M....
23页
查看更多>>摘要：Key message The integration of known and latent environmental covariates within a single-stage genomic selection approach provides breeders with an informative and practical framework to utilise genotype by environment interaction for prediction into current and future environments. This paper develops a single-stage genomic selection approach which integrates known and latent environmental covariates within a special factor analytic framework. The factor analytic linear mixed model of Smith et al. (2001) is an effective method for analysing multi-environment trial (MET) datasets, but has limited practicality since the underlying factors are latent so the modelled genotype by environment interaction (GEI) is observable, rather than predictable. The advantage of using random regressions on known environmental covariates, such as soil moisture and daily temperature, is that the modelled GEI becomes predictable. The integrated factor analytic linear mixed model (IFA-LMM) developed in this paper includes a model for predictable and observable GEI in terms of a joint set of known and latent environmental covariates. The IFA-LMM is demonstrated on a late-stage cotton breeding MET dataset from Bayer CropScience. The results show that the known covariates predominately capture crossover GEI and explain 34.4% of the overall genetic variance. The most notable covariates are maximum downward solar radiation ( 10.1%), average cloud cover (4.5%) and maximum temperature (4.0%). The latent covariates predominately capture non-crossover GEI and explain 40.5% of the overall genetic variance. The results also show that the average prediction accuracy of the IFA-LMM is 0.02 - 0.10 higher than conventional random regression models for current environments and 0.06 - 0.24 higher for future environments. The IFA-LMM is therefore an effective method for analysing MET datasets which also utilises crossover and non-crossover GEI for genomic prediction into current and future environments. This is becoming increasingly important with the emergence of rapidly changing environments and climate change.
查看更多>>摘要：Key message We report the map-based cloning and functional characterization of SNG1, which encodes OsHXK3, a hexokinase-like protein that plays a pivotal role in controlling grain size in rice. Grain size is an important agronomic trait determining grain yield and appearance quality in rice. Here, we report the discovery of rice mutant short and narrow grain1 (sng1) with reduced grain length, width and weight. Map-based cloning revealed that the mutant phenotype was caused by loss of function of gene OsHXK3 that encodes a hexokinase-like (HKL) protein. OsHXK3 was associated with the mitochondria and was ubiquitously distributed in various organs, predominately in younger organs. Analysis of glucose (Glc) phosphorylation activities in young panicles and protoplasts showed that OsHXK3 was a non-catalytic hexokinase (HXK). Overexpression of OsHXK3 could not complement the Arabidopsis glucose insensitive2-1 (gin2-1) mutant, indicating that OsHXK3 lacked Glc signaling activity. Scanning electron microscopy analysis revealed that OsHXK3 affects grain size by promoting spikelet husk cell expansion. Knockout of other nine OsHXK genes except OsHXK3 individually did not change grain size, indicating that functions of OsHXKs have differentiated in rice. OsHXK3 influences gibberellin (GA) biosynthesis and homeostasis. Compared with wild type, OsGA3ox2 was significantly up-regulated and OsGA2ox1 was significantly down-regulated in young panicle of sng1, and concentrations of biologically active GAs were significantly decreased in young panicles of the mutants. The yield per plant of OsHXK3 overexpression lines (OE-4 and OE-35) was increased by 10.91% and 7.62%, respectively, compared to that of wild type. Our results provide evidence that an HXK lacking catalytic and sensory functions plays an important role in grain size and has the potential to increase yield in rice.
查看更多>>摘要：Key message Contamination at the FAD2B locus due to inadequate screening protocols is the primary cause of sporadic, insufficient oleic acid content in Virginia-type peanut. The high oleic trait in peanut is conditioned by loss-of-function mutations in a pair of homeologous enzymes and is well known to improve the shelf life of peanut products. As such, the trait is given high priority in current and future cultivars by the North Carolina State University peanut breeding program. For unknown reasons, high oleic cultivars and breeding lines intermittently failed to meet self-imposed thresholds for oleic acid content in internal testing. To determine why, a manual seed chipper, crude DNA isolation protocol, genotyping assays for both mutations, and a web-based SNP calling application were developed. The primary cause was determined to be contamination with normal oleic seeds resulting from inadequate screening protocols. In order to correct the problem, a faster screening method was acquired to accommodate a higher oleic acid threshold. Additionally, results showed the mutation in one homeolog is fixed in the program, dig date had no significant effect on oleic acid content, and minor modifiers segregating within the program explained 6% of the variation in oleic acid content.
查看更多>>摘要：Key message A GST for red-spot-petals in Gossypium arboreum was identified as the candidate under the scope of multi-omics approaches. Colored petal spots are correlated with insect pollination efficiency in Gossypium species. However, molecular mechanisms concerning the formation of red spots on Gossypium arboreum flowers remain elusive. In the current study, the Shixiya1-R (SxyR, with red spots) x Shixiya1-W (SxyW, without red spots) segregating population was utilized to determine that the red-spot-petal phenotype was levered by a single dominant locus. This phenotype was expectedly related to the anthocyanin metabolites, wherein the cyanidin and delphinidin derivatives constituted the major partition. Subsequently, this dominant locus was narrowed to a 3.27 Mb range on chromosome 7 by genomic resequencing from the two parents and the two segregated progeny bulks that have spotted petals or not. Furthermore, differential expressed genes generated from the two bulks at either of three sequential flower developmental stages that spanning the spot formation were intersected with the annotated ones that allocated to the 3.27 Mb interval, which returned eight genes. A glutathione S-transferase-coding gene (Gar07G08900) out of the eight was the only one that exhibited simultaneously differential expression among all three developmental stages, and it was therefore considered to be the probable candidate. Finally, functional validation upon this candidate was achieved by the appearance of scattered petal spots with inhibited expression of Gar07G08900. In conclusion, the current report identified a key gene for the red spotted petal in G. arboreum under the scope of multi-omics approaches, such efforts and embedded molecular resources would benefit future applications underlying the flower color trait in cotton.
查看更多>>摘要：Key message The causal gene, CaHY5 of a chemical induced green-hypocotyl mutant was identified by molecular mapping. CaHY5 regulates anthocyanin accumulation by directly binding to the promoter of genes in anthocyanin pathway. Morphological markers at seedling stage are useful indicators for F-1 hybrid seeds screening. Pepper is a worldwide vegetable with diverse uses, and F-1 hybrids are popular in the pepper industry. Hypocotyl color is a useful marker to identify F-1 hybrid seeds. However, most pepper accessions have purple hypocotyl caused by anthocyanin accumulation, while green hypocotyl pepper accessions are rare. In this study, we identified a green hypocotyl mutant (e1898) from a pepper ethylmethanesulfonate (EMS) mutant library. By combining bulked segregant RNA-seq (BSR), genome resequencing and recombinant analysis, it was found that CaHY5 is the causal gene of this mutant. Virus-induced gene silencing (VIGS) of CaHY5 resulted in the decrease of anthocyanin accumulation in pepper hypocotyls. RNA-seq data showed that many genes related to anthocyanin biosynthesis and transport decreased significantly in the mutant. Yeast one-hybrid (Y1H) assays showed that CaHY5 can bind to the promoter of CaF3H, CaF3 ' 5'H, CaDFR, CaANS and CaGST, which are important genes in anthocyanin biosynthesis or transport. Our results indicate that CaHY5 directly regulates anthocyanin biosynthesis and transport, thus governing anthocyanin accumulation in pepper hypocotyl. The mutant and gene identified in this work shall be valuable in the purity control of hybrid pepper seeds.
NSTL
Springer Nature