Effect of silicon on grain yield of rice under cadmium-stress

Many publications indicated various beneficial effects of the addition of silicon (Si) in soil on the physiology of rice plants. The gene responsible for the Si-uptake in rice, low Si-influx 1 (Lsi1), was identified and cloned for this study. The photosynthetic rate (Pn), grain yield, and resistance to Cadmium (Cd)-stress of the wild-type (WT) and Lsi1-transgenic Lemont rice lines under Cd-stress were examined in an attempt to better understand the mechanism associated with the Si-addition, Cd-stress, and rice physiology. Si-fertilization significantly reduced the Cd-content in rice under Cd-stress. The effect was most significant in the Lsi1-overexpression transgenic Lemont rice (Lsi1-OE line) under high Cd-stress. Conversely, Cd in soil lowered the Si-uptake of the plants indicating a significant interaction between the two elements. During the grain-filling period, Cd-stress greatly reduced the chlorophyll content and Pn of the rice resulting in a diminished grain output. However, Lsi1-OE line with a higher chlorophyll content and Pn than either WT or Lsi1-RNAi transgenic Lemont rice (Lsi1-RNAi line) maintained a high photo-assimilate transportation for high yield potential. At harvest, Lsi1-OE line contained more Si and less Cd than WT, whereas the Lsi1-RNAi line showed an opposite result. In general, Cd-stress reduced, while Si-fertilization significantly increased, the grain yield on rice. However, no significant difference on the grain yields existed between WT and Lsi1-RNAi line. This might be due to a compensation effect generated by Lsi1-RNAi line. It appeared that Si in the soil, as well as the enhancing or inhibiting Lsi1 expression and the resistance to Cd-toxicity of the plants, could significantly affect the rice yield making alternations on these factors a plausible approach for production improvement.     

Genome wide association studies (GWAS) of spot blotch resistance at the seedling and the adult plant stages in a collection of spring barley

Spot blotch (SB) in barley is caused by the fungal pathogen Cochliobolus sativus and considered one of the major constraints to successful barley production. Resistance to C. sativus was evaluated, using a barley collection of 336 genotypes (AM-2014), at the seedling and adult stages. Seedling resistance was evaluated by using a mixture of 19 virulent isolates in Morocco. Virulent isolates prevalent in Uttar Pradesh were used for phenotyping resistance at the adult stage in India. The AM-2014 panel was genotyped with 9-K single-nucleotide polymorphism (SNP) markers using iSelect Illumina Infinium. Genome wide association studies (GWAS) were carried out using SNP markers, infection responses, disease severity, and area under the disease progress curve (AUDPC). The mixed linear model was employed in TASSEL using principal component analysis (PCA) and Kinship matrix (K) as covariates. Higher SB severity, 82.3?±?13.5 (mean?±?SD), was recorded at the Banaras Hindu University (BHU) compared to 47.6?±?15.0 at the Narendra Dev University of Agriculture and Technology (NDUAT). Nine QTL, Rcs-qtl-1H-126.9, Rcs-qtl-2H-148.16, Rcs-qtl-3H-25.27, Rcs-qtl-5H-80.35, Rcs-qtl-6H-58.24, Rcs-qtl-7H-29.62, Rcs-qtl-7H-29.72, Rcs-qtl-7H-32.81, and Rcs-qtl-7H-34.74, were detected for SB resistance at the seedling stage. For SB severity at the adult stage, a QTL, Rcs-qtl-7H-32.81, was detected at BHU while seven QTL, Rcs-qtl-2H-91.09, Rcs-qtl-3H-145.64, Rcs-qtl-4H-14.43, Rcs-qtl-6H-6.49, Rcs-qtl-7H-114.43, Rcs-qtl-7H-151.66, and Rcs-qtl-7H-150.36, were found for SB severity at NDUAT. Three QTL, Rcs-qtl-4H-18.61, Rcs-qtl-4H-67.91, and Rcs-qtl-5H-110.25, were significant for AUDPC of SB at BHU. The QTLs reported in this study are important to advance marker-assisted selection and gene pyramiding of SB resistance in South Asia and North Africa in future.     

Proteomics to identify pathogenesis-related proteins in rice roots under water deficit

Upland and lowland rice (Oryza sativa L.) showed different mechanisms of water stress resistance. Hydroponically grown 3-week-old seedlings of a lowland variety IR64 and an upland variety were exposed to 15% polyethylene glycol (PEG-6000). After 7 d of treatment, IR64 maintained high relative water content and developed a well-branched root. Therefore, IR64 had better water-deficit tolerance than Azucena under PEG treatment. To identify water-deficit-responsive proteins associated with the tolerance differences between two ecotypes, a comparative proteomic analysis of roots was conducted. Out of 700 proteins reproducibly detected on two-dimensional electrophoresis gels, 65 proteins exhibited significant changes in at least one ecotype at 48 h of water deficit. Only 15 proteins showed different responses to water deficit between the two ecotypes. Twelve proteins were identified by matrix-assisted laser desorption/ionization-time of flight/time of flight-mass spectrometry, which involved in energy and metabolism, protein processing and degradation, detoxification and pathogenrelated (PR) proteins, i.e. PR-1a, RSOsPR10 and JIOsPR10. All three PR proteins were induced more strongly in IR64 than in Azucena by water deficit at both protein and mRNA level. The results suggested that PR-1a, RSOsPR10 and JIOsPR10 may play important roles in protecting root cells against water deficit in rice.     

A large-effect QTL for rice grain yield under upland drought stress on chromosome 1

Drought is a major abiotic stress factor limiting rice production in rainfed areas. In this study we identified a large-effect quantitative trait locus (QTL) associated with grain yield under stress in five different populations on chromosome 1. The effect of this QTL was further confirmed and characterized in five backcross populations in a total of sixteen stress and non-stress trials during 2006 and 2008. In all the stress trials (eight in total) qDTY1.1 showed strong association with grain yield explaining on average 58% of the genetic variation in the trait. Homozygotes for the tolerant parent allele (Apo) yielded on average 27% more than the susceptible parent allele (IR64) homozygotes. Using an Apo/^3*IR64 population, the peak of this QTL (qDTY1.1) was mapped to an interval between RM486 and RM472 at 162.8?cM at a LOD score of 9.26. qDTY1.1 was strongly associated with plant height in all the environments; this was probably due to the presence of the sd1 locus in this genomic region. In a Vandana/^3*IR64 population segregating for sd1, a strong relation between plant height and yield under stress was observed. The observed relation between increased height and drought tolerance is likely due to tight linkage between qDTY1.1 and sd1 and not due to pleiotrophy of sd1. Thus there is a possibility of combining reduced plant height and drought tolerance in rice. The large and consistent effect of qDTY1.1 across several genetic backgrounds and environments makes it a potential strong candidate for use in molecular breeding of rice for drought tolerance.     

Identifying and exploiting grain yield genes in rice

Improved grain yield has been a major focus of crop breeding programs around the world. With the accomplishments of the Rice Genome Project, genes regulating several agronomically important traits related to grain yield, such as tiller number, grain number, grain size, and plant height, have recently been identified. Although these findings have not been enough to fully characterize the mechanisms that regulate each trait, these genes and knowledge of the molecular mechanisms involved provide a set of tools that can be combined to achieve tailor-made breeding suitable for various programs aimed at higher grain yield.     

Genome-wide association study (GWAS) of salt tolerance in worldwide soybean germplasm lines

Salt is a severe abiotic stress causing soybean yield loss in saline soils and irrigated fields. Marker-assisted selection (MAS) is a powerful genomic tool for improving the efficiency of breeding salt-tolerant soybean varieties. The objectives of this study were to uncover novel single-nucleotide polymorphisms (SNPs) and quantitative trait loci (QTLs) associated with salt tolerance and to confirm the previously identified genomic regions and SNPs for salt tolerance. A total of 283 diverse soybean plant introductions (PIs) were screened for salt tolerance in the greenhouse based on leaf chloride concentrations and leaf chlorophyll concentrations after 12–18 days of 120-mM NaCl treatment. A total of 33,009 SNPs across 283 genotypes from the Illumina Infinium SoySNP50K BeadChip database were employed in the association analysis with leaf chloride concentrations and leaf chlorophyll concentrations. Genome-wide association mapping showed that 45 SNPs representing nine genomic regions on chromosomes (Chr.) 2, 3, 7, 8, 10, 13, 14, 16, and 20 were significantly associated with both leaf chloride concentrations and leaf chlorophyll concentrations in 2014, 2015, and combined years. A total of 31 SNPs on Chr. 3 were mapped at or near the previously reported major salt tolerance QTL. The significant SNP on Chr. 2 was also in proximity to the previously reported SNP for salt tolerance. The other significant SNPs represent seven putative novel QTLs for salt tolerance. The significant SNP markers on Chr. 2, 3, 14, 16, and 20, which were identified in both general linear model and mixed linear model, were highly recommended for MAS in breeding salt-tolerant soybean varieties.     

Genome wide association studies for milk production traits in Chinese Holstein population

Genome-wide association studies (GWAS) based on high throughput SNP genotyping technologies open a broad avenue for exploring genes associated with milk production traits in dairy cattle. Motivated by pinpointing novel quantitative trait nucleotide (QTN) across Bos Taurus genome, the present study is to perform GWAS to identify genes affecting milk production traits using current state-of-the-art SNP genotyping technology, i.e., the Illumina BovineSNP50 BeadChip. In the analyses, the five most commonly evaluated milk production traits are involved, including milk yield (MY), milk fat yield (FY), milk protein yield (PY), milk fat percentage (FP) and milk protein percentage (PP). Estimated breeding values (EBVs) of 2,093 daughters from 14 paternal half-sib families are considered as phenotypes within the framework of a daughter design. Association tests between each trait and the 54K SNPs are achieved via two different analysis approaches, a paternal transmission disequilibrium test (TDT)-based approach (L1-TDT) and a mixed model based regression analysis (MMRA). In total, 105 SNPs were detected to be significantly associated genome-wise with one or multiple milk production traits. Of the 105 SNPs, 38 were commonly detected by both methods, while four and 63 were solely detected by L1-TDT and MMRA, respectively. The majority (86 out of 105) of the significant SNPs is located within the reported QTL regions and some are within or close to the reported candidate genes. In particular, two SNPs, ARS-BFGL-NGS-4939 and BFGL-NGS-118998, are located close to the DGAT1 gene (160bp apart) and within the GHR gene, respectively. Our findings herein not only provide confirmatory evidences for previously findings, but also explore a suite of novel SNPs associated with milk production traits, and thus form a solid basis for eventually unraveling the causal mutations for milk production traits in dairy cattle.     

Upland rice and lowland rice exhibited different PIP expression under water deficit and ABA treatment

Aquaporins play a significant role in plant water relations. To further understand the aquaporin function in plants under water stress, the expression of a subgroup of aquaporins, plasma membrane intrinsic proteins （PIPs）, was studied at both the protein and mRNA level in upland rice （Oryza sativa L. cv. Zhonghan 3） and lowland rice （Oryza sativa L. cv. Xiushui 63） when they were water stressed by treatment with 20% polyethylene glycol （PEG）. Plants responded differently to 20% PEG treatment. Leaf water content of upland rice leaves was reduced rapidly. PIP protein level increased markedly in roots of both types, but only in leaves of upland rice after 10 h of PEG treatment. At the mRNA level, OsPIP1,2, OsPIP1,3, OsPIP2;1 and OsPIP2;5 in roots as well as OsPIP1,2 and OsPIP1;3 in leaves were significantly up-regulated in upland rice, whereas the corresponding genes remained unchanged or down-regulated in lowland rice. Meanwhile, we observed a significant increase in the endogenous abscisic acid （ABA） level in upland rice but not in lowland rice under water deficit. Treatment with 60 μM ABA enhanced the expression of OsPIP1;2, OsPIP2;5 and OsPIP2;6 in roots and OsPIP1;2, OsPIP2;4 and OsPIP2;6 in leaves of upland rice. The responsiveness of PIP genes to water stress and ABA were different, implying that the regulation of PIP genes involves both ABA-dependent and ABA-independent signaling oathways during water deficit.     

Genome wide association studies in presence of misclassified binary responses

Background

Misclassification has been shown to have a high prevalence in binary responses in both livestock and human populations. Leaving these errors uncorrected before analyses will have a negative impact on the overall goal of genome-wide association studies (GWAS) including reducing predictive power. A liability threshold model that contemplates misclassification was developed to assess the effects of mis-diagnostic errors on GWAS. Four simulated scenarios of case–control datasets were generated. Each dataset consisted of 2000 individuals and was analyzed with varying odds ratios of the influential SNPs and misclassification rates of 5% and 10%.

Results

Analyses of binary responses subject to misclassification resulted in underestimation of influential SNPs and failed to estimate the true magnitude and direction of the effects. Once the misclassification algorithm was applied there was a 12% to 29% increase in accuracy, and a substantial reduction in bias. The proposed method was able to capture the majority of the most significant SNPs that were not identified in the analysis of the misclassified data. In fact, in one of the simulation scenarios, 33% of the influential SNPs were not identified using the misclassified data, compared with the analysis using the data without misclassification. However, using the proposed method, only 13% were not identified. Furthermore, the proposed method was able to identify with high probability a large portion of the truly misclassified observations.

Conclusions

The proposed model provides a statistical tool to correct or at least attenuate the negative effects of misclassified binary responses in GWAS. Across different levels of misclassification probability as well as odds ratios of significant SNPs, the model proved to be robust. In fact, SNP effects, and misclassification probability were accurately estimated and the truly misclassified observations were identified with high probabilities compared to non-misclassified responses. This study was limited to situations where the misclassification probability was assumed to be the same in cases and controls which is not always the case based on real human disease data. Thus, it is of interest to evaluate the performance of the proposed model in that situation which is the current focus of our research.

     

Genome wide association (GWA) study for early onset extreme obesity supports the role of fat mass and obesity associated gene (FTO) variants

Background

Obesity is a major health problem. Although heritability is substantial, genetic mechanisms predisposing to obesity are not very well understood. We have performed a genome wide association study (GWA) for early onset (extreme) obesity.

Methodology/Principal Findings

a) GWA (Genome-Wide Human SNP Array 5.0 comprising 440,794 single nucleotide polymorphisms) for early onset extreme obesity based on 487 extremely obese young German individuals and 442 healthy lean German controls; b) confirmatory analyses on 644 independent families with at least one obese offspring and both parents. We aimed to identify and subsequently confirm the 15 SNPs (minor allele frequency ≥10%) with the lowest p-values of the GWA by four genetic models: additive, recessive, dominant and allelic. Six single nucleotide polymorphisms (SNPs) in FTO (fat mass and obesity associated gene) within one linkage disequilibrium (LD) block including the GWA SNP rendering the lowest p-value (rs1121980; log-additive model: nominal p = 1.13×10⁻⁷, corrected p = 0.0494; odds ratio (OR)_CT 1.67, 95% confidence interval (CI) 1.22–2.27; OR_TT 2.76, 95% CI 1.88–4.03) belonged to the 15 SNPs showing the strongest evidence for association with obesity. For confirmation we genotyped 11 of these in the 644 independent families (of the six FTO SNPs we chose only two representing the LD bock). For both FTO SNPs the initial association was confirmed (both Bonferroni corrected p<0.01). However, none of the nine non-FTO SNPs revealed significant transmission disequilibrium.

Conclusions/Significance

Our GWA for extreme early onset obesity substantiates that variation in FTO strongly contributes to early onset obesity. This is a further proof of concept for GWA to detect genes relevant for highly complex phenotypes. We concurrently show that nine additional SNPs with initially low p-values in the GWA were not confirmed in our family study, thus suggesting that of the best 15 SNPs in the GWA only the FTO SNPs represent true positive findings.     

Association mapping for yield and grain quality traits in rice (Oryza sativa L.)

Association analysis was applied to a panel of accessions of Embrapa Rice Core Collection (ERiCC) with 86 SSR and field data from two experiments. A clear subdivision between lowland and upland accessions was apparent, thereby indicating the presence of population structure. Thirty-two accessions with admixed ancestry were identified through structure analysis, these being discarded from association analysis, thus leaving 210 accessions subdivided into two panels. The association of yield and grain-quality traits with SSR was undertaken with a mixed linear model, with markers and subpopulation as fixed factors, and kinship matrix as a random factor. Eight markers from the two appraised panels showed significant association with four different traits, although only one (RM190) maintained the marker-trait association across years and cultivation. The significant association detected between amylose content and RM190 was in agreement with previous QTL analyses in the literature. Herein, the feasibility of undertaking association analysis in conjunction with germplasm characterization was demonstrated, even when considering low marker density. The high linkage disequilibrium expected in rice lines and cultivars facilitates the detection of marker-trait associations for implementing marker assisted selection, and the mining of alleles related to important traits in germplasm.     

Germplasm-regression-combined (GRC) marker-trait association identification in plant breeding: a challenge for plant biotechnological breeding under soil water deficit conditions

In the past 20 years, the major effort in plant breeding has changed from quantitative to molecular genetics with emphasis on quantitative trait loci (QTL) identification and marker assisted selection (MAS). However, results have been modest. This has been due to several factors including absence of tight linkage QTL, non-availability of mapping populations, and substantial time needed to develop such populations. To overcome these limitations, and as an alternative to planned populations, molecular marker–trait associations have been identified by the combination between germplasm and the regression technique. In the present preview, the authors (1) survey the successful applications of germplasm–regression–combined (GRC) molecular marker–trait association identification in plants; (2) describe how to do the GRC analysis and its differences from mapping QTL based on a linkage map reconstructed from the planned populations; (3) consider the factors that affect the GRC association identification, including selections of optimal germplasm and molecular markers and testing of identification efficiency of markers associated with traits; and (4) finally discuss the future prospects of GRC marker–trait association analysis used in plant MAS/QTL breeding programs, especially in long-juvenile woody plants when no other genetic information such as linkage maps and QTL are available.     

Physiological parameters of desert truffle mycorrhizal Helianthemun almeriense plants cultivated in orchards under water deficit conditions

Physiological parameters of mycorrhizal symbiosis by Helianthemum almeriense and Terfezia claveryi in orchards were characterized under water deficit conditions. Our orchard included 40 mycorrhizal and 40 nonmycorrhizal plants. Only mycorrhizal plants survived at the beginning of the experimental period, indicating dependency on fungal symbionts in roots for survival. Drought stress significantly affected the mycorrhizal colonization percentage which was 70% in nonirrigated mycorrhizal and 48% in irrigated mycorrhizal plants. No significant differences in plant growth were observed between nonirrigated and irrigated mycorrhizal plants before and after drought stress. Stomatal conductance was more sensitive to water stress than shoot water potential. It decreased more than two-fold under drought-stress compared to control mycorrhizal plants under irrigation/light saturating conditions, indicating important stomatal closure with water deficit. Plants’ water use efficiency improved with drought with stomatal conductance values below 0.3 mol?m^?2?s^?1. The ability to maintain open stomata and photosynthesis under drought increased carbon supply for growth, and ascocarp fruiting which requires current photosynthates. Basically, H. almeriense shows a conservative water use strategy based mainly on avoiding drought stress by reducing stomatal conductance as soil water potential decreases and atmospheric conditions dry. The results show that mycorrhizal H. almeriense plants maintain good physiological parameters with low soil matric potentials, thus making them an alternative agricultural crop in arid/semi-arid areas.