Association analysis of physiological traits in spring barley (Hordeum vulgare L.) under water-deficit conditions.

In the present study, 148 commercial barley cultivars were assessed by 14 AFLP primer combinations and 32 SSRs primer pairs. Population structure, linkage disequilibrium, and genomic regions associated with physiological traits under drought stress were investigated. The phenotypic results showed a high level of diversity between studied cultivars. The studied barley cultivars were divided into two subgroups. Linkage disequilibrium analysis revealed that r 2 values among all possible marker pairs have an average value of 0.0178. The mixed linear model procedure showed that totally, 207 loci had a significant association with investigated traits. 120 QTLs out of 207 were detected for traits under normal conditions, and 90 QTLs were detected for traits under drought stress conditions. Identified QTLs after validation and transferring to SCAR markers in the case of AFLPs can be used to develop MAS strategies for barley breeding programs. Some common markers were identified for a particular trait or some traits across normal and drought stress conditions. These markers show low interaction with environmental conditions (stable markers); therefore, selection by them for a trait under normal conditions will improve the trait value under stress conditions, too.

Detection of genomic regions associated with tiller number in Iranian bread wheat under different water regimes using genome-wide association study.

Two of the important traits for wheat yield are tiller and fertile tiller number, both of which have been thought to increase cereal yield in favorable and unfavorable environments. A total of 6,349 single nucleotide polymorphism (SNP) markers from the 15 K wheat Infinium array were employed for genome-wide association study (GWAS) of tillering number traits, generating a physical distance of 14,041.6 Mb based on the IWGSC wheat genome sequence. GWAS analysis using Fixed and random model Circulating Probability Unification (FarmCPU) identified a total of 47 significant marker-trait associations (MTAs) for total tiller number (TTN) and fertile tiller number (FTN) in Iranian bread wheat under different water regimes. After applying a 5% false discovery rate (FDR) threshold, a total of 13 and 11 MTAs distributed on 10 chromosomes were found to be significantly associated with TTN and FTN, respectively. Linked single nucleotide polymorphisms for IWB39005 (2A) and IWB44377 (7A) were highly significantly associated (FDR < 0.01) with TTN and FTN traits. Moreover, to validate GWAS results, meta-analysis was performed and 30 meta-QTL regions were identified on 11 chromosomes. The integration of GWAS and meta-QTLs revealed that tillering trait in wheat is a complex trait which is conditioned by the combined effects of minor changes in multiple genes. The information provided by this study can enrich the currently available candidate genes and genetic resources pools, offering evidence for subsequent analysis of genetic adaptation of wheat to different climatic conditions of Iran and other countries.

Tolerance responses in wheat landrace Bolani are related to enhanced metabolic adjustments under drought stress.

Physio-biochemical adaptations of wheat landraces may have great importance in their growth, survival and yield under drought stress. Here, we evaluated the effects of drought stress on some defense systems of wheat cultivar "Sistan" (drought-sensitive) and landrace "Bolani" (drought-tolerant). Under drought stress, Bolani plants showed lower increases in hydrogen peroxide content compared to Sistan ones, which was accompanied with significant decrease in malondialdehyde and electrolyte leakage indices. Increasing the transcript levels and activity of enzymatic and non-enzymatic antioxidants along with phenylpropanoid metabolites improved relative tolerance to drought-induced oxidative stress, particularly in Bolani plants, results which may be confirmed by a significant decrease in the damage indices. In the phenylpropanoid pathway, the biosynthetic pathway of total phenol, flavonoids and anthocyanins was more active than lignin-biosynthetic pathway, which could early respond to drought stress. These results may be confirmed by their negative significant correlations with damage indices as well as a non-significant correlation of lignin with most enzymatic and non-enzymatic antioxidants in plants. Lower decrease of chlorophyll (Chl) and carotenoid contents in Bolani plants compared to Sistan ones indicated the relative stability of photosynthetic pigments under drought stress. Our results suggested that integrating metabolic pathways could coordinately alleviate oxidative stress that can lead to introducing suitable genetic sources for drought tolerance.

Protein complex prediction: A survey.

Protein complexes are one of the most important functional units for deriving biological processes within the cell. Experimental methods have provided valuable data to infer protein complexes. However, these methods have inherent limitations. Considering these limitations, many computational methods have been proposed to predict protein complexes, in the last decade. Almost all of these in-silico methods predict protein complexes from the ever-increasing protein-protein interaction (PPI) data. These computational approaches usually use the PPI data in the format of a huge protein-protein interaction network (PPIN) as input and output various sub-networks of the given PPIN as the predicted protein complexes. Some of these methods have already reached a promising efficiency in protein complex detection. Nonetheless, there are challenges in prediction of other types of protein complexes, specially sparse and small ones. New methods should further incorporate the knowledge of biological properties of proteins to improve the performance. Additionally, there are several challenges that should be considered more effectively in designing the new complex prediction algorithms in the future. This article not only reviews the history of computational protein complex prediction but also provides new insight for improvement of new methodologies. In this article, most important computational methods for protein complex prediction are evaluated and compared. In addition, some of the challenges in the reconstruction of the protein complexes are discussed. Finally, various tools for protein complex prediction and PPIN analysis as well as the current high-throughput databases are reviewed.

Genetic control of some plant growth characteristics of bread wheat (Triticum aestivum L.) under aluminum stress.

BACKGROUND: Biomass yield is an important trait for wheat breeding programs. Enhancing the yield of the aerial components of wheat cultivars will be an integral part of future wheat improvement. Aluminum (Al) toxicity is one of the main factors limiting wheat growth and production in acid soils, which occur on up to 50% of the arable lands of the world especially in tropical and subtropical regions. OBJECTIVE: Our objective was to identify quantitative trait loci (QTL) of plant growth characteristics and yield in wheat. METHODS: A recombinant inbred line (RIL) population consisting of 167 lines, derived from a cross between SeriM82 and Babax were evaluated under two Al treatments (+ Al, 800 µM of Al; -Al, 0 µM of Al) in the field based on an alpha lattice design with two replications for two consecutive crop seasons. RESULTS: A total of 40 QTLs including nine putative and 31 suggestive QTLs were found for all traits using the composite interval mapping (CIM) method. By mixed model-based composite interval mapping (MCIM) method, 42 additive QTLs and nine pairs of epistatic effects were detected for studied traits, of which 20 additive and six pairs of epistatic QTLs showed significant QTL × environment interactions. Most of the detected QTLs across environments were stable, and the highest number of stable QTLs was related to A genome. Co-localization of QTL was found on linkage groups (LGs) 2B, 4B, 6A-a, and 7A (CIM method) and 2A-d, and 6A-a (MCIM method). CONCLUSION: These results have implications for selection strategies in biomass yield and for increasing the yield of the aerial part of wheat following further evaluations in various genetic backgrounds and environments.

Fumaric acids as a novel antagonist of TLR-4 pathway mitigates arsenic-exposed inflammation in human monocyte-derived dendritic cells.

Exposure to environmentally relevant doses of arsenic has several harmful effects on the human immune system. In traditional Eastern medicines, nettle has been used as an anti-inflammatory agent to treat rheumatism and osteoarthritis. Fumaric acid (FA) as a major effective compound in nettle was chosen based on very accurate virtual screening to find antagonist for TLR4/MD structure. In this study, the in vitro therapeutic effects of FA on arsenic-exposed monocytes-derived dendritic cells (MDDCs) were evaluated. All the canonical functions of dendritic cells in bridging innate and adaptive immune system including phagocytosis and antigen-presenting capacity, and also cytokines secretion, were evaluated after exposure to arsenic/FA. FA profoundly over-expressed antigen-presenting capacity of MDDCs after exposure to arsenic through the upregulation of MHCιι. However, phagocytosis capacity of arsenic-exposed MDDCs is not compensated for, by treatment with FA. Arsenic up-regulates pro-inflammatory cytokines independents of TLR4 pathway. FA surprisingly mitigates the up-regulation of IL-1ß and TNF-α but not TLR4 and NF-kB. Moreover, FA increases the viability of MDDCs even at a high dose of arsenic. Totally, FA reduced inflammatory factors induced by arsenic. This finding confirmed that nettle and other medicinal plants containing similar structures with FA could be further analyzed as valuable candidates for the reduction of drastic effects of arsenic in human immune systems.

Mapping QTLs of flag leaf morphological and physiological traits related to aluminum tolerance in wheat (Triticum aestivum L.).

Genetic improvement of aluminum (Al) tolerance is one of the cost-effective solutions to improve plant productivity in acidic soils around the world. This study was performed to progress our understanding of the genetic mechanisms of aluminum tolerance underlying wheat (Triticum aestivum L.) flag leaf morphological and physiological traits. A recombinant inbred line population derived from SeriM82 and Babax was used for mapping quantitative trait loci (QTL) in wheat for tolerance to Al toxicity through 477 DNA markers. Based on a single-locus analysis, 48 QTLs including 16 putative and 32 suggestive QTLs were identified for all studied traits. Individual QTL explained 4.57-11.29% of the phenotypic variance in different environments during both the crop seasons. These QTLs located unevenly throughout the wheat genome. Among them, 52.08%, 29.17%, and 18.75% were in the A, B, and D genomes, respectively. Based on two-locus analysis, 54 additive QTLs and 6 pairs of epistatic effects were detected, among which 29 additive and 5 pairs of epistatic QTLs showed significant QTL × environment interactions. The highest number of stable QTLs was identified on genome A. Determining a number of QTL clusters indicated tight linkage or pleiotropy in the inheritance of different traits. The stable and major QTLs controlling traits in this research can be applied for verification in different environments and genetic backgrounds and identifying superior allelic variations in wheat to increase the performance of selection of high yielding lines adapted to Al stress in breeding programs.

Evolutionary dynamics models in biometrical genetics supports QTL × environment interactions.

The process of development of quantitative trait locus (QTL) involves interactions between many factors, both environmental and genetic, in which many genes interact often in no additive pathways together and with environment. Integration of the mathematical, statistical and biological aspects of these subjects has made important and interesting results. In this review, mathematical methods offered to study the QTL × environment interactions. The topic is circumscribed, going from basic selection equations to models of evolution of QTLs. Discrete and continuous time mathematical models and subsequently, QTL modelling were introduced with and without environmental interactions. The mathematical models derived here showed that the gradients of mean fitness which have revealed in studies by many researchers had a basic role in mathematical genetics, evolutionary aspects of biometrical genetics and QTL analysis. QTL × environment interactions were studied mathematically including fitness components too. It was revealed that QTL × environment interactions in fitness could generate a balancing selection. Also, QTL analysis could be used to calculate the geometry of the phenotype landscape. In this paper, models applied in biometrical genetics corresponds to QTL analysis and matched with results from other researchers. The originality of this synthesis is the evolutionary modelling of QTL × environment interactions which can be used to investigate the extinction or stability of a population. Also to emphasize that although some scientific subjects like Brownian motion, quantum mechanics, general relativity, differential geometry, and evolutionarybiometrical genetics were apparently different subjects, but the mathematical models were the backbone of these branches of science. This implies that such matters in nature have probably common and elegant basis. The perspective of the subject of this paper in future will be a new and interesting branch of interdisciplinary science.

Genetic Mapping and Validation of Quantitative Trait Loci (QTL) for the Grain Appearance and Quality Traits in Rice (Oryza sativa L.) by Using Recombinant Inbred Line (RIL) Population.

Rice grain shape and nutritional quality traits have high economic value for commercial production of rice and largely determine the market price, besides influencing the global food demand for high-quality rice. In order to understand the genetic components of grain appearance traits in paddy, brown, and head rice, 15 traits were evaluated by using 157 recombinant inbred lines (RILs) derived from a cross between two Iranian rice cultivars Ali-Kazemi (A) and Kadous (K). A significant variation was observed and showed transgressive segregation among the RILs. Correlations between the visual appearances of grain traits were studied. A linkage map with 65 polymorphic SSR markers was constructed, which covered 1517.32 cM of the rice genome. A total of seven QTLs were identified on four chromosomes, 1, 6, 9, and 12, associated with four traits, which are explained by the total phenotypic variation of 44.27% and LOD score of 32.77 in 2014 and 2015, respectively. Among these, four QTLs for two traits were consistently flanked by RM23904 and RM24432 on chromosome 9. Single QTL for head grain length (HGL) expressed in both the years on chromosomes 1 and 9. A major QTL for seed weight was detected on chromosome 9, which explained 10.18% of the phenotypic variation. The additive effect of all the QTLs was positively contributed by Ali-Kazemi allele, except one QTL on chromosome 6 (qBGL_6) that showed a negative additive effect being contributed by the Kadous allele. The study also validated the identified QTLs with the polymorphic SSR markers that were previously reported. Novel QTLs were identified on chromosomes 6 and 9, and many of the polymorphic markers were found to be associated with milling processing of grain quality, cooking, and nutraceutical properties of rice by extensive literature and database analysis. Therefore, these validated QTLs and marker information could be utilized in the marker-assisted selection to improve grain appearance and nutritional grain quality traits in rice.

Mapping QTL controlling agronomic traits in a doubled haploid population of winter oilseed rape (Brassica napus L.).

Identification of superior alleles for agronomic traits in genetic resources of oilseed rape (Brassica napus L.) would be useful for improving the performance of locally adapted cultivars in Iran. The objective of the present work was to analyse the genetic variation and inheritance of important agronomic traits in a doubled haploid population derived from a cross between two German oilseed rape cultivars, Sansibar and Oase. Field experiments were performed in 2016-2017 with 200 doubled haploid lines and the parental genotypes applying an alpha-lattice design with two replicates. Phenological traits were recorded during the cultivation period and at maturity, seed yield, yield components and seed quality traits were determined. Significant genetic variation was found in most of the traits and heritabilities ranged from medium (48.5%) for days to end of flowering to high (92.6%) for oil content. A molecular marker linkage map was used to map 36 QTL for different traits on 17 linkage groups. Between three and four QTL were identified for each seed yield, seed weight, oil and protein content. Some of the plant material and positive QTL alleles identified for agronomic traits may be useful for improving those characters in locally adapted cultivars in Iran.

Mapping QTLs for physiological and biochemical traits related to grain yield under control and terminal heat stress conditions in bread wheat (Triticum aestivum L.).

In order to detect genomic regions with different effects for some of the physiological and biochemical traits of wheat, four experiments were conducted at Research Farm of Agricultural and Natural Resources Research Center of Zabol in 2015-2016 and 2016-2017 growing seasons. The experiments were carried out using four alpha lattice designs with two replications under non-stress and terminal heat stress conditions. Plant materials used in this study included 167 recombinant inbred lines and their parents ('SeriM82' and 'Babax'). Six traits including grain yield (GY), proline content (PRO), water soluble carbohydrates (WSC), maximum efficiency of photosystem II (Fv/Fm), cytoplasmic membrane stability (CMS) and chlorophyll content (CHL) were evaluated. Genetic linkage map consisted of 211 AFLP marker, 120 SSR marker and 144 DArT markers with 1864 cm length and 4.4 cm mean distance. QTL analysis was carried out using a mixed-model-based composite interval mapping (MCIM) method. By the combined analysis of normal phenotypic values, 27 additive QTLs and five pairs of epistatic effects were identified for studied traits, among which two additive and one epistatic QTL showed significant QTL × environment interactions. By the combined analysis of stress phenotypic values, a total of 26 QTLs with additive effects and 5 epistatic QTLs were detected, among which one additive and one epistatic QTL showed QTL × environment interactions. Six QTLs with major effects (QGY-2B, QGY-2D, QPro-5B, QWSC-4A, QFv/Fm-6A and QCMS-4B), which were common between two conditions could be useful for marker-assisted selection (MAS) in order to develop heat tolerant and high-performance wheat varieties.

GWAS analysis in spring barley (Hordeum vulgare L.) for morphological traits exposed to drought.

Association analysis based on linkage disequilibrium has become a common and powerful approach for detection of QTLs underlying complex agronomic traits including drought tolerance. To determine marker/trait association, 148 modern European spring barley cultivars were evaluated under drought stress. Associations of morphological traits with AFLP/SSR markers were investigated based on the mixed linear model using the TASSEL3.0. Population structure was estimated using various methods including Bayesian clustering model by STRUCTURE software, PCoA analysis, NJ dendrogram and Hierarchical Clustering. Linkage disequilibrium patterns were explored among the whole genome and each chromosome separately. All the analysis for population structure divided the population into two sub-groups. Linkage disequilibrium analysis showed that by increasing genetic distance, LD decreases. Totally, 167 significant marker trait associations were found which delineated into 65 QTLs in both treatments. Two stable QTLs on 5H at 86.880 cM were detected for Internode Length and on 3H at 126.421 cM for flag leaf length in drought stress treatment. Fourteen QTLs were co-localized with previously reported QTLs and others were novel. The results indicate that these putative genomic regions contain genes that have pleiotropic effects on morphological traits in drought condition.

Leaf proteomics of drought-sensitive and -tolerant genotypes of fennel.

Fennel is attracted attention as a useful resource as researching medicinal plant for drought tolerance. To elucidate the response mechanism in drought-sensitive and -tolerant genotypes of fennel leaf, a gel-free/label-free proteomic technique was used. Fifty-day-old plants were subjected to drought stress for 60days. The relative water and proline contents were decreased and increased in sensitive genotypes, respectively; however, they were not a big change in tolerant genotypes. Photosynthesis was decreased in the sensitive genotypes under drought; however, it was increased in the tolerant genotype. In both drought-sensitive and -tolerant genotypes, proteins related to protein metabolism and cell organization were predominately affected under drought stress. The abundance of phosphoribulokinase and phosphoglycerate kinase enzymes were decreased and increased in drought-sensitive and -tolerant genotypes, respectively; however, the abundance of RuBisCO and glyceraldehyde-3-phosphate dehydrogenase enzymes were increased and decreased in drought-sensitive and -tolerant genotypes, respectively. Under drought stress, the abundance of glycolysis-related proteins was decreased in sensitive genotypes; however, they were increased in tolerance genotypes. Commonly changed proteins with polyethylene glycol fractionation such as cobalamin-independent methionine synthase were decreased and increased in drought-sensitive and -tolerant genotypes, respectively. These results suggest that cobalamin-independent methionine synthetase is involved in the tolerance of drought-tolerant fennel leaf under drought stress.