Deciphering Spatial Protein-Protein Interactions in Brain Using Proximity Labeling.

Cellular biomolecular complexes including protein-protein, protein-RNA, and protein-DNA interactions regulate and execute most biological functions. In particular in brain, protein-protein interactions (PPIs) mediate or regulate virtually all nerve cell functions, such as neurotransmission, cell-cell communication, neurogenesis, synaptogenesis, and synaptic plasticity. Perturbations of PPIs in specific subsets of neurons and glia are thought to underly a majority of neurobiological disorders. Therefore, understanding biological functions at a cellular level requires a reasonably complete catalog of all physical interactions between proteins. An enzyme-catalyzed method to biotinylate proximal interacting proteins within 10 to 300 nm of each other is being increasingly used to characterize the spatiotemporal features of complex PPIs in brain. Thus, proximity labeling has emerged recently as a powerful tool to identify proteomes in distinct cell types in brain as well as proteomes and PPIs in structures difficult to isolate, such as the synaptic cleft, axonal projections, or astrocyte-neuron junctions. In this review, we summarize recent advances in proximity labeling methods and their application to neurobiology.

RhoC in association with TET2/WDR5 regulates cancer stem cells by epigenetically modifying the expression of pluripotency genes.

Emerging evidence illustrates that RhoC has divergent roles in cervical cancer progression where it controls epithelial to mesenchymal transition (EMT), migration, angiogenesis, invasion, tumor growth, and radiation response. Cancer stem cells (CSCs) are the primary cause of recurrence and metastasis and exhibit all of the above phenotypes. It, therefore, becomes imperative to understand if RhoC regulates CSCs in cervical cancer. In this study, cell lines and clinical specimen-based findings demonstrate that RhoC regulates tumor phenotypes such as clonogenicity and anoikis resistance. Accordingly, inhibition of RhoC abrogated these phenotypes. RNA-seq analysis revealed that RhoC over-expression resulted in up-regulation of 27% of the transcriptome. Further, the Infinium MethylationEPIC array showed that RhoC over-expressing cells had a demethylated genome. Studies divulged that RhoC via TET2 signaling regulated the demethylation of the genome. Further investigations comprising ChIP-seq, reporter assays, and mass spectrometry revealed that RhoC associates with WDR5 in the nucleus and regulates the expression of pluripotency genes such as Nanog. Interestingly, clinical specimen-based investigations revealed the existence of a subset of tumor cells marked by RhoC+/Nanog+ expression. Finally, combinatorial inhibition (in vitro) of RhoC and its partners (WDR5 and TET2) resulted in increased sensitization of clinical specimen-derived cells to radiation. These findings collectively reveal a novel role for nuclear RhoC in the epigenetic regulation of Nanog and identify RhoC as a regulator of CSCs. The study nominates RhoC and associated signaling pathways as therapeutic targets.

Transcriptome profiling at osmotic and ionic phases of salt stress response in bread wheat uncovers trait-specific candidate genes.

BACKGROUND: Bread wheat is one of the most important crops for the human diet, but the increasing soil salinization is causing yield reductions worldwide. Improving salt stress tolerance in wheat requires the elucidation of the mechanistic basis of plant response to this abiotic stress factor. Although several studies have been performed to analyze wheat adaptation to salt stress, there are still some gaps to fully understand the molecular mechanisms from initial signal perception to the onset of responsive tolerance pathways. The main objective of this study is to exploit the dynamic salt stress transcriptome in underlying QTL regions to uncover candidate genes controlling salt stress tolerance in bread wheat. The massive analysis of 3'-ends sequencing protocol was used to analyze leave samples at osmotic and ionic phases. Afterward, stress-responsive genes overlapping QTL for salt stress-related traits in two mapping populations were identified. RESULTS: Among the over-represented salt-responsive gene categories, the early up-regulation of calcium-binding and cell wall synthesis genes found in the tolerant genotype are presumably strategies to cope with the salt-related osmotic stress. On the other hand, the down-regulation of photosynthesis-related and calcium-binding genes, and the increased oxidative stress response in the susceptible genotype are linked with the greater photosynthesis inhibition at the osmotic phase. The specific up-regulation of some ABC transporters and Na+/Ca2+ exchangers in the tolerant genotype at the ionic stage indicates their involvement in mechanisms of sodium exclusion and homeostasis. Moreover, genes related to protein synthesis and breakdown were identified at both stress phases. Based on the linkage disequilibrium blocks, salt-responsive genes within QTL intervals were identified as potential components operating in pathways leading to salt stress tolerance. Furthermore, this study conferred evidence of novel regions with transcription in bread wheat. CONCLUSION: The dynamic transcriptome analysis allowed the comparison of osmotic and ionic phases of the salt stress response and gave insights into key molecular mechanisms involved in the salt stress adaptation of contrasting bread wheat genotypes. The leveraging of the highly contiguous chromosome-level reference genome sequence assembly facilitated the QTL dissection by targeting novel candidate genes for salt tolerance.

Effect of point mutation on structure-function correlation of hemoglobin variants, HbE and HbD Punjab.

Hemoglobinopathies are examples of autosomal recessive disorders of human hemoglobin. Hemoglobin E (HbE) and Hemoglobin D Punjab (HbD Punjab) are two of the most common hemoglobin variants geographically spread across Asian continent. These two variants differ from normal human hemoglobin (HbA) at a single amino acid residue caused by the point mutation of ß globin gene. The presence of the mutated amino acid residue causes perturbation in the function of both variants. However, the structure-function correlation of these variants has not been established yet. In the present study, we analyzed the conformational changes associated with oxygenation of hemoglobin variants using hydrogen/deuterium exchange-based mass spectrometry of backbone amide hydrogens of α and ß globin chains in the tetrameric hemoglobin molecule. We also performed the functional assay of these variants using oxygen dissociation equilibrium curve. Compared to HbA, both variants showed reduced oxygen affinity, as reported earlier. The functional perturbations exhibited by these variants were correlated well with their structural alterations with respect to the reported changes in the residue level interactions upon oxygenation of normal hemoglobin, monitored through the hydrogen/deuterium exchange kinetics of several peptic peptides originated from the isotopically exchanged oxy and deoxy forms of HbE and HbD Punjab.

Homologs from sulfur oxidation (Sox) and methanol dehydrogenation (Xox) enzyme systems collaborate to give rise to a novel pathway of chemolithotrophic tetrathionate oxidation.

The SoxXAYZB(CD)2 -mediated pathway of bacterial sulfur-chemolithotrophy explains the oxidation of thiosulfate, sulfide, sulfur and sulfite but not tetrathionate. Advenella kashmirensis, which oxidizes tetrathionate to sulfate, besides forming it as an intermediate during thiosulfate oxidation, possesses a soxCDYZAXOB operon. Knock-out mutations proved that only SoxBCD is involved in A. kashmirensis tetrathionate oxidation, whereas thiosulfate-to-tetrathionate conversion is Sox independent. Expression of two glutathione metabolism-related proteins increased under chemolithotrophic conditions, as compared to the chemoorganotrophic one. Substrate-dependent oxygen consumption pattern of whole cells, and sulfur-oxidizing enzyme activities of cell-free extracts, measured in the presence/absence of thiol inhibitors/glutathione, corroborated glutathione involvement in tetrathionate oxidation. Furthermore, proteome analyses detected a sulfite:acceptor oxidoreductase (SorAB) exclusively under chemolithotrophic conditions, while expression of a methanol dehydrogenase (XoxF) homolog, subsequently named thiol dehydrotransferase (ThdT), was found to increase 3- and 10-fold during thiosulfate-to-tetrathionate conversion and tetrathionate oxidation respectively. A thdT knock-out mutant did not oxidize tetrathionate but converted half of the supplied 40 mM S-thiosulfate to tetrathionate. Knock-out of another thiosulfate dehydrogenase (tsdA) gene proved that both ThdT and TsdA individually converted ∼ 20 mM S-thiosulfate to tetrathionate. The overexpressed and isolated ThdT protein exhibited PQQ-dependent thiosulfate dehydrogenation, whereas its PQQ-independent thiol transfer activity involving tetrathionate and glutathione potentially produced a glutathione:sulfodisulfane adduct and sulfite. SoxBCD and SorAB were hypothesized to oxidize the aforesaid adduct and sulfite respectively.

Elevated levels of glutathionyl haemoglobin as an oxidative stress marker in patients with major depressive disorder.

Background & objectives: Oxidative stress has been implicated in the pathophysiology of major depressive disorder (MDD), but biomarkers to assess oxidative stress in patients with MDD have yielded ambiguous results. Glutathionyl haemoglobin (GS-Hb) has been reported as a stable and potential biomarker for oxidative stress in various clinical conditions. The objective of the study was to evaluate GS-Hb as a potential biomarker of oxidative stress in patients with MDD through its quantification and to compare the levels of GS-Hb in age- and gender-matched healthy controls. Methods: The levels of GS-Hb were estimated using liquid chromatography coupled to electrospray ionization mass spectrometry in patients diagnosed with MDD and in a subset of patients after six weeks of treatment with selective serotonin reuptake inhibitors (SSRIs). Results: GS-Hb levels in drug-naïve patients with MDD (n=26) were significantly elevated compared to matched healthy controls (n=17). GS-Hb levels were not significantly different between MDD patients with and without co-morbid anxiety disorders. There were no significant differences in GS-Hb levels following six weeks of treatment with SSRIs compared to baseline. Interpretation & conclusions: Compared to controls, GS-Hb level in patients with MDD was significantly elevated, suggestive of increased oxidative stress associated with MDD. However, six weeks of antidepressant treatment was not sufficient to modify the alterations in antioxidant/oxidant system. Further studies need to be done with a large sample of MDD patients with a longer duration of antidepressant treatment.

Downregulation of apolipoprotein A-IV in plasma & impaired reverse cholesterol transport in individuals with recent acts of deliberate self-harm.

Background & objectives: The major limiting factor in the prevention of suicide is the limited knowledge on molecular insights in individuals at risk. Identification of peripheral protein markers which can classify individuals at high-risk of suicide might aid in early diagnosis and effective medical intervention. The aim of the present study was, therefore, to analyze the differential regulation of plasma proteins in individuals with deliberate self-harm compared to controls. Methods: Using two-dimensional gel electrophoresis coupled with matrix-assisted laser desorption-ionization mass spectrometry, differentially expressed plasma proteins were identified in study participants with deliberate self-harm compared to age- and gender-matched controls. The finding was validated using mass spectrometry-based isotope-labelled relative quantification and Western blot analysis in a new set of individuals with deliberate self-harm and controls. Results: The plasma proteomic analysis showed that apolipoprotein A-IV (Apo A-IV ) was downregulated by 2.63-fold (confidence interval: 1.52-4.54) in individuals with deliberate self-harm (n=10) compared to matched controls, which was consistent in mass spectrometry-based relative quantification and Western blot analysis performed in an independent set of individuals with deliberate self-harm (n=18). In addition, plasma levels of total cholesterol, esterified cholesterol and high-density lipoprotein (HDL) were observed to be significantly lower individuals with deliberate self-harm compared to controls. Interpretation & conclusions: Apo A-IV, which plays a crucial role in the esterification of free cholesterol, was found to be downregulated with concomitantly decreased levels of HDL, esterified cholesterol and total cholesterol in individuals with deliberate self-harm compared to matched controls. The present findings might provide a link between the differential regulation of plasma proteins and the previously reported results on altered cholesterol levels in individuals with deliberate self-harm.

Ethylenediurea (EDU) mitigates the negative effects of ozone in rice: Insights into its mode of action.

Monitoring of ozone damage to crops plays an increasingly important role for the food security of many developing countries. Ethylenediurea (EDU) could be a tool to assess ozone damage to vegetation on field scale, but its physiological mode of action remains unclear. This study investigated mechanisms underlying the ozone-protection effect of EDU in controlled chamber experiments. Ozone sensitive and tolerant rice genotypes were exposed to ozone (108 ppb, 7 hr day-1 ) and control conditions. EDU alleviated ozone effects on plant morphology, foliar symptoms, lipid peroxidation, and photosynthetic parameters in sensitive genotypes. Transcriptome profiling by RNA sequencing revealed that thousands of genes responded to ozone in a sensitive variety, but almost none responded to EDU. Significant interactions between ozone and EDU application occurred mostly in ozone responsive genes, in which up-regulation was mitigated by EDU application. Further experiments documented ozone degrading properties of EDU, as well as EDU deposits on leaf surfaces possibly related to surface protection. EDU application did not mitigate the reaction of plants to other abiotic stresses, including iron toxicity, zinc deficiency, and salinity. This study provided evidence that EDU is a surface protectant that specifically mitigates ozone stress without interfering directly with the plants' stress response systems.

A novel linkage-disequilibrium corrected genomic relationship matrix for SNP-heritability estimation and genomic prediction.

Single nucleotide polymorphism (SNP)-heritability estimation is an important topic in several research fields, including animal, plant and human genetics, as well as in ecology. Linear mixed model estimation of SNP-heritability uses the structures of genomic relationships between individuals, which is constructed from genome-wide sets of SNP-markers that are generally weighted equally in their contributions. Proposed methods to handle dependence between SNPs include, "thinning" the marker set by linkage disequilibrium (LD)-pruning, the use of haplotype-tagging of SNPs, and LD-weighting of the SNP-contributions. For improved estimation, we propose a new conceptual framework for genomic relationship matrix, in which Mahalanobis distance-based LD-correction is used in a linear mixed model estimation of SNP-heritability. The superiority of the presented method is illustrated and compared to mixed-model analyses using a VanRaden genomic relationship matrix, a matrix used by GCTA and a matrix employing LD-weighting (as implemented in the LDAK software) in simulated (using real human, rice and cattle genotypes) and real (maize, rice and mice) datasets. Despite of the computational difficulties, our results suggest that by using the proposed method one can improve the accuracy of SNP-heritability estimates in datasets with high LD.

Development of new SNP derived cleaved amplified polymorphic sequence marker set and its successful utilization in the genetic analysis of seed color variation in barley.

The aim of the present study was to develop a new cost effective PCR based CAPS marker set using advantages of high-throughput SNP genotyping. Initially, SNP survey was made using 20 diverse barley genotypes via 9k iSelect array genotyping that resulted in 6334 polymorphic SNP markers. Principle component analysis using this marker data showed fine differentiation of barley diverse gene pool. Till this end, we developed 200 SNP derived CAPS markers distributed across the genome covering around 991cM with an average marker density of 5.09cM. Further, we genotyped 68 CAPS markers in an F2 population (Cheri×ICB181160) segregating for seed color variation in barley. Genetic mapping of seed color revealed putative linkage of single nuclear gene on chromosome 1H. These findings showed the proof of concept for the development and utility of a newer cost effective genomic tool kit to analyze broader genetic resources of barley worldwide.

Reparametrization-based estimation of genetic parameters in multi-trait animal model using Integrated Nested Laplace Approximation.

KEY MESSAGE: A novel reparametrization-based INLA approach as a fast alternative to MCMC for the Bayesian estimation of genetic parameters in multivariate animal model is presented. ABSTRACT: Multi-trait genetic parameter estimation is a relevant topic in animal and plant breeding programs because multi-trait analysis can take into account the genetic correlation between different traits and that significantly improves the accuracy of the genetic parameter estimates. Generally, multi-trait analysis is computationally demanding and requires initial estimates of genetic and residual correlations among the traits, while those are difficult to obtain. In this study, we illustrate how to reparametrize covariance matrices of a multivariate animal model/animal models using modified Cholesky decompositions. This reparametrization-based approach is used in the Integrated Nested Laplace Approximation (INLA) methodology to estimate genetic parameters of multivariate animal model. Immediate benefits are: (1) to avoid difficulties of finding good starting values for analysis which can be a problem, for example in Restricted Maximum Likelihood (REML); (2) Bayesian estimation of (co)variance components using INLA is faster to execute than using Markov Chain Monte Carlo (MCMC) especially when realized relationship matrices are dense. The slight drawback is that priors for covariance matrices are assigned for elements of the Cholesky factor but not directly to the covariance matrix elements as in MCMC. Additionally, we illustrate the concordance of the INLA results with the traditional methods like MCMC and REML approaches. We also present results obtained from simulated data sets with replicates and field data in rice.

Mass Spectrometry-Based Diagnosis of Hemoglobinopathies: A Potential Tool for the Screening of Genetic Disorder.

Hemoglobinopathies are caused by point mutation in globin gene that results in structural variant of hemoglobin. While 7 % of world populations are carrier of hemoglobinopathies, the prevalence of the disease varies between 3 to 17 % across different population groups in India. In a diagnostic laboratory, alkaline gel electrophoresis and cation exchange-based HPLC (CE-HPLC) are most widely used techniques for characterization of hemoglobin variants. In the above methods, the differential surface charge of hemoglobin molecule in variants is exploited for their characterization. Sometime, co-migration of variants in gel electrophoresis and co-elution or elution with unknown retention time in automated CE-HPLC might lead to ambiguity in the analysis of hemoglobinopathies. Under such circumstances, it is necessary to use other analytical methods that provide unambiguous results. Mass spectrometry-based proteomics approach and DNA sequence analysis are examples of such alternative methods. In the present study, liquid chromatography coupled to mass spectrometry has been used for three commonly observed variants in India, e.g., HbE, HbQ India and HbD Punjab that appeared with inappropriate results in the conventional analysis. A customized hemoglobin variant database has been used in the mass spectrometry-based analysis of those three variants. Mass spectrometry-based proteomics approach was used to analyze above variant sample accurately.

A genetic map of cassava (Manihot esculenta Crantz) with integrated physical mapping of immunity-related genes.

BACKGROUND: Cassava, Manihot esculenta Crantz, is one of the most important crops world-wide representing the staple security for more than one billion of people. The development of dense genetic and physical maps, as the basis for implementing genetic and molecular approaches to accelerate the rate of genetic gains in breeding program represents a significant challenge. A reference genome sequence for cassava has been made recently available and community efforts are underway for improving its quality. Cassava is threatened by several pathogens, but the mechanisms of defense are far from being understood. Besides, there has been a lack of information about the number of genes related to immunity as well as their distribution and genomic organization in the cassava genome. RESULTS: A high dense genetic map of cassava containing 2,141 SNPs has been constructed. Eighteen linkage groups were resolved with an overall size of 2,571 cM and an average distance of 1.26 cM between markers. More than half of mapped SNPs (57.4%) are located in coding sequences. Physical mapping of scaffolds of cassava whole genome sequence draft using the mapped markers as anchors resulted in the orientation of 687 scaffolds covering 45.6% of the genome. One hundred eighty nine new scaffolds are anchored to the genetic cassava map leading to an extension of the present cassava physical map with 30.7 Mb. Comparative analysis using anchor markers showed strong co-linearity to previously reported cassava genetic and physical maps. In silico based searching for conserved domains allowed the annotation of a repertory of 1,061 cassava genes coding for immunity-related proteins (IRPs). Based on physical map of the corresponding sequencing scaffolds, unambiguous genetic localization was possible for 569 IRPs. CONCLUSIONS: This is the first study reported so far of an integrated high density genetic map using SNPs with integrated genetic and physical localization of newly annotated immunity related genes in cassava. These data build a solid basis for future studies to map and associate markers with single loci or quantitative trait loci for agronomical important traits. The enrichment of the physical map with novel scaffolds is in line with the efforts of the cassava genome sequencing consortium.

Protein Structure-Function Correlation in Living Human Red Blood Cells Probed by Isotope Exchange-based Mass Spectrometry.

To gain insight into the underlying mechanisms of various biological events, it is important to study the structure-function correlation of proteins within cells. Structural probes used in spectroscopic tools to investigate protein conformation are similar across all proteins. Therefore, structural studies are restricted to purified proteins in vitro and these findings are extrapolated in cells to correlate their functions in vivo. However, due to cellular complexity, in vivo and in vitro environments are radically different. Here, we show a novel way to monitor the structural transition of human hemoglobin upon oxygen binding in living red blood cells (RBCs), using hydrogen/deuterium exchange-based mass spectrometry (H/DX-MS). Exploiting permeability of D2O across cell membrane, the isotope exchange of polypeptide backbone amide hydrogens of hemoglobin was carried out inside RBCs and monitored using matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS). To explore the conformational transition associated with oxygenation of hemoglobin in vivo, the isotope exchange kinetics was simplified using the method of initial rates. RBC might be considered as an in vivo system of pure hemoglobin. Thus, as a proof-of-concept, the observed results were correlated with structural transition of hemoglobin associated with its function established in vitro. This is the first report on structural changes of a protein upon ligand binding in its endogenous environment. The proposed method might be applicable to proteins in their native state, irrespective of location, concentration, and size. The present in-cell approach opens a new avenue to unravel a plethora of biological processes like ligand binding, folding, and post-translational modification of proteins in living cells.

Mass spectrometry based characterization of Hb Beckman variant in a falsely elevated HbA(1c) sample.

Glycated hemoglobin (HbA1c) is a 'gold standard' biomarker for assessing the glycemic index of an individual. HbA1c is formed due to nonenzymatic glycosylation at N-terminal valine residue of the ß-globin chain. Cation exchange based high performance liquid chromatography (CE-HPLC) is mostly used to quantify HbA1c in blood sample. A few genetic variants of hemoglobin and post-translationally modified variants of hemoglobin interfere with CE-HPLC-based quantification, resulting in its false positive estimation. Using mass spectrometry, we analyzed a blood sample with abnormally high HbA1c (52.1%) in the CE-HPLC method. The observed HbA1c did not corroborate the blood glucose level of the patient. A mass spectrometry based bottom up proteomics approach, intact globin chain mass analysis, and chemical modification of the proteolytic peptides identified the presence of Hb Beckman, a genetic variant of hemoglobin, in the experimental sample. A similar surface area to charge ratio between HbA1c and Hb Beckman might have resulted in the coelution of the variant with HbA1c in CE-HPLC. Therefore, in the screening of diabetes mellitus through the estimation of HbA1c, it is important to look for genetic variants of hemoglobin in samples that show abnormally high glycemic index, and HbA1c must be estimated using an alternative method.

Automated analysis of hemoglobin variants using nanoLC-MS and customized databases.

Unambiguous analysis of hemoglobin variants is critical in the diagnosis of hemoglobinopathies. In diagnostic laboratories, alkaline gel electrophoresis and automated HPLC are used in identifying variants. In specific instances, comigration of hemoglobin variant bands in gel and coelution of different variants or elution of variants with unmatched library information in HPLC can result in ambiguities in interpretation. Hemoglobin variants mostly arise from point mutations leading to very high sequence homology between normal and variant hemoglobin. In addition, unavailability of a variant database compatible with proteomics data analysis software makes mass spectrometry based variant analysis very challenging. In the present study, we standardized a nanoLC-MS based method for variant analysis to achieve substantially high sequence coverage. We developed three hemoglobin variant databases, specific to three different proteolytic enzymes, compatible with proteomics search engine software. The above nanoLC-MS method and the compatibility of the customized databases were validated by analysis of a sickle hemoglobin variant. Six other hemoglobin variants were characterized wherein diagnosis reports based on conventional tools were ambiguous. The novelty of our method lies in its simplicity and accuracy of the analysis with minimal manual intervention. The presently described method may be used in the future for the routine hemoglobin variant diagnosis.

NeuralLasso: Neural Networks Meet Lasso in Genomic Prediction.

Prediction of complex traits based on genome-wide marker information is of central importance for both animal and plant breeding. Numerous models have been proposed for the prediction of complex traits and still considerable effort has been given to improve the prediction accuracy of these models, because various genetics factors like additive, dominance and epistasis effects can influence of the prediction accuracy of such models. Recently machine learning (ML) methods have been widely applied for prediction in both animal and plant breeding programs. In this study, we propose a new algorithm for genomic prediction which is based on neural networks, but incorporates classical elements of LASSO. Our new method is able to account for the local epistasis (higher order interaction between the neighboring markers) in the prediction. We compare the prediction accuracy of our new method with the most commonly used prediction methods, such as BayesA, BayesB, Bayesian Lasso (BL), genomic BLUP and Elastic Net (EN) using the heterogenous stock mouse and rice field data sets.

Transcriptome profiling of barley and tomato shoot and root meristems unravels physiological variations underlying photoperiodic sensitivity.

The average sowing date of crops in temperate climate zones has been shifted forwards by several days, resulting in a changed photoperiod regime at the emergence stage. In the present study, we performed a global transcriptome profiling of plant development genes in the seedling stage of root and shoot apical meristems of a photoperiod-sensitive species (barley) and a photoperiod insensitive species (tomato) in short-day conditions (8h). Variant expression indicated differences in physiological development under this short day-length regime between species and tissues. The barley tissue transcriptome revealed reduced differentiation compared to tomato. In addition, decreased photosynthetic activity was observed in barley transcriptome and leaf chlorophyll content under 8h conditions, indicating a slower physiological development of shoot meristems than in tomatoes. The photomorphogenesis controlling cryptochrome gene cry1, with an effect on physiological differentiation, showed an underexpression in barley compared to tomato shoot meristems. This might lead to a cascade of suspended sink-source activities, which ultimately delay organ development and differentiation in barley shoot meristems under short photoperiods.

Analysis of hemoglobin variants using nondenaturing gel electrophoresis and matrix-assisted laser desorption ionization mass spectrometry.

Molecular analysis of hemoglobin variants is crucial in the diagnosis of hemoglobinopathies. Routinely used techniques for identifying variants include alkaline gel electrophoresis and automated HPLC. Sometimes comigration of variants in electrophoresis or coelution in HPLC provides ambiguous results. Due to high sequence homology between normal and variant hemoglobin, proteomic analysis using LC/ESI-MS data is also challenging. Here we describe a novel method wherein alkaline gel electrophoresis and MALDI-MS were used in combination to characterize variant samples such as Hb FSD and Hb D-Iran unambiguously. The method is rapid, efficient, and cost effective. In the future, it can be applied as a diagnostic tool.

Genomic regions associated with physiological, biochemical and yield-related responses under water deficit in diploid potato at the tuber initiation stage revealed by GWAS.

Water deficit, which is increasing with climate change, is a serious threat to agricultural sustainability worldwide. Dissection of the genetic architecture of water deficit responses is highly desirable for developing water-deficit tolerant potato cultivars and enhancing the resilience of existing cultivars. This study examined genetic variation in response to water deficit in a panel of diploid potato and identified the QTL governing this trait via a genome-wide association study (GWAS). A panel of 104 diploid potato accessions were evaluated under both well-watered and water deficit treatments at tuber initiation stage. Drought stress index (DTI) was calculated to assess tolerance of the diploid potato genotypes to water deficit. The GWAS was conducted using a matrix of 47K single nucleotide polymorphisms (SNP), recently available for this population. We are reporting 38 QTL, seven for well-watered conditions, twenty-two for water deficit conditions and nine for DTI which explain between 12.6% and 44.1% of the phenotypic variance. A set of 6 QTL were found to be associated with more than one variable. Marker WDP-9.21 was found associated with tuber fresh weigh under WD and gene annotation analysis revealed co-localization with the Glucan/water dikinase (GWD) gene. Of the nine QTL detected from DTI on chromosomes 2,3,5,8,10 and 12, three candidate genes with a feasible role in water deficit response were identified. The findings of this study can be used in marker-assisted selection (MAS) for water- deficit tolerance breeding in potato.