Analysis and review of techniques and tools based on machine learning and deep learning for prediction of lysine malonylation sites in protein sequences

The post-translational modifications occur as crucial molecular regulatory mechanisms utilized to regulate diverse cellular processes. Malonylation of proteins, a reversible post-translational modification of lysine/k residues, is linked to a variety of biological functions, such as cellular regulation and pathogenesis. This modification plays a crucial role in metabolic pathways, mitochondrial functions, fatty acid oxidation and other life processes. However, accurately identifying malonylation sites is crucial to understand the molecular mechanism of malonylation, and the experimental identification can be a challenging and costly task. Recently, approaches based on machine learning (ML) have been suggested to address this issue. It has been demonstrated that these procedures improve accuracy while lowering costs and time constraints. However, these approaches also have specific shortcomings, including inappropriate feature extraction out of protein sequences, high-dimensional features and inefficient underlying classifiers. As a result, there is an urgent need for effective predictors and calculation methods. In this study, we provide a comprehensive analysis and review of existing prediction models, tools and benchmark datasets for predicting malonylation sites in protein sequences followed by a comparison study. The review consists of the specifications of benchmark datasets, explanation of features and encoding methods, descriptions of the predictions approaches and their embedding ML or deep learning models and the description and comparison of the existing tools in this domain. To evaluate and compare the prediction capability of the tools, a new bunch of data has been extracted based on the most updated database and the tools have been assessed based on the extracted data. Finally, a hybrid architecture consisting of several classifiers including classical ML models and a deep learning model has been proposed to ensemble the prediction results. This approach demonstrates the better performance in comparison with all prediction tools included in this study (the source codes of the models presented in this manuscript are available in https://github.com/Malonylation). Database URL: https://github.com/A-Golshan/Malonylation.

A new solid phase extraction sorbent developed based on cyanopropyl functionalized silica nanoparticles for organophosphorus pesticides determination

In this work, a simple sol-gel approach was used for the preparation of cyanopropyl (CNPr) functionalized silica nanoparticles (SiO2-CNPr) that tetraethoxysilane (TEOS) and cyanopropyltriethoxysilane (CNPrTEOS) used as precursors. This as-prepared SiO2-CNPr nanoparticle sorbent was first characterized using FESEM, EDX, FTIR, TGA, and BET techniques. Then, the SiO2-CNPr nanoparticle was applied as a new SPE sorbent for determining trace levels of OPPs in environmental water samples. To enhance the simultaneous extraction of non-polar or/and polar OPPs and to obtain the most efficient sorbent, several sol-gel synthesis parameters were studied. In addition, the effect of several effective parameters on SPE performance was investigated toward simultaneous extraction of non-polar or/and polar OPPs. Moreover, the figures of merit such as precision, linearity, LOQ, LOD, and recovery were evaluated for the sorbent. Finally, the designed SiO2-CNPr SPE was used to determine OPPs in real water samples, and its extraction performance was compared to commercial cartridges based on cyanopropyl.

MiR-548c-3p through suppressing Tyms and Abcg2 increases the sensitivity of colorectal cancer cells to 5-fluorouracil

Background

Colorectal cancer, is one of most prevalent the cancer in the world. 5-Fluorouracil is a standard chemotherapeutic drug while the acquisition of resistance to 5-Fluorouracil is one of the problems during treatment. In this study, we aimed to find the miRNAs that modulate the expression of Tyms and Abcg2 as resistance-inducing genes in the resistant cell lines to 5-Fluorouracil.

Methods

5-Fluorouracil-resistant HCT116 and SW480 cell lines were generated by consecutive treatment of cells with 5-Fluorouracil. This resistance induction was validated by MTT assays. The expression of the Tyms and Abcg2 gene and miR-548c-3p were studied by quantitative real-time PCR in the cell lines.

Results

We hypothesized that miR-548c-3p is targeting Tyms and Abcg2 simultaneously. Increased expression Tyms gene in the two most resistant cell lines derived from HCT116 and all resistant cell lines derived from SW480 except one were seen. Increased expression of Abcg2 was observed in the most resistant HCT116-derived cell line and all resistant cell lines, derived from SW480. In all resistant cell lines, the expression of miR-548c-3p was decreased.

Conclusion

It can be concluded downregulation of miR548c-3p is in line with Tyms and Abcg2 overexpression in resistant cell lines to 5-Fluorouracil.

Evaluation of rheological and optical properties plus stability of beverage cloud emulsions prepared with corn oil, gum rosin, and modified starch

Rheological and optical properties as well as stability of beverage cloud emulsion prepared with corn oil, gum rosin (EG), and modified starch were evaluated in model juices. The emulsions were prepared with three levels of modified starch (6%, 12%, and 18% w/w), corn oil (5%, 7%, and 9% w/w), and gum rosin (1%, 3%, and 5% w/w). Experiments were designed using the Box-Behnken design. The analysis of variance (ANOVA) was used to evaluate the significance of the experimental factors and the factors were then optimized using response surface methodology (RSM). The stability of emulsions was measured through ring formation in both the primary emulsion and the model beverage as a function of storage time. Also, the effect of heat treatment was examined on the stability of emulsions in model beverages. The results revealed that heat treatment did not cause the formation of an observable ring in the model juice containing stabilized starch emulsion. Rheological examinations of the stable emulsion samples showed a pseudoplastic and time-independent non-Newtonian behavior. The optimum emulsion sample consistency coefficient was 0.46 Pa.sn and the flow behavior index was 0.88. The apparent viscosity of the optimum emulsion sample based on Herschel-Bulkley model at shear rate of 100 s-1 was 0.0439 Pa.s. The results indicated that the concentration of modified starch, gum rosin, and corn oil has a significant effect on the stability and creaminess of the emulsion. In general, with an increase in the percentage of modified starch, the stability rises while the rate of creaminess decreases (p < 0.05). Furthermore, elevation of the concentration of corn oil had a significant effect on the opacity of emulsions and the final product (p < 0.05).

Molecular profiling of bacterial blight resistance in Malaysian rice cultivars

Bacteria blight is one of the most serious bacterial diseases of rice worldwide. The identification of genetic potential against bacterial blight in the existing rice resources is a prerequisite to develop multigenic resistance to combat the threat of climate change. This investigation was conducted to evaluate alleles variation in 38 Malaysian cultivars using thirteen Simple Sequences Repeats markers and one Sequence Tagged Sites (STS) marker which were reported to be linked with the resistance to bacterial blight. Based on molecular data, a dendrogram was constructed which classified the rice cultivars into seven major clusters at 0.0, 0.28 and 0.3 of similarity coefficient. Cluster 5 was the largest group comprised of ten rice cultivars where multiple genes were identified. However, xa13 could not be detected in the current rice germplasm, whereas xa2 was detected in 25 cultivars. Molecular analysis revealed that Malaysian rice cultivars possess multigenic resistance.

Omental torsion mimicking acute appendicitis in a 7-year-old boy: a case report

Background

Torsion of the greater omentum is an uncommon cause of acute abdominal pain. Omental torsion can be divided into primary and secondary. Owing to its nonspecific abdominal pain, preoperative diagnosis is difficult. Ultrasound sonography and abdominal computed tomography scans do not have a major role in preoperative diagnosis. The definite diagnosis is usually made during operation.

Case presentation

A 7-year-old Persian boy was referred with right lower quadrant pain associated with nausea and vomiting. Laboratory blood tests and urinalysis were requested that revealed normal values. Ultrasonography was performed, revealing inflammatory changes with mild free fluid collection in the interloop. The patient underwent an open appendectomy, confirming a normal appendix with omental torsion. Two days later, he was discharged home without postoperative complications.

Conclusions

In patients with acute abdomen, particularly those with acute appendicitis symptoms, omental torsion should be considered in the differential diagnosis.

Olfactory dysfunction is associated with motor function only in tremor-dominant Parkinson's disease

BACKGROUND

The prevalence of olfactory impairment in patients with Parkinson's disease (PD) is 50-90%, and therefore, olfactory dysfunction is one of the most prevalent non-motor symptoms (NMSs) in patients with PD. Numerous studies have evaluated the association between motor and non-motor symptoms and olfactory dysfunction in PD.

AIM

In this study, we investigated the relationship between olfactory dysfunction, which is measured using the UPSIT test, with other motor and non-motor symptoms separately in three motor subtypes of PD, including tremor dominant (TD), postural instability and gait difficulty (PIGD), and indeterminate and healthy subjects.

METHODS

We recruited 487 early-stage PD patients (43 PIGD, 406 TD, and 38 indeterminate) and healthy controls (HCs) (n = 197) from the Parkinson Progression Markers Initiative (PPMI). All participants completed motor and non-motor tests at baseline visit and after 4 years of follow-up. Subjects underwent common PD scaling tests.

RESULTS

Olfactory dysfunction was significantly correlated with declined motor functions only in the TD subtype. Also, significant correlations were noticed between olfactory dysfunction and speed-attention processing and executive function in the HCs as well. Finally, no significant or meaningful association was observed in the PIGD and indeterminate subtype. Anosmia and hyposmia subjects in the TD group had the worse motor and non-motor scores compared to normosmia subjects after 4 years.

CONCLUSION

Olfactory dysfunction was significantly correlated with declined motor functions in the TD subtype. This is indicating that olfactory dysfunction may be an early motor and non-motor biomarker only in the TD subtype. However, it is possible that the involvement of olfactory function in other subtypes is not strong enough to make it a useful marker of diseases progression.

A review on antimicrobial peptides databases and the computational tools

Antimicrobial Peptides (AMPs) have been considered as potential alternatives for infection therapeutics since antibiotic resistance has been raised as a global problem. The AMPs are a group of natural peptides that play a crucial role in the immune system in various organisms AMPs have features such as a short length and efficiency against microbes. Importantly, they have represented low toxicity in mammals which makes them potential candidates for peptide-based drugs. Nevertheless, the discovery of AMPs is accompanied by several issues which are associated with labour-intensive and time-consuming wet-lab experiments. During the last decades, numerous studies have been conducted on the investigation of AMPs, either natural or synthetic type, and relevant data are recently available in many databases. Through the advancement of computational methods, a great number of AMP data are obtained from publicly accessible databanks, which are valuable resources for mining patterns to design new models for AMP prediction. However, due to the current flaws in assessing computational methods, more interrogations are warranted for accurate evaluation/analysis. Considering the diversity of AMPs and newly reported ones, an improvement in Machine Learning algorithms are crucial. In this review, we aim to provide valuable information about different types of AMPs, their mechanism of action and a landscape of current databases and computational tools as resources to collect AMPs and beneficial tools for the prediction and design of a computational model for new active AMPs.

Efficacy and safety of favipiravir plus interferon-beta versus lopinavir/ritonavir plus interferon-beta in moderately ill patients with COVID-19: A randomized clinical trial

Favipiravir (FVP), lopinavir/ritonavir (LPV/RTV), and interferon‐beta (INF‐beta) are considered as potential treatments for COVID‐19. We examined the efficacy and safety of FVP and INF‐beta compared to LPV/RTV and INF‐beta combinations for the treatment of SARS‐CoV‐2. It was a single‐center randomized clinical trial. Eligible patients were randomized to receive FVP plus INF‐beta versus LPV/RTV plus INF‐beta. The primary endpoint was the viral clearance after seven days of randomization. ICU admission, length of stay (LOS) in hospital, in‐hospital mortality, and the incidence of adverse events were also measured. This trial was registered on the Iranian Registry of Clinical Trials (IRCT20200506047323N3). Patients were randomly allocated to the FVP (n = 33) and LPV/RTV (n = 33) groups. The viral clearance on Day seven was not significantly different between the FVP (31.1%) and the LPV/RTV groups (16.1%). The rate of ICU admission and likewise the in‐hospital mortality in the FVP group (12.5% and 6.3%, respectively) were similar to the LPV/RTV groups (19.4% and 19.4%, respectively). The median LOS in the hospital was also not different (6.8 days [interquartile range; IQR = 5.0–11.0] in the FVP and (8.0 days [IQR = 5.5–12.5]) in LPV/RTV groups (p = 0.140). Adverse events were observed in 25.0% of FVP and 32.3% of LPV/RTV groups. The combination therapy with FVP did not exert a higher efficacy compared to the combination regimen of LPV/RTV. However, both treatment regimens demonstrated a mild profile of adverse events.

Late presentation of congenital type IV esophageal hiatus hernia in a 9-year-old boy: a case report

Background

Congenital diaphragmatic hernia affects 1 in every 2000–5000 live births. The mediastinum shifts to the opposite side, the lungs are hypoplastic, and the arterioles are abnormal, resulting in pulmonary hypertension. Respiratory and cardiovascular functions are severely impaired at birth, resulting in significant mortality and morbidity as a result of the associated malformations.

Case presentation

A 9-year-old persian boy was referred with complaint of intermittent abdominal pain in the left lower quadrant and an episode of vomiting. The patient was tachypneic, and the abdomen was nontender on examination. Lung sounds on the left side were considerably decreased, whereas heart sounds on the right side were louder. There was no history of underlying disease in the patient. Initial laboratory blood tests, chest x-ray, spiral computed tomography scan, and chest sonography were requested. Blood tests were normal, and chest x-ray revealed a round-shaped lesion with relatively clear boundaries containing air–fluid level and shift of the heart and mediastinum to the right. A spiral computed tomography scan of the lungs demonstrated the shift of the heart and mediastinum to the right side was due to dilated stomach and colon pressure, and chest sonography revealed that half of the stomach was inside the thorax. Laparotomy surgery was performed. The patient had no complications following surgery.

Conclusions

Herniation of abdominal contents through the diaphragmatic hiatus should be suspected in patients with tachypnea and mediastinal shift to the right side. Rapid diagnosis and early surgical treatment are necessary to avert any potentially life-threatening complications.

Predicting protein phosphorylation sites in soybean using interpretable deep tabular learning network

Phosphorylation of proteins is one of the most significant post-translational modifications (PTMs) and plays a crucial role in plant functionality due to its impact on signaling, gene expression, enzyme kinetics, protein stability and interactions. Accurate prediction of plant phosphorylation sites (p-sites) is vital as abnormal regulation of phosphorylation usually leads to plant diseases. However, current experimental methods for PTM prediction suffers from high-computational cost and are error-prone. The present study develops machine learning-based prediction techniques, including a high-performance interpretable deep tabular learning network (TabNet) to improve the prediction of protein p-sites in soybean. Moreover, we use a hybrid feature set of sequential-based features, physicochemical properties and position-specific scoring matrices to predict serine (Ser/S), threonine (Thr/T) and tyrosine (Tyr/Y) p-sites in soybean for the first time. The experimentally verified p-sites data of soybean proteins are collected from the eukaryotic phosphorylation sites database and database post-translational modification. We then remove the redundant set of positive and negative samples by dropping protein sequences with >40% similarity. It is found that the developed techniques perform >70% in terms of accuracy. The results demonstrate that the TabNet model is the best performing classifier using hybrid features and with window size of 13, resulted in 78.96 and 77.24% sensitivity and specificity, respectively. The results indicate that the TabNet method has advantages in terms of high-performance and interpretability. The proposed technique can automatically analyze the data without any measurement errors and any human intervention. Furthermore, it can be used to predict putative protein p-sites in plants effectively. The collected dataset and source code are publicly deposited at https://github.com/Elham-khalili/Soybean-P-sites-Prediction.

P-tau231 as a Diagnostic Biomarker for Alzheimer's Disease and Mild Cognitive Impairment: A Systematic Review and Meta-Analysis

Objective

Some previous studies have shown that cerebrospinal fluid (CSF) levels of p-tau231 were significantly higher in patients with Alzheimer's disease (AD) compared to that in patients with mild cognitive impairment (MCI) and normal control (NC), whereas some other studies did not. Due to contradictory results, we aimed to conduct a systematic review and meta-analysis study on previous investigations to examine the potential role of CSF p-tau231 as a biomarker of AD and MCI.

Method

PubMed, Scopus, and Web of Science were searched in March 2021 for studies on the CSF level of p-tau231 in AD, MCI, and NC. The statistical analysis was performed via standardized mean difference (SMD) methodology with a 95% confidence interval.

Results

A total of 10 studies including 1141 subjects were included. The present study showed that CSF level of p-tau231 was significantly higher in AD patients compared to that in MCI patients (SMD = 160.94 [11.11, 310.78], P = 0.04) and NC patients (SMD = 436.21 [164.88, 707.54], P < 0.00). Moreover, comparison of MCI and NC showed a significantly higher level of CSF p-tau231 in MCI compared to NC (SMD = 341.44 [59.73, 623.14], P = 0.02).

Conclusion

P-tau231 showed to be a valuable biomarker of discrimination AD, MCI, and NC based on our findings. This meta-analysis showed that the CSF p-tau231 can reliably differentiate AD patients from MCI and NC patients. Furthermore, based on our findings the level of CSF p-tau231 was significantly higher in MCI compared to NC. Therefore, p-tau231 can be added to the list of potential biomarkers for the diagnosis of AD and MCI in further studies. However, further investigations are needed to confirm our findings.

Era-like GTP protein gene expression in rice

The mutations are genetic changes in the genome sequences and have a significant role in biotechnology, genetics, and molecular biology even to find out the genome sequences of a cell DNA along with the viral RNA sequencing. The mutations are the alterations in DNA that may be natural or spontaneous and induced due to biochemical reactions or radiations which damage cell DNA. There is another cause of mutations which is known as transposons or jumping genes which can change their position in the genome during meiosis or DNA replication. The transposable elements can induce by self in the genome due to cellular and molecular mechanisms including hypermutation which caused the localization of transposable elements to move within the genome. The use of induced mutations for studying the mutagenesis in crop plants is very common as well as a promising method for screening crop plants with new and enhanced traits for the improvement of yield and production. The utilization of insertional mutations through transposons or jumping genes usually generates stable mutant alleles which are mostly tagged for the presence or absence of jumping genes or transposable elements. The transposable elements may be used for the identification of mutated genes in crop plants and even for the stable insertion of transposable elements in mutated crop plants. The guanine nucleotide-binding (GTP) proteins have an important role in inducing tolerance in rice plants to combat abiotic stress conditions.

Machine Learning Techniques for Soybean Charcoal Rot Disease Prediction

Early prediction of pathogen infestation is a key factor to reduce the disease spread in plants. Macrophomina phaseolina (Tassi) Goid, as one of the main causes of charcoal rot disease, suppresses the plant productivity significantly. Charcoal rot disease is one of the most severe threats to soybean productivity. Prediction of this disease in soybeans is very tedious and non-practical using traditional approaches. Machine learning (ML) techniques have recently gained substantial traction across numerous domains. ML methods can be applied to detect plant diseases, prior to the full appearance of symptoms. In this paper, several ML techniques were developed and examined for prediction of charcoal rot disease in soybean for a cohort of 2,000 healthy and infected plants. A hybrid set of physiological and morphological features were suggested as inputs to the ML models. All developed ML models were performed better than 90% in terms of accuracy. Gradient Tree Boosting (GBT) was the best performing classifier which obtained 96.25% and 97.33% in terms of sensitivity and specificity. Our findings supported the applicability of ML especially GBT for charcoal rot disease prediction in a real environment. Moreover, our analysis demonstrated the importance of including physiological featured in the learning. The collected dataset and source code can be found in https://github.com/Elham-khalili/Soybean-Charcoal-Rot-Disease-Prediction-Dataset-code.

Four novel ARSA gene mutations with pathogenic impacts on metachromatic leukodystrophy: a bioinformatics approach to predict pathogenic mutations

Metachromatic leukodystrophy (MLD) disorder is a rare lysosomal storage disorder that leads to severe neurological symptoms and an early death. MLD occurs due to the deficiency of enzyme arylsulfatase A (ARSA) in leukocytes, and patients with MLD excrete sulfatide in their urine. In this study, the ARSA gene in 12 non-consanguineous MLD patients and 40 healthy individuals was examined using polymerase chain reaction sequencing. Furthermore, the structural and functional effects of new mutations on ARSA were analyzed using SIFT (sorting intolerant from tolerant), I-Mutant 2, and PolyPhen bioinformatics software. Here, 4 new pathogenic homozygous mutations c.585G>T, c.661T>A, c.849C>G, and c.911A>G were detected. The consequence of this study has extended the genotypic spectrum of MLD patients, paving way to a more effective method for carrier detection and genetic counseling.

Parasitic infection in various stages life of cultured Acipenser persicus

The present study was conducted to evaluate the status of the parasite fauna in Acipenser persicus at different development stages, in order to find prevention protocols for parasitic diseases in this valuable species. For this purpose, sampling from each sex breeder, 10 egg samples, 5-day-old larvae (n = 20), 20-day-old larvae (n = 80) and fingerling of A. persicus (n = 60) released in earthen ponds were done. After the bioassay and preparing wet mount from the internal and external organs, identification was done according to the keys. According to the results, no fauna parasites were isolated from egg samples and 5-day-old larvae; but Trichodina spp. was isolated from 20-day-old larvae. Also, the same protozoan was isolated from fingerling released in earthen ponds, the mean intensity, prevalence and range of contamination by fingerling were higher with compared to 20-day-old larvae. Trichodina sp. and Diplostomum spathaceum were isolated from skin and eyes of females, respectively. However, Trichodina sp. and Ichthyophthirius multifiliis were isolated from skin of male breeders. In this study, no parasites were isolated from internal organs of larves and fingerling but four intestinal parasites included: Cucullanus sphaerocephlaus, Anisakis sp., Skyrjabinopsilus semiarmatus, and Lepto-rhynchoides plagicephalu were isolated from internal organs of breeder. Based on a wide range of parasitic infection observed in various life stages of A. persicus, it seems necessary to consider hygienic and management measures.

Association of genetic variations in the mitochondrial D-loop with β-thalassemia

Beta-thalassemia, one of the most common single-gene disorders, is the result of reduced or absent production of β-globin chains. Patients with β-thalassemia show weak genotype-phenotype correlations. Mitochondrial DNA polymorphisms are a potential source for different physiological and pathological characteristics and have been found to be associated as genetic modifiers with various pathophysiologies, including cancers and neurodegenerative diseases. A group of 35 patients with β-thalassemia was investigated for the presence of mtDNA D-loop polymorphisms in comparison with 504 normal controls. We found four mtDNA D-loop polymorphisms at nucleotides 16,069C > T, 16,189T > C, 16,319G > A, and 16,519T > C that showed significant differences between patients and normal subjects. There is no strong proof for the association of these polymorphisms with β-thalassemia. It is hypothesized that iron overload or its effects on sequestration of calcium or zinc can lead to oxidative stress and ROS production inside the mitochondria. Therefore, possible accompanying of mtDNA polymorphisms with β-thalassemia disease may complicate the genotype-phenotype correlation and could affect the clinical outcomes in the patients.

A newly identified c.1824_1828dupATACG mutation in exon 13 of the GAA gene in infantile-onset glycogen storage disease type II (Pompe disease)

Pompe disease or glycogen storage disease type II is a glycogen storage disorder associated with malfunction of the acid α-glucosidase enzyme (GAA; EC.3.2.1.3) leading to intracellular aggregations of glycogenin muscles. The infantile-onset type is the most life-threatening form of this disease, in which most of patients suffer from cardiomyopathy and hypotonia in early infancy. In this study, a typical case of Pompe disease was reported in an Iranian patient using molecular analysis of the GAA gene. Our results revealed a new c.1824_1828dupATACG mutation in exon 13 of the GAA gene. In conclusion, with the finding of this novel mutation, the genotypic spectrum of Iranian patients with Pompe disease has been extended, facilitating the definition of disease-related mutations.

Molecular and clinical investigation of Iranian patients with Friedreich ataxia

BACKGROUND

Friedreich ataxia (FRDA) is an autosomal recessive disorder caused by guanine-adenine-adenine (GAA) triplet expansions in the FXN gene. Its product, frataxin, which severely reduces in FRDA patients, leads to oxidative damage in mitochondria. The purpose of this study was to evaluate the triple nucleotide repeated expansions in Iranian FRDA patients and to elucidate distinguishable FRDA clinical differences in these patients.

METHODS

A number of 22 Iranian patients (8 females and 14 males) from 16 unrelated families were studied. DNA was extracted from the peripheral blood of patients. The frequency and length of (GAA)n repeats in intron 1 of the FXN gene were analyzed using long-range PCR. In this study, the clinical criteria of FRDA in our patients and the variability in their clinical signs were also demonstrated.

RESULTS

An inverse relationship was observed between GAA repeat size and the age of onset. Although some distinguishable clinical features (such as limb ataxia and lower limb areflexia) were found in our patients, 90-95% of them had extensor plantar response and dysarthria. The results showed only one positive diabetes patient and also different effects on eye movement abnormality among our patients.

CONCLUSION

The onset age of symptoms showed a significant inverse correlation with allele size in our patients (P>0.05). Based on comparisons of the clinical data of all patients, clinical presentation of FRDA in Iranian patients did not differ significantly from other FRDA patients previously reported.

Beta-Thalassemia in Iran: new insight into the role of genetic admixture and migration

Iran with an area of 1.648 million km² is located between the Caspian Sea and the Persian Gulf. The Iranian population consists of multiethnic groups that have been influenced by various invasions and migration throughout history. Studies have revealed the presence of more than 47 different β-globin gene mutations responsible for β-Thalassemia in Iran. This paper is an attempt to study the origin of β-Thalassemia mutations in different parts of Iran. Distribution of β-Thalassemia mutations in Iran shows different patterns in different areas. β-Thalassemia mutations have been a reflection of people and area in correlation with migration and origin of ancestors. We compared the frequencies of β-globin mutations in different regions of Iran with those derived from neighboring countries. The analysis provided evidence of complementary information about the genetic admixture and migration of some mutations, as well as the remarkable genetic classification of the Iranian people and ethnic groups.

Biological control of rice brown spot with native isolates of three Trichoderma species

Brown spot caused by Bipolaris oryzae is an important rice disease in Southern coast of Caspian Sea, the major rice growing region in Iran. A total of 45 Trichoderma isolates were obtained from rice paddy fields in Golestan and Mazandaran provinces which belonged to Trichoderma harzianum, T. virens and T. atroviride species. Initially, they were screened against B. oryzae by antagonism tests including dual culture, volatile and nonvolatile metabolites and hyperparasitism. Results showed that Trichoderma isolates can significantly inhibit mycelium growth of pathogen in vitro by producing volatile and nonvolatile metabolites Light microscopic observations showed no evidence of mycoparasitic behaviour of the tested isolates of Trichoderma spp. such as coiling around the B. oryzae. According to in vitro experiments, Trichoderma isolates were selected in order to evaluate their efficacy in controlling brown spot in glasshouse using seed treatment and foliar spray methods. Concerning the glasshouse tests, two strains of T. harzianum significantly controlled the disease and one strain of T. atroviride increased the seedling growth. It is the first time that the biological control of rice brown spot and increase of seedling growth with Trichoderma species have been studied in Iran.