Biology subjects

Banaei-Moghaddam, A. M.

Publications and source records attributed to Banaei-Moghaddam, A. M..

4 recordsLinked to original sources

bioRxiv2022

Sturgeons: An Evolutionary Insight to The α-globin Protein Speciation and Diversification

Sturgeons are living fossils and among the oldest surviving vertebrate species, and Caspian Sea is habitat of the vast majority of sturgeon species. It is tempting to assume that speciation of sturgeons occurred in response to the severe environmental changes during the formation of Caspian Sea from the ancient Paratethys Sea. Hemoglobin (Hb) reflects the evolutionary history of fishes. Changes in the Hb sequences will affect the protein structure and consequently the vital function of oxygen delivery. As complete sequence data for any sturgeon hemoglobin gene or protein was hitherto not available, we determined the complete gene and protein sequences of an -globin chain (as one of the constituents of Hb complex) from six Caspian Sea sturgeons of different species and compared these sequences mutually and with all available fish -globin sequences. The phylogenetic analyses based on alpha globin sequences can highlight the essentiality of proper changes in globin chains in the speciation process. Estimating the divergence time of -globin genes for different fish families discloses important facts about the rate of evolution and decodes. The results support the hypothesis of simultaneity between the time of morphological speciation of fish families and their -globin divergence. The correlation and concurrency between morphological and molecular changes can be interpreted as a sign of struggling to acquire more fitness to changing environment.

evolutionary biology↗

bioRxiv2022

Comparative Transcriptome Analysis of Hypocotyls During the Developmental Transition of C3 cotyledons to C4 Leaves in Halimocnemis mollissima: Exploring Root-Shoot Signalings Involved in the Establishing of C4 traits

Identification of signaling pathways that control C4 photosynthesis development is essential for introducing the C4 pathway into C3 crops. Species with dual photosynthesis in their life cycle are interesting models to study such regulatory mechanisms. The species used here Halimocnemis mollissima Bunge, belonging to the Caroxyleae tribe, displays C3 photosynthesis in its cotyledons and a NAD-ME subtype of C4 photosynthesis in the First leaves (FLs) onwards. We explored the long-distance signaling pathways that are probably implicated in the shoot-root coordination associated with the manifestation of the C4 traits, including efficient resource usage by comparing the mRNA content of hypocotyls before and after the C4 first leaves formation. Histological examination showed the presence of C3 anatomy in cotyledons and C4 anatomy in the FLs. Our transcriptome analyses verified the performance of the NAD-ME subtype of C4 in FLs and revealed differential transcript abundance of several potential mobile regulators and their associated receptors or transporters in two developmentally different hypocotyls of H. mollissima Bunge. These differentially expressed genes (DEGs) belong to diverse functional groups, including various transcription factor (TF) families, phytohormones metabolism, and signaling peptides, part of which could be related to hypocotyl development. Our findings support the higher nitrogen and water use efficiency associated with C4 photosynthetic and provide insights into the coordinated above- and under-ground tissue communication during the developmental transition of C3 to C4 photosynthesis in this species.

plant biology↗

bioRxiv2022

Computational modeling of the evolutionary transition from C3 to C4 photosynthesis

C4 photosynthesis is an evolutionary adaptation that minimizes the adverse effects of the high photorespiration rate. Although it is widely accepted that the C4 plants are evolved from C3 ancestors, the knowledge about the details of this process is yet to be complete. One application of constraint-based metabolic network modeling is to simulate evolutionary trajectories that an organism endures under a certain selective pressure. However, this approach is barely used to predict the evolution of a complex trait in eukaryotes. Here, we utilized a genetic algorithm combined with a constraint-based metabolic network model of Arabidopsis thaliana to simulate the trajectories of C3 to C4 conversion under high photorespiration rate conditions combined with different environmental conditions. Our modeling predicted that the C3-C4 intermediates and C4 strategies are superior to C3 photosynthesis in these environmental conditions. Besides, resource scarcities drive different evolutionary trajectories toward the emergence of C4 photosynthesis. AUTHOR SUMMARYIt is estimated that high photorespiration reduces C3 crops productivity up to 50% [1]. Carbon concentrating mechanisms have evolved in many plants to overcome adverse effects of high photorespiration rate in especial environments. C4 photosynthesis is one of these adaptations that separate carbon assimilation reactions spatially between mesophyll and bundle sheath cells of the leaves. It is reported that C4 photosynthesis is evolved more than 65 times in 19 different families of angiosperms independently from C3 ancestors. Therefore, it is hypothesized that the potential modules, at the level of metabolism, anatomy, and gene regulation, which are needed to perform C4 photosynthesis are present in C3 plants. Since C4 plants grow better than C3 plants in hot and dry environments, scientists are working on converting C3 crops such as rice to C4 plants. However, several challenges, including a lack of understanding of the evolutionary paths toward manifestation of C4 trait, have hampered the C3-to-C4 engineering ([2]). Here, we used a metabolic network model of Arabidopsis thaliana as a C3 model plant and attempted to understand the possible evolutionary events leading to emerging of C4 photosynthesis in various scenarios and examined the results.

bioinformatics↗

bioRxiv2018

A relative comparison between Hidden Markov- and Log-Linear- based models for differential expression analysis in a real time course RNA sequencing data

With the advent of the Next Generation Sequencing technologies, RNA-seq has become known as an optimal approach for studying gene expression profiling. Particularly, time course RNA-seq differential expression analysis has been used in many studies to identify candidate genes. However, applying a statistical method to efficiently identify differentially expressed genes (DEGs) in time course studies is challenging due to inherent characteristics of such data including correlation and dependencies over time. Here we aim to relatively compare EBSeq-HMM, a Hidden Markov-based model, with multiDE, a Log-Linear-based model, in a real time course RNA sequencing data. In order to conduct the comparison, common DEGs detected by edgeR, DESeq2 and Voom (referred to as Benchmark DEGs) were utilized as a measure. Each of the two models were compared using different normalization methods. The findings revealed that multiDE identified more Benchmark DEGs and showed a higher agreement with them than EBSeq-HMM. Furthermore, multiDE and EBSeq-HMM displayed their best performance using TMM and Upper-Quartile normalization methods, respectively.

bioinformatics↗