scholarly journals Unique Shine–Dalgarno Sequences in Cyanobacteria and Chloroplasts Reveal Evolutionary Differences in Their Translation Initiation

2019 ◽  
Vol 11 (11) ◽  
pp. 3194-3206 ◽  
Author(s):  
Yulong Wei ◽  
Xuhua Xia

Abstract Microorganisms require efficient translation to grow and replicate rapidly, and translation is often rate-limited by initiation. A prominent feature that facilitates translation initiation in bacteria is the Shine–Dalgarno (SD) sequence. However, there is much debate over its conservation in Cyanobacteria and in chloroplasts which presumably originated from endosymbiosis of ancient Cyanobacteria. Elucidating the utilization of SD sequences in Cyanobacteria and in chloroplasts is therefore important to understand whether 1) SD role in Cyanobacterial translation has been reduced prior to chloroplast endosymbiosis or 2) translation in Cyanobacteria and in plastid has been subjected to different evolutionary pressures. To test these alternatives, we employed genomic, proteomic, and transcriptomic data to trace differences in SD usage among Synechocystis species, Microcystis aeruginosa, cyanophages, Nicotiana tabacum chloroplast, and Arabidopsis thaliana chloroplast. We corrected their mis-annotated 16S rRNA 3′ terminus using an RNA-Seq-based approach to determine their SD/anti-SD locational constraints using an improved measurement DtoStart. We found that cyanophages well-mimic Cyanobacteria in SD usage because both have been under the same selection pressure for SD-mediated initiation. Whereas chloroplasts lost this similarity because the need for SD-facilitated initiation has been reduced in plastids having much reduced genome size and different ribosomal proteins as a result of host-symbiont coevolution. Consequently, SD sequence significantly increases protein expression in Cyanobacteria but not in chloroplasts, and only Cyanobacterial genes compensate for a lack of SD sequence by having weaker secondary structures at the 5′ UTR. Our results suggest different evolutionary pressures operate on translation initiation in Cyanobacteria and in chloroplast.

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jing Xu ◽  
Xiangdong Liu ◽  
Qiming Dai

Abstract Background Hypertrophic cardiomyopathy (HCM) represents one of the most common inherited heart diseases. To identify key molecules involved in the development of HCM, gene expression patterns of the heart tissue samples in HCM patients from multiple microarray and RNA-seq platforms were investigated. Methods The significant genes were obtained through the intersection of two gene sets, corresponding to the identified differentially expressed genes (DEGs) within the microarray data and within the RNA-Seq data. Those genes were further ranked using minimum-Redundancy Maximum-Relevance feature selection algorithm. Moreover, the genes were assessed by three different machine learning methods for classification, including support vector machines, random forest and k-Nearest Neighbor. Results Outstanding results were achieved by taking exclusively the top eight genes of the ranking into consideration. Since the eight genes were identified as candidate HCM hallmark genes, the interactions between them and known HCM disease genes were explored through the protein–protein interaction (PPI) network. Most candidate HCM hallmark genes were found to have direct or indirect interactions with known HCM diseases genes in the PPI network, particularly the hub genes JAK2 and GADD45A. Conclusions This study highlights the transcriptomic data integration, in combination with machine learning methods, in providing insight into the key hallmark genes in the genetic etiology of HCM.


Author(s):  
Fabricio Almeida-Silva ◽  
Kanhu C Moharana ◽  
Thiago M Venancio

Abstract In the past decade, over 3000 samples of soybean transcriptomic data have accumulated in public repositories. Here, we review the state of the art in soybean transcriptomics, highlighting the major microarray and RNA-seq studies that investigated soybean transcriptional programs in different tissues and conditions. Further, we propose approaches for integrating such big data using gene coexpression network and outline important web resources that may facilitate soybean data acquisition and analysis, contributing to the acceleration of soybean breeding and functional genomics research.


2011 ◽  
Vol 49 (8) ◽  
pp. 843-851 ◽  
Author(s):  
Annelies Delporte ◽  
Nausicaä Lannoo ◽  
Gianni Vandenborre ◽  
Maté Ongenaert ◽  
Els J.M. Van Damme

BMC Genomics ◽  
2015 ◽  
Vol 16 (1) ◽  
Author(s):  
Anna V. Klepikova ◽  
Maria D. Logacheva ◽  
Sergey E. Dmitriev ◽  
Aleksey A. Penin

2019 ◽  
Vol 11 (10) ◽  
pp. 816-828 ◽  
Author(s):  
Lichao Liu ◽  
J Yuyang Lu ◽  
Fajin Li ◽  
Xudong Xing ◽  
Tong Li ◽  
...  

Abstract The metabolic enzyme isocitrate dehydrogenase 1 (IDH1) catalyzes the oxidative decarboxylation of isocitrate to α-ketoglutarate (α-KG). Its mutation often leads to aberrant gene expression in cancer. IDH1 was reported to bind thousands of RNA transcripts in a sequence-dependent manner; yet, the functional significance of this RNA-binding activity remains elusive. Here, we report that IDH1 promotes mRNA translation via direct associations with polysome mRNA and translation machinery. Comprehensive proteomic analysis in embryonic stem cells (ESCs) revealed striking enrichment of ribosomal proteins and translation regulators in IDH1-bound protein interactomes. We performed ribosomal profiling and analyzed mRNA transcripts that are associated with actively translating polysomes. Interestingly, knockout of IDH1 in ESCs led to significant downregulation of polysome-bound mRNA in IDH1 targets and subtle upregulation of ribosome densities at the start codon, indicating inefficient translation initiation upon loss of IDH1. Tethering IDH1 to a luciferase mRNA via the MS2-MBP system promotes luciferase translation, independently of the catalytic activity of IDH1. Intriguingly, IDH1 fails to enhance luciferase translation driven by an internal ribosome entry site. Together, these results reveal an unforeseen role of IDH1 in fine-tuning cap-dependent translation via the initiation step.


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