GABNet: global attention block for retinal OCT disease classification.

Introduction: The retina represents a critical ocular structure. Of the various ophthalmic afflictions, retinal pathologies have garnered considerable scientific interest, owing to their elevated prevalence and propensity to induce blindness. Among clinical evaluation techniques employed in ophthalmology, optical coherence tomography (OCT) is the most commonly utilized, as it permits non-invasive, rapid acquisition of high-resolution, cross-sectional images of the retina. Timely detection and intervention can significantly abate the risk of blindness and effectively mitigate the national incidence rate of visual impairments. Methods: This study introduces a novel, efficient global attention block (GAB) for feed forward convolutional neural networks (CNNs). The GAB generates an attention map along three dimensions (height, width, and channel) for any intermediate feature map, which it then uses to compute adaptive feature weights by multiplying it with the input feature map. This GAB is a versatile module that can seamlessly integrate with any CNN, significantly improving its classification performance. Based on the GAB, we propose a lightweight classification network model, GABNet, which we develop on a UCSD general retinal OCT dataset comprising 108,312 OCT images from 4686 patients, including choroidal neovascularization (CNV), diabetic macular edema (DME), drusen, and normal cases. Results: Notably, our approach improves the classification accuracy by 3.7% over the EfficientNetV2B3 network model. We further employ gradient-weighted class activation mapping (Grad-CAM) to highlight regions of interest on retinal OCT images for each class, enabling doctors to easily interpret model predictions and improve their efficiency in evaluating relevant models. Discussion: With the increasing use and application of OCT technology in the clinical diagnosis of retinal images, our approach offers an additional diagnostic tool to enhance the diagnostic efficiency of clinical OCT retinal images.

Marker Development for Phylogenomics: The Case of Orobanchaceae, a Plant Family with Contrasting Nutritional Modes.

Phylogenomic approaches, employing next-generation sequencing (NGS) techniques, have revolutionized systematic and evolutionary biology. Target enrichment is an efficient and cost-effective method in phylogenomics and is becoming increasingly popular. Depending on availability and quality of reference data as well as on biological features of the study system, (semi-)automated identification of suitable markers will require specific bioinformatic pipelines. Here, we established a highly flexible bioinformatic pipeline, BaitsFinder, to identify putative orthologous single copy genes (SCGs) and to construct bait sequences in a single workflow. Additionally, this pipeline has been constructed to be able to cope with challenging data sets, such as the nutritionally heterogeneous plant family Orobanchaceae. To this end, we used transcriptome data of differing quality available for four Orobanchaceae species and, as reference, SCG data from monkeyflower (Erythranthe guttata, syn. Mimulus g.; 1,915 genes) and tomato (Solanum lycopersicum; 391 genes). Depending on whether gaps were permitted in initial blast searches of the four Orobanchaceae species against the reference, our pipeline identified 1,307 and 981 SCGs with average length of 994 bp and 775 bp, respectively. Automated bait sequence construction (using 2× tiling) resulted in 38,170 and 21,856 bait sequences, respectively. In comparison to the recently published MarkerMiner 1.0 pipeline BaitsFinder identified about 1.6 times as many SCGs (of at least 900 bp length). Skipping steps specific to analyses of Orobanchaceae, BaitsFinder was successfully used in a group of non-parasitic plants (three Asteraceae species and, as reference, SCG data from Arabidopsis thaliana based on previously compiled SCGs). Thus, BaitsFinder is expected to be broadly applicable in groups, where only transcriptomes or partial genome data of differing quality are available.

Adaptive sequence evolution is driven by biotic stress in a pair of orchid species (Dactylorhiza) with distinct ecological optima.

The orchid family is the largest in the angiosperms, but little is known about the molecular basis of the significant variation they exhibit. We investigate here the transcriptomic divergence between two European terrestrial orchids, Dactylorhiza incarnata and Dactylorhiza fuchsii, and integrate these results in the context of their distinct ecologies that we also document. Clear signals of lineage-specific adaptive evolution of protein-coding sequences are identified, notably targeting elements of biotic defence, including both physical and chemical adaptations in the context of divergent pools of pathogens and herbivores. In turn, a substantial regulatory divergence between the two species appears linked to adaptation/acclimation to abiotic conditions. Several of the pathways affected by differential expression are also targeted by deviating post-transcriptional regulation via sRNAs. Finally, D. incarnata appears to suffer from insufficient sRNA control over the activity of RNA-dependent DNA polymerase, resulting in increased activity of class I transposable elements and, over time, in larger genome size than that of D. fuchsii. The extensive molecular divergence between the two species suggests significant genomic and transcriptomic shock in their hybrids and offers insights into the difficulty of coexistence at the homoploid level. Altogether, biological response to selection, accumulated during the history of these orchids, appears governed by their microenvironmental context, in which biotic and abiotic pressures act synergistically to shape transcriptome structure, expression and regulation.

Identification, characterization and expression analysis of lineage-specific genes within sweet orange (Citrus sinensis).

BACKGROUND: With the availability of rapidly increasing number of genome and transcriptome sequences, lineage-specific genes (LSGs) can be identified and characterized. Like other conserved functional genes, LSGs play important roles in biological evolution and functions. RESULTS: Two set of citrus LSGs, 296 citrus-specific genes (CSGs) and 1039 orphan genes specific to sweet orange, were identified by comparative analysis between the sweet orange genome sequences and 41 genomes and 273 transcriptomes. With the two sets of genes, gene structure and gene expression pattern were investigated. On average, both the CSGs and orphan genes have fewer exons, shorter gene length and higher GC content when compared with those evolutionarily conserved genes (ECs). Expression profiling indicated that most of the LSGs expressed in various tissues of sweet orange and some of them exhibited distinct temporal and spatial expression patterns. Particularly, the orphan genes were preferentially expressed in callus, which is an important pluripotent tissue of citrus. Besides, part of the CSGs and orphan genes expressed responsive to abiotic stress, indicating their potential functions during interaction with environment. CONCLUSION: This study identified and characterized two sets of LSGs in citrus, dissected their sequence features and expression patterns, and provided valuable clues for future functional analysis of the LSGs in sweet orange.

Whole-genome sequencing of Mesorhizobium huakuii 7653R provides molecular insights into host specificity and symbiosis island dynamics.

BACKGROUND: Evidence based on genomic sequences is urgently needed to confirm the phylogenetic relationship between Mesorhizobium strain MAFF303099 and M. huakuii. To define underlying causes for the rather striking difference in host specificity between M. huakuii strain 7653R and MAFF303099, several probable determinants also require comparison at the genomic level. An improved understanding of mobile genetic elements that can be integrated into the main chromosomes of Mesorhizobium to form genomic islands would enrich our knowledge of how genome dynamics may contribute to Mesorhizobium evolution in general. RESULTS: In this study, we sequenced the complete genome of 7653R and compared it with five other Mesorhizobium genomes. Genomes of 7653R and MAFF303099 were found to share a large set of orthologs and, most importantly, a conserved chromosomal backbone and even larger perfectly conserved synteny blocks. We also identified candidate molecular differences responsible for the different host specificities of these two strains. Finally, we reconstructed an ancestral Mesorhizobium genomic island that has evolved into diverse forms in different Mesorhizobium species. CONCLUSIONS: Our ortholog and synteny analyses firmly establish MAFF303099 as a strain of M. huakuii. Differences in nodulation factors and secretion systems T3SS, T4SS, and T6SS may be responsible for the unique host specificities of 7653R and MAFF303099 strains. The plasmids of 7653R may have arisen by excision of the original genomic island from the 7653R chromosome.

RNA-Seq and microarrays analyses reveal global differential transcriptomes of Mesorhizobium huakuii 7653R between bacteroids and free-living cells.

Mesorhizobium huakuii 7653R occurs either in nitrogen-fixing symbiosis with its host plant, Astragalus sinicus, or free-living in the soil. The M. huakuii 7653R genome has recently been sequenced. To better understand the complex biochemical and developmental changes that occur in 7653R during bacteroid development, RNA-Seq and Microarrays were used to investigate the differential transcriptomes of 7653R bacteroids and free-living cells. The two approaches identified several thousand differentially expressed genes. The most prominent up-regulation occurred in the symbiosis plasmids, meanwhile gene expression is concentrated to a set of genes (clusters) in bacteroids to fulfill corresponding functional requirements. The results suggested that the main energy metabolism is active while fatty acid metabolism is inactive in bacteroid and that most of genes relevant to cell cycle are down-regulated accordingly. For a global analysis, we reconstructed a protein-protein interaction (PPI) network for 7653R and integrated gene expression data into the network using Cytoscape. A highly inter-connected subnetwork, with function enrichment for nitrogen fixation, was found, and a set of hubs and previously uncharacterized genes participating in nitrogen fixation were identified. The results described here provide a broader biological landscape and novel insights that elucidate rhizobial bacteroid differentiation, nitrogen fixation and related novel gene functions.

Citrus sinensis annotation project (CAP): a comprehensive database for sweet orange genome.

Citrus is one of the most important and widely grown fruit crop with global production ranking firstly among all the fruit crops in the world. Sweet orange accounts for more than half of the Citrus production both in fresh fruit and processed juice. We have sequenced the draft genome of a double-haploid sweet orange (C. sinensis cv. Valencia), and constructed the Citrus sinensis annotation project (CAP) to store and visualize the sequenced genomic and transcriptome data. CAP provides GBrowse-based organization of sweet orange genomic data, which integrates ab initio gene prediction, EST, RNA-seq and RNA-paired end tag (RNA-PET) evidence-based gene annotation. Furthermore, we provide a user-friendly web interface to show the predicted protein-protein interactions (PPIs) and metabolic pathways in sweet orange. CAP provides comprehensive information beneficial to the researchers of sweet orange and other woody plants, which is freely available at http://citrus.hzau.edu.cn/.

The draft genome of sweet orange (Citrus sinensis).

Oranges are an important nutritional source for human health and have immense economic value. Here we present a comprehensive analysis of the draft genome of sweet orange (Citrus sinensis). The assembled sequence covers 87.3% of the estimated orange genome, which is relatively compact, as 20% is composed of repetitive elements. We predicted 29,445 protein-coding genes, half of which are in the heterozygous state. With additional sequencing of two more citrus species and comparative analyses of seven citrus genomes, we present evidence to suggest that sweet orange originated from a backcross hybrid between pummelo and mandarin. Focused analysis on genes involved in vitamin C metabolism showed that GalUR, encoding the rate-limiting enzyme of the galacturonate pathway, is significantly upregulated in orange fruit, and the recent expansion of this gene family may provide a genomic basis. This draft genome represents a valuable resource for understanding and improving many important citrus traits in the future.