ABSTRACT
We described a challenge named "DRAC - Diabetic Retinopathy Analysis Challenge" in conjunction with the 25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2022). Within this challenge, we provided the DRAC datset, an ultra-wide optical coherence tomography angiography (UW-OCTA) dataset (1,103 images), addressing three primary clinical tasks: diabetic retinopathy (DR) lesion segmentation, image quality assessment, and DR grading. The scientific community responded positively to the challenge, with 11, 12, and 13 teams submitting different solutions for these three tasks, respectively. This paper presents a concise summary and analysis of the top-performing solutions and results across all challenge tasks. These solutions could provide practical guidance for developing accurate classification and segmentation models for image quality assessment and DR diagnosis using UW-OCTA images, potentially improving the diagnostic capabilities of healthcare professionals. The dataset has been released to support the development of computer-aided diagnostic systems for DR evaluation.
ABSTRACT
Salt stress is a significant abiotic stress that reduces crop yield and quality globally. In this study, we utilized RNA sequencing (RNA-Seq) to identify differentially expressed genes (DEGs) in response to salt stress induced by gamma-ray irradiation in a salt-tolerant soybean mutant. The total RNA library samples were obtained from the salt-sensitive soybean cultivar Kwangan and the salt-tolerant mutant KA-1285. Samples were taken at three time points (0, 24, and 72 h) from two tissues (leaves and roots) under 200 mM NaCl. A total of 967,719,358 clean reads were generated using the Illumina NovaSeq 6000 platform, and 94.48% of these reads were mapped to 56,044 gene models of the soybean reference genome (Glycine_max_Wm82.a2.v1). The DEGs with expression values were compared at each time point within each tissue between the two soybeans. As a result, 296 DEGs were identified in the leaves, while 170 DEGs were identified in the roots. In the case of the leaves, eight DEGs were related to the phenylpropanoid biosynthesis pathway; however, in the roots, Glyma.03G171700 within GmSalt3, a major QTL associated with salt tolerance in soybean plants, was differentially expressed. Overall, these differences may explain the mechanisms through which mutants exhibit enhanced tolerance to salt stress, and they may provide a basic understanding of salt tolerance in soybean plants.
ABSTRACT
Soybean (Glycine max L.) is a globally important source of plant proteins, oils, and amino acids for both humans and livestock. Wild soybean (Glycine soja Sieb. and Zucc.), the ancestor of cultivated soybean, could be a useful genetic source for increasing these components in soybean crops. In this study, 96,432 single-nucleotide polymorphisms (SNPs) across 203 wild soybean accessions from the 180K Axiom® Soya SNP array were investigated using an association analysis. Protein and oil content exhibited a highly significant negative correlation, while the 17 amino acids exhibited a highly significant positive correlation with each other. A genome-wide association study (GWAS) was conducted on the protein, oil, and amino acid content using the 203 wild soybean accessions. A total of 44 significant SNPs were associated with protein, oil, and amino acid content. Glyma.11g015500 and Glyma.20g050300, which contained SNPs detected from the GWAS, were selected as novel candidate genes for the protein and oil content, respectively. In addition, Glyma.01g053200 and Glyma.03g239700 were selected as novel candidate genes for nine of the amino acids (Ala, Asp, Glu, Gly, Leu, Lys, Pro, Ser, and Thr). The identification of the SNP markers related to protein, oil, and amino acid content reported in the present study is expected to help improve the quality of selective breeding programs for soybeans.
ABSTRACT
Soybean seeds consist of approximately 40% protein and 20% oil, making them one of the world's most important cultivated legumes. However, the levels of these compounds are negatively correlated with each other and regulated by quantitative trait loci (QTL) that are controlled by several genes. In this study, a total of 190 F2 and 90 BC1F2 plants derived from a cross of Daepung (Glycine max) with GWS-1887 (G. soja, a source of high protein), were used for the QTL analysis of protein and oil content. In the F2:3 populations, the average protein and oil content was 45.52% and 11.59%, respectively. A QTL associated with protein levels was detected at Gm20_29512680 on chr. 20 with a likelihood of odds (LOD) of 9.57 and an R2 of 17.2%. A QTL associated with oil levels was also detected at Gm15_3621773 on chr. 15 (LOD: 5.80; R2: 12.2%). In the BC1F2:3 populations, the average protein and oil content was 44.25% and 12.14%, respectively. A QTL associated with both protein and oil content was detected at Gm20_27578013 on chr. 20 (LOD: 3.77 and 3.06; R2 15.8% and 10.7%, respectively). The crossover to the protein content of BC1F3:4 population was identified by SNP marker Gm20_32603292. Based on these results, two genes, Glyma.20g088000 (S-adenosyl-l-methionine-dependent methyltransferases) and Glyma.20g088400 (oxidoreductase, 2-oxoglutarate-Fe(II) oxygenase family protein), in which the amino acid sequence had changed and a stop codon was generated due to an InDel in the exon region, were identified.
