Comparison of RNA expression profiles on generations of <it>Porphyra yezoensis </it>(Rhodophyta), based on suppression subtractive hybridization (SSH)

Abstract Background Porphyra yezoensis Ueda is one of the most important edible seaweed, with a dimorphic life cycle which consists of gametophyte as macroscopical blade and sporophyte as microscopic filamentous. Conspicuous differences exist in the two generations, such as morphology, cell structure, biochemistry, physiology, and so on. The developmental process of Porphyra yezoensis has been studied thoroughly, but the mechanism is still ambiguous and few studies on genetic expression have been carried out. In this study, the suppression subtractive hybridization (SSH) method conducted to generate large-scale expressed sequence tags (EST) is designed to identify gene candidates related to the morphological and physiological differences between the gametophytic and sporophytic generations of Porphyra yezoensis Ueda. Findings Each 300 clones of sporophyte and gametophyte cells were dipped onto the membrane for hybridization. The result of dot-blot suggested there were 222 positive clones in gametophyte library and 236 positive clones in sporophyte library. 383 positive clones of strongest signals had been sequenced, and 191 EST sequences of gametophyte and 192 of sporophyte were obtained. A total of 196 genes were obtained, within which 104 genes were identified from the gametophyte and 92 from the sporophyte. Thirty-nine genes of the gametophyte and 62 genes of the sporophyte showed sequence similarity to those genes with known or putative functions which were classified according to their putative biological roles and molecular functions. The GO annotation showed about 58% of the cellular component of sporophyte and gametophyte cells were mainly located in cytoplasm and nucleus. The special genes were located in Golgi apparatus, and high expression in plastid, ribosome and endoplasmic reticulum. The main biological functions of gametophyte cells contributed to DNA repair/replication, carbohydrate metabolism, transport and transcription, especially in response to heat and oxidative stress. The sporophyte cell expresses more genes in transcription, transport, carbohydrate metabolism, particularly in signal transduction, DNA and protein modification, protein and nucleotide metabolism. Four genes are expressed on both gametophyte and sporophyte cells and eighteen genes have not been annotated. Conclusion According to the information of GO annotation, the gametophyte tends to growth and self- protection while the sporophyte tends to be more active in development. Interpretation of the differentially expressed genes revealed new insights into the molecular processes of the generation alternation of Porphyra yezoensis. Further investigation are needed due to insufficiency of functional genes research and indeterminancy of the functions of many sequences.</p

CrusTF: a comprehensive resource of transcriptomes for evolutionary and functional studies of crustacean transcription factors

Abstract Background Crustacea, the second largest subphylum of Arthropoda, includes species of major ecological and economic importance, such as crabs, lobsters, crayfishes, shrimps, and barnacles. With the rapid development of crustacean aquaculture and biodiversity loss, understanding the gene regulatory mechanisms of growth, reproduction, and development of crustaceans is crucial to both aquaculture development and biodiversity conservation of this group of organisms. In these biological processes, transcription factors (TFs) play a vital role in regulating gene expression. However, crustacean transcription factors are still largely unknown, because the lack of complete genome sequences of most crustacean species hampers the studies on their transcriptional regulation on a system-wide scale. Thus, the current TF databases derived from genome sequences contain TF information for only a few crustacean species and are insufficient to elucidate the transcriptional diversity of such a large animal group. Results Our database CrusTF ( http://qinlab.sls.cuhk.edu.hk/CrusTF ) provides comprehensive information for evolutionary and functional studies on the crustacean transcriptional regulatory system. CrusTF fills the knowledge gap of transcriptional regulation in crustaceans by exploring publicly available and newly sequenced transcriptomes of 170 crustacean species and identifying 131,941 TFs within 63 TF families. CrusTF features three categories of information: sequence, function, and evolution of crustacean TFs. The database enables searching, browsing and downloading of crustacean TF sequences. CrusTF infers DNA binding motifs of crustacean TFs, thus facilitating the users to predict potential downstream TF targets. The database also presents evolutionary analyses of crustacean TFs, which improve our understanding of the evolution of transcriptional regulatory systems in crustaceans. Conclusions Given the importance of TF information in evolutionary and functional studies on transcriptional regulatory systems of crustaceans, this database will constitute a key resource for the research community of crustacean biology and evolutionary biology. Moreover, CrusTF serves as a model for the construction of TF database derived from transcriptome data. A similar approach could be applied to other groups of organisms, for which transcriptomes are more readily available than genomes

Additional file 1: Table S1. of CrusTF: a comprehensive resource of transcriptomes for evolutionary and functional studies of crustacean transcription factors

List of crustacean transcriptome data. Table S2. Crustacean transcriptome data collection from Short Read Archive. Table S3. Crustacean transcriptome data collection from Transcriptome Shotgun Assembly. Table S4. Crustacean TFs from GenBank. Table S5. List of the 63 TF families identified in the crustacean species. (XLSX 336 kb

NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results

This paper reviews the NTIRE 2022 challenge on efficient single image super-resolution with focus on the proposed solutions and results. The task of the challenge was to super-resolve an input image with a magnification factor of $\times$4 based on pairs of low and corresponding high resolution images. The aim was to design a network for single image super-resolution that achieved improvement of efficiency measured according to several metrics including runtime, parameters, FLOPs, activations, and memory consumption while at least maintaining the PSNR of 29.00dB on DIV2K validation set. IMDN is set as the baseline for efficiency measurement. The challenge had 3 tracks including the main track (runtime), sub-track one (model complexity), and sub-track two (overall performance). In the main track, the practical runtime performance of the submissions was evaluated. The rank of the teams were determined directly by the absolute value of the average runtime on the validation set and test set. In sub-track one, the number of parameters and FLOPs were considered. And the individual rankings of the two metrics were summed up to determine a final ranking in this track. In sub-track two, all of the five metrics mentioned in the description of the challenge including runtime, parameter count, FLOPs, activations, and memory consumption were considered. Similar to sub-track one, the rankings of five metrics were summed up to determine a final ranking. The challenge had 303 registered participants, and 43 teams made valid submissions. They gauge the state-of-the-art in efficient single image super-resolution.Comment: Validation code of the baseline model is available at https://github.com/ofsoundof/IMDN. Validation of all submitted models is available at https://github.com/ofsoundof/NTIRE2022_ES