Outbred genome sequencing and CRISPR/Cas9 gene editing in butterflies

Butterflies are exceptionally diverse but their potential as an experimental system has been limited by the difficulty of deciphering heterozygous genomes and a lack of genetic manipulation technology. Here we use a hybrid assembly approach to construct high-quality reference genomes for Papilio xuthus (contig and scaffold N50: 492 kb, 3.4 Mb) and Papilio machaon (contig and scaffold N50: 81 kb, 1.15 Mb), highly heterozygous species that differ in host plant affiliations, and adult and larval colour patterns. Integrating comparative genomics and analyses of gene expression yields multiple insights into butterfly evolution, including potential roles of specific genes in recent diversification. To functionally test gene function, we develop an efficient (up to 92.5%) CRISPR/Cas9 gene editing method that yields obvious phenotypes with three genes, Abdominal-B, ebony and frizzled. Our results provide valuable genomic and technological resources for butterflies and unlock their potential as a genetic model system

circSMARCA5 Promoted Osteosarcoma Cell Proliferation, Adhesion, Migration, and Invasion through a Competing Endogenous RNA Network

Osteosarcoma (OS) is a widely common sort among bone cancer in children, and its overall survival ratio is low. The hidden mechanism of tumor genesis, progression, and metastasis regarding osteosarcoma needed to be further investigated. Emerging studies concentrated on exploring the functional roles of circular RNAs (circRNAs) in human cancers. The present study conducted a loss-of-function experiments to explore the circSMARCA5-induced influence on OS proliferation, cell cycle, and metastasis. Moreover, our manuscript unearthed the potential mechanisms of circSMARCA5 in regulating OS progression by in silico analysis. Our findings would provide new evidence to support that circSMARCA5 could be indicated as a biomarker for OS

Donkey genomes provide new insights into domestication and selection for coat color

Current knowledge about the evolutionary history of donkeys is still incomplete due to the lack of archeological and whole-genome diversity data. To fill this gap, we have de novo assembled a chromosome-level reference genome of one male Dezhou donkey and analyzed the genomes of 126 domestic donkeys and seven wild asses. Population genomics analyses indicate that donkeys were domesticated in Africa and conclusively show reduced levels of Y chromosome variability and discordant paternal and maternal histories, possibly reflecting the consequences of reproductive management. We also investigate the genetic basis of coat color. While wild asses show diluted gray pigmentation (Dun phenotype), domestic donkeys display non-diluted black or chestnut coat colors (non-Dun) that were probably established during domestication. Here, we show that the non-Dun phenotype is caused by a 1 bp deletion downstream of the TBX3 gene, which decreases the expression of this gene and its inhibitory effect on pigment deposition.This work was supported by the National Natural Science Foundation of China (grant nos. 31671287 and 31601007), Agricultural Science and Technology Innovation Project of Shandong Academy of Agricultural Sciences (grant no. CXGC2016C02), Well-bred Program of Shandong Province (grant no. 2017LZGC020), Joint Innovation Funds of Dong E. E. Jiao and Shandong Academy of Agricultural Sciences, Taishan Leading Industry Talents-Agricultural Science of Shandong Province (grant no. LJNY201713), and Shandong Province Modern Agricultural Technology System Donkey Industrial Innovation Team (grant no. SDAIT-27).Peer reviewe

NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results

This paper reviews the challenge on constrained high dynamic range (HDR) imaging that was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conjunction with CVPR 2022. This manuscript focuses on the competition set-up, datasets, the proposed methods and their results. The challenge aims at estimating an HDR image from multiple respective low dynamic range (LDR) observations, which might suffer from under- or over-exposed regions and different sources of noise. The challenge is composed of two tracks with an emphasis on fidelity and complexity constraints: In Track 1, participants are asked to optimize objective fidelity scores while imposing a low-complexity constraint (i.e. solutions can not exceed a given number of operations). In Track 2, participants are asked to minimize the complexity of their solutions while imposing a constraint on fidelity scores (i.e. solutions are required to obtain a higher fidelity score than the prescribed baseline). Both tracks use the same data and metrics: Fidelity is measured by means of PSNR with respect to a ground-truth HDR image (computed both directly and with a canonical tonemapping operation), while complexity metrics include the number of Multiply-Accumulate (MAC) operations and runtime (in seconds).Comment: CVPR Workshops 2022. 15 pages, 21 figures, 2 table

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