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Interestingly, complete ASE genes showed higher gene body CHG methylation than partial ( I P i = 0.05) and non-ASE genes and partial ASE genes showed lower CG methylation than others ( I P i = 3.8 e-08, Figure 1g), suggesting that DNA methylation alterations between alleles from different haplotypes are frequently accompanied with ASEs. Since the cassava genome is highly heterozygous, DNA methylome of the haplotype-collapsed genome misses many features of the methylome. Keywords: haplotype-resolved; DNA methylation; cassava EN haplotype-resolved DNA methylation cassava 247 249 3 01/31/23 20230201 NES 230201 Cytosine DNA methylation is involved in transposable element (TE) silencing, imprinting and X-chromosome inactivation. [Extracted from the article]

• A hierarchical prior-guided quality assessment method is proposed for underwater images (HPUIQA). • Luminance and texture feature mining for underwater IQA by simulating the multi-scale perception characteristics of human visual system. • The optical imaging principle of the underwater image is utilized for accurately and reliably luminance feature extraction. • Prior information of the underwater image is adopted to guide IQA model training. Many underwater image enhancement (UIE) algorithms have been proposed to improve the quality of the underwater image. However, the lack of effective objective image quality assessment (IQA) methods has hindered the further development of UIE algorithms. Unlike traditional distorted images, underwater images usually contain natural distortions such as color cast and fog effects induced by light absorption and scattering. In addition, due to the complexity of underwater scenes, the enhanced results generated using existing UIE algorithms may have artificial distortions such as under-enhancement, over-enhancement, and detail loss. Thus, it is difficult for traditional IQA methods to comprehensively capture quality-related features in complicated underwater conditions. Based on this, this paper proposes a new hierarchical prior-guided quality assessment method for underwater images with the aid of deep learning technology, which first decomposes the underwater image into the base layer and detail layer. Then, the two layers are taken as input of feature extraction network for extracting the luminance information and texture information of the image, respectively. Meanwhile, two pseudo-reference images are used to guide model training so as to obtain luminance and texture features more accurately and efficiently. Finally, the two types of features are fused to obtain the quality score of the underwater image. Extensive experiments have been conducted on two publicly available underwater image datasets, and the experimental results show that the proposed method outperforms other underwater image quality assessment methods. [ABSTRACT FROM AUTHOR]

In eukaryotes, small RNAs (sRNAs) play critical roles in multiple biological processes. Dicer endonucleases are a central part of sRNA biogenesis. In plants, DICER-LIKE PROTEIN 3 (DCL3) produces 24-nucleotide (nt) small interfering RNAs (siRNAs) that determine the specificity of the RNA-directed DNA methylation pathway. Here, we determined the structure of a DCL3–pre-siRNA complex in an active dicing-competent state. The 5′-phosphorylated A1 of the guide strand and the 1-nt 3′ overhang of the complementary strand are specifically recognized by a positively charged pocket and an aromatic cap, respectively. The 24-nt siRNA length dependence relies on the separation between the 5′-phosphorylated end of the guide RNA and dual cleavage sites formed by the paired ribonuclease III domains. These structural studies, complemented by functional data, provide insight into the dicing principle for Dicers in general. [ABSTRACT FROM AUTHOR]