Jixiang Zhang

BACKGROUND: In addition to genetic variation, epigenetic variation plays an important role in determining various biological processes. The importance of natural genetic variation to crop domestication and improvement has been widely investigated. However, the contribution of epigenetic variation in crop domestication at population level has rarely been explored. RESULTS: To understand the impact of epigenetics on crop domestication, we investigate the variation of DNA methylation during soybean domestication and improvement by whole-genome bisulfite sequencing of 45 soybean accessions, including wild soybeans, landraces, and cultivars. Through methylomic analysis, we identify 5412 differentially methylated regions (DMRs). These DMRs exhibit characters distinct from those of genetically selected regions. In particular, they have significantly higher genetic diversity. Association analyses suggest only 22.54% of DMRs can be explained by local genetic variations. Intriguingly, genes in the DMRs that are not associated with any genetic variation are enriched in carbohydrate metabolism pathways. CONCLUSIONS: This study provides a valuable map of DNA methylation across diverse accessions and dissects the relationship between DNA methylation variation and genetic variation during soybean domestication, thus expanding our understanding of soybean domestication and improvement.

RELATIVE OF EARLY FLOWERING 6 (REF6/JMJ12), a Jumonji C (JmjC)-domain-containing H3K27me3 histone demethylase, finds its target loci in Arabidopsis genome by directly recognizing the CTCTGYTY motif via its zinc-finger (ZnF) domains. REF6 tends to bind motifs located in active chromatin states that are depleted for heterochromatic modifications. However, the underlying mechanism remains unknown. Here, we show that REF6 preferentially bind to hypo-methylated CTCTGYTY motifs in vivo, and that CHG methylation decreases REF6 DNA binding affinity in vitro. In addition, crystal structures of ZnF-clusters in complex with DNA oligonucleotides reveal that 5-methylcytosine is unfavorable for REF6 binding. In drm1 drm2 cmt2 cmt3 (ddcc) quadruple mutants, in which non-CG methylation is significantly reduced, REF6 can ectopically bind a small number of new target loci, most of which are located in or neighbored with short TEs in euchromatic regions. Collectively, our findings reveal that DNA methylation, likely acting in combination with other epigenetic modifications, may partially explain why REF6 binding is depleted in heterochromatic loci.

Patchouli (Pogostemon cablin (Blanco) Benth.), a member of the Lamiaceae family, is an important aromatic plant that has been widely used in medicine and perfumery. Here, we report a 1.94 Gb chromosome-scale assembly of the patchouli genome (contig N50 = 7.97 Mb). The gene annotation reveals that tandem duplication of sesquiterpene biosynthetic genes may be a major contributor to the biosynthesis of patchouli bioactivity components. We further phase the genome into two distinct subgenomes (A and B), and identify a chromosome substitution event that have occurred between them. Further investigations show that a burst of universal LTR-RTs in the A subgenome lead to the divergence between two subgenomes. However, no significant subgenome dominance is detected. Finally, we track the evolutionary scenario of patchouli including whole genome tetraploidization, subgenome divergency, hybridization, and chromosome substitution, which are the key forces to determine the complexity of patchouli genome. Our work sheds light on the evolutionary history of patchouli and offers unprecedented genomic resources for fundamental patchouli research and elite germplasm development.

We address the problem of visual place recognition with perceptual changes. The fundamental problem of visual place recognition is generating robust image representations which are not only insensitive to environmental changes but also distinguishable to different places. Taking advantage of the feature extraction ability of Convolutional Neural Networks (CNNs), we further investigate how to localize discriminative visual landmarks that positively contribute to the similarity measurement, such as buildings and vegetations. In particular, a Landmark Localization Network (LLN) is designed to indicate which regions of an image are used for discrimination. Detailed experiments are conducted on open source datasets with varied appearance and viewpoint changes. The proposed approach achieves superior performance against state-of-the-art methods.