A comprehensive lettuce variation map reveals the impact of structural variations in agronomic traits.

BACKGROUND: As an important vegetable crop, cultivated lettuce is grown worldwide and a great variety of agronomic traits have been preserved within germplasm collections. The mechanisms underlying these phenotypic variations remain to be elucidated in association with sequence variations. Compared with single nucleotide polymorphisms, structural variations (SVs) that have more impacts on gene functions remain largely uncharacterized in the lettuce genome. RESULTS: Here, we produced a comprehensive SV set for 333 wild and cultivated lettuce accessions. Comparison of SV frequencies showed that the SVs prevalent in L. sativa affected the genes enriched in carbohydrate derivative catabolic and secondary metabolic processes. Genome-wide association analysis of seven agronomic traits uncovered potentially causal SVs associated with seed coat color and leaf anthocyanin content. CONCLUSION: Our work characterized a great abundance of SVs in the lettuce genome, and provides a valuable genomic resource for future lettuce breeding.

BERT-PAGG: a Chinese relationship extraction model fusing PAGG and entity location information.

Relationship extraction is one of the important tasks of constructing knowledge graph. In recent years, many scholars have introduced external information other than entities into relationship extraction models, which perform better than traditional relationship extraction methods. However, they ignore the importance of the relative position between entities. Considering the relative position between entity pairs and the influence of sentence level information on the performance of relationship extraction model, this article proposes a BERT-PAGG relationship extraction model. The model introduces the location information of entities, and combines the local features extracted by PAGG module with the entity vector representation output by BERT. Specifically, BERT-PAGG integrates entity location information into local features through segmented convolution neural network, uses attention mechanism to capture more effective semantic features, and finally regulates the transmission of information flow through gating mechanism. Experimental results on two open Chinese relation extraction datasets show that the proposed method achieves the best results compared with other models. At the same time, ablation experiments show that PAGG module can effectively use external information, and the introduction of this module makes the Macro-F1 value of the model increase by at least 2.82%.

The Cycas genome and the early evolution of seed plants.

Cycads represent one of the most ancient lineages of living seed plants. Identifying genomic features uniquely shared by cycads and other extant seed plants, but not non-seed-producing plants, may shed light on the origin of key innovations, as well as the early diversification of seed plants. Here, we report the 10.5-Gb reference genome of Cycas panzhihuaensis, complemented by the transcriptomes of 339 cycad species. Nuclear and plastid phylogenomic analyses strongly suggest that cycads and Ginkgo form a clade sister to all other living gymnosperms, in contrast to mitochondrial data, which place cycads alone in this position. We found evidence for an ancient whole-genome duplication in the common ancestor of extant gymnosperms. The Cycas genome contains four homologues of the fitD gene family that were likely acquired via horizontal gene transfer from fungi, and these genes confer herbivore resistance in cycads. The male-specific region of the Y chromosome of C. panzhihuaensis contains a MADS-box transcription factor expressed exclusively in male cones that is similar to a system reported in Ginkgo, suggesting that a sex determination mechanism controlled by MADS-box genes may have originated in the common ancestor of cycads and Ginkgo. The C. panzhihuaensis genome provides an important new resource of broad utility for biologists.

Whole-genome resequencing of 445 Lactuca accessions reveals the domestication history of cultivated lettuce.

Lettuce (Lactuca sativa) is an important vegetable crop worldwide. Cultivated lettuce is believed to be domesticated from L. serriola; however, its origins and domestication history remain to be elucidated. Here, we sequenced a total of 445 Lactuca accessions, including major lettuce crop types and wild relative species, and generated a comprehensive map of lettuce genome variations. In-depth analyses of population structure and demography revealed that lettuce was first domesticated near the Caucasus, which was marked by loss of seed shattering. We also identified the genetic architecture of other domestication traits and wild introgressions in major resistance clusters in the lettuce genome. This study provides valuable genomic resources for crop breeding and sheds light on the domestication history of cultivated lettuce.

High sensitive detection of cancer cell with a folic acid-based boron-doped diamond electrode using an AC impedimetric approach.

An electrochemical impedance method at a fixed frequency (10Hz) is used to detect folate receptor-rich cancer cells with the interaction between folic acid immobilized on gold nanoparticles deposited on boron-doped diamond (BDD) electrode surface and its receptor over-expressed on cancer cell membrane without additional labeling. Experimental results have shown that the BDD electrode modified with folic acid can clearly denote folate receptor-rich cancer cells, such as HeLa cells, at a concentration down to 10 cells mL(-1). The high sensitivity of BDD electrode is resulted from the change of field effect and surface charge density of BDD after cancer cells attachment. The BDD electrodes can be regenerated with 0.1M citric acid/glycine/HC1 at pH 3.0 and used seven times again. Therefore, electrochemical technique with BDD electrode has been introduced for cancer cells detection and a simple method to detect folate receptor-rich cancer cells without additional labeling has been developed.

Conjugating folic acid to gold nanoparticles through glutathione for targeting and detecting cancer cells.

Gold nanoparticles (GNPs) were modified with glutathione (GSH) to form GSH-capped GNPs, which have carboxyl groups on the surface of these nanoparticles. Then folic acid (FA) was conjugated with GNPs through the reaction between amino group of FA and carboxyl group of GSH. These folic acid-conjugated nanoparticles (FA-GSH-GNPs) were stable in aqueous solution over a broad range of pH and ionic strength values. The targeting of FA-GSH-GNPs in human cervices carcinoma cells (HeLa cells) with high-level folate receptor expression was confirmed by transmission electron microscopy (TEM) and confocal laser scanning microscopy (CLSM). No cellular uptake of these nanoparticles was observed in A549 cells lack of folate receptor. HeLa cells and mouse fibroblasts incubated with FA-GSH-GNPs were assayed by measuring the relative absorbance of the supernatant collected at low-speed centrifugation. Based on this simple spectroscopic method, HeLa cells have been detected with a detection limit of 10(2)cells/mL.

Effect of pH on the Interaction of Gold Nanoparticles with DNA and Application in the Detection of Human p53 Gene Mutation.

Gold nanoparticles (GNPs) are widely used to detect DNA. We studied the effect of pH on the assembly/disassembly of single-stranded DNA functionalized GNPs. Based on the different binding affinities of DNA to GNPs, we present a simple and fast way that uses HCl to drive the assembly of GNPs for detection of DNA sequences with single nucleotide differences. The assembly is reversible and can be switched by changing the solution pH. No covalent modification of DNA or GNP surface is needed. Oligonucleotide derived from human p53 gene with one-base substitution can be distinguished by a color change of the GNPs solution or a significant difference of the maximum absorption wavelength (lambda(max)), compared with wildtype sequences. This method enables detection of 10 picomole quantities of target DNA.