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The yellow nutsedge (Cyperus esculentus L. 1753) is an unconventional oil plant with oil-rich tubers, and a potential alternative for traditional oil crops. Here, we reported the first high-quality and chromosome-level genome assembly of the yellow nutsedge generated by combining PacBio HiFi long reads, Novaseq short reads, and Hi-C data. The final genome size is 225.6 Mb with an N50 of 4.3 Mb. More than 222.9 Mb scaffolds were anchored to 54 pseudochromosomes with a BUSCO score of 96.0%. We identified 76.5 Mb (33.9%) repetitive sequences across the genome. A total of 23,613 protein-coding genes were predicted in this genome, of which 22,847 (96.8%) were functionally annotated. A whole-genome duplication event was found after the divergence of Carex littledalei and Rhynchospora breviuscula, indicating the rich genetic resources of this species for adaptive evolution. Several significantly enriched GO terms were related to invasiveness of the yellow nutsedge, which may explain its plastic adaptability. In addition, several enriched Kyoto Encyclopedia of Genes and Genomes pathways and expanded gene families were closely related with substances in tubers, partially explaining the genomic basis of characteristics of this oil-rich tuber.

Anaerobic fungi are effective fibre-degrading microorganisms in the digestive tract of horses. However, our understanding of their diversity and community structure is limited, especially in different parts of the gastrointestinal tract.

Antioxidant proteins perform significant functions in disease control and delaying aging which can prevent free radicals from damaging organisms. Accurate identification of antioxidant proteins has important implications for the development of new drugs and the treatment of related diseases, as they play a critical role in the control or prevention of cancer and aging-related conditions. Since experimental identification techniques are time-consuming and expensive, many computational methods have been proposed to identify antioxidant proteins. Although the accuracy of these methods is acceptable, there are still some challenges. In this study, we developed a computational model called ANPrAod to identify antioxidant proteins based on a support vector machine. In order to eliminate potential redundant features and improve prediction accuracy, 673 amino acid reduction alphabets were calculated by us to find the optimal feature representation scheme. The final model could produce an overall accuracy of 87.53% with the ROC of 0.7266 in five-fold cross-validation, which was better than the existing methods. The results of the independent dataset also demonstrated the excellent robustness and reliability of ANPrAod, which could be a promising tool for antioxidant protein identification and contribute to hypothesis-driven experimental design.

Flax is an important crop for oil and fiber, however, no high-density genetic maps have been reported for this species. Specific length amplified fragment sequencing (SLAF-seq) is a high-resolution strategy for large scale de novo discovery and genotyping of single nucleotide polymorphisms. In this study, SLAF-seq was employed to develop SNP markers in an F2 population to construct a high-density genetic map for flax. In total, 196.29 million paired-end reads were obtained. The average sequencing depth was 25.08 in male parent, 32.17 in the female parent, and 9.64 in each F2 progeny. In total, 389,288 polymorphic SLAFs were detected, from which 260,380 polymorphic SNPs were developed. After filtering, 4,638 SNPs were found suitable for genetic map construction. The final genetic map included 4,145 SNP markers on 15 linkage groups and was 2,632.94 cM in length, with an average distance of 0.64 cM between adjacent markers. To our knowledge, this map is the densest SNP-based genetic map for flax. The SNP markers and genetic map reported in here will serve as a foundation for the fine mapping of quantitative trait loci (QTLs), map-based gene cloning and marker assisted selection (MAS) for flax.