Transformation of FASTA files into feature vectors for unsupervised compression of short reads databases

Vector embeddings by sequence similarity and context for improved compression, similarity search, clustering, organization, and manipulation of cDNA libraries

This paper demonstrates the utility of organized numerical representations of genes in research involving flat string gene formats (i.e., FASTA/FASTQ5). By assigning a unique vector embedding to each short sequence, it is possible to more efficiently cluster and improve upon compression performance for the string representations of cDNA libraries. Furthermore, by studying alternative coordinate vector embeddings trained on the context of codon triplets, we can demonstrate clustering based on amino acid properties. Employing this sequence embedding method to encode barcodes and cDNA sequences, we can improve the time complexity of similarity searches. By pairing vector embeddings with an algorithm that determines the vector proximity in Euclidean space, this approach enables quicker and more flexible sequence searches.

Transcriptome and Metabolome Integration Reveals the Impact of Fungal Elicitors on Triterpene Accumulation in Sanghuangporus sanghuang

Sanghuangporus sanghuang is a large wood-decaying mushroom highly valued in traditional Chinese medicine due to its medicinal properties, including hypoglycemic, antioxidant, antitumor, and antibacterial properties effects. Its key bioactive compounds include flavonoids and triterpenoids. Specific fungal genes can be selectively induced by fungal elicitors. To investigate the effect of fungal polysaccharides derived from Perenniporia tenuis mycelia on the metabolites of S. sanghuang, we conducted metabolic and transcriptional profiling with and without elicitor treatment (ET and WET, respectively). Correlation analysis showed significant differences in triterpenoid biosynthesis between the ET and WET groups. In addition, the structural genes associated with triterpenoids and their metabolites in both groups were verified using quantitative real-time polymerase chain reaction (qRT-PCR) and high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). Through metabolite screening, three triterpenoids were identified: betulinol, betulinic acid, and 2-hydroxyoleanolic acid. Excitation treatment increased the level of betulinic acid by 2.62-fold and 2-hydroxyoleanolic acid by 114.67-fold compared to WET. The qRT-PCR results of the four genes expressed in secondary metabolic pathways, defense gene activation, and signal transduction showed significant variation between the ET and WET groups. Overall, our study suggests that the fungal elicitor induced the aggregation of pentacyclic triterpenoid secondary metabolites in S. sanghuang.

SCA-NGS: Secure compression algorithm for next generation sequencing data using genetic operators and block sorting

Recent advancements in sequencing methods have led to significant increase in sequencing data. Increase in sequencing data leads to research challenges such as storage, transfer, processing, etc. data compression techniques have been opted to cope with the storage of these data. There have been good achievements in compression ratio and execution time. This fast-paced advancement has raised major concerns about the security of data. Confidentiality, integrity, authenticity of data needs to be ensured. This paper presents a novel lossless reference-free algorithm that focuses on data compression along with encryption to achieve security in addition to other parameters. The proposed algorithm uses preprocessing of data before applying general-purpose compression library. Genetic algorithm is used to encrypt the data. The technique is validated with experimental results on benchmark datasets. Comparative analysis with state-of-the-art techniques is presented. The results show that the proposed method achieves better results in comparison to existing methods.