Nubeam-dedup: a fast and RAM-efficient tool to de-duplicate sequencing reads without mapping

NGS-based Aspergillus detection in plasma and lung lavage of children with invasive pulmonary aspergillosis

In immunocompromised pediatric patients, diagnosing invasive pulmonary aspergillosis (IPA) poses a significant challenge. Next-Generation Sequencing (NGS) shows promise for detecting fungal DNA but lacks standardization. This study aims to advance towards clinical evaluation of liquid biopsy NGS for Aspergillus detection, through an evaluation of wet-lab procedures and computational analysis. Our findings support using both CHM13v2.0 and GRCh38.p14 in host-read mapping to reduce fungal false-positives. We demonstrate the sensitivity of our custom kraken2 database, cRE.21, in detecting Aspergillus species. Additionally, cell-free DNA sequencing shows superior performance to whole-cell DNA sequencing by recovering higher fractions of fungal DNA in lung fluid (bronchoalveolar lavage [BAL] fluid) and plasma samples from pediatric patients with probable IPA. In a proof-of-principle, A. fumigatus was identified in 5 out of 7 BAL fluid samples and 3 out of 5 plasma samples. This optimized workflow can advance fungal-NGS research and represents a step towards enhancing diagnostic certainty by enabling more sensitive and accurate species-level diagnosis of IPA in immunocompromised patients.

Genomic analyses of agronomic traits in tea plants and related Camellia species

The genus Camellia contains three types of domesticates that meet various needs of ancient humans: the ornamental C. japonica, the edible oil-producing C. oleifera, and the beverage-purposed tea plant C. sinensis. The genomic drivers of the functional diversification of Camellia domesticates remain unknown. Here, we present the genomic variations of 625 Camellia accessions based on a new genome assembly of C. sinensis var. assamica ('YK10'), which consists of 15 pseudo-chromosomes with a total length of 3.35 Gb and a contig N50 of 816,948 bp. These accessions were mainly distributed in East Asia, South Asia, Southeast Asia, and Africa. We profiled the population and subpopulation structure in tea tree Camellia to find new evidence for the parallel domestication of C. sinensis var. assamica (CSA) and C. sinensis var. sinensis (CSS). We also identified candidate genes associated with traits differentiating CSA, CSS, oilseed Camellia, and ornamental Camellia cultivars. Our results provide a unique global view of the genetic diversification of Camellia domesticates and provide valuable resources for ongoing functional and molecular breeding research.

Systematic dissection of genomic features determining the vast diversity of conotoxins

BACKGROUND

Conus, a highly diverse species of venomous predators, has attracted significant attention in neuroscience and new drug development due to their rich collection of neuroactive peptides called conotoxins. Recent advancements in transcriptome, proteome, and genome analyses have facilitated the identification of conotoxins within Conus' venom glands, providing insights into the genetic features and evolutionary patterns of conotoxin genes. However, the underlying mechanism behind the extraordinary hypervariability of conotoxins remains largely unknown.

RESULTS

We analyzed the transcriptomes of 34 Conus species, examining various tissues such as the venom duct, venom bulb, and salivary gland, leading to the identification of conotoxin genes. Genetic variation analysis revealed that a subset of these genes (15.78% of the total) in Conus species underwent positive selection (Ka/Ks > 1, p < 0.01). Additionally, we reassembled and annotated the genome of C. betulinus, uncovering 221 conotoxin-encoding genes. These genes primarily consisted of three exons, with a significant portion showing high transcriptional activity in the venom ducts. Importantly, the flanking regions and adjacent introns of conotoxin genes exhibited a higher prevalence of transposon elements, suggesting their potential contribution to the extensive variability observed in conotoxins. Furthermore, we detected genome duplication in C. betulinus, which likely contributed to the expansion of conotoxin gene numbers. Interestingly, our study also provided evidence of introgression among Conus species, indicating that interspecies hybridization may have played a role in shaping the evolution of diverse conotoxin genes.

CONCLUSIONS

This study highlights the impact of adaptive evolution and introgressive hybridization on the genetic diversity of conotoxin genes and the evolution of Conus. We also propose a hypothesis suggesting that transposable elements might significantly contribute to the remarkable diversity observed in conotoxins. These findings not only enhance our understanding of peptide genetic diversity but also present a novel approach for peptide bioengineering.

Fuzzy-Dedup: A secure deduplication model using cosine based Fuzzy interference system in cloud application

Storage consumption is increasing significantly these days, with consumers trying to find an effective approach to safe storage space. In these situations, a deduplication in cloud storage services is a significant way to reduce bandwidth and service space by omitting unnecessary information and keeping only a single copy of the information. This raises computational, privacy and storage issues when large numbers of handlers outsource the similar data to cloud service storage. To overcome these problems, an effective Fuzzy-Dedup framework is designed in this research by integrating four steps namely is introduced, which breaks down the data into fixed size chunks and is immediately fingerprinted by a hashing algorithm for ensuring data authentication and then indexing is done with the help of traditional b-tree indexing, similarity function is calculated to compute the similarity value in the documents. After calculating the similar values, the fuzzy interference system is designed by formulating appropriate rules for the decision-making process that determines duplicate and non-duplicate files by obtaining an effective de-duplication ratio over existing methods. After detecting duplicate files, the inline based deduplication policy checks that the new data is ready to send for storage against existing data and does not store any redundant data it discovers. The proposed model is implemented in MATLAB software is carried out several performance metrics and these parameter attained better performance such as, deduplication ratio of 1.2, memory utilization of 12500 bytes in inline and 9550 bytes in offline, throughput of 32500 Mb/s in inline and 25500 Mb/s in offline and processing time of 0.4494 s in inline and 0.1139 s in offline. Thus when compared to previous methods, such as Two Thresholds Two Divisors deduplication (TTTD) approach proposed design shows high range of performance.

Large structural variations in the haplotype-resolved African cassava genome

Cassava (Manihot esculenta Crantz, 2n = 36) is a global food security crop. It has a highly heterozygous genome, high genetic load, and genotype-dependent asynchronous flowering. It is typically propagated by stem cuttings and any genetic variation between haplotypes, including large structural variations, is preserved by such clonal propagation. Traditional genome assembly approaches generate a collapsed haplotype representation of the genome. In highly heterozygous plants, this results in artifacts and an oversimplification of heterozygous regions. We used a combination of Pacific Biosciences (PacBio), Illumina, and Hi-C to resolve each haplotype of the genome of a farmer-preferred cassava line, TME7 (Oko-iyawo). PacBio reads were assembled using the FALCON suite. Phase switch errors were corrected using FALCON-Phase and Hi-C read data. The ultralong-range information from Hi-C sequencing was also used for scaffolding. Comparison of the two phases revealed >5000 large haplotype-specific structural variants affecting over 8 Mb, including insertions and deletions spanning thousands of base pairs. The potential of these variants to affect allele-specific expression was further explored. RNA-sequencing data from 11 different tissue types were mapped against the scaffolded haploid assembly and gene expression data are incorporated into our existing easy-to-use web-based interface to facilitate use by the broader plant science community. These two assemblies provide an excellent means to study the effects of heterozygosity, haplotype-specific structural variation, gene hemizygosity, and allele-specific gene expression contributing to important agricultural traits and further our understanding of the genetics and domestication of cassava.

Minirmd: accurate and fast duplicate removal tool for short reads via multiple minimizers

SUMMARY

Removing duplicate and near-duplicate reads, generated by high-throughput sequencing technologies, is able to reduce computational resources in downstream applications. Here we develop minirmd, a de novo tool to remove duplicate reads via multiple rounds of clustering using different length of minimizer. Experiments demonstrate that minirmd removes more near-duplicate reads than existing clustering approaches and is faster than existing multi-core tools. To the best of our knowledge, minirmd is the first tool to remove near-duplicates on reverse-complementary strand.

AVAILABILITY AND IMPLEMENTATION

https://github.com/yuansliu/minirmd.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The Nubeam reference-free approach to analyze metagenomic sequencing reads

We present Nubeam (nucleotide be a matrix) as a novel reference-free approach to analyze short sequencing reads. Nubeam represents nucleotides by matrices, transforms a read into a product of matrices, and assigns numbers to reads based on the product matrix. Nubeam capitalizes on the noncommutative property of matrix multiplication, such that different reads are assigned different numbers and similar reads similar numbers. A sample, which is a collection of reads, becomes a collection of numbers that form an empirical distribution. We demonstrate that the genetic difference between samples can be quantified by the distance between empirical distributions. Nubeam includes the k-mer method as a special case, but unlike the k-mer method, it is convenient for Nubeam to account for GC bias and nucleotide quality. As a reference-free approach, Nubeam avoids reference bias and mapping bias, and can work with organisms without reference genomes. Thus, Nubeam is ideal to analyze data sets from metagenomics whole genome shotgun (WGS) sequencing, where the amount of unmapped reads is substantial. When applied to a WGS sequencing data set to quantify distances between metagenomics samples from various human body habitats, Nubeam recapitulates findings made by mapping-based methods and sheds light on contributions of unmapped reads. Nubeam is also useful in analyzing 16S rRNA sequencing data, which is a more prevalent type of data set in metagenomics studies. In our analysis, Nubeam recapitulated the findings that natural microbiota in mouse gut are resilient under challenges, and Nubeam detected differences in vaginal microbiota between cases of polycystic ovary syndrome and healthy controls.