Performance optimization in DNA short-read alignment

Aerospace Mutagenized Tea Tree Increases Rhizospheric Microorganisms, Enhances Nutrient Conversion Capacity and Promotes Growth

The utilization of aerospace mutagenesis in plant breeding is a novel, efficient technology. This study investigates the effects of aerospace mutagenesis on tea tree growth, soil nutrient conversion, and soil microbial community structure and function. The results showed that aerospace mutagenized tea trees showed increased leaf area, 100-bud weight, and yield. The rhizosphere soil of mutagenized tea tree displayed an increase in microorganisms, enhanced carbon and nitrogen cycling capacity, and significant increases in nutrient conversion and antioxidant enzyme activities. In addition, the content of available nutrients was also increased. Aerospace mutagenesis showed an increase in the abundance of soil-characteristic microorganisms (Solirubrobacterales bacterium, Capillimicrobium parvum, Mycobacterium colombiense, Mycobacterium rhizamassiliense, and Conexibacter woesei), and enhancement of the intensity of metabolic pathways, glyoxylate and dicarboxylate metabolism, biosynthesis of secondary metabolites, microbial metabolism in diverse environments, carbon metabolism, fatty acid metabolism, carbon metabolism, biosynthesis of amino acids, and biosynthesis of cofactors of soil microorganisms. Interaction network and partial least squares structural equation modeling (PLS-SEM) equation analysis showed that after aerospace mutagenesis, soil-characteristic microorganisms positively affected soil microbial functions, soil microbial biomass carbon and nitrogen, respiration intensity, and soil enzyme activities; furthermore, it improved available nutrient content and tea tree growth. This study provides an important reference for the cultivation and management of aerospace mutagenized tea trees and microbial regulation of tea tree growth.

Combined metabolome and transcriptome analysis reveal the mechanism of water stress in Ophiocordyceps sinensis

BACKGROUND

Ophiocordyceps sinensis (O. sinensis) is the dominant bacterium in the asexual stage of Chinese cordyceps, and its growth usually suffers from water stress. Thus, simulating its ecological growth environment is crucial for artificial cultivation. This study aimed to reveal the mechanism underlying the water stress tolerance of Ophiocordyceps sinensis (O. sinensis) by combining metabolomic and transcriptome analyses to identify crucial pathways related to differentially expressed genes (DEGs) and metabolites (DEMs) involved in the response to water stress.

RESULTS

Gene coexpression analysis revealed that many genes related to 'betalain biosynthesis', 'tyrosine metabolism', 'linoleic acid metabolism', 'fructose and mannose metabolism', and 'starch and sucrose metabolism' were highly upregulated after 20d-water stress. Metabolomic analysis revealed that many metabolites regulated by these genes in these metabolic pathways were markedly decreased. On the one hand, we surmised that carbohydrate metabolism and the β-oxidation pathway worked cooperatively to generate enough acyl-CoA and then entered the TCA cycle to provide energy when exposed to water stress. On the other hand, the betalain biosynthesis and tyrosine metabolism pathway might play crucial roles in response to water stress in O. sinensis by enhancing cell osmotic potential and producing osmoregulatory substances (betaine) and antioxidant pigments (eumelanin).

CONCLUSIONS

Overall, our findings provide important information for further exploration of the mechanism underlying the water stress tolerance of O. sinensis for the industrialization of artificial cultivation of Chinese cordyceps.

An updated resource for the detection of protein-coding circRNA with CircProPlus

Protein-encoding circular RNAs (circRNAs) are newly identified RNA molecules characterized by intense interaction with translating ribosome. Emerging evidence has implicated physiological and pathological significance of these non-canonical RNAs, yet a large body of them remains unidentified. Due to limited tools at hand, we developed CircProPlus, an automated computational pipeline for de novo detection of translated circRNAs. In comparison to previously established CircPro, CircProPlus adjusts the overall workflow and integrates more robust implements for achieving easier accessibility, higher flexibility and productivity. In present study, we tested the performance of CircProPlus when using different circRNA-detecting implements (i.e., CIRI2, CirComPara2) in the evaluation of coding ability of circRNAs. Results showed that CirComPara2, a state-of-the-art algorithm, consistently outperformed CIRI2 when coupled with CircProPlus in testing real data collected from different RNA libraries and species, which highlighted its potency in data mining of circRNAs with protein-coding potential.

Benchmarking of five NGS mapping tools for the reference alignment of bacterial outer membrane vesicles-associated small RNAs

Advances in small RNAs (sRNAs)-related studies have posed a challenge for NGS-related bioinformatics, especially regarding the correct mapping of sRNAs. Depending on the algorithms and scoring matrices on which they are based, aligners are influenced by the characteristics of the dataset and the reference genome. These influences have been studied mainly in eukaryotes and to some extent in prokaryotes. However, in bacteria, the selection of aligners depending on sRNA-seq data associated with outer membrane vesicles (OMVs) and the features of the corresponding bacterial reference genome has not yet been investigated. We selected five aligners: BBmap, Bowtie2, BWA, Minimap2 and Segemehl, known for their generally good performance, to test them in mapping OMV-associated sRNAs from Aliivibrio fischeri to the bacterial reference genome. Significant differences in the performance of the five aligners were observed, resulting in differential recognition of OMV-associated sRNA biotypes in A. fischeri. Our results suggest that aligner(s) should not be arbitrarily selected for this task, which is often done, as this can be detrimental to the biological interpretation of NGS analysis results. Since each aligner has specific advantages and disadvantages, these need to be considered depending on the characteristics of the input OMV sRNAs dataset and the corresponding bacterial reference genome to improve the detection of existing, biologically important OMV sRNAs. Until we learn more about these dependencies, we recommend using at least two, preferably three, aligners that have good metrics for the given dataset/bacterial reference genome. The overlapping results should be considered trustworthy, yet their differences should not be dismissed lightly, but treated carefully in order not to overlook any biologically important OMV sRNA. This can be achieved by applying the intersect-then-combine approach. For the mapping of OMV-associated sRNAs of A. fischeri to the reference genome organized into two circular chromosomes and one circular plasmid, containing copies of sequences with rRNA- and tRNA-related features and no copies of sequences with protein-encoding features, if the aligners are used with their default parameters, we advise avoiding Segemehl, and recommend using the intersect-then-combine approach with BBmap, BWA and Minimap2 to improve the potential for discovery of biologically important OMV-associated sRNAs.

RepEnTools: an automated repeat enrichment analysis package for ChIP-seq data reveals hUHRF1 Tandem-Tudor domain enrichment in young repeats

BACKGROUND

Repeat elements (REs) play important roles for cell function in health and disease. However, RE enrichment analysis in short-read high-throughput sequencing (HTS) data, such as ChIP-seq, is a challenging task.

RESULTS

Here, we present RepEnTools, a software package for genome-wide RE enrichment analysis of ChIP-seq and similar chromatin pulldown experiments. Our analysis package bundles together various software with carefully chosen and validated settings to provide a complete solution for RE analysis, starting from raw input files to tabular and graphical outputs. RepEnTools implementations are easily accessible even with minimal IT skills (Galaxy/UNIX). To demonstrate the performance of RepEnTools, we analysed chromatin pulldown data by the human UHRF1 TTD protein domain and discovered enrichment of TTD binding on young primate and hominid specific polymorphic repeats (SVA, L1PA1/L1HS) overlapping known enhancers and decorated with H3K4me1-K9me2/3 modifications. We corroborated these new bioinformatic findings with experimental data by qPCR assays using newly developed primate and hominid specific qPCR assays which complement similar research tools. Finally, we analysed mouse UHRF1 ChIP-seq data with RepEnTools and showed that the endogenous mUHRF1 protein colocalizes with H3K4me1-H3K9me3 on promoters of REs which were silenced by UHRF1. These new data suggest a functional role for UHRF1 in silencing of REs that is mediated by TTD binding to the H3K4me1-K9me3 double mark and conserved in two mammalian species.

CONCLUSIONS

RepEnTools improves the previously available programmes for RE enrichment analysis in chromatin pulldown studies by leveraging new tools, enhancing accessibility and adding some key functions. RepEnTools can analyse RE enrichment rapidly, efficiently, and accurately, providing the community with an up-to-date, reliable and accessible tool for this important type of analysis.

A compressive seeding algorithm in conjunction with reordering-based compression

MOTIVATION

Seeding is a rate-limiting stage in sequence alignment for next-generation sequencing reads. The existing optimization algorithms typically utilize hardware and machine-learning techniques to accelerate seeding. However, an efficient solution provided by professional next-generation sequencing compressors has been largely overlooked by far. In addition to achieving remarkable compression ratios by reordering reads, these compressors provide valuable insights for downstream alignment that reveal the repetitive computations accounting for more than 50% of seeding procedure in commonly used short read aligner BWA-MEM at typical sequencing coverage. Nevertheless, the exploited redundancy information is not fully realized or utilized.

RESULTS

In this study, we present a compressive seeding algorithm, named CompSeed, to fill the gap. CompSeed, in collaboration with the existing reordering-based compression tools, finishes the BWA-MEM seeding process in about half the time by caching all intermediate seeding results in compact trie structures to directly answer repetitive inquiries that frequently cause random memory accesses. Furthermore, CompSeed demonstrates better performance as sequencing coverage increases, as it focuses solely on the small informative portion of sequencing reads after compression. The innovative strategy highlights the promising potential of integrating sequence compression and alignment to tackle the ever-growing volume of sequencing data.

AVAILABILITY AND IMPLEMENTATION

CompSeed is available at https://github.com/i-xiaohu/CompSeed.

Quantum gate algorithm for reference-guided DNA sequence alignment

Reference-guided DNA sequencing and alignment is an important process in computational molecular biology. The amount of DNA data grows very fast, and many new genomes are waiting to be sequenced while millions of private genomes need to be re-sequenced. Each human genome has 3.2B base pairs, and each one could be stored with 2 bits of information, so one human genome would take 6.4B bits or ∼760MB of storage (National Institute of General Medical Sciences, n.d.). Today's most powerful tensor processing units cannot handle the volume of DNA data necessitating a major leap in computing power. It is, therefore, important to investigate the usefulness of quantum computers in genomic data analysis, especially in DNA sequence alignment. Quantum computers are expected to be involved in DNA sequencing, initially as parts of classical systems, acting as quantum accelerators. The number of available qubits is increasing annually, and future quantum computers could conduct DNA sequencing, taking the place of classical computing systems. We present a novel quantum algorithm for reference-guided DNA sequence alignment modeled with gate-based quantum computing. The algorithm is scalable, can be integrated into existing classical DNA sequencing systems and is intentionally structured to limit computational errors. The quantum algorithm has been tested using the quantum processing units and simulators provided by IBM Quantum, and its correctness has been confirmed.

Proteogenomics in Cancer: Then and Now

For years, the paths of sequencing technologies and mass spectrometry have occurred in isolation, with each developing its own unique culture and expertise. These two technologies are crucial for inspecting complementary aspects of the molecular phenotype across the central dogma. Integrative multiomics strives to bridge the analysis gap among different fields to complete more comprehensive mechanisms of life events and diseases. Proteogenomics is one integrated multiomics field. Here in this review, we mainly summarize and discuss three aspects: workflow of proteogenomics, proteogenomics applications in cancer research, and the SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis of proteogenomics in cancer research. In conclusion, proteogenomics has a promising future as it clarifies the functional consequences of many unannotated genomic abnormalities or noncanonical variants and identifies driver genes and novel therapeutic targets across cancers, which would substantially accelerate the development of precision oncology.

Exploration of Potential Target Genes of miR-24-3p in Chicken Myoblasts by Transcriptome Sequencing Analysis

Broiler skeletal muscle growth is significantly influenced by miRNAs. Our earlier research demonstrated that miR-24-3p significantly suppressed the proliferation of chicken myoblasts while promoting their differentiation. The purpose of this study is to investigate miR-24-3p potential target genes in chickens. We collected myoblasts of Jinghai yellow chicken and transfected four samples with mimics of miR-24-3p and another four samples with mimic NC (negative control) for RNA-seq. We obtained 54.34 Gb of raw data in total and 50.79 Gb of clean data remained after filtering. Moreover, 11,635 genes were found to be co-expressed in these two groups. The mimic vs. NC comparison group contained 189 DEGs in total, 119 of which were significantly up-regulated and 70 of which were significantly down-regulated. Important biological process (BP) terminology such as nuclear chromosomal segregation, reproduction, and nuclear division were discovered by GO enrichment analysis for DEGs in the mimic vs. NC comparison group. KEGG pathway analysis showed that focal adhesion, cytokine-cytokine receptor interaction, the TGF-β signaling pathway, and the MAPK signaling pathway were enriched in the top 20. Variation site analysis illustrated the SNP (single nucleotide polymorphisms) and INDEL (insertion-deletion) in the tested samples. By comparing the target genes predicted by miRDB (MicroRNA target prediction database) and TargetScan with the 189 DEGs found by the transcriptome sequencing, we discovered two up-regulated DEGs (NEURL1 and IQSEC3) and two down-regulated DEGs (REEP1 and ST6GAL1). Finally, we carried out qPCR experiments on eight DEGs and discovered that the qPCR results matched the sequencing outcomes. These findings will aid in identifying potential miR-24-3p target genes in chicken skeletal muscle and offer some new directions for upcoming research on broiler breeding.

Short-read aligner performance in germline variant identification

MOTIVATION

Read alignment is an essential first step in the characterization of DNA sequence variation. The accuracy of variant-calling results depends not only on the quality of read alignment and variant-calling software but also on the interaction between these complex software tools.

RESULTS

In this review, we evaluate short-read aligner performance with the goal of optimizing germline variant-calling accuracy. We examine the performance of three general-purpose short-read aligners-BWA-MEM, Bowtie 2, and Arioc-in conjunction with three germline variant callers: DeepVariant, FreeBayes, and GATK HaplotypeCaller. We discuss the behavior of the read aligners with regard to the data elements on which the variant callers rely, and illustrate how the runtime configurations of these software tools combine to affect variant-calling performance.

AVAILABILITY AND IMPLEMENTATION

The quick brown fox jumps over the lazy dog.