Next-generation DNA sequencing

Łabaj P, Mangul S. RNA-seq data science: From raw data to effective interpretation

RNA sequencing (RNA-seq) has become an exemplary technology in modern biology and clinical science. Its immense popularity is due in large part to the continuous efforts of the bioinformatics community to develop accurate and scalable computational tools to analyze the enormous amounts of transcriptomic data that it produces. RNA-seq analysis enables genes and their corresponding transcripts to be probed for a variety of purposes, such as detecting novel exons or whole transcripts, assessing expression of genes and alternative transcripts, and studying alternative splicing structure. It can be a challenge, however, to obtain meaningful biological signals from raw RNA-seq data because of the enormous scale of the data as well as the inherent limitations of different sequencing technologies, such as amplification bias or biases of library preparation. The need to overcome these technical challenges has pushed the rapid development of novel computational tools, which have evolved and diversified in accordance with technological advancements, leading to the current myriad of RNA-seq tools. These tools, combined with the diverse computational skill sets of biomedical researchers, help to unlock the full potential of RNA-seq. The purpose of this review is to explain basic concepts in the computational analysis of RNA-seq data and define discipline-specific jargon.

Extensive sequence duplication in Arabidopsis revealed by pseudo-heterozygosity

BACKGROUND

It is apparent that genomes harbor much structural variation that is largely undetected for technical reasons. Such variation can cause artifacts when short-read sequencing data are mapped to a reference genome. Spurious SNPs may result from mapping of reads to unrecognized duplicated regions. Calling SNP using the raw reads of the 1001 Arabidopsis Genomes Project we identified 3.3 million (44%) heterozygous SNPs. Given that Arabidopsis thaliana (A. thaliana) is highly selfing, and that extensively heterozygous individuals have been removed, we hypothesize that these SNPs reflected cryptic copy number variation.

RESULTS

The heterozygosity we observe consists of particular SNPs being heterozygous across individuals in a manner that strongly suggests it reflects shared segregating duplications rather than random tracts of residual heterozygosity due to occasional outcrossing. Focusing on such pseudo-heterozygosity in annotated genes, we use genome-wide association to map the position of the duplicates. We identify 2500 putatively duplicated genes and validate them using de novo genome assemblies from six lines. Specific examples included an annotated gene and nearby transposon that transpose together. We also demonstrate that cryptic structural variation produces highly inaccurate estimates of DNA methylation polymorphism.

CONCLUSIONS

Our study confirms that most heterozygous SNP calls in A. thaliana are artifacts and suggest that great caution is needed when analyzing SNP data from short-read sequencing. The finding that 10% of annotated genes exhibit copy-number variation, and the realization that neither gene- nor transposon-annotation necessarily tells us what is actually mobile in the genome suggests that future analyses based on independently assembled genomes will be very informative.

Encouraging news for in situ conservation: Translocation of salamander larvae has limited impacts on their skin microbiota

The key role of symbiotic skin bacteria communities in amphibian resistance to emerging pathogens is well recognized, but factors leading to their dysbiosis are not fully understood. In particular, the potential effects of population translocations on the composition and diversity of hosts' skin microbiota have received little attention, although such transfers are widely carried out as a strategy for amphibian conservation. To characterize the potential reorganization of the microbiota over such a sudden environmental change, we conducted a common-garden experiment simulating reciprocal translocations of yellow-spotted salamander larvae across three lakes. We sequenced skin microbiota samples collected before and 15 days after the transfer. Using a database of antifungal isolates, we identified symbionts with known function against the pathogen Batrachochytrium dendrobatidis, a major driver of amphibian declines. Our results indicate an important reorganization of bacterial assemblages throughout ontogeny, with strong changes in composition, diversity and structure of the skin microbiota in both control and translocated individuals over the 15 days of monitoring. Unexpectedly, the diversity and community structure of the microbiota were not significantly affected by the translocation event, thus suggesting a strong resilience of skin bacterial communities to environmental change-at least across the time-window studied here. A few phylotypes were more abundant in the microbiota of translocated larvae, but no differences were found among pathogen-inhibiting symbionts. Taken together, our results support amphibian translocations as a promising strategy for this endangered animal class, with limited impact on their skin microbiota.

Developmental validation of the ForenSeq MainstAY kit, MiSeq FGx sequencing system and ForenSeq Universal Analysis Software

For human identification purposes, forensic genetics has primarily relied upon a core set of autosomal (and to a lesser extent Y chromosome) short tandem repeat (STR) markers that are enriched by amplification using the polymerase chain reaction (PCR) that are subsequently separated and detected using capillary electrophoresis (CE). While STR typing conducted in this manner is well-developed and robust, advances in molecular biology that have occurred over the last 15 years, in particular massively parallel sequencing (MPS) [1-7], offer certain advantages as compared to CE-based typing. First and foremost is the high throughput capacity of MPS. Current bench top high throughput sequencers enable larger batteries of markers to be multiplexed and multiple samples to be sequenced simultaneously (e.g., millions to billions of nucleotides can be sequenced in one run). Second, compared to the length-based CE approach, sequencing STRs increases discrimination power, enhances sensitivity of detection, reduces noise due to instrumentation, and improves mixture interpretation [4,8-23]. Third, since detection of STRs is based on sequence and not fluorescence, amplicons can be designed that are shorter in length and of similar lengths among loci, where possible, which can improve amplification efficiency and analysis of degraded samples. Lastly, MPS offers a single format approach that can be applied to analysis of a wide variety of genetic markers of forensic interest (e.g., STRs, mitochondrial DNA, single nucleotide polymorphisms, insertion/deletions). These features make MPS a desirable technology for casework [14,15,24,25-48]. The developmental validation of the ForenSeq MainstAY library preparation kit with the MiSeq FGx Sequencing System and ForenSeq Universal Software is reported here to assist with validation of this MPS system for casework [49]. The results show that the system is sensitive, accurate and precise, specific, and performs well with mixtures and mock case-type samples.

Genetic analysis for detection of genes associated to drought tolerance in rice accessions belonging to north east India

INTRODUCTION

The North East (NE) India is rich in biodiversity and also considered as the secondary centre for origin of rice. The NE rice accessions was characterized previously using genetic markers and morphological traits. Simultaneously, genome-wide association studies (GWAS) reveal significant marker-trait associations for the drought tolerance traits.

METHODS AND RESULTS

The genetic diversity and population structure of 296 NE rice accessions were studied using 96,712 single nucleotide polymorphism (SNP) markers distributed across 12 chromosomes. The accessions were clustered into two major sub-groups (SG). A total of 91 accessions were assembled as SG1 and 114 accessions as SG2, while the remaining 91 were admixture genotypes. A total of 200 genotypes belonging to different groups were phenotyped for yield component traits under drought and control conditions. The GWAS was performed to identify significant marker-trait associations (MTAs). Consequently, 47 MTAs were detected under drought, exhibiting 0.02-9.95% of phenotypic variance (P.V.). Whereas 58 MTAs were discovered under control conditions, showing a 0.01-9.74% contribution to the phenotype. Through in-silico mining of QTLs, 2999 genes were identified. Among these; only 22 genes were directly associated with stress response.

CONCLUSION

These QTLs/genes may be deployed for marker-assisted pyramiding to improve drought tolerance in popular drought susceptible rice varieties.

Insight into molecular diagnosis for antimalarial drug resistance of Plasmodium falciparum parasites: A review

Malaria is an infectious disease transmitted by the female Anopheles mosquito and poses a severe threat to human health. At present, antimalarial drugs are the primary treatment for malaria. The widespread use of artemisinin-based combination therapies (ACTs) has dramatically reduced the number of malaria-related deaths; however, the emergence of resistance has the potential to reverse this progress. Accurate and timely diagnosis of drug-resistant strains of Plasmodium parasites via detecting molecular markers (such as Pfnhe1, Pfmrp, Pfcrt, Pfmdr1, Pfdhps, Pfdhfr, and Pfk13) is essential for malaria control and elimination. Here, we review the current techniques which commonly used for molecular diagnosis of antimalarial resistance in P. falciparum and discuss their sensitivities and specificities for different drug resistance-associated molecular markers, with the aim of providing insights into possible directions for future precise point-of-care testing (POCT) of antimalarial drug resistance of malaria parasites.

Molecular Accounting and Profiling of Human Respiratory Microbial Communities: Toward Precision Medicine by Targeting the Respiratory Microbiome for Disease Diagnosis and Treatment

The wide diversity of microbiota at the genera and species levels across sites and individuals is related to various causes and the observed differences between individuals. Efforts are underway to further understand and characterize the human-associated microbiota and its microbiome. Using 16S rDNA as a genetic marker for bacterial identification improved the detection and profiling of qualitative and quantitative changes within a bacterial population. In this light, this review provides a comprehensive overview of the basic concepts and clinical applications of the respiratory microbiome, alongside an in-depth explanation of the molecular targets and the potential relationship between the respiratory microbiome and respiratory disease pathogenesis. The paucity of robust evidence supporting the correlation between the respiratory microbiome and disease pathogenesis is currently the main challenge for not considering the microbiome as a novel druggable target for therapeutic intervention. Therefore, further studies are needed, especially prospective studies, to identify other drivers of microbiome diversity and to better understand the changes in the lung microbiome along with the potential association with disease and medications. Thus, finding a therapeutic target and unfolding its clinical significance would be crucial.

Specific-Locus Amplified Fragment Sequencing (SLAF-Seq)

Specific length amplified fragment sequencing (SLAF-seq) technology is a simplified genome sequencing technology based on next-generation sequencing. SLAF-seq technology has several distinguishing characteristics: 1. Deep sequencing to ensure accuracy of genotyping; 2. Effectively reduce sequencing costs; 3. Pre-designed simplified representation scheme to optimize marker efficiency; 4. Doubled barcode system for large populations. The advantages and technical process of SLAF-seq are described briefly with summarized results for the application of SLAF-seq in development of molecular markers, construction of high-density genetic map and gene mapping in ornamental plants. Finally, the difficulties and prospects of this method are discussed in application.

Microbiome Changes in Pregnancy Disorders

The human microbiota comprises all microorganisms, such as bacteria, fungi, and viruses, found within a specific environment that live on our bodies and inside us. The last few years have witnessed an explosion of information related to the role of microbiota changes in health and disease. Even though the gut microbiota is considered the most important in maintaining our health, other regions of the human body, such as the oral cavity, lungs, vagina, and skin, possess their own microbiota. Recent work suggests a correlation between the microbiota present during pregnancy and pregnancy complications. The aim of our literature review was to provide a broad overview of this growing and important topic. We focused on the most significant changes in the microbiota in the four more common obstetric diseases affecting women's health. Thus, our attention will be focused on hypertensive disorders, gestational diabetes mellitus, preterm birth, and recurrent miscarriage. Pregnancy is a unique period in a woman's life since the body undergoes different adaptations to provide an optimal environment for fetal growth. Such changes also involve all the microorganisms, which vary in composition and quantity during the three trimesters of gestation. In addition, special attention will be devoted to the potential and fundamental advances in developing clinical applications to prevent and treat those disorders by modulating the microbiota to develop personalized therapies for disease prevention and tailored treatments.

Combining sensors and actuators with electrowetting-on-dielectric (EWOD): advanced digital microfluidic systems for biomedical applications

The concept of digital microfluidics (DMF) enables highly flexible and precise droplet manipulation at a picoliter scale, making DMF a promising approach to realize integrated, miniaturized "lab-on-a-chip" (LOC) systems for research and clinical purposes. Owing to its simplicity and effectiveness, electrowetting-on-dielectric (EWOD) is one of the most commonly studied and applied effects to implement DMF. However, complex biomedical assays usually require more sophisticated sample handling and detection capabilities than basic EWOD manipulation. Alternatively, combined systems integrating EWOD actuators and other fluidic handling techniques are essential for bringing DMF into practical use. In this paper, we briefly review the main approaches for the integration/combination of EWOD with other microfluidic manipulation methods or additional external fields for specified biomedical applications. The form of integration ranges from independently operating sub-systems to fully coupled hybrid actuators. The corresponding biomedical applications of these works are also summarized to illustrate the significance of these innovative combination attempts.

Intra-Exon Motif Correlations as a Proxy Measure for Mean Per-Tile Sequence Quality Data in RNA-Seq

Given the wide variability in the quality of next-generation sequencing data submitted to public repositories, it is essential to identify methods that can perform quality control on these data sets when additional quality control data, such as mean tile data, are missing from public repositories. In this study, we present evidence that correlating counts of reads corresponding to pairs of motifs separated over specific distances on individual exons can be used as a proxy mean tile data in the data sets we analyzed and hence could be used when mean tile data are not available. As test data sets we use the Homo sapiens in vitro transcribed (IVT) data set, and a Drosophila melanogaster data set comprising wild and mutant types. We find that a FastQC analysis of the available parts of these data sets demonstrates that the per-tile sequencing quality is good for all the data sets apart from the mutant-type data where the mutant-r3 data are worse than the mutant-r2 data. Correspondingly, intra-exon motif correlations are reasonably large for all data sets except this latter case where the mutant-r2 correlations are low and the mutant-r3 correlations close to zero. We propose that these extremely low correlations are indicative of bias of technical origin, such as flowcell errors. In addition to this, the intra-exon motif correlations as a function of both guanosine-cytosine (GC) content parameters are somewhat higher and less dependent on the GC content parameters in the IVT-Plasmids messenger RNA (mRNA) selection free RNA-Seq sample (control) than in the other RNA-Seq samples that did undergo mRNA selection: both ribosomal depletion (IVT-Only) and PolyA selection (IVT-PolyA, wild type, and mutant).

Liquid Biopsy for Lung Cancer: Up-to-Date and Perspectives for Screening Programs

Lung cancer is the deadliest cancer worldwide. Tissue biopsy is currently employed for the diagnosis and molecular stratification of lung cancer. Liquid biopsy is a minimally invasive approach to determine biomarkers from body fluids, such as blood, urine, sputum, and saliva. Tumor cells release cfDNA, ctDNA, exosomes, miRNAs, circRNAs, CTCs, and DNA methylated fragments, among others, which can be successfully used as biomarkers for diagnosis, prognosis, and prediction of treatment response. Predictive biomarkers are well-established for managing lung cancer, and liquid biopsy options have emerged in the last few years. Currently, detecting EGFR p.(Tyr790Met) mutation in plasma samples from lung cancer patients has been used for predicting response and monitoring tyrosine kinase inhibitors (TKi)-treated patients with lung cancer. In addition, many efforts continue to bring more sensitive technologies to improve the detection of clinically relevant biomarkers for lung cancer. Moreover, liquid biopsy can dramatically decrease the turnaround time for laboratory reports, accelerating the beginning of treatment and improving the overall survival of lung cancer patients. Herein, we summarized all available and emerging approaches of liquid biopsy-techniques, molecules, and sample type-for lung cancer.

Measurable Residual Disease and Clonal Evolution in Acute Myeloid Leukemia from Diagnosis to Post-Transplant Follow-Up: The Role of Next-Generation Sequencing

It has now been ascertained that acute myeloid leukemias-as in most type of cancers-are mixtures of various subclones, evolving by acquiring additional somatic mutations over the course of the disease. The complexity of leukemia clone architecture and the phenotypic and/or genotypic drifts that can occur during treatment explain why more than 50% of patients-in hematological remission-could relapse. Moreover, the complexity and heterogeneity of clone architecture represent a hindrance for monitoring measurable residual disease, as not all minimal residual disease monitoring methods are able to detect genetic mutations arising during treatment. Unlike with chemotherapy, which imparts a relatively short duration of selective pressure on acute myeloid leukemia clonal architecture, the immunological effect related to allogeneic hematopoietic stem cell transplant is prolonged over time and must be overcome for relapse to occur. This means that not all molecular abnormalities detected after transplant always imply inevitable relapse. Therefore, transplant represents a critical setting where a measurable residual disease-based strategy, performed during post-transplant follow-up by highly sensitive methods such as next-generation sequencing, could optimize and improve treatment outcome. The purpose of our review is to provide an overview of the role of next-generation sequencing in monitoring both measurable residual disease and clonal evolution in acute myeloid leukemia patients during the entire course of the disease, with special focus on the transplant phase.

De Novo Transcriptome Assembly and EST-SSR Marker Development and Application in Chrysosplenium macrophyllum

Chrysosplenium macrophyllum Oliv., belonging to the family Saxifragaceae, is a traditional and unique Chinese herbal medicine. However, the lack of adequate molecular markers has hampered the progress regarding population genetics and evolution within this species. In this research, we used the DNBSEQ-T7 Sequencer (MGI) sequencing assay to analyze the transcriptome profiles of C. macrophyllum. SSR markers were developed on the basis of transcriptomic sequences and further validated on C. macrophyllum and other Chrysosplenium species. The genetic diversity and structure of the 12 populations were analyzed by using polymorphic expressed sequence tag simple sequence repeat (EST-SSR) markers. A potential pool of 3127 non-redundant EST-SSR markers were identified for C. macrophyllum in this study. The developed EST-SSR markers had high amplification rates and cross-species transferability in Chrysosplenium. Our results also showed that the natural populations of C. macrophyllum had a high level of genetic diversity. Genetic distance, principal component analysis, and popular structure analysis revealed that all 60 samples clustered into two major groups that were consistent with their geographical origins. This study provided a batch of highly polymorphic EST-SSR molecular markers that were developed via transcriptome sequencing. These markers will be of great significance for the study of the genetic diversity and evolutionary history of C. macrophyllum and other Chrysosplenium species.

Methods to improve the accuracy of next-generation sequencing

Next-generation sequencing (NGS) is present in all fields of life science, which has greatly promoted the development of basic research while being gradually applied in clinical diagnosis. However, the cost and throughput advantages of next-generation sequencing are offset by large tradeoffs with respect to read length and accuracy. Specifically, its high error rate makes it extremely difficult to detect SNPs or low-abundance mutations, limiting its clinical applications, such as pharmacogenomics studies primarily based on SNP and early clinical diagnosis primarily based on low abundance mutations. Currently, Sanger sequencing is still considered to be the gold standard due to its high accuracy, so the results of next-generation sequencing require verification by Sanger sequencing in clinical practice. In order to maintain high quality next-generation sequencing data, a variety of improvements at the levels of template preparation, sequencing strategy and data processing have been developed. This study summarized the general procedures of next-generation sequencing platforms, highlighting the improvements involved in eliminating errors at each step. Furthermore, the challenges and future development of next-generation sequencing in clinical application was discussed.

A Step toward Amino Acid-Labeled DNA Sequencing: Boosting Transmission Sensitivity of Graphene Nanogap

Existing obstacles in next-generation DNA sequencing techniques, for instance, high noise, high translocation speed, and configurational fluctuations, call for approaches capable of reaching the goal and accelerating the process of personalized medicine development. The labeling nucleotide approach has the potential to overcome these barriers and boost the recognition sensitivity of a solid-state nanodevice. In this theoretical report, the first-principles density functional theory calculations have been employed to study the role of three different labels, tyrosine (Tyr), aspartic acid (Asp), and arginine (Arg), for labeling DNA nucleotides and study their effect in rapid and controlled DNA sequencing at atomic resolution. Remarkable differences in interaction energy values are noticed in all three cases of differently labeled nucleotides. The zero-bias transmission spectra confirm that proposed labels have the ability to detect the individual nucleotide, amplifying the tunneling current sensitivity by several orders of magnitude. The current-voltage characteristics of Arg-labeled nucleotides are found to be promising for single nucleotide recognition even at a very low bias voltage of 0.1 V.

Analysis of mutational genotyping using correctable decoding sequencing with superior specificity

The ability to accurately identify SNPs or low-abundance mutations is important for early clinical diagnosis of diseases, but the existing high-throughput sequencing platforms are limited in terms of their accuracy. Here, we propose a correctable decoding sequencing strategy that may be used for high-throughput sequencing platforms. This strategy is based on adding a mixture of two types of mononucleotides, natural nucleotide and cyclic reversible termination (CRT), for cyclic sequencing. Using the synthetic characteristic of CRTs, about 75% of the calls are unambiguous for a single sequencing run, and the remaining ambiguous sequence can be accurately deduced by two parallel sequencing runs. We demonstrate the feasibility of this strategy, and its cycle efficiency can reach approximately 99.3%. This strategy is proved to be effective for correcting errors and identifying whether the sequencing information is correct or not. And its conservative theoretical error rate was determined to be 0.0009%, which is lower than that of Sanger sequencing. In addition, we establish that the information of only a single sequencing run can be used to detect samples with known mutation sites. We apply this strategy to accurately identify a mutation site in mitochondrial DNA from human cells.

DNA and RNA Alterations Associated with Colorectal Peritoneal Metastases: A Systematic Review

BACKGROUND

As colorectal cancer (CRC) patients with peritoneal metastases (PM) have a poor prognosis, new treatment options are currently being investigated for CRC patients. Specific biomarkers in the primary tumor could serve as a prediction tool to estimate the risk of distant metastatic spread. This would help identify patients eligible for early treatment.

AIM

To give an overview of previously studied DNA and RNA alterations in the primary tumor correlated to colorectal PM and investigate which gene mutations should be further studied.

METHODS

A systematic review of all published studies reporting genomic analyses on the primary tissue of CRC tumors in relation to PM was undertaken according to PRISMA guidelines.

RESULTS

Overall, 32 studies with 18,906 patients were included. BRAF mutations were analyzed in 17 articles, of which 10 found a significant association with PM. For all other reported genes, no association with PM was found. Two analyses with broader cancer panels did not reveal any new biomarkers.

CONCLUSION

An association of specific biomarkers in the primary tumors of CRC patients with metastatic spread into peritoneum could not be proven. The role of BRAF mutations should be further investigated. In addition, studies searching for potential novel biomarkers are still required.

Towards a graphene semi/hybrid-nanogap: a new architecture for ultrafast DNA sequencing

The tremendous upsurge in the research of next-generation sequencing (NGS) methods has broadly been driven by the rise of the wonder material graphene and continues to dominate the futuristic approaches for fast and accurate DNA sequencing. The success of graphene has also triggered the search for many new potential NGS methods capable of ultrafast, reliable, and controlled DNA sequencing. The present study delves into the potential of a new NGS architecture utilizing graphene, namely, a 'semi/hybrid-nanogap' for the identification of DNA nucleobases with single-base resolution. In the framework of first-principles density functional theory methods, we have calculated the transmission function and current-voltage (I-V) characteristics which are of particular significance for DNA sequencing applications. It is noted that the interaction energy values are significantly reduced compared to the previously reported graphene nanodevices, which can lead to a controlled translocation during experimental measurements. Based on the transmission function, each nucleobase can be identified with pertinent sensitivity. It is noticed that the use of highly conductive nucleobase analogs can facilitate improved single nucleobase sensing by increasing the transmission sensitivity. Therefore, we believe that the present study opens up promising frontiers for sequencing applications.

HMMerge: an ensemble method for multiple sequence alignment

Motivation

Despite advances in method development for multiple sequence alignment over the last several decades, the alignment of datasets exhibiting substantial sequence length heterogeneity, especially when the input sequences include very short sequences (either as a result of sequencing technologies or of large deletions during evolution) remains an inadequately solved problem.

Results

We present HMMerge, a method to compute an alignment of datasets exhibiting high sequence length heterogeneity, or to add short sequences into a given 'backbone' alignment. HMMerge builds on the technique from its predecessor alignment methods, UPP and WITCH, which build an ensemble of profile HMMs to represent the backbone alignment and add the remaining sequences into the backbone alignment using the ensemble. HMMerge differs from UPP and WITCH by building a new 'merged' HMM from the ensemble, and then using that merged HMM to align the query sequences. We show that HMMerge is competitive with WITCH, with an advantage over WITCH when adding very short sequences into backbone alignments.

Availability and implementation

HMMerge is freely available at https://github.com/MinhyukPark/HMMerge.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Next-generation sequencing and molecular therapy

Cancers contain a plethora of mutations, few of which are critical to maintaining a state of malignancy. With our ever-expanding understanding of the genomic complexity of cancer, potentially actionable biomarkers whose inhibition could cripple cancer growth are increasingly being elucidated. Modern cancer drug development has largely switched from cytotoxic agents to targeted therapies and immunotherapy, with noteworthy success in several cancer types including non-small-cell lung cancer (NSCLC), breast cancer and melanoma. Next-generation sequencing offers high-throughput, widescale genomic interrogation in a far more efficient and affordable manner than previous sequencing methods. This facilitates detection of potentially actionable mutations and fusions for individual patients and contributes to the identification of novel predictive and prognostic biomarkers in a population. Challenges in the technical aspects of biopsy and sequencing, interpretation, and development of targeted therapies against common genomic aberrations will need to be addressed for personalised medicine to become a reality for more patients with cancer.

Recent advances in machine learning applications in metabolic engineering

Metabolic engineering encompasses several widely-used strategies, which currently hold a high seat in the field of biotechnology when its potential is manifesting through a plethora of research and commercial products with a strong societal impact. The genomic revolution that occurred almost three decades ago has initiated the generation of large omics-datasets which has helped in gaining a better understanding of cellular behavior. The itinerary of metabolic engineering that has occurred based on these large datasets has allowed researchers to gain detailed insights and a reasonable understanding of the intricacies of biosystems. However, the existing trail-and-error approaches for metabolic engineering are laborious and time-intensive when it comes to the production of target compounds with high yields through genetic manipulations in host organisms. Machine learning (ML) coupled with the available metabolic engineering test instances and omics data brings a comprehensive and multidisciplinary approach that enables scientists to evaluate various parameters for effective strain design. This vast amount of biological data should be standardized through knowledge engineering to train different ML models for providing accurate predictions in gene circuits designing, modification of proteins, optimization of bioprocess parameters for scaling up, and screening of hyper-producing robust cell factories. This review briefs on the premise of ML, followed by mentioning various ML methods and algorithms alongside the numerous omics datasets available to train ML models for predicting metabolic outcomes with high-accuracy. The combinative interplay between the ML algorithms and biological datasets through knowledge engineering have guided the recent advancements in applications such as CRISPR/Cas systems, gene circuits, protein engineering, metabolic pathway reconstruction, and bioprocess engineering. Finally, this review addresses the probable challenges of applying ML in metabolic engineering which will guide the researchers toward novel techniques to overcome the limitations.

T-cell repertoire diversity: friend or foe for protective antitumor response?

Profiling the T-Cell Receptor (TCR) repertoire is establishing as a potent approach to investigate autologous and treatment-induced antitumor immune response. Technical and computational breakthroughs, including high throughput next-generation sequencing (NGS) approaches and spatial transcriptomics, are providing unprecedented insight into the mechanisms underlying antitumor immunity. A precise spatiotemporal variation of T-cell repertoire, which dynamically mirrors the functional state of the evolving host-cancer interaction, allows the tracking of the T-cell populations at play, and may identify the key cells responsible for tumor eradication, the evaluation of minimal residual disease and the identification of biomarkers of response to immunotherapy. In this review we will discuss the relationship between global metrics characterizing the TCR repertoire such as T-cell clonality and diversity and the resultant functional responses. In particular, we will explore how specific TCR repertoires in cancer patients can be predictive of prognosis or response to therapy and in particular how a given TCR re-arrangement, following immunotherapy, can predict a specific clinical outcome. Finally, we will examine current improvements in terms of T-cell sequencing, discussing advantages and challenges of current methodologies.

Analysis of Copy Number Variation in the Whole Genome of Normal-Haired and Long-Haired Tianzhu White Yaks

Long-haired individuals in the Tianzhu white yak population are a unique genetic resource, and have important landscape value. Copy number variation (CNV) is an important source of phenotypic variation in mammals. In this study, we used resequencing technology to detect the whole genome of 10 long-haired Tianzhu white yaks (LTWY) and 10 normal-haired Tianzhu white yaks (NTWY), and analyzed the differences of CNV in the genome of LTWYs and NTWYs. A total of 110268 CNVs were identified, 2006 CNVRs were defined, and the distribution map of these CNVRs on chromosomes was constructed. The comparison of LTWYs and NTWYs identified 80 differential CNVR-harbored genes, which were enriched in lipid metabolism, cell migration and other functions. Notably, some differential genes were identified as associated with hair growth and hair-follicle development (e.g., ASTN2, ATM, COL22A1, GK5, SLIT3, PM20D1, and SGCZ). In general, we present the first genome-wide analysis of CNV in LTWYs and NTWYs. Our results can provide new insights into the phenotypic variation of different hair lengths in Tianzhu white yaks.

Reading Information Stored in Synthetic Macromolecules

The storage of information in synthetic (macro)molecules provides an attractive alternative for current archival storage media, and the advancements made within this area have prompted the investigation of such molecules for numerous other applications (e.g., anti-counterfeiting tags, steganography). While different strategies have been described for storing information at the molecular level, this Perspective aims to provide a critical overview of the most prominent approaches that can be utilized for retrieving the encoded information. The major part will focus on the sequence determination of synthetic macromolecules, wherein information is stored by the precise arrangement of constituting monomers, with an emphasis on chemically aided strategies, (tandem) mass spectrometry, and nanopore sensing. In addition, recent progress in utilizing (mixtures of) small molecules for information storage will be discussed. Finally, the closing remarks aim to highlight which strategy we believe is the most suitable for a series of specific applications, and will also touch upon the future research avenues that can be pursued for reading (macro)molecular information.

Application of second-generation sequencing in congenital pulmonary airway malformations

To investigate the differential expression of genes in whole transcripts of congenital pulmonary airway malformation (CPAM) using second-generation sequencing (also known as next-generation sequencing, NGS) technology. Children with CPAM were strictly screened after setting the criteria, and grouped by taking CPAM parietal tissue and CPAM lesion tissue respectively, and RNA-Seq libraries were established separately using second-generation sequencing technology, followed by differential expression analysis and GO (gene ontology) functional enrichment analysis, KEGG (Kyoto encyclopedia of genes and genomes, a database) pathway analysis and GSEA (Gene Set Enrichment Analysis) analysis. Five cases were screened from 36 children with CPAM, and high-throughput sequencing was performed to obtain 10 whole transcripts of samples with acceptable sequence quality and balanced gene coverage. One aberrantly expressed sample (3b) was found by analysis of principal components, which was excluded and then subjected to differential expression analysis, and 860 up-regulated genes and 203 down-regulated genes. GO functional enrichment analysis of differentially expressed genes demonstrates the functional class and cellular localization of target genes. The whole transcript of CPAM shows obvious gene up and down-regulation, differentially expressed genes are located in specific cells and belong to different functional categories, and NGS can provide an effective means to study the transcriptional regulation of CPAM from the overall transcriptional level.

Medicine and health of 21st Century: Not just a high biotech-driven solution

Many biotechnological innovations have shaped the contemporary healthcare system (CHS) with significant progress to treat or cure several acute conditions and diseases of known causes (particularly infectious, trauma). Some have been successful while others have created additional health care challenges. For example, a reliance on drugs has not been a panacea to meet the challenges related to multifactorial noncommunicable diseases (NCDs)-the main health burden of the 21st century. In contrast, the advent of omics-based and big data technologies has raised global hope to predict, treat, and/or cure NCDs, effectively fight even the current COVID-19 pandemic, and improve overall healthcare outcomes. Although this digital revolution has introduced extensive changes on all aspects of contemporary society, economy, firms, job market, and healthcare management, it is facing and will face several intrinsic and extrinsic challenges, impacting precision medicine implementation, costs, possible outcomes, and managing expectations. With all of biotechnology's exciting promises, biological systems' complexity, unfortunately, continues to be underestimated since it cannot readily be compartmentalized as an independent and segregated set of problems, and therefore is, in a number of situations, not readily mimicable by the current algorithm-building proficiency tools. Although the potential of biotechnology is motivating, we should not lose sight of approaches that may not seem as glamorous but can have large impacts on the healthcare of many and across disparate population groups. A balanced approach of "omics and big data" solution in CHS along with a large scale, simpler, and suitable strategies should be defined with expectations properly managed.

Toward Precision Radiotherapy: A Nonlinear Optimization Framework and an Accelerated Machine Learning Algorithm for the Deconvolution of Tumor-Infiltrating Immune Cells

Tumor-infiltrating immune cells (TIICs) form a critical part of the ecosystem surrounding a cancerous tumor. Recent advances in radiobiology have shown that, in addition to damaging cancerous cells, radiotherapy drives the upregulation of immunosuppressive and immunostimulatory TIICs, which in turn impacts treatment response. Quantifying TIICs in tumor samples could form an important predictive biomarker guiding patient stratification and the design of radiotherapy regimens and combined immune-radiation treatments. As a result of several limitations associated with experimental methods for quantifying TIICs and the availability of extensive gene sequencing data, deconvolution-based computational methods have appeared as a suitable alternative for quantifying TIICs. Accordingly, we introduce and discuss a nonlinear regression approach (remarkably different from the traditional linear modeling approach of current deconvolution-based methods) and a machine learning algorithm for approximating the solution of the resulting constrained optimization problem. This way, the deconvolution problem is treated naturally, given that the gene expression levels of pure and heterogenous samples do not have a strictly linear relationship. When applied across transcriptomics datasets, our approach, which also allows the coupling of different loss functions, yields results that closely match ground-truth values from experimental methods and exhibits superior performance over popular deconvolution-based methods.

Identification and characterization of mixed infections of Chlamydia trachomatis via high-throughput sequencing

Precise genotyping is necessary to understand epidemiology and clinical manifestations of Chlamydia trachomatis infection with different genotypes. Next-generation high-throughput sequencing (NGHTS) has opened new frontiers in microbial genotyping, but has been clinically characterized in only a few settings. This study aimed to determine C. trachomatis genotypes in particular mixed-genotype infections and their association with clinical manifestations and to characterize the sensitivity and accuracy of NGHTS. Cervical specimens were collected from 8,087 subjects from physical examination center (PEC), assisted reproductive technology center (ART) and gynecology clinics (GC) of Chenzhou Hospital of China. The overall prevalence of C. trachomatis was 3.8% (311/8087) whereas a prevalence of 2.8, 3.7 and 4.8% was found in PEC, ART and GC, respectively. The most frequent three C. trachomatis genotypes were E (27.4%, 83/303), F (21.5%, 65/303) and J (18.2%, 55/303). Moreover, NGHTS identified 20 (6.6%, 20/303) mixed-genotype infections of C. trachomatis. Genotype G was more often observed in the subjects with pelvic inflammatory disease than genotype E (adjusted OR = 3.61, 95%CI, 1.02-12.8, p = 0.046). Mixed-genotype infection was associated with severe vaginal cleanliness (degree IV) with an adjusted OR of 5.17 (95%CI 1.03-25.9, p = 0.046) whereas mixed-genotype infection with large proportion of minor genotypes was associated with cervical squamous intraepithelial lesion (SIL) with an adjusted OR of 5.51 (95%CI 1.17-26.01, p = 0.031). Our results indicated that NGHTS is a feasible tool to identity C. trachomatis mixed-genotype infections, which may be associated with worse vaginal cleanliness and cervical SIL.

Utilization of Genotyping-by-Sequencing (GBS) for Rice Pre-Breeding and Improvement: A Review

Molecular markers play a crucial role in the improvement of rice. To benefit from these markers, genotyping is carried out to identify the differences at a specific position in the genome of individuals. The advances in sequencing technologies have led to the development of different genotyping techniques such as genotyping-by-sequencing. Unlike PCR-fragment-based genotyping, genotyping-by-sequencing has enabled the parallel sequencing and genotyping of hundreds of samples in a single run, making it more cost-effective. Currently, GBS is being used in several pre-breeding programs of rice to identify beneficial genes and QTL from different rice genetic resources. In this review, we present the current advances in the utilization of genotyping-by-sequencing for the development of rice pre-breeding materials and the improvement of existing rice cultivars. The challenges and perspectives of using this approach are also highlighted.

Ecological and Oceanographic Perspectives in Future Marine Fungal Taxonomy

Marine fungi are an ecological rather than a taxonomic group that has been widely researched. Significant progress has been made in documenting their phylogeny, biodiversity, ultrastructure, ecology, physiology, and capacity for degradation of lignocellulosic compounds. This review (concept paper) summarizes the current knowledge of marine fungal diversity and provides an integrated and comprehensive view of their ecological roles in the world's oceans. Novel terms for 'semi marine fungi' and 'marine fungi' are proposed based on the existence of fungi in various oceanic environments. The major maritime currents and upwelling that affect species diversity are discussed. This paper also forecasts under-explored regions with a greater diversity of marine taxa based on oceanic currents. The prospects for marine and semi-marine mycology are highlighted, notably, technological developments in culture-independent sequencing approaches for strengthening our present understanding of marine fungi's ecological roles.

Advancements and future prospective of DNA barcodes in the herbal drug industry

Ethnopharmacological relevance: The past couple of decades have witnessed the global resurgence of medicinal plants in the field of herbal-based health care. Increased consumption of medicinal plants and their derivative products is the major cause of the adulteration issues in herbal industries. As a result, the quality of herbal products is affected by spurious and unauthorized raw materials. Recent development in molecular plant identification using DNA barcodes has become a robust methodology to identify and authenticate the adulterants in herbal samples. Hence, rapid and accurate identification of medicinal plants is the key to success for the herbal industry. Aim of the study: This paper provides a comprehensive review of the application of DNA barcoding and advanced technologies that have emerged over the past 10 years related to medicinal plant identification and authentication and the future prospects of this technology. Materials and methods: Information on DNA barcodes was compiled from scientific databases (Google Scholar, Web of Science, SciFinder and PubMed). Additional information was obtained from books, Ph.D. thesis and MSc. Dissertations. Results: Working out an appropriate DNA barcode for plants is challenging; the single locus-based DNA barcodes (rbcL, ITS, ITS2, matK, rpoB, rpoC, trnH-psbA) to multi-locus DNA barcodes have become the successful species-level identification among herbal plants. Additionally, multi-loci have become efficient in the authentication of herbal products. Emerging advances in DNA barcoding and related technologies such as next-generation sequencing, high-resolution melting curve analysis, meta barcodes and mini barcodes have paved the way for successful herbal plant/samples identification. Conclusion: DNA barcoding needs to be employed together with other techniques to check and rationally and effectively quality control the herbal drugs. It is suggested that DNA barcoding techniques combined with metabolomics, transcriptomics, and proteomics could authenticate the herbal products. The invention of simple, cost-effective and improved DNA barcoding techniques to identify herbal drugs and their associated products of medicinal value in a fool-proof manner will be the future thrust of Pharmacopoeial monograph development for herbal drugs.

Multi-Omics Approaches and Resources for Systems-Level Gene Function Prediction in the Plant Kingdom

In higher plants, the complexity of a system and the components within and among species are rapidly dissected by omics technologies. Multi-omics datasets are integrated to infer and enable a comprehensive understanding of the life processes of organisms of interest. Further, growing open-source datasets coupled with the emergence of high-performance computing and development of computational tools for biological sciences have assisted in silico functional prediction of unknown genes, proteins and metabolites, otherwise known as uncharacterized. The systems biology approach includes data collection and filtration, system modelling, experimentation and the establishment of new hypotheses for experimental validation. Informatics technologies add meaningful sense to the output generated by complex bioinformatics algorithms, which are now freely available in a user-friendly graphical user interface. These resources accentuate gene function prediction at a relatively minimal cost and effort. Herein, we present a comprehensive view of relevant approaches available for system-level gene function prediction in the plant kingdom. Together, the most recent applications and sought-after principles for gene mining are discussed to benefit the plant research community. A realistic tabulation of plant genomic resources is included for a less laborious and accurate candidate gene discovery in basic plant research and improvement strategies.

Beyond Basic Diversity Estimates-Analytical Tools for Mechanistic Interpretations of Amplicon Sequencing Data

Understanding microbial ecology through amplifying short read regions, typically 16S rRNA for prokaryotic species or 18S rRNA for eukaryotic species, remains a popular, economical choice. These methods provide relative abundances of key microbial taxa, which, depending on the experimental design, can be used to infer mechanistic ecological underpinnings. In this review, we discuss recent advancements in in situ analytical tools that have the power to elucidate ecological phenomena, unveil the metabolic potential of microbial communities, identify complex multidimensional interactions between species, and compare stability and complexity under different conditions. Additionally, we highlight methods that incorporate various modalities and additional information, which in combination with abundance data, can help us understand how microbial communities respond to change in a typical ecosystem. Whilst the field of microbial informatics continues to progress substantially, our emphasis is on popular methods that are applicable to a broad range of study designs. The application of these methods can increase our mechanistic understanding of the ongoing dynamics of complex microbial communities.

A Comprehensive Review of Performance of Next-Generation Sequencing Platforms

Background

Next-generation sequencing methods have been developed and proposed to investigate any query in genomics or clinical activity involving DNA. Technical advancement in these sequencing methods has enhanced sequencing volume to several billion nucleotides within a very short time and low cost. During the last few years, the usage of the latest DNA sequencing platforms in a large number of research projects helped to improve the sequencing methods and technologies, thus enabling a wide variety of research/review publications and applications of sequencing technologies.

Objective

The proposed study is aimed at highlighting the most fast and accurate NGS instruments developed by various companies by comparing output per hour, quality of the reads, maximum read length, reads per run, and their applications in various domains. This will help research institutions and biological/clinical laboratories to choose the sequencing instrument best suited to their environment. The end users will have a general overview about the history of the sequencing technologies, latest developments, and improvements made in the sequencing technologies till now.

Results

The proposed study, based on previous studies and manufacturers' descriptions, highlighted that in terms of output per hour, Nanopore PromethION outperformed all sequencers. BGI was on the second position, and Illumina was on the third position.

Conclusion

The proposed study investigated various sequencing instruments and highlighted that, overall, Nanopore PromethION is the fastest sequencing approach. BGI and Nanopore can beat Illumina, which is currently the most popular sequencing company. With respect to quality, Ion Torrent NGS instruments are on the top of the list, Illumina is on the second position, and BGI DNB is on the third position. Secondly, memory- and time-saving algorithms and databases need to be developed to analyze data produced by the 3rd- and 4th-generation sequencing methods. This study will help people to adopt the best suited sequencing platform for their research work, clinical or diagnostic activities.

DNA metabarcoding reveals that coyotes in New York City consume wide variety of native prey species and human food

Carnivores are currently colonizing cities where they were previously absent. These urban environments are novel ecosystems characterized by habitat degradation and fragmentation, availability of human food, and different prey assemblages than surrounding areas. Coyotes (Canis latrans) established a breeding population in New York City (NYC) over the last few decades, but their ecology within NYC is poorly understood. In this study, we used non-invasive scat sampling and DNA metabarcoding to profile vertebrate, invertebrate, and plant dietary items with the goal to compare the diets of urban coyotes to those inhabiting non-urban areas. We found that both urban and non-urban coyotes consumed a variety of plants and animals as well as human food. Raccoons (Procyon lotor) were an important food item for coyotes within and outside NYC. In contrast, white-tailed deer (Odocoileus virginianus) were mainly eaten by coyotes inhabiting non-urban areas. Domestic chicken (Gallus gallus) was the human food item found in most scats from both urban and non-urban coyotes. Domestic cats (Felis catus) were consumed by urban coyotes but were detected in only a small proportion of the scats (<5%), which differs markedly from high rates of cat depredation in some other cities. In addition, we compared our genetic metabarcoding analysis to a morphological analysis of the same scat samples. We found that the detection similarity between the two methods was low and it varied depending on the type of diet item.

Gut symbiotic bacteria are involved in nitrogen recycling in the tephritid fruit fly Bactrocera dorsalis

Background

Nitrogen is considered the most limiting nutrient element for herbivorous insects. To alleviate nitrogen limitation, insects have evolved various symbiotically mediated strategies that enable them to colonize nitrogen-poor habitats or exploit nitrogen-poor diets. In frugivorous tephritid larvae developing in fruit pulp under nitrogen stress, it remains largely unknown how nitrogen is obtained and larval development is completed.

Results

In this study, we used metagenomics and metatranscriptomics sequencing technologies as well as in vitro verification tests to uncover the mechanism underlying the nitrogen exploitation in the larvae of Bactrocera dorsalis. Our results showed that nitrogenous waste recycling (NWR) could be successfully driven by symbiotic bacteria, including Enterobacterales, Lactobacillales, Orbales, Pseudomonadales, Flavobacteriales, and Bacteroidales. In this process, urea hydrolysis in the larval gut was mainly mediated by Morganella morganii and Klebsiella oxytoca. In addition, core bacteria mediated essential amino acid (arginine excluded) biosynthesis by ammonium assimilation and transamination.

Conclusions

Symbiotic bacteria contribute to nitrogen transformation in the larvae of B. dorsalis in fruit pulp. Our findings suggest that the pattern of NWR is more likely to be applied by B. dorsalis, and M. morganii, K. oxytoca, and other urease-positive strains play vital roles in hydrolysing nitrogenous waste and providing metabolizable nitrogen for B. dorsalis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-022-01399-9.

Effective Identification of Bacterial Genomes From Short and Long Read Sequencing Data

With the development of sequencing technology, microbiological genome sequencing analysis has attracted extensive attention. For inexperienced users without sufficient bioinformatics skills, making sense of sequencing data for microbial identification, especially for bacterial identification, through reads analysis is still challenging. In order to address the challenge of effectively analyzing genomic information, in this paper, we develop an effective approach and automatic bioinformatics pipeline called PBGI for bacterial genome identification, performing automatedly and customized bioinformatics analysis using short-reads or long-reads sequencing data produced by multiple platforms such as Illumina, PacBio and Oxford Nanopore. An evaluation of the proposed approach on the practical data set is presented, showing that PBGI provides a user-friendly way to perform bacterial identification through short or long reads analysis, and could provide accurate analyzing results. The source code of the PBGI is freely available at https://github.com/lyotvincent/PBGI.

High-throughput method for the hybridisation-based targeted enrichment of long genomic fragments for PacBio third-generation sequencing

Hybridisation-based targeted enrichment is a widely used and well-established technique in high-throughput second-generation short-read sequencing. Despite the high potential to genetically resolve highly repetitive and variable genomic sequences by, for example PacBio third-generation sequencing, targeted enrichment for long fragments has not yet established the same high-throughput due to currently existing complex workflows and technological dependencies. We here describe a scalable targeted enrichment protocol for fragment sizes of >7 kb. For demonstration purposes we developed a custom blood group panel of challenging loci. Test results achieved > 65% on-target rate, good coverage (142.7×) and sufficient coverage evenness for both non-paralogous and paralogous targets, and sufficient non-duplicate read counts (83.5%) per sample for a highly multiplexed enrichment pool of 16 samples. We genotyped the blood groups of nine patients employing highly accurate phased assemblies at an allelic resolution that match reference blood group allele calls determined by SNP array and NGS genotyping. Seven Genome-in-a-Bottle reference samples achieved high recall (96%) and precision (99%) rates. Mendelian error rates were 0.04% and 0.13% for the included Ashkenazim and Han Chinese trios, respectively. In summary, we provide a protocol and first example for accurate targeted long-read sequencing that can be used in a high-throughput fashion.

Nonsyndromic arteriopathy and aortopathy and vascular Ehlers-Danlos syndrome causing COL3A1 variants

Vascular Ehlers-Danlos syndrome (vEDS) is an autosomal dominant genetic disorder characterized by soft connective tissue vulnerability due to dysfunction of Type III collagen and caused by the pathogenic variants in COL3A1 gene. In the era of next-generation sequencing, multiple genes including COL3A1 can be simultaneously analyzed, and among patients suffering from aortopathy even without any other clinical features suggestive of vEDS, pathogenic COL3A1 variants have been increasingly identified. Here, we briefly summarize the characteristics of 12 Japanese patients from 11 families with arteriopathy and pathogenic or likely pathogenic COL3A1 variants in our hospital. Five patients did not have any extra-arterial clinical features, however, the multigene panel testing for hereditary thoracic aortic aneurysm and dissection unexpectedly revealed that two had glycine substitutions in the triple-helical region and three had haploinsufficient type variants in the COL3A1 gene, whose pathogenicities were all classified as pathogenic or likely pathogenic. Further genetic screening and identification of pathogenic variants in patients with nonsyndromic arteriopathy and aortopathy will enable us to develop risk-stratification and management based on the genetic diagnosis.

Listeria monocytogenes in foods-From culture identification to whole-genome characteristics

Listeria monocytogenes is an important foodborne pathogen, which is able to persist in the food production environments. The presence of these bacteria in different niches makes them a potential threat for public health. In the present review, the current information on the classical and alternative methods used for isolation and identification of L. monocytogenes in food have been described. Although these techniques are usually simple, standardized, inexpensive, and are routinely used in many food testing laboratories, several alternative molecular-based approaches for the bacteria detection in food and food production environments have been developed. They are characterized by the high sample throughput, a short time of analysis, and cost-effectiveness. However, these methods are important for the routine testing toward the presence and number of L. monocytogenes, but are not suitable for characteristics and typing of the bacterial isolates, which are crucial in the study of listeriosis infections. For these purposes, novel approaches, with a high discriminatory power to genetically distinguish the strains during epidemiological studies, have been developed, e.g., whole-genome sequence-based techniques such as NGS which provide an opportunity to perform comparison between strains of the same species. In the present review, we have shown a short description of the principles of microbiological, alternative, and modern methods of detection of L. monocytogenes in foods and characterization of the isolates for epidemiological purposes. According to our knowledge, similar comprehensive papers on such subject have not been recently published, and we hope that the current review may be interesting for research communities.

Environmental DNA Metabarcoding: A Novel Contrivance for Documenting Terrestrial Biodiversity

Simple Summary

The innovative concept of environmental DNA has found its foot in aquatic ecosystems but remains an unexplored area of research concerning terrestrial ecosystems. When making management choices, it is important to understand the rate of eDNA degradation, the persistence of DNA in terrestrial habitats, and the variables affecting eDNA detectability for a target species. Therefore an attempt has been made to provide comprehensive information regarding the exertion of eDNA in terrestrial ecosystems from 2012 to 2022. The information provided will assist ecologists, researchers and decision-makers in developing a holistic understanding of environmental DNA and its applicability as a biodiversity monitoring contrivance.

Abstract

The dearth of cardinal data on species presence, dispersion, abundance, and habitat prerequisites, besides the threats impeded by escalating human pressure has enormously affected biodiversity conservation. The innovative concept of eDNA, has been introduced as a way of overcoming many of the difficulties of rigorous conventional investigations, and is hence becoming a prominent and novel method for assessing biodiversity. Recently the demand for eDNA in ecology and conservation has expanded exceedingly, despite the lack of coordinated development in appreciation of its strengths and limitations. Therefore it is pertinent and indispensable to evaluate the extent and significance of eDNA-based investigations in terrestrial habitats and to classify and recognize the critical considerations that need to be accounted before using such an approach. Presented here is a brief review to summarize the prospects and constraints of utilizing eDNA in terrestrial ecosystems, which has not been explored and exploited in greater depth and detail in such ecosystems. Given these obstacles, we focused primarily on compiling the most current research findings from journals accessible in eDNA analysis that discuss terrestrial ecosystems (2012–2022). In the current evaluation, we also review advancements and limitations related to the eDNA technique.

Advances in the human skin microbiota and its roles in cutaneous diseases

Skin is the largest organ in the human body, and the interplay between the environment factors and human skin leads to some skin diseases, such as acne, psoriasis, and atopic dermatitis. As the first line of human immune defense, skin plays significant roles in human health via preventing the invasion of pathogens that is heavily influenced by the skin microbiota. Despite being a challenging niche for microbes, human skin is colonized by diverse commensal microorganisms that shape the skin environment. The skin microbiota can affect human health, and its imbalance and dysbiosis contribute to the skin diseases. This review focuses on the advances in our understanding of skin microbiota and its interaction with human skin. Moreover, the potential roles of microbiota in skin health and diseases are described, and some key species are highlighted. The prevention, diagnosis and treatment strategies for microbe-related skin diseases, such as healthy diets, lifestyles, probiotics and prebiotics, are discussed. Strategies for modulation of skin microbiota using synthetic biology are discussed as an interesting venue for optimization of the skin-microbiota interactions. In summary, this review provides insights into human skin microbiota recovery, the interactions between human skin microbiota and diseases, and the strategies for engineering/rebuilding human skin microbiota.

Identification of Novel Genes Associated with Partial Resistance to Aphanomyces Root Rot in Field Pea by BSR-Seq Analysis

Aphanomyces root rot, caused by Aphanomyces euteiches, causes severe yield loss in field pea (Pisum sativum). The identification of a pea germplasm resistant to this disease is an important breeding objective. Polygenetic resistance has been reported in the field pea cultivar '00-2067'. To facilitate marker-assisted selection (MAS), bulked segregant RNA-seq (BSR-seq) analysis was conducted using an F8 RIL population derived from the cross of 'Carman' × '00-2067'. Root rot development was assessed under controlled conditions in replicated experiments. Resistant (R) and susceptible (S) bulks were constructed based on the root rot severity in a greenhouse study. The BSR-seq analysis of the R bulks generated 44,595,510~51,658,688 reads, of which the aligned sequences were linked to 44,757 genes in a reference genome. In total, 2356 differentially expressed genes were identified, of which 44 were used for gene annotation, including defense-related pathways (jasmonate, ethylene and salicylate) and the GO biological process. A total of 344.1 K SNPs were identified between the R and S bulks, of which 395 variants were located in 31 candidate genes. The identification of novel genes associated with partial resistance to Aphanomyces root rot in field pea by BSR-seq may facilitate efforts to improve management of this important disease.

Rapid and simple analysis of short and long sequencing reads using DuesselporeTM

Transcriptome analysis experiments enable researchers to gain extensive insights into the molecular mechanisms underlying cell physiology and disease. Oxford Nanopore Technologies (ONT) has recently been developed as a fast, miniaturized, portable, and cost-effective alternative to next-generation sequencing (NGS). However, RNA-Seq data analysis software that exploits ONT portability and allows scientists to easily analyze ONT data everywhere without bioinformatics expertise is not widely available. We developed Duesselpore^TM, an easy-to-follow deep sequencing workflow that runs as a local webserver and allows the analysis of ONT data everywhere without requiring additional bioinformatics tools or internet connection. Duesselpore^TM output includes differentially expressed genes and further downstream analyses, such as variance heatmap, disease and gene ontology plots, gene concept network plots, and exports customized pathways for different cellular processes. We validated Duesselpore^TM by analyzing the transcriptomic changes induced by PCB126, a dioxin-like PCB, and a potent aryl hydrocarbon receptor (AhR) agonist in human HaCaT keratinocytes, a well-characterized model system. Duesselpore^TM was specifically developed to analyze ONT data, but we also implemented NGS data analysis. Duesselpore^TM is compatible with Linux, Microsoft, and Mac operating systems and allows convenient, reliable, and cost-effective analysis of ONT and NGS data.

A Critical Assessment of the Congruency between Environmental DNA and Palaeoecology for the Biodiversity Monitoring and Palaeoenvironmental Reconstruction

The present study suggests that standardized methodology, careful site selection, and stratigraphy are essential for investigating ancient ecosystems in order to evaluate biodiversity and DNA-based time series. Based on specific keywords, this investigation reviewed 146 publications using the SCOPUS, Web of Science (WoS), PUBMED, and Google Scholar databases. Results indicate that environmental deoxyribose nucleic acid (eDNA) can be pivotal for assessing and conserving ecosystems. Our review revealed that in the last 12 years (January 2008–July 2021), 63% of the studies based on eDNA have been reported from aquatic ecosystems, 25% from marine habitats, and 12% from terrestrial environments. Out of studies conducted in aquatic systems using the environmental DNA (eDNA) technique, 63% of the investigations have been reported from freshwater ecosystems, with an utmost focus on fish diversity (40%). Further analysis of the literature reveals that during the same period, 24% of the investigations using the environmental DNA technique were carried out on invertebrates, 8% on mammals, 7% on plants, 6% on reptiles, and 5% on birds. The results obtained clearly indicate that the environmental DNA technique has a clear-cut edge over other biodiversity monitoring methods. Furthermore, we also found that eDNA, in conjunction with different dating techniques, can provide better insight into deciphering eco-evolutionary feedback. Therefore, an attempt has been made to offer extensive information on the application of dating methods for different taxa present in diverse ecosystems. Last, we provide suggestions and elucidations on how to overcome the caveats and delineate some of the research avenues that will likely shape this field in the near future. This paper aims to identify the gaps in environmental DNA (eDNA) investigations to help researchers, ecologists, and decision-makers to develop a holistic understanding of environmental DNA (eDNA) and its utility as a palaeoenvironmental contrivance.

Rhizosphere soil microbial community and its response to different utilization patterns in the semi-arid alpine grassland of northern Tibet

As the link between plants and soils, rhizosphere soil microorganisms play an important role in the element cycle. This study aimed to understand the response of the rhizosphere soil microbial community structure and interaction network to grassland utilization in the alpine steppe of the northern Tibet Plateau. High-throughput sequencing was employed to study the composition, diversity, and species interaction network of rhizosphere soil microbial communities under grazing, mowing, and enclosing treatments. Proteobacteria (47.19%) and Actinobacteria (42.20%) were the dominant bacteria in the rhizosphere soil. There was no significant difference in relative abundance among rhizosphere soil microorganisms at phylum and genus levels, but differences were found in Chlorobi, Ignavibacteriae, and Micromonospora. The alpha diversity index based on Shannon, Chao1, and Simpson indices revealed that except for a significant difference in the Shannon index of the Artemisia nanschanica group, the richness and evenness of rhizosphere soil microbial communities among all groups were similar. Non-metric multidimensional scaling (NMDS) and multi-response permutation procedure (MRPP) analyses showed that the inter-group differences of three plants (Stipa purpurea, Carex moorcroftii, and Artemisia nanschanica) were greater than the differences within the groups; however, only the inter-group difference with the Stipa purpurea group was significant. The microbial interaction network showed that the network complexity of the Artemisia nanschanica group and the enclosing treatment, which were not easily influenced by external factors, were higher than those of the other groups and treatments; this again demonstrated that Proteobacteria and Actinobacteria were the network core microbial species in alpine steppe of the northern Tibet Plateau and were crucial for maintaining stability of the microbial communities. Findings from this study provide a theoretical basis for the restoration of degraded alpine grassland and the development of microbial functions.

Comparative transcriptome analysis on the mangrove Acanthus ilicifolius and its two terrestrial relatives provides insights into adaptation to intertidal habitats

Acanthus is a unique genus covering both mangroves and terrestrial species, and thus is an ideal system to comparatively analyze the mechanisms of mangrove adaptation to intertidal habitats. We performed RNA sequencing of the mangrove plant Acanthus ilicifolius and its two terrestrial relatives, Acanthus leucostachyus and Acanthus mollis. A total of 91,125, 118,290, and 141,640 unigenes were obtained. Simple sequence repeats (SSR) analysis showed that A. ilicifolius had more SSRs, the highest frequency of distribution, and higher in polymorphism potential compared to the two terrestrial relatives. Phylogenetic analyses suggested a relatively recent split between A. ilicifolius and A. leucostachyus, i.e., about 16.76 million years ago (Mya), after their ancestor divergence with A. mollis (32.11 Mya), indicating that speciation of three Acanthus species occurred in the Early to Middle Miocene. Gene Ontology (GO) enrichment revealed that the unique unigenes in A. ilicifolius are predominantly related to rhythmic process, reproductive process and response to stimuli. The accelerated evolution and positive selection analyses indicated that the genus Acanthus migrated from terrestrial to intertidal habitats, where 311 pairs may be under positive selection. Functional enrichment analysis revealed that these genes associated with essential metabolism and biosynthetic pathways such as oxidative phosphorylation, plant hormone signal transduction, photosynthetic carbon fixation and arginine and proline metabolism, are related to the adaptation of A. ilicifolius to intertidal habitats, which are characterized by high salinity and hypoxia. Our results indicate the evolutionary processes and the mechanisms underlying the adaptability of Acanthus to various harsh environments from the arid terrestrial to intertidal habitats.