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This study investigates the impact of casein hydrolysates on the poultry ceca inoculated with Campylobacter focusing on microbial molecular preferences for different protein sources in the presence of Campylobacter jejuni. Three casein sources (intact casein (IN), casein enzyme hydrolysate (EH), and casein acid hydrolysate (AH)) were introduced to cecal contents in combination with inoculated C. jejuni in an in vitro model system incubated for 48 h at 42°C under microaerophilic conditions. Samples were collected at 0, 24, and 48 h. Genomic DNA was extracted and amplified using custom dual-indexed primers, followed by sequencing on an Illumina MiSeq platform. The obtained sequencing data were then analyzed via QIIME2-2021.11. Metabolite extracts were analyzed with ultra-high-performance liquid orbitrap chromatography-mass spectrometry (UHPLC-MS). Statistical analysis of metabolites was conducted using MetaboAnalyst 5.0, while functional analysis was performed using Mummichog 2.0 with a significance threshold set at P < 0.00001. DNA sequencing and metabolomic analyses revealed that C. jejuni was most abundant in the EH group. Microbial diversity and richness improved in casein supplemented groups, with core microbial differences observed, compared to non-supplemented groups. Vitamin B-associated metabolites significantly increased in the supplemented groups, displaying distinct patterns in vitamin B6 and B9 metabolism between EH and AH groups (P < 0.05). Faecalibacterium and Phascolarctobacterium were associated with AH and EH groups, respectively. These findings suggest microbial interactions in the presence of C. jejuni and casein supplementation are influenced by microbial community preferences for casein hydrolysates impacting B vitamin production and shaping competitive dynamics within the cecal microbial community. These findings underscore the potential of nutritional interventions to modulate the poultry GIT microbiota for improved health outcomes. [ABSTRACT FROM AUTHOR]

Copy Number Variants (CNV) are modifications affecting the genome sequence of DNA, for instance, they can be duplications or deletions of a considerable number of base pairs (i.e., greater than 1000 bp and up to millions of bp). Their impact on the variation of the phenotypic traits has been widely demonstrated. In addition, CNVs are a class of markers useful to identify the genetic biodiversity among populations related to adaptation to the environment. The aim of this study was to detect CNVs in more than four thousand Holstein cows, using information derived by a genotyping done with the GGP (GeneSeek Genomic Profiler) bovine 100K SNP chip. To detect CNV the SVS 8.9 software was used, then CNV regions (CNVRs) were detected. A total of 123,814 CNVs (4,150 non redundant) were called and aggregated into 1,397 CNVRs. The PCA results obtained using the CNVs information, showed that there is some variability among animals. For many genes annotated within the CNVRs, the role in immune response is well known, as well as their association with important and economic traits object of selection in Holstein, such as milk production and quality, udder conformation and body morphology. Comparison with reference revealed unique CNVRs of the Holstein breed, and others in common with Jersey and Brown. The information regarding CNVs represents a valuable resource to understand how this class of markers may improve the accuracy in prediction of genomic value, nowadays solely based on SNPs markers. [ABSTRACT FROM AUTHOR]

Influenza A viruses of the H2 subtype represent a zoonotic and pandemic threat to humans due to a lack of widespread specific immunity. Although A(H2) viruses that circulate in wild bird reservoirs are distinct from the 1957 pandemic A(H2N2) viruses, there is concern that they could impact animal and public health. There is limited information on AIVs in Latin America, and next to nothing about H2 subtypes in Brazil. In the present study, we report the occurrence and genomic sequences of two influenza A viruses isolated from wild-caught white-rumped sandpipers (Calidris fuscicollis). One virus, identified as A(H2N1), was isolated from a bird captured in Restinga de Jurubatiba National Park (PNRJ, Rio de Janeiro), while the other, identified as A(H2N2), was isolated from a bird captured in Lagoa do Peixe National Park (PNLP, Rio Grande do Sul). DNA sequencing and phylogenetic analysis of the obtained sequences revealed that each virus belonged to distinct subtypes. Furthermore, the phylogenetic analysis indicated that the genomic sequence of the A(H2N1) virus isolated from PNRJ was most closely related to other A(H2N1) viruses isolated from North American birds. On the other hand, the A(H2N2) virus genome recovered from the PNLP-captured bird exhibited a more diverse origin, with some sequences closely related to viruses from Iceland and North America, and others showing similarity to virus sequences recovered from birds in South America. Viral genes of diverse origins were identified in one of the viruses, indicating local reassortment. This suggests that the extreme South of Brazil may serve as an environment conducive to reassortment between avian influenza virus lineages from North and South America, potentially contributing to an increase in overall viral diversity. [ABSTRACT FROM AUTHOR]

The analysis of the DNA entrapped in ancient shells of molluscs has the potential to shed light on the evolution and ecology of this very diverse phylum. Ancient genomics could help reconstruct the responses of molluscs to past climate change, pollution, and human subsistence practices at unprecedented temporal resolutions. Applications are however still in their infancy, partly due to our limited knowledge of DNA preservation in calcium carbonate shells and the need for optimized methods for responsible genomic data generation. To improve ancient shell genomic analyses, we applied high-throughput DNA sequencing to 27 Mytilus mussel shells dated to ~111–6500 years Before Present, and investigated the impact, on DNA recovery, of shell imaging, DNA extraction protocols and shell sub-sampling strategies. First, we detected no quantitative or qualitative deleterious effect of micro-computed tomography for recording shell 3D morphological information prior to sub-sampling. Then, we showed that double-digestion and bleach treatment of shell powder prior to silica-based DNA extraction improves shell DNA recovery, also suggesting that DNA is protected in preservation niches within ancient shells. Finally, all layers that compose Mytilus shells, i.e., the nacreous (aragonite) and prismatic (calcite) carbonate layers, with or without the outer organic layer (periostracum) proved to be valuable DNA reservoirs, with aragonite appearing as the best substrate for genomic analyses. Our work contributes to the understanding of long-term molecular preservation in biominerals and we anticipate that resulting recommendations will be helpful for future efficient and responsible genomic analyses of ancient mollusc shells. [ABSTRACT FROM AUTHOR]

Chilling sensitivity is one of the greatest challenges affecting the marketability and profitability of sweet basil (Ocimum basilicum L.) in the US and worldwide. Currently, there are no sweet basils commercially available with significant chilling tolerance and traditional aroma profiles. This study was conducted to identify quantitative trait loci (QTLs) responsible for chilling tolerance and aroma compounds in a biparental mapping population, including the Rutgers advanced breeding line that served as a chilling tolerant parent, 'CB15', the chilling sensitive parent, 'Rutgers Obsession DMR' and 200 F2 individuals. Chilling tolerance was assessed by percent necrosis using machine learning and aroma profiling was evaluated using gas chromatography (GC) mass spectrometry (MS). Single nucleotide polymorphism (SNP) markers were generated from genomic sequences derived from double digestion restriction-site associated DNA sequencing (ddRADseq) and converted to genotype data using a reference genome alignment. A genetic linkage map was constructed and five statistically significant QTLs were identified in response to chilling temperatures with possible interactions between QTLs. The QTL on LG24 (qCH24) demonstrated the largest effect for chilling response and was significant in all three replicates. No QTLs were identified for linalool, as the population did not segregate sufficiently to detect this trait. Two significant QTLs were identified for estragole (also known as methyl chavicol) with only qEST1 on LG1 being significant in the multiple-QTL model (MQM). QEUC26 was identified as a significant QTL for eucalyptol (also known as 1,8-cineole) on LG26. These QTLs may represent key mechanisms for chilling tolerance and aroma in basil, providing critical knowledge for future investigation of these phenotypic traits and molecular breeding. [ABSTRACT FROM AUTHOR]

Reductions in sequencing costs have enabled widespread use of shotgun metagenomics and amplicon sequencing, which have drastically improved our understanding of the microbial world. However, large sequencing projects are now hampered by the cost of library preparation and low sample throughput, comparatively to the actual sequencing costs. Here, we benchmarked three high-throughput DNA extraction methods: ZymoBIOMICS™ 96 MagBead DNA Kit, MP BiomedicalsTM FastDNATM-96 Soil Microbe DNA Kit, and DNeasy® 96 PowerSoil® Pro QIAcube® HT Kit. The DNA extractions were evaluated based on length, quality, quantity, and the observed microbial community across five diverse soil types. DNA extraction of all soil types was successful for all kits, however DNeasy® 96 PowerSoil® Pro QIAcube® HT Kit excelled across all performance parameters. We further used the nanoliter dispensing system I.DOT One to miniaturize Illumina amplicon and metagenomic library preparation volumes by a factor of 5 and 10, respectively, with no significant impact on the observed microbial communities. With these protocols, DNA extraction, metagenomic, or amplicon library preparation for one 96-well plate are approx. 3, 5, and 6 hours, respectively. Furthermore, the miniaturization of amplicon and metagenome library preparation reduces the chemical and plastic costs from 5.0 to 3.6 and 59 to 7.3 USD pr. sample. This enhanced efficiency and cost-effectiveness will enable researchers to undertake studies with greater sample sizes and diversity, thereby providing a richer, more detailed view of microbial communities and their dynamics. [ABSTRACT FROM AUTHOR]

Situated in the Eastern section of the European Alps, Austria encompasses a great diversity of different habitat types, ranging from alpine to lowland Pannonian ecosystems, and a correspondingly high level of species diversity, some of which has been addressed in various DNA barcoding projects. Here, we report a DNA barcode library of all the 476 species of Geometridae (Lepidoptera) that have been recorded in Austria. As far as possible, species were sampled from different Austrian regions in order to capture intraspecific genetic variation. In total, 2500 DNA barcode sequences, representing 438 species, were generated in this study. For complete coverage of Austrian geometrid species in the subsequent analyses, the dataset was supplemented with DNA barcodes from specimens of non-Austrian origin. Species delimitations by ASAP, BIN and bPTP methods yielded 465, 510 and 948 molecular operational taxonomic units, respectively. Congruency of BIN and ASAP partitions with morphospecies assignments was reasonably high (85% of morphospecies in unique partitions), whereas bPTP appeared to overestimate the number of taxonomic units. The study furthermore identified taxonomically relevant cases of morphospecies splitting and sharing in the molecular partitions. We conclude that DNA barcoding and sequence analysis revealed a high potential for accurate DNA-based identification of the Austrian Geometridae species. Additionally, the study provides an updated checklist of the geometrid moths of Austria. [ABSTRACT FROM AUTHOR]

The Quince (Cydonia oblonga Mill.), typically known for its self-compatibility, surprisingly presents a degree of self-incompatibility. This research focused on exploring the diversity within the self-incompatibility gene locus (S) in various C. oblonga genotypes. Through meticulous DNA sequencing, the study sought to unearth potential novel S alleles. In the process of genotyping the S gene across multiple quince genotypes, not only were the previously documented S1 and S2 alleles identified, but this investigation also uncovered two previously unrecognized alleles, termed S4 and S5. These alleles, particularly S4, emerged as the most prevalent among the tested genotypes. To corroborate the findings derived from DNA sequencing, the study employed pollen tube growth germination assays. These assays elucidated a higher pollen germination rate in the Ardabil2 genotype in contrast to Behta. Additionally, the study involved assessing pollen tube growth in both Ardabil2 and Behta through cross-pollination techniques, meticulously tracking the development of pollen tubes at various stages. Remarkably, the outcomes demonstrated that the Behta genotype possesses self-incompatibility, whereas the Ardabil2 genotype showcases a notable degree of self-compatibility. This groundbreaking discovery of new S alleles in quince not only affirms the species' self-compatibility but also sheds light on the complexities of allelic diversity and its impact on self-incompatibility. Such insights are invaluable for enhancing the yield of quince orchards through strategic breeding programs. [ABSTRACT FROM AUTHOR]

Recent advances in long-read sequencing technologies have enabled the complete assembly of eukaryotic genomes from telomere to telomere by allowing repeated regions to be fully sequenced and assembled, thus filling the gaps left by previous short-read sequencing methods. Furthermore, long-read sequencing can also help characterizing structural variants, with applications in the fields of genome evolution or cancer genomics. For many organisms, the main bottleneck to sequence long reads remains the lack of robust methods to obtain high-molecular-weight (HMW) DNA. For this purpose, we developed an optimized protocol to extract DNA suitable for long-read sequencing from the unicellular green alga Chlamydomonas reinhardtii, based on CTAB/phenol extraction followed by a size selection step for long DNA molecules. We provide validation results for the extraction protocol, as well as statistics obtained with Oxford Nanopore Technologies sequencing. [ABSTRACT FROM AUTHOR]

DNA-functionalized hydrogels are capable of sensing oligonucleotides, proteins, and small molecules, and specific DNA sequences sensed in the hydrogels' environment can induce changes in these hydrogels' shape and fluorescence. Fabricating DNA-functionalized hydrogel architectures with multiple domains could make it possible to sense multiple molecules and undergo more complicated macroscopic changes, such as changing fluorescence or changing the shapes of regions of the hydrogel architecture. However, automatically fabricating multi-domain DNA-functionalized hydrogel architectures, capable of enabling the construction of hydrogel architectures with tens to hundreds of different domains, presents a significant challenge. We describe a platform for fabricating multi-domain DNA-functionalized hydrogels automatically at the micron scale, where reaction and diffusion processes can be coupled to program material behavior. Using this platform, the hydrogels' material properties, such as shape and fluorescence, can be programmed, and the fabricated hydrogels can sense their environment. DNA-functionalized hydrogel architectures with domain sizes as small as 10 microns and with up to 4 different types of domains can be automatically fabricated using ink volumes as low as 50 μL. We also demonstrate that hydrogels fabricated using this platform exhibit responses similar to those of DNA-functionalized hydrogels fabricated using other methods by demonstrating that DNA sequences can hybridize within them and that they can undergo DNA sequence-induced shape change. [ABSTRACT FROM AUTHOR]

Early detection of SARS-CoV-2 infection is key to managing the current global pandemic, as evidence shows the virus is most contagious on or before symptom onset. Here, we introduce a low-cost, high-throughput method for diagnosing and studying SARS-CoV-2 infection. Dubbed Pathogen-Oriented Low-Cost Assembly & Re-Sequencing (POLAR), this method amplifies the entirety of the SARS-CoV-2 genome. This contrasts with typical RT-PCR-based diagnostic tests, which amplify only a few loci. To achieve this goal, we combine a SARS-CoV-2 enrichment method developed by the ARTIC Network (https://artic.network/) with short-read DNA sequencing and de novo genome assembly. Using this method, we can reliably (>95% accuracy) detect SARS-CoV-2 at a concentration of 84 genome equivalents per milliliter (GE/mL). The vast majority of diagnostic methods meeting our analytical criteria that are currently authorized for use by the United States Food and Drug Administration with the Coronavirus Disease 2019 (COVID-19) Emergency Use Authorization require higher concentrations of the virus to achieve this degree of sensitivity and specificity. In addition, we can reliably assemble the SARS-CoV-2 genome in the sample, often with no gaps and perfect accuracy given sufficient viral load. The genotypic data in these genome assemblies enable the more effective analysis of disease spread than is possible with an ordinary binary diagnostic. These data can also help identify vaccine and drug targets. Finally, we show that the diagnoses obtained using POLAR of positive and negative clinical nasal mid-turbinate swab samples 100% match those obtained in a clinical diagnostic lab using the Center for Disease Control's 2019-Novel Coronavirus test. Using POLAR, a single person can manually process 192 samples over an 8-hour experiment at the cost of ~$36 per patient (as of December 7th, 2022), enabling a 24-hour turnaround with sequencing and data analysis time. We anticipate that further testing and refinement will allow greater sensitivity using this approach. [ABSTRACT FROM AUTHOR]

Objective: Identify system-level features in HIV migration within a host across body tissues. Evaluate heterogeneity in the presence and magnitude of these features across hosts. Method: Using HIV DNA deep sequencing data generated across multiple tissues from 8 people with HIV, we represent the complex dependencies of HIV migration among tissues as a network and model these networks using the family of exponential random graph models (ERGMs). ERGMs allow for the statistical assessment of whether network features occur more (or less) frequently in viral migration than might be expected by chance. The analysis investigates five potential features of the viral migration network: (1) bi-directional flow between tissues; (2) preferential migration among tissues in the same biological system; (3) heterogeneity in the level of viral migration related to HIV reservoir size; (4) hierarchical structure of migration; and (5) cyclical migration among several tissues. We calculate the Cohran's Q statistic to assess heterogeneity in the magnitude of the presence of these features across hosts. The analysis adjusts for missing data on body tissues. Results: We observe strong evidence for bi-directional flow between tissues; migration among tissues in the same biological system; and hierarchical structure of the viral migration network. This analysis shows no evidence for differential level of viral migration with respect to the HIV reservoir size of a tissue. There is evidence that cyclical migration among three tissues occurs less frequent than expected given the amount of viral migration. The analysis also provides evidence for heterogeneity in the magnitude that these features are present across hosts. Adjusting for missing tissue data identifies system-level features within a host as well as heterogeneity in the presence of these features across hosts that are not detected when the analysis only considers the observed data. Discussion: Identification of common features in viral migration may increase the efficiency of HIV cure efforts as it enables targeting specific processes. [ABSTRACT FROM AUTHOR]

Study of the genome of the SARS-CoV-2 virus, particularly with regard to understanding evolution of the virus, is crucial for managing the COVID-19 pandemic. To this end, we sample viral genomes from the GISAID repository and use several of the maximum likelihood approaches implemented in PAML, a collection of open source programs for phylogenetic analyses of DNA and protein sequences, to assess evidence for positive selection in the protein-coding regions of the SARS-CoV-2 genome. Across all major variants identified by June 2021, we find limited evidence for positive selection. In particular, we identify positive selection in a small proportion of sites (5-15%) in the protein-coding region of the spike protein across variants. Most other variants did not show a strong signal for positive selection overall, though there were indications of positive selection in the Delta and Kappa variants for the nucleocapsid protein. We additionally use a forward selection procedure to fit a model that allows branch-specific estimates of selection along a phylogeny relating the variants, and find that there is variation in the selective pressure across variants for the spike protein. Our results highlight the utility of computational approaches for identifying genomic regions under selection. [ABSTRACT FROM AUTHOR]

Caprine theileriosis, caused by Theileria ovis is a serious production issue, especially in the areas that depend on goats and sheep for milk, meat, and other economic benefits. Pakistan has a large goat population, but few reports have been documented from this country regarding PCR-based detection of T. ovis. The molecular prevalence of T. ovis, on a seasonal basis, in various goat breeds enrolled from Muzaffar Garh district of Punjab in Pakistan was determined from October 2018 to September 2019. In this study, 1084 goat blood samples were screened for the detection of T. ovis DNA through PCR-based amplification of 18S rRNA gene. Out of 1084 goats, 12 (1.11%) were infected with T. ovis. The parasite prevalence varied with the sampling seasons (Chi square test, P = 0.008), and the parasite prevalence was highest in goat blood samples collected in summer (2.39%) followed by winter (1.88%). DNA sequencing and BLAST analysis confirmed the presence of T. ovis, and the amplified isolates from the 18S rRNA gene of T. ovis were found to be highly conserved during phylogenetic analysis. Young goats (Fischer exact test, P = 0.022) were found more infected with T. ovis during the winter season. Infected goats had elevated white blood cell counts (Two-sample t-test, P = 0.04), blood urea nitrogen to Creatinine ratio (Two-sample t-test, P = 0.02) and decreased serum Creatinine (Two-sample t-test, P = 0.001) as compared to T. ovis negative goats. We report a relatively low molecular prevalence of T. ovis in goats from the Muzaffar Garh district. However, it is recommended that control measures to eradicate T. ovis infection in goats in this area should be taken. [ABSTRACT FROM AUTHOR]

Bacterial content of mosquitoes has given rise to the development of innovative tools that influence and seek to control malaria transmission. This study identified the bacterial microbiota in field-collected female adults of the Anopheles hyrcanus group and three Anopheles species, Anopheles nivipes, Anopheles philippinensis, and Anopheles vagus, from an endemic area in the southeastern part of Ubon Ratchathani Province, northeastern Thailand, near the Lao PDR-Cambodia-Thailand border. A total of 17 DNA libraries were generated from pooled female Anopheles abdomen samples (10 abdomens/ sample). The mosquito microbiota was characterized through the analysis of DNA sequences from the V3−V4 regions of the 16S rRNA gene, and data were analyzed in QIIME2. A total of 3,442 bacterial ASVs were obtained, revealing differences in the microbiota both within the same species/group and between different species/group. Statistical difference in alpha diversity was observed between An. hyrcanus group and An. vagus and between An. nivipes and An. vagus, and beta diversity analyses showed that the bacterial community of An. vagus was the most dissimilar from other species. The most abundant bacteria belonged to the Proteobacteria phylum (48%-75%) in which Pseudomonas, Serratia, and Pantoea were predominant genera among four Anopheles species/group. However, the most significantly abundant genus observed in each Anopheles species/group was as follows: Staphylococcus in the An. hyrcanus group, Pantoea in the An. nivipes, Rosenbergiella in An. philippinensis, and Pseudomonas in An. vagus. Particularly, Pseudomonas sp. was highly abundant in all Anopheles species except An. nivipes. The present study provides the first study on the microbiota of four potential malaria vectors as a starting step towards understanding the role of the microbiota on mosquito biology and ultimately the development of potential tools for malaria control. [ABSTRACT FROM AUTHOR]

Arthropods account for a large proportion of animal biomass and diversity in terrestrial systems, making them crucial organisms in our environments. However, still too little is known about the highly abundant and megadiverse groups that often make up the bulk of collected samples, especially in the tropics. With molecular identification techniques ever more evolving, analysis of arthropod communities has accelerated. In our study, which was conducted within the Global Malaise trap Program (GMP) framework, we operated two closely placed Malaise traps in Padang, Sumatra, for three months. We analyzed the samples by DNA barcoding and sequenced a total of more than 70,000 insect specimens. For sequence clustering, we applied three different delimitation techniques, namely RESL, ASAP, and SpeciesIdentifier, which gave similar results. Despite our (very) limited sampling in time and space, our efforts recovered more than 10,000 BINs, of which the majority are associated with "dark taxa". Further analysis indicates a drastic undersampling of both sampling sites, meaning that the true arthropod diversity at our sampling sites is even higher. Regardless of the close proximity of both Malaise traps (< 360 m), we discovered significantly distinct communities. [ABSTRACT FROM AUTHOR]

The transcriptional activator p53 is a tumor suppressor protein that controls cellular pathways important for cell fate decisions, including cell cycle arrest, senescence, and apoptosis. It functions as a tetramer by binding to specific DNA sequences known as response elements (REs) to control transcription via interactions with co-regulatory complexes. Despite its biological importance, the mechanism by which p53 binds REs remains unclear. To address this, we have used an in vitro single molecule fluorescence approach to quantify the dynamic binding of full-length human p53 to five native REs in real time under equilibrium conditions. Our approach enabled us to quantify the oligomeric state of DNA-bound p53. We found little evidence that dimer/DNA complexes form as intermediates en route to binding or dissociation of p53 tetramer/DNA complexes. Interestingly, however, at some REs dimers can rapidly exchange from tetramer/DNA complexes. Real time kinetic measurements enabled us to determine rate constants for association and dissociation at all five REs, which revealed two kinetically distinct populations of tetrameric p53/RE complexes. For the less stable population, the rate constants for dissociation were larger at REs closest to consensus, showing that the more favorable binding sequences form the least kinetically stable complexes. Together our single molecule measurements provide new insight into mechanisms by which tetrameric p53 forms complexes on different native REs. [ABSTRACT FROM AUTHOR]

Many high-throughput sequencing datasets can be represented as objects with coordinates along a reference genome. Currently, biological investigations often involve a large number of such datasets, for example representing different cell types or epigenetic factors. Drawing overall conclusions from a large collection of results for individual datasets may be challenging and time-consuming. Meaningful interpretation often requires the results to be aggregated according to metadata that represents biological characteristics of interest. In this light, we here propose the hierarchical Genomic Suite HyperBrowser (hGSuite), an open-source extension to the GSuite HyperBrowser platform, which aims to provide a means for extracting key results from an aggregated collection of high-throughput DNA sequencing data. The hGSuite utilizes a metadata-informed data cube to calculate various statistics across the multiple dimensions of the datasets. With this work, we show that the hGSuite and its associated data cube methodology offers a quick and accessible way for exploratory analysis of large genomic datasets. The web-based toolkit named hGsuite Hyperbrowser is available at https://hyperbrowser.uio.no/hgsuite under a GPLv3 license. [ABSTRACT FROM AUTHOR]

Rhyacoglanis pulcher is a rare Neotropical rheophilic bumblebee catfish known only from the type locality in the Cis-Andean Amazon region, Ecuador, and the type-species of the genus. So far, the three syntypes collected in 1880 were the only specimens unambiguously associated to the name R. pulcher available in scientific collections. Recently, a specimen was discovered in a fast-flowing stretch of the Villano river, a tributary of the Curaray river, Napo river basin, Ecuador, representing a new record after nearly 140 years. Here, we present this new record, identified by morphology, provide the DNA barcode sequence of the specimen, and propose why the species of Rhyacoglanis are scarce in zoological collections. Additionally, we discuss the intraspecific variation in the color pattern observed in R. pulcher. [ABSTRACT FROM AUTHOR]

The present study is the first to report Xylaria karsticola isolated from the basidiocarp of Macrolepiota procera (Basidiomycota), from Stara Planina Mountain, Bulgaria and second report for such species found in Europe. The fungal isolate was in vitro cultivated and the morphology was observed. It was primarily determined as a xylariaceous morphotype at the intragenus level, based on the evaluation of colony growth rate, color, and stromatic structure formation and was confirmed by unique conidiophores and conidia. The molecular identification of the isolate was performed by amplification of ITS1-5.8S-ITS2 region and the strain was identified as Xylaria karsticola with 97.57% of confidence. The obtained sequence was deposited in the GenBank database under the accession number MW996752 and in the National Bank of Industrial Microorganisms and Cell Cultures of Bulgaria under accession number NBIMCC 9097. The phylogenetic analysis of the isolate was also conducted by including 26 sequences obtained from different Xylaria isolates. Considering the phylogenetic data, X. karsticola NBIMCC 9097 was grouped along with other X. karsticola isolates, although the DNA sequence of the novel X. karsticola was rather distantly related to the other X. karsticola sequence data. The results were supported by the bootstrap analysis (100%) and indicated the different origin of the examined X. karsticola NBIMCC 9097. [ABSTRACT FROM AUTHOR]

The grapevine trunk disease, Eutypa dieback (ED), causes significant vine decline and yield reduction. For many years, the fungus Eutypa lata was considered the main pathogen causing ED of grapevines in Australia. Recent studies showed other Diatrypaceous fungi were also associated with vines exhibiting dieback symptoms but there is limited information on how these fungal pathogens spread in vineyards. Thus, information on the spore dispersal patterns of Diatrypaceous fungi in different wine regions will assist in identifying high-risk infection periods in vineyards. Using more than 6800 DNA samples from airborne spores collected from eight wine regions in south-eastern Australia over 8 years using a Burkard spore trap, this study investigated the diversity and abundance of Diatrypaceous species, using multi-faceted molecular tools. A multi-target quantitative PCR (qPCR) assay successfully detected and quantified Diatrypaceous spores from 30% of the total samples with spore numbers and frequency of detection varying between regions and years. The high-resolution melting analysis (HRMA) coupled with DNA sequencing identified seven species, with E. lata being present in seven regions and the most prevalent species in the Adelaide Hills, Barossa Valley and McLaren Vale. Cryptovalsa ampelina and Diatrype stigma were the predominant species in the Clare Valley and Coonawarra, respectively while Eutypella citricola and Eu. microtheca dominated in the Hunter Valley and the Riverina regions. This study represents the first report of D. stigma and Cryptosphaeria multicontinentalis in Australian vineyards. This study further showed rainfall as a primary factor that triggers spore release, however, other weather factors that may influence the spore release in different climatic regions of Australia still requires further investigation. [ABSTRACT FROM AUTHOR]

To reduce the genome sequence representation, restriction site-associated DNA sequencing (RAD-seq) protocols is being widely used either with single-digest or double-digest methods. In this study, we genotyped the sesame population (48 sample size) in a pilot scale to compare single and double-digest RAD-seq (sd and ddRAD-seq) methods. We analysed the resulting short-read data generated from both protocols and assessed their performance impacting the downstream analysis using various parameters. The distinct k-mer count and gene presence absence variation (PAV) showed a significant difference between the sesame samples studied. Additionally, the variant calling from both datasets (sdRAD-seq and ddRAD-seq) exhibits a significant difference between them. The combined variants from both datasets helped in identifying the most diverse samples and possible sub-groups in the sesame population. The most diverse samples identified from each analysis (k-mer, gene PAV, SNP count, Heterozygosity, NJ and PCA) can possibly be representative samples holding major diversity of the small sesame population used in this study. The best possible strategies with suggested inputs for modifications to utilize the RAD-seq strategy efficiently on a large dataset containing thousands of samples to be subjected to molecular analysis like diversity, population structure and core development studies were discussed. [ABSTRACT FROM AUTHOR]

Early detection of breast cancer can be achieved through mutation detection in DNA sequences, which can be acquired through patient blood samples. Mutation detection can be performed using alignment and machine learning techniques. However, alignment techniques require reference sequences, and machine learning techniques still cannot predict index mutation and require supporting tools. Therefore, in this research, a Temporal Convolutional Network (TCN) model was proposed to detect the type and index mutation faster and without reference sequences and supporting tools. The architecture of the proposed TCN model is specifically designed for sequential labeling tasks on DNA sequence data. This allows for the detection of the mutation type of each nucleotide in the sequence, and if the nucleotide has a mutation, the index mutation can be obtained. The proposed model also uses 2-mers and 3-mers mapping techniques to improve detection performance. Based on the tests that have been carried out, the proposed TCN model can achieve the highest F1-score of 0.9443 for COSMIC dataset and 0.9629 for RSCM dataset, Additionally, the proposed TCN model can detect index mutation six times faster than BiLSTM model. Furthermore, the proposed model can detect type and index mutations based on the patient's DNA sequence, without the need for reference sequences or other additional tools. [ABSTRACT FROM AUTHOR]

Protein tandem repeats (TRs) are motifs comprised of near-identical contiguous sequence duplications. They are found in approximately 14% of all proteins and are implicated in diverse biological functions facilitating both structured and disordered protein-protein and protein-DNA interactions. These functionalities make protein TR domains an attractive component for the modular design of protein constructs. However, the repetitive nature of DNA sequences encoding TR motifs complicates their synthesis and mutagenesis by traditional molecular biology workflows commonly employed by protein engineers and synthetic biologists. To address this challenge, we developed a computational protocol to significantly reduce the complementarity of DNA sequences encoding TRs called TReSR (for Tandem Repeat DNA Sequence Redesign). The utility of TReSR was demonstrated by constructing a novel constitutive repressor synthesized by duplicating the LacI DNA binding domain into a single-chain TR construct by assembly PCR. Repressor function was evaluated by expression of a fluorescent reporter delivered on a single plasmid encoding a three-component genetic circuit. The successful application of TReSR to construct a novel TR-containing repressor with a DNA sequence that is amenable to PCR-based construction and manipulation will enable the incorporation of a wide range of TR-containing proteins for protein engineering and synthetic biology applications. [ABSTRACT FROM AUTHOR]

Within the realms of human thoughts on nature, Fourier analysis is considered as one of the greatest ideas currently put forwarded. The Fourier transform shows that any periodic function can be rewritten as the sum of sinusoidal functions. Having a Fourier transform view on real-world problems like the DNA sequence of genes, would make things intuitively simple to understand in comparison with their initial formal domain view. In this study we used discrete Fourier transform (DFT) on DNA sequences of a set of genes in the bovine genome known to govern milk production, in order to develop a new gene clustering algorithm. The implementation of this algorithm is very user-friendly and requires only simple routine mathematical operations. By transforming the configuration of gene sequences into frequency domain, we sought to elucidate important features and reveal hidden gene properties. This is biologically appealing since no information is lost via this transformation and we are therefore not reducing the number of degrees of freedom. The results from different clustering methods were integrated using evidence accumulation algorithms to provide in insilico validation of our results. We propose using candidate gene sequences accompanied by other genes of biologically unknown function. These will then be assigned some degree of relevant annotation by using our proposed algorithm. Current knowledge in biological gene clustering investigation is also lacking, and so DFT-based methods will help shine a light on use of these algorithms for biological insight. [ABSTRACT FROM AUTHOR]

Echinostomatid digeneans belonging to the genus Rhopalias are intestinal trematodes found mainly in opossums in the New World. The genus comprises seven species, but their life cycles and intermediate hosts have been unknown until now. During our long-term study carried out in freshwater habitats within the state of Minas Gerais, Southeast Brazil, echinostomatid cercariae lacking collar spines were found in planorbid snails Biomphalaria glabrata, Biomphalaria straminea, Drepanotrema lucidum and Gundlachia ticaga in six different batches of snail samples collected between 2010 and 2019. Morphologically, the larvae reported herein are morphologically consistent with each other and characterized by the presence of 2–3 large ovoid or spherical corpuscles in each main duct of the excretory system, resembling to Cercaria macrogranulosa previously described from the same region of Brazil. Partial sequences of the ITS (ITS1-5.8S-ITS2) region and 28S gene of the nuclear ribosomal RNA operon, and partial sequences of mitochondrial nad1 and cox1 genes were obtained and compared with the data available for members of the family Echinostomatidae. Nuclear markers indicate that all samples of cercariae evaluated in the present study can be assigned to Rhopalias, but distinct from North American isolates of Rhopalias macracanthus, Rhopalias coronatus and Rhopalias oochi (divergence 0.2–1.2% in 28S and 0.8–4.7% in ITS). The lack of differences verified in both 28S and ITS in 5 out 6 studied samples suggested that they belong to the same species. However, nad1 sequences revealed that our cercariae correspond to three distinct species of Rhopalias (interspecific divergence: 7.7–9.9%), named here as Rhopalias sp. 1, found in B. straminea and G. ticaga, Rhopalias sp. 2 found in B. glabrata and D. lucidum, and Rhopalias sp. 3 also found in D. lucidum. They also differ by 10.8–17.2% from a North American isolate of R. macracanthus sequenced in this study. The cox1 sequences obtained for Rhopalias sp. 1 and Rhopalias sp. 2 (but not Rhopalias sp. 3) reveal that they are distinct from North American isolates of R. macracanthus (genetic divergence 16.3–16.5% and 15.6–15.7%, respectively), R. coronatus (9.2–9.3% and 9.3–9.5%) and Rhopalias oochi (9.0% and 9.5–10.1%). Encysted metacercariae with general morphology similar to that of the body of cercariae were found in tadpoles of Rhinella sp. from the same stream where snails harbored Rhopalias sp. 2, suggesting that the amphibians could act as second intermediate hosts of species of Rhopalias. Data obtained provide the first insights into the life cycle of this unusual echinostomatid genus. [ABSTRACT FROM AUTHOR]

Campylobacter spp. is often underreported and underrated bacteria that present real health risks to both humans and animals, including non-human primates. It is a commensal microorganism of gastrointestinal tract known to cause gastroenteritis in humans. Commonly found in many wild animals including non-human primates (monkeys- Rhesus macaques) these pathogens are known to be a common cause of diarrhea in humans in many parts of developing and under developed countries. Rhesus macaques from the two holy sites in Kathmandu (Pashupati and Swoyambhu) were included in this cross-sectional study. Diarrheal samples of monkeys were analyzed to detect and characterize the pathogen using 16S rRNA-based PCR screening, followed by DNA sequencing and phylogenetic analysis. Out of a total 67 collected diarrheal samples, Campylobacter spp. were detected in the majority of the samples (n = 64; 96%). DNA sequences of the amplified PCR products were successfully obtained from 13 samples. Phylogenetic analysis identified Candidatus Campylobacter infans (n = 10, Kimura-2 parameter (K2P) pairwise distance values of 0.002287). Remaining three sequences might potentially belong to a novel Campylobacter species/sub-species- closely relating to known species of C. helviticus (K2P pairwise distance of 0.0267). Both Candidatus Campylobacter infans and C. helvitucus are known to infect humans and animals. Additionally, we also detected the bacteria in water and soil samples from the sites. Campylobacter spp. caused the 2018 diarrhea outbreak in Rhesus macaques in the Kathmandu valley. Campylobacter might be one of the important contributing pathogens in diarrheal outbreaks-both in humans and animals (monkeys) in Nepal. Due to close interactions of these animals with humans and other animals, One Health approach might be the most effective way to prevent and mitigate the threat posed by this pathogen. [ABSTRACT FROM AUTHOR]

Microbiomes have been the focus of a substantial research effort in the last decades. The composition of microbial populations is normally determined by comparing DNA sequences sampled from those populations with the sequences stored in genomic databases. Therefore, the amount of information available in databanks should be expected to constrain the accuracy of microbiome analyses. Albeit normally ignored in microbiome studies, this constraint could severely compromise the reliability of microbiome data. To test this hypothesis, we generated virtual bacterial populations that exhibit the ecological structure of real-world microbiomes. Confronting the analyses of virtual microbiomes with their original composition revealed critical issues in the current approach to characterizing microbiomes, issues that were empirically confirmed by analyzing the microbiome of Galleria mellonella larvae. To reduce the uncertainty of microbiome data, the effort in the field must be channeled towards significantly increasing the amount of available genomic information and optimizing the use of this information. [ABSTRACT FROM AUTHOR]

Massively parallel, second-generation short-read DNA sequencing has become an integral tool in biology for genomic studies. Offering highly accurate base-pair resolution at the most competitive price, the technology has become widespread. However, high-throughput generation of multiplexed DNA libraries can be costly and cumbersome. Here, we present a cost-conscious protocol for generating multiplexed short-read DNA libraries using a bead-linked transposome from Illumina. We prepare libraries in high-throughput with small reaction volumes that use 1/50th the amount of transposome compared to Illumina DNA Prep tagmentation protocols. By reducing transposome usage and optimising the protocol to circumvent magnetic bead-based clean-ups between steps, we reduce costs, labour time and DNA input requirements. Developing our own dual index primers further reduced costs and enables up to nine 96-well microplate combinations. This facilitates efficient usage of large-scale sequencing platforms, such as the Illumina NovaSeq 6000, which offers up to three terabases of sequencing per S4 flow cell. The protocol presented substantially reduces the cost per library by approximately 1/20th compared to conventional Illumina methods. [ABSTRACT FROM AUTHOR]

A DNA barcode is a short piece of standard DNA sequence used for species determination and discrimination. Representation of DNA barcodes is essential for DNA barcodes' applications in the transportation and recognition of biological materials. Previously, we have compared different strategies for representing the DNA barcodes. In the present study, we have developed a compression algorithm based on binary coding or Huffman coding scheme, followed by converting the binary digits into Base64 digits. The combination of this compression algorithm and the QR representation leads to the dynamic DNA QR coding algorithm (DDQR). We tested the DDQR algorithm on simulated data and real DNA barcode sequences from the commonly used plant and animal DNA barcode markers: rbcL, matK, trnH-psbA, ITS2, and COI. We compared the compression efficiency of DDQR and another state-of-the-art DNA compression algorithm GeCo3 for sequences with various base compositions and lengths. We found that DDQR had a higher compression rate than GeCo3 for DNA sequences shorter than 800 bp, which is the typical size range for DNA barcodes. We also upgraded a web server (http://www.1kmpg.cn/ddqr) that provides three functions: retrieval of DNA barcode sequences, encoding DNA barcode sequences to DDQR codes, and decoding DDQR codes to DNA barcode sequences. The DDQR algorithm and the webserver will be invaluable to applying DNA barcode technology in the food and traditional medicine industries. [ABSTRACT FROM AUTHOR]

A G-rich DNA sequence from yeast that can form a non-canonical G-quadruplex structure was cloned into a plasmid vector and subjected to Sanger sequencing using dye-labeled dideoxynucleotides. Two different effects were observed. In one, presence of the G4 sequence on the template strand led to incorrect incorporation of an A residue at an internal position in the G4 sequence. In the other, the nascent strand caused attenuation of the readout coincident with synthesis of the G-rich DNA. The two effects are novel examples of disruption in DNA synthesis caused by a G4 sequence. These results provide a new example of a DNA structure that could influence genomic stability in human cells. [ABSTRACT FROM AUTHOR]

We developed a simple and reliable method for the isolation of haploid nuclei from fresh and frozen testes. The described protocol uses readily available reagents in combination with flow cytometry to separate haploid and diploid nuclei. The protocol can be completed within 1 hour and the resulting individual haploid nuclei have intact morphology. The isolated nuclei are suitable for library preparation for high-throughput DNA and RNA sequencing using bulk or single nuclei. The protocol was optimised with mouse testes and we anticipate that it can be applied for the isolation of mature sperm from other mammals including humans. [ABSTRACT FROM AUTHOR]

The naturally occurring ectoparasite salmon lice (Lepeophtherirus salmonis) poses a great challenge for the salmon farming industry, as well as for wild salmonids in the Northern hemisphere. To better control the infestation pressure and protect the production, there is a need to provide fish farmers with sensitive and efficient tools for rapid early detection and monitoring of the parasitic load. This can be achieved by targeting L. salmonis DNA in environmental samples. Here, we developed and tested a new L. salmonis specific DNA-based assay (qPCR assay) for detection and quantification from seawater samples using an analytical pipeline compatible with the Environmental Sample Processor (ESP) for autonomous water sample analysis of gene targets. Specificity of the L. salmonis qPCR assay was demonstrated through in-silico DNA analyses covering sequences of different L. salmonis isolates. Seawater was spiked with known numbers of nauplii and copepodite free-swimming (planktonic) stages of L. salmonis to investigate the relationship with the number of marker gene copies (MGC). Finally, field samples collected at different times of the year in the vicinity of a salmon production farm in Western Norway were analyzed for L. salmonis detection and quantification. The assay specificity was high and a high correlation between MGC and planktonic stages of L. salmonis was established in the laboratory conditions. In the field, L. salmonis DNA was consequently detected, but with MGC number below that expected for one copepodite or nauplii. We concluded that only L. salmonis tissue or eDNA residues were detected. This novel study opens for a fully automatized L. salmonis DNA quantification using ESP robotic to monitor the parasitic load, but challenges remain to exactly transfer information about eDNA quantities to decisions by the farmers and possible interventions. [ABSTRACT FROM AUTHOR]

Although bacterial detection by 16S rRNA gene amplicon DNA sequencing is a widely-applied technique, standardized methods for sample preparation and DNA extraction are needed to ensure accuracy, reproducibility, and scalability for automation. To develop these methods for bovine bulk milk, we assembled and tested a bacterial cell mock community (BCMC) containing bacterial species commonly found in milk. The following protocol variations were examined:: BCMC enumeration (colony enumeration or microscopy), sample volume (200 μl to 30 ml), sample storage condition (frozen in PBS or 25% glycerol or exposure to freeze-thaw cycles), cell lysis method (bead-beating, vortex, enzymatic), and DNA extraction procedure (MagMAX Total, MagMAX CORE, and MagMAX Ultra 2.0, with and without either Proteinase K or RNase A). Cell enumeration by microscopy was more accurate for quantification of the BCMC contents. We found that least 10 mL (≥ 104 cells in high quality milk) is needed for reproducible bacterial detection by 16S rRNA gene amplicon DNA sequencing, whereas variations in storage conditions caused minor differences in the BCMC. For DNA extraction and purification, a mild lysis step (bead-beating for 10 s at 4 m/s or vortexing at 1800 rpm for 10 s) paired with the MagMAX Total kit and Proteinase K digestion provided the most accurate representation of the BCMC. Cell lysis procedures conferred the greatest changes to milk microbiota composition and these effects were confirmed to provide similar results for commercial milk samples. Overall, our systematic approach with the BCMC is broadly applicable to other milk, food, and environmental samples therefore recommended for improving accuracy of culture-independent, DNA sequence-based analyses of microbial composition in different habitats. [ABSTRACT FROM AUTHOR]

Circular single stranded DNA viruses (CRESS DNA) encoding a homologous replication-associated protein (REP) have been identified in most of eukaryotic groups. It is not clear yet the role in human diseases or details of the life cycle of these viruses. Recently, much interest has been raised in the evolutionary history of CRESS DNA owing to the increasing number of new sequences obtained by Next-Generation Sequencing (NGS) in distinct host species. In this study we describe two full-length CRESS DNA genomes obtained of two newly diagnosed HIV patients from São Paulo State, Brazil. The initial BLASTx search indicated that both sequences (named SP-FFB/2020 and SP-MJMS/2020) are highly similar (98%) to a previous CRESS DNA sequence detected in human fecal sample from Peru in 2016 and designated as pecovirus (Peruvian stool-associated circo-like virus). This study reported for the first time the Human feces pecovirus in the feces of two newly diagnosed HIV patients in Brazil. Our comparative analysis showed that although pecoviruses in South America share an identical genome structure they diverge and form distinct clades. Thus, we suggest the circulation of different species of pecoviruses in Latin America. Nevertheless, further studies must be done to examine the pathogenicity of this virus. [ABSTRACT FROM AUTHOR]

Aim: To identify the molecular basis of Congenital Hereditary Endothelial Dystrophy CHED caused by mutations in SLC4A11, in the consanguineous Pakistani families. Methods: A total of 7 consanguineous families affected with Congenital Hereditary Endothelial Dystrophy were diagnosed and registered with the help of ophthalmologists. Blood samples were collected from affected and unaffected members of the enrolled families. Mutational analysis was carried out by DNA sequencing using both Sanger and Whole Exome Sequencing (WES). Probands of each pedigree from the 7 families were used for WES. Results were analyzed with the help of different bioinformatics tools. Results: The sequencing results demonstrated three known homozygous mutations in gene SLC4A11 in probands of 7 families. These mutations p.Glu675Ala, p.Val824Met, and p.Arg158fs include 2 missense and 1 frameshift mutation. The mutations result in amino acids that were highly conserved in SLC4A11 across different species. The mutations were segregated with the disease phenotype in the families. Conclusion: This study reports 3 mutations in 7 families. One of the pathogenic mutations (p.R158fs) was identified for the first time in the Pakistani population. However, two mutations (p.Glu675Ala, p.Val824Met) were previously reported in two and one Pakistani family respectively. As these mutations segregate with the disease phenotype and bioinformatics tool also liable them as pathogenic, they are deemed as probable cause of underlying disease. [ABSTRACT FROM AUTHOR]

We formulate and apply a novel paradigm for characterization of genome data quality, which quantifies the effects of intentional degradation of quality. The rationale is that the higher the initial quality, the more fragile the genome and the greater the effects of degradation. We demonstrate that this phenomenon is ubiquitous, and that quantified measures of degradation can be used for multiple purposes, illustrated by outlier detection. We focus on identifying outliers that may be problematic with respect to data quality, but might also be true anomalies or even attempts to subvert the database. [ABSTRACT FROM AUTHOR]

Bayesian skyline plots (BSPs) are a useful tool for making inferences about demographic history. For example, researchers typically apply BSPs to test hypotheses regarding how climate changes have influenced intraspecific genetic diversity over time. Like any method, BSP has assumptions that may be violated in some empirical systems (e.g., the absence of population genetic structure), and the naïve analysis of data collected from these systems may lead to spurious results. To address these issues, we introduce P2C2M.Skyline, an R package designed to assess model adequacy for BSPs using posterior predictive simulation. P2C2M.Skyline uses a phylogenetic tree and the log file output from Bayesian Skyline analyses to simulate posterior predictive datasets and then compares this null distribution to statistics calculated from the empirical data to check for model violations. P2C2M.Skyline was able to correctly identify model violations when simulated datasets were generated assuming genetic structure, which is a clear violation of BSP model assumptions. Conversely, P2C2M.Skyline showed low rates of false positives when models were simulated under the BSP model. We also evaluate the P2C2M.Skyline performance in empirical systems, where we detected model violations when DNA sequences from multiple populations were lumped together. P2C2M.Skyline represents a user-friendly and computationally efficient resource for researchers aiming to make inferences from BSP. [ABSTRACT FROM AUTHOR]

Successful recruitment of invertebrate larvae to reef substrates is essential to the health of tropical coral reef ecosystems and to their capacity to recover from disturbances. Crustose calcifying red algae (CCRA) are a species rich group of seaweeds that have been identified as important recruitment substrates for scleractinian corals. Most studies on the settlement preference of coral larvae on CCRA use morphological species identifications that can lead to unreliable species identification and do not allow for examining species-specific interactions between coral larvae and CCRA. Accurate identifications of CCRA species is important for coral reef restoration and management to assess CCRA community composition and to detect CCRA species that are favored as coral recruitment substrates. In this study, DNA sequence analysis, was used to identify CCRA species to (1) investigate the species richness and community composition of CCRA on experimental coral recruitment tiles and (2) assess if the coral Acropora surculosa preferred any of these CCRA species as recruitment substrates. The CCRA community assemblages on the coral recruitment tiles was species-rich, comprising 27 distinct CCRA species of the orders Corallinales and Peyssonneliales which constitute new species records for Guam. Lithophylloideae sp. 1 (Corallinales) was the CCRA species that was significantly favored by coral larvae as a recruitment substrate. Lithophylloideae sp. 1 showed to hold a valuable ecological role for coral larval recruitment preference. Lithophylloideae sp. 1 had the highest benthic cover on the recruitment tiles and contained most A. surculosa recruits. DNA barcoding revealed a high taxonomic diversity of CCRA species on a microhabitat scale and provided detailed insight into the species-specific ecological interactions between CCRA and corals. With a steady decline in coral cover, detailed information on species interactions that drive reef recovery is valuable for the planning of marine management actions and restoration efforts. [ABSTRACT FROM AUTHOR]

Structural fluctuations of nucleosomes modulate the access to internal DNA in eukaryotic cells; clearly characterisation of this fundamental process is crucial to understanding gene regulation. Here we apply PhAST (Photochemical Analysis of Structural Transitions) to monitor at a base pair level, structural alterations induced all along the DNA upon histone binding or release. By offering the first reliable, detailed comparison of nucleosome assembly and disassembly in vitro, we reveal similarities and differences between the two processes. We identify multiple, sequential intermediate states characterised by specific PhAST signals whose localisation and amplitude reflect asymmetries of DNA/histone interactions with respect to the nucleosome pseudo dyad. These asymmetries involve not only the DNA extremities but also regions close to the pseudo dyad. Localisations of asymmetries develop in a consistent manner during both assembly and disassembly processes; they primarily reflect the DNA sequence effect on the efficiency of DNA-histone binding. More unexpectedly, the amplitude component of PhAST signals not only evolves as a function of intermediate states but does so differently between assembly and disassembly pathways. Our observation of differences between assembly and disassembly opens up new avenues to define the role of the DNA sequence in processes underlying the regulation of gene expression. Overall, we provide new insights into how the intrinsic properties of DNA are integrated into a holistic mechanism that controls chromatin structure. [ABSTRACT FROM AUTHOR]

One of the most precise methods to detect prostate cancer is by evaluation of a stained biopsy by a pathologist under a microscope. Regions of the tissue are assessed and graded according to the observed histological pattern. However, this is not only laborious, but also relies on the experience of the pathologist and tends to suffer from the lack of reproducibility of biopsy outcomes across pathologists. As a result, computational approaches are being sought and machine learning has been gaining momentum in the prediction of the Gleason grade group. To date, machine learning literature has addressed this problem by using features from magnetic resonance imaging images, whole slide images, tissue microarrays, gene expression data, and clinical features. However, there is a gap with regards to predicting the Gleason grade group using DNA sequences as the only input source to the machine learning models. In this work, using whole genome sequence data from South African prostate cancer patients, an application of machine learning and biological experiments were combined to understand the challenges that are associated with the prediction of the Gleason grade group. A series of machine learning binary classifiers (XGBoost, LSTM, GRU, LR, RF) were created only relying on DNA sequences input features. All the models were not able to adequately discriminate between the DNA sequences of the studied Gleason grade groups (Gleason grade group 1 and 5). However, the models were further evaluated in the prediction of tumor DNA sequences from matched-normal DNA sequences, given DNA sequences as the only input source. In this new problem, the models performed acceptably better than before with the XGBoost model achieving the highest accuracy of 74 ± 01, F1 score of 79 ± 01, recall of 99 ± 0.0, and precision of 66 ± 0.1. [ABSTRACT FROM AUTHOR]

Diabetes mellitus causes an increased incidence of congenital heart malformations. However, the pathogenesis and potential epigenetic mechanism involved in this process are unclear. In this study, we used MethylRAD sequencing to compare changes in methylation levels in the genomic landscapes in the fetal heart in a rat model of hyperglycemia. Our results showed that methylation of CCGG/CCNGG sites were mostly enriched in intergenic regions, followed by intron, exon, upstream and the 5′ and 3′ untranslated regions. qRT-PCR results confirmed the MethylRAD sequencing findings, suggesting that abnormal CCGG/CCNGG methylation in the upstream region regulated gene expression. The differential methylation genes (DMGs) based on the CCGG and CCNGG sites in the upstream region were examined by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis. Gene Ontology indicated that the CCGG-based DMGs involved in biological process and function were mainly related to transcription and co-SMAD binding. The CCNGG-based DMGs were mainly related to transcription and cytokine-mediated signaling pathways. Kyoto Encyclopedia of Genes and Genomes analysis indicated that CCGG-based DMGs were mainly involved in the Wnt signaling and TGF-β signaling pathways. CCNGG-based DMGs were involved in the TNF signaling and apoptosis pathways. These genes may play dominant roles in cardiomyocyte apoptosis and heart disease and require further study. These genes may also serve as potential molecular targets or diagnostic biomarkers for heart malformations under hyperglycemia. [ABSTRACT FROM AUTHOR]

Next generation sequencing (NGS) assays with large targeted gene panels can comprehensively profile cancer somatic mutations in a tumor sample. Given the rapid adoption of such assays for circulating tumor DNA (ctDNA) analysis in clinical oncology, it is essential for the community to understand their analytical performance in liquid biopsy settings. Here, we directly compared five ctDNA NGS assays, most of which having a panel of 400 or more genes, with simulated samples harboring mutations relevant to solid tumors or myeloid malignancy. Our results indicate that the detection sensitivity and reproducibility of all five assays was 90% or higher when the mutations were at 0.5% or 1.0% allele frequency, and with optimal DNA input of 30 ng or 50 ng per vendor's protocol. The performances decreased and varied dramatically, when mutations were at a 0.1% allele frequency and/or when a lower genomic input of 10 ng DNA was used. Interestingly, one of the assays repeatedly showed higher rate of false positivity than the others across two different sample sets. Multiple intrinsic technical factors pertaining to the NGS assays were further investigated. Notable differences among the assays were seen for depth of coverage and background noise, which profoundly impacted assay performance. The results derived from this study are highly informative and provide a framework to assess and select suitable assays for specific application in cancer monitoring and potential clinical use. [ABSTRACT FROM AUTHOR]

The respiratory tract has a resident microbiome with low biomass and limited diversity. This results in difficulties with sample preparation for sequencing due to uneven bacteria-to-host DNA ratio, especially for small tissue samples such as mouse lungs. We compared effectiveness of current procedures used for DNA extraction in microbiome studies. Bronchoalveolar lavage fluid (BALF) and lung tissue samples were collected to test different forms of sample pre-treatment and extraction methods to increase bacterial DNA yield and optimize library preparation. DNA extraction using a pre-treatment method of mechanical lysis (lung tissue) and one-step centrifugation (BALF) increased DNA yield and bacterial content of samples. In contrast, a significant increase of environmental contamination was detected after phenol chloroform isoamyl alcohol (PCI) extraction and nested PCR. While PCI has been a standard procedure used in microbiome studies, our data suggests that it is not efficient for DNA extraction of frozen low biomass samples. Finally, a DNA Enrichment kit was tested and found to improve the 16S copy number of lung tissue with a minor shift in microbial composition. Overall, we present a standardized method to provide high yielding DNA and improve sequencing coverage of low microbial biomass frozen samples with minimal contamination. [ABSTRACT FROM AUTHOR]

Determining the genetic basis of yield and water deficient tolerance in wheat is vital for wheat breeding programs. Herein, a genome-wide association study (GWAS) was performed for water deficient and yield-related attributes on wheat genotypes with high-density Illumina 90K Infinium SNP array. Major yield and drought-related attributes were phenotyped on a panel of Pakistani and foreign accessions grown in non-stressed and water deficient stressed environments during two crop cycles. Among all accessions, highly significant variations were shown in studied environments for examined characters. Water deficient conditions, reduced the wheat yield and had strong and positive correlation among relative water content and grain yield per plant. Population structure analyses based on 90,000 SNP data, classify the accessions into 4 sub-populations. Marker-trait association analyses (MTA) revealed that 134 significant SNPs were linked with yield and drought tolerance attributes. Pleotropic loci RAC875_s117925_244 and RAC875_c16333_340 located on chromosome 5A and 2A respectively, were significantly linked with relative water contents (RWC), cell membrane thermo-stability (CMT), grain per spike (GPS), spikelet per spike (SPS) and grain yield per plant (GYP). The markers Ra_c58279_684, BobWhite_c23828_341 and IAAV3414 located on chromosomes 2A, 6B and 7B respectively, showed pleotropic effects for RWC, GPS and GYP under both environments. The current experiment not only validated several MTAs reported in other studies but also discovered novel MTAs which significant under drought-stressed conditions. A total of 171 candidate genes were recognized that could be cloned and functionally characterized for the respective associated traits. For RWC and CMT, total 11 and 3 associated SNPs were mapped on coding DNA sequence (CDS) of the identified candidate genes. Isolation and characterization of the candidate genes herein mapped SNPs will be useful in discovering novel genes underpinning drought tolerance in bread wheat to fulfill the wheat demand and sustainable food security under limited water conditions. [ABSTRACT FROM AUTHOR]

5-Methylcytosine is one of the major epigenetic marks of DNA in living organisms. Some bacterial species possess DNA methyltransferases that modify cytosines on both strands to produce fully-methylated sites or on either strand to produce hemi-methylated sites. In this study, we characterized a DNA methyltransferase that produces two sequences with different methylation patterns: one methylated on both strands and another on one strand. M.BatI is the orphan DNA methyltransferase of Bacillus anthracis coded in one of the prophages on the chromosome. Analysis of M.BatI modified DNA by bisulfite sequencing revealed that the enzyme methylates the first cytosine in sequences of 5ʹ-GCAGC-3ʹ, 5ʹ-GCTGC-3ʹ, and 5ʹ-GCGGC-3ʹ, but not of 5ʹ-GCCGC-3ʹ. This resulted in the production of fully-methylated 5ʹ-GCWGC-3ʹ and hemi-methylated 5ʹ-GCSGC-3ʹ. M.BatI also showed toxicity when expressed in E. coli, which was caused by a mechanism other than DNA modification activity. Homologs of M.BatI were found in other Bacillus species on different prophage like regions, suggesting the spread of the gene by several different phages. The discovery of the DNA methyltransferase with unique modification target specificity suggested unrevealed diversity of target sequences of bacterial cytosine DNA methyltransferase. [ABSTRACT FROM AUTHOR]

Dinoflagellate species are traditionally defined using morphological characters, but molecular evidence accumulated over the past several decades indicates many morphologically-based descriptions are inaccurate. This recognition led to an increasing reliance on DNA sequence data, particularly rDNA gene segments, in defining species. The validity of this approach assumes the divergence in rDNA or other selected genes parallels speciation events. Another concern is whether single gene rDNA phylogenies by themselves are adequate for delineating species or if multigene phylogenies are required instead. Currently, few studies have directly assessed the relative utility of multigene versus rDNA-based phylogenies for distinguishing species. To address this, the current study examined D1-D3 and ITS/5.8S rDNA gene regions, a multi-gene phylogeny, and morphological characters in Gambierdiscus and other related dinoflagellate genera to determine if they produce congruent phylogenies and identify the same species. Data for the analyses were obtained from previous sequencing efforts and publicly available dinoflagellate transcriptomic libraries as well from the additional nine well-characterized Gambierdiscus species transcriptomic libraries generated in this study. The D1-D3 and ITS/5.8S phylogenies successfully identified the described Gambierdiscus and Alexandrium species. Additionally, the data showed that the D1-D3 and multigene phylogenies were equally capable of identifying the same species. The multigene phylogenies, however, showed different relationships among species and are likely to prove more accurate at determining phylogenetic relationships above the species level. These data indicated that D1-D3 and ITS/5.8S rDNA region phylogenies are generally successful for identifying species of Gambierdiscus, and likely those of other dinoflagellates. To assess how broadly general this finding is likely to be, rDNA molecular phylogenies from over 473 manuscripts representing 232 genera and 863 described species of dinoflagellates were reviewed. Results showed the D1-D3 rDNA and ITS phylogenies in combination are capable of identifying 97% of dinoflagellate species including all the species belonging to the genera Alexandrium, Ostreopsis and Gambierdiscus, although it should be noted that multi-gene phylogenies are preferred for inferring relationships among these species. A protocol is presented for determining when D1-D3, confirmed by ITS/5.8S rDNA sequence data, would take precedence over morphological features when describing new dinoflagellate species. This protocol addresses situations such as: a) when a new species is both morphologically and molecularly distinct from other known species; b) when a new species and closely related species are morphologically indistinguishable, but genetically distinct; and c) how to handle potentially cryptic species and cases where morphotypes are clearly distinct but have the same rDNA sequence. The protocol also addresses other molecular, morphological, and genetic approaches required to resolve species boundaries in the small minority of species where the D1-D3/ITS region phylogenies fail. [ABSTRACT FROM AUTHOR]

We performed a comparative analysis of replication origin activation by genome-wide single-stranded DNA mapping in two yeast strains challenged by hydroxyurea, an inhibitor of the ribonucleotide reductase. We gained understanding of the impact on origin activation by three factors: S-phase checkpoint control, DNA sequence polymorphisms, and relative positioning of origin and transcription unit. Wild type W303 showed a significant reduction of fork progression accompanied by an elevated level of Rad53 phosphorylation as well as physical presence at origins compared to A364a. Moreover, a rad53K227A mutant in W303 activated more origins, accompanied by global reduction of ssDNA across all origins, compared to A364a. Sequence polymorphism in the consensus motifs of origins plays a minor role in determining strain-specific activity. Finally, we identified a new class of origins only active in checkpoint-proficient cells, which we named "Rad53-dependent origins". Our study presents a comprehensive list of differentially used origins and provide new insights into the mechanisms of origin activation. [ABSTRACT FROM AUTHOR]

Bacterial protein secretion is crucial to the maintenance of viability and pathogenicity. Although many bacterial secretion systems have been identified, the underlying mechanisms regulating their expression are less well explored. Yersinia entomophaga MH96, an entomopathogenic bacterium, releases an abundance of proteins including the Yen-Tc into the growth medium when cultured in Luria Bertani broth at ≤ 25°C. Through the development of a high-throughput exoproteome screening assay (HESA), genes involved in MH96 exoprotein production were identified. Of 4,080 screened transposon mutants, 34 mutants exhibited a decreased exoprotein release, and one mutation located in the intergenic region of the Yen-Tc operon displayed an elevated exoprotein release relative to the wild-type strain MH96. DNA sequencing revealed several transposon insertions clustered in gene regions associated with lipopolysaccharide (LPSI and LPSII), and N-acyl-homoserine lactone synthesis (quorum sensing). Twelve transposon insertions were located within transcriptional regulators or intergenic regions. The HESA will have broad applicability for identifying genes associated with exoproteome production in a range of microorganisms. [ABSTRACT FROM AUTHOR]

We present a novel Deep Learning method for the Unsupervised Clustering of DNA Sequences (DeLUCS) that does not require sequence alignment, sequence homology, or (taxonomic) identifiers. DeLUCS uses Frequency Chaos Game Representations (FCGR) of primary DNA sequences, and generates "mimic" sequence FCGRs to self-learn data patterns (genomic signatures) through the optimization of multiple neural networks. A majority voting scheme is then used to determine the final cluster assignment for each sequence. The clusters learned by DeLUCS match true taxonomic groups for large and diverse datasets, with accuracies ranging from 77% to 100%: 2,500 complete vertebrate mitochondrial genomes, at taxonomic levels from sub-phylum to genera; 3,200 randomly selected 400 kbp-long bacterial genome segments, into clusters corresponding to bacterial families; three viral genome and gene datasets, averaging 1,300 sequences each, into clusters corresponding to virus subtypes. DeLUCS significantly outperforms two classic clustering methods (K-means++ and Gaussian Mixture Models) for unlabelled data, by as much as 47%. DeLUCS is highly effective, it is able to cluster datasets of unlabelled primary DNA sequences totalling over 1 billion bp of data, and it bypasses common limitations to classification resulting from the lack of sequence homology, variation in sequence length, and the absence or instability of sequence annotations and taxonomic identifiers. Thus, DeLUCS offers fast and accurate DNA sequence clustering for previously intractable datasets. [ABSTRACT FROM AUTHOR]