Optimizing Multiplex PCR for a Set of Malay Ancestry Informative Marker-Single Nucleotide Polymorphisms (AIM-SNPs) and Preliminary Analysis of Genotypes Between Malay and non-Malay Population.

Background: Inference of genetic ancestry is of great interest in many fields and one of the markers in these analyses is ancestry informative marker single nucleotide polymorphisms (AIMSNPs). The Malay population is an ethnic group located mainly in South East Asia and comprises the largest ethnicity in Malaysia. Objectives: To determine Malay ancestry, Yahya et al, 2017 selected 37,487 SNPs from the genotyping data collected by the Malaysian Node of the Human Variome Project and Singapore Genome Variation Project and referenced them against the data from the International HapMap Project Phase 3. The SNPs determined to be informative for ancestry were compiled into AIM-SNP panels, and from these a few SNPs were selected for optimization in preparation for single base extension reaction multiplexing. Methodology: The chosen AIMSNPs were optimized and validated on Malay and non-Malay populations. Genotyping was carried out on participants of self-reported Malay and non-Malay ancestry respectively and the data were compared for Malay and non-Malay population to investigate for significant differences in the genotype between Malay and non-Malay participants. Findings: The results showed great similarities between the Malay and non-Malay population, which may arise from many factors, and further optimization of more SNPs and genotyping is required to definitively conclude the validity of the AIM-SNP panels for Malay population Conclusion: Knowledge of ancestry is important to minimise spurious association. This pilot study gives a brief account of the optimization process and offers an insight into how this may be done in South East Asian populations.

Multilocus Genotyping of ‘Candidatus Phytoplasma solani’ Associated with Rubbery Taproot Disease of Sugar Beet in the Pannonian Plain

Rubbery taproot disease of sugar beet (RTD), associated with ‘Candidatus Phytoplasma solani’, appeared in 2020 on an epidemic scale in northern Serbia and southern Slovakia, situated at opposite edges of the Pannonian Plain. In the affected locations where the disease was assessed, symptomatic sugar beets were analysed for phytoplasma infection. Additionally, multilocus sequence analyses of ‘Ca. P. solani’ strains on epidemiologically informative marker genes (tuf, stamp and vmp1) were performed. Symptomatic sugar beets from other countries of the Pannonian Plain (Croatia, Hungary and Austria), one sample from Germany, and red beets from Serbia were included in the analyses. ‘Ca. P. solani’ was detected in sugar beet in all assessed countries, as well as in red beet. Molecular analyses revealed the high genetic variability of ‘Ca. P. solani’ with the presence of all four tuf-types (a, b1, b2 and d), 14 stamp genotypes (seven new) and five vmp1 profiles (one new). The most common multilocus genotype in Serbia, Slovakia, Croatia, and Hungary was dSTOLg (tuf-d/STOL/V2-TA). It was dominant on sites with epidemic RTD outbreaks in the Pannonian Plain and in several sugar beet fields with non-epidemic RTD occurrence suggesting the prevalence of a particular epidemiological pathway during the epidemic’s phases.

ensembleTax: an R package for determinations of ensemble taxonomic assignments of phylogenetically-informative marker gene sequences

Background High-throughput sequencing of phylogenetically informative marker genes is a widely used method to assess the diversity and composition of microbial communities. Taxonomic assignment of sampled marker gene sequences (referred to as amplicon sequence variants, or ASVs) imparts ecological significance to these genetic data. To assign taxonomy to an ASV, a taxonomic assignment algorithm compares the ASV to a collection of reference sequences (a reference database) with known taxonomic affiliations. However, many taxonomic assignment algorithms and reference databases are available, and the optimal algorithm and database for a particular scientific question is often unclear. Here, we present the ensembleTax R package, which provides an efficient framework for integrating taxonomic assignments predicted with any number of taxonomic assignment algorithms and reference databases to determine ensemble taxonomic assignments for ASVs. Methods The ensembleTax R package relies on two core algorithms: taxmapper and assign.ensembleTax. The taxmapper algorithm maps taxonomic assignments derived from one reference database onto the taxonomic nomenclature (a set of taxonomic naming and ranking conventions) of another reference database. The assign.ensembleTax algorithm computes ensemble taxonomic assignments for each ASV in a data set based on any number of taxonomic assignments determined with independent methods. Various parameters allow analysts to prioritize obtaining either more ASVs with more predicted clade names or more robust clade name predictions supported by multiple independent methods in ensemble taxonomic assignments. Results The ensembleTax R package is used to compute two sets of ensemble taxonomic assignments for a collection of protistan ASVs sampled from the coastal ocean. Comparisons of taxonomic assignments predicted by individual methods with those predicted by ensemble methods show that conservative implementations of the ensembleTax package minimize disagreements between taxonomic assignments predicted by individual and ensemble methods, but result in ASVs with fewer ranks assigned taxonomy. Less conservative implementations of the ensembleTax package result in an increased fraction of ASVs classified at all taxonomic ranks, but increase the number of ASVs for which ensemble assignments disagree with those predicted by individual methods. Discussion We discuss how implementation of the ensembleTax R package may be optimized to address specific scientific objectives based on the results of the application of the ensembleTax package to marine protist communities. While further work is required to evaluate the accuracy of ensemble taxonomic assignments relative to taxonomic assignments predicted by individual methods, we also discuss scenarios where ensemble methods are expected to improve the accuracy of taxonomy prediction for ASVs.

Strategies for sample labelling and library preparation in DNA metabarcoding studies

Metabarcoding of DNA extracted from environmental or bulk specimen samples is increasingly used to detect plant and animal taxa in basic and applied biodiversity research because of its targeted nature that allows sequencing of genetic markers from many samples in parallel. To achieve this, PCR amplification is carried out with primers designed to target a taxonomically informative marker within a taxonomic group, and sample-specific nucleotide identifiers are added to the amplicons prior to sequencing. This enables assignment of the sequences back to the samples they originated from. Nucleotide identifiers can be added during the metabarcoding PCR and/or during ‘library preparation’, i.e. when amplicons are prepared for sequencing. Different strategies to achieve this labelling exist. All have advantages, challenges and limitations, some of which can lead to misleading results, and in the worst case compromise the fidelity of the metabarcoding data. Given the range of questions addressed using metabarcoding, the importance of ensuring that data generation is robust and fit for purpose should be at the forefront of practitioners seeking to employ metabarcoding for biodiversity assessments. Here, we present an overview of the three main workflows for sample-specific labelling and library preparation in metabarcoding studies on Illumina sequencing platforms. Further, we distil the key considerations for researchers seeking to select an appropriate metabarcoding strategy for their specific study. Ultimately, by gaining insights into the consequences of different metabarcoding workflows, we hope to further consolidate the power of metabarcoding as a tool to assess biodiversity across a range of applications.

KERAGAMAN GENETIK 64 AKSESI KUNYIT ASAL INDONESIA BERDASARKAN MARKA P450-BASED ANALOGUE (PBA)

<em>Turmeric is a rhizome producing plant with many utilization such as for consumption, medicine, and colorant industries. The development of superior turmeric varieties in Indonesia needs to be supported by genetic diversity information availability. Despite its potential, genetic diversity information of Indonesian turmeric has not been widely observed. A molecular marker is used to address genetic diversity information with the accurate result due to minimum environmental influences. PBA can detect the P450 gene as a functional marker, which is related to the synthesis of secondary metabolites in a wide genome area. Thus, it can be used as an alternative marker to identify genetic diversity. This research aimed to obtain genetic diversity information of 64 turmeric accessions using eight primer sets of P450-Based Analogue (PBA). The study was conducted in the Central Laboratory of Padjadjaran University from June 2019 to January 2020. Results showed that the full 133 bands were detected with a range of allele number 8 - 45 bands and an average of 22.3 bands per allele. PIC analysis showed six primer sets of PBA had high polymorphisms ranged from 0.90 to 0.98, hence categorized </em><em>PBA as a highly informative marker. Cluster analysis divided 64 turmeric accessions into two main clusters based on a similarity index ranged from 0.01 to 0.83. The accession of CL-GTL01 origins from Gorontalo had a low similarity coefficient of 0.01 to the other 64 accessions cluster. On the other hand, CL-NTB01 dan CL-PPB01 had the highest similarity index of 0.83. Based on the PIC value, the total number of polymorphic bands, and genetic distance, it can be concluded that local Indonesian turmeric had wide diversity based on PBA marker.</em>

Enlarged perivascular spaces are not associated with vascular co-morbidities, clinical outcomes, and brain volumes in people with secondary progressive multiple sclerosis

Background In secondary progressive multiple sclerosis (SPMS) significance of enlarged perivascular spaces (ePVS) is unknown. Objectives, Methods: Analysis of associations between vascular co-morbidities, clinical outcomes, and volumetrics with categorical ePVS scores in midbrain, basal ganglia (BG), and centrum semiovale (CSO) in SPMS(n-46). Results, Conclusion: In BG, advancing age (Z = 2.68) and lower Expanded Disability Status Scale (Z = −2.04) were associated with increasing ePVS score. In CSO, advancing age (Z = 2.66) and male gender (Z = 2.45) were associated with increasing ePVS score. No associations between ePVS score and vascular co-morbidities or volumetrics existed; ePVS may not be an informative marker for SPMS.

Identification of Ancestry Informative Marker (AIM) Panels to Assess Hybridisation between Feral and Domestic Sheep

Hybridisation of wild populations with their domestic counterparts can lead to the loss of wildtype genetic integrity, outbreeding depression, and loss of adaptive features. The Mediterranean island of Sardinia hosts one of the last extant autochthonous European mouflon (Ovis aries musimon) populations. Although conservation policies, including reintroduction plans, have been enforced to preserve Sardinian mouflon, crossbreeding with domestic sheep has been documented. We identified panels of single nucleotide polymorphisms (SNPs) that could act as ancestry informative markers able to assess admixture in feral x domestic sheep hybrids. The medium-density SNP array genotyping data of Sardinian mouflon and domestic sheep (O. aries aries) showing pure ancestry were used as references. We applied a two-step selection algorithm to this data consisting of preselection via Principal Component Analysis followed by a supervised machine learning classification method based on random forest to develop SNP panels of various sizes. We generated ancestry informative marker (AIM) panels and tested their ability to assess admixture in mouflon x domestic sheep hybrids both in simulated and real populations of known ancestry proportions. All the AIM panels recorded high correlations with the ancestry proportion computed using the full medium-density SNP array. The AIM panels proposed here may be used by conservation practitioners as diagnostic tools to exclude hybrids from reintroduction plans and improve conservation strategies for mouflon populations.

Differential diagnosis of pancreatic diseases: new approaches in laboratory and radiologic diagnosis

Aim. To assess significance of serum fibronectin (FN) and new approaches of processing computed tomography (CT) results for pancreatic cancer (PC) and chronic pancreatitis (CP) differential diagnosis. Materials and methods. Data of 49 patients with pancreatic lesions who underwent multislice computed tomography (MSCT) with intravenous contrast enhancement and FN evaluation in 2018 were analyzed. There were 29 (59.2%) males and 20 (40.8%) females, mean age 51.9±13.9 (30–82). All patients were divided in 3 groups: 1 — PC (17 patients, 34.6%) — morphologically verified, 2 — chronic pancreatitis with previous pancreonecrosis (CPPN) — 16 patients, 32.7%, 3 — chronic calcifying pancreatitis (CCP) — 16 patients, 32.7%. We calculated median of enhancement gradient between region of interest and intact parenchyma (Мgrad) based on MSCT results. Pearson’s correlation coefficient (rp) was calculated for correlation assessment. Results. We assessed mean Мgrad and mean serum FN rate in all three groups: PC — 28.1±2.6, р=0.0001, CPPN — 14.9±2.4, р=0.07, CCP — 13.3±0.7, р=0.08 for Мgrad, and 239.8±30.1, p=0.8, 243.5±33.8, p=0.7, 227.2±34.3, p=0.8 for serum FN rate, respectively. There was statistically significant strong correlation of Мgrad in patients with PC (rp=0.63, p=0.0001). We revealed cut-off point of Мgrad value for PC that was 20 (p=0.001). There were no statistically significant correlations of serum FN rate in all groups (PC rp=0.04, p=0.8; CPPN rp=0.06, p=0.7; CCP rp=-0.03, p=0.8). Conclusions. Mgrad evaluation based on MSCT is an informative marker for differential diagnosis between PC and chronic pancreatitis, high rates of Мgrad positively correlate with PC existence. There was no correlation between serum FN rate and existence of PC, CPPN or CCP.