Evaluation of Cultivated and Wild Brinjal Germplasm against Bacterial Wilt Disease with Tollinterleukin-1 Receptors (TIR)-NBS-LRR Type R-gene Specific Degenerate Primer

The experiment was conducted at C-Block Farm of Bidhan Chandra Krishi Viswavidyalaya, Kalyani, West Bengal, India during 2017–18 to screen eight brinjal germplasm lines against BW disease using tollinterleukin-1 receptors (TIR)-NBS-LRR type R-gene specific degenerate primer. The study showed that wild genotype S. torvum was highly resistant to bacterial wilt incidence with no wilting symptom whereas two cultivated genotypes (Utkal Anushree and Utkal Madhuri) and one wild genotype S. sisymbriifolium were found to be resistant to BW disease. Out of the 7 germplasm sequences, 2 had no match with R-genes whereas the remaining 5 sequences have 70-93% homology with R-genes of other plant species submitted in Gene Bank sequence database. Nearly 90% sequence identity of brinjal NBS-LRR RGA was found by analyzing through BLASTn with NBS-LRR RGAs of other solanaceous crops. Two cultivated resistant genotypes (Utkal Madhuri and Utkal Tarini) were similar to the wild resistant type S. sisymbriifloium, while cultivable resistant genotype Utkal Anushree was highly different at sequence level. Two cultivable susceptible genotypes (BCB-30 and Garia) showed high level of similarity among them and they were strongly associated with the wild susceptible genotype S. macrocarpum. Two cultivable genotypes Utkal Anushree and Utkal Madhuri could be utilized in future breeding programme and two wild genotypes S. torvum and S. sisymbriifolium could be used as resistant rootstocks in brinjal grafting.

FUSARIUM-ID v.3.0: An updated, downloadable resource for Fusarium species identification

Species within Fusarium are of global agricultural, medical, and food/feed safety concern and have been extensively characterized. However, accurate identification of species is challenging and usually requires DNA sequence data. FUSARIUM-ID (http://isolate.fusariumdb.org/) is a publicly available database designed to support the identification of Fusarium species using sequences of multiple phylogenetically informative loci, especially the highly informative ~680 bp 5' portion of the translation elongation factor 1-alpha (TEF1) gene that has been adopted as the primary barcoding locus in the genus. However, FUSARIUM-ID v.1.0 and 2.0 had several limitations, including inconsistent metadata annotation for the archived sequences and poor representation of some species complexes and marker loci. Here, we present FUSARIUM-ID v.3.0, which provides the following improvements: (i) additional and updated annotation of metadata for isolates associated with each sequence, (ii) expanded taxon representation in the TEF1 sequence database, (iii) availability of the sequence database as a downloadable file to enable local BLAST queries, and (iv) a tutorial file for users to perform local BLAST searches using either freely-available software, such as SequenceServer, BLAST+ executable in the command line, and Galaxy, or the proprietary Geneious software. FUSARIUM-ID will be updated on a regular basis by archiving sequences of TEF1 and other loci from newly identified species and greater in-depth sampling of currently recognized species.

Decoding the link of microbiome niches with homologous sequences enables accurately targeted protein structure prediction

Information derived from metagenome sequences through deep-learning techniques has significantly improved the accuracy of template free protein structure modeling. However, most of the deep learning–based modeling studies are based on blind sequence database searches and suffer from low efficiency in computational resource utilization and model construction, especially when the sequence library becomes prohibitively large. We proposed a MetaSource model built on 4.25 billion microbiome sequences from four major biomes (Gut, Lake, Soil, and Fermentor) to decode the inherent linkage of microbial niches with protein homologous families. Large-scale protein family folding experiments on 8,700 unknown Pfam families showed that a microbiome targeted approach with multiple sequence alignment constructed from individual MetaSource biomes requires more than threefold less computer memory and CPU (central processing unit) time but generates contact-map and three-dimensional structure models with a significantly higher accuracy, compared with that using combined metagenome datasets. These results demonstrate an avenue to bridge the gap between the rapidly increasing metagenome databases and the limited computing resources for efficient genome-wide database mining, which provides a useful bluebook to guide future microbiome sequence database and modeling development for high-accuracy protein structure and function prediction.

Best BLAST hit alone cannot be used as evidence of fraud

In a recent study, Blanco-Fernandez et al. applied molecular tools to authenticate fish products and conclude evidence of 'worrying international fraud'. They revealed mislabeling in recognizable and unrecognizable fish products labeled as anchovy, hake and tuna commercialized by European companies. Their analyses consisted on extracting DNA from the fish product to be authenticated followed by amplification and sequencing of a suite of DNA markers and on comparing the resulting sequences to the GenBank sequence database using BLAST (Basic Tool Alignment Search Tool) (https://blast.ncbi.nlm.nih.gov/Blast.cgi). By carefully reanalyzing their data, we identify errors in their species identification and conclude that best BLAST hit alone cannot be used as evidence of fraud.

Cattle Maternal Diversity Inferred From 1,883 Taurine And Indicine Mitogenomes

Maternal diversity based on a sub-region of mitochondrial genome or variants were commonly used to understand past demographic events in livestock. Additionally, there is growing evidence of direct association of mitochondrial genetic variants with a range of phenotypes. Therefore, this study used bovine complete mitogenomes from a large sequence database to explore the full spectrum of maternal diversity. Mitogenome diversity was evaluated among 1883 animals representing 156 globally important cattle breeds. Overall, the mitogenomes were diverse: presenting 11 major haplogroups, expanding to 1309 unique haplotypes, with nucleotide diversity 0.011 and haplotype diversity 0.99. A small proportion of African taurine (3.5%) and indicine (1.3%) haplogroups were found among the European taurine breeds and composites. The haplogrouping was largely consistent with the population structure derived from alternate clustering methods (e.g. PCA and hierarchical clustering). Further, we present evidence confirming a new indicine subgroup (I1a, 64 animals) mainly consisting of breeds originating from China and characterised by two private mutations within the I1 haplogroup. The total genetic variation was attributed mainly to within-breed variance (96.9%). The accuracy of the imputation of missing genotypes was high (99.8%) except for the relatively rare heteroplasmic genotypes, suggesting the potential for trait association studies within a breed.

Distribution of Hepatitis B Genotypes Among Hepatitis B Patients Visiting Decode Genomics Research Center

The hepatitis B virus (HBV) is non-cytopathic, hepatotropic and enveloped virus which causes Hepatitis B and infects the liver causing inflammation and hepatocellular necrosis. The genome sequence database shows that HBV has ten genetic diversities (A-J) ten in which the HBV genotypes, I and J are the new one. Three major genotypes of HBV (A, C and D) were found in Nepal. Despite being a low prevalence, Nepal has a diversity of hepatitis B. Hence, the study aims to determine the distribution of hepatitis B genotypes among the hepatitis B patients visiting Decode Genomics Research Center. HBV genotypes were determined by using a simpler, more rapid, and more specific genotyping system for HBV involving PCR using type-specific primers. Our study showed that different HBV genotypes were identified in which genotype D to be predominant one followed by C and also showed presence of genotype A, B and F. Many recombinant genotypes were also present in our study.

Effect of Red Orange and Lemon Extract-Enriched Diet in Suckling Lambs’ Fecal Microbiota

Red orange and lemon extract (RLE) is an anthocyanins-rich dietary supplement that may influence gastrointestinal bacterial community in ruminants. The aim of the present study was to investigate the RLE effects on gut microbiota composition in lambs. Twenty-eight lambs were randomly divided into a control group (CON; n = 14) and an anthocyanin group (ANT; n = 14) and fed the same diet; additionally, only the ANT received 90 mg/kg live weight of RLE at day. After lamb slaughter (40 ± 1 days), fecal samples were collected from the rectum and stored at −20 °C until analysis. Analysis of fecal microbiome was carried out by metabarcoding analysis of 16S rRNA. After reads denoising, sequences were aligned against SILVA rRNA sequence database using MALT, and taxonomic binning was performed with MEGAN. A significant increase in Firmicutes and Bacteroidetes and a decrease in Proteobacteria and Actinobacteria was observed in ANT compared to CON. Moreover, an interesting increase of Lactobacillus and Bifidobacterium genera and a decrease in Escherichia coli and Salmonella species were detected in ANT compared to CON. Results recommend that anthocyanin supplementation in lamb diet is able to modulate positively gut microbiota and may inhibit the growth of some potential pathogenic microorganisms.

Investigating the PageRank and sequence prediction based approaches for next page prediction

Discovering unseen patterns from web clickstream is an upcoming research area. One of the meaningful approaches for making predictions is using sequence prediction that is typically the improved compact prediction tree (CPT+). However, to increase this method's effectiveness, combining it with at least other methods is necessary. This work investigates such PageRank-based methods related to sequence prediction as All-K-Markov, DG, Markov 1st, CPT, CPT+. The experimental results proved that the integration of CPT+ and PageRank is the right solution for next page prediction in terms of accuracy, which is more than a standard method of approximately 0.0621%. Still, the size of the newly created sequence database is reduced up to 35%. Furthermore, our proposed solution has an accuracy that is much higher than other ones. It is intriguing for the next phase (testing one) to make the next page prediction in terms of time performance.

Sensitive and specific spectral library searching with COSS and Percolator

Maintaining high sensitivity while limiting false positives is a key challenge in peptide identification from mass spectrometry data. Here, we therefore investigate the effects of integrating the machine learning-based post-processor Percolator into our spectral library searching tool COSS. To evaluate the effects of this post-processing, we have used twenty data sets from two different projects and have matched these against the NIST spectral library. The matching is carried out using two performant spectral library search engines (COSS and MsPepSearch), both with and without Percolator post-processing, and using sequence database search engine MS-GF+ as a baseline comparator. The addition of the Percolator rescoring step was particularly effective for COSS, resulting in a substantial improvement in sensitivity and specificity of the identifications. Importantly, the false discovery rate was especially strongly affected, resulting in much more reliable results. COSS is freely available as open source under the permissive Apache2 license, and binaries and source code are found at https://github.com/compomics/COSS .