The hTERT -VNTR2-2 nd alleles are involved in genomic stability in gastrointestinal cancer Abstract Background hTERT contains a high density of minisatellites, of which rare alleles of hTERT-VNTR2-2nd have been reported to be associated with prostate cancer. This shows an association between VNTR and cancer, but this repeat sequence is likely to be associated with genomic instability. Therefore, we investigated the effects of hTERT-VNTR2-2nd on gastrointestinal cancer and the relationship between repeated sequence and chromosome instability. Methods A case–control study was performed using DNA from 818 cancer-free controls, 539 cases with gastric cancer, 275 cases with colon cancer and 274 cases with rectal cancer. To determine whether minisatellites affect gene expression, expression levels were examined using TERT-reporter vectors in cell lines. In addition, the length of the hTERT-VNTR2-2nd alleles were determined in blood and cancer tissues from 107 gastric cancers, 112 colon cancers and 76 rectal cancers patients to determine whether the repeat sequence was associated with genomic instability during cancer development. Results No statistically significant association between hTERT-VNTR2-2nd and risk of gastrointestinal cancer was detected. However, it has been shown that VNTRs inserted into the enhancer region can regulate the expression of TERT in gastrointestinal cancer cells. Moreover, hTERT-VNTR2-2nd was analyzed in matched blood and cancer tissue from patients with gastrointestinal cancer and in seven among 294 subjects, and hTERT-VNTR2-2nd was found to be rearranged. Conclusions We suggest that minisatellites are associated with genomic instability in cancer and that the hTERT-VNTRs region may increase hTERT expression in gastrointestinal cancer cells.

Correction to: Hair follicles transcriptome profiles in Bashang long-tailed chickens with different plumage colors The words ‘hair follicles’ was replaced with ‘feather follicles’ in the title and the main text.

Improving classification accuracy of cancer types using parallel hybrid feature selection on microarray gene expression data Abstract Background Data mining techniques are used to mine unknown knowledge from huge data. Microarray gene expression (MGE) data plays a major role in predicting type of cancer. But as MGE data is huge in volume, applying traditional data mining approaches is time consuming. Hence parallel programming frameworks like Hadoop, Spark and Mahout are necessary to ease the task of computation. Objective Not all the gene expressions are necessary in prediction, it is very essential to select important genes for improving classification accuracy. So feature selection algorithms are parallelized and executed on Spark framework to eliminate unnecessary genes and identify only predictive genes in very less time without affecting prediction accuracy. Methods Parallelized hybrid feature selection (HFS) method is proposed to serve the purpose. This method includes parallelized correlation feature subset selection followed by rank-based feature selection methods. The selected subset of genes is evaluated using parallel classification algorithms. The accuracy values obtained are compared with existing rank-weight feature selection, parallelized recursive feature selection methods and also with the values obtained by executing parallelized HFS on DistributedWekaSpark. Results The classification accuracy obtained with the proposed parallelized HFS method is 97% and 79% for gastric cancer and childhood leukemia respectively. The proposed parallelized HFS method produced ~ 4% to ~ 15% improvement in classification accuracy when compared with previous methods. Conclusion The results reveal the fact that the proposed parallelized feature selection algorithm is scalable to growing medical data and predicts cancer sub-types in lesser time with higher accuracy.

Validation of MADS-box genes from apple fruit pedicels during early fruit abscission by transcriptome analysis and real-time PCR Abstract Background Fruit abscission in an isolated region called abscission zone (AZ) is regulated by several genes including JOINTLESS, MACROCALYX and SEPALLATA, MADS-box genes, in tomato. Objective The surviving central pedicels and the abscised lateral pedicels were examined in fruit clusters in order to investigate apple MADS-box genes from fruit pedicels of self-abscising apple ‘Saika’ during early fruit abscission. Methods After performing RNA-Seq, transcription profiling was conducted on the MADS-box genes from apple central and lateral pedicels. The JOINTLESS homolog of apple (MdJOINTLESS) was amplified using degenerate primers annealing to a highly conserved domain based on the orthologous genes of various crops, including JOINTLESS gene of tomato. The expression pattern of MdJOINTLESS was investigated in central and lateral pedicles by real-time PCR. Results Some homologs were found which similar to JOINTLESS, MACROCALYX and SEPALLATA of tomato MADS-box genes from transcriptome analysis and RACE. Using phylogenetic analyses with the MADS-box gene family, MdJOINTLESS was classified into the SHORT VEGETATIVE PHASE (SVP) clade that included Arabidopsis and other crops. The expression level of MdJOINTLESS in central pedicel was more than twice as high as that of lateral pedicel. Conclusion In the current study, we could find apple homologs of JOINTLESS, MACROCALYX, SEPALLATA, which were known to regulate pedicel AZ development in tomato. Furthermore, MdJOINTLESS might contribute to auxin gradation, influencing hierarchical ranking of auxin transport between fruit pedicels of self-abscising apple.

Proteome-wide subtractive approach to prioritize a hypothetical protein of XDR- Mycobacterium tuberculosis as potential drug target Abstract Background Among the resistant isolates of MTB, multidrug resistant tuberculosis (MDR-TB) and extensively drug resistant tuberculosis (XDR-TB) have been the areas of growing concern. The genomic analysis showed that the respective genomic pool of the XDR-MTB proteome contains more than 30% of the hypothetical proteins for which no functions have been annotated yet. This class of proteins presumably have their own importance to complete genome and proteome information. The bioinformatics advancements have helped to annotate those hypothetical proteins by using various computational tools and have potential to classify them functionally. Objective The objective of this study was to propose a new and unique drug target against the deadly Mycobacterium tuberculosis using Bioinformatics approaches to characterize the hypothetical proteins. Results We stepwise reduced the hypothetical proteins (total number: 1256) out of the complete proteome to only 26 essential hypothetical proteins. Out of those 26 proteins, the protein WP_003401246.1 was computationally characterized as the druggable target. Conclusion The study proposed a hypothetical protein from complete proteome of the XDR-MTB as a new drug target against which new drug candidates can be proposed. Hence, the study opens up the new avenues in the areas of drug discovery against deadly M. tuberculosis.

Hair follicles transcriptome profiles in Bashang long-tailed chickens with different plumage colors Abstract Despite the rich variety in plumage color found in nature, genetic studies on how hair follicles affect pigmentation are often limited to animals that have black and white pigment. To test how gene expression influences plumage color, transcriptomes of chicken hair follicles with white, black, hemp, reed catkins, silvery grey, and landscape plumage colors were generated using Illumina sequencing. We generated six RNA-Seq libraries with over 25 million paired-end clean reads per library with percentage of paired-end clean reads ranging from 96.73 to 96.98%. 78% of the reads mapped to the chicken genome, and approximately 70% of the reads were mapped to exons and 6% mapped to introns. Transcriptomes of hair follicles producing hemp and land plumage were similar, but these two showed moderate differences compared with gray and reed colored plumage. The black and white follicle transcriptomes were most divergent from the other colors. We identified several candidate genes, including GPNMB, PMEL, TYRP1, GPR143, OCA2, SOX10, SLC45A2, KRT75, and TYR. All of these genes are known to induce pigment formation in mice. White feathers result from the lack of pigment formation, and our results suggest that the white chickens due to the recessive insertion mutation of TYR. The formation of black area size and color depth may be due to the expression levels of GPNMB, PMEL, TYRP1, GPR143, OCA2, SOX10, SLC45A2, KRT75, and TYR. The GO analysis of the differentially expressed genes (DEGs) revealed that DEGs in our transcriptome analysis were enriched in cytoskeleton and cell structure related pathways. The black plumage transcriptome showed significant differences in melanogenesis, tyrosine metabolism, and riboflavin metabolism compared with transcriptomes of other plumage colors. The transcriptome profiles of the different chicken plumage colors provide a valuable resource to understand how gene expression influences plumage color, and will be an important resource for identifying candidate genes in breeding programs.

Cytological, genetic, and proteomic analysis of a sesame ( Sesamum indicum L.) mutant Siyl - 1 with yellow–green leaf color Abstract Background Both photosynthetic pigments and chloroplasts in plant leaf cells play an important role in deciding on the photosynthetic capacity and efficiency in plants. Systematical investigating the regulatory mechanism of chloroplast development and chlorophyll (Chl) content variation is necessary for clarifying the photosynthesis mechanism for crops. Objective This study aims to explore the critical regulatory mechanism of leaf color mutation in a yellow–green leaf sesame mutant Siyl-1. Methods We performed the genetic analysis of the yellow-green leaf color mutation using the F2 population of the mutant Siyl-1. We compared the morphological structure of the chloroplasts, chlorophyll content of the three genotypes of the mutant F2 progeny. We performed the two-dimensional gel electrophoresis (2-DE) and compared the protein expression variation between the mutant progeny and the wild type. Results Genetic analysis indicated that there were 3 phenotypes of the F2 population of the mutant Siyl-1, i.e., YY type with light-yellow leaf color (lethal); Yy type with yellow-green leaf color, and yy type with normal green leaf color. The yellow-green mutation was controlled by an incompletely dominant nuclear gene, Siyl-1. Compared with the wild genotype, the chloroplast number and the morphological structure in YY and Yy mutant lines varied evidently. The chlorophyll content also significantly decreased (P < 0.05). The 2-DE comparison showed that there were 98 differentially expressed proteins (DEPs) among YY, Yy, and yy lines. All the 98 DEPs were classified into 5 functional groups. Of which 82.7% DEPs proteins belonged to the photosynthesis and energy metabolism group. Conclusion The results revealed the genetic character of yellow-green leaf color mutant Siyl-1. 98 DEPs were found in YY and Yy mutant compared with the wild genotype. The regulation pathway related with the yellow leaf trait mutation in sesame was analyzed for the first time. The findings supplied the basic theoretical and gene basis for leaf color and chloroplast development mechanism in sesame.

Comparative genomic and functional analysis of Akkermansia muciniphila and closely related species Abstract Background Akkermansia muciniphila is an important bacterium that resides on the mucus layer of the intestinal tract. Akkermansia muciniphila has a high abundance in human feces and plays an important role in human health. Objective In this article, 23 whole genome sequences of the Akkermansia genus were comparatively studied. Methods Phylogenetic trees were constructed with three methods: All amino acid sequences of each strain were used to construct the first phylogenetic tree using the web server of Composition Vector Tree Version 3. The matrix of Genome-to-Genome Distances which were obtained from GGDC 2.0 was used to construct the second phylogenetic tree using FastME. The concatenated single-copy core gene-based phylogenetic tree was generated through MEGA. The single-copy genes were obtained using OrthoMCL. Population structure was assessed by STRUCTURE 2.3.4 using the SNPs in core genes. PROKKA and Roary were used to do pan-genome analyses. The biosynthetic gene clusters were predicted using antiSMASH 4.0. IalandViewer 4 was used to detect the genomic islands. Results The results of comparative genomic analysis revealed that: (1) The 23 Akkermansia strains formed 4 clades in phylogenetic trees. The A. muciniphila strains isolated from different geographic regions and ecological niches, formed a closely related clade. (2) The 23 Akkermansia strains were divided into 4 species based on digital DNA-DNA hybridization (dDDH) values. (3) Pan-genome of A. muciniphila is in an open state and increases with addition of new sequenced genomes. (4) SNPs were not evenly distributed throughout the A. muciniphila genomes. The genes in regions with high SNP density are related to metabolism and cell wall/membrane envelope biogenesis. (5) The thermostable outer-membrane protein, Amuc_1100, was conserved in the Akkermansia genus, except for Akkermansia glycaniphila PytT. Conclusion Overall, applying comparative genomic and pan-genomic analyses, we classified and illuminated the phylogenetic relationship of the 23 Akkermansia strains. Insights of the evolutionary, population structure, gene clusters and genome islands of Akkermansia provided more information about the possible physiological and probiotic mechanisms of the Akkermansia strains, and gave some instructions for the in-depth researches about the use of Akkermansia as a gut probiotic in the future.

Genome-wide characterization of the NUCLEAR FACTOR - Y ( NF - Y ) family in Citrus grandis identified CgNF - YB9 involved in the fructose and glucose accumulation Abstract Background Nuclear factor Y (NF-Y) is increasingly known to be involved in many aspects of plant growth and development. To date, the systematic characterization of NF-Y family has never been reported in Citrus grandis. Objective Genome-wide characterization of C. grandis NF-Y (CgNF-Y) family and analysis of their role in sucrose metabolism. Methods NF-Y conserved models were employed to identify CgNF-Y genes from genomic data. Phylogenetic tree was generated by the neighbor-joining method using program MEGA 7.0. Based on our previous transcriptomic data, the transcription levels were calculated by RSEM software and were clustered by ShortTime-series Expression Miner. The plant expression vector of CgNF-YB9 was constructed using In-Fusion Cloning and transferred into tobacco by leaf disc transformation method. Soluble sugars and gene expressions were analysis by HPLC and qRT-PCR, respectively. Results A total of 24 CgNF-Y genes (6 CgNF-YAs, 13 CgNF-YBs and 5 CgNF-YCs) were identified with conserved domains. Phylogenetic analysis of the NF-Y proteins indicated that NF-YA, NF-YB and NF-YC could be categorized into four, five and three clades, respectively. Expression profiling analysis reflected spatio-temporally distinct expression patterns for CgNF-Y genes. Importantly, we observed a positive correlation between the expression level of CgNF-YB9 and the content of soluble sugar. Moreover, CgNF-YB9-corelated genes were enriched in carbohydrate metabolism. In CgNF-YB9 overexpression lines, sucrose content showed a decrease, whereas glucose and fructose contents displayed an increase. As expected, the transcription levels of sucrose-phosphate synthase and vacuolar invertase in transgenic Line 3 were observed with significantly down- and up-regulated, respectively. Conclusions The structure, phylogenetic relationship and expression pattern of 24 CgNF-Y genes were identified, and CgNF-YB9 was involved in sucrose metabolism.

Comparative transcriptome analysis reveals higher expression of stress and defense responsive genes in dwarf soybeans obtained from the crossing of G. max and G. soja Abstract Background Plant height is an important component of plant architecture and significantly affects crop breeding practices and yield. Dwarfism in plants prevents lodging and therefore it’s a desired trait in crops. Objective To find differentially expressed genes to classify and understand the regulation of genes related to plant growth in mutant dwarf soybeans, which appeared in the F5 generation. Methods We obtained a few segregated dwarf soybeans in the populations derived from the crossing of Glycine max var. Peking and Glycine soja var. IT182936 in an F5 RIL population. These dwarf soybeans may be useful genetic resources for plant breeders, geneticists and biologists. Using the Illumina high-throughput platform, transcriptomes were generated and compared among normal and dwarf soybeans in triplicate. Conclusion We found complex relationship of the expressed genes to plant growth. There were highly significantly up-/downregulated genes according to the comparison of gene expression in normal and dwarf soybeans. The genes related to disease and stress responses were found to be upregulated in dwarf soybeans. Such over-expression of disease resistance and other immune response genes can be targeted to understand how the immune genes regulate the response of plant growth. In addition, photosynthesis-related genes showed very low expression in dwarf lines. The transcriptome expression and genes classified as related to plant growth may be useful resources to researchers studying plant growth.