Revisiting traditional SSR based methodologies available for elephant genetic studies.
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ABSTRACT:
SUBMITTER: Marasinghe MSLRP
PROVIDER: S-EPMC8062488 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:UnlabelledSimple Sequence Repeats (SSRs) are used to address a variety of research questions in a variety of fields (e.g. population genetics, phylogenetics, forensics, etc.), due to their high mutability within and between species. Here, we present an innovative algorithm, SA-SSR, based on suffix and longest common prefix arrays for efficiently detecting SSRs in large sets of sequences. Existing SSR detection applications are hampered by one or more limitations (i.e. speed, accuracy, ease-of-use, etc.). Our algorithm addresses these challenges while being the most comprehensive and correct SSR detection software available. SA-SSR is 100% accurate and detected >1000 more SSRs than the second best algorithm, while offering greater control to the user than any existing software.Availability and implementationSA-SSR is freely available at http://github.com/ridgelab/SA-SSR CONTACT: perry.ridge@byu.eduSupplementary informationSupplementary data are available at Bioinformatics online.
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Project description:Taraxacum koksaghyz Rodin (TKS) has been studied in many occasions as a possible alternative source for natural rubber production of good quality and for inulin production. Some tire companies are already testing TKS tire prototypes. There are also many investigations on the production of bio-fuels from inulin and inulin applications for health improvement and in the food industry. A limited amount of genomic resources exist for TKS and particularly no genetic linkage map is available in this species. We have constructed the first TKS genetic linkage map based on AFLP, COS, SSR and EST-SSR markers. The integrated linkage map with eight linkage groups (LG), representing the eight chromosomes of Russian dandelion, has 185 individual AFLP markers from parent 1, 188 individual AFLP markers from parent 2, 75 common AFLP markers and 6 COS, 1 SSR and 63 EST-SSR loci. Blasting the EST-SSR sequences against known sequences from lettuce allowed a partial alignment of our TKS map with a lettuce map. Blast searches against plant gene databases revealed some homologies with useful genes for downstream applications in the future.
| S-EPMC4973268 | biostudies-literature
Project description:In 2013, we published a comparative analysis of mutation and gene expression profiles and drug sensitivity measurements for 15 drugs characterized in the 471 cancer cell lines screened in the Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Cell Line Encyclopedia (CCLE). While we found good concordance in gene expression profiles, there was substantial inconsistency in the drug responses reported by the GDSC and CCLE projects. We received extensive feedback on the comparisons that we performed. This feedback, along with the release of new data, prompted us to revisit our initial analysis. We present a new analysis using these expanded data, where we address the most significant suggestions for improvements on our published analysis - that targeted therapies and broad cytotoxic drugs should have been treated differently in assessing consistency, that consistency of both molecular profiles and drug sensitivity measurements should be compared across cell lines, and that the software analysis tools provided should have been easier to run, particularly as the GDSC and CCLE released additional data. Our re-analysis supports our previous finding that gene expression data are significantly more consistent than drug sensitivity measurements. Using new statistics to assess data consistency allowed identification of two broad effect drugs and three targeted drugs with moderate to good consistency in drug sensitivity data between GDSC and CCLE. For three other targeted drugs, there were not enough sensitive cell lines to assess the consistency of the pharmacological profiles. We found evidence of inconsistencies in pharmacological phenotypes for the remaining eight drugs. Overall, our findings suggest that the drug sensitivity data in GDSC and CCLE continue to present challenges for robust biomarker discovery. This re-analysis provides additional support for the argument that experimental standardization and validation of pharmacogenomic response will be necessary to advance the broad use of large pharmacogenomic screens.
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Project description:BackgroundPreeclampsia (PE) is associated with a high risk of perinatal morbidity and mortality. However, there is no consensus in the definition of high-risk women.AimTo question current definition of high PE risk and propose a definition that considers individual heterogeneity to improves risk classification.MethodsA stratified analysis by parity was conducted using the Swedish Birth Register between 2002-2010 including 626.600 pregnancies. The discriminatory accuracy (DA) of traditional definitions of high-risk women was compared with a new definition based on 1) specific combinations of individual variables and 2) a centile cut-off of the probability of PE predicted by a multiple logistic regression model.ResultsNone of the classical risk-factors alone reached an acceptable DA. In multiparous, any combination of a risk-factor with previous PE or HBP reached a +LR>10. The combination of obesity and multiple pregnancy reached a good DA particularly in the presence of previous preeclampsia (positive likelihood ratio (LR+) = 26.5 or chronic hypertension (HBP) LR+ = 40.5. In primiparous, a LR+>15 was observed in multiple pregnancies with the simultaneous presence of obesity and diabetes mellitus or with HBP. Predicted probabilities above 97 centile in multiparous and 99 centile in primiparous provided high (LR+ = 12.5), and moderate (LR+ = 5.85), respectively. No one risk factor alone or in combination provided a LR- sufficiently low to rule-out the disease.ConclusionsIn preeclampsia prediction the combination of specific risk factors provided a better discriminatory accuracy than traditional single risk approach. Our results contribute to a more personalized risk estimation of preeclampsia.
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Project description:This work addresses the energy-based source localization problem in wireless sensors networks. Instead of circumventing the maximum likelihood (ML) problem by applying convex relaxations and approximations, we approach it directly by the use of metaheuristics. To the best of our knowledge, this is the first time that metaheuristics are applied to this type of problem. More specifically, an elephant herding optimization (EHO) algorithm is applied. Through extensive simulations, the key parameters of the EHO algorithm are optimized such that they match the energy decay model between two sensor nodes. A detailed analysis of the computational complexity is presented, as well as a performance comparison between the proposed algorithm and existing non-metaheuristic ones. Simulation results show that the new approach significantly outperforms existing solutions in noisy environments, encouraging further improvement and testing of metaheuristic methods.
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Project description:The primary aim of this study was to estimate genetic diversity among Secale cereale L. accessions using 22 previously published simple sequence repeat (SSR) markers. The plant material included 367 rye accessions comprising historical and contemporary cultivars, cultivated materials, landraces, and breeding strains from the Polish breeding company Danko. The studied accessions represented a wide geographical diversity. Several methods were employed to analyze genetic diversity among the Secale cereale L. accessions and to determine population structure: principal coordinate analysis (PCoA), neighbor-joining (NJ), and Bayesian clustering. We also defined a core collection of 25 rye accessions representing over 93 % of SSR alleles. The results of these analyses showed that accessions from the rye gene bank are clearly divergent in comparison with materials received directly from European breeding companies. Our findings suggest also that the genetic pool of current rye cultivars is becoming narrower during breeding processes. The selected panel of SSR markers performed well in detection of genetic diversity patterns and can be recommended for future germplasm characterization studies in rye.
| S-EPMC4722074 | biostudies-literature
Project description:Juglans mandshurica is a native tree species in Northeast China. Due to habitat destruction and human disturbance, its population size has sharply decreased. Currently, information on molecular markers of J. mandshurica is limited and cannot meet the needs of germplasm resource evaluation and molecular marker-assisted breeding of J. mandshurica. Based on transcriptomic data from three tissues (leaves, bark, and fruit pericarp), we developed expressed sequence tag-simple sequence repeats (EST-SSRs) for J. mandshurica, and 15 polymorphic EST-SSR primers were initially selected. The average number of alleles (Na), expected heterozygosity (He), and the polymorphic information content (PIC) at different loci were 18.27, 0.670, and 0.797, respectively. Population genetic diversity analysis revealed that the average Na, He, and Shannon information indices (I) for 15 J. mandshurica populations were 6.993, 0.670, and 1.455, respectively. Among them, population Hunchun exhibited the highest genetic diversity (Na = 7.933, He = 0.723, and I = 1.617), while population Heihe exhibited the lowest genetic diversity (Na = 4.200, He = 0.605, and I = 1.158). STRUCTURE analysis, neighbor-joining method cluster analysis, and principal coordinate analysis showed that the 343 individuals of J. mandshurica from 15 populations were clustered into three categories. Category 1 (green) had 147 individuals from eight populations in Qingyuan, Caohekou, Jian, Ningan, Yongji, Baishishan, Helong, and Maoershan; category 2 (blue) had 81 individuals from three populations in Hulin, Boli, and Sanchazi; and category 3 (red) had 115 individuals from four populations in Heihe, Hunchun, Fangzheng, and Liangshui. Analysis of molecular variance (AMOVA) showed that genetic variations among and within individuals accounted for 16.22% and 21.10% of the total genetic variation, respectively, indicating that genetic variations within populations were greater than genetic variations among populations. The average genetic differentiation coefficient (Fst) and gene flow (Nm) between different populations were 0.109 and 4.063, respectively, implying moderate levels of genetic differentiation and gene flow. Based on the genetic diversity characteristics of different populations, we proposed various genetic conservation strategies for J. mandshurica.
| S-EPMC9280368 | biostudies-literature
Project description:Rice is critical for sustainable food and nutritional security; however, nominal micronutrient quantities in grains aggravate malnutrition in rice-eating poor populations. In this study, we evaluated genetic diversity in grain iron (Fe) and zinc (Zn) contents using trait-linked simple sequence repeat (SSR) markers in the representative subset of a large collection of local and exotic rice germplasm. Results demonstrated that aromatic fine grain accessions contained relatively higher Fe and Zn contents in brown rice (BR) than coarse grain accessions and a strong positive correlation between both mineral elements. Genotyping with 24 trait-linked SSR markers identified 21 polymorphic markers, among which 17 demonstrated higher gene diversity and polymorphism information content (PIC) values, strongly indicating that markers used in current research were moderate to highly informative for evaluating the genetic diversity. Population structure, principal coordinate and phylogenetic analyses classified studied rice accessions into two fine grain specific and one fine and coarse grain admixture subpopulations. Single marker analysis recognized four ZnBR and single FeBR significant marker-trait associations (MTAs) contributing 15.41-39.72% in total observed phenotypic variance. Furthermore, high grain Fe and Zn contents linked marker alleles from significant MTAs were also identified. Collectively, these results indicate a wide genetic diversity exist in grain Fe and Zn contents of studied rice accessions and reveal perspective for marker-assisted biofortification breeding.
| S-EPMC7521695 | biostudies-literature
Project description:BackgroundHost genetic backgrounds affect gene functions. The genetic backgrounds of genetically engineered organisms must be identified to confirm their genetic backgrounds identity with those of recipients. Marker-assisted backcrossing (MAB), transgenesis and clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (CRISPR/Cas9) editing are three commonly used genetic engineering techniques. However, methods for genetic background screening between genetically engineered organisms and corresponding recipients suffer from low efficiency, low accuracy or high cost.ResultsHere, we improved our previously reported AmpSeq-SSR method, an amplicon sequencing-based simple sequence repeat (SSR) genotyping method, by selecting SSR loci with high polymorphism among varieties. Ultimately, a set of 396 SSRs was generated and applied to evaluate the genetic backgrounds identity between rice lines developed through MAB, transgenesis, and CRISPR/Cas9 editing and the respective recipient rice. We discovered that the percentage of different SSRs between the MAB-developed rice line and its recipient was as high as 23.5%. In contrast, only 0.8% of SSRs were different between the CRISPR/Cas9-system-mediated rice line and its recipient, while no SSRs showed different genotypes between the transgenic rice line and its recipient. Furthermore, most differential SSRs induced by MAB technology were located in non-coding regions (62.9%), followed by untranslated regions (21.0%) and coding regions (16.1%). Trinucleotide repeats were the most prevalent type of altered SSR. Most importantly, all altered SSRs located in coding regions were trinucleotide repeats.ConclusionsThis method is not only useful for the background evaluation of genetic resources but also expands our understanding of the unintended effects of different genetic engineering techniques. While the work we present focused on rice, this method can be readily extended to other organisms.
| S-EPMC6547574 | biostudies-literature
Project description:Methods for analyzing the terminal sequences of proteins have been refined over the previous decade; however, few studies have evaluated the quality of the data that have been produced from those methodologies. While performing global N-terminal labelling on bacteria, we observed that the labelling was not complete and investigated whether this was a common occurrence. We assessed the completeness of labelling in a selection of existing, publicly available N-terminomics datasets and empirically determined that amine-based labelling chemistry does not achieve complete labelling and potentially has issues with labelling amine groups at sequence-specific residues. This finding led us to conduct a thorough review of the historical literature that showed that this is not an unexpected finding, with numerous publications reporting incomplete labelling. These findings have implications for the quantitation of N-terminal peptides and the biological interpretations of these data.
| S-EPMC6631386 | biostudies-literature