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opencc-by-4.0Oct 2022View details →

Genetic Constructs of From UManitoba iGEM 2022 ZebraZap

The file titled zebrazap_plasmids.zip contains all of the plasmids mentioned in the ZebraZap project, they are available as annotated GenBank files. The file titled zebrazap_primmers.zip contains all of the primmers mentioned in the ZebraZap project, they are available as annotated GenBank files.

opencc-zeroOct 2022View details →

Oenothera Section Calylophus population genetic study

Premise: Animal pollinators play an important role in pollen dispersal. Differences in foraging patterns, flight distances and grooming behaviors are assumed to have consequences for genetic diversity of plants but are rarely tested explicitly. Here, we assess the role of pollinator functional groups with different foraging behaviors (hawkmoth and bee) in generating patterns of genetic diversity over similar geographic ranges for two closely related taxa. Methods: This study focuses on two members of Oenothera section Calylophus that co-occur on gypsum outcrops throughout the Chihuahua Desert but differ in floral phenotype and primary pollinator: Oenothera gayleana (bee) and O. hartwegii subsp. filifolia (hawkmoth). We measured breeding system and floral traits in the greenhouse and conducted a population genetic study at the local (<13km; four populations) and landscape (60–440km; five populations) scales using 10–11 nuclear (pollen dispersal) and three plastid (seed dispersal) microsatellite markers. Key Results: Both taxa were self-incompatible and floral traits were consistent with expectations for different pollinators. We found no evidence of genetic structure at the local scale, but at the landscape scale, O. gayleana showed greater differentiation and significant isolation by distance than O. hartwegii subsp. filifolia. The plastid data were consistent with gravity dispersal of seeds and suggest that pollen dispersal is the principal driver of genetic structure in both species. Conclusions: We demonstrate that pollinator functional groups can impact genetic differentiation in different and predictable ways. Hawkmoths, with larger foraging distances, can maintain gene flow across greater spatial scales than bees.

opencc-by-4.0Jan 2017View details →

Figure 5 in Hybrid neural network with genetic algorithms for predicting distribution pattern of Tetranychus urticae (Acari: Tetranychidae) in cucumbers field of Ramhormoz, Iran

Figure 5. Tetranychus urticae distribution maps in actual (b, d and f) and classified conditions by MLPNN (c, e and a). The maps of a, c, e and b, d, f have been drawn according to economic threshold of 4, 8 and 12, respectively.

opencc-by-4.0Oct 2022View details →

Construction of a SNP fingerprinting database and population genetic analysis of 329 cauliflower cultivars

The VCF file contains the information of 1662 SNP sites of 820 cauliflower inbred lines that were filtered according to a series of stringent conditions.

opencc-by-4.0Nov 2020View details →

How ancient forest fragmentation and riparian connectivity generate high levels of genetic diversity in a micro-endemic Malagasy tree

This repository contains all the scripts and most of the intermediary files necessary to replicate the analyses of the preprint "How ancient forest fragmentation and riparian connectivity generate high levels of genetic diversity in a micro-endemic Malagasy tree" submitted to Molecular Ecology and available at: <a href="https://www.biorxiv.org/content/10.1101/2020.11.25.394544v1">https://www.biorxiv.org/content/10.1101/2020.11.25.394544v5</a> Within each of the different zipped folders a readme.txt file briefly explains how the analyses are organized. This version of the dataset has been revised in agreement with the manuscript revision to answer the comments of the first two rounds of reviews in Peer Community In Evolutionary Biolology (PCI-EvolBiol; <a href="https://evolbiol.peercommunityin.org/">https://evolbiol.peercommunityin.org/</a>) by M. Navascues (Recommender), Katharina Budde (reviewer) and Yurena Arjona (reviewer), as well as two rounds of reviews in Molecular Ecology. All PCIevolbiol comments, response and changes are documented on the PCIevolbiol website.

Figure 6. One chromosome from the population and the five chromosomes existing in the evaluation partition.-Genetic Algorithms Principles Towards Hidden Markov Model

For example comparing the chromosome given in Figure 6 with the first chromosome in the evaluation partition, the difference between the relation Med-Med and Med-High as a pair is 0.0 and the difference between the relation High-High and High-Med as a pair is 0.1. Similarly the difference between the relation Med-Cold and Med-Hot as a pair is 0.1 and the difference between the relation High-Cold and High-Hot as a pair is 0.2. We sum all these differences to get the value of compare(i,j), the sum value is 0+0.1+0.1+0.2 = 0.4. Using the same approach we compute the compare function with the other four chromosomes and we get values 0.4, 0.5,0.4 and 0.6. Now we sum the five values 0.4 + 0.4 + 0.5+ 0.4 +0.6 = 2.3. The fitness value is then 1/ 2.3 = 0.434. The highest is the fitness value, the better is the performance of the chromosome.

Figure 4. Incorrect crossover operation. The High-High and High-Med probability values summation should be 1.-Genetic Algorithms Principles Towards Hidden Markov Model

In this genetic operator, we choose two chromosomes at random and apply crossover between them. Figure 3 shows the proposed crossover. We choose a crossing cut site at random. It is to be noted that the crossing cut site should be even number. We should have two crossing cut sites. If we make crossing cut site odd number, the resultant child will not have a correct value of probability. The incorrect crossover is shown in Figure 4.

Figure 5. Mutation process. This is happened by decreasing 0.2 from Med-Cold probability and adding 0.2 to Med- Hot.-Genetic Algorithms Principles Towards Hidden Markov Model

Figure 5 illustrates an example of mutation process. In Figure 5, Med-Cold:0.9 and Med-Hot:0.1 before mutation and become Med-Cold:0.7 and Med-Hot:0.3 after mutation. This is done by decreasing 0.2 from Med-Cold probability and adding 0.2 to Med-Hot probability.

Figure 3. The crossover operation between two HMM chromosomes Figure-Genetic Algorithms Principles Towards Hidden Markov Model

Crossover In this genetic operator, we choose two chromosomes at random and apply crossover between them. Figure 3 shows the proposed crossover. We choose a crossing cut site at random. It is to be noted that the crossing cut site should be even number. We should have two crossing cut sites. If we make crossing cut site odd number, the resultant child will not have a correct value of probability. The incorrect crossover is shown in Figure 4.

Figure 2. The general structure of the proposed approach-Genetic Algorithms Principles Towards Hidden Markov Model

The chromosome contains 8 genes, each is represented by the relation between two states accompanied with a probability value. The genes should be formed in this way because this is important in the crossover operation as to be explained later. The most important thing is that each two genes has the probability summation of 1.0. For example Med-Med:02 and Med-High:08 have the summation of 1.0. Similarly High-High:0.6 and High-Med:0.4 have the summation of 1.0. Each two genes with summation of 1.0 should be neighbors.

Figure 1. HMM to describe a relation between the states Med. and High with the observations (invisible states) cold and hot.-Genetic Algorithms Principles Towards Hidden Markov Model

Hewahi [4] presented a modified version of Censored Production Rule (CPR) called Modified Censored Production Rules (MCPR). CPR is proposed by Michalski and Winston [6 ] to capture real time situations. MCPR can fit with hidden Markov model and present a scheme to compute the certainty values of the obtained conclusions out of the induced rules. To compute the certainty values for the rule actions (conclusions), the approach exploited only the probability values associated with the hidden Markov model without using any of the other well known certainty computation approaches. Hewahi [3] also proposed an intelligent networking management system based on the induced MCPRs extracted from a networking structure based on HMM. The advantage of using this technique is that MCPRs are very useful in real time applications and can be adapted over time based on the obtained experience of the networking working process. Let us consider the HMM presented in Figure 1.

opencc-by-4.0Oct 2013View details →

BRAIN Journal-Evolving Spiking Neural Networks for Control of Artificial Creatures-Figure 12. Genetic Algorithm flowchart

Then next generation are produced by combination of the elites (15%), crossover (55%) and mutation (30%) of the initial population. Elites are the best chromosomes which are directly transferred to the next generation. Because of long chromosome length, for crossover, five points are randomly chosen in each parent as cut points. Figure 11 shows a typical crossover with two cutpoints and Figure 12 illustrates a flowchart for the proposed evolutionary model. Selections are based on Roulette Wheel selection, more detailed information can be found in.

opencc-by-4.0Jul 2021View details →

FIGURE 1 in Genetic diversity in two threatened species of guitarfish (Elasmobranchii: Rhinobatidae) from the Brazilian and Argentinian coasts: an alert for conservation

FIGURE 1 | Median-joining network of mtCR haplotypes for A. Pseudobatos horkelii and B. Pseudobatos percellens. Haplotypes are represented by circles with size proportional to frequency in the total sample. All hatch marks correspond to one mutation. Samples from northern Argentina (AR), Torrinha/RS (RS), Florianópolis/SC (SC), Pontal do Paraná/PR (PR), Cananéia/ SP (SP1), Mongaguá/SP (SP2), Santos/SP (SP3), Rio de Janeiro/RJ(RJ).

opencc-by-4.0Jul 2021View details →

FIGURE 2 in Genetic diversity in two threatened species of guitarfish (Elasmobranchii: Rhinobatidae) from the Brazilian and Argentinian coasts: an alert for conservation

FIGURE 2 | Graph of the Bayesian analysis of population structure of mtCR for A. Pseudobatos horkelii and B. Pseudobatos percellens. Samples from northern Argentina (AR), Torrinha/RS (RS), Florianópolis/SC (SC), Pontal do Paraná/PR (PR), Cananéia/ SP (SP1), Mongaguá/SP (SP2), Santos/SP (SP3), Rio de Janeiro/RJ(RJ).

opencc-by-4.0Jan 2023View details →

Indirect genetic effects are shaped by demographic history and ecology in Arabidopsis thaliana

This folder contains data & code used for the study "Indirect genetic effects are shaped by demographic history and ecology in Arabidopsis thaliana" All data analyzed in the study are stored in the folder "data": <ul> <li>"pheno_file.csv": the main phenotypic file corresponding to the experiment with paired plants used to estimate Indirect Genetic Effects.</li> <li>"pheno_file_single_plants.csv": phenotypic file with measurements of plant biomasses in the absence of competition (single plants)</li> <li>"call_method_75_TAIR9.csv": genomic data (SNPs) for each accession from the RegMap panel (ref [1])</li> <li>"Data_geo_RegMap_accessions.csv": geographic localization of each accession from the RegMap panel (ref [2])</li> <li>"igeGWAS_scores.csv": Genome-Wide Association Study (GWAS) results reporting for each SNP from the RegMap panel the p-value and estimated effect sizes of their direct and indirect genetic effects</li> <li>"1001_accessions_info.csv": geographic localization and admixture group for each accession from the 1001 genomes project (ref [3])</li> <li>"snp_data_all_samples.txt": allelic value of each accession from the 1001 genomes project at the eleven top SNPs associated with IGE</li> <li>"sample_names.txt": names of  accessions listed in the file "snp_data_all_samples.txt"</li> <li>"climatic_data.csv": climatic data for each accessions from the 1001 genomes project (ref [4])</li> <li>"candidate_genes_all.csv":  list of all genes (and associated GO terms) with a non-synonymous, nonsense, or frameshift mutation in close proximity (distance < half LD decay distance) and high linkage (r2>0.5) with a SNP significantly associated with IGE</li> <li>"genes.coord.bed": list of all genes in a +- 500 kb around top IGE SNPs and their coordinates</li> <li>"AllGenes_fst.GeneID.txt": pairwise Fst computed between each pair of admixture groups, for all genes annotated in the genome of A. thaliana</li> </ul> "ABBA_BABA" subfolder contains ABBA_BABA statistics computed for each individual chromosome (Chr1-Chr5) using genomic windows of 20 kb with at least 250 SNPs per windows. ABBA-BABA statistics were computed using custom python scripts from https://github.com/simonhmartin/genomics_general "GEA" subfolder contains Genome-Environment Association results, with one file per chromosome x climatic variable. Climatique variable are indexed, following the order listed in the file "Climatic_variables.txt" within the subfolder "GEA". GEA analysis were run with the gemma program: https://github.com/genetics-statistics/GEMMA. "LD_IGE_SNPs" subfolders contains the list of SNPs located at +- 2Mb of a significant IGE SNP (one file per IGE SNP, named "SNPalias_LDSimplified.csv") and their linkage (r2) with the IGE SNP. It also contains the file "LD_windows_sizes.csv" with the half LD decay distances for all significant IGE SNP. All analysis performed to produce the tables and figures presented in the study (main manuscript & supplementary information) were done with the R script "Arabidopsis_IGE_analysis.R", which uses "manhattan_custom.R" as a source function to produce custom manhattan plots.   REFERENCES: [1] Horton MW, Hancock AM, Huang YS, Toomajian C, Atwell S, Auton A, Muliyati NW, Platt A, Sperone FG, Vilhjálmsson BJ, et al. 2012. Genome-wide patterns of genetic variation in worldwide Arabidopsis thaliana accessions from the RegMap panel. Nature Genetics 44: 212–216. [2] Anastasio AE, Platt A, Horton M, Grotewold E, Scholl R, Borevitz JO, Nordborg M, Bergelson J. 2011. Source verification of mis-identified Arabidopsis thaliana accessions. The Plant Journal 67: 554–566. [3] 1001 Genomes Consortium. 2016. 1,135 genomes reveal the global pattern of polymorphism in Arabidopsis thaliana. Cell 166: 481–491. [4] Ferrero-Serrano Á, Assmann SM. 2019. Phenotypic and genome-wide association with the local environment of Arabidopsis. Nature Ecology & Evolution 3: 274–285.

opencc-zeroApr 2024View details →

Global patterns of nuclear and mitochondrial genetic diversity in marine fishes

Genetic diversity is a fundamental component of biodiversity. Examination of global patterns of genetic diversity can help highlight mechanisms underlying species diversity, though a recurring challenge has been that patterns may vary by molecular marker. Here, we compiled 6862 observations of genetic diversity from 492 species of marine fish and tested among hypotheses for diversity gradients: the founder effect hypothesis, the kinetic energy hypothesis, and the productivity-diversity hypothesis. We fit generalized linear mixed effect models (GLMMs) and explored the extent to which various macroecological drivers (latitude, longitude, temperature (SST), and chlorophyll-a concentration) explained variation in genetic diversity. We found that mitochondrial genetic diversity followed geographic gradients similar to those of species diversity, being highest near the Equator, particularly in the Coral Triangle, while nuclear genetic diversity did not follow clear geographic patterns. Despite these differences, all genetic diversity metrics were correlated with chlorophyll-a concentration, while mitochondrial diversity was also positively associated with SST. Our results provide support for the kinetic energy hypothesis, which predicts that elevated mutation rates at higher temperatures increase mitochondrial but not necessarily nuclear diversity, and the productivity-diversity hypothesis, which posits that resource-rich regions support larger populations with greater genetic diversity. Overall, these findings reveal how environmental variables can influence mutation rates and genetic drift in the ocean, caution against using mitochondrial macro-genetic patterns as proxies for whole-genome diversity, and aid in defining global gradients of genetic diversity.

opencc-zeroDec 2023View details →

Genetic architecture of disease resistance and tolerance in Douglas-fir trees

Understanding the genetic architecture of tolerance and resistance to pathogens is important to monitor and maintain resilient tree populations. Here we investigate the genetic basis of tolerance and resistance to needle cast disease in Douglas-fir (Pseudotsuga menziesii) caused by two fungal pathogens: Swiss needle cast (SNC) caused by Nothophaeocryptopus gaeumannii, and Rhabdocline needle cast (RNC) caused by Rhabdocline pseudotsugae). We performed a case-control genome-wide association analysis (GWA) and found these traits to be polygenic and under selection. We showed that stomatal regulation as well as ethylene and jasmonic acid pathways are important for resisting SNC infection and secondary metabolite pathways play a role in tolerating SNC once the plant is infected. We identified a key upstream transcription factor of plant defence, ERF1, as the main candidate for RNC resistance. Our findings contribute to the understanding of the highly polygenic architectures underlying disease resistance and tolerance in Douglas-fir and have important implications for forestry and conservation as the climate changes.

opencc-zeroApr 2024View details →

Genetic modification of the bee parasite Crithidia bombi for improved visualization and protein localization

Crithidia bombi is a trypanosomatid parasite that infects several species of bumble bees (Bombus spp.), by adhering to their intestinal tract. Crithidia bombi infection impairs learning and reduces survival of workers and overwintering queens. Although there is extensive research on the ecology of this host-pathogen system, we understand far less about the mechanisms that mediate internal infection dynamics. Crithidia bombi infects hosts by attaching to the hindgut via the flagellum, and one previous study found that a nectar secondary compound removed the flagellum, preventing attachment. However, approaches that allow more detailed observation of parasite attachment and growth would allow us to better understand factors mediating this host-pathogen relationship. We established techniques for genetic manipulation and visualization of cultured C. bombi. Using constructs established for Crithidia fasciculata, we successfully generated C. bombi cells expressing ectopic fluorescent transgenes using two different selectable markers. To our knowledge, this is the first genetic modification of this species. We also introduced constructs that label the mitochondrion and nucleus of the parasite, showing that subcellular targeting signals can function across parasite species to highlight specific organelles. Finally, we visualized fluorescently tagged parasites in vitro in both their swimming and attached forms, and in vivo in bumble bee (Bombus impatiens) hosts. Expanding our cell and molecular toolkit for C. bombi will help us better understand how factors such as host diet, immune system, and physiology mediate outcomes of infection by these common parasites.

opencc-zeroMay 2024View details →

Data from: Genome-wide association mapping within a local Arabidopsis thaliana population more fully reveals the genetic architecture for defensive metabolite diversity

A paradoxical finding from genome-wide association studies (GWAS) in plants is that variation in metabolite profiles typically maps to a small number of loci, despite the complexity of underlying biosynthetic pathways. This discrepancy may partially arise from limitations presented by geographically diverse mapping panels. Properties of metabolic pathways that impede GWAS by diluting the additive effect of a causal variant, such as allelic and genic heterogeneity and epistasis, would be expected to increase in severity with the geographic range of the mapping panel. We hypothesized that a population from a single locality would reveal an expanded set of associated loci. We tested this in a French Arabidopsis thaliana population (< 1 km transect) by profiling and conducting GWAS for glucosinolates, a suite of defensive metabolites that have been studied in depth through functional and genetic mapping approaches. For two distinct classes of glucosinolates, we discovered more associations at biosynthetic loci than previous GWAS with continental-scale mapping panels. Candidate genes underlying novel associations were supported by concordance between their observed effects in the TOU-A population and previous functional genetic and biochemical characterization. Local populations complement geographically diverse mapping panels to reveal a more complete genetic architecture for metabolic traits.