scholarly journals Mate choice and gene expression signatures associated with nutritional adaptation in the medfly (Ceratitis capitata)

2018 ◽  
Author(s):  
Will Nash ◽  
Irina Mohorianu ◽  
Tracey Chapman

AbstractEvolutionary responses to nutrition are key to understanding host shifts and the potential for reproductive isolation. Previously, experimental evolution was used to describe responses of the medfly (Ceratitis capitata) to divergent larval diets. Within 30 generations there was divergence in larval development time, egg to adult survival and adaptation in adult body size. In this study, the gene expression signatures associated with these changes were examined, using mRNA-seq on males following 60 generations of nutritional selection. Variation in gene expression was also validated using qRT-PCR. The results showed observed an over-representation of differential expression in metabolism, oxidative phosphorylation and proteolysis genes. In addition, at generations 60 and 90, we tested whether these evolved patterns (differences in gene expression) were associated with mate choice. We found evidence for assortative mating by diet at generation 60, but not in mating tests within and between replicate lines at generation 90. Hence, there was no consistent evidence for assortative mating by diet, which emphasises the importance of replicate tests of evolutionary responses over time. Overall, the study provides the first genome-wide survey of the putative mechanisms underpinning evolved responses to nutritional adaptation.

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Carlos Lopez-Ortiz ◽  
Yadira Peña-Garcia ◽  
Purushothaman Natarajan ◽  
Menuka Bhandari ◽  
Venkata Abburi ◽  
...  

2021 ◽  
Author(s):  
Pavitra Muralidhar ◽  
Graham Coop ◽  
Carl Veller

Hybridization and subsequent genetic introgression are now known to be common features of the histories of many species, including our own. Following hybridization, post-zygotic selection tends to purge introgressed DNA genome-wide. While mate choice can prevent hybridization in the first place, it is also known to play an important role in post-zygotic selection against hybrids, and thus the purging of introgressed DNA. However, this role is usually thought of as a direct one: a mating preference for conspecifics reduces the sexual fitness of hybrids, reducing the transmission of introgressed ancestry. Here, we explore a second, indirect role of mate choice as a barrier to gene flow. Under assortative mating, parents covary in their ancestry, causing ancestry to be "bundled" in their offspring and later generations. This bundling effect increases ancestry variance in the population, enhancing the efficiency with which post-zygotic selection purges introgressed DNA. Using whole-genome simulations, we show that the bundling effect can comprise a substantial portion of mate choice's overall effect as a postzygotic barrier to gene flow, and that it is driven by ancestry covariances both between and within maternally and paternally inherited genomes. Using estimates of the strength of assortative mating in avian hybrid zones, we calculate that the bundling effect of mate choice may increase the amount of purging of introgressed DNA by 40-80%, contributing substantially to the genetic isolation of species.


PLoS Genetics ◽  
2011 ◽  
Vol 7 (12) ◽  
pp. e1002415 ◽  
Author(s):  
Chia Huey Ooi ◽  
Hue Kian Oh ◽  
Hannah Zhu'Ai Wang ◽  
Angie Lay Keng Tan ◽  
Jeanie Wu ◽  
...  

2019 ◽  
Author(s):  
Krzysztof Koras ◽  
Dilafruz Juraeva ◽  
Julian Kreis ◽  
Johanna Mazur ◽  
Eike Staub ◽  
...  

Drug sensitivity prediction constitutes one of the main challenges in personalized medicine. The major difficulty of this problem stems from the fact that the sensitivity of cancer cells to treatment depends on an unknown subset of a large number of biological features. Although feature selection is the key to interpretable results and identification of potential biomarkers, a comprehensive assessment of feature selection methods for drug sensitivity prediction has so far not been performed. We propose feature selection approaches driven by prior knowledge of drug targets, target pathways, and gene expression signatures. We asses these methodologies on Genomics of Drug Sensitivity in Cancer (GDSC) dataset, a panel of around 1000 cell lines screened against multiple anticancer compounds. We compare our results with a baseline model utilizing genome-wide gene expression features and common data-driven feature selection techniques. Together, 2484 unique models were evaluated, providing a comprehensive study of feature selection strategies for the drug response prediction problem. For 23 drugs, the models achieve better predictive performance when the features are selected according to prior knowledge of drug targets and pathways. The best correlation of observed and predicted response using the test set is achieved for Linifanib (r=0.75). Extending the drug-dependent features with gene expression signatures yields models that are most predictive of drug response for 60 drugs, with the best performing example of Dabrafenib. Examples of how pre-selection of features benefits the model interpretability are given for Dabrafenib, Linifanib and Quizartinib. Based on GDSC drug data, we find that feature selection driven by prior knowledge tends to yield better results for drugs targeting specific genes and pathways, while models with the genome-wide features perform better for drugs affecting general mechanisms such as metabolism and DNA replication. For a significant group of the compounds, even a very small number of features based on simple drug properties is often highly predictive of drug sensitivity, can explain the mechanism of drug action and be used as guidelines for their prescription. In general, choosing appropriate feature selection strategies has the potential to develop interpretable models that are indicative for therapy design.


Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 2186-2186
Author(s):  
Francesca Messa ◽  
Monica Pradotto ◽  
Francesca Arruga ◽  
Roberto Bernardoni ◽  
Enrico Bracco ◽  
...  

Abstract Abstract 2186 Poster Board II-163 Despite the role of Bcr-Abl in the pathogenesis of Chronic Myeloid Leukaemia (CML) is well established, the mechanisms responsible for CML progression remain largely unknown. The aim of the study was to perform a genome-wide screening to identify new genes and pathways leading to CML progression. We performed a genome-wide genetic screening using our set-up model of human p210 Bcr-Abl transgenic Drosophila melanogaster (Dm) in which the expression of hBcr-Abl in a tissue specific manner is able to induce a severe eye-glazed phenotype or the formation of melanotic tumors, (clusters of hemocytes) when expressed into the fly lymph gland which represent the Dm hematopoietic system. A wide modifier screening of the whole fly genome containing approx 14.000 genes was performed using 278 fly stocks commercially available and carrying well characterized chromosome deletions. The resulting progeny was screened using the eye phenotype as first read-out system. Furthermore each deletion responsible for phenotype changes was analyzed either by expressing it into lymph gland as second read-out system, in order to analyze their function into a haematopoietic background and to exclude genes involved in eye development, such as genes able to modify the eye phenotype even without being directly involved in Bcr-Abl oncogenic signalling (false positives). Data obtained from primary and secondary screen were first analyzed using the Gene Ontology software. These results were compared with gene expression signatures of CML from Microarray data. As final point, the identified candidate genes were tested and validated analyzing either BM or PB samples from CML patients and healthy donors. 14.000 Dm genes were analyzed for their capability to genetically interact with hBcr-Abl in the fly model. The analysis of eye/lymph gland-phenotypes in the progeny obtained from screening crosses, shows a first group of flies (38%) displaying a more aggressive phenotype since they lack genes encoding for hBcr-Abl negative regulators and a second group (32%) showing a mild phenotype due to the absence of genes involved in the oncogenic signalling. We found that 42% of the 4000 Dm genes mapping in the deleted regions able to modify Bcr-Abl phenotype, displayed a known human counterpart. GeneOntology profiles of these genes included oncogenes, tumor suppression genes and human genes encoding proteins involved in the regulation of transcriptions, signal transduction, proliferation and cell growth, differentiation, apoptosis and splicing processes. Moreover, a computational comparison of our results with gene expression signatures of CML from Microarray data, showed only a partially overlap between genes identified in fly screen and genes obtained from Microarray analysis. The 72% of identified genes in fact was not known to be involved in human leukaemia. However, further confirmation of our findings into fly comes from the validation in human samples in which 1250 genes were found to be significantly associated with human CML; among these genes, we found not only an alteration of their expression profiles in CML patients with respect to the healthy donors, but also protein alterations, such as expression of different splicing forms or misplaced proteins, suggesting that Dm screening is a valid approach able to identify not only differentially expressed genes but also specific pathways and genes otherwise altered by hBcr-Abl. In conclusion, the identification of these genes allows identifying of the changes occurring in CML at the genomic level and gives deeper insights into the molecular basis of the disease; moreover this study point to specific gene pathways that might represent new targets for therapy in CML in order to prevent or overcome resistance and progression Disclosures: No relevant conflicts of interest to declare.


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