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dc.contributor.authorCrawford, Jacoben_US
dc.date.accessioned2013-01-31T19:46:35Z
dc.date.available2013-01-31T19:46:35Z
dc.date.issued2012-08-20en_US
dc.identifier.otherbibid: 7959778
dc.identifier.urihttps://hdl.handle.net/1813/31214
dc.description.abstractHuman malaria parasites are vectored primarily by three mosquito species of the genus Anopheles, and new technologies and strategies to control disease transmission by targeting the mosquito vector have been proposed or are in development. The success of these strategies depends on knowledge of genetic variation at relevant loci in targeted mosquito populations. However, we know very little about the selective forces shaping genetic variation of proteins involved in the mosquito-parasite interaction that could potentially be developed for intervention. Genetic variation in populations is largely shaped by natural selection, demography, and genetic drift. I used population genetic approaches to study the historical demographic and selective events of multiple populations of one of the primary vectors, Anopheles gambiae. Statistical inference through comparisons of population samples simulated under a variety of demographic models to genomically distributed empirical re-sequencing data revealed evidence for both historical population growth and migration in the M and S molecular forms, two insipient species of A. gambiae. Importantly, significantly different demographic histories were inferred for the two molecular forms. Both forms show evidence of population growth that predated the agricultural revolution, which has been suggested as a cause of population growth in this system. Novel vector-based disease intervention strategies are largely based on two types of mosquito proteins: non-immune proteins that physically interact with the malaria parasite during parasite development and immune genes involved in the anti-malaria immune response. To test whether two transmission- blocking vaccine candidate proteins saglin and laminin are adaptively evolving, I v sampled alleles from wild caught populations of the M and S molecular forms and analyzed both intraspecific and interspecific patterns of variation using population genetic tests. Neither protein showed significant evidence for positive selection in these populations. On the contrary, these proteins are evolving neutrally, one protein is evolving under particularly strong purifying selection, suggesting that it may be relatively reliable vaccine target. Immune genes show different patterns of evolution, however. I sampled alleles at 28 candidate immune genes in wild caught samples of three populations of A. gambiae: the M and S molecular forms and the recently discovered and genetically distinct GOUNDRY population. Population genetic neutrality tests revealed striking divisions of putative selection signals among these strata, with only 1 of the 11 loci that rejected the neutral model being shared among the populations. Interestingly, the S molecular form showed no evidence of positive selection at any loci. Putative positive selection was identified at loci that encode immune proteins from a variety of functional classes. When considered in the context of differences between the larval ecologies of these populations, these results point to a complex division of selection regimes among these strata of A. gambiae, probably related to larval pathogens encountered during niche expansion in the M molecular form and GOUNDRY. Recent advancements in DNA sequencing technology make the prospects of wholegenome sequencing-based population genomic studies likely for Anopheles mosquitoes in the near future, but this so-called ʻnext-generation sequencing' (NGS) is complicated by relatively high sequencing error rates and subsequent uncertainty in genotype inference. To explore potential biases and statistical power of NGS-based population genomic studies, I used a simulation approach to identify biases introduced into demographic analysis, tests for positive natural selection, and analysis of genetic differentiation between populations. At relatively shallow sequencing depth (4x), vi demographic inference and estimates of genetic differentiation are systematically biased, and positive selection can only be reliably detected if it is strong and recent. Many of the biases are mitigated and statistical power improved when sequencing depth is increased to even 8x, and 15x recovers the population genetic signals almost completely. This analysis provides insight into the biases that can be expected in NGS-based studies, and provides parameter values that can be used to inform the design of future NGSbased studies. Anopheles funestus is a primary vector of malaria, but little is known about the basic biology and few genetic resources are available for this species. I used next-generation Illumina RNA-sequencing technology to sequence and assemble the transcriptome of A. funestus de novo, generating over 15,000 putative transcripts. I annotated the transcriptome through comparisons to the sequenced genomes of other Dipteran insects and functional domain databases, identified over 300 putative immune genes, and mapped the raw sequence reads back to the transcriptome and identified over 300,000 potential genetic variants. These data provide the largest and most exhaustive sequence and bioinformatic resource as well as putative genetic variants that can be developed for population genetic or mapping studies for this system viien_US
dc.language.isoen_USen_US
dc.subjectAnopheles gambiaeen_US
dc.subjectmalariaen_US
dc.subjectpopulation geneticsen_US
dc.titlePopulation Genetic And Genomic Analysis Of Demography And Natural Selection In Anopheles Malaria Vectorsen_US
dc.typedissertation or thesisen_US
thesis.degree.disciplineEntomology
thesis.degree.grantorCornell Universityen_US
thesis.degree.levelDoctor of Philosophy
thesis.degree.namePh. D., Entomology
dc.contributor.chairLazzaro, Brianen_US
dc.contributor.committeeMemberHarrington, Laura C.en_US
dc.contributor.committeeMemberAquadro, Charles Fen_US


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