Project description:Statistical parametric maps formed via voxel-wise mass-univariate tests, such as the general linear model, are commonly used to test hypotheses about regionally specific effects in neuroimaging cross-sectional studies where each subject is represented by a single image. Despite being informative, these techniques remain limited as they ignore multivariate relationships in the data. Most importantly, the commonly employed local Gaussian smoothing, which is important for accounting for registration errors and making the data follow Gaussian distributions, is usually chosen in an ad hoc fashion. Thus, it is often suboptimal for the task of detecting group differences and correlations with non-imaging variables. Information mapping techniques, such as searchlight, which use pattern classifiers to exploit multivariate information and obtain more powerful statistical maps, have become increasingly popular in recent years. However, existing methods may lead to important interpretation errors in practice (i.e., misidentifying a cluster as informative, or failing to detect truly informative voxels), while often being computationally expensive. To address these issues, we introduce a novel efficient multivariate statistical framework for cross-sectional studies, termed MIDAS, seeking highly sensitive and specific voxel-wise brain maps, while leveraging the power of regional discriminant analysis. In MIDAS, locally linear discriminative learning is applied to estimate the pattern that best discriminates between two groups, or predicts a variable of interest. This pattern is equivalent to local filtering by an optimal kernel whose coefficients are the weights of the linear discriminant. By composing information from all neighborhoods that contain a given voxel, MIDAS produces a statistic that collectively reflects the contribution of the voxel to the regional classifiers as well as the discriminative power of the classifiers. Critically, MIDAS efficiently assesses the statistical significance of the derived statistic by analytically approximating its null distribution without the need for computationally expensive permutation tests. The proposed framework was extensively validated using simulated atrophy in structural magnetic resonance imaging (MRI) and further tested using data from a task-based functional MRI study as well as a structural MRI study of cognitive performance. The performance of the proposed framework was evaluated against standard voxel-wise general linear models and other information mapping methods. The experimental results showed that MIDAS achieves relatively higher sensitivity and specificity in detecting group differences. Together, our results demonstrate the potential of the proposed approach to efficiently map effects of interest in both structural and functional data.

Project description:BACKGROUND: Animal pigmentation has received much attention in evolutionary biology research due to its strong implications for adaptation and speciation. However, apart from a few cases the genetic changes associated with these evolutionary processes remain largely unknown. The Midas cichlid fish from Central America are an ideal model system for investigating pigmentation traits that may also play a role in speciation. Most Midas cichlids maintain their melanophores and exhibit a grayish (normal) color pattern throughout their lives. A minority of individuals, however, undergo color change and exhibit a distinctive gold or even white coloration in adulthood. The ontogenetic color change in the Midas cichlids may also shed light on the molecular mechanisms underlying pigmentation disorders in humans. RESULTS: Here we use next-generation sequencing (Illumina) RNAseq analyses to compare skin transcriptome-wide expression levels in three distinct stages of color transformation in Midas cichlids. cDNA libraries of scale tissue, for six biological replicates of each group, were generated and sequenced using Illumina technology. Using a combination of three differential expression (DE) analyses we identified 46 candidate genes that showed DE between the color morphs. We find evidence for two key DE patterns: a) genes involved in melanosomal pathways are up-regulated in normally pigmented fish; and b) immediate early and inflammatory response genes were up-regulated in transitional fish, a response that parallels some human skin disorders such as melanoma formation and psoriasis. One of the DE genes segregates with the gold phenotype in a genetic cross and might be associated with incipient speciation in this highly "species-rich" lineage of cichlids. CONCLUSIONS: Using transcriptomic analyses we successfully identified key expression differences between different color morphs of Midas cichlid fish. These differentially expressed genes have important implications for our understanding of the molecular mechanisms underlying speciation in this lineage of extremely young species since they mate strongly assortatively, and new species may arise by sexual selection due to this color polymorphism. Some of the human orthologues of the genes identified here may also be involved in pigmentation differences and diseases and therefore provide genetic markers for the detection of human pigmentation disorders.

			Action	DRS
	CCOE01.dat.gz	Other
	CCOE01.fasta.gz	Fasta.gz
	CCOE01.master.dat	Other
	ERR583977_1.fastq.gz	Fastqsanger.gz
	ERR583977_2.fastq.gz	Fastqsanger.gz

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Midas v5

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