A 3D cellular context for the macromolecular world

We report the outcomes of the discussion initiated at the workshop entitled A 3D Cellular Context for the Macromolecular World and propose how data from emerging three-dimensional (3D) cellular imaging techniques—such as electron tomography, 3D scanning electron microscopy and soft X-ray tomography—should be archived, curated, validated and disseminated, to enable their interpretation and reuse by the biomedical community

Hypothesis-driven genome-wide association studies provide novel insights into genetics of reading disabilities

Peer reviewe

Genome-wide analyses of individual differences in quantitatively assessed reading- and language-related skills in up to 34,000 people

The use of spoken and written language is a fundamental human capacity. Individual differences in reading- and language-related skills are influenced by genetic variation, with twin-based heritability estimates of 30 to 80% depending on the trait. The genetic architecture is complex, heterogeneous, and multifactorial, but investigations of contributions of single-nucleotide polymorphisms (SNPs) were thus far underpowered. We present a multicohort genome-wide association study (GWAS) of five traits assessed individually using psychometric measures (word reading, nonword reading, spelling, phoneme awareness, and nonword repetition) in samples of 13,633 to 33,959 participants aged 5 to 26 y. We identified genome-wide significant association with word reading (rs11208009, P = 1.098 x 10(-8)) at a locus that has not been associated with intelligence or educational attainment. All five reading-/language-related traits showed robust SNP heritability, accounting for 13 to 26% of trait variability. Genomic structural equation modeling revealed a shared genetic factor explaining most of the variation in word/nonword reading, spelling, and phoneme awareness, which only partially overlapped with genetic variation contributing to nonword repetition, intelligence, and educational attainment. A multivariate GWAS of word/nonword reading, spelling, and phoneme awareness maximized power for follow-up investigation. Genetic correlation analysis with neuroimaging traits identified an association with the surface area of the banks of the left superior temporal sulcus, a brain region linked to the processing of spoken and written language. Heritability was enriched for genomic elements regulating gene expression in the fetal brain and in chromosomal regions that are depleted of Neanderthal variants. Together, these results provide avenues for deciphering the biological underpinnings of uniquely human traits.Peer reviewe

Genome-wide analyses of individual differences in quantitatively assessed reading- and language-related skills in up to 34,000 people

The use of spoken and written language is a fundamental human capacity. Individual differences in reading- and language-related skills are influenced by genetic variation, with twin-based heritability estimates of 30-80%, depending on the trait. The genetic architecture is complex, heterogeneous, and multifactorial, but investigations of contributions of single-nucleotide polymorphisms (SNPs) were thus far underpowered. We present a multicohort genome-wide association study (GWAS) of five traits assessed individually using psychometric measures: word reading, nonword reading, spelling, phoneme awareness, and nonword repetition, in samples of 13,633 to 33,959 participants aged 5-26 years. We identified genome-wide significant association with word reading (rs11208009, p=1.098 x 10-8) at a locus that has not been associated with intelligence or educational attainment. All five reading-/language-related traits showed robust SNP-heritability, accounting for 13-26% of trait variability. Genomic structural equation modelling revealed a shared genetic factor explaining most variation in word/nonword reading, spelling, and phoneme awareness, which only partially overlapped with genetic variation contributing to nonword repetition, intelligence and educational attainment. A multivariate GWAS of word/nonword reading, spelling, and phoneme awareness maximized power for follow-up investigation. Genetic correlation analysis of multivariate GWAS results with neuroimaging traits identified association with the surface area of the banks of the left superior temporal sulcus, a brain region linked to processing of spoken and written language. Heritability was enriched for genomic elements regulating gene expression in the fetal brain, and in chromosomal regions that are depleted of Neanderthal variants. Together, these results provide new avenues for deciphering the biological underpinnings of uniquely human traits

An efficient method for tensor voting using steerable filters

In many image analysis applications there is a need to extract curves in noisy images. To achieve a more robust extraction, one can exploit correlations of oriented features over a spatial context in the image. Tensor voting is an existing technique to extract features in this way. In this paper, we present a new computational scheme for tensor voting on a dense field of rank-2 tensors. Using steerable filter theory, it is possible to rewrite the tensor voting operation as a linear combination of complex-valued convolutions. This approach has computational advantages since convolutions can be implemented efficiently. We provide speed measurements to indicate the gain in speed, and illustrate the use of steerable tensor voting on medical applications

Image processing via shift-twist invariant operations on orientation bundle functions

Inspired by our own visual system we consider the construction of-and reconstruction from- an orientation bundle function (OBF) Uf : R2 ¿ S1 ¿C as a local orientation score of an image, f : R2 ¿ R, via a wavelet transform W¿ corresponding to a representation of the Euclidean motion group onto L2(R2) and oriented wavelet ¿ ¿L2(R2). This wavelet transform is a unitary mapping with stable inverse, which allows us to directly relate each operation ¿ on OBF’s to an operation ¿ on images in a robust manner. We examine the geometry of the domain of an OBF and show that the only sensible operations on OBF’s are non-linear and shift-twist invariant. As an example we consider all linear 2nd order shift-twist invariant evolution equations on OBF’s corresponding to stochastic processes on the Euclidean motion group in order to construct nonlinear shift-twist invariant operations on OBF’s. Given two such stochastic processes we derive the probability density that particles of the different processes collide. As an application we detect elongated structures in images and automatically close the gaps between them

An efficient method for tensor voting using steerable filters

In many image analysis applications there is a need to extract curves in noisy images. To achieve a more robust extraction, one can exploit correlations of oriented features over a spatial context in the image. Tensor voting is an existing technique to extract features in this way. In this paper, we present a new computational scheme for tensor voting on a dense field of rank-2 tensors. Using steerable filter theory, it is possible to rewrite the tensor voting operation as a linear combination of complex-valued convolutions. This approach has computational advantages since convolutions can be implemented efficiently. We provide speed measurements to indicate the gain in speed, and illustrate the use of steerable tensor voting on medical applications