Biology subjects

Song, Y. S.

Publications and source records attributed to Song, Y. S..

60 records · Page 4Linked to original sources

bioRxiv2017

Three-way clustering of multi-tissue multi-individual gene expression data using constrained tensor decomposition

The advent of next generation sequencing methods has led to an increasing availability of large, multi-tissue datasets which contain gene expression measurements across different tissues and individuals. In this setting, variation in expression levels arises due to contributions specific to genes, tissues, individuals, and interactions thereof. Classical clustering methods are illsuited to explore these three-way interactions, and struggle to fully extract the insights into transcriptome complexity and regulation contained in the data. Thus, to exploit the multi-mode structure of the data, new methods are required. To this end, we propose a new method, called MultiCluster, based on constrained tensor decomposition which permits the investigation of transcriptome variation across individuals and tissues simultaneously. Through simulation and application to the GTEx RNA-seq data, we show that our tensor decomposition identifies three-way clusters with higher accuracy, while being 11x faster, than the competing Bayesian method. For several age-, race-, or gender-related genes, the tensor projection approach achieves increased significance over single-tissue analysis by two orders of magnitude. Our analysis finds gene modules consistent with existing knowledge while further detecting novel candidate genes exhibiting either tissue-, individual-, or tissue-by-individual specificity. These identified genes and gene modules offer bases for future study, and the uncovered multi-way specificities provide a finer, more nuanced snapshot of transcriptome variation than previously possible.

genomics↗

bioRxiv2017

Model-based detection and analysis of introgressed Neanderthal ancestry in modern humans

Genetic evidence has revealed that the ancestors of modern human populations outside of Africa and their hominin sister groups, notably the Neanderthals, exchanged genetic material in the past. The distribution of these introgressed sequence-tracts along modern-day human genomes provides insight into the ancient structure and migration patterns of these archaic populations. Furthermore, it facilitates studying the selective processes that lead to the accumulation or depletion of introgressed genetic variation. Recent studies have developed methods to localize these introgressed regions, reporting long regions that are depleted of Neanderthal introgression and enriched in genes, suggesting negative selection against the Neanderthal variants. On the other hand, enriched Neanderthal ancestry in hair- and skin-related genes suggests that some introgressed variants facilitated adaptation to new environments. Here, we present a model-based method called diCal-admix and apply it to detect tracts of Neanderthal introgression in modern humans. We demonstrate its efficiency and accuracy through extensive simulations. We use our method to detect introgressed regions in modern human individuals from the 1000 Genomes Project, using a high coverage genome from a Neanderthal individual from the Altai mountains as reference. Our introgression detection results and findings concerning their functional implications are largely concordant with previous studies, and are consistent with weak selection against Neanderthal ancestry. We find some evidence that selection against Neanderthal ancestry was due to higher genetic load in Neanderthals, resulting from small effective population size, rather than Dobzhansky-Muller incompatibilities. Finally, we investigate the role of the X-chromosome in the divergence between Neanderthals and modern humans.

evolutionary biology↗

bioRxiv2017

Worldwide genetic variation of the IGHV and TRBV immune receptor gene families in humans

The immunoglobulin heavy variable (IGHV) and T cell beta variable (TRBV) loci are among the most complex and variable regions in the human genome. Generated through a process of gene duplication/deletion and diversification, these loci can vary extensively between individuals in copy number and contain genes that are highly similar, making their analysis technically challenging. Here, we present a comprehensive study of the functional gene segments in the IGHV and TRBV loci, quantifying their copy number and single nucleotide variation in a globally diverse sample of 109 (IGHV) and 286 (TRBV) humans from over a hundred populations. We find that the IGHV and TRBV gene families exhibit starkly different patterns of variation. In particular, with hundreds of copy number haplotypes (instances that have differences in the number of functional gene segments), the IGHV locus has undergone more frequent gene duplication/deletion compared to the TRBV locus, which has only a few copy number haplotypes. In contrast, the TRBV locus has a greater or at least equal propensity to mutate, as evidenced by greater single nucleotide variation, compared to the IGHV locus. Thus, despite common molecular and functional characteristics, the genes that comprise the IGHV and TRBV loci have evolved in strikingly different ways. As well as providing insight into the different evolutionary paths the IGHV and TRBV loci have taken, our results are also important to the adaptive immune repertoire sequencing community, where the lack of frequencies of common alleles and copy number variants is hampering existing analytical pipelines.

genomics↗

bioRxiv2017

Theoretical quantification of interference in the TASEP: Application to mRNA translation shows near-optimality of termination rates

The Totally Asymmetric Exclusion Process (TASEP) is a classical stochastic model for describing the transport of interacting particles, such as ribosomes moving along the mRNA during translation. Although this model has been widely studied in the past, the extent of collision between particles and the average distance between a particle to its nearest neighbor have not been quantified explicitly. We provide here a theoretical analysis of such quantities via the distribution of isolated particles. In the classical form of the model in which each particle occupies only a single site, we obtain an exact analytic solution using the Matrix Ansatz. We then employ a refined mean field approach to extend the analysis to a generalized TASEP with particles of an arbitrary size. Our theoretical study has direct applications in mRNA translation and the interpretation of experimental ribosome profiling data. In particular, our analysis of data from S. cerevisiae suggests a potential bias against the detection of nearby ribosomes with gap distance less than ~ 3 codons, which leads to some ambiguity in estimating the initiation rate and protein production flux for a substantial fraction of genes. Despite such ambiguity, however, we demonstrate theoretically that the interference rate associated with collisions can be robustly estimated, and show that approximately 1% of the translating ribosomes get obstructed.

systems biology↗

bioRxiv2016

Identification and quantitative analysis of the major determinants of translation elongation rate variation

Previous studies have shown that translation elongation is regulated by multiple factors, but the observed heterogeneity remains only partially explained. To dissect quantitatively the different determinants of elongation speed, we use probabilistic modeling to estimate initiation and local elongation rates from ribosome profiling data. This model-based approach allows us to quantify the extent of interference between ribosomes on the same transcript. We show that neither interference nor the distribution of slow codons is sufficient to explain the observed heterogeneity. Instead, we find that electrostatic interactions between the ribosomal exit tunnel and specific parts of the nascent polypeptide govern the elongation rate variation as the polypeptide makes its initial pass through the tunnel. Once the N-terminus has escaped the tunnel, the hydropathy of the nascent polypeptide within the ribosome plays a major role in modulating the speed. We show that our results are consistent with the biophysical properties of the tunnel.

genomics↗

bioRxiv2016

Time-resolved proteomics vs. ribosome profiling reveals translation dynamics under stress

Many small molecule chemotherapeutics induce stresses that globally inhibit mRNA translation, remodeling the cancer proteome and governing response to treatment. Here we measured protein synthesis in multiple myeloma cells treated with low-dose bortezomib by coupling pulsed-SILAC (pSILAC) with high-accuracy targeted quantitative proteomics. We found that direct measurement of protein synthesis by pSILAC correlated well with the indirect measurement of protein synthesis by ribosome profiling under conditions of robust translation. By developing a statistical model integrating longitudinal proteomic and mRNA-seq measurements, we found that proteomics could directly detect global alterations in translational rate as a function of therapy-induced stress after prolonged bortezomib exposure. Finally, the model we develop here, in combination with our experimental data including both protein synthesis and degradation, predicts changes in proteome remodeling under a variety of cellular perturbations. pSILAC therefore provides an important complement to ribosome profiling in directly measuring proteome dynamics under conditions of cellular stress.

cancer biology↗