Meiotic recombination rates vary across the genome, often involving localized crossover hotspots and coldspots. Studying the molecular basis and mechanisms underlying this variation has been ...challenging due to the high cost and effort required to construct individualized genome-wide maps of recombination crossovers. Here we introduce a new method, called ReMIX, to detect crossovers from gamete DNA of a single individual using Illumina sequencing of 10X Genomics linked-read libraries. ReMIX reconstructs haplotypes and identifies the valuable rare molecules spanning crossover breakpoints, allowing quantification of the genomic location and intensity of meiotic recombination. Using a single mouse and stickleback fish, we demonstrate how ReMIX faithfully recovers recombination hotspots and landscapes that have previously been built using hundreds of offspring. ReMIX provides a high-resolution, high-throughput, and low-cost approach to quantify recombination variation across the genome, providing an exciting opportunity to study recombination among multiple individuals in diverse organisms.
Correlation metrics are widely utilized in genomics analysis and often implemented with little regard to assumptions of normality, homoscedasticity, and independence of values. This is especially ...true when comparing values between replicated sequencing experiments that probe chromatin accessibility, such as assays for transposase-accessible chromatin via sequencing (ATAC-seq). Such data can possess several regions across the human genome with little to no sequencing depth and are thus non-normal with a large portion of zero values. Despite distributed use in the epigenomics field, few studies have evaluated and benchmarked how correlation and association statistics behave across ATAC-seq experiments with known differences or the effects of removing specific outliers from the data. Here, we developed a computational simulation of ATAC-seq data to elucidate the behavior of correlation statistics and to compare their accuracy under set conditions of reproducibility. Using these simulations, we monitored the behavior of several correlation statistics, including the Pearson's R and Spearman's formula omitted coefficients as well as Kendall's formula omitted and Top-Down correlation. We also test the behavior of association measures, including the coefficient of determination Rformula omitted, Kendall's W, and normalized mutual information. Our experiments reveal an insensitivity of most statistics, including Spearman's formula omitted, Kendall's formula omitted, and Kendall's W, to increasing differences between simulated ATAC-seq replicates. The removal of co-zeros (regions lacking mapped sequenced reads) between simulated experiments greatly improves the estimates of correlation and association. After removing co-zeros, the Rformula omitted coefficient and normalized mutual information display the best performance, having a closer one-to-one relationship with the known portion of shared, enhanced loci between simulated replicates. When comparing values between experimental ATAC-seq data using a random forest model, mutual information best predicts ATAC-seq replicate relationships. Collectively, this study demonstrates how measures of correlation and association can behave in epigenomics experiments. We provide improved strategies for quantifying relationships in these increasingly prevalent and important chromatin accessibility assays.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract The genome folds into complex configurations and structures thought to profoundly impact its function. The intricacies of this dynamic structure-function relationship are not well understood ...particularly in the context of viral infection. To unravel this interplay, here we provide a comprehensive investigation of simultaneous host chromatin structural (via Hi-C and ATAC-seq) and functional changes (via RNA-seq) in response to vaccinia virus infection. Over time, infection significantly impacts global and local chromatin structure by increasing long-range intra-chromosomal interactions and B compartmentalization and by decreasing chromatin accessibility and inter-chromosomal interactions. Local accessibility changes are independent of broad-scale chromatin compartment exchange (~12% of the genome), underscoring potential independent mechanisms for global and local chromatin reorganization. While infection structurally condenses the host genome, there is nearly equal bidirectional differential gene expression. Despite global weakening of intra-TAD interactions, functional changes including downregulated immunity genes are associated with alterations in local accessibility and loop domain restructuring. Therefore, chromatin accessibility and local structure profiling provide impactful predictions for host responses and may improve development of efficacious anti-viral counter measures including the optimization of vaccine design.