A vision for ubiquitous sequencing

A vision for ubiquitous sequencing
Yaniv Erlich
doi: http://dx.doi.org/10.1101/019018

Genomics has recently celebrated reaching the \$1000 genome milestone, making affordable DNA sequencing a reality. This goal of the sequencing revolution has been successfully completed. Looking forward, the next goal of the revolution can be ushered in by the advent of sequencing sensors – miniaturized sequencing devices that are manufactured for real time applications and deployed in large quantities at low costs. The first part of this manuscript envisions applications that will benefit from moving the sequencers to the samples in a range of domains. In the second part, the manuscript outlines the critical barriers that need to be addressed in order to reach the goal of ubiquitous sequencing sensors.

Rail-RNA: Scalable analysis of RNA-seq splicing and coverage

Rail-RNA: Scalable analysis of RNA-seq splicing and coverage
Abhinav Nellore , Leonardo Collado-Torres , Andrew E Jaffe , James Morton , Jacob Pritt , José Alquicira-Hernández , Jeffrey T Leek , Ben Langmead
doi: http://dx.doi.org/10.1101/019067

RNA sequencing (RNA-seq) experiments now span hundreds to thousands of samples. A source of frustration for investigators analyzing a given dataset is the inability to rapidly and reproducibly align its samples jointly. Current spliced alignment software is designed to analyze each sample separately. Consequently, no information is gained from analyzing multiple samples together, and it is difficult to reproduce the exact analysis without access to original computing resources. We describe Rail-RNA, a cloud-enabled spliced aligner that analyzes many samples at once. Rail-RNA eliminates redundant work across samples, making it more efficient as samples are added. For many samples, Rail-RNA is more accurate than annotation-assisted aligners. We use Rail-RNA to align 666 RNA-seq samples from the GEUVADIS project on Amazon Web Services in 12 hours for US$0.69 per sample. Rail-RNA produces alignments and base-resolution bigWig coverage files, ready for use with downstream packages for reproducible statistical analysis. We identify 290,416 expressed regions in the GEUVADIS samples, including 21,224 that map to intergenic sequence. We show that these regions show consistent patterns of variation across populations and with respect to known technological confounders. We identify expressed regions in the GEUVADIS samples and show that both annotated and unannotated (novel) expressed regions exhibit consistent patterns of variation across populations and with respect to known confounders. Rail-RNA is open-source software available at http://rail.bio .

Bayesian Inference of Divergence Times and Feeding Evolution in Grey Mullets (Mugilidae)

Bayesian Inference of Divergence Times and Feeding Evolution in Grey Mullets (Mugilidae)
Francesco Santini , Michael R. May , Giorgio Carnevale , Brian R. Moore
doi: http://dx.doi.org/10.1101/019075

Grey mullets (Mugilidae, Ovalentariae) are coastal fishes found in near-shore environments of tropical, subtropical, and temperate regions within marine, brackish, and freshwater habitats throughout the world. This group is noteworthy both for the highly conserved morphology of its members—which complicates species identification and delimitation—and also for the uncommon herbivorous or detritivorous diet of most mullets. In this study, we first attempt to identify the number of mullet species, and then—for the resulting species—estimate a densely sampled time-calibrated phylogeny using three mitochondrial gene regions and three fossil calibrations. Our results identify two major subgroups of mullets that diverged in the Paleocene/Early Eocene, followed by an Eocene/Oligocene radiation across both tropical and subtropical habitats. We use this phylogeny to explore the evolution of feeding preference in mullets, which indicates multiple independent origins of both herbivorous and detritivorous diets within this group. We also explore correlations between feeding preference and other variables, including body size, habitat (marine, brackish, or freshwater), and geographic distribution (tropical, subtropical, or temperate). Our analyses reveal: (1) a positive correlation between trophic index and habitat (with herbivorous and/or detritivorous species predominantly occurring in marine habitats); (2) a negative correlation between trophic index and geographic distribution (with herbivorous species occurring predominantly in subtropical and temperate regions), and; (3) a negative correlation between body size and geographic distribution (with larger species occurring predominantly in subtropical and temperate regions).

GWGGI: software for genome-wide gene-gene interaction analysis

GWGGI: software for genome-wide gene-gene interaction analysis
Changshuai Wei, Qing Lu
Journal-ref: BMC Genetics 2014, 15:101
Subjects: Quantitative Methods (q-bio.QM); Data Structures and Algorithms (cs.DS); Genomics (q-bio.GN); Applications (stat.AP)

Background: While the importance of gene-gene interactions in human diseases has been well recognized, identifying them has been a great challenge, especially through association studies with millions of genetic markers and thousands of individuals. Computationally efficient and powerful tools are in great need for the identification of new gene-gene interactions in high-dimensional association studies. Result: We develop C++ software for genome-wide gene-gene interaction analyses (GWGGI). GWGGI utilizes tree-based algorithms to search a large number of genetic markers for a disease-associated joint association with the consideration of high-order interactions, and then uses non-parametric statistics to test the joint association. The package includes two functions, likelihood ratio Mann-whitney (LRMW) and Tree Assembling Mann-whitney (TAMW).We optimize the data storage and computational efficiency of the software, making it feasible to run the genome-wide analysis on a personal computer. The use of GWGGI was demonstrated by using two real data-sets with nearly 500 k genetic markers. Conclusion: Through the empirical study, we demonstrated that the genome-wide gene-gene interaction analysis using GWGGI could be accomplished within a reasonable time on a personal computer (i.e., ~3.5 hours for LRMW and ~10 hours for TAMW). We also showed that LRMW was suitable to detect interaction among a small number of genetic variants with moderate-to-strong marginal effect, while TAMW was useful to detect interaction among a larger number of low-marginal-effect genetic variants.

Trees Assembling Mann Whitney Approach for Detecting Genome-wide Joint Association among Low Marginal Effect loci

Trees Assembling Mann Whitney Approach for Detecting Genome-wide Joint Association among Low Marginal Effect loci
Changshuai Wei, Daniel J. Schaid, Qing Lu
Journal-ref: Genet Epidemiol. 2013 Jan;37(1):84-91
Subjects: Quantitative Methods (q-bio.QM); Computation (stat.CO); Machine Learning (stat.ML)

Common complex diseases are likely influenced by the interplay of hundreds, or even thousands, of genetic variants. Converging evidence shows that genetic variants with low marginal effects (LME) play an important role in disease development. Despite their potential significance, discovering LME genetic variants and assessing their joint association on high dimensional data (e.g., genome wide association studies) remain a great challenge. To facilitate joint association analysis among a large ensemble of LME genetic variants, we proposed a computationally efficient and powerful approach, which we call Trees Assembling Mann whitney (TAMW). Through simulation studies and an empirical data application, we found that TAMW outperformed multifactor dimensionality reduction (MDR) and the likelihood ratio based Mann whitney approach (LRMW) when the underlying complex disease involves multiple LME loci and their interactions. For instance, in a simulation with 20 interacting LME loci, TAMW attained a higher power (power=0.931) than both MDR (power=0.599) and LRMW (power=0.704). In an empirical study of 29 known Crohn’s disease (CD) loci, TAMW also identified a stronger joint association with CD than those detected by MDR and LRMW. Finally, we applied TAMW to Wellcome Trust CD GWAS to conduct a genome wide analysis. The analysis of 459K single nucleotide polymorphisms was completed in 40 hours using parallel computing, and revealed a joint association predisposing to CD (p-value=2.763e-19). Further analysis of the newly discovered association suggested that 13 genes, such as ATG16L1 and LACC1, may play an important role in CD pathophysiological and etiological processes.

Reconstructing A/B compartments as revealed by Hi-C using long-range correlations in epigenetic data

Reconstructing A/B compartments as revealed by Hi-C using long-range correlations in epigenetic data
Jean-Philippe Fortin , Kasper D Hansen
doi: http://dx.doi.org/10.1101/019000

Analysis of Hi-C data has shown that the genome can be divided into two compartments called A/B compartments. These compartments are cell-type specific and are associated with open and closed chromatin. We show that A/B compartments can be reliably estimated using epigenetic data from two different platforms, the Illumina 450k DNA methylation microarray and DNase hypersensitivity sequencing. We do this by exploiting the fact that the structure of long range correlations differs between open and closed compartments. This work makes A/B compartments readily available in a wide variety of cell types, including many human cancers.

Negative Niche Construction Favors the Evolution of Cooperation

Negative Niche Construction Favors the Evolution of Cooperation
Brian D Connelly , Katherine J Dickinson , Sarah P Hammarlund , Benjamin Kerr
doi: http://dx.doi.org/10.1101/018994

By benefitting others at a cost to themselves, cooperators face an ever present threat from defectors—individuals that avail themselves of the cooperative benefit without contributing. A longstanding challenge to evolutionary biology is to understand the mechanisms that support the many instances of cooperation that nevertheless exist. Hammarlund et al. recently demonstrated that cooperation can persist by hitchhiking along with beneficial non-social adaptations. Importantly, cooperators play an active role in this process. In spatially-structured environments, clustered cooperator populations reach greater densities, which creates more mutational opportunities to gain beneficial non-social adaptations. Cooperation rises in abundance by association with these adaptations. However, once adaptive opportunities have been exhausted, the ride abruptly ends as cooperators are displaced by adapted defectors. Using an agent-based model, we demonstrate that the selective feedback that is created as populations construct their local niches can maintain cooperation indefinitely. This cooperator success depends specifically on negative niche construction, which acts as a perpetual source of adaptive opportunities. As populations adapt, they alter their environment in ways that reveal additional opportunities for adaptation. Despite being independent of niche construction in our model, cooperation feeds this cycle. By reaching larger densities, populations of cooperators are better able to adapt to changes in their constructed niche and successfully respond to the constant threat posed by defectors. We relate these findings to previous studies from the niche construction literature and discuss how this model could be extended to provide a greater understanding of how cooperation evolves in the complex environments in which it is found.

Sequencing of 15,622 gene-bearing BACs reveals new features of the barley genome

Sequencing of 15,622 gene-bearing BACs reveals new features of the barley genome
María Muñoz-Amatriaín , Stefano Lonardi , MingCheng Luo , Kavitha Madishetty , Jan Svensson , Matthew Moscou , Steve Wanamaker , Tao Jiang , Andris Kleinhofs , Gary Muehlbauer , Roger Wise , Nils Stein , Yaqin Ma , Edmundo Rodriguez , Dave Kudrna , Prasanna R Bhat , Shiaoman Chao , Pascal Condamine , Shane Heinen , Josh Resnik , Rod Wing , Heather N Witt , Matthew Alpert , Marco Beccuti , Serdar Bozdag , Francesca Cordero , Hamid Mirebrahim , Rachid Ounit , Yonghui Wu , Frank You , Jie Zheng , Hana Šimková , Jaroslav Doležel , Jane Grimwood , Jeremy Schmutz , Denisa Duma , Lothar Altschmied , Tom Blake , Phil Bregitzer , Laurel Cooper , Muharrem Dilbirligi , Anders Falk , Leila Feiz , Andreas Graner , Perry Gustafson , Patrick Hayes , Peggy Lemaux , Jafar Mammadov , Timothy Close
doi: http://dx.doi.org/10.1101/018978

Barley (Hordeum vulgare L.) possesses a large and highly repetitive genome of 5.1 Gb that has hindered the development of a complete sequence. In 2012, the International Barley Sequencing Consortium released a resource integrating whole-genome shotgun sequences with a physical and genetic framework. However, since only 6,278 BACs in the physical map were sequenced, detailed fine structure was limited. To gain access to the gene-containing portion of the barley genome at high resolution, we identified and sequenced 15,622 BACs representing the minimal tiling path of 72,052 physical mapped gene-bearing BACs. This generated about 1.7 Gb of genomic sequence containing 17,386 annotated barley genes. Exploration of the sequenced BACs revealed that although distal ends of chromosomes contain most of the gene-enriched BACs and are characterized by high rates of recombination, there are also gene-dense regions with suppressed recombination. Knowledge of these deviant regions is relevant to trait introgression, genome-wide association studies, genomic selection model development and map-based cloning strategies. Sequences and their gene and SNP annotations can be accessed and exported via http://harvest-web.org/hweb/utilmenu.wc or through the software HarvEST:Barley (download from harvest.ucr.edu). In the latter, we have implemented a synteny viewer between barley and Aegilops tauschii to aid in comparative genome analysis.

A Chronological Atlas of Natural Selection in the Human Genome during the Past Half-million Years

A Chronological Atlas of Natural Selection in the Human Genome during the Past Half-million Years
Hang Zhou , Sile Hu , Rostislav Matveev , Qianhui Yu , Jing Li , Philipp Khaitovich , Li Jin , Michael Lachmann , Mark Stoneking , Qiaomei Fu , Kun Tang
doi: http://dx.doi.org/10.1101/018929

The spatiotemporal distribution of recent human adaptation is a long standing question. We developed a new coalescent-based method that collectively assigned human genome regions to modes of neutrality or to positive, negative, or balancing selection. Most importantly, the selection times were estimated for all positive selection signals, which ranged over the last half million years, penetrating the emergence of anatomically modern human (AMH). These selection time estimates were further supported by analyses of the genome sequences from three ancient AMHs and the Neanderthals. A series of brain function-related genes were found to carry signals of ancient selective sweeps, which may have defined the evolution of cognitive abilities either before Neanderthal divergence or during the emergence of AMH. Particularly, signals of brain evolution in AMH are strongly related to Alzheimer’s disease pathways. In conclusion, this study reports a chronological atlas of natural selection in Human.

Theoretical consequences of the Mutagenic Chain Reaction for manipulating natural populations

Theoretical consequences of the Mutagenic Chain Reaction for manipulating natural populations
Robert Unckless , Philipp Messer , Andrew Clark
doi: http://dx.doi.org/10.1101/018986

The use of recombinant genetic technologies for population manipulation has mostly remained an abstract idea due to the lack of a suitable means to drive novel gene constructs to high frequency in populations. Recently Gantz and Bier showed that the use of CRISPR/Cas9 technology could provide an artificial drive mechanism, the so-called Mutagenic Chain Reaction (MCR), which could lead to rapid fixation of even a deleterious introduced allele. We establish the equivalence of this system to models of meiotic drive and review the results of simple models showing that, when there is a fitness cost to the MCR allele, an internal equilibrium exists that is usually unstable. Introductions must be at a frequency above this critical point for the successful invasion of the MCR allele. These modeling results have important implications for application of MCR in natural populations.