Maize is an important crop species of high genetic diversity. We identified and genotyped several million sequence polymorphisms among 27 diverse maize inbred lines and discovered that the genome was characterized by highly divergent haplotypes and showed 10- to 30-fold variation in recombination rates. Most chromosomes have pericentromeric regions with highly suppressed recombination that appear to have influenced the effectiveness of selection during maize inbred development and may be a major component of heterosis. We found hundreds of selective sweeps and highly differentiated regions that probably contain loci that are key to geographic adaptation. This survey of genetic diversity provides a foundation for uniting breeding efforts across the world and for dissecting complex traits through genome-wide association studies.
Rapid progress in comparative genomics among the grasses has revealed similar gene content and order despite exceptional differences in chromosome size and number. Large- and small-scale genomic variations are of particular interest, especially among cultivated and wild species, as they encode rapidly evolving features that may be important in adaptation to particular environments. We present a genome-wide study of intermediate-sized structural variation (SV) among rice (Oryza sativa) and three of its closest relatives in the genus Oryza (Oryza nivara, Oryza rufipogon and Oryza glaberrima). We computationally identified regional expansions, contractions and inversions in the Oryza species genomes relative to O. sativa by combining data from paired-end clone alignments to the O. sativa reference genome and physical maps. A subset of the computational predictions was validated using a new approach for BAC size determination. The result was a confirmed catalog of 674 expansions (25-38 Mb) and 611 (4-19 Mb) contractions, and 140 putative inversions (14-19 Mb) between the three Oryza species and O. sativa. In the expanded regions unique to O. sativa we found enrichment in transposable elements (TEs): long terminal repeats (LTRs) were randomly located across the chromosomes, and their insertion times corresponded to the date of the A genome radiation. Also, rice-expanded regions contained an over-representation of single-copy genes related to defense factors in the environment. This catalog of confirmed SV in reference to O. sativa provides an entry point for future research in genome evolution, speciation, domestication and novel gene discovery.
Metagenomics promises insight into uncultured microbes across space and time. Yet, the tsunami of low-cost sequencing meant to enable these discoveries is leaving scientists drowning in data. We present Libra, a comparative metagenomics algorithm, that considers genetic distance and microbial abundance simultaneously using a vector-space model, and scales using Apache Hadoop. We compare Libra to other tools to examine effects of data reduction and distance metrics using simulated metagenomes, controlled bacterial mixtures, and metagenomes from the Human Microbiome Project and Tara Oceans Expedition. We show that Libra provides accurate, efficient, and scalable compute for discerning global patterns in microbial ecology.
Bacteriophages play an important role in host-driven biological processes by controlling bacterial population size, horizontally transferring genes between hosts and expressing host-derived genes to alter host metabolism. Metagenomics provides the genetic basis for understanding the interplay between uncultured bacteria, their phage and the environment. In particular, viral metagenomes (viromes) are providing new insight into phage-encoded host genes (i.e. auxiliary metabolic genes; AMGs) that reprogram host metabolism during infection. Yet, despite deep sequencing efforts of viral communities, the majority of sequences have no match to known proteins. Reference-independent computational techniques, such as protein clustering, contig spectra and ecological profiling are overcoming these barriers to examine both the known and unknown components of viromes. As the field of viral metagenomics progresses, a critical assessment of tools is required as the majority of algorithms have been developed for analyzing bacteria. The aim of this paper is to offer an overview of current computational methodologies for virome analysis and to provide an example of reference-independent approaches using human skin viromes. Additionally, we present methods to carefully validate AMGs from host contamination. Despite computational challenges, these new methods offer novel insights into the diversity and functional roles of phages in diverse environments.