We have developed an algorithm for genetic analysis of complex traits using genome-wide SNPs in a linear mixed model framework. Compared to current standard REML software, our method could be more than 1000 times faster. The advantage is largest when there is only a single genetic covariance structure. The method is particularly useful for multivariate analysis, including random regression models for studying reaction norms. We applied our proposed method to publicly available mice and human data and discuss advantages and limitations.

The accurate identification of low-frequency variants in tumors remains an unsolved problem. To support characterization of the issues in a realistic setting, we have developed software tools and a reference dataset for diagnosing variant calling pipelines. The dataset contains millions of variants at frequencies ranging from 0.05 to 1.0. To generate the dataset, we performed whole-genome sequencing of a mixture of two Corriel cell lines, NA19240 and NA12878, the mothers of YRI (Y) and CEU (C) HapMap trios, respectively. The cells were mixed in three different proportions, 10Y/90C, 50Y/50C and 90Y/10C, in an effort to simulate the heterogeneity found in tumor samples. We sequenced three biological replicates for each mixture, yielding approximately 1.4 billion reads per mixture for an average of 64X coverage. Using the published genotypes as our reference, we evaluate the performance of a general variant calling algorithm, constructed as a demonstration of our flexible toolset, and make comparisons to a standard GATK pipeline. We estimate the overall FDR to be 0.028 and the FNR (when coverage exceeds 20X) to be 0.019 in the 50Y/50C mixture. Interestingly, even with these relatively well studied individuals, we predict over 475,000 new variants, validating in well-behaved coding regions at a rate of 0.97, that were not included in the published genotypes.

Analysis of environmental DNA (eDNA) enables detection of specific species from water and soil samples. Typically, these analyses are performed by amplifying a short DNA sequence using species-specific primers. Alternatively, primers amplifying many species within a taxonomic group are used and amplicons are subsequently sequenced. Here, we describe a method to quickly characterize the biodiversity of a given environment by amplification of eDNA using a combination of primer pairs targeting a wide range of taxa and species identification by high-throughput sequencing. We tested this approach by analyzing 91 water samples of 40mL collected along the Cuyahoga River (Ohio, USA). We amplified eDNA extracted from each water sample using 12 primer pairs targeting mammals, fish, amphibians, birds, bryophytes, arthropods, copepods, plants and several microorganism taxa and simultaneously sequenced all PCR products by high-throughput sequencing. Despite the small sample volumes analyzed, we identified DNA sequences from 15 species of fish, 17 species of mammals, 8 species of birds, 15 species of arthropods, one turtle and one salamander. Interestingly, in addition to aquatic and semi-aquatic animal species, we identified DNA from many terrestrial species that live near the banks of the Cuyahoga River. We also identified DNA from one Asian carp species invasive to the Great Lakes but that had not been reported in the Cuyahoga River. Our study shows that analysis of eDNA extracted from a small sample of water using wide-range PCR amplification combined with massively parallel sequencing can provide a broad perspective on the biological diversity of a given environment.

In this study, we adapt a protocol for the growth of previously uncultured environmental bacterial isolates, to make it compatible with whole genome sequencing. We demonstrate that in combination with the MinION sequencing device, complete assemblies can be derived, allowing genomic comparisons to be made. This approach allows rapid, inexpensive and straightforward discovery, and genomic analysis, of previously uncultured prokaryotic genomes, and brings greater ownership of all parts of the sequencing process back to individual researchers.

Scientists have access to artifacts of evolutionary history (namely, the fossil record and genomic sequences of living organisms) but they have limited means with which to infer the exact evolutionary events that occurred to produce today s living world. An intriguing question to arise from this historical limitation is whether the evolutionary paths of organisms are dominated by internal or external controlled processes (i.e., Life as a factory) or whether they are inherently random and subject to completely different outcomes if repeated under identical conditions (i.e., Life as a casino parlor). Two experimental approaches, ancestral sequence reconstruction and experimental evolution with microorganisms, can be used to recapitulate ancient adaptive pathways and provide valuable insights into the mutational steps that constitute an organism s genetic heritage. Ancestral sequence reconstruction follows a backwards-from-present-day strategy in which various ancestral forms of a modern gene or protein are reconstructed and then studied mechanistically. Experimental evolution, by contrast, follows a forward-from-present day strategy in which microbial populations are evolved in the laboratory under defined conditions in which their evolutionary paths may be closely monitored. Here I describe a novel hybrid of these two methods, in which synthetic components constructed from inferred ancestral gene or protein sequences are placed into the genomes of modern organisms that are then experimentally evolved. Through this system, we aim to establish the comparative study of ancient phenotypes as a novel, statistically rigorous methodology with which to explore the respective impacts of biophysics and chance in evolution within the scope of the Extended Synthesis.

Beneficial mutations fuel adaptation by altering phenotypes that enhance the fit of organisms to their environment. However, the phenotypic effects of mutations often depend on ecological context, making the distribution of effects across multiple environments essential to understanding the true nature of beneficial mutations. Studies that address both the genetic basis and ecological consequences of adaptive mutations remain rare. Here, we characterize the direct and pleiotropic fitness effects of a collection of 21 first-step beneficial mutants derived from naive and adapted genotypes used in a long-term experimental evolution of Escherichia coli. Whole-genome sequencing was used to identify most beneficial mutations. In contrast to previous studies, we find diverse fitness effects of mutations selected in a simple environment and few cases of genetic parallelism. The pleiotropic effects of these mutations were predominantly positive but some mutants were highly antagonistic in alternative environments. Further, the fitness effects of mutations derived from the adapted genotypes were dramatically reduced in nearly all environments. These findings suggest that many beneficial variants are accessible from a single point on the fitness landscape, and the fixation of alternative beneficial mutations may have dramatic consequences for niche breadth reduction via metabolic erosion.

For the past 15 years, the UCSC Genome Browser (http://genome.ucsc.edu/) has served the international research community by offering an integrated platform for viewing and analyzing information from a large database of genome assemblies and their associated annotations. The UCSC Genome Browser has been under continuous development since its inception with new data sets and software features added frequently. Some release highlights of this year include new and updated genome browsers for various assemblies, including bonobo and zebrafish; new gene annotation sets; improvements to track and assembly hub support; and a new interactive tool, the “Data Integrator”, for intersecting data from multiple tracks. We have greatly expanded the data sets available on the most recent human assembly, hg38/GRCh38, to include updated gene prediction sets from GENCODE, more phenotype- and disease-associated variants from ClinVar and ClinGen, more genomic regulatory data, and a new multiple genome alignment.

Animals and plants have evolved a range of mechanisms for recognizing noxious substances and organisms. A particular challenge, most successfully met by the adaptive immune system in vertebrates, is the specific recognition of potential pathogens, which themselves evolve to escape recognition. A variety of genomic and evolutionary mechanisms shape large families of proteins dedicated to detecting pathogens and create the diversity of binding sites needed for epitope recognition. One family involved in innate immunity are the NACHT-domain-and Leucine-Rich-Repeat-containing (NLR) proteins. Mammals have a small number of NLR proteins, which are involved in first-line immune defense and recognize several conserved molecular patterns. However, there is no evidence that they cover a wider spectrum of differential pathogenic epitopes. In other species, mostly those without adaptive immune systems, NLRs have expanded into very large families. A family of nearly 400 NLR proteins is encoded in the zebrafish genome. They are subdivided into four groups defined by their NACHT and effector domains, with a characteristic overall structure that arose in fishes from a fusion of the NLR domains with a domain used for immune recognition, the B30.2 domain. The majority of the genes are located on one chromosome arm, interspersed with other large multi-gene families, including a new family encoding proteins with multiple tandem arrays of Zinc fingers. This chromosome arm may be a hot spot for evolutionary change in the zebrafish genome. NLR genes not on this chromosome tend to be located near chromosomal ends. Extensive duplication, loss of genes and domains, exon shuffling and gene conversion acting differentially on the NACHT and B30.2 domains have shaped the family. Its four groups, which are conserved across the fishes, are homogenised within each group by gene conversion, while the B30.2 domain is subject to gene conversion across the groups. Evidence of positive selection on diversifying mutations in the B30.2 domain, probably driven by pathogen interactions, indicates that this domain rather than the LRRs acts as a recognition domain. The NLR-B30.2 proteins represent a new family with diversity in the specific recognition module that is present in fishes in spite of the parallel existence of an adaptive immune system.