Reed A. Cartwright

Comparative population genomics of maize domestication and improvement

Domestication and plant breeding are ongoing 10,000-year-old evolutionary experiments that have radically altered wild species to meet human needs. Maize has undergone a particularly striking transformation. Researchers have sought for decades to identify the genes underlying maize evolution, but these efforts have been limited in scope. Here, we report a comprehensive assessment of the evolution of modern maize based on the genome-wide resequencing of 75 wild, landrace and improved maize lines. We find evidence of recovery of diversity after domestication, likely introgression from wild relatives, and evidence for stronger selection during domestication than improvement. We identify a number of genes with stronger signals of selection than those previously shown to underlie major morphological changes. Finally, through transcriptome-wide analysis of gene expression, we find evidence both consistent with removal of cis-acting variation during maize domestication and improvement and suggestive of modern breeding having increased dominance in expression while targeting highly expressed genes.

Variation in genome-wide mutation rates within and between human families.

J.B.S. Haldane proposed in 1947 that the male germline may be more mutagenic than the female germline. Diverse studies have supported Haldanes contention of a higher average mutation rate in the male germline in a variety of mammals, including humans. Here we present, to our knowledge, the first direct comparative analysis of male and female germline mutation rates from the complete genome sequences of two parent-offspring trios. Through extensive validation, we identified 49 and 35 germline de novo mutations (DNMs) in two trio offspring, as well as 1,586 non-germline DNMs arising either somatically or in the cell lines from which the DNA was derived. Most strikingly, in one family, we observed that 92% of germline DNMs were from the paternal germline, whereas, in contrast, in the other family, 64% of DNMs were from the maternal germline. These observations suggest considerable variation in mutation rates within and between families.

DNA assembly with gaps (Dawg): simulating sequence evolution

MOTIVATION Relationships amongst taxa are inferred from biological data using phylogenetic methods and procedures. Very few known phylogenies exist against which to test the accuracy of our inferences. Therefore, in the absence of biological data, simulated data must be used to test the accuracy of methods which produce these inferences. Researchers have limited or non-existent options for simulations useful for studying the impact of insertions, deletions, and alignments on phylogenetic accuracy. RESULTS To satisfy this gap I have developed a new algorithm of indel formation and incorporated it into a new, flexible, and portable application for sequence simulation. The application, called Dawg, simulates phylogenetic evolution of DNA sequences in continuous time using the robust general time reversible model with gamma and invariant rate heterogeneity and a novel length-dependent model of indel formation. On completion, Dawg produces the true alignment of the simulated sequences. Unlike other applications, Dawg allows indel lengths to be explicitly distributed via a biologically realistic power law. Many options are available to allow users to customize their simulations and results. Because simulating with indels would be problematic if biologically realistic parameters could not be estimated, a script is provided with Dawg that can estimate the parameters of indel formation from sequence data. Dawg was applied to the sequences of four chloroplast trnK introns. It was used to parametrically bootstrap an estimation of the rate of indel formation for the phylogeny. Because Dawg can assist in parametric bootstrapping of sequence data it is useful beyond phylogenetics, such as studying alignment algorithms or parameters of molecular evolution. AVAILABILITY Dawg 1.0.0 can be obtained at the following websites: http://www.genetics.uga.edu/sw/ or http://scit.us/dawg/. The package includes source code, example files, a brief manual and helper scripts. Binary distributions are available for Windows and Macintosh OS X. A development page for Dawg exists at http://scit.us/dawg/, with links to a Subversion repository, mailing lists and updated versions.

The khmer software package: enabling efficient nucleotide sequence analysis

The khmer package is a freely available software library for working efficiently with fixed length DNA words, or k-mers. khmer provides implementations of a probabilistic k-mer counting data structure, a compressible De Bruijn graph representation, De Bruijn graph partitioning, and digital normalization. khmer is implemented in C++ and Python, and is freely available under the BSD license at https://github.com/dib-lab/khmer/.

DeNovoGear: de novo indel and point mutation discovery and phasing

We present DeNovoGear software for analyzing de novo mutations from familial and somatic tissue sequencing data. DeNovoGear uses likelihood-based error modeling to reduce the false positive rate of mutation discovery in exome analysis and fragment information to identify the parental origin of germ-line mutations. We used DeNovoGear on human whole-genome sequencing data to produce a set of predicted de novo insertion and/or deletion (indel) mutations with a 95% validation rate.

Problems and Solutions for Estimating Indel Rates and Length Distributions

Insertions and deletions (indels) are fundamental but understudied components of molecular evolution. Here we present an expectation-maximization algorithm built on a pair hidden Markov model that is able to properly handle indels in neutrally evolving DNA sequences. From a data set of orthologous introns, we estimate relative rates and length distributions of indels among primates and rodents. This technique has the advantage of potentially handling large genomic data sets. We find that a zeta power-law model of indel lengths provides a much better fit than the traditional geometric model and that indel processes are conserved between our taxa. The estimated relative rates are about 12-16 indels per 100 substitutions, and the estimated power-law magnitudes are about 1.6-1.7. More significantly, we find that using the traditional geometric/affine model of indel lengths introduces artifacts into evolutionary analysis, casting doubt on studies of the evolution and diversity of indel formation using traditional models and invalidating measures of species divergence that include indel lengths.

Logarithmic gap costs decrease alignment accuracy

BackgroundStudies on the distribution of indel sizes have consistently found that they obey a power law. This finding has lead several scientists to propose that logarithmic gap costs, G (k) = a + c ln k, are more biologically realistic than affine gap costs, G (k) = a + bk, for sequence alignment. Since quick and efficient affine costs are currently the most popular way to globally align sequences, the goal of this paper is to determine whether logarithmic gap costs improve alignment accuracy significantly enough the merit their use over the faster affine gap costs.ResultsA group of simulated sequences pairs were globally aligned using affine, logarithmic, and log-affine gap costs. Alignment accuracy was calculated by comparing resulting alignments to actual alignments of the sequence pairs. Gap costs were then compared based on average alignment accuracy. Log-affine gap costs had the best accuracy, followed closely by affine gap costs, while logarithmic gap costs performed poorly. Subsequently a model was developed to explain the results.ConclusionIn contrast to initial expectations, logarithmic gap costs produce poor alignments and are actually not implied by the power-law behavior of gap sizes, given typical match and mismatch costs. Furthermore, affine gap costs not only produce accurate alignments but are also good approximations to biologically realistic gap costs. This work provides added confidence for the biological relevance of existing alignment algorithms.

A Toxic Mutator and Selection Alternative to the Non-Mendelian RNA Cache Hypothesis for hothead Reversion

Lolle and colleagues observed frequent true reversion of hothead ( hth ) mutations of Arabidopsis thaliana , whereby up to 10% of the progeny of self-pollinated homozygous hth/hth mutants carried a grandparental HTH allele ([Lolle et al., 2005][1]). Instability was not limited to the HTH gene: hth

Phylogenomic reconstruction supports supercontinent origins for Leishmania.

Leishmania, a genus of parasites transmitted to human hosts and mammalian/reptilian reservoirs by an insect vector, is the causative agent of the human disease complex leishmaniasis. The evolutionary relationships within the genus Leishmania and its origins are the source of ongoing debate, reflected in conflicting phylogenetic and biogeographic reconstructions. This study employs a recently described bioinformatics method, SISRS, to identify over 200,000 informative sites across the genome from newly sequenced and publicly available Leishmania data. This dataset is used to reconstruct the evolutionary relationships of this genus. Additionally, we constructed a large multi-gene dataset, using it to reconstruct the phylogeny and estimate divergence dates for species. We conclude that the genus Leishmania evolved at least 90-100 million years ago, supporting a modified version of the Multiple Origins hypothesis that we call the Supercontinent hypothesis. According to this scenario, separate Leishmania clades emerged prior to, and during, the breakup of Gondwana. Additionally, we confirm that reptile-infecting Leishmania are derived from mammalian forms and that the species that infect porcupines and sloths form a clade long separated from other species. Finally, we firmly place the guinea-pig infecting species, Leishmaniaenriettii, the globally dispersed Leishmaniasiamensis, and the newly identified Australian species from a kangaroo, as sibling species whose distribution arises from the ancient connection between Australia, Antarctica, and South America.

Whole Genome Sequencing of Field Isolates Reveals Extensive Genetic Diversity in Plasmodium vivax from Colombia.

Plasmodium vivax is the most prevalent malarial species in South America and exerts a substantial burden on the populations it affects. The control and eventual elimination of P. vivax are global health priorities. Genomic research contributes to this objective by improving our understanding of the biology of P. vivax and through the development of new genetic markers that can be used to monitor efforts to reduce malaria transmission. Here we analyze whole-genome data from eight field samples from a region in Cordóba, Colombia where malaria is endemic. We find considerable genetic diversity within this population, a result that contrasts with earlier studies suggesting that P. vivax had limited diversity in the Americas. We also identify a selective sweep around a substitution known to confer resistance to sulphadoxine-pyrimethamine (SP). This is the first observation of a selective sweep for SP resistance in this species. These results indicate that P. vivax has been exposed to SP pressure even when the drug is not in use as a first line treatment for patients afflicted by this parasite. We identify multiple non-synonymous substitutions in three other genes known to be involved with drug resistance in Plasmodium species. Finally, we found extensive microsatellite polymorphisms. Using this information we developed 18 polymorphic and easy to score microsatellite loci that can be used in epidemiological investigations in South America.