Biology subjects

Matthew D MacManes

Publications and source records attributed to Matthew D MacManes.

7 recordsLinked to original sources

bioRxiv2016

Characterization of a Male Reproductive Transcriptome for Peromyscus eremicus (Cactus mouse)

AbstractRodents of the genus Peromyscus have become increasingly utilized models for investigations into adaptive biology. This genus is particularly powerful for research linking genetics with adaptive physiology and behaviors, and recent research has capitalized on the unique opportunities afforded by the ecological diversity of these rodents. However, well characterized genomic and transcriptomic data is intrinsic to explorations of the genetic architecture responsible for ecological adaptations. This study characterizes a reproductive transcriptome of male Peromyscus eremicus (Cactus mouse), a desert specialist with extreme physiological adaptations to water limitation. We describe a reproductive transcriptome comprising three tissues in order to expand upon existing research in this species and to facilitate further studies elucidating the genetic basis of potential desert adaptations in male reproductive physiology.

Genomics↗

bioRxiv2016

De novo Genome Assembly of Geosmithia morbida, the Causal Agent of Thousand Cankers Disease

Background: Geosmithia morbida is a filamentous ascomycete that causes Thousand Cankers Disease in the eastern black walnut tree. This pathogen is commonly found in the western U.S.; however, recently the disease was also detected in several eastern states where the black walnut lumber industry is concentrated. G. morbida is one of two known phytopathogens within the genus Geosmithia, and it is vectored into the host tree via the walnut twig beetle.\n\nResults: We present the first de novo draft genome of G. morbida. It is 26.5 Mbp in length and contains less than 1% repetitive elements. The genome possesses an estimated 6,273 genes, 277 of which are predicted to encode proteins with unknown functions. Approximately 31.5% of the proteins in G. morbida are homologous to proteins involved in pathogenicity, and 5.6% of the proteins contain signal peptides that indicate these proteins are secreted.\n\nConclusions: Several studies have investigated the evolution of pathogenicity in pathogens of agricultural crops; forest fungal pathogens are often neglected because research efforts are focused on food crops. G. morbida is one of the few tree phytopathogens to be sequenced, assembled and annotated. The first draft genome of G. morbida serves as a valuable tool for comprehending the underlying molecular and evolutionary mechanisms behind pathogenesis within the Geosmithia genus.

Genomics↗

bioRxiv2015

Establishing evidenced-based best practice for the de novo assembly and evaluation of transcriptomes from non-model organisms

Characterizing transcriptomes in both model and non-model organisms has resulted in a massive increase in our understanding of biological phenomena. This boon, largely made possible via high-throughput sequencing, means that studies of functional, evolutionary and population genomics are now being done by hundreds or even thousands of labs around the world. For many, these studies begin with a de novo transcriptome assembly, which is a technically complicated process involving several discrete steps. Each step may be accomplished in one of several different ways, using different software packages, each producing different results. This analytical complexity begs the question - Which method(s) are optimal? Using reference and non-reference based evaluative methods, I propose a set of guidelines that aim to standardize and facilitate the process of transcriptome assembly. These recommendations include the generation of between 20 million and 40 million sequencing reads from single individual where possible, error correction of reads, gentle quality trimming, assembly filtering using Transrate and/or gene expression, annotation using dammit, and appropriate reporting. These recommendations have been extensively benchmarked and applied to publicly available transcriptomes, resulting in improvements in both content and contiguity. To facilitate the implementation of the proposed standardized methods, I have released a set of version controlled open-sourced code, The Oyster River Protocol for Transcriptome Assembly, available at http://oyster-river-protocol.rtfd.org/.

Bioinformatics↗

bioRxiv2015

Characterizing the Adult and Larval Transcriptome of the Multicolored Asian Lady Beetle, Harmonia axyridis

AbstractThe reasons for the evolution and maintenance of striking visual phenotypes are as widespread as the species that display these phenotypes. While study systems such as Heliconius and Dendrobatidae have been well characterized and provide critical information about the evolution of these traits, a breadth of new study systems, in which the phenotype of interest can be easily manipulated and quantified, are essential for gaining a more general understanding of these specific evolutionary processes. One such model is the multicolored Asian lady beetle, Harmonia axyridis, which displays significant elytral spot and color polymorphism. Using transcriptome data from two life stages, adult and larva, we characterize the transcriptome, thereby laying a foundation for further analysis and identification of the genes responsible for the continual maintenance of spot variation in H. axyridis.

Genomics↗

bioRxiv2015

Optimizing error correction of RNAseq reads

MotivationThe correction of sequencing errors contained in Illumina reads derived from genomic DNA is a common pre-processing step in many de novo genome assembly pipelines, and has been shown to improved the quality of resultant assemblies. In contrast, the correction of errors in transcriptome sequence data is much less common, but can potentially yield similar improvements in mapping and assembly quality. This manuscript evaluates several popular read-correction tools ability to correct sequence errors commonplace to transcriptome derived Illumina reads.\n\nResultsI evaluated the efficacy of correction of transcriptome derived sequencing reads using using several metrics across a variety of sequencing depths. This evaluation demonstrates a complex relationship between the quality of the correction, depth of sequencing, and hardware availability which results in variable recommendations depending on the goals of the experiment, tolerance for false positives, and depth of coverage. Overall, read error correction is an important step in read quality control, and should become a standard part of analytical pipelines.\n\nAvailabilityResults are non-deterministically repeatable using AMI:ami-3dae4956 (MacManes_EC_2015) and the Makefile available here: https://goo.gl/oVIuE0\n\nContactmatthew.macmanes@unh.edu and @PeroMHC

Bioinformatics↗

bioRxiv2014

Characterization of the transcriptome, nucleotide sequence polymorphism, and natural selection in the desert adapted mouse Peromyscus eremicus

As a direct result of intense heat and aridity, deserts are thought to be among the most harsh of environments, particularly for their mammalian inhabitants. Given that osmoregulation can be challenging for these animals, with failure resulting in death, strong selection should be observed on genes related to the maintenance of water and solute balance. One such animal, Peromyscus eremicus, is native to the desert regions of the southwest United States and may live its entire life without oral fluid intake. As a first step toward understanding the genetics that underlie this phenotype, we present a characterization of the P. eremicus transcriptome. We assay four tissues (kidney, liver, brain, testes) from a single individual and supplement this with population level renal transcriptome sequencing from 15 additional animals. We identified a set of transcripts undergoing both purifying and balancing selection based on estimates of Tajimas D. In addition, we used the branch-site test to identify a transcript - Slc2a9, likely related to desert osmoregulation - undergoing enhanced selection in P. eremicus relative to a set of related non-desert rodents.

Genomics↗

bioRxiv2013

On the optimal trimming of high-throughput mRNAseq data

The widespread and rapid adoption of high-throughput sequencing technologies has afforded researchers the opportunity to gain a deep understanding of genome level processes that underlie evolutionary change, and perhaps more importantly, the links between genotype and phenotype. In particular, researchers interested in functional biology and adaptation have used these technologies to sequence mRNA transcriptomes of specific tissues, which in turn are often compared to other tissues, or other individuals with different phenotypes. While these techniques are extremely powerful, careful attention to data quality is required. In particular, because high-throughput sequencing is more error-prone than traditional Sanger sequencing, quality trimming of sequence reads should be an important step in all data processing pipelines. While several software packages for quality trimming exist, no general guidelines for the specifics of trimming have been developed. Here, using empirically derived sequence data, I provide general recommendations regarding the optimal strength of trimming, specifically in mRNA-Seq studies. Although very aggressive quality trimming is common, this study suggests that a more gentle trimming, specifically of those nucleotides whose PO_SCPLOWHREDC_SCPLOW score <2 or <5, is optimal for most studies across a wide variety of metrics.

Bioinformatics↗