Biology subjects

Jermiin, L. S.

Publications and source records attributed to Jermiin, L. S..

9 recordsLinked to original sources

bioRxiv2020

A minimum reporting standard for multiple sequence alignments

Multiple sequence alignments (MSAs) play a pivotal role in studies of molecular sequence data, but nobody has developed a minimum reporting standard (MRS) to quantify the completeness of MSAs in terms of completely-specified nucleotides or amino acids. We present an MRS that relies on four simple completeness metrics. The metrics are implemented in AliStat, a program developed to support the MRS. A survey of published MSAs illustrates the benefits and unprecedented transparency offered by the MRS.

bioinformatics↗

bioRxiv2020

Measuring historical and compositional signals in phylogenetic data

Most commonly-used molecular phylogenetic methods assume that the sequences evolved on a single bifurcating tree and that the evolutionary processes operating at the variable sites are Markovian. Typically, it is also assumed that these evolutionary processes were stationary, reversible and homogenous across the edges of the tree and that the multiple substitutions at variable sites occurred so infrequently that the historical signal (i.e., the signal in DNA that is due to the order and time of divergence event) in phylogenetic data has been retained, allowing for accurate phylogenetic estimates to be obtained from the data. Here, we present two metrics,{lambda} and{delta} CFS, to quantify the strength of the historical and compositional signals in phylogenetic data.{lambda} quantifies loss of historical signal, with{lambda} = 0.0 indicating evidence of a strong historical signal and{lambda} = 1.0 indicating evidence of a fully eroded historical signal.{delta} CFS quantifies compositional distance from full symmetry of a divergence matrix generated by comparing two sequences, with{delta} CFS = 0.0 indicating no evidence of evolution under dissimilar conditions and{delta} CFS > 0.0 indicating increasing evidence of lineages diverging under different conditions. The metrics are implemented in methods intended for use after multiple sequence alignment and before model selection and phylogenetic analysis. Results generated using these methods allow users of phylogenetic tools to select phylogenetic data more wisely than it previously was possible. The merits of these metrics and methods are illustrated using simulated data and multi-gene alignments obtained from 144 insect genomes.

evolutionary biology↗

bioRxiv2019

Six new reference-quality bat genomes illuminate the molecular basis and evolution of bat adaptations

Bats account for ~20% of all extant mammal species and are considered exceptional given their extraordinary adaptations, including biosonar, true flight, extreme longevity, and unparalleled immune systems. To understand these adaptations, we generated reference-quality genomes of six species representing the key divergent lineages. We assembled these genomes with a novel pipeline incorporating state-of-the-art long-read and long-range sequencing and assembly techniques. The genomes were annotated using a maximal evidence approach, de novo predictions, protein/mRNA alignments, Iso-seq long read and RNA-seq short read transcripts, and gene projections from our new TOGA pipeline, retrieving virtually all (>99%) mammalian BUSCO genes. Phylogenetic analyses of 12,931 protein coding-genes and 10,857 conserved non-coding elements identified across 48 mammalian genomes helped to resolve bats closest extant relatives within Laurasiatheria, supporting a basal position for bats within Scrotifera. Genome-wide screens along the bat ancestral branch revealed (a) selection on hearing-involved genes (e.g LRP2, SERPINB6, TJP2), which suggest that laryngeal echolocation is a shared ancestral trait of bats; (b) selection (e.g INAVA, CXCL13, NPSR1) and loss of immunity related proteins (e.g. LRRC70, IL36G), including pro-inflammatory NF-kB signalling; and (c) expansion of the APOBEC family, associated with restricting viral infection, transposon activity and interferon signalling. We also identified unique integrated viruses, indicating that bats have a history of tolerating viral pathogens, lethal to other mammal species. Non-coding RNA analyses identified variant and novel microRNAs, revealing regulatory relationships that may contribute to phenotypic diversity in bats. Together, our reference-quality genomes, high-quality annotations, genome-wide screens and in-vitro tests revealed previously unknown genomic adaptations in bats that may explain their extraordinary traits.

genomics↗

bioRxiv2019

Software for detecting heterogeneous evolutionary processes across aligned sequence data

Most model-based molecular phylogenetic methods assume that the sequences diverged on a tree under homogeneous conditions. If evolution occurred under these conditions, then it is unlikely that the sequences would become compositionally heterogeneous. Conversely, if the sequences are compositionally heterogeneous, then it is unlikely that they have evolved under homogeneous conditions. We present methods to detect and analyse heterogeneous evolution in aligned sequence data and to examine--visually and numerically--its effect on phylogenetic estimates. The methods are implemented in three programs, allowing users to better examine under what conditions their phylogenetic data may have evolved.

evolutionary biology↗

bioRxiv2019

MitoImpute: A Snakemake pipeline for imputation of mitochondrial genetic variants

BackgroundVariation in mitochondrial DNA (mtDNA) identified by genotyping microarrays or by sequencing only hypervariable regions of the genome may be insufficient to reliably assign mitochondrial genomes to phylogenetic lineages or haplogroups. This lack of resolution can limit functional and clinical interpretation of a substantial body of existing mtDNA data. To address this limitation, we developed and evaluated a method for imputing missing mtDNA single nucleotide variants (mtSNVs) that uses a large reference alignment of complete mtDNA sequences. The method and reference alignment are combined into a pipeline, which we call MitoImpute. ResultsWe aligned the sequences of 36,960 complete human mitochondrial genomes downloaded from GenBank, filtered and controlled for quality. These sequences were reformatted for use in imputation software, IMPUTE2. We assessed the imputation accuracy of MitoImpute by measuring haplogroup and genotype concordance in data from the 1,000 Genomes Project and the Alzheimers Disease Neuroimaging Initiative (ADNI). The mean improvement of haplogroup assignment in the 1,000 Genomes samples was 42.7% (Matthews correlation coefficient = 0.64). In the ADNI cohort, we imputed missing single nucleotide variants. ConclusionsThese results show that our reference alignment and panel can be used to impute missing mtSNVs in exiting data obtained from using microarrays, thereby broadening the scope of functional and clinical investigation of mtDNA. This improvement may be particularly useful in studies where participants have been recruited over time and mtDNA data obtained using different methods, enabling better integration of early data collected using less accurate methods with more recent sequence data.

genomics↗

bioRxiv2019

Genome-wide analysis of MIKC-type MADS-box genes in wheat: pervasive duplications may have facilitated adaptation to different environmental conditions

BackgroundWheat (Triticum aestivum) is one of the most important crops worldwide. Given a growing global population coupled with increasingly challenging climate and cultivation conditions, facilitating wheat breeding by fine-tuning important traits such as stress resistance, yield and plant architecture is of great importance. Since they are involved in virtually all aspects of plant development and stress responses, prime candidates for improving these traits are MIKC-type (type II) MADS-box genes.\n\nResultsWe present a detailed overview of number, phylogeny, and expression of 201 wheat MIKC-type MADS-box genes, which can be assigned to 15 subfamilies. Homoeolog retention is significantly above the average genome-wide retention rate for wheat genes, indicating that many MIKC-type homoeologs are functionally important and not redundant. Gene expression is generally in agreement with the expected subfamily-specific expression pattern, indicating broad conservation of function of MIKC-type genes during wheat evolution.\n\nWe find the extensive expansion of some MIKC-type subfamilies to be correlated with their chromosomal location and propose a link between MADS-box gene duplications and the adaptability of wheat. A number of MIKC-type genes encode for truncated proteins that lack either the DNA-binding or protein-protein interaction domain and occasionally show novel expression patterns, possibly pointing towards neofunctionalization.\n\nConclusionsConserved and neofunctionalized MIKC-type genes may have played an important role in the adaptation of wheat to a diversity of conditions, hence contributing to its importance as a global staple food. Therefore, we propose that MIKC-type MADS-box genes are especially well suited for targeted breeding approaches and phenotypic fine tuning.

plant biology↗

bioRxiv2018

Sensitivity and Specificity of Information Criteria

Information criteria (ICs) based on penalized likelihood, such as Akaikes Information Criterion (AIC), the Bayesian Information Criterion (BIC), and sample-size-adjusted versions of them, are widely used for model selection in health and biological research. However, different criteria sometimes support different models, leading to discussions about which is the most trustworthy. Some researchers and fields of study habitually use one or the other, often without a clearly stated justification. They may not realize that the criteria may disagree. Others try to compare models using multiple criteria but encounter ambiguity when different criteria lead to substantively different answers, leading to questions about which criterion is best. In this paper we present an alternative perspective on these criteria that can help in interpreting their practical implications. Specifically, in some cases the comparison of two models using ICs can be viewed as equivalent to a likelihood ratio test, with the different criteria representing different alpha levels and BIC being a more conservative test than AIC. This perspective may lead to insights about how to interpret the ICs in more complex situations. For example, AIC or BIC could be preferable, depending on the relative importance one assigns to sensitivity versus specificity. Understanding the differences and similarities among the ICs can make it easier to compare their results and to use them to make informed decisions.

bioinformatics↗

bioRxiv2018

A new phylogenetic protocol: Dealing with model misspecification and confirmation bias in molecular phylogenetics

Molecular phylogenetics plays a key role in comparative genomics and has an increasingly-significant impacts on science, industry, government, public health, and society. In this opinion paper, we posit that the current phylogenetic protocol is missing two critical steps, and that their absence allows model misspecification and confirmation bias to unduly influence our phylogenetic estimates. Based on the potential offered by well-established but under-used procedures, such as assessment of phylogenetic assumptions and tests of goodness-of-fit, we introduce a new phylogenetic protocol that will reduce confirmation bias and increase the accuracy of phylogenetic estimates. DedicationTo the memory of Rossiter H. Crozier (1943-2009), an evolutionary biologist, who, with his great generosity and wide-reaching inquisitiveness, inspired students and scientists in Australia, and abroad.

evolutionary biology↗

bioRxiv2017

GHOST: Recovering Historical Signal from Heterotachously-evolved Sequence Alignments

Molecular sequence data that have evolved under the influence of heterotachous evolutionary processes are known to mislead phylogenetic inference. We introduce the General Heterogeneous evolution On a Single Topology (GHOST) model of sequence evolution, implemented under a maximum-likelihood framework in the phylogenetic program IQ-TREE (http://www.iqtree.org). Simulations show that using the GHOST model, IQ-TREE can accurately recover the tree topology, branch lengths and substitution model parameters from heterotachously-evolved sequences. We develop a model selection algorithm based on simulation results, and investigate the performance of the GHOST model on empirical data by sampling phylogenomic alignments of varying lengths from a plastome alignment. We then carry out inference under the GHOST model on a phylogenomic dataset composed of 248 genes from 16 taxa, where we find the GHOST model concurs with the currently accepted view, placing turtles as a sister lineage of archosaurs, in contrast to results obtained using traditional variable rates-across-sites models. Finally, we apply the model to a dataset composed of a sodium channel gene of 11 fish taxa, finding that the GHOST model is able to infer a subtle component of the historical signal, linked to the previously established convergent evolution of the electric organ in two geographically distinct lineages of electric fish. We compare inference under the GHOST model to partitioning by codon position and show that, owing to the minimization of model constraints, the GHOST model is able to offer unique biological insights when applied to empirical data.

evolutionary biology↗