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1. Three Co-expression Pattern Types across Microbial Transcriptional Networks of Plankton in Two Oceanic Waters

   https://doi.org/10.1145/3388440.3412485  

   Sharma, Ruby; Luo, Xuye; Kumar, Sajal; Song, Mingzhou (September 2020, Proceedings. The 11th ACM Int'l Conf on Bioinform, Comput Biol and Health Inform)

   null (Ed.)

   Patterns of two molecules across biological systems are often labeled as conserved or differential. We argue that this classification is insufficient. Here, we introduce three types of relationships across systems. Upon stimuli, a type-0 pattern arises from conserved circuitry with active conserved trajectory; a type-1 pattern is conserved circuitry with active differential trajectory; a type-2 pattern is rewired circuitry with active trajectory. We present a 1st-order marginal change test, prove its optimality, and establish its asymptotic chi-squared distribution under the null hypothesis of identical marginals across conditions. The test outperformed other methods in detecting 1st-order difference in simulation studies. We also introduce a zeroth-order strength test to assess association of two variables across systems. We compared gene co-expression networks of planktonic microbial communities in cold California coastal water against the warm water of North Pacific Subtropical Gyre. The frequency of type-1 patterns is much higher than those of type-2 and type-0 patterns, revealing that the microbial communities are mostly conserved in molecular circuitry but responded differentially to ocean habitats. Type-1 and 2 patterns are enriched with genes known to respond to environmental changes or stress; type-0 patterns involve genes having essential function such as photosynthesis and general transcription. Our work provides a deep understanding to effects of the environment on gene regulation in microbial communities. The method is generally applicable to other biological systems. All tests are provided in the R package 'DiffXTables' at https://cran.r-project.org/package=DiffXTables. Other source code and lists of significant gene patterns are available at https://www.cs.nmsu.edu/~joemsong/ACM-BCB-2020/Plankton 

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2. Detecting genetic epistasis by differential departure from independence

   https://doi.org/10.1007/s00438-022-01893-3  

   Sharma, Ruby; Sadeghian Tehrani, Zeinab; Kumar, Sajal; Song, Mingzhou (May 2022, Molecular Genetics and Genomics)

   Countering prior beliefs that epistasis is rare, genomics advancements suggest the other way. Current practice often filters out genomic loci with low variant counts before detecting epistasis. We argue that this practice is far from optimal because it can throw away strong epistatic patterns. Instead, we present the compensated Sharma–Song test to infer genetic epistasis in genome-wide association studies by differential departure from independence. The test does not require a minimum number of replicates for each variant. We also introduce algorithms to simulate epistatic patterns that differentially depart from independence. Using two simulators, the test performed comparably to the original Sharma–Song test when variant frequencies at a locus are marginally uniform; encouragingly, it has a marked advantage over alternatives when variant frequencies are marginally nonuniform. The test further revealed uniquely clean epistatic variants associated with chicken abdominal fat content that are not prioritized by other methods. Genes involved in most numbers of inferred epistasis between single nucleotide polymorphisms (SNPs) belong to pathways known for obesity regulation; many top SNPs are located on chromosome 20 and in intergenic regions. Measuring differential departure from independence, the compensated Sharma–Song test offers a practical choice for studying epistasis robust to nonuniform genetic variant frequencies. 

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3. Assessing the fit of the multi-species network coalescent to multi-locus data

   https://doi.org/10.1093/bioinformatics/btaa863  

   Cai, Ruoyi; Ané, Cécile (December 2020, Bioinformatics)

   Russell, Schwartz (Ed.)

   Abstract Motivation With growing genome-wide molecular datasets from next-generation sequencing, phylogenetic networks can be estimated using a variety of approaches. These phylogenetic networks include events like hybridization, gene flow or horizontal gene transfer explicitly. However, the most accurate network inference methods are computationally heavy. Methods that scale to larger datasets do not calculate a full likelihood, such that traditional likelihood-based tools for model selection are not applicable to decide how many past hybridization events best fit the data. We propose here a goodness-of-fit test to quantify the fit between data observed from genome-wide multi-locus data, and patterns expected under the multi-species coalescent model on a candidate phylogenetic network. Results We identified weaknesses in the previously proposed TICR test, and proposed corrections. The performance of our new test was validated by simulations on real-world phylogenetic networks. Our test provides one of the first rigorous tools for model selection, to select the adequate network complexity for the data at hand. The test can also work for identifying poorly inferred areas on a network. Availability and implementation Software for the goodness-of-fit test is available as a Julia package at https://github.com/cecileane/QuartetNetworkGoodnessFit.jl. Supplementary information Supplementary data are available at Bioinformatics online. 

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4. Seasonal heterochrony of reproductive development and gene expression in a polymorphic salamander

   https://doi.org/10.1002/dvdy.744  

   Herrboldt, Madison_A; Wright, Claire_N_C; Bonett, Ronald_M (October 2024, Developmental Dynamics)

   Abstract BackgroundLife cycle evolution includes ecological transitions and shifts in the timing of somatic and reproductive development (heterochrony). However, heterochronic changes can be tissue‐specific, ultimately leading to the differential diversification of traits. Salamanders exhibit alternative life cycle polymorphisms involving either an aquatic to terrestrial metamorphosis (biphasic) or retention of aquatic larval traits into adulthood (paedomorphic). In this study, we used gene expression and histology to evaluate how life cycle evolution impacts temporal reproductive patterns in males of a polymorphic salamander. ResultsWe found that heterochrony shifts the distribution of androgen signaling in the integument, which is correlated with significant differences in seasonal reproductive gland development and pheromone gene expression. In the testes, androgen receptor (ar) expression does not significantly vary between morphs or across seasons. We found significant differences in the onset of spermatogenesis, but by peak breeding season the testes were the same with respect to both histology and gene expression. ConclusionThis study provides an example of how seasonal heterochronic shifts in tissue‐specificargene expression can disparately impact seasonal development and expression patterns across tissues, providing a potential mechanism for differential diversification of reproductive traits. 

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5. Temporal Analysis of Gene Expression and Isoform Switching in Brown Bears ( Ursus arctos )

   https://doi.org/10.1093/icb/icac093  

   Perry, Blair W.; Armstrong, Ellie E.; Robbins, Charles T.; Jansen, Heiko T.; Kelley, Joanna L. (June 2022, Integrative And Comparative Biology)

   Abstract Hibernation in brown bears is an annual process involving multiple physiologically distinct seasons—hibernation, active, and hyperphagia. While recent studies have characterized broad patterns of differential gene regulation and isoform usage between hibernation and active seasons, patterns of gene and isoform expression during hyperphagia remain relatively poorly understood. The hyperphagia stage occurs between active and hibernation seasons and involves the accumulation of large fat reserves in preparation for hibernation. Here, we use time-series analyses of gene expression and isoform usage to interrogate transcriptomic regulation associated with all three seasons. We identify a large number of genes with significant differential isoform usage (DIU) across seasons and show that these patterns of isoform usage are largely tissue-specific. We also show that DIU and differential gene-level expression responses are generally non-overlapping, with only a small subset of multi-isoform genes showing evidence of both gene-level expression changes and changes in isoform usage across seasons. Additionally, we investigate nuanced regulation of candidate genes involved in the insulin signaling pathway and find evidence of hyperphagia-specific gene expression and isoform regulation that may enhance fat accumulation during hyperphagia. Our findings highlight the value of using temporal analyses of both gene- and isoform-level gene expression when interrogating complex physiological phenotypes and provide new insight into the mechanisms underlying seasonal changes in bear physiology. 

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