David C. Tack

Bio: David C. Tack is an academic researcher from Pennsylvania State University. The author has contributed to research in topics: RNA & Messenger RNA. The author has an hindex of 12, co-authored 19 publications receiving 1716 citations. Previous affiliations of David C. Tack include University of British Columbia & Michigan State University.

Early allopolyploid evolution in the post-Neolithic Brassica napus oilseed genome

Abstract: Oilseed rape (Brassica napus L.) was formed ~7500 years ago by hybridization between B. rapa and B. oleracea, followed by chromosome doubling, a process known as allopolyploidy. Together with more ancient polyploidizations, this conferred an aggregate 72× genome multiplication since the origin of angiosperms and high gene content. We examined the B. napus genome and the consequences of its recent duplication. The constituent An and Cn subgenomes are engaged in subtle structural, functional, and epigenetic cross-talk, with abundant homeologous exchanges. Incipient gene loss and expression divergence have begun. Selection in B. napus oilseed types has accelerated the loss of glucosinolate genes, while preserving expansion of oil biosynthesis genes. These processes provide insights into allopolyploid evolution and its relationship with crop domestication and improvement.

Structure-seq2: sensitive and accurate genome-wide profiling of RNA structure in vivo.

Abstract: RNA serves many functions in biology such as splicing, temperature sensing, and innate immunity. These functions are often determined by the structure of RNA. There is thus a pressing need to understand RNA structure and how it changes during diverse biological processes both in vivo and genome-wide. Here, we present Structure-seq2, which provides nucleotide-resolution RNA structural information in vivo and genome-wide. This optimized version of our original Structure-seq method increases sensitivity by at least 4-fold and improves data quality by minimizing formation of a deleterious by-product, reducing ligation bias, and improving read coverage. We also present a variation of Structure-seq2 in which a biotinylated nucleotide is incorporated during reverse transcription, which greatly facilitates the protocol by eliminating two PAGE purification steps. We benchmark Structure-seq2 on both mRNA and rRNA structure in rice (Oryza sativa). We demonstrate that Structure-seq2 can lead to new biological insights. Our Structure-seq2 datasets uncover hidden breaks in chloroplast rRNA and identify a previously unreported N1-methyladenosine (m1A) in a nuclear-encoded Oryza sativa rRNA. Overall, Structure-seq2 is a rapid, sensitive, and unbiased method to probe RNA in vivo and genome-wide that facilitates new insights into RNA biology.

Genome-wide RNA structurome reprogramming by acute heat shock globally regulates mRNA abundance

Abstract: The heat shock response is crucial for organism survival in natural environments. RNA structure is known to influence numerous processes related to gene expression, but there have been few studies on the global RNA structurome as it prevails in vivo. Moreover, how heat shock rapidly affects RNA structure genome-wide in living systems remains unknown. We report here in vivo heat-regulated RNA structuromes. We applied Structure-seq chemical [dimethyl sulfate (DMS)] structure probing to rice (Oryza sativa L.) seedlings with and without 10 min of 42 °C heat shock and obtained structural data on >14,000 mRNAs. We show that RNA secondary structure broadly regulates gene expression in response to heat shock in this essential crop species. Our results indicate significant heat-induced elevation of DMS reactivity in the global transcriptome, revealing RNA unfolding over this biological temperature range. Our parallel Ribo-seq analysis provides no evidence for a correlation between RNA unfolding and heat-induced changes in translation, in contrast to the paradigm established in prokaryotes, wherein melting of RNA thermometers promotes translation. Instead, we find that heat-induced DMS reactivity increases correlate with significant decreases in transcript abundance, as quantified from an RNA-seq time course, indicating that mRNA unfolding promotes transcript degradation. The mechanistic basis for this outcome appears to be mRNA unfolding at both 5′ and 3′-UTRs that facilitates access to the RNA degradation machinery. Our results thus reveal unexpected paradigms governing RNA structural changes and the eukaryotic RNA life cycle.

Causes and Consequences of Genetic Background Effects Illuminated by Integrative Genomic Analysis

Abstract: The phenotypic consequences of individual mutations are modulated by the wild-type genetic background in which they occur. Although such background dependence is widely observed, we do not know whether general patterns across species and traits exist or about the mechanisms underlying it. We also lack knowledge on how mutations interact with genetic background to influence gene expression and how this in turn mediates mutant phenotypes. Furthermore, how genetic background influences patterns of epistasis remains unclear. To investigate the genetic basis and genomic consequences of genetic background dependence of the scallopedE3 allele on the Drosophila melanogaster wing, we generated multiple novel genome-level datasets from a mapping-by-introgression experiment and a tagged RNA gene expression dataset. In addition we used whole genome resequencing of the parental lines—two commonly used laboratory strains—to predict polymorphic transcription factor binding sites for SD. We integrated these data with previously published genomic datasets from expression microarrays and a modifier mutation screen. By searching for genes showing a congruent signal across multiple datasets, we were able to identify a robust set of candidate loci contributing to the background-dependent effects of mutations in sd. We also show that the majority of background-dependent modifiers previously reported are caused by higher-order epistasis, not quantitative noncomplementation. These findings provide a useful foundation for more detailed investigations of genetic background dependence in this system, and this approach is likely to prove useful in exploring the genetic basis of other traits as well.

Genomic Consequences of Background Effects on scalloped Mutant Expressivity in the Wing of Drosophila melanogaster

Abstract: Genetic background effects contribute to the phenotypic consequences of mutations and are pervasive across all domains of life that have been examined, yet little is known about how they modify genetic systems. In part this is due to the lack of tractable model systems that have been explicitly developed to study the genetic and evolutionary consequences of background effects. In this study we demonstrate that phenotypic expressivity of the scallopedE3 (sdE3) mutation of Drosophila melanogaster is background dependent and is the result of at least one major modifier segregating between two standard lab wild-type strains. We provide evidence that at least one of the modifiers is linked to the vestigial region and demonstrate that the background effects modify the spatial distribution of known sd target genes in a genotype-dependent manner. In addition, microarrays were used to examine the consequences of genetic background effects on the global transcriptome. Expression differences between wild-type strains were found to be as large as or larger than the effects of mutations with substantial phenotypic effects, and expression differences between wild type and mutant varied significantly between genetic backgrounds. Significantly, we demonstrate that the epistatic interaction between sdE3 and an optomotor blind mutation is background dependent. The results are discussed within the context of developing a complex but more realistic view of the consequences of genetic background effects with respect to mutational analysis and studies of epistasis and cryptic genetic variation segregating in natural populations.

Sequencing of allotetraploid cotton ( Gossypium hirsutum L. acc. TM-1) provides a resource for fiber improvement

Abstract: Upland cotton is a model for polyploid crop domestication and transgenic improvement. Here we sequenced the allotetraploid Gossypium hirsutum L. acc. TM-1 genome by integrating whole-genome shotgun reads, bacterial artificial chromosome (BAC)-end sequences and genotype-by-sequencing genetic maps. We assembled and annotated 32,032 A-subgenome genes and 34,402 D-subgenome genes. Structural rearrangements, gene loss, disrupted genes and sequence divergence were more common in the A subgenome than in the D subgenome, suggesting asymmetric evolution. However, no genome-wide expression dominance was found between the subgenomes. Genomic signatures of selection and domestication are associated with positively selected genes (PSGs) for fiber improvement in the A subgenome and for stress tolerance in the D subgenome. This draft genome sequence provides a resource for engineering superior cotton lines.

Evolution of Gene Duplication in Plants.

Abstract: Ancient duplication events and a high rate of retention of extant pairs of duplicate genes have contributed to an abundance of duplicate genes in plant genomes. These duplicates have contributed to the evolution of novel functions, such as the production of floral structures, induction of disease resistance, and adaptation to stress. Additionally, recent whole-genome duplications that have occurred in the lineages of several domesticated crop species, including wheat (Triticum aestivum), cotton (Gossypium hirsutum), and soybean (Glycine max), have contributed to important agronomic traits, such as grain quality, fruit shape, and flowering time. Therefore, understanding the mechanisms and impacts of gene duplication will be important to future studies of plants in general and of agronomically important crops in particular. In this review, we survey the current knowledge about gene duplication, including gene duplication mechanisms, the potential fates of duplicate genes, models explaining duplicate gene retention, the properties that distinguish duplicate from singleton genes, and the evolutionary impact of gene duplication.

Genome sequence of cultivated Upland cotton ( Gossypium hirsutum TM-1) provides insights into genome evolution

Abstract: Gossypium hirsutum has proven difficult to sequence owing to its complex allotetraploid (AtDt) genome. Here we produce a draft genome using 181-fold paired-end sequences assisted by fivefold BAC-to-BAC sequences and a high-resolution genetic map. In our assembly 88.5% of the 2,173-Mb scaffolds, which cover 89.6%∼96.7% of the AtDt genome, are anchored and oriented to 26 pseudochromosomes. Comparison of this G. hirsutum AtDt genome with the already sequenced diploid Gossypium arboreum (AA) and Gossypium raimondii (DD) genomes revealed conserved gene order. Repeated sequences account for 67.2% of the AtDt genome, and transposable elements (TEs) originating from Dt seem more active than from At. Reduction in the AtDt genome size occurred after allopolyploidization. The A or At genome may have undergone positive selection for fiber traits. Concerted evolution of different regulatory mechanisms for Cellulose synthase (CesA) and 1-Aminocyclopropane-1-carboxylic acid oxidase1 and 3 (ACO1,3) may be important for enhanced fiber production in G. hirsutum.

Epistasis and quantitative traits: using model organisms to study gene-gene interactions

Abstract: The role of epistasis in the genetic architecture of quantitative traits is controversial, despite the biological plausibility that nonlinear molecular interactions underpin the genotype-phenotype map. This controversy arises because most genetic variation for quantitative traits is additive. However, additive variance is consistent with pervasive epistasis. In this Review, I discuss experimental designs to detect the contribution of epistasis to quantitative trait phenotypes in model organisms. These studies indicate that epistasis is common, and that additivity can be an emergent property of underlying genetic interaction networks. Epistasis causes hidden quantitative genetic variation in natural populations and could be responsible for the small additive effects, missing heritability and the lack of replication that are typically observed for human complex traits.