A main role of a forensic entomologist is to determine when insects have become associated with remains to estimate the time of colonization (TOC) of specimens in evidence (Tomberlin et al

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A main role of a forensic entomologist is to determine when insects

have become associated with remains to estimate the time of colonization (TOC) of specimens in evidence (Tomberlin et al. 2011, Tomberlin et al. 2012), which can be informative for estimating the postmortem interval (PMI). This determination is typically done with immature Diptera of the family Calliphoridae that use decomposing tissue as a food resource (Byrd and Castner 2001). Adults deposit eggs on remains which develop into larvae and pass through three instars, pupate, and emerge as adults. Age of individual insects collected from remains can be accurate in estimating TOC when certain assumptions are met , but such estimates are less precise when made with third instar and pupal stages due to these stages taking more time to complete.


In the case of blow fly larval evidence, one can determine the stage of the instar based on spiracular morphology. However, morphology does not tell the age within a stage, thus widening the insect age estimate range and increasing uncertainty if additional information is not available to an analyst. This problem also exists for the pupal stage. Attempts have been made to determine ages of puparia based on color changes but are imprecise due to their rapid change in color, where tanning can occur within 24 h. Others have taken a histological approach by investigating intra-puparial development to identify the progressive phases. However, dissection and imaging methods are expensive, time consuming, and require detailed expertise regarding intra-puparial development - of which a limited number of forensic entomologists have training in. Recent studies have turned to hyperspectral imaging (HSI) techniques as a non-destructive and inexpensive method for determining age within stage for larval and pupal samples based on changes in pixel reflectance profiles of the insect cuticle. However, researchers have noted certain stages such as the newly molted third instar can be susceptible to the washing treatment made before the imaging.




Gene expression is an alternative approach that is a cost-effective and quantitative measurement to age immature insects; it is also one that DNA analysts have the skills to perform. Research has shown that temporal patterns of gene expression exist throughout immature insect development. Temporal gene expression is well understood with data available online in bioinformatic databases such as FlyAtlas and FlyBase. Gene expression profiles found throughout the immature development of Drosophila Fallen (Diptera: Drosophilidae) have proven useful in understanding regulation in development and basic biology studies, making them a true model organism. Extending similar gene expression studies into other dipteran species such as blow flies could lead to better understandings of their evolutionary and developmental histories.
Dipteran gene expression has been of recent interest in forensic entomology and colleagues have shown that quantitative studies with gene expression can be used to age immature blow flies . Such biological information can be used to break lengthier stages (e.g., third instar or pupa) into smaller temporal pieces and improve the precision of insect age estimates. Tarone et al. (2007) was the first to investigate the use of gene expression to age blow flies; this pilot study identified significant trends in expression for three genes over Lucilia sericata (Meigen) (Diptera: Calliphoridae) egg development.


Predictions made with the expression data were within 2 h of the true age. Following this study, Tarone and Foran (2011) demonstrated how generalized additive models (GAMs) that included expression profiles of 11 genes improved insect age determination in L. sericata larval and pupal stages. Resulting models were tested in a blind study where immature L. sericata of a known age were collected from rat carcasses. The inclusion of gene expression data in GAMs resulted in a 3-8% increase in precision for larval and pupal age predictions. Evaluation of gene expression patterns in the pupal stage of the forensically
relevant species Calliphora vicina Robineau-Desvoidy (Diptera: Calliphoridae) determined combinations of candidate gene expression profiles that were differentially expressed at three time points within the pupal stage. However, at the time they were unable to determine the identity of the candidate genes through BLAST® (Zehner et al. 2009). Boehme et al. (2013) continued gene expression studies with C. vicina; they found two reference genes and four candidate genes that, when used in combination, their expression profiles could be used to determine pupal age. This same research group then performed a series of blind studies in which they used gene expression profiles of the previously described study to age C. vicina pupae collected from different temperature regimes (Boehme et al. 2014). In a majority of age interval estimates, the lower bound of the pupal age was correctly predicted with the gene expression profiles; however, the upper bound of the age interval consistently over estimated true age (Boehme et al. 2014). Currently, insect age estimates based on gene expression for pupae appear to be imprecise yet accurate.


At the time of the aforementioned studies researchers used the genes they had at hand from Drosophila based studies, as well as limited species-specific transcript and sequence data, but with the recent advances in biotechnology, genome and transcriptome assemblies of forensically important blow flies have resulted in a wealth of information. This information can be used for studies on evolution, population structure, behavior, and physiology of calliphorids. Genome and transcriptome assemblies also allow researchers to identify candidate genes for studies on development. The question is no longer as to whether gene expression can be used to age blow flies, but now what genes can be used to determine age within development stage? Also, there is a need for validation of these markers across a range of environmental and genetic groups.


An additional advancement in biotechnology has been in the area of high throughput technologies. In the past, studies have relied on traditional Real-Time PCR (RT-PCR) for gene expression studies; these instruments are currently available in crime labs throughout the United States. Although this method is both useful and informative, it is costly in protocol time, money for reagents, and sample loss (Liu et al. 2003). Another limitation is the number of genes and samples that can be analyzed on a single run. Within the past decade, the development of high throughput technologies has reduced time, money, and loss of precious samples (Liu et al. 2003). Such technology has been applied to microfluidic chips, which can be useful for screening numerous genes at a time (Liu et al. 2003). Unfortunately, such instruments are not readily available in crime lab settings so such an approach may be best suited for research settings. However, by running traditional RT-PCR in parallel with high throughput technologies, one can validate expression between both technologies and the transcriptome used to select candidate genes.
 


One calliphorid species used to identify potential markers for determining age within development stage is the common green bottle fly, L. sericata, which is a cosmopolitan blow fly with forensic (Catts and Haskell 1990, Byrd and Castner 2001), medical (Baumann et al. 2015, Poppel et al. 2015), and veterinary important. There are a number of published development data sets for this species, but like for most blow fly species, a published genome does not exist for L. sericata. However, a de novo transcriptome assembly has been published for the species. These transcript data can be used to identify clusters of genes with similar expression profiles that have different temporal patterns, which is informative for selecting candidate genes for expression studies.


The objective for this study was to use the de novo transcriptome assembled by Sze et al. (2012) to identify genes that are uniquely expressed in the lengthy third instar and pupal development stages of L. sericata to reduce uncertainty in insect age estimates.
How the study of differential gene expression can help for precise estimation of insect's age and post mortem interval determination?