DegNorm: normalization of generalized transcript degradation improves accuracy in RNA-seq analysis

Age-Invariant Genes: Multi-Tissue Identification and Characterization of Murine Reference Genes

Studies of the aging transcriptome focus on genes that change with age. But what can we learn from age-invariant genes-those that remain unchanged throughout the aging process? These genes also have a practical application: they serve as reference genes (often called housekeeping genes) in expression studies. Reference genes have mostly been identified and validated in young organisms, and no systematic investigation has been done across the lifespan. Here, we build upon a common pipeline for identifying reference genes in RNA-seq datasets to identify age-invariant genes across seventeen C57BL/6 mouse tissues (brain, lung, bone marrow, muscle, white blood cells, heart, small intestine, kidney, liver, pancreas, skin, brown, gonadal, marrow, and subcutaneous adipose tissue) spanning 1 to 21+ months of age. We identify 9 pan-tissue age-invariant genes and many tissue-specific age-invariant genes. These genes are stable across the lifespan and are validated in independent bulk RNA-seq datasets and RT-qPCR. We find age-invariant genes have shorter transcripts on average and are enriched for CpG islands. Interestingly, pathway enrichment analysis for age-invariant genes identifies an overrepresentation of molecular functions associated with some, but not all, hallmarks of aging. Thus, though hallmarks of aging typically involve changes in cell maintenance mechanisms, select genes associated with these hallmarks resist fluctuations in expression with age. Finally, our analysis concludes no classical reference gene is appropriate for aging studies in all tissues. Instead, we provide tissue-specific and pan-tissue genes for assays utilizing reference gene normalization (i.e., RT-qPCR) that can be applied to animals across the lifespan.

Host-gut microbiota interactions shape parasite infections in farmed Atlantic salmon

Animals and their associated microbiota share long evolutionary histories. However, it is not always clear how host genotype and microbiota interact to affect phenotype. We applied a hologenomic approach to explore how host-microbiota interactions shape lifetime growth and parasite infection in farmed Atlantic salmon (Salmo salar). Multi-omics data sets were generated from the guts of 460 salmon, 82% of which were naturally infected with an intestinal cestode. A single Mycoplasma bacterial strain, MAG01, dominated the gut metagenome of large, non-parasitized fish, consistent with previous studies showing high levels of Mycoplasma in the gut microbiota of healthy salmon. While small and/or parasitized salmon also had high abundance of MAG01, we observed increased alpha diversity in these individuals, driven by increased frequency of low-abundance Vibrionaceae and other Mycoplasma species that carried known virulence genes. Colonization by one of these cestode-associated Mycoplasma strains was associated with host individual genomic variation in long non-coding RNAs. Integrating the multi-omic data sets revealed coordinated changes in the salmon gut mRNA transcriptome and metabolome that correlated with shifts in the microbiota of smaller, parasitized fish. Our results suggest that the gut microbiota of small and/or parasitized fish is in a state of dysbiosis that partly depends on the host genotype, highlighting the value of using a hologenomic approach to incorporate the microbiota into the study of host-parasite dynamics.IMPORTANCEStudying host-microbiota interactions through the perspective of the hologenome is gaining interest across all life sciences. Intestinal parasite infections are a huge burden on human and animal health; however, there are few studies investigating the role of the hologenome during parasite infections. We address this gap in the largest multi-omics fish microbiota study to date using natural cestode infection of farmed Atlantic salmon. We find a clear association between cestode infection, salmon lifetime growth, and perturbation of the salmon gut microbiota. Furthermore, we provide the first evidence that the genetic background of the host may partly determine how the gut microbiota changes during parasite-associated dysbiosis. Our study therefore highlights the value of a hologenomic approach for gaining a more in-depth understanding of parasitism.

Environmental RNA as a Noninvasive Tool for Assessing Toxic Effects in Fish: A Proof-of-concept Study Using Japanese Medaka Exposed to Pyrene

Although environmental RNA (eRNA) is emerging as a noninvasive tool to assess the health status of aquatic macroorganisms, the potential of eRNA in assessing chemical hazards remain largely untested. In this study, we investigated the ability of eRNA to detect changes in gene expression in Japanese medaka fish (Oryzias latipes) in response to sublethal pyrene exposure, as a model toxic chemical. We performed standardized acute toxicity tests and collected eRNA from tank water and RNA from fish tissue after 96 h of exposure. Our results showed that over 1000 genes were detected in eRNA and the sequenced read counts of these genes correlated with those in fish tissue (r = 0.50). Moreover, eRNA detected 86 differentially expressed genes in response to pyrene, some of which were shared by fish RNA, including the suppression of collagen fiber genes. These results suggest that eRNA has the potential to detect changes in gene expression in fish in response to environmental stressors without the need for sacrificing or causing pain to fish. However, we also found that the majority of sequenced reads of eRNA (>99%) were not mapped to the reference medaka genome and they originated from bacteria and fungi, resulting in low sequencing depth. In addition, eRNA, in particular nuclear genes, was highly degraded with a median transcript integrity number (TIN) of <20. These limitations highlight the need for future studies to improve the analytical methods of eRNA application.

Pervasive effects of RNA degradation on Nanopore direct RNA sequencing

Oxford Nanopore direct RNA sequencing (DRS) is capable of sequencing complete RNA molecules and accurately measuring gene and isoform expression. However, as DRS is designed to profile intact RNA, expression quantification may be more heavily dependent upon RNA integrity than alternative RNA sequencing methodologies. It is currently unclear how RNA degradation impacts DRS or whether it can be corrected for. To assess the impact of RNA integrity on DRS, we performed a degradation time series using SH-SY5Y neuroblastoma cells. Our results demonstrate that degradation is a significant and pervasive factor that can bias DRS measurements, including a reduction in library complexity resulting in an overrepresentation of short genes and isoforms. Degradation also biases differential expression analyses; however, we find that explicit correction can almost fully recover meaningful biological signal. In addition, DRS provided less biased profiling of partially degraded samples than Nanopore PCR-cDNA sequencing. Overall, we find that samples with RNA integrity number (RIN) > 9.5 can be treated as undegraded and samples with RIN > 7 can be utilized for DRS with appropriate correction. These results establish the suitability of DRS for a wide range of samples, including partially degraded in vivo clinical and post-mortem samples, while limiting the confounding effect of degradation on expression quantification.

The transcript integrity index (TII) provides a standard measure of sperm RNA

Standardizing RNA quality is key to interpreting RNA-seq data as a compromised sample can mask the underlying biology. The challenge remains when evaluating RNA quality in samples with high RNA fragmentation. For example, programmed fragmentation and cytoplasmic expulsion, integral to sperm maturation, is a prime example of the complexities of interpreting RNA-seq data, given that fragmentation can be random and\or targeted. To meet this challenge, we developed an algorithm that accurately measures RNA quality in samples with high fragmentation, such as spermatozoa. The integrity of 1,000 previously identified abundant sperm transcripts were independently visualized and evaluated using the Transcript Integrity Index (TII) algorithm to identify intact transcripts. Full-length transcripts from visual and the TII algorithm were evaluated for testis preference in humans using the GTEx tissues database. Samples were then filtered by the Interquartile Range (IQR), identifying those in which the greatest number of transcripts failed to pass the visual or TII thresholds. Transcript lists were overlapped, forming the set of intact transcripts used as TII standards. Each sample was re-evaluated as a function of this TII set of intact transcripts, with poor quality samples identified as those failing in the largest number of transcripts. While ontologically enriched in roles related to spermatogenesis and/or fertilization, samples did not segregate based on birth outcome. The TII algorithm proved an effective means to identify samples of similar quality from sperm, a cell type enriched in biologically fragmented RNAs. The algorithm should facilitate other studies using samples compromised by high levels of RNA fragmentation, such as Formalin-Fixed Paraffin-Embedded samples. Requisite to assessing male health, TII provides a solution to the long-sought-after standard that identifies samples of similar quality.

Assessment of RNA extraction protocols from cladocerans

The usage of cladocerans as non-model organisms in ecotoxicological and risk assessment studies has intensified in recent years due to their ecological importance in aquatic ecosystems. The molecular assessment such as gene expression analysis has been introduced in ecotoxicological and risk assessment to link the expression of specific genes to a biological process in the cladocerans. The validity and accuracy of gene expression analysis depends on the quantity, quality and integrity of extracted ribonucleic acid (RNA) of the sample. However, the standard methods of RNA extraction from the cladocerans are still lacking. This study evaluates the extraction of RNA from tropical freshwater cladocerans Moina micrura using two methods: the phenol-chloroform extraction method (QIAzol) and a column-based kit (Qiagen Micro Kit). Glycogen was introduced in both approaches to enhance the recovery of extracted RNA and the extracted RNA was characterised using spectrophotometric analysis (NanoDrop), capillary electrophoresis (Bioanalyzer). Then, the extracted RNA was analysed with reverse transcription polymerase chain reaction (RT-PCR) to validate the RNA extraction method towards downstream gene expression analysis. The results indicate that the column-based kit is most suitable for the extraction of RNA from M. micrura, with the quantity (RNA concentration = 26.90 ± 6.89 ng/μl), quality (A260:230 = 1.95 ± 0.15, A280:230 = 1.85 ± 0.09) and integrity (RNA integrity number, RIN = 7.20 ± 0.16). The RT-PCR analysis shows that the method successfully amplified both alpha tubulin and actin gene at 33-35 cycles (i.e. Ct = 32.64 to 33.48). The results demonstrate that the addition of glycogen is only suitable for the phenol-chloroform extraction method. RNA extraction with high and comprehensive quality control assessment will increase the accuracy and reliability of downstream gene expression, thus providing more ecotoxicological data at the molecular biological level on other freshwater zooplankton species.

Differential gene expression reveals host factors for viral shedding variation in mallards (Anas platyrhynchos) infected with low-pathogenic avian influenza virus

Intraspecific variation in pathogen shedding impacts disease transmission dynamics; therefore, understanding the host factors associated with individual variation in pathogen shedding is key to controlling and preventing outbreaks. In this study, ileum and bursa of Fabricius tissues of wild-bred mallards (Anas platyrhynchos) infected with low-pathogenic avian influenza (LPAIV) were evaluated at various post-infection time points to determine genetic host factors associated with intraspecific variation in viral shedding. By analysing transcriptome sequencing data (RNA-seq), we found that LPAIV-infected wild-bred mallards do not exhibit differential gene expression compared to uninfected birds, but that gene expression was associated with cloacal viral shedding quantity early in the infection. In both tissues, immune gene expression was higher in high/moderate shedding birds compared to low shedding birds, and significant positive relationships with viral shedding were observed. In the ileum, expression for host genes involved in viral cell entry was lower in low shedders compared to moderate shedders at 1 day post-infection (DPI), and expression for host genes promoting viral replication was higher in high shedders compared to low shedders at 2 DPI. Our findings indicate that viral shedding is a key factor for gene expression differences in LPAIV-infected wild-bred mallards, and the genes identified in this study could be important for understanding the molecular mechanisms driving intraspecific variation in pathogen shedding.

The functional genetic architecture of egg-laying and live-bearing reproduction in common lizards

All amniotes reproduce either by egg-laying (oviparity), which is ancestral to vertebrates or by live-bearing (viviparity), which has evolved many times independently. However, the genetic basis of these parity modes has never been resolved and, consequently, its convergence across evolutionary scales is currently unknown. Here, we leveraged natural hybridizations between oviparous and viviparous common lizards (Zootoca vivipara) to describe the functional genes and genetic architecture of parity mode and its key traits, eggshell and gestation length, and compared our findings across vertebrates. In these lizards, parity trait genes were associated with progesterone-binding functions and enriched for tissue remodelling and immune system pathways. Viviparity involved more genes and complex gene networks than did oviparity. Angiogenesis, vascular endothelial growth and adrenoreceptor pathways were enriched in the viviparous female reproductive tissue, while pathways for transforming growth factor were enriched in the oviparous. Natural selection on these parity mode genes was evident genome-wide. Our comparison to seven independent origins of viviparity in mammals, squamates and fish showed that genes active in pregnancy were related to immunity, tissue remodelling and blood vessel generation. Therefore, our results suggest that pre-established regulatory networks are repeatedly recruited for viviparity and that these are shared at deep evolutionary scales.

homeRNA: A Self-Sampling Kit for the Collection of Peripheral Blood and Stabilization of RNA

Gene expression analysis (e.g., targeted gene panels and transcriptomics) from whole blood can elucidate mechanisms of the immune function and aid in the discovery of biomarkers. Conventional venipuncture offers only a small snapshot of our broad immune landscape as immune responses may occur outside of the time and location parameters available for conventional venipuncture. A self-operated method that enables flexible sampling of liquid whole blood coupled with immediate stabilization of cellular RNA is instrumental in facilitating capture and preservation of acute or transient immune fluxes. To this end, we developed homeRNA, a kit for self-collection of peripheral blood (∼0.5 mL) and immediate stabilization of cellular RNA, using the Tasso-SST blood collection device with a specially designed stabilizer tube containing RNAlater. To assess the feasibility of homeRNA for self-collection and stabilization of whole blood RNA, we conducted a pilot study (n = 47 participants) in which we sent homeRNA to participants aged 21-69, located across 10 US states (94% successful blood collections, n = 61/65). Among participants who successfully collected blood, 93% reported no or minimal pain/discomfort using the kit (n = 39/42), and 79% reported very easy/somewhat easy stabilization protocol (n = 33/42). Total RNA yield from the stabilized samples ranged between 0.20 and 5.99 μg (mean = 1.51 μg), and all but one RNA integrity number values were above 7.0 (mean = 8.1), indicating limited RNA degradation. The results from this study demonstrate the self-collection and RNA stabilization of whole blood with homeRNA by participants themselves in their own home.

Expression Pattern of the Pneumocystis jirovecii Major Surface Glycoprotein Superfamily in Patients with Pneumonia

BACKGROUND

The human pathogen Pneumocystis jirovecii harbors 6 families of major surface glycoproteins (MSGs) encoded by a single gene superfamily. MSGs are presumably responsible for antigenic variation and adhesion to host cells. The genomic organization suggests that a single member of family I is expressed at a given time per cell, whereas members of the other families are simultaneously expressed.

METHODS

We analyzed RNA sequences expressed in several clinical samples, using specific weighted profiles for sorting of reads and calling of single-nucleotide variants to estimate the diversity of the expressed genes.

RESULTS

A number of different isoforms of at least 4 MSG families were expressed simultaneously, including isoforms of family I, for which confirmation was obtained in the wet laboratory.

CONCLUSION

These observations suggest that every single P. jirovecii population is made of individual cells with distinct surface properties. Our results enhance our understanding of the unique antigenic variation system and cell surface structure of P. jirovecii.

mRNA Inventory of Extracellular Vesicles from Ustilago maydis

Extracellular vesicles (EVs) can transfer diverse RNA cargo for intercellular communication. EV-associated RNAs have been found in diverse fungi and were proposed to be relevant for pathogenesis in animal hosts. In plant-pathogen interactions, small RNAs are exchanged in a cross-kingdom RNAi warfare and EVs were considered to be a delivery mechanism. To extend the search for EV-associated molecules involved in plant-pathogen communication, we have characterised the repertoire of EV-associated mRNAs secreted by the maize smut pathogen, Ustilago maydis. For this initial survey, we examined EV-enriched fractions from axenic filamentous cultures that mimic infectious hyphae. EV-associated RNAs were resistant to degradation by RNases and the presence of intact mRNAs was evident. The set of mRNAs enriched inside EVs relative to the fungal cells are functionally distinct from those that are depleted from EVs. mRNAs encoding metabolic enzymes are particularly enriched. Intriguingly, mRNAs of some known effectors and other proteins linked to virulence were also found in EVs. Furthermore, several mRNAs enriched in EVs are also upregulated during infection, suggesting that EV-associated mRNAs may participate in plant-pathogen interactions.

A novel computational framework for genome-scale alternative transcription units prediction

Alternative transcription units (ATUs) are dynamically encoded under different conditions and display overlapping patterns (sharing one or more genes) under a specific condition in bacterial genomes. Genome-scale identification of ATUs is essential for studying the emergence of human diseases caused by bacterial organisms. However, it is unrealistic to identify all ATUs using experimental techniques because of the complexity and dynamic nature of ATUs. Here, we present the first-of-its-kind computational framework, named SeqATU, for genome-scale ATU prediction based on next-generation RNA-Seq data. The framework utilizes a convex quadratic programming model to seek an optimum expression combination of all of the to-be-identified ATUs. The predicted ATUs in Escherichia coli reached a precision of 0.77/0.74 and a recall of 0.75/0.76 in the two RNA-Sequencing datasets compared with the benchmarked ATUs from third-generation RNA-Seq data. In addition, the proportion of 5'- or 3'-end genes of the predicted ATUs, having documented transcription factor binding sites and transcription termination sites, was three times greater than that of no 5'- or 3'-end genes. We further evaluated the predicted ATUs by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functional enrichment analyses. The results suggested that gene pairs frequently encoded in the same ATUs are more functionally related than those that can belong to two distinct ATUs. Overall, these results demonstrated the high reliability of predicted ATUs. We expect that the new insights derived by SeqATU will not only improve the understanding of the transcription mechanism of bacteria but also guide the reconstruction of a genome-scale transcriptional regulatory network.

Temporal Dynamic Methods for Bulk RNA-Seq Time Series Data

Dynamic studies in time course experimental designs and clinical approaches have been widely used by the biomedical community. These applications are particularly relevant in stimuli-response models under environmental conditions, characterization of gradient biological processes in developmental biology, identification of therapeutic effects in clinical trials, disease progressive models, cell-cycle, and circadian periodicity. Despite their feasibility and popularity, sophisticated dynamic methods that are well validated in large-scale comparative studies, in terms of statistical and computational rigor, are less benchmarked, comparing to their static counterparts. To date, a number of novel methods in bulk RNA-Seq data have been developed for the various time-dependent stimuli, circadian rhythms, cell-lineage in differentiation, and disease progression. Here, we comprehensively review a key set of representative dynamic strategies and discuss current issues associated with the detection of dynamically changing genes. We also provide recommendations for future directions for studying non-periodical, periodical time course data, and meta-dynamic datasets.

Multiple freeze-thaw cycles lead to a loss of consistency in poly(A)-enriched RNA sequencing

Background

Both RNA-Seq and sample freeze-thaw are ubiquitous. However, knowledge about the impact of freeze-thaw on downstream analyses is limited. The lack of common quality metrics that are sufficiently sensitive to freeze-thaw and RNA degradation, e.g. the RNA Integrity Score, makes such assessments challenging.

Results

Here we quantify the impact of repeated freeze-thaw cycles on the reliability of RNA-Seq by examining poly(A)-enriched and ribosomal RNA depleted RNA-seq from frozen leukocytes drawn from a toddler Autism cohort. To do so, we estimate the relative noise, or percentage of random counts, separating technical replicates. Using this approach we measured noise associated with RIN and freeze-thaw cycles. As expected, RIN does not fully capture sample degradation due to freeze-thaw. We further examined differential expression results and found that three freeze-thaws should extinguish the differential expression reproducibility of similar experiments. Freeze-thaw also resulted in a 3′ shift in the read coverage distribution along the gene body of poly(A)-enriched samples compared to ribosomal RNA depleted samples, suggesting that library preparation may exacerbate freeze-thaw-induced sample degradation.

Conclusion

The use of poly(A)-enrichment for RNA sequencing is pervasive in library preparation of frozen tissue, and thus, it is important during experimental design and data analysis to consider the impact of repeated freeze-thaw cycles on reproducibility.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07381-z.

RNAseq Analysis of Rodent Spaceflight Experiments Is Confounded by Sample Collection Techniques

To understand the physiological changes that occur in response to spaceflight, mice are transported to the International Space Station (ISS) and housed for variable periods of time before euthanasia on-orbit or return to Earth. Sample collection under such difficult conditions introduces confounding factors that need to be identified and addressed. We found large changes in the transcriptome of mouse tissues dissected and preserved on-orbit compared with tissues from mice euthanized on-orbit, preserved, and dissected after return to Earth. Changes due to preservation method eclipsed those between flight and ground samples, making it difficult to identify spaceflight-specific changes. Follow-on experiments to interrogate the roles of euthanasia methods, tissue and carcass preservation protocols, and library preparation methods suggested that differences due to preservation protocols are exacerbated when coupled with polyA selection. This has important implications for the interpretation of existing datasets and the design of future experiments.

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Experimentation is necessary to understand how organisms respond to space

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Specialized protocols are used for preserving biological samples on the ISS

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RNAseq datasets are impacted by preservation protocols used on the ISS

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Impacts can be alleviated with improved carcass preservation protocols

Classification models using circulating neutrophil transcripts can detect unruptured intracranial aneurysm

Background

Intracranial aneurysms (IAs) are dangerous because of their potential to rupture. We previously found significant RNA expression differences in circulating neutrophils between patients with and without unruptured IAs and trained machine learning models to predict presence of IA using 40 neutrophil transcriptomes. Here, we aim to develop a predictive model for unruptured IA using neutrophil transcriptomes from a larger population and more robust machine learning methods.

Methods

Neutrophil RNA extracted from the blood of 134 patients (55 with IA, 79 IA-free controls) was subjected to next-generation RNA sequencing. In a randomly-selected training cohort (n = 94), the Least Absolute Shrinkage and Selection Operator (LASSO) selected transcripts, from which we constructed prediction models via 4 well-established supervised machine-learning algorithms (K-Nearest Neighbors, Random Forest, and Support Vector Machines with Gaussian and cubic kernels). We tested the models in the remaining samples (n = 40) and assessed model performance by receiver-operating-characteristic (ROC) curves. Real-time quantitative polymerase chain reaction (RT-qPCR) of 9 IA-associated genes was used to verify gene expression in a subset of 49 neutrophil RNA samples. We also examined the potential influence of demographics and comorbidities on model prediction.

Results

Feature selection using LASSO in the training cohort identified 37 IA-associated transcripts. Models trained using these transcripts had a maximum accuracy of 90% in the testing cohort. The testing performance across all methods had an average area under ROC curve (AUC) = 0.97, an improvement over our previous models. The Random Forest model performed best across both training and testing cohorts. RT-qPCR confirmed expression differences in 7 of 9 genes tested. Gene ontology and IPA network analyses performed on the 37 model genes reflected dysregulated inflammation, cell signaling, and apoptosis processes. In our data, demographics and comorbidities did not affect model performance.

Conclusions

We improved upon our previous IA prediction models based on circulating neutrophil transcriptomes by increasing sample size and by implementing LASSO and more robust machine learning methods. Future studies are needed to validate these models in larger cohorts and further investigate effect of covariates.

Gene Expression Profiling of the Pancreas in Patients Undergoing Total Pancreatectomy With Islet Autotransplant Suggests Unique Features of Alcoholic, Idiopathic, and Hereditary Pancreatitis

OBJECTIVES

To determine if RNA collected from pancreatic tissue, without the use of RNAlater, is useful for RNA sequencing (RNA-seq) despite degradation, and if so, then, via RNA-seq analysis, how does gene expression vary between pancreatitis etiologies.

METHODS

Data were assessed in 2 dimensions, based on RNA-seq signal shape assessed by RSeQC v.2.6.4 and RNA expression after accounting for different degrees of degradation.

RESULTS

Six measures of RNA characteristics (median RNA fragment size, reads per million kilobases saturation, transcript integrity number, distribution of hexamers, percentage of nucleotides that are guanine or cytosine, and duplicated reads) were significantly different between hereditary pancreatitis and idiopathic pancreatitis. Differential expression analysis revealed that 150 genes were differentially expressed between hereditary and idiopathic etiologies, 197 genes were differentially expressed between alcoholic and idiopathic etiologies, and 200 genes were differentially expressed between alcoholic and hereditary etiologies. We then determined that many enriched pathways between hereditary and idiopathic etiologies are related to the matrisome, and many of the enriched pathways between alcoholic and idiopathic etiology or hereditary etiology are related to ion transport.

CONCLUSIONS

We found distinct RNA-seq signals between different pancreatitis etiologies in both of the dimensions in critical pathways for pancreas biology.

Reliable and robust droplet digital PCR (ddPCR) and RT-ddPCR protocols for mouse studies

Droplet digital PCR (ddPCR) is a recent method developed for the quantification of nucleic acids sequences. It is an evolution of PCR methodology incorporating two principal differences: a PCR reaction is performed in thousands of water-oil emulsion droplets and fluorescence is measured at the end of PCR amplification. It leads to the precise and reproducible quantification of DNA and RNA sequences. Here, we present quantitative methods for DNA and RNA analysis using Bio-Rad QX100 or QX200 systems, respectively. The aim of these methods is to provide useful molecular tools for validating genetically altered animal models such as those subject to CRISPR/Cas9 genome editing, as well for expression or CNV studies. A standard procedure for simultaneous DNA and RNA extraction adapted for mouse organs is also described. These methods were initially designed for mouse studies but also work for samples from other species like rat or human. In our lab, thousands of samples and hundreds of target genes from genetically altered lines were examined using these methods. This large dataset was analyzed to evaluate technical optimizations and limitations. Finally, we propose additional recommendations to be included in dMIQE (Minimum information for publication of quantitative digital PCR experiments) guidelines when using ddPCR instruments.