Chronic pain is poorly treated in the clinic as most available analgesics have low efficacy and can cause serious side effects. A recent survey on chronic pain shows that one in five European people suffers from chronic pain, thus, the development of new types of analgesic drugs is urgently needed (Alliance, 2017). This depends on a more detailed understanding of the molecular mechanisms underlying pain syndromes. The concept of nociceptors was introduced by neurophysiologist Sir Charles Sherrington in the early twentieth century and their existence was first demonstrated by Edward R. Perl (Sherrington, 1903; Mason, 2007; Wood, 2020). Nociceptors are specialized primary sensory neurons resident in dorsal root ganglia (DRG) and trigeminal ganglia that play a fundamental role in both acute pain and chronic pain conditions (Abrahamsen et al., 2008; Reichling and Levine, 2009; Dubin and Patapoutian, 2010; Middleton et al., 2021). DRG are located outside the blood-brain barrier rendering them an important therapeutic target of chronic pain, in particular for peripherally-acting treatments (Woolf and Ma, 2007; Sapunar et al., 2012; Price et al., 2018). Previous work has established that the expression of the sodium channel NaV1.8 defines a distinct subset of nociceptors involved in mechanical and inflammatory pain (Akopian et al., 1999; Wood, 2020). Many studies have focused on investigating pain-associated gene expression changes in DRG. Microarray profiling and RNA-Seq have been widely employed to investigate the DRG transcriptome in many species such as mouse, rat, primate, and human (Chiu et al., 2014; Gong et al., 2016; Li et al., 2016; Barry et al., 2018; Ray et al., 2018; Megat et al., 2019a,b; Yokoyama et al., 2020; Kupari et al., 2021). Among these reports, some assessed mRNA levels specifically in NaV1.8-expressing (NaV1.8+) nociceptors. For example, Thakur et al. identified 920 transcripts enriched in nociceptors using NaV1.8-tdTomato mice combined with magnetic cell sorting (MACS) and RNA-Seq technologies (Thakur et al., 2014). In 2008, we described insights into the nociceptor transcriptome of NaV1.8Cre+/−; ROSA26-flox-stop-flox-DTA (Diphtheria toxin fragment A) mutant mice (DTA), in which NaV1.8+ DRG neurons, representing mainly nociceptors, were specifically ablated by expression of DTA. More recently, subtypes of DRG neurons, including nociceptors, were identified, and distinguished by comprehensive single-cell RNA-Seq profiles in mouse and primates generating a highly valuable reference atlas of gene expression in DRG and beyond (Usoskin et al., 2015; Zeisel et al., 2018; Kupari et al., 2021). Furthermore, Megat et al. reported the translatome of NaV1.8+ DRG neurons using translating ribosome affinity purification (TRAP) and compared their data to the transcriptome elucidated by RNA-Seq (Megat et al., 2019a). Importantly, they observed only minor correlations between the translatome and transcriptome. It is well-known that transcript levels only show limited correspondence with protein abundance given diverse cellular buffering mechanisms, e.g., regulation at the level of transcription, translation, post-translation, and degradation or protein stability (Liu et al., 2016; Reimegård et al., 2021). In functional terms, proteins are the building blocks of a cell, and they are crucially implicated in determining phenotypes, including pain-related outcomes and behaviors. However, compared to the transcriptome of nociceptors, the NaV1.8+ nociceptor proteome remains undefined. We have recently shown the immense potential of defining pain-associated proteome dynamics in DRG by data-independent acquisition mass spectrometry (DIA-MS) (Rouwette et al., 2016; Barry et al., 2018; De Clauser et al., 2022). Here, we employed DIA-MS to reveal the previously unknown protein set-up of NaV1.8+ nociceptors by using aforementioned DTA mice (Abrahamsen et al., 2008). Following the workflow chart shown in Figure 1, we, in parallel, re-analyzed the raw microarray data (ArrayExpress: E-MEXP-1622) obtained in our previous study (Abrahamsen et al., 2008) using the latest version of Transcriptome Analysis Console (TAC) Software 4.0.2. Furthermore, the two datasets were compared and are presented here with Volcano plots, Venn diagrams, Pearson scatter plots and bar charts. The top 50 nociceptor-enriched transcripts/proteins can be found in Supplementary Tables 1, 2. Overall, this study provides a valuable resource atlas covering transcripts and proteins in NaV1.8+ nociceptors of mouse DRG.