HCR of the gut of young and old killifish males and females

<p dir="ltr">Aging is associated with progressive tissue dysfunction, leading to frailty and mortality. Characterizing aging features, such as changes in gene expression and dynamics, that are shared across tissues or specific to each tissue, is crucial for understanding the systemic and local factors contributing to the aging process. We performed RNA-sequencing on 13 tissues at six different ages in the African turquoise killifish, the shortest-lived vertebrate that can be raised in captivity. This comprehensive, sex-balanced 'atlas' dataset revealed the varying strength of sex-age interactions across killifish tissues and the age-altered biological genes and pathways that are evolutionarily conserved in mice and humans. We identified 47 genes that were consistently changed with age across at least six tissues and had human orthologs. We validated a top-upregulated gene, a noncoding RNA (<i>ncRNA-3777</i>), and a top-downregulated gene, the conserved IGF2 regulator (<i>IGF2BP3</i>). Demonstrating the utility of this resource, we discovered a female-biased myeloid shift with age in the head kidney, which is supported by single-cell deconvolution and FACS analysis. Additionally, we developed tissue-specific 'transcriptomic clocks' and identified biomarkers that predict chronological age. We demonstrated the importance of sex-specific clocks for selected tissues, validated these tissue clocks using an independent transcriptomic dataset, and used them to evaluate various lifespan interventions (diet, genetic mutants, and microbiome transfer) in the killifish. Our work provides a comprehensive resource for studying aging dynamics across tissues in the killifish, a powerful vertebrate aging model.</p><p dir="ltr">The images included in this dataset were generated from an HCR-immunofluorescence (IF) experiment designed to detect two mRNAs: <i>IGF2BP3</i> (<i>LOC107383282</i>) and <i>ncRNA-3777</i> (<i>LOC107373777</i> or <i>LOC129165246</i> in the 2024 NfuGRZ-RIMD1 reference genome in the Genome release). The channel information is as follows: <i>IGF2BP3</i> in channel 1 (AF546), DAPI in channel 2 (DAPI), and <i>ncRNA-3777</i> in channel 3 (AF647).</p><p dir="ltr">Sample information is as follows (o = old; y = young; f = female; m = male):</p><p dir="ltr">ShortName, Age, Sex</p><p dir="ltr">A5, o, f</p><p dir="ltr">B6, o, f</p><p dir="ltr">D3, o, f</p><p dir="ltr">C4, o, f</p><p dir="ltr">A3, y, f</p><p dir="ltr">B5, y, f</p><p dir="ltr">C1, y, f</p><p dir="ltr">C8, y, f</p><p dir="ltr">A1, o, m</p><p dir="ltr">B4, o, m</p><p dir="ltr">C3, o, m</p><p dir="ltr">D2, o, m</p><p dir="ltr">A6, y, m</p><p dir="ltr">B8, y, m</p><p dir="ltr">D5, y, m</p><p dir="ltr">D7, y, m</p><p><br></p><p dir="ltr">The slides were imaged using a Zeiss LSM900 confocal laser scanning microscope (Zeiss) equipped with Zen 3.0 (blue edition) software, a Zeiss Plan-Apochromat 40x/1.4 oil objective, and Zeiss Immersol oil 518F (Zeiss, 4Y00-R0DY-1007-3VF3) as the immersion medium. The imaging conditions were the following: 9-slice z-stacks with a step size of 0.75 µm; the Alexa Fluor 546 channel (laser at 1%, detector gain: 775V, detector offset: 256, detector digital gain: 1.0); the Alexa Fluor 647 channel (laser at 8.0%, detector gain: 650V, detector offset: 512, detector digital gain: 1.0); and DAPI (laser at 0.5%, detector gain: 650V, detector offset: 256, detector digital gain: 1.0). Four fields of view per tissue section and four animals per condition were imaged. All images were taken in comparable regions across biological replicates, specifically along the caudal-rostral axis of the ‘Swiss roll’ for the gut (using individual villi as landmarks).</p>