Do you smell what I smell? Linking inner nose phenotypic traits and their underlying olfactory receptor genes to olfactory performance based on genotype-phenotype associations. A case study in Primates (Mammalia)

哺乳动物的嗅觉能力很难通过形态学特征来评估，目前对形态学特征的研究大多脱离了对嗅觉受体基因的分析。在本项目中，我们应用比较基因组学将基因型（OR基因）与嗅觉嗅觉差的灵长类动物的鼻区表型（如形态学）联系起来，以揭示尽管鼻区缩小，但它们对气味的敏感性相对较高。我们采用创新的表型分析方法，在包括13个科的45种灵长类动物的在线数据矩阵中以数字代码给出表型特征。主要数据（例如，嗅上皮厚度和表面积，神经元密度）将根据我的两位宿主研究人员开发的一种新应用来推断：首先用微计算机断层扫描（μCT）扫描标本，或者用碘溶液进行diceCT染色，然后准备进行组织学切片。然后将鼻腔的μCT和diceCT切片与相应的数字化组织序列切片进行匹配，合并单个细胞和组织结构，重建整体虚拟3D模型。基于描述性数据收集形态和地形特征，使用几何形态计量学收集形态特征。我们进一步纳入了从文献中推断的活动模式和饮食，因为它们与嗅觉有关，并被认为也与鼻内形态相互作用。对标本收集的原始数据和关于生态/动物行为学特征的文字文献信息被转换成机器可操作的数据。通过描述性和统计分析，它们代表了与测序或基因相关的表型（与遗传学家合作）。我们考虑系统发育关系，并应用平面重建来探索鼻子表型及其相关OR基因之间的共同进化如何决定灵长类动物的嗅觉能力。我们研究了沿着选择谱系的进化约束及其对生态位占领期间适应策略的影响。通过结合两种创新方法，表型分析和互补成像技术的融合，我们为新生物和古生物学的多学科研究提供了全面的计算机可访问的表型数据，如生态相互作用、进化模式和基因型-表型关联。特别是，组织学与CT数据的合并提供了迄今为止最精确的结构复合体检查。它可以转移到任何身体部位和组织，并将促进生物学和生物医学研究。

The olfactory ability of mammals is difficult to assess based on morphological traits, which are mostly studied apart from the analyses of olfactory receptor (OR) genes. In the present project, we apply comparative genomics to associate the genotype (OR genes) with the phenotype (e.g., morphology) of the nasal region in microsmatic (poor sense of smell) primates to reveal their yet comparatively high sensitivity to odorants despite a reduced nasal region. We apply the innovative phenotyping approach, in that phenotypic traits are given in a numeric code in an online data matrix which includes 45 primate species of 13 families. The primary data (e.g., olfactory epithelium thickness and surface area, neuron density) will be inferred based on a novel application which was developed by my two host researchers: a specimen is first scanned with micro-computed tomography (μCT) or additionally stained with an iodine solution for diceCT and subsequently prepared for histological sectioning. The μCT and diceCT sections of the nasal cavity are then matched with the corresponding digitized histological serial sections to merge individual cell and tissue structures for the reconstruction of an overall virtual 3D model. Morphological and topographical traits are collected based on descriptive data, and morphometric traits by use of Geometric Morphometrics. We further include activity patterns and diets inferred from literature, as they are associated with olfaction and assumed to interact with intranasal morphology, too. The primary data collected on the specimens and the worded literature information on ecological/ethological traits are converted into machine-actionable data. They represent the phenotypes which are associated with the sequenced OR genes (collaboration with geneticists) by use of descriptive and statistical analyses. We consider phylogenetic relationships and apply grundplan reconstruction to explore how the co-evolution between the nose phenotypes and their associated OR genes determine the olfactory ability among primates. We examine evolutionary constraints along selected lineages and their effects on adaptive strategies during ecological niche occupation. By combining two innovative approaches, phenotyping and the fusion of complementary imaging techniques, we provide comprehensive computer-accessible phenotypic data for multidisciplinary research in neontology and paleontology, like ecological interactions, evolutionary patterns, and genotype-phenotype associations. Particularly, the merging of histology with CT data offers so far the most precise examination of structural complexes. It can be transferred to any body part and tissue, and will promote biological and biomedical research.