Animal Molecular Breeding 2024, Vol.14, No.1, 130-140 http://animalscipublisher.com/index.php/amb 133 3.2 Case studies of successful integration Several case studies highlight the successful integration of genomics and remote sensing in wildlife monitoring. For example, genomic tools have been used to monitor European wildcat populations by optimizing microfluidic SNP panels for individual identification and population structure assessment, which can be complemented with remote sensing data on habitat changes (Thaden et al., 2020) (Figure 1). In marine environments, genomic methods such as qPCR and DNA barcoding have been integrated with remote sensing to provide rapid and accurate assessments of marine health status, demonstrating the added value of combining these technologies (Bourlat et al., 2013). Figure 1 Power of the ID SNP panel to distinguish individuals (a) and reconstruct kinships (b) (Adopted from Thaden et al., 2020) Image caption: (a) Relationship between the number of genotyped SNP loci and probability of identity (PID) and probability of identity between siblings (PIDsib). Loci were ranked according to highest heterozygosity (HE). A cut-off of 0.0001 was used because it is considered as sufficiently low for most applications involving natural populations (Waits et al., 2001). (b) Assignments of parentage or siblingship as calculated with ml-relate (Kalinowski et al., 2006) compared to known pedigrees of a domestic cat family. Circles represent females and squares represent males. Shaded symbols represent individuals not known or sampled. Assignments for single parent–offspring relationships are highlighted with grey dashed lines, and sibling relationships with dotted lines. PO, parent–offspring; FS, full siblingship (Adopted from Thaden et al., 2020) The research results of Thaden et al. (2020) provide insights into the efficacy of single nucleotide polymorphism (SNP) panels in distinguishing individual identities and reconstructing kinships in a domestic cat family. The graph in panel (a) shows that as the number of genotyped SNP loci increases, the probability of identity (PID) and the probability of identity between siblings (PIDsib) decreases sharply, indicating the effectiveness of using a higher number of loci for accurate genetic differentiation. A cut-off of 0.0001 for PID is deemed sufficiently low for most natural population applications, ensuring reliable individual identification.Panel (b) illustrates the application of these genetic markers in assigning parentage and sibling relationships within a known cat pedigree. The use of the software ml-relate for genetic analysis aligns well with the known pedigrees, validating its utility in accurately determining familial relationships. This approach highlights the robustness of SNP panels in genetic studies involving natural populations and domestic animals. Another notable example is the integration of genomic and remote sensing data to study the phenology and evolution of plant species under global change. Genome-wide RNA sequencing and DNA metabarcoding have been used alongside remote sensing to monitor functional traits and predict biodiversity changes, showcasing the potential of this synergistic approach (Yamasaki et al., 2017). 3.3 Technological and data integration challenges Despite the promising potential, integrating genomics and remote sensing technologies presents several challenges. One major challenge is the need for standardized methodologies and data formats to ensure compatibility and
RkJQdWJsaXNoZXIy MjQ4ODY0NQ==