Identification of Ancestry Informative Markers in Mediterranean Trout Populations of Molise (Italy): A Multi-Methodological Approach with Machine Learning

Abstract

Brown trout (Salmo trutta), like many other freshwater species, is threated by the release in its natural environment of alien species and the restocking with allochthonous conspecific stocks. Many conservation projects are ongoing and several morphological and genetic tools have been proposed to support activities aimed to restore genetic integrity status of native populations. Nevertheless, due to the complexity of degree of introgression reached up after many generations of crossing, the use of dichotomous key and molecular markers, such as mtDNA, LDH-C1* and microsatellites, are often not sufficient to discriminate native and admixed specimens at individual level. Here we propose a reduced panel of ancestry-informative SNP markers (AIMs) to support on field activities for Mediterranean trout management and conservation purpose. Starting from the genotypes data obtained on specimens sampled in the main two Molise’s rivers (Central-Southern Italy), a 47 AIMs panel was identified and validated on simulated and real hybrid population datasets, mainly through a Machine Learning approach based on Random Forest classifier. The AIMs panel proposed may represent an interesting and cost-effective tool for monitoring the level of introgression between native and allochthonous trout population for conservation purpose and this methodology could be also applied in other species.

The role of semen cryobanks for protecting endangered native salmonids: Advantages and perspectives as outlined by the LIFE Nat.Sal.Mo. project on Mediterranean brown trout (Molise region – Italy)

“…More in detail, since the beginning of the project, N=672 individuals were genotyped through the 57 K rainbow trout Axiom SNP array. The genetic ancestry was estimated using ADMIXTURE software v.1.3.0 with K = 2 population cluster, roughly corresponding to "native" and "alien" trout population inhabiting Molise rivers (Palombo et al, 2021;Salvatore et al, 2022). SNP's analysis was combined withPCR-RFLP analysis of mitochondrial (16s rDNA; McMeel et al, 2001) and nuclear (LDH-C1*; Chiesa et al, 2016) markers, which provide an extensive genetic characterization of Mediterranean brown trout population in many studies (Penserini et al, 2006;Splendiani et al, 2006;Rossi et al, 2019;Lorenzoni et al, 2019;Salvatore et al, 2022), For gametes collection we prioritized tagged individuals genotyped by the combination of SNP array and PCR-RFLP analysis.…”

Natural clines and human management impact the genetic structure of Algerian honey bee populations

“…Finally, we performed a machine learning (ML) approach to select a reduced set of 96 single nucleotide polymorphisms (SNPs) with the aim of differentiating the Algerian subspecies from the European ones, to aid in conservation management. For such purposes, combining high-throughput sequencing and ML has the potential of making a significant impact on genetic characterization analysis across various taxa, as already shown for instance in cattle, pig, sheep and trout [ 19 – 22 ]. We also demonstrated the efficiency of our SNP set in a study simulating an F1 and several reciprocal backcross populations between Algerian and European genetic backgrounds.…”