Biology subjects

Gamboa, M.

Publications and source records attributed to Gamboa, M..

5 recordsLinked to original sources

bioRxiv2026

Optimizing DNA extraction from environmentally degraded bone samples for molecular identification of cetacean species

Molecular identification of cetacean bone remains can be limited by DNA degradation and the presence of PCR inhibitors. Here, we present an optimized DNA extraction protocol based on a total demineralization method for environmentally exposed cetacean bones. The protocol uses 100 mg of bone powder, 24 h digestion with EDTA, N-lauroylsarcosine, and proteinase K, followed by a modified silica-column purification. Nine environmentally degraded bone samples representing eight individuals were processed. DNA concentrations ranged from 7.3 to 57.1 ng/uL (mean SD = 25.91- 13.91 ng/uL). The mitochondrial cytochrome b gene was successfully amplified from all samples using conventional PCR, and five samples (55.6%) yielded sequences suitable for downstream analysis. BLASTn identified Balaenoptera physalus as the closest database match for all recovered sequences, and phylogenetic analysis further supported their association with B. physalus reference sequences. These results demonstrate that the proposed protocol provides a practical approach for recovering amplifiable and molecularly informative mitochondrial DNA from environmentally degraded cetacean bone material, facilitating molecular identification from challenging skeletal remains.

genetics↗

bioRxiv2018

Genome-wide signatures of local adaptation among seven stoneflies species along a nationwide latitudinal gradient in Japan

BackgroundEnvironmental heterogeneity continuously produces a selective pressure that results in genomic variation among organisms; understanding this relationship remains a challenge in evolutionary biology. Here, we evaluated the degree of genome-environmental association of seven stonefly species across a wide geographic area in Japan and additionally identified putative environmental drivers and their effect on co-existing multiple stonefly species. Double-digest restriction-associated DNA (ddRAD) libraries were independently sequenced for 219 individuals from 23 sites across four geographical regions along a nationwide latitudinal gradient in Japan.\n\nResultsA total of 4,251 candidate single nucleotide polymorphisms (SNPs) strongly associated with local adaptation were discovered using Latent mixed models; of these, 294 SNPs showed strong correlation with environmental variables, specifically precipitation and altitude, using distance-based redundancy analysis. Genome-genome comparison among the seven species revealed a high sequence similarity of candidate SNPs within a geographical region, suggesting the occurrence of a parallel evolution process.\n\nConclusionsOur results revealed genomic signatures of local adaptation and their influence on multiple, co-occurring species. These results can be potentially applied for future studies on river management and climatic stressor impacts.

genomics↗

bioRxiv2018

Molecular phylogeny and diversification timing of the Nemouridae family (Insecta, Plecoptera) in the Japanese Archipelago

The generation of the high species diversity of insects in Japan was profoundly influenced by the formation of the Japanese Archipelago. We explored the species diversification and biogeographical history of the Nemouridae family in the Japanese Archipelago using mitochondrial DNA and nuclear DNA markers. We collected 49 species among four genera: Indonemoura, Protonemura, Amphinemura and Nemoura in Japan, China, South Korea and North America. We estimated their divergence times--based on three molecular clock node calibrations--using Bayesian phylogeography approaches. Our results suggested that Japanese Archipelago formation events resulted in diversification events in the middle of the Cretaceous (<120 Ma), speciation in the Paleogene (<50 Ma) and intra-species diversification segregated into eastern and western Japan of the Fossa Magna region at late Neogene (20 Ma). The Indonemoura samples were genetically separated into two clades--that of Mainland China and that of Japan. The Japanese clade clustered with the Nemouridae species from North America, suggesting the possibility of a colonisation event prior to the formation of the Japanese Archipelago. We believe that our results enhanced the understanding both of the origin of the species and of local species distribution in the Japanese Archipelago.

evolutionary biology↗

bioRxiv2018

Comparison of DNA metabarcoding and morphological identification for stream macroinvertebrate biodiversity assessment and monitoring

Conventional morphology-based identification is commonly used for routine assessment of freshwater ecosystems. However, cost and time efficient techniques such as high-throughput sequencing (HTS) based approaches may resolve the constraints encountered in conducting morphology-based surveys. Here, we characterized stream macroinvertebrate species diversity and community composition via metabarcoding and morphological analysis from environmental samples collected from the Shigenobu River Basin in Ehime Prefecture, Japan. We compared diversity metrics and assessed both approaches ability to evaluate the relationship between macroinvertebrate community and environmental variables. In total, we morphologically identified 45 taxa (3 families, six subfamilies, 31 genera, and five species) from 8,276 collected individuals from ten study sites. We detected 44 species by metabarcoding, with 35 species collapsed into 11 groups matching the morphologically identified taxa. A significant positive correlation between logged depth (number of HTS reads) and abundance of morphological taxa was observed, which implied that quantitative data can be used for subsequent analyses. Relatively higher estimates of alpha diversity were calculated from the metabarcoding data in comparison to morphology-based data. However, beta diversity estimates between metabarcoding and morphology data based on both incidence and abundance-based matrices were correlated proving that community differences between sampling sites were preserved in the molecular data. Also, both models were significant, but metabarcoding data (93%) explained a relatively higher percentage of variation in the relationship between community composition and the environmental variables than morphological data (91%). Overall, we present both the feasibility and limitations of HTS-driven estimations of taxonomic richness, community composition, and diversity metrics, and that metabarcoding was proven comparable and more sensitive against morphology-based analysis for stream macroinvertebrate biodiversity assessment and environmental monitoring.

ecology↗

bioRxiv2018

Detection of adaptive divergence in populations of the stream mayfly Ephemera strigata with machine learning

Adaptive divergence is a key mechanism shaping the genetic variation of natural populations. A central question linking ecology with evolutionary biology concerns the role of environmental heterogeneity in determining adaptive divergence among local populations within a species. In this study, we examined adaptive the divergence among populations of the stream mayfly Ephemera strigata in the Natori River Basin in northeastern Japan. We used a genome scanning approach to detect candidate loci under selection and then applied a machine learning method (i.e. Random Forest) and traditional distance-based redundancy analysis (dbRDA) to examine relationships between environmental factors and adaptive divergence at non-neutral loci. We also assessed spatial autocorrelation at neutral loci to quantify the dispersal ability of E. strigata. Our main findings were as follows: 1) random forest shows a higher resolution than traditional statistical analysis for detecting adaptive divergence; 2) separating markers into neutral and non-neutral loci provides insights into genetic diversity, local adaptation and dispersal ability and 3) E. strigata shows altitudinal adaptive divergence among the populations in the Natori River Basin.

evolutionary biology↗