Use Of Single Nucleotide Polymorphisms Research Articles

Single nucleotide gene polymorphisms (SNPs) as markers of the increased risk of health disorders associated with exposure to industrial noise

It is known that the same environmental factors, including industrial ones, with the same intensity of exposure can cause different responses of the human body depending on its individual characteristics, which are determined, inter alia, by the presence and combination of single-nucleotide polymorphisms of genes responsible for the specificity of the human body's response to stress factors, which causes the importance of their study from the point of view of prevention of public health disorders.
 Based on the generalization and systematization of modern domestic and foreign experience, the authors have examined the use of single-nucleotide polymorphisms of genes as markers of increased risk of health disorders associated with exposure to noise in the workplace.
 Scientists have identified a list of specific single-nucleotide polymorphisms of genes, the presence of which can affect the development of health disorders when exposed to noise.
 It is shown that the use of genetic markers to assess the individual risk of health disorders of persons working under the influence of industrial noise will contribute to the development of personalized medicine and timely prevention of occupational and general diseases associated with exposure to harmful working conditions. The authors have selected for review publications devoted to studies of the body's response to industrial noise, with access to the full text.

Building Phylogenetic Trees From Genome Sequences With kSNP4.

Performing phylogenetic analysis with genome sequences maximizes the information used to estimate phylogenies and the resolution of closely related taxa. The use of single-nucleotide polymorphisms (SNPs) permits estimating trees without genome alignments and permits the use of data sets of hundreds of microbial genomes. kSNP4 is a program that identifies SNPs without using a reference genome, estimates parsimony, maximum likelihood, and neighbor-joining trees, and is able to annotate the discovered SNPs. kSNP4 is a command-line program that does not require any additional programs or dependencies to install or use. kSNP4 does not require any programming experience or bioinformatics experience to install and use. It is suitable for use by students through senior investigators. It includes a detailed user guide that explains all of the many features of kSNP4. In this study, we provide a detailed step-by-step protocol for downloading, installing, and using kSNP4 to build phylogenetic trees from genome sequences.

Genetic predictors of neurocognitive outcomes in survivors of pediatric brain tumors

BackgroundNeurocognitive deficits are common in pediatric brain tumor survivors. The use of single nucleotide polymorphism (SNP) analysis in DNA repair genes may identify children treated with radiation therapy for brain tumors at increased risk for treatment toxicity and adverse neurocognitive outcomes.MaterialsThe Human 660W-Quad v1.0 DNA BeadChip analysis (Illumina) was used to evaluate 1048 SNPs from 59 DNA repair genes in 46 subjects. IQ testing was measured by the Wechsler Intelligence Scale for Children. Linear regression was used to identify the 10 SNPs with the strongest association with IQ scores while adjusting for radiation type.ResultsThe low vs high IQ patient cohorts were well matched for time from first treatment to most recent IQ, first treatment age, sex, and treatments received. 5 SNPs on 3 different genes (CYP29, XRCC1, and BRCA1) and on 3 different chromosomes (10, 19, and 17) had the strongest association with most recent IQ score that was not modified by radiation type. Furthermore, 5 SNPs on 4 different genes (WRN, NR3C1, ERCC4, RAD51L1) on 4 different chromosomes (8, 5, 16, 14) had the strongest association with change in IQ independent of radiation type, first IQ, and years between IQ measures.ConclusionsSNPs offer the potential to predict adverse neurocognitive outcomes in pediatric brain tumor survivors. Our results require validation in a larger patient cohort. Improving the ability to identify children at risk of treatment related neurocognitive deficits could allow for better treatment stratification and early cognitive interventions.

Detection and distribution of two dominant alleles associated with the sweet kernel phenotype in almond cultivated germplasm.

Almond [Prunus dulcis Miller (D. A. Webb), syn. Prunus amygdalus L.)] is the major tree nut crop worldwide in terms of production and cultivated area. Almond domestication was enabled by the selection of individuals bearing sweet kernels, which do not accumulate high levels of the toxic cyanogenic glucoside amygdalin. Previously, we showed that the Sweet kernel (Sk) gene, controlling the kernel taste in almond, encodes a basic helix loop helix (bHLH) transcription factor regulating the amygdalin biosynthetic pathway. In addition, we characterized a dominant allele of this gene, further referred to as Sk-1, which originates from a C1036→T missense mutation and confers the sweet kernel phenotype. Here we provide evidence indicating that the allele further referred to as Sk-2, originally detected in the cultivar "Atocha" and arising from a T989→G missense mutation, is also dominantly inherited and confers the sweet kernel phenotype in almond cultivated germplasm. The use of single nucleotide polymorphism (SNP) data from genotyping by sequencing (GBS) for population structure and hierarchical clustering analyses indicated that Sk-2 occurs in a group of related genotypes, including the widespread cultivar "Texas", descending from the same ancestral population. KASP and dual label functional markers were developed for the accurate and high-throughput selection of the Sk-1 and Sk-2 alleles, and the genotyping of a panel of 134 almond cultivars. Overall, our results provide further insights on the understanding of the almond cultivation history. In addition, molecular marker assays and genotypic data presented in this study are expected to be of major interest for the conduction of almond breeding programs, which often need to select sweet kernel individuals in segregant populations.

Evaluation of parentage testing using single nucleotide polymorphism markers for draft horses in Japan.

We evaluated the utility of single nucleotide polymorphism (SNP) markers for parentage testing in Breton (BR) and Percheron (PR) horses in Japan using the proposed International Society for Animal Genetics (P-ISAG) 147 SNP panel and 414 autosomal SNPs. Genomic DNA was extracted from 98 horses of two breeds, BR (n = 47) and PR (n = 51), and sequenced using next-generation sequencing. The average minor allele frequencies for the P-ISAG panel for BR and PR were 0.306 and 0.301, respectively. The combined probabilities of exclusion (PEs) given two parents and one offspring: exclude a relationship (PE01) and given one parent and one offspring: exclude their relationship (PE02) were over 0.9999 for both breeds. Using the P-ISAG panel, no exclusion or doubtful cases were identified in 35 valid parent-offspring pairs, suggesting that the P-ISAG panel is helpful for parentage verification in both breeds. In contrast, as 0.18% of falsely accepted parentages were observed in the parentage discovery cases, additional markers such as the combination of the P-ISAG panel and 414 autosomal SNPs (561-SNP set) presented here should be used to identify valid parent-offspring pairs of horses with unknown parentage relationships.

GenoDrawing: An Autoencoder Framework for Image Prediction from SNP Markers.

Advancements in genome sequencing have facilitated whole-genome characterization of numerous plant species, providing an abundance of genotypic data for genomic analysis. Genomic selection and neural networks (NNs), particularly deep learning, have been developed to predict complex traits from dense genotypic data. Autoencoders, an NN model to extract features from images in an unsupervised manner, has proven to be useful for plant phenotyping. This study introduces an autoencoder framework, GenoDrawing, for predicting and retrieving apple images from a low-depth single-nucleotide polymorphism (SNP) array, potentially useful in predicting traits that are difficult to define. GenoDrawing demonstrates proficiency in its task using a small dataset of shape-related SNPs. Results indicate that the use of SNPs associated with visual traits has substantial impact on the generated images, consistent with biological interpretation. While using substantial SNPs is crucial, incorporating additional, unrelated SNPs results in performance degradation for simple NN architectures that cannot easily identify the most important inputs. The proposed GenoDrawing method is a practical framework for exploring genomic prediction in fruit tree phenotyping, particularly beneficial for small to medium breeding companies to predict economically substantial heritable traits. Although GenoDrawing has limitations, it sets the groundwork for future research in image prediction from genomic markers. Future studies should focus on using stronger models for image reproduction, SNP information extraction, and dataset balance in terms of phenotypes for more precise outcomes.

172 Developing Genomic Tools for Bison

Abstract Genomic tools are increasingly being used in livestock production due to their practical applications in production management and animal genetic improvement balanced with a price point that is acceptable to the livestock producer. Our program developed three genetic tools for the bison industry, including Parentage Verification, Subspecies Composition, and Cattle Introgression. The development of these tools occurred in two phases. The first was to use whole genome sequencing to discover single nucleotide polymorphisms (SNPs) in bison; approximately 52.5 million biallelic SNPs were discovered from 21 bison animals with high quality sequence data. The second phase was to select a subset of the SNPs for use on a genotyping assay that would ultimately consist of the SNP content for the commercial tool. The resulting genomic tools may provide an opportunity to increase the sustainability, competitiveness, and profitability of the bison industry from both production and conservation perspectives.

An evolutionary look into the history of lentil reveals unexpected diversity

The characterization and preservation of genetic variation in crops is critical to meeting the challenges of breeding in the face of changing climates and markets. In recent years, the use of single nucleotide polymorphisms (SNPs) has become routine, allowing us to understand the population structure, find divergent lines for crosses, and illuminate the origin of crops. However, the focus on SNPs overlooks other forms of variation, such as copy number variation (CNVs). Lentil is the third most important cold‐season legume and was domesticated in the Fertile Crescent. We genotyped 324 accessions that represent its global diversity, and using both SNPs and CNVs, we dissected the population structure and genetic variation, and identified candidate genes. Eight clusters were detected, most of them located in or near the Fertile Crescent, even though different clusters were present in distinct regions. The cluster from South Asia was particularly differentiated and presented low diversity, contrasting with the clusters from the Mediterranean and the northern temperate. Accessions from North America were mainly assigned to one cluster and were highly diverse, reflecting the efforts of breeding programs to integrate variation. Thirty‐three genes were identified as candidates under selection and among their functions were sporopollenin synthesis in pollen, a component of chlorophyll B reductase that partially determines the antenna size, and two genes related to the import system of chloroplasts. Eleven percent of all lentil genes and 21% of lentil disease resistance genes were affected by CNVs. The gene categories overrepresented in these genes were “enzymes,” “Cell Wall Organization,” and “external stimuli response.” All the genes found in the latter were associated with pathogen response. CNVs provided information about population structure and might have played a role in adaptation. The incorporation of CNVs in diversity studies is needed for a broader understanding of how they evolve and contribute to domestication.

SNP Genotyping for Purity Assessment of a Forage Oat (Avena sativa L.) Variety from Colombia

Single nucleotide polymorphism (SNP) markers have multiple applications in plant breeding of small grains. They are used for the selection of divergent parents, the identification of genetic variants and marker-assisted selection. However, the use of SNPs in varietal purity assessment is under-reported, especially for multi-line varieties from the public sector. In the case of variety evaluation, these genetic markers are tools for maintaining varietal distinctness, uniformity and stability needed for cultivar release of multi-line or pure-line varieties of inbred crops. The objective of this research was to evaluate the purity and relationships of one original (AV-25) and two multi-line sub-populations (AV25-T and AV25-S) of the inbreeding species, oats (Avena sativa L.). Both sub-populations could be useful as forages in the central highland region of Colombia (>2000 masl), such as in the departments of Boyacá and Cundinamarca, even though they were derived from an original composite mixture widely used in the mountainsides of the southern department of Nariño named Avena 25. Representative single plant selections (SPS) from the two sub-populations were grown together with SPS harvests from off-type plants (early and late) and plants from the original AV25 composite mixture, to determine their genetic similarity. Plants were genotyped by DNA extraction of a plateful of 96 individual plant samples and SNPs were detected for an Illumina Infinium 6K Chip assay. The data were used for the analysis of genetic structure and population relationships. The grouping observed based on the genetic data indicated that AV25-T and AV25-S were homogeneous populations and somewhat divergent in their genetic profile compared to the original AV25-C mix. In addition, to the two commercial, certified oat varieties (Cajicá and Cayuse) were different from these. The early and late selections were probable contaminants and could be discarded. We concluded that the use of SNP markers is an appropriate tool for ensuring genetic purity of oat varieties.

Study of interactions between HTRA1 gene polymorphism and retinal pigment epithelial phenotype in age-related macular degeneration

Annotation. Age-related macular degeneration is a multifactorial nosology caused by the interaction of various risk factors, but the pathogenesis remains unclear. An alternative point of application in the pathogenesis of the disease was the product of the HTRA1 gene, which is actively expressed in retinal epithelial cells and modulates their response to stimuli. That is why the aim of our study was to elucidate the effect of the rs11200638 polymorphism of the HTRA1 gene on the occurrence and development of age-related macular degeneration and to determine the intensity of this pathological effect. The study group consisted of 291 individuals, while the comparison group consisted of 105 individuals of the appropriate age. Optical coherence tomography of the macular area of the retina using the ILM-RPE parameter was used to establish the diagnosis. Real-time polymerase chain reaction was used to detect polymorphism on the BioRad CFX 96 thermocycler-amplifier. Statistical processing of the results was performed by determining Hardy-Weinberg equilibrium, Kruskal-Wallace methods, logistic regression using OR and 95% CI curves and indicators of sensitivity and specificity. The study found a predominance of wild type among the comparison group, while heterozygous and mutant genotypes were almost equally distributed among patients with “dry” and “wet” forms of age-related macular degeneration (AMD). A statistically significant associative association was found between the mutant allele A and the occurrence of both atrophic (OR=7.75; 95% CI 3.87-15.49) and neovascular (OR=3.3; 95% CI 1, 89-5.91) forms of AMD (p<0.001). Subsequent analysis revealed a significant statistical relationship between variant AA and “wet” AMD (OR=21.3; 95% CI 2.57-176.8; p<0.001), as well as between heterozygous variant and “dry” (OR=7.7; 95% CI 3.8-15.46) and “wet” (OR=2.45; 95% CI 1.36-4.43) forms of the disease (p <0.01). In addition, the use of single nucleotide polymorphism (SNP) rs11200638 allows with a specificity of 59.2-98.4% and a sensitivity of 12.5-83.9% to diagnose AMD, depending on its form and the available genotype of the patient. Thus, our results indicate the high significance of the prognostic effect of the rs11200638 polymorphism of the HTRA1 gene on the development and progression of AMD, and the sensitivity and specificity indicators allow the use of the definition of this SNP to diagnose the disease.

A multipurpose panel of microhaplotypes for use with STR markers in casework

A small panel of highly informative loci that can be genotyped on the same equipment as the standard CODIS short tandem repeat (STR) markers has strong potential for application in forensic casework. Single nucleotide polymorphisms (SNPs) can be typed by a couple of methods on capillary electrophoresis (CE) machines and on sequencers, but the amount of information relative to the laboratory effort has hindered use of SNPs in actual casework. Insertion-deletion markers (InDels) suffer from similar problems. Microhaplotypes (MHs) are much more informative per locus but have similar technical difficulties unless they are typed by massively parallel sequencing (MPS). As forensic labs are acquiring sequencing machines, MHs become more likely to be used in casework, especially if multiplexed with STRs. Here we present the details of a multipurpose panel of 24 MHs with the highest effective number of alleles (Ae) from previous work. An augmented STR panel of 24 loci (20 CODIS markers plus four commonly typed STRs) is also considered. The Ae and ancestry informativeness (In) distributions of these two datasets are compared. The MH panel is shown to have better individualization and population distinction than the augmented CODIS STRs. We note that the 24 MHs should be better for mixture analyses than the STRs. Finally, we suggest that a commercial kit including both the standard CODIS markers and this set of 24 MH would greatly improve the discrimination power over that of current commercial assays.

Donor-Derived Cell-Free DNA for the Detection of Heart Allograft Injury: Impact of Timing of the Liquid Biopsy

<h3>Purpose</h3> In heart transplant recipients, donor-derived cell-free DNA (ddcfDNA) is a potential biomarker for acute rejection (AR), in that increased values may indicate rejection. Blood plasma sampling around the endomyocardial biopsy (EMB) seems a practical approach for the assessment of ddcfDNA. Nevertheless, the EMB procedure itself might also induce injury and therefore a rise in ddcfDNA values. Here, the effect of the EMB procedure was evaluated by pairwise comparing ddcfDNA values before EMB to ddcfDNA values after EMB. <h3>Methods</h3> Plasma samples from in total 15 heart transplant recipients were obtained pre-EMB and post-EMB. A droplet digital PCR (ddPCR) method was used for measuring ddcfDNA, making use of single-nucleotide polymorphisms (SNPs) that allowed both absolute quantification in copies/mL as well as relative quantification of ddcfDNA (ddcfDNA% of total cfDNA). <h3>Results</h3> The median (IQR) pre-EMB ddcfDNA concentration was 7.5 (3.0-14.5) copies/mL and increased significantly to 9.6 (5.4-20.8) copies/mL post-EMB, corresponding to a 1.28-fold increase (n=113; p=0.007). DdcfDNA% increased significantly from 0.08% (0.00-0.14) pre-EMB to 0.10% (0.02-0.20) post-EMB, corresponding to a 1.31-fold increase in ddcfDNA% (n=113; p=0.03). DdcfDNA concentration and ddcfDNA% demonstrated a comparable fold increase after the EMB procedure. This suggests that variations in total recipient cfDNA due to the EMB procedure is small or even absent. <h3>Conclusion</h3> The EMB procedure causes iatrogenic injury to the heart allograft that results in an increase in ddcfDNA% and ddcfDNA concentration. For the assessment of ddcfDNA as marker for AR in heart transplant recipients, collection of plasma samples before the EMB procedure is therefore essential.

Donor-Derived Cell-Free DNA for the Detection of Heart Allograft Injury: The Impact of the Timing of the Liquid Biopsy.

Background: In heart transplant recipients, donor-derived cell-free DNA (ddcfDNA) is a potential biomarker for acute rejection (AR), in that increased values may indicate rejection. For the assessment of ddcfDNA as new biomarker for rejection, blood plasma sampling around the endomyocardial biopsy (EMB) seems a practical approach. To evaluate the effect of the EMB procedure on ddcfDNA values, ddcfDNA values before the EMB were pairwise compared to ddcfDNA values after the EMB. We aimed at evaluating whether it matters whether the ddcfDNA sampling is done before or after the EMB-procedure. Methods: Plasma samples from heart transplant recipients were obtained pre-EMB and post-EMB. A droplet digital PCR method was used for measuring ddcfDNA, making use of single-nucleotide polymorphisms that allowed both relative quantification, as well as absolute quantification of ddcfDNA. Results: Pairwise comparison of ddcfDNA values pre-EMB with post-EMB samples (n = 113) showed significantly increased ddcfDNA concentrations and ddcfDNA% in post-EMB samples: an average 1.28-fold increase in ddcfDNA concentrations and a 1.31-fold increase in ddcfDNA% was observed (p = 0.007 and p = 0.03, respectively). Conclusion: The EMB procedure causes iatrogenic injury to the allograft that results in an increase in ddcfDNA% and ddcfDNA concentrations. For the assessment of ddcfDNA as marker for AR, collection of plasma samples before the EMB procedure is therefore essential.

SNP-based phylogenomic inference in Holarctic ground squirrels (Urocitellus)

Resolution of rapid evolutionary radiatons requires harvesting maximal signal from phylogenomic datasets. However, studies of non-model clades often target conserved loci that are characterized by reduced information content, which can negatively affect gene tree precision and species tree accuracy. Single nucleotide polymorphism (SNP)-based methods are an underutilized but potentially valuable tool for estimating phylogeny and divergence times because they do not rely on resolved gene trees, allowing information from many or all variant loci to be leveraged in species tree reconstruction. We evaluated the utility of SNP-based methods in resolving phylogeny of Holarctic ground squirrels (Urocitellus), a radiation that has been difficult to disentangle, even in prior phylogenomic studies. We inferred phylogeny from a dataset of >3,000 ultraconserved element loci (UCEs) using two methods (SNAPP, SVDquartets) and compared our results with a new mitogenome phylogeny. We also systematically evaluated how phasing of UCEs improves per-locus information content, inference of topology, and other parameters within each of these SNP-based methods. Phasing improved topological resolution and branch length estimation at shallow levels (within species complexes), but less so at deeper levels, likely reflecting true uncertainty due to ancestral polymorphisms segregating in rapidly diverging lineages. We resolved key clades in Urocitellus and present targeted opportunities for future phylogenomic inquiry. Our results also extend the roadmap for use of SNPs to address vertebrate radiations and inform comparative analyses at multiple temporal scales.

Species Tree Inference with SNP Data.

While the inference of species trees from molecular sequences has become a common type of analysis in studies of species diversification, few programs so far allow for the use of single-nucleotide polymorphisms (SNPs) for the same purpose. In this book chapter, I discuss the use of the Bayesian program SNAPP, which infers the species tree by mathematically integrating over all possible genealogies at each SNP. In particular, I focus on a molecular clock model developed for SNAPP, allowing the inference of divergence times together with the species tree topology and the population size, directly from SNP datasets in variant call format. With the growing availability of SNP datasets for multiple closely related species, this approach is becoming increasingly relevant for the reconstruction of the temporal framework of recent species diversification.

Genetic polymorphisms of reproductive hormones and their receptors in assisted reproduction technology for patients with polycystic ovary syndrome.

Polycystic ovary syndrome (PCOS) is one of the most common endocrinopathies in women of childbearing, which is defined by the accumulation of multiple, small fluid-filled ovarian cysts without the selection of a single dominant follicle. Most PCOS phenotypes are characterized by the absence of spontaneous ovulation, resistance toward ovulation inductors, the production of a large immature oocytes number, and the high prevalence of ovarian hyperstimulation syndrome, resulting in reduced assisted reproductive technologies (ART) programs effectiveness. The review analyses current data about the relationship between polymorphism genotypes of KISS genes, follicle stimulating hormone (FSH), luteinizing hormone (LH), anti-Müllerian hormone (AMH) and their receptors genes, gonadotropin-releasing hormone (GnRH), estrogen, and progesterone receptors genes, the PCOS risk and the features of ovarian response to stimulation during ART cycles. The use of single nucleotide polymorphisms (SNPs) as prognostic markers of ART programs outcomes would provide a personalized approach to the drugs and doses choice for ovarian stimulation and significantly increase the chance of pregnancy.

Cross-sectional study of the association of 5 single nucleotide polymorphisms with enalapril treatment response among South African adults with hypertension.

This study investigates the association of 5 single nucleotide polymorphisms (SNPs) in selected genes (ABO, VEGFA, BDKRB2, NOS3, and ADRB2) with blood pressure (BP) response to enalapril. The study further assessed genetic interactions that exist within these genes and their implications in enalapril treatment response among South African adults with hypertension.A total of 284 participants belonging to the Nguni tribe of South Africa on continuous treatment for hypertension were recruited. Five SNPs in enalapril pharmacogenes were selected and genotyped using MassArray. Uncontrolled hypertension was defined as BP ≥140/90 mm Hg. The association between genotypes, alleles, and BP response to treatment was determined by fitting multivariate logistic regression model analysis, and genetic interactions between SNPs were assessed by multifactor dimensionality reduction.Majority of the study participants were female (75.00%), Xhosa (78.87%), and had uncontrolled hypertension (69.37%). All 5 SNPs were exclusively detected among Swati and Zulu participants. In the multivariate (adjusted) logistic model analysis, ADRB2 rs1042714 GC (adjusted odds ratio [AOR] = 2.31; 95% confidence interval [CI] 1.02–5.23; P = .044) and BDKRB2 rs1799722 CT (AOR = 2.74; 95% CI 1.19–6.28; P = .017) were independently associated with controlled hypertension in response to enalapril. While the C allele of VEGFA rs699947 (AOR = 0.37; 95% CI 0.15–0.94; P = .037) was significantly associated with uncontrolled hypertension. A significant interaction between rs699947, rs495828, and rs2070744 (cross-validation consistency = 10/10; P = .0005) in response to enalapril was observed.We confirmed the association of rs1042714 (ADRB2) and rs1799722 (BDKRB2) with controlled hypertension and established an interaction between rs699947 (VEGFA), rs495828 (ABO), and rs2070744 (NOS3) with BP response to enalapril. Our findings have provided substantial evidence for the use of SNPs as predictors for enalapril response among South Africans adults with hypertension.

Identification of Root Rot Resistance QTLs in Pea Using Fusarium solani f. sp. pisi-Responsive Differentially Expressed Genes.

Pisum sativum (pea) yields in the United States have declined significantly over the last decades, predominantly due to susceptibility to root rot diseases. One of the main causal agents of root rot is the fungus Fusarium solani f. sp. pisi (Fsp), leading to yield losses ranging from 15 to 60%. Determining and subsequently incorporating the genetic basis for resistance in new cultivars offers one of the best solutions to control this pathogen; however, no green-seeded pea cultivars with complete resistance to Fsp have been identified. To date, only partial levels of resistance to Fsp has been identified among pea genotypes. SNPs mined from Fsp-responsive differentially expressed genes (DEGs) identified in a preceding study were utilized to identify QTLs associated with Fsp resistance using composite interval mapping in two recombinant inbred line (RIL) populations segregating for partial root rot resistance. A total of 769 DEGs with single nucleotide polymorphisms (SNPs) were identified, and the putative SNPs were evaluated for being polymorphic across four partially resistant and four susceptible P. sativum genotypes. The SNPs with validated polymorphisms were used to screen two RIL populations using two phenotypic criteria: root disease severity and plant height. One QTL, WB.Fsp-Ps 5.1 that mapped to chromosome 5 explained 14.8% of the variance with a confidence interval of 10.4 cM. The other four QTLs located on chromosomes 2, 3, and 5, explained 5.3–8.1% of the variance. The use of SNPs derived from Fsp-responsive DEGs for QTL mapping proved to be an efficient way to identify molecular markers associated with Fsp resistance in pea. These QTLs are potential candidates for marker-assisted selection and gene pyramiding to obtain high levels of partial resistance in pea cultivars to combat root rot caused by Fsp.

Genetic and Morphological Approach for Western Corn Rootworm Resistance Management

The western corn rootworm (WCR), is one of the most serious pests of maize in the United States. In this study, we aimed to find a reliable pattern of difference related to resistance type using population genetic and geometric morphometric approaches. To perform a detailed population genetic analysis of the whole genome, we used single nucleotide polymorphisms (SNPs) markers. For the morphometric analyses, hindwings of the resistant and non-resistant WCR populations from the US were used. Genetic results showed that there were some differences among the resistant US populations. The low value of pairwise FST = 0.0181 estimated suggests a lack of genetic differentiation and structuring among the putative populations genotyped. However, STRUCTURE analysis revealed three genetic clusters. Heterozygosity estimates (HO and HE) over all loci and populations were very similar. There was no exact pattern, and resistance could be found throughout the whole genome. The geometric morphometric results confirmed the genetic results, with the different genetic populations showing similar wing shape. Our results also confirmed that the hindwings of WCR carry valuable genetic information. This study highlights the ability of geometric morphometrics to capture genetic patterns and provides a reliable and low-cost alternative for preliminary estimation of population structure. The combined use of SNPs and geometric morphometrics to detect resistant variants is a novel approach where morphological traits can provide additional information about underlying population genetics, and morphology can retain useful information about genetic structure. Additionally, it offers new insights into an important and ongoing area of pest management on how to prevent or delay pest evolution towards resistant populations, minimizing the negative impacts of resistance.

Thermal adaptation rather than demographic history drives genetic structure inferred by copy number variants in a marine fish

Increasing evidence shows that structural variants represent an overlooked aspect of genetic variation with consequential evolutionary roles. Among those, copy number variants (CNVs), including duplicated genomic region and transposable elements (TEs) may contribute to local adaptation and/or reproductive isolation among divergent populations. Those mechanisms suppose that CNVs could be used to infer neutral and/or adaptive population genetic structure, whose study has been restricted to microsatellites, mtDNA, and AFLP markers in the past and more recently the use of SNPs. Taking advantage of recent developments allowing CNV analysis from RAD-seq data, we investigated how variation in fitness-related traits, local environmental conditions and demographic history are associated with CNVs, and how subsequent copy number variation drives population genetic structure in a marine fish, the capelin (Mallotus villosus). We collected 1538 DNA samples from 35 sampling sites in the north Atlantic Ocean and identified 6620 putative CNVs. We found associations between CNVs and the gonadosomatic index, suggesting that six duplicated regions could affect female fitness by modulating oocyte production. We also detected 105 CNV candidates associated with water temperature, among which 20% corresponded to genomic regions located within the sequence of protein-coding genes, suggesting local adaptation to cold water by means of gene sequence amplification. We also identified 175 CNVs associated with the divergence of three previously defined parapatric glacial lineages, of which 24% were located within protein-coding genes, making those loci potential candidates for reproductive isolation. Lastly, our analyses unveiled a hierarchical, complex CNV population structure determined by temperature and local geography, which was in stark contrast with that inferred based on SNPs in a previous study. Our findings underscore the complementarity of those two types of genomic variation in population genomics studies.