Characterization Of Genetic Diversity Research Articles

Whole-genome re-sequencing reveals genetic structure and selection signals of different populations in Megalobrama amblycephala

Characterization of genetic variants is crucial for understanding the molecular mechanisms behind selected traits and enhancing the rate of genetic gain through artificial selection. This study explored the genetic diversity and population structure of blunt snout bream Megalobrama amblycephala, a key freshwater fish in Chinese aquaculture. We conducted whole-genome re-sequencing of individuals from six populations, comprising three natural and three genetically improved strains, to assess genetic diversity, population structure and the impacts of selective breeding. We identified 17,009,590 high-quality biallelic single nucleotide polymorphism (SNP) loci. Genetic diversity assessments revealed low levels of polymorphism across populations, with genetically improved strains showing moderate to high genetic differentiation from their source populations. The study also highlighted runs of homozygosity (ROH) and analyzed linkage disequilibrium (LD) decay, indicating minimal recent inbreeding and diverse recombination events among populations. Selective sweep analyses uncovered significant selection loci associated with growth and hypoxia tolerance traits. Enrichment analyses identified genes involved in olfactory signal transduction, immune response, and metabolism pathways, which are closely related to these selective traits. These findings offer insights into the genetic basis of critical traits in M. amblycephala, contributing to the conservation of germplasm resources and supporting ongoing selective breeding efforts.

Comparing Sequence-Based and Literature-Based Pathogenicity Scoring Methods for Human Variants.

Assessing the pathogenicity of genetic variants is a critical aspect of genomic medicine and precision healthcare. Over the last decades, the identification of genetic variants and their characterization has become simpler (advent of high-throughput sequencing technologies, analysis, and visualization support tools, etc.). However, the quality of assessments to distinguish benign from pathogenic variants is critical to inform clinical decision-making and improve patient outcomes. In this article, we investigate the relationships using correlation tests between the characterization of genetic variants in the literature and their pathogenicity scores computed by two state-of-the-art assessment tools (SIFT and PolyPhen-2).

Cytogenetics investigation in 151 Brazilian infertile male patients and genomic analysis in selected cases: experience of 14 years in a public genetic service

ObjectivesMale infertility accounts for approximately 30% of cases of reproductive failure. The characterization of genetic variants using cytogenomic techniques is essential for the adequate clinical management of these patients. We aimed to conduct a cytogenetic investigation of numerical and structural rearrangements and a genomic study of Y chromosome microdeletions/microduplications in infertile men derived from a single centre with over 14 years of experience.ResultsWe evaluated 151 infertile men in a transversal study using peripheral blood karyotypes and 15 patients with normal karyotypes through genomic investigation by multiplex ligation-dependent probe amplification (MLPA) or polymerase chain reaction of sequence-tagged sites (PCR-STS) techniques. Out of the 151 patients evaluated by karyotype, 13 presented chromosomal abnormalities: two had numerical alterations, and 11 had structural chromosomal rearrangements. PCR-STS detected a BPY2 gene region and RBMY2DP pseudogene region microdeletion in one patient. MLPA analysis allowed the identification of one patient with CDY2B_1 and CDY2B_2 probe duplications (CDY2B and NLGN4Y genes) and one patient with BPY2_1, BPY2_2, and BPY2_4 probe duplications (PRY and RBMY1J genes).

Characterization of genetic variability among sorghum genotypes by morphological descriptors associated with high yield and shoot fly resistance

Characterization of genetic variability among sorghum genotypes by morphological descriptors associated with high yield and shoot fly resistance

Characterization of genetic variants in children with refractory epilepsy

To analyze the characteristics of genetic variants among children with refractory epilepsy (RE). One hundred and seventeen children with RE who had presented at the Affiliated Jinhua Hospital of Zhejiang University School of Medicine from January 1, 2018 to November 21, 2019 were selected as the study subjects. The children were divided into four groups according to their ages of onset: < 1 year old, 1 ~ 3 years old, 3 ~ 12 years old, and >= 12 years old. Clinical data and results of trio-whole exome sequencing were retrospectively analyzed. In total 67 males and 50 females were included. The age of onset had ranged from 4 days to 14 years old. Among the 117 patients, 33 (28.21%) had carried pathogenic or likely pathogenic variants. The detection rates for the < 1 year old, 1 ~ 3 years old and >= 3 years old groups were 53.85% (21/39), 12.00% (3/25) and 16.98% (9/53), respectively, with a significant difference among the groups (χ2 = 19.202, P < 0.001). The detection rates for patients with and without comorbidities were 33.33% (12/36) and 25.93% (21/81), respectively (χ2 = 0.359, P = 0.549). Among the 33 patients carrying genetic variants, 27 were single nucleotide polymorphisms (SNPs) or insertion/deletions (InDels), and 6 were copy number variations (CNVs). The most common mutant genes were PRRT2 (15.15%, 5/33) and SCN1A (12.12%, 4/33). Among children carrying genetic variants, 72.73% (8/11) had attained clinical remission after adjusting the medication according to the references. 28.21% of RE patients have harbored pathogenic or likely pathogenic variants or CNVs. The detection rate is higher in those with younger age of onset. PRRT2 and SCN1A genes are more commonly involved. Adjusting medication based on the types of affected genes may facilitate improvement of the remission rate.

Characterization of genetic variants in the EGLN1/PHD2 gene identified in a European collection of patients with erythrocytosis.

Hereditary erythrocytosis is a rare hematologic disorder characterized by an excess of red blood cell production. Here we describe a European collaborative study involving a collection of 2,160 patients with erythrocytosis sequenced in ten different laboratories. We focused our study on the EGLN1 gene and identified 39 germline missense variants including one gene deletion in 47 probands. EGLN1 encodes the PHD2 prolyl 4-hydroxylase, a major inhibitor of hypoxia-inducible factor. We performed a comprehensive study to evaluate the causal role of the identified PHD2 variants: (i) in silico studies of localization, conservation, and deleterious effects; (ii) analysis of hematologic parameters of carriers identified in the UK Biobank; (iii) functional studies of the protein activity and stability; and (iv) a comprehensive study of PHD2 splicing. Altogether, these studies allowed the classification of 16 pathogenic or likely pathogenic mutants in a total of 48 patients and relatives. The in silico studies extended to the variants described in the literature showed that a minority of PHD2 variants can be classified as pathogenic (36/96), without any differences from the variants of unknown significance regarding the severity of the developed disease (hematologic parameters and complications). Here, we demonstrated the great value of federating laboratories working on such rare disorders in order to implement the criteria required for genetic classification, a strategy that should be extended to all hereditary hematologic diseases.

Genome-wide association analysis identifies ancestry-specific genetic variation associated with acute response to metformin and glipizide in SUGAR-MGH.

Characterisation of genetic variation that influences the response to glucose-lowering medications is instrumental to precision medicine for treatment of type 2 diabetes. The Study to Understand the Genetics of the Acute Response to Metformin and Glipizide in Humans (SUGAR-MGH) examined the acute response to metformin and glipizide in order to identify new pharmacogenetic associations for the response to common glucose-lowering medications in individuals at risk of type 2 diabetes. One thousand participants at risk for type 2 diabetes from diverse ancestries underwent sequential glipizide and metformin challenges. A genome-wide association study was performed using the Illumina Multi-Ethnic Genotyping Array. Imputation was performed with the TOPMed reference panel. Multiple linear regression using an additive model tested for association between genetic variants and primary endpoints of drug response. In a more focused analysis, we evaluated the influence of 804 unique type 2 diabetes- and glycaemic trait-associated variants on SUGAR-MGH outcomes and performed colocalisation analyses to identify shared genetic signals. Five genome-wide significant variants were associated with metformin or glipizide response. The strongest association was between an African ancestry-specific variant (minor allele frequency [MAFAfr]=0.0283) at rs149403252 and lower fasting glucose at Visit 2 following metformin (p=1.9×10-9); carriers were found to have a 0.94 mmol/l larger decrease in fasting glucose. rs111770298, another African ancestry-specific variant (MAFAfr=0.0536), was associated with a reduced response to metformin (p=2.4×10-8), where carriers had a 0.29 mmol/l increase in fasting glucose compared with non-carriers, who experienced a 0.15 mmol/l decrease. This finding was validated in the Diabetes Prevention Program, where rs111770298 was associated with a worse glycaemic response to metformin: heterozygous carriers had an increase in HbA1c of 0.08% and non-carriers had an HbA1c increase of 0.01% after 1 year of treatment (p=3.3×10-3). We also identified associations between type 2 diabetes-associated variants and glycaemic response, including the type 2 diabetes-protective C allele of rs703972 near ZMIZ1 and increased levels of active glucagon-like peptide 1 (GLP-1) (p=1.6×10-5), supporting the role of alterations in incretin levels in type 2 diabetes pathophysiology. We present a well-phenotyped, densely genotyped, multi-ancestry resource to study gene-drug interactions, uncover novel variation associated with response to common glucose-lowering medications and provide insight into mechanisms of action of type 2 diabetes-related variation. The complete summary statistics from this study are available at the Common Metabolic Diseases Knowledge Portal ( https://hugeamp.org ) and the GWAS Catalog ( www.ebi.ac.uk/gwas/ , accession IDs: GCST90269867 to GCST90269899).

Genetic variability in sporadic amyotrophic lateral sclerosis.

With the advent of gene therapies for amyotrophic lateral sclerosis, there is a surge in gene testing for ALS. Although there is ample experience with gene testing for C9orf72, SOD1, FUS and TARDBP in familial ALS, large studies exploring genetic variation in all ALS-associated genes in sporadic ALS (sALS) are still scarce. Gene testing in a diagnostic setting is challenging given the complex genetic architecture of sALS with genetic variants with large and small effect sizes. Guidelines for interpretation of genetic variants in gene panels and for counselling of patients are lacking. We aimed to provide a thorough characterization of genetic variability in ALS genes by applying the ACMG criteria on whole genome sequencing data from a large cohort of 6013 sporadic ALS patients and 2411 matched controls from Project MinE. We studied genetic variation in 90 ALS-associated genes and applied customized ACMG-criteria to identify pathogenic and likely pathogenic variants. Variants of unknown significance were collected as well. In addition, we determined the length of repeat expansions in C9orf72, ATXN1, ATXN2 and NIPA1 using the ExpansionHunter tool. We found C9orf72 repeat expansions in 5.21% of sALS patients. In 50 ALS-associated genes, we did not identify any pathogenic or likely pathogenic variants. In 5.89%, a pathogenic or likely pathogenic variant was found, most commonly in SOD1, TARDBP, FUS, NEK1, OPTN or TBK1. Significantly more cases carried at least one pathogenic or likely pathogenic variant compared to controls (OR 1.75; p-value 1.64 × 10-5). Isolated risk factors in ATXN1, ATXN2, NIPA1 and/or UNC13A were detected in 17.33% of cases. In 71.83%, we did not find any genetic clues. A combination of variants was found in 2.88%. This study provides an inventory of pathogenic and likely pathogenic genetic variation in a large cohort of sALS. Overall, we identified pathogenic and likely pathogenic variants in 11.13% of ALS patients in 38 known ALS genes. In line with the oligogenic hypothesis, we found significantly more combinations of variants in cases compared to controls. Many variants of unknown significance may contribute to ALS risk, but diagnostic algorithms to reliably identify and weigh them are lacking. This work can serve as a resource for counselling and for the assembly of gene panels for ALS. Further characterization of the genetic architecture of sALS is necessary given the growing interest in gene testing in ALS.

40P The detection and quantification of different sequence-variable NPM1 mutations using RNase H-dependent PCR (rhPCR)

Molecular diagnostics for the detection and characterization of genetic variants is based in the majority of cases on PCR technology. Since the primers and probes are designed according to the nucleotide sequence of the DNA region for the specific mutation, PCR technology can only be applied if the mutation is well known. In cases where the mutated region of a gene may have variable sequences, different between patients, a set of primers for each sequence variant is necessary, which involves a large volume of work.

Development of Retrotransposon-Based Molecular Markers for Characterization of Persea americana (Avocado) Cultivars and Horticultural Races

Persea americana (avocado) represents one of the most demanded food products worldwide, with an important impact in several agronomy-based economies. The avocado is one of the most salt-sensitive and valuable crops. It is therefore necessary to use salt-tolerant varieties, such as the West Indian, for cultivation in locations with soil salinity problems, such as the Canary Islands. Therefore, characterization of avocado cultivars is in demand, as well as development of molecular tools able to easily identify the main avocado cultivars and horticultural races. In the present work, inter-Primer Binding Site (iPBS) and Inter-Retrotransposon Amplified Polymorphism (IRAP) techniques, which are based on retrotransposon with Long Terminal Repeats (LTR), have been implemented for the first time in P. americana, allowing the characterization of genetic variation among cultivars from the three main horticultural races and the identification of potential P. americana LTR sequences. The iPBS approach showed clear advantages over its technical implementation, and allowed a better delimitation of horticultural races, especially when focused on West Indian cultivars. However, both techniques generated reproducible genetic fingerprints that not only allowed genetic characterization of each cultivar analyzed, but also revealed potential molecular markers for the identification of avocado cultivars and horticultural races.

Abstract 2706: Ultra-Low Input High-Fidelity (ULI-HiFi) long-reads uncover variants in genomic dark matter from pre-cancer polyp and tumor samples

Abstract Long-read sequencing technologies have been constrained by high error rates and large sample input requirements. The recent introduction of HiFi sequencing has enabled highly accurate detection of single-nucleotide variants (SNVs) from long reads (10-15 kb). However, a major limiting factor is the amount of sample input required, where current protocols require ≥15 micrograms of DNA. Here we report Ultra-Low Input High Fidelity Sequencing (ULI-HiFi), an amplification-based library preparation that reduces this input to 10 nanograms of DNA, a more than 10,000-fold reduction in sample input. When the ultra-low input method was tested using a benchmark genome, HG002, we observed high precision and improved recall of structural variants compared to a ground truth dataset from the Genome in a Bottle Consortium. We also benchmarked small variants and reported the accurate analysis of many variants in clinically important genes that are unmappable with short reads. We used this strategy to sequence tumor and polyp samples from a patient with familial adenomatous polyposis, a hereditary form of colon cancer, which revealed SNVs and structural variants not detected by short-read techniques. This strategy will enable the improved characterization of genetic variants from limited clinical samples. Citation Format: Hayan Lee, Graham Erwin, Aaron Horning, Raushun Kirtikar, Emmett Griffin-Baldwin, William Rowell, Philip Li, Sarah Kingan, Michael P. Snyder. Ultra-Low Input High-Fidelity (ULI-HiFi) long-reads uncover variants in genomic dark matter from pre-cancer polyp and tumor samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2706.

PPVED: A machine learning tool for predicting the effect of single amino acid substitution on protein function in plants.

SummarySingle amino acid substitution (SAAS) produces the most common variant of protein function change under physiological conditions. As the number of SAAS events in plants has increased exponentially, an effective prediction tool is required to help identify and distinguish functional SAASs from the whole genome as either potentially causal traits or as variants. Here, we constructed a plant SAAS database that stores 12 865 SAASs in 6172 proteins and developed a tool called Plant Protein Variation Effect Detector (PPVED) that predicts the effect of SAASs on protein function in plants. PPVED achieved an 87% predictive accuracy when applied to plant SAASs, an accuracy that was much higher than those from six human database software: SIFT, PROVEAN, PANTHER‐PSEP, PhD‐SNP, PolyPhen‐2, and MutPred2. The predictive effect of six SAASs from three proteins in Arabidopsis and maize was validated with wet lab experiments, of which five substitution sites were accurately predicted. PPVED could facilitate the identification and characterization of genetic variants that explain observed phenotype variations in plants, contributing to solutions for challenges in functional genomics and systems biology. PPVED can be accessed under a CC‐BY (4.0) license via http://www.ppved.org.cn.

Identification and validation of a QTL for spikelet number on chromosome arm 6BL of common wheat (Triticum aestivum L.)

To provide food security for a growing world population, it will be necessary to increase yields of staple crops such as wheat (Triticum aestivum L.). Yield is a complex, polygenic trait influenced by grain weight and number, which are negatively correlated with one another. Spikelet number is an important determinant of grain number, but allelic variants impacting its expression are often associated with heading date, constraining their use in wheat germplasm that must be adapted for specific environments. Identification and characterization of genetic variants affecting spikelet number will increase selection efficiency through their deployment in breeding programs. In this study, a quantitative trait locus (QTL) on chromosome arm 6BL for spikelet number was identified and validated using an association mapping panel, a recombinant inbred line population, and seven derived heterogeneous inbred families. The superior allele, QSn.csu-6Bb, was associated with an increase of 0.248 to 0.808 spikelets per spike across multiple environments that varied for mean spikelet number. Despite epistatic interactions between QSn.csu-6B and three other loci (WAPO-A1, VRN-D3, and PPD-B1), genotypes with a greater number of superior alleles at these loci consistently exhibit higher spikelet number. The frequency of superior alleles at these loci varies among winter wheat varieties adapted to different latitudes of the US Great Plains, revealing opportunities for breeders to select for increased spikelet number using simple molecular markers. This work lays the foundation for the positional cloning of the genetic variant underlying the QSn.csu-6B QTL to strengthen our understanding of spikelet number determination in wheat.

Genetička varijabilnost i srodnost genotipova jarog lanika različitog porekla

Camelina sativa L. is one of the oldest crops of the Brassicaceae family, first domesticated in the region of south-eastern Europe. It has regained interest as a very promising alternative oilseed crop with broad adaptability, a wide range of tolerances to pests and diseases, and low-input requirements. The genetic diversity in spring camelina proved to be limited, so the identification and characterization of genetic variations in germplasm originating from different sources is considered very useful for development of efficient breeding programmes. The aim of the study was to use SSR markers in order to investigate genetic variation of twenty spring camelina accessions of different origin and estimate their genetic relatedness. Forty-five individual samples were taken from each accession and used for amplification of SSR markers P4C11, P6E4 and LIB19. Percentage of polymorphic loci, number of alleles, effective number of alleles, expected heterozygosity and Shannon's information index were used to estimate genetic variation. The accessions expressed different levels of genetic variation. The highest variability was found in cultivar Zavolzskij, breeding line CK2X-7, cultivar NS Zlatka and breeding line CK2X-9. The most uniform were cultivar Pernice, and population Maslomania. AMOVA (analysis of molecular variance) showed that 64% of the total genetic variation was attributed to variance within accessions and 36% to variance among them. IBased on genetic distance, accessions were divided in two clades, which both were further divided in two subclades. Genetic distance analysis indicated that there was overlapping in certain breeding programs and exchange of breeding germplasm.

LORSEN: Fast and Efficient eQTL Mapping With Low Rank Penalized Regression.

Characterization of genetic variations that are associated with gene expression levels is essential to understand cellular mechanisms that underline human complex traits. Expression quantitative trait loci (eQTL) mapping attempts to identify genetic variants, such as single nucleotide polymorphisms (SNPs), that affect the expression of one or more genes. With the availability of a large volume of gene expression data, it is necessary and important to develop fast and efficient statistical and computational methods to perform eQTL mapping for such large scale data. In this paper, we proposed a new method, the low rank penalized regression method (LORSEN), for eQTL mapping. We evaluated and compared the performance of LORSEN with two existing methods for eQTL mapping using extensive simulations as well as real data from the HapMap3 project. Simulation studies showed that our method outperformed two commonly used methods for eQTL mapping, LORS and FastLORS, in many scenarios in terms of area under the curve (AUC). We illustrated the usefulness of our method by applying it to SNP variants data and gene expression levels on four chromosomes from the HapMap3 Project.

Applying Bioinformatic Platforms, In Vitro, and In Vivo Functional Assays in the Characterization of Genetic Variants in the GH/IGF Pathway Affecting Growth and Development

Heritability accounts for over 80% of adult human height, indicating that genetic variability is the main determinant of stature. The rapid technological development of Next-Generation Sequencing (NGS), particularly Whole Exome Sequencing (WES), has resulted in the characterization of several genetic conditions affecting growth and development. The greatest challenge of NGS remains the high number of candidate variants identified. In silico bioinformatic tools represent the first approach for classifying these variants. However, solving the complicated problem of variant interpretation requires the use of experimental approaches such as in vitro and, when needed, in vivo functional assays. In this review, we will discuss a rational approach to apply to the gene variants identified in children with growth and developmental defects including: (i) bioinformatic tools; (ii) in silico modeling tools; (iii) in vitro functional assays; and (iv) the development of in vivo models. While bioinformatic tools are useful for a preliminary selection of potentially pathogenic variants, in vitro—and sometimes also in vivo—functional assays are further required to unequivocally determine the pathogenicity of a novel genetic variant. This long, time-consuming, and expensive process is the only scientifically proven method to determine causality between a genetic variant and a human genetic disease.

Characterization of Genetic Variants in the SLC5A5 Gene and Associations With Breast Milk Iodine Concentration in Lactating Women of African Descent: The NUPED Study.

Background: The sodium iodide symporter is responsible for the transfer of iodine into breast milk and is encoded for by the SLC5A5 gene. The role of genetic variants in the SLC5A5 gene locus in relation to the transfer of iodine from plasma into breast milk in healthy lactating individuals has, to our knowledge, not been explored.Objective: To identify and characterize possible genetic variants of the SLC5A5 gene in women of African descent living in urban South Africa, and to study associations with breast milk iodine concentrations (BMIC) in lactating women.Methods: This study is affiliated to the Nutrition during Pregnancy and Early Development (NuPED) cohort study (n = 250 enrolled pregnant women). In a randomly selected sub-sample of 32 women, the SLC5A5 gene was sequenced to identify known and novel variants. Of the identified variants, genotyping of selected variants was performed in all pregnant women who gave consent for genetic analyses (n = 246), to determine the frequency of the variants in the study sample. Urinary iodine concentration (UIC) in spot urine samples and BMIC were measured to determine iodine status. Associations of SLC5A5 genetic variants with BMIC were studied in lactating women (n = 55).Results: We identified 27 variants from sequencing of gene exomes and 10 variants were selected for further study. There was a significant difference in BMIC between the genotypes of the rs775249401 variant (P = 0.042), with the homozygous GG group having lower BMIC [86.8 (54.9–167.9) μg/L] compared to the (A) allele carriers rs775249401(AG+AA) [143.9 (122.4–169.3) μg/L] (P = 0.042). Of the rs775249401(GG), 49% had UIC <100 μg/L and 61% had BMIC <100 μg/L. On the other hand, 60% of the rs775249401(AG+AA) carriers had UIC <100 μg/L, and none had a BMIC <100 μg/L.Conclusion: Our results suggest that A-allele carriers of rs775249401(AG+AA) are likely to have higher iodine transfer into breast milk compared to the homozygous GG counterparts. Thus, genetic variations in the SLC5A5 gene may play an important role in the transfer of iodine from plasma into breast milk and may partially explain inter-individual variability in BMIC.

CURRENT TRENDS AND FUTURE OF ARTIFICIAL INTELLIGENCE IN CARDIOVASCULAR RESEARCH AND IMAGING

The domain of science that would witness the greatest exponential contribution of articial intelligence in near future is health care. Improved health care efciency in diagnosis, treatment and prognosis would be the end result. There is great potential of articial intelligence in future directions in cardiovascular imaging. Genotype is a great inuence on disease risk. Identication and characterization of genetic variants is one domain where AI shows great promise. Variant interpretation is one of the key challenges in genetic sequencing. Heterogeneity, low delity and integration difculties stalk the traditional statistical approaches in this eld. High resolution whole organ models and genome wide approaches nally unravel tackling points in interaction of environment with genes, making cardiovascular disease prevention or even auto engineered organs an ultimate reality. Improved access to health and well-being empowers both patients and the physician with reliable access and assistance that intelligently supports clinical decision-making would be the greatest benet. Data analysis with predictive potential would enhance patient safety and preventive medicine and cardiovascular disease that causes the greatest mortality would be the greatest beneciary

Genetic Epidemiology of Complex Phenotypes.

Genetic and environmental factors are critical elements in most common complex disease. Genetics is increasingly being recognized to play a substantive role in the susceptibility, prognosis, and treatment of common diseases. Due to recent and rapid advancements in characterization of genetic variants and large-scale genotyping platforms, multiple genes and genetic variants have now been identified for common, complex diseases. The most efficient method for gene identification at present appears to be large-scale association-based studies, which integrate genetic and epidemiological principles. As the strategy for gene identification studies has shifted toward genetic association-based methods rather than traditional linkage analysis, epidemiological methods are increasingly being integrated into genetic investigations and in public health research. Consequently, the disciplines of genetics and epidemiology, which historically have functioned separately, have been integrated into a hybrid discipline referred to as genetic epidemiology. In this chapter, we review methods for establishing the genetic burden of complex genetic disease, followed by methods for gene and/or genetic variant identification. When appropriate, we will highlight the epidemiological issues and clinical applications that guide these methods.

Population genetic variation characterization of the boreal tree Acer ginnala in Northern China

Genetic diversity and differentiation are revealed particularly through spatio-temporal environmental heterogeneity. Acer ginnala, as a deciduous shrub/small tree, is a foundation species in many terrestrial ecosystems of Northern China. Owing to its increased use as an economic resource, this species has been in the vulnerability. Therefore, the elucidations of the genetic differentiation and influence of environmental factors on A. ginnala are very critical for its management and future utilization strategies. In this study, high genetic diversity and differentiation occurred in A. ginnala, which might be resulted from its pollination mechanism and species characteristics. Compared with the species level, relatively low genetic diversity was detected at the population level that might be the cause for its vulnerability. There was no significant relationship between genetic and geographical distances, while a significant correlation existed between genetic and environmental distances. Among nineteen climate variables, Annual Mean Temperature (bio1), Mean Diurnal Range (bio2), Isothermality (bio3), Temperature Seasonality (bio4), Precipitation of Wettest Month (bio13), Precipitation Seasonality (bio15), and Precipitation of Warmest Quarter (bio18) could explain the substantial levels of genetic variation (> 40%) in this species. The A. ginnala populations were isolated into multi-subpopulations by the heterogeneous climate conditions, which subsequently promoted the genetic divergence. Climatic heterogeneity played an important role in the pattern of genetic differentiation and population distribution of A. ginnala across a relatively wide range in Northern China. These would provide some clues for the conservation and management of this vulnerable species.