SNP Array Research Articles

Genome-wide association studies of root system architecture traits in a broad collection of Brassica genotypes.

The root systems of Brassica species are complex. Eight root system architecture (RSA) traits, including total root length, total root surface area, root average diameter, number of tips, total primary root length, total lateral root length, total tertiary root length, and basal link length, were phenotyped across 379 accessions representing six Brassica species (B. napus, B. juncea, B. carinata, B. oleracea, B. nigra, and B. rapa) using a semi-hydroponic system and image analysis software. The results suggest that, among the assessed species, B. napus and B. oleracea had the most intricate and largest root systems, while B. nigra exhibited the smallest roots. The two species B. juncea and B. carinata shared comparable root system complexity and had root systems with larger root diameters. In addition, 313 of the Brassica accessions were genotyped using a 19K Brassica single nucleotide polymorphism (SNP) array. After filtering by TASSEL 5.0, 6,213 SNP markers, comprising 5,103 markers on the A-genome (covering 302,504 kb) and 1,110 markers on the C-genome (covering 452,764 kb), were selected for genome-wide association studies (GWAS). Two general linear models were tested to identify the genomic regions and SNPs associated with the RSA traits. GWAS identified 79 significant SNP markers associated with the eight RSA traits investigated. These markers were distributed across the 18 chromosomes of B. napus, except for chromosome C06. Sixty-five markers were located on the A-genome, and 14 on the C-genome. Furthermore, the major marker-trait associations (MTAs)/quantitative trait loci (QTLs) associated with root traits were located on chromosomes A02, A03, and A06. Brassica accessions with distinct RSA traits were identified, which could hold functional, adaptive, evolutionary, environmental, pathological, and breeding significance.

Integrating Bioinformatics and Machine Learning for Genomic Prediction in Chickens.

Genomic prediction plays an increasingly important role in modern animal breeding, with predictive accuracy being a crucial aspect. The classical linear mixed model is gradually unable to accommodate the growing number of target traits and the increasingly intricate genetic regulatory patterns. Hence, novel approaches are necessary for future genomic prediction. In this study, we used an illumina 50K SNP chip to genotype 4190 egg-type female Rhode Island Red chickens. Machine learning (ML) and classical bioinformatics methods were integrated to fit genotypes with 10 economic traits in chickens. We evaluated the effectiveness of ML methods using Pearson correlation coefficients and the RMSE between predicted and actual phenotypic values and compared them with rrBLUP and BayesA. Our results indicated that ML algorithms exhibit significantly superior performance to rrBLUP and BayesA in predicting body weight and eggshell strength traits. Conversely, rrBLUP and BayesA demonstrated 2-58% higher predictive accuracy in predicting egg numbers. Additionally, the incorporation of suggestively significant SNPs obtained through the GWAS into the ML models resulted in an increase in the predictive accuracy of 0.1-27% across nearly all traits. These findings suggest the potential of combining classical bioinformatics methods with ML techniques to improve genomic prediction in the future.

Development and validation of a reliable DNA copy-number-based machine learning algorithm (CopyClust) for breast cancer integrative cluster classification

The Integrative Cluster subtypes (IntClusts) provide a framework for the classification of breast cancer tumors into 10 distinct groups based on copy number and gene expression, each with unique biological drivers of disease and clinical prognoses. Gene expression data is often lacking, and accurate classification of samples into IntClusts with copy number data alone is essential. Current classification methods achieve low accuracy when gene expression data are absent, warranting the development of new approaches to IntClust classification. Copy number data from 1980 breast cancer samples from METABRIC was used to train multiclass XGBoost machine learning algorithms (CopyClust). A piecewise constant fit was applied to the average copy number profile of each IntClust and unique breakpoints across the 10 profiles were identified and converted into ~ 500 genomic regions used as features for CopyClust. These models consisted of two approaches: a 10-class model with the final IntClust label predicted by a single multiclass model and a 6-class model with binary reclassification in which four pairs of IntClusts were combined for initial multiclass classification. Performance was validated on the TCGA dataset, with copy number data generated from both SNP arrays and WES platforms. CopyClust achieved 81% and 79% overall accuracy with the TCGA SNP and WES datasets, respectively, a nine-percentage point or greater improvement in overall IntClust subtype classification accuracy. CopyClust achieves a significant improvement over current methods in classification accuracy of IntClust subtypes for samples without available gene expression data and is an easily implementable algorithm for IntClust classification of breast cancer samples with copy number data.

Genome-wide association analysis of the resistance to infectious hematopoietic necrosis virus in two rainbow trout aquaculture lines confirms oligogenic architecture with several moderate effect quantitative trait loci

Infectious hematopoietic necrosis (IHN) is a disease of salmonid fish that is caused by the IHN virus (IHNV), which can cause substantial mortality and economic losses in rainbow trout aquaculture and fisheries enhancement hatchery programs. In a previous study on a commercial rainbow trout breeding line that has undergone selection, we found that genetic resistance to IHNV is controlled by the oligogenic inheritance of several moderate and many small effect quantitative trait loci (QTL). Here we used genome wide association analyses in two different commercial aquaculture lines that were naïve to previous exposure to IHNV to determine whether QTL were shared across lines, and to investigate whether there were major effect loci that were still segregating in the naïve lines. A total of 1,859 and 1,768 offspring from two commercial aquaculture strains were phenotyped for resistance to IHNV and genotyped with the rainbow trout Axiom 57K SNP array. Moderate heritability values (0.15–0.25) were estimated. Two statistical methods were used for genome wide association analyses in the two populations. No major QTL were detected despite the naïve status of the two lines. Further, our analyses confirmed an oligogenic architecture for genetic resistance to IHNV in rainbow trout. Overall, 17 QTL with notable effect (≥1.9% of the additive genetic variance) were detected in at least one of the two rainbow trout lines with at least one of the two statistical methods. Five of those QTL were mapped to overlapping or adjacent chromosomal regions in both lines, suggesting that some loci may be shared across commercial lines. Although some of the loci detected in this GWAS merit further investigation to better understand the biological basis of IHNV disease resistance across populations, the overall genetic architecture of IHNV resistance in the two rainbow trout lines suggests that genomic selection may be a more effective strategy for genetic improvement in this trait.

Polygenic risk score predicting susceptibility and outcome of benign prostatic hyperplasia in the Han Chinese.

Given the high prevalence of BPH among elderly men, pinpointing those at elevated risk can aid in early intervention and effective management. This study aimed to explore that polygenic risk score (PRS) is effective in predicting benign prostatic hyperplasia (BPH) incidence, prognosis and risk of operation in Han Chinese. A retrospective cohort study included 12,474 male participants (6,237 with BPH and 6,237 non-BPH controls) from the Taiwan Precision Medicine Initiative (TPMI). Genotyping was performed using the Affymetrix Genome-Wide TWB 2.0 SNP Array. PRS was calculated using PGS001865, comprising 1,712 single nucleotide polymorphisms. Logistic regression models assessed the association between PRS and BPH incidence, adjusting for age and prostate-specific antigen (PSA) levels. The study also examined the relationship between PSA, prostate volume, and response to 5-α-reductase inhibitor (5ARI) treatment, as well as the association between PRS and the risk of TURP. Individuals in the highest PRS quartile (Q4) had a significantly higher risk of BPH compared to the lowest quartile (Q1) (OR = 1.51, 95% CI = 1.274-1.783, p < 0.0001), after adjusting for PSA level. The Q4 group exhibited larger prostate volumes and a smaller volume reduction after 5ARI treatment. The Q1 group had a lower cumulative TURP probability at 3, 5, and 10 years compared to the Q4 group. PRS Q4 was an independent risk factor for TURP. In this Han Chinese cohort, higher PRS was associated with an increased susceptibility to BPH, larger prostate volumes, poorer response to 5ARI treatment, and a higher risk of TURP. Larger prospective studies with longer follow-up are warranted to further validate these findings.

Genome-Wide Detection of Copy Number Variations and Their Potential Association with Carcass and Meat Quality Traits in Pingliang Red Cattle.

Copy number variation (CNV) serves as a significant source of genetic diversity in mammals and exerts substantial effects on various complex traits. Pingliang red cattle, an outstanding indigenous resource in China, possess remarkable breeding value attributed to their tender meat and superior marbling quality. However, the genetic mechanisms influencing carcass and meat quality traits in Pingliang red cattle are not well understood. We generated a comprehensive genome-wide CNV map for Pingliang red cattle using the GGP Bovine 100K SNP chip. A total of 755 copy number variable regions (CNVRs) spanning 81.03 Mb were identified, accounting for approximately 3.24% of the bovine autosomal genome. Among these, we discovered 270 potentially breed-specific CNVRs in Pingliang red cattle, including 143 gains, 73 losses, and 54 mixed events. Functional annotation analysis revealed significant associations between these specific CNVRs and important traits such as carcass and meat quality, reproduction, exterior traits, growth traits, and health traits. Additionally, our network and transcriptome analysis highlighted CACNA2D1, CYLD, UBXN2B, TG, NADK, and ITGA9 as promising candidate genes associated with carcass weight and intramuscular fat deposition. The current study presents a genome-wide CNV map in Pingliang red cattle, highlighting breed-specific CNVRs, and transcriptome findings provide valuable insights into the underlying genetic characteristics of Pingliang red cattle. These results offer potential avenues for enhancing meat quality through a targeted breeding program.

Copy number variant scan in more than four thousand Holstein cows bred in Lombardy, Italy.

Copy Number Variants (CNV) are modifications affecting the genome sequence of DNA, for instance, they can be duplications or deletions of a considerable number of base pairs (i.e., greater than 1000 bp and up to millions of bp). Their impact on the variation of the phenotypic traits has been widely demonstrated. In addition, CNVs are a class of markers useful to identify the genetic biodiversity among populations related to adaptation to the environment. The aim of this study was to detect CNVs in more than four thousand Holstein cows, using information derived by a genotyping done with the GGP (GeneSeek Genomic Profiler) bovine 100K SNP chip. To detect CNV the SVS 8.9 software was used, then CNV regions (CNVRs) were detected. A total of 123,814 CNVs (4,150 non redundant) were called and aggregated into 1,397 CNVRs. The PCA results obtained using the CNVs information, showed that there is some variability among animals. For many genes annotated within the CNVRs, the role in immune response is well known, as well as their association with important and economic traits object of selection in Holstein, such as milk production and quality, udder conformation and body morphology. Comparison with reference revealed unique CNVRs of the Holstein breed, and others in common with Jersey and Brown. The information regarding CNVs represents a valuable resource to understand how this class of markers may improve the accuracy in prediction of genomic value, nowadays solely based on SNPs markers.

Development of 51 K liquid-phased probe array for Loblolly and Slash pines and its application to GWAS of Slash pine breeding population

Loblolly pine (Pinus taeda) and Slash pine (Pinus elliottii) are important economically and ecologically tree species worldwide. To implement genomic based breeding strategy, genotyping large number of samples is needed. However, huge and complex pines genome make it difficult to obtain abundant and cost-effectively markers. In this study, we designed a SNP array containing 51 K liquid-phased probes based on the published SNPs and probes of the two species, novel Slash pine-specific long-read transcript, and SNPs obtained from a double digest Restriction-Site Associated DNA sequencing (ddRADseq). We performed targeted capture sequencing using the developed SNP array on three pine species of Loblolly, Slash, and Caribbean pine (Pinus caribaea). The probe capture had an efficiency of 68.26% on average. Principal Component Analysis (PCA), phylogenetic analysis, and genetic structure analysis of 28,670 SNPs genotyped for the three pine species demonstrated the transferability of the SNP array for the three pines. Furthermore, we genotyped 221 range-wide Slash pine genotypes, analyzed their genetic diversity and performed a genome-wide association study (GWAS). We identified 95 SNPs significantly associated with growth and wood quality traits of Slash pine. We have identified potential roles of the MYB2 and MYB46 transcription factors in regulating cell cycle and differentiation in Slash pine, while also suggesting that AP2/ERF and Glycosyl hydrolase may play significant roles in wood formation processes. This new SNP array can be widely applied in future molecular breeding research of conifers.

Gain-Type Aneuploidies Influence the Burden of Selective Long Non-Coding Transcripts in Colorectal Cancer.

Chromosomal instability is a hallmark of colorectal carcinogenesis and produces an accumulation of different forms of aneuploidies or broad copy number aberrations. Colorectal cancer is characterized by gain-type broad copy number aberrations, specifically in Chr20, Chr8q, Chr13 and Chr7, but their roles and mechanisms in cancer progression are not fully understood. It has been suggested that broad copy number gains might contribute to tumor development through the so-called caricature transcriptomic effect. We intend to investigate the impact of broad copy number gains on long non-coding RNAs' expression in colorectal cancer, given their well-known role in oncogenesis. The influence of such chromosomal aberrations on lncRNAs' transcriptome profile was investigated by SNP and transcriptome arrays in our series of colorectal cancer samples and cell lines. The correlation between aneuploidies and transcriptomic profiles led us to obtain a class of Over-UpT lncRNAs, which are transcripts upregulated in CRC and further overexpressed in colon tumors bearing specific chromosomal aberrations. The identified lncRNAs can contribute to a wide interaction network to establish the cancer driving effect of gain-type aneuploidies.

Genome-wide association study identifies novel loci and candidate genes for rust resistance in wheat (Triticum aestivum L.)

BackgroundWheat rusts are important biotic stresses, development of rust resistant cultivars through molecular approaches is both economical and sustainable. Extensive phenotyping of large mapping populations under diverse production conditions and high-density genotyping would be the ideal strategy to identify major genomic regions for rust resistance in wheat. The genome-wide association study (GWAS) population of 280 genotypes was genotyped using a 35 K Axiom single nucleotide polymorphism (SNP) array and phenotyped at eight, 10, and, 10 environments, respectively for stem/black rust (SR), stripe/yellow rust (YR), and leaf/brown rust (LR).ResultsForty-one Bonferroni corrected marker-trait associations (MTAs) were identified, including 17 for SR and 24 for YR. Ten stable MTAs and their best combinations were also identified. For YR, AX-94990952 on 1A + AX-95203560 on 4A + AX-94723806 on 3D + AX-95172478 on 1A showed the best combination with an average co-efficient of infection (ACI) score of 1.36. Similarly, for SR, AX-94883961 on 7B + AX-94843704 on 1B and AX-94883961 on 7B + AX-94580041 on 3D + AX-94843704 on 1B showed the best combination with an ACI score of around 9.0. The genotype PBW827 have the best MTA combinations for both YR and SR resistance. In silico study identifies key prospective candidate genes that are located within MTA regions. Further, the expression analysis revealed that 18 transcripts were upregulated to the tune of more than 1.5 folds including 19.36 folds (TraesCS3D02G519600) and 7.23 folds (TraesCS2D02G038900) under stress conditions compared to the control conditions. Furthermore, highly expressed genes in silico under stress conditions were analyzed to find out the potential links to the rust phenotype, and all four genes were found to be associated with the rust phenotype.ConclusionThe identified novel MTAs, particularly stable and highly expressed MTAs are valuable for further validation and subsequent application in wheat rust resistance breeding. The genotypes with favorable MTA combinations can be used as prospective donors to develop elite cultivars with YR and SR resistance.

A heatmap for expected cumulative live birth rate in preimplantation genetic testing for monogenic disorders and chromosomal structural rearrangements

PurposeOur objective is to predict the cumulative live birth rate (CLBR) and identify the specific subset within the population undergoing preimplantation genetic testing for monogenic disorders (PGT-M) and chromosomal structural rearrangements (PGT-SR) which is likely to exhibit a diminished expected CLBR based on various patient demographics.MethodsWe performed a single-centre retrospective cohort study including 1522 women undergoing 3130 PGT cycles at a referral centre for PGT. A logistic regression analysis was performed to predict the CLBR per ovarian stimulation in women undergoing PGT-M by polymerase chain reaction (PCR) or single-nucleotide polymorphism (SNP) array, and in women undergoing PGT-SR by SNP array, array comparative genomic hybridization (CGH) or next-generation sequencing (NGS).ResultsThe mean age of women was 32.6 years, with a mean AMH of 2.75 µg/L. Female age and AMH significantly affected the expected CLBR irrespective of the inheritance mode or PGT technology. An expected CLBR < 10% was reached above the age of 42 years and AMH ≤ 1.25 µg/L. We found no significant difference in outcome per ovarian stimulation between the different PGT technologies, i.e. PCR, SNP array, array CGH and NGS. Whereas per embryo transfer, we noticed a significantly higher probability of live birth when SNP array, array CGH and NGS were used as compared to PCR.ConclusionIn a PGT-setting, couples with an unfavourable female age and AMH should be informed of the prognosis to allow other reproductive choices. The heatmap produced in this study can be used as a visual tool for PGT couples.

Natural selection on feralization genes contributed to the invasive spread of wild pigs throughout the United States.

Despite a long presence in the contiguous United States (US), the distribution of invasive wild pigs (Sus scrofa × domesticus) has expanded rapidly since the 1980s, suggesting a more recent evolutionary shift towards greater invasiveness. Contemporary populations of wild pigs represent exoferal hybrid descendants of domestic pigs and European wild boar, with such hybridization expected to enrich genetic diversity and increase the adaptive potential of populations. Our objective was to characterize how genetic enrichment through hybridization increases the invasiveness of populations by identifying signals of selection and the ancestral origins of selected loci. Our study focused on invasive wild pigs within Great Smoky Mountains National Park, which represents a hybrid population descendent from the admixture of established populations of feral pigs and an introduction of European wild boar to North America. Accordingly, we genotyped 881 wild pigs with multiple high-density single-nucleotide polymorphism (SNP) arrays. We found 233 markers under putative selection spread over 79 regions across 16 out of 18 autosomes, which contained genes involved in traits affecting feralization. Among these, genes were found to be related to skull formation and neurogenesis, with two genes, TYRP1 and TYR, also encoding for crucial melanogenesis enzymes. The most common haplotypes associated with regions under selection for the Great Smoky Mountains population were also common among other populations throughout the region, indicating a key role of putatively selective variants in the fitness of invasive populations. Interestingly, many of these haplotypes were absent among European wild boar reference genotypes, indicating feralization through genetic adaptation.

Genomic prediction model optimization for growth traits of olive flounder (Paralichthys olivaceus)

Genomic prediction (GP) has emerged an effective tool for addressing the many shortcomings of traditional selective breeding, thereby enhancing the selection process. In this study, we optimized GP methods using 5-fold cross-validation to estimate genome-estimated breeding values for the weight traits of olive flounder (Paralichthys olivaceus). To accomplish our goal, we determined the parentage of the target broodstock and the ability of 11 prediction models to predict the weight traits of 1.8-year-old olive flounders, which were genotyped using a 70 K single nucleotide polymorphism (SNP) array. Moreover, our optimization efforts toward the predictive ability of genomic best linear unbiased prediction (GBLUP), Bayesian B (BB), and random forest (RF) methods encompassed changes in various aspects such as fixed effects, SNP quantity, population size, and phenotypic data collected at different fish ages. Additionally, we assessed the predictive ability for the total length and body depth of fish using GBLUP, BB, and RF. Among the 11 prediction methods used in this study, the BB (0.675), Elastic Net (0.679), and RF (0.698) methods exhibited the highest predictive abilities, whereas the GBLUP (0.637) method demonstrated the lowest. Incorporating information regarding fish sex as a fixed effect substantially improved the predictive ability of GBLUP and BB. For mean models, utilizing 3000–5000 random SNP markers resulted in a higher predictive ability, similar to that obtained using 50,000 SNPs. Increasing the population size reduced the standard deviation of the predictive ability. Notably, phenotypic records from 1.8-year-old fish exhibited a significantly higher predictive ability than those from the other age groups. Furthermore, GBLUP, BB, and RF provided higher predictive abilities for length (0.655–0.852) and body depth (0.665–0.861). These findings may significantly shape future olive flounder genomic selection programs and offer valuable insights into GP in aquaculture.

Development and validation of the Axiom-MaruPri SNP chip for genetic analyses of domesticated old world camelids

Camels play a crucial socio-economic role in sustaining the livelihoods of millions in arid and semi-arid regions. They possess remarkable physiological attributes which enable them to thrive in extreme environments, and provide a source of meat, milk and transportation. With their unique traits, camels embody an irreplaceable source of untapped genomic knowledge. This study introduces Axiom-MaruPri, a medium-density SNP chip meticulously designed and validated for both Camelus bactrianus and Camelus dromedarius. Comprising of 182,122 SNP markers, derived from the re-sequenced data of nine Indian dromedary breeds and the double-humped Bactrian camel, this SNP chip offers 34,894 markers that display polymorphism in both species. It achieves an estimated inter-marker distance of 14 Kb, significantly enhancing the coverage of the camel genome. The medium-density chip has been successfully genotyped using 480 camel samples, achieving an impressive 99 % call rate, with 96 % of the 182,122 SNPs being highly reliable for genotyping. Phylogenetic analysis and Discriminant Analysis of Principal Components yield clear distinctions between Bactrian camels and dromedaries. Moreover, the discriminant functions substantially enhance the classification of dromedary camels into different breeds. The clustering of various camel breeds reveals an apparent correlation between geographical and genetic distances. The results affirm the efficacy of this SNP array, demonstrating high genotyping precision and clear differentiation between Bactrian and dromedary camels. With an enhanced genome coverage, accuracy and economic efficiency the Axiom_MaruPri SNP chip is poised to advance genomic breeding research in camels. It holds the potential to serve as an invaluable genetic resource for investigating population structure, genome-wide association studies and implementing genomic selection in domesticated camelid species.

Genetic Diversity, Linkage Disequilibrium, and Population Structure in a Common Bean Reference Collection

An in-depth understanding of the extent and pattern of genetic diversity and population structure in crop populations is of paramount importance for any crop improvement program to efficiently promote the translation of genetic diversity into genetic gain. A reference collection of 150 common bean genotypes selected from the International Center for Tropical Agriculture’s global core collection was evaluated using single-nucleotide polymorphism (SNP) markers to quantify the amount of genetic diversity, linkage disequilibrium, and population structure. The cultivars and landraces of the collection were diverse and originated from 14 countries, and wild accessions were used as controls for each gene pool. The collection was genotyped using an SNP array, generating a total of 5398 locus calls distributed across the entire bean genome. The SNP data quality was checked, and two datasets were generated. The first dataset (Dataset_1) comprised a set of 5108 SNPs and 150 genotypes after filtering for 10% missing alleles and an MAF &lt; 0.05. The second dataset (Dataset_2) comprised a set of 2300 SNPs that remained after removing any null-allele SNPs and LD pruning for a criterion of r2 &lt; 0.2. Dataset_1 was used for a principal coordinate analysis (PCoA), phylogenetic relationship determination, an analysis of molecular variance (AMOVA), and a discriminant analysis of principal components. Dataset_2 was used for a population structure analysis using STRUCTURE software and is proposed for a genome-wide association study (GWAS). The population structure analysis split the reference collection into two subpopulations according to an Andean or Mesoamerican gene pool. The Mesoamerican populations displayed higher genetic differentiation and tended to split into more groups that were somewhat aligned with common bean races. Andean beans were characterized by a larger average LD but lower LD percentage, a small average genetic distance between members of the population, and a higher major allele frequency, which suggested narrower genetic diversity compared to the Mesoamerican gene pool. In conclusion, the results indicated the presence of high genetic diversity, which is useful for a GWAS. However, the presence of significant linkage disequilibrium requires that genetic distance be considered as a co-factor for any further genetic studies. Overall, the molecular variation observed in the genotypes shows that this reference collection is valuable as a genebank-derived diversity panel which is useful for marker trait association studies.

QTL Mapping of Yield-Related Traits in Tetraploid Wheat Based on Wheat55K SNP Array.

To enhance the understanding of yield-related traits in tetraploid wheat, it is crucial to investigate and identify genes that govern superior yield characteristics. This study utilized the wheat55K single nucleotide polymorphism array to genotype a recombinant inbred line (RIL) population consisting of 120 lines developed through the crossbreeding of two tetraploid wheat varieties, Qin Hei-1 (QH-1) and Durum Wheat (DW). An investigation and analysis were conducted on 11 yield-related traits, including peduncle length (PL), neck length (NL), spike length (SL), flowering date (FD), heading date (HD), thousand-kernel weight (TKW), kernel area ratio (KAR), kernel circumference (KC), kernel length (KL), kernel width (KW), and kernel length-width ratio (KL-WR), over a period of three years in two locations, Yang Ling, Shaanxi, and Lin He, Inner Mongolia. The analysis identified nine stable loci among eight agronomic traits, named QSL.QD-1A.1, QNL.QD-4B.2, QPL.QD-4B.1, QFD.QD-2B, QHD.QD-2B.1, QHD.QD-4B, QKC.QD-4B.2, QKL-WR.QD-4B.6, and QKL.QD-4B.2. Among them, the additive effects of three QTLs, QSL.QD-1A.1, QNL.QD-4B.2, and QFD.QD-2B, were positive, indicating that the enhancing alleles at these loci were derived from the parent line QH-1. These three QTLs showed significant positive effects on the phenotypes of the population materials. Furthermore, potential functional genes were identified within the mapping intervals of QSL.QD-1A.1 and QNL.QD-4B.2, which regulate the development of spike length and neck length, respectively. These results provide potential QTLs and candidate genes, which broaden the genetic basis of agronomic traits related to yield, such as SL, NL, PL, and FD, and benefits for wheat breeding and improvement.

Trans-Atlantic genomic differentiation and parallel environmental and allelic variation in Lumpfish (Cyclopterus lumpus)

Abstract In marine species with large populations and high dispersal potential, large-scale genetic differences and clinal trends in allele frequency can provide insight into the evolutionary processes that shape diversity. Lumpfish, Cyclopterus lumpus, is found throughout the North Atlantic and has traditionally been harvested for roe and more recently used as a cleaner fish in salmon aquaculture. We used a 70 K SNP array to evaluate trans-Atlantic differentiation, genetic structuring, and clinal variation across the North Atlantic. Basin-scale structuring between the Northeast and Northwest Atlantic was significant, with enrichment for loci associated with developmental/mitochondrial function. We identified a putative structural variant on chromosome 2, likely contributing to differentiation between Northeast and Northwest Atlantic Lumpfish, and consistent with post-glacial trans-Atlantic secondary contact. Redundancy analysis identified climate associations both in the Northeast (N = 1269 loci) and Northwest (N = 1637 loci), with 103 shared loci between them. Clinal patterns in allele frequencies were observed in some loci (15%—Northwest and 5%—Northeast) of which 708 loci were shared and involved with growth, developmental processes, and locomotion. The combined evidence of trans-Atlantic differentiation, environmental associations, and clinal loci, suggests that both regional and large-scale potentially-adaptive population structuring is present across the North Atlantic.

Identification of novel genes associated with herbicide tolerance in Lentil (Lens culinaris ssp. culinaris Medik.)

Weeds pose a major constraint in lentil cultivation, leading to decrease farmers’ revenues by reducing the yield and increasing the management costs. The development of herbicide tolerant cultivars is essential to increase lentil yield. Even though herbicide tolerant lines have been identified in lentils, breeding efforts are still limited and lack proper validation. Marker assisted selection (MAS) can increase selection accuracy at early generations. Total 292 lentil accessions were evaluated under different dosages of two herbicides, metribuzin and imazethapyr, during two seasons at Marchouch, Morocco and Terbol, Lebanon. Highly significant differences among accessions were observed for days to flowering (DF) and maturity (DM), plant height (PH), biological yield (BY), seed yield (SY), number of pods per plant (NP), as well as the reduction indices (RI) for PH, BY, SY and NP. A total of 10,271 SNPs markers uniformly distributed along the lentil genome were assayed using Multispecies Pulse SNP chip developed at Agriculture Victoria, Melbourne. Meta-GWAS analysis was used to detect marker-trait associations, which detected 125 SNPs markers associated with different traits and clustered in 85 unique quantitative trait loci. These findings provide valuable insights for initiating MAS programs aiming to enhance herbicide tolerance in lentil crop.

Extragonadal germ cell tumors: A clinicopathologic study with emphasis on molecular features, clinical outcomes and associated secondary malignancies

Extragonadal germ cell tumors (EGCTs) are rare, representing <5% of all germ cell tumors (GCTs). Whilst EGCTs share morphological and immunohistochemical features with their gonadal counterparts, they tend to be more aggressive and are frequently associated with secondary somatic malignancies. The aim of our study was to evaluate the clinical, morphological and immunohistochemical features, and to analyze tumors for chromosomal abnormalities of 12p, in addition to any novel genetic alterations, in a series of EGCTs. Seventy-seven EGCTs were included. Anterior mediastinum was the most common anatomic site, followed by central nervous system, retroperitoneum, sacroccygeal area, and neck. Whole genome SNP array identified isochromosome 12p in 26% of tumors. Additional cytogenetic abnormalities included the presence of gain of chr 21 in 37% of tumors. Somatic-type malignancies were identified in 8% of patients. Disease progression (metastasis and/or recurrence) was documented in 8 patients, most of whom died from their relapse. Three patients who died of disease had somatic-type malignancies. Mediastinal seminomas had a significantly better overall survival when compared to mediastinal non-seminomatous GCTs. Our study demonstrates that EGCTs share similar histologic features, but diverse clinical outcomes compared to their gonadal counterparts. Outcomes vary according to anatomic location and histologic subtypes. Our data corroborate that somatic-type malignancies are frequently encountered in mediastinal EGCTs and that their presence portends a poorer prognosis.

Current Diagnostic Approaches in the Genetic Diagnosis of Disorders of Sex Development.

Disorders of sex development (DSD) are a clinically and genetically highly heterogeneous group of congenital disorders. The most accurate and rapid diagnosis may be possible with a complementary multidisciplinary diagnostic approach, including comprehensive clinical, hormonal, and genetic investigations. Rapid and accurate diagnosis of DSD requires urgency in terms of gender selection and management of the case. Despite the genetic tests performed in current daily practice, the genetic cause is still not elucidated in a significant proportion of cases. Karyotype analysis can be used as a standard for sex chromosome identification. In addition, quantitative fluorescent polymerase chain reaction (QF-PCR) or fluorescence in situ hybridization (FISH) analysis can be used for faster and more cost-effective detection of the sex chromosome and SRY gene. Multiplex ligation-dependent probe amplification (MLPA), single-gene sequence analysis, next-generation sequence analysis (NGSA), targeted NGSA, whole-exome sequencing (WES), and whole-genome sequencing (WGS) analyses can be performed according to preliminary diagnoses. Microarray analysis (array comparative genomic hybridization (aCGH) and single nucleotide polymorphism array (SNPa)) should be performed in cases with syndromic findings and if no pathology is detected with other tests. In DSD cases, the use of optical genome mapping and techniques, which will probably be in daily practice in near future, may be considered. In conclusion, the clinical and genetic diagnosis of DSD is difficult, and molecular genetic diagnosis is often not available. This has psychosocial and health implications for patients and their families. New genetic techniques, especially those targeting the whole genome, may provide a better understanding of DSD through the identification of little-known genetic causes. This review focuses on conventional genetic and next-generation genetic techniques used in the genetic diagnosis of DSD, as well as possible genetic diagnostic techniques and approaches that may be used in routine practice in near future.