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Supplementary Figure 1 from Estimating CDKN2A Carrier Probability and Personalizing Cancer Risk Assessments in Hereditary Melanoma Using MelaPRO

Supplementary Table 1 from Estimating CDKN2A Carrier Probability and Personalizing Cancer Risk Assessments in Hereditary Melanoma Using MelaPRO

Allelic imbalance (AI) is the differential expression of the two alleles in a diploid. AI can vary between tissues, treatments, and environments. Statistical methods for testing in this area exist, with impacts of explosive type I error in the presence of bias well understood. However, for study design, the more important and understudied problem is the type II error and power. As the biological questions for this type of study explode, and the costs of the technology plummet, what is more important: reads or replicates? How small of an interaction can be detected while keeping the type I error at bay? Here we present a simulation study that demonstrates that the proper model can control type I error below 5% for most scenarios. We find that a minimum of 2400, 480, and 240 allele specific reads divided equally among 12, 5, and 3 replicates is needed to detect a 10%, 20%, and 30%, respectively, deviation from allelic balance in a condition with power >80%. A minimum of 960 and 240 allele specific reads is needed to detect a 20% or 30% difference in AI between conditions with comparable power but these reads need to be divided amongst 8 replicates. Higher numbers of replicates increase power more than adding coverage without affecting type I error. We provide a Python package that enables simulation of AI scenarios and enables individuals to estimate type I error and power in detecting AI and differences in AI between conditions tailored to their own specific study needs.

Roots of the European hazelnut (Corylus avellana L.), i.e., one of the most economically important nut species, form symbiosis with ectomycorrhizal (ECM) fungi, including truffles. Although physical interactions only occur in roots, the presence of mycorrhizal fungi can lead to metabolic changes at a systemic level, i.e., in leaves. However, how root colonization by ECM fungi modifies these processes in the host plant has so far not been widely studied. This work aimed to investigate the response in two C. avellana genotypes, focusing on leaves from plants inoculated with the black truffle Tuber melanosporum Vittad. Transcriptomic profiles of leaves of colonized plants were compared with those of non-colonized plants, as well as sugar and polyphenolic content. Results suggested that T. melanosporum has the potential to support plants in stressed conditions, leading to the systemic regulation of several genes involved in signaling and defense responses. Although further confirmation is needed, our results open new perspectives for future research aimed to highlight novel aspects in ECM symbiosis.

Background ‘Candidatus Phytoplasma solani’ is endemic in Europe and infects a wide range of weeds and cultivated plants. Phytoplasmas are prokaryotic plant pathogens that colonize the sieve elements of their host plant, causing severe alterations in phloem function and impairment of assimilate translocation. Typical symptoms of infected plants include yellowing of leaves or shoots, leaf curling, and general stunting, but the molecular mechanisms underlying most of the reported changes remain largely enigmatic. To infer a possible involvement of Fe in the host-phytoplasma interaction, we investigated the effects of ‘Candidatus Phytoplasma solani’ infection on tomato plants (Solanum lycopersicum cv. Micro-Tom) grown under different Fe regimes. Results Both phytoplasma infection and Fe starvation led to the development of chlorotic leaves and altered thylakoid organization. In infected plants, Fe accumulated in phloem tissue, altering the local distribution of Fe. In infected plants, Fe starvation had additive effects on chlorophyll content and leaf chlorosis, suggesting that the two conditions affected the phenotypic readout via separate routes. To gain insights into the transcriptional response to phytoplasma infection, or Fe deficiency, transcriptome profiling was performed on midrib-enriched leaves. RNA-seq analysis revealed that both stress conditions altered the expression of a large (> 800) subset of common genes involved in photosynthetic light reactions, porphyrin / chlorophyll metabolism, and in flowering control. In Fe-deficient plants, phytoplasma infection perturbed the Fe deficiency response in roots, possibly by interference with the synthesis or transport of a promotive signal transmitted from the leaves to the roots. Conclusions ‘Candidatus Phytoplasma solani’ infection changes the Fe distribution in tomato leaves, affects the photosynthetic machinery and perturbs the orchestration of root-mediated transport processes by compromising shoot-to-root communication.

The microbiota of different types of Italian high-moisture Mozzarella cheese produced using cow or buffalo milk, acidified with natural or selected cultures, and sampled at the dairy or at the mass market, was evaluated using a Next Generation Sequencing approach, in order to identify possible drivers of the bacterial diversity. Cow Mozzarella and buffalo Mozzarella acidified with commercial cultures were dominated by Streptococcus thermophilus, while buffalo samples acidified with natural whey cultures showed similar prevalence of L. delbrueckii subsp. bulgaricus, L. helveticus and S. thermophilus. Moreover, several species of non-starter lactic acid bacteria were frequently detected. The diversity in cow Mozzarella microbiota was much higher than that of water buffalo samples. Cluster analysis clearly separated cow's cheeses from buffalo's ones, the former having a higher prevalence of psychrophilic taxa, and the latter of Lactobacillus and Streptococcus. A higher prevalence of psychrophilic species and potential spoilers was observed in samples collected at the mass retail, suggesting that longer exposures to cooling temperatures and longer production-to-consumption times could significantly affect microbiota diversity. Our results could help in detecting some kind of thermal abuse during the production or storage of mozzarella cheese.

Allelic imbalance (AI) occurs when alleles in a diploid individual are differentially expressed and indicates cis acting regulatory variation. What is the distribution of allelic effects in a natural population? Are all alleles the same? Are all alleles distinct? The approach described applies to any technology generating allele-specific sequence counts, for example for chromatin accessibility and can be applied generally including to comparisons between tissues or environments for the same genotype. Tests of allelic effect are generally performed by crossing individuals and comparing expression between alleles directly in the F1. However, a crossing scheme that compares alleles pairwise is a prohibitive cost for more than a handful of alleles as the number of crosses is at least (n2-n)/2 where n is the number of alleles. We show here that a testcross design followed by a hypothesis test of AI between testcrosses can be used to infer differences between nontester alleles, allowing n alleles to be compared with n crosses. Using a mouse data set where both testcrosses and direct comparisons have been performed, we show that the predicted differences between nontester alleles are validated at levels of over 90% when a parent-of-origin effect is present and of 60%−80% overall. Power considerations for a testcross, are similar to those in a reciprocal cross. In all applications, the testing for AI involves several complex bioinformatics steps. BayesASE is a complete bioinformatics pipeline that incorporates state-of-the-art error reduction techniques and a flexible Bayesian approach to estimating AI and formally comparing levels of AI between conditions. The modular structure of BayesASE has been packaged in Galaxy, made available in Nextflow and as a collection of scripts for the SLURM workload manager on github (https://github.com/McIntyre-Lab/BayesASE).

The study of orchid mycorrhizal interactions is particularly complex because of the peculiar life cycle of these plants and their diverse trophic strategies. Here, transcriptomics has been applied to investigate gene expression in the mycorrhizal roots of Limodorum abortivum, a terrestrial mixotrophic orchid that associates with ectomycorrhizal fungi in the genus Russula. Our results provide new insights into the mechanisms underlying plant&ndash, fungus interactions in adult orchids in nature and in particular into the plant responses to the mycorrhizal symbiont(s) in the roots of mixotrophic orchids. Our results indicate that amino acids may represent the main nitrogen source in mycorrhizal roots of L. abortivum, as already suggested for orchid protocorms and other orchid species. The upregulation, in mycorrhizal L. abortivum roots, of some symbiotic molecular marker genes identified in mycorrhizal roots from other orchids as well as in arbuscular mycorrhiza, may mirror a common core of plant genes involved in endomycorrhizal symbioses. Further efforts will be required to understand whether the specificities of orchid mycorrhiza depend on fine-tuned regulation of these common components, or whether specific additional genes are involved.

SUMMARY The characterization of the genetic basis of maize (Zea mays) leaf development may support breeding efforts to obtain plants with higher vigor and productivity. In this study, a mapping panel of 197 biparental and multiparental maize recombinant inbred lines (RILs) was analyzed for multiple leaf traits at the seedling stage. RNA sequencing was used to estimate the transcription levels of 29 573 gene models in RILs and to derive 373 769 single nucleotide polymorphisms (SNPs), and a forward genetics approach combining these data was used to pinpoint candidate genes involved in leaf development. First, leaf traits were correlated with gene expression levels to identify transcript–trait correlations. Then, leaf traits were associated with SNPs in a genome‐wide association (GWA) study. An expression quantitative trait locus mapping approach was followed to associate SNPs with gene expression levels, prioritizing candidate genes identified based on transcript–trait correlations and GWAs. Finally, a network analysis was conducted to cluster all transcripts in 38 co‐expression modules. By integrating forward genetics approaches, we identified 25 candidate genes highly enriched for specific functional categories, providing evidence supporting the role of vacuolar proton pumps, cell wall effectors, and vesicular traffic controllers in leaf growth. These results tackle the complexity of leaf trait determination and may support precision breeding in maize., Significance Statement Innovative genomics‐ and transcriptomics‐based forward genetic approaches can improve our understanding of the molecular basis of leaf development in maize (Zea mays). By combining transcript–trait correlations, genome‐wide associations, and expression quantitative trait locus mapping, we identified 25 candidate genes that may have a key role in early leaf growth.

Summary Vitis vinifera is an economically important crop and a useful model in which to study chromatin dynamics. In contrast to the small and relatively simple genome of Arabidopsis thaliana, grapevine contains a complex genome of 487 Mb that exhibits extensive colonization by transposable elements. We used Hi‐C, ChIP‐seq and ATAC‐seq to measure how chromatin features correlate to the expression of 31 845 grapevine genes. ATAC‐seq revealed the presence of more than 16 000 open chromatin regions, of which we characterize nearly 5000 as possible distal enhancer candidates that occur in intergenic space > 2 kb from the nearest transcription start site (TSS). A motif search identified more than 480 transcription factor (TF) binding sites in these regions, with those for TCP family proteins in greatest abundance. These open chromatin regions are typically within 15 kb from their nearest promoter, and a gene ontology analysis indicated that their nearest genes are significantly enriched for TF activity. The presence of a candidate cis‐regulatory element (cCRE) > 2 kb upstream of the TSS, location in the active nuclear compartment as determined by Hi‐C, and the enrichment of H3K4me3, H3K4me1 and H3K27ac at the gene are correlated with gene expression. Taken together, these results suggest that regions of intergenic open chromatin identified by ATAC‐seq can be considered potential candidates for cis‐regulatory regions in V. vinifera. Our findings enhance the characterization of a valuable agricultural crop, and help to clarify the understanding of unique plant biology., Significance Statement We use ATAC‐seq to identify open chromatin regions in Vitis vinifera, and show that they contain transcription factor binding sites and are correlated with gene expression, making them likely enhancer candidates. These findings add to the knowledge of biology of horticultural crops and provide possible targets for improved grape breeding strategies.

The ectoparasite protozoan Amyloodinium ocellatum (AO) is the etiological agent of amyloodiniosis in European seabass (Dicentrarchus labrax) (ESB). There is a lack of information about basic molecular data on AO biology and its interaction with the host. Therefore, de novo transcriptome sequencing of AO tomonts was performed. AO trophonts were detached from infested ESB gills, and quickly becoming early tomonts were purified by Percoll&reg, density gradient. Tomont total RNA was processed and quality was assessed immediately. cDNA libraries were constructed using TruSeq&reg, Stranded mRNA kit and sequenced using Illumina sequencer. CLC assembly was used to generate the Transcriptome assembly of AO tomonts. Out of 48,188 contigs, 56.12% belong to dinophyceae wherein Symbiodinium microadriaticum had 94.61% similarity among dinophyceae. Functional annotations of contigs indicated that 12,677 had associated GO term, 9005 with KEGG term. The contigs belonging to dinophyceae resulted in the detection of several peptidases. A BLAST search for known virulent factors from the virulence database resulted in hits to Rab proteins, AP120, Ribosomal phosphoprotein, Heat-shock protein70, Casein kinases, Plasmepsin IV, and Brucipain. Hsp70 and casein kinase II alpha were characterized in-silico. Altogether, these results provide a reference database in understanding AO molecular biology, aiding to the development of novel diagnostics and future vaccines.

Allelic imbalance (AI) occurs when alleles in a diploid individual are differentially expressed and indicates cis acting regulatory variation. What is the distribution of allelic effects in a natural population? Are all alleles the same? Are all alleles distinct? Tests of allelic effect are performed by crossing individuals and comparing expression between alleles directly in the F1. However, a crossing scheme that compares alleles pairwise is a prohibitive cost for more than a handful of alleles as the number of crosses is at least (n2-n)/2 where n is the number of alleles. We show here that a testcross design followed by a hypothesis test of AI between testcrosses can be used to infer differences between non-tester alleles, allowing n alleles to be compared with n crosses. Using a mouse dataset where both testcrosses and direct comparisons have been performed, we show that ∼75% of the predicted differences between non-tester alleles are validated in a background of ∼10% differences in AI. The testing for AI involves several complex bioinformatics steps. BASE is a complete bioinformatics pipeline that incorporates state-of-the-art error reduction techniques and a flexible Bayesian approach to estimating AI and formally comparing levels of AI between conditions. The modular structure of BASE has been packaged in Galaxy, made available in Nextflow and sbatch. (https://github.com/McIntyre-Lab/BASE_2020). In the mouse data, the direct test identifies more cis effects than the testcross. Cis-by-trans interactions with trans-acting factors on the X contributing to observed cis effects in autosomal genes in the direct cross remains a possible explanation for the discrepancy.

Sweet cherry (Prunus avium L.) trees are both economically important fruit crops but also important components of natural forest ecosystems in Europe, Asia and Africa. Wild and domesticated trees currently coexist in the same geographic areas with important questions arising on their historical relationships. Little is known about the effects of the domestication process on the evolution of the sweet cherry genome. We assembled and annotated the genome of the cultivated variety "Big Star*" and assessed the genetic diversity among 97 sweet cherry accessions representing three different stages in the domestication and breeding process (wild trees, landraces and modern varieties). The genetic diversity analysis revealed significant genome-wide losses of variation among the three stages and supports a clear distinction between wild and domesticated trees, with only limited gene flow being detected between wild trees and domesticated landraces. We identified 11 domestication sweeps and five breeding sweeps covering, respectively, 11.0 and 2.4 Mb of the P. avium genome. A considerable fraction of the domestication sweeps overlaps with those detected in the related species, Prunus persica (peach), indicating that artificial selection during domestication may have acted independently on the same regions and genes in the two species. We detected 104 candidate genes in sweep regions involved in different processes, such as the determination of fruit texture, the regulation of flowering and fruit ripening and the resistance to pathogens. The signatures of selection identified will enable future evolutionary studies and provide a valuable resource for genetic improvement and conservation programs in sweet cherry.

The transcriptional regulatory structure of plant genomes is still relatively unexplored, and little is known about factors that influence expression variation in plants. We used a genetic system consisting of 10 heterozygous grape varieties with high consanguinity and high haplotypic diversity to: (i) identify regions of haplotype sharing through whole-genome resequencing and single-nucleotide polymorphism (SNP) genotyping; (ii) analyse gene expression through RNA-seq in four stages of berry development; and (iii) associate gene expression variation with genetic and epigenetic properties. We found that haplotype sharing in and around genes was positively correlated with similarity in expression and was negatively correlated with the fraction of differentially expressed genes. Genetic and epigenetic properties of the gene and the surrounding region showed significant effects on the extent of expression variation, with negative associations for the level of gene body methylation and mean expression level, and with positive associations for nucleotide diversity, structural diversity and ratio of non-synonymous to synonymous nucleotide diversity. We also observed a spatial dependency of covariation of gene expression among varieties. These results highlight relevant roles for cis-acting factors, selective constraints and epigenetic features of the gene, and the regional context in which the gene is located, in the determination of expression variation. OPEN RESEARCH BADGES: This article has earned an Open Data Badge for making publicly available the digitally-shareable data necessary to reproduce the reported results. The data is available at https://www.ncbi.nlm.nih.gov/bioproject/PRJNA385116; https://www.ncbi.nlm.nih.gov/bioproject/PRJNA392287; https://www.ncbi.nlm.nih.gov/bioproject/PRJNA373967 (released upon publication); https://www.ncbi.nlm.nih.gov/bioproject/PRJNA490160 (released upon publication); https://www.ncbi.nlm.nih.gov/bioproject/PRJNA265039; https://www.ncbi.nlm.nih.gov/bioproject/PRJNA265040.

Background and Aims The advent of molecular breeding is advocated to improve the productivity and sustainability of second-generation bioenergy crops. Advanced molecular breeding in bioenergy crops relies on the ability to massively sample the genetic diversity. Genotyping-by-sequencing has become a widely adopted method for cost-effective genotyping. It basically requires no initial investment for design as compared with array-based platforms which have been shown to offer very robust assays. The latter, however, has the drawback of being limited to analyse only the genetic diversity accounted during selection of a set of polymorphisms and design of the assay. In contrast, genotyping-by-sequencing with random sampling of genomic loci via restriction enzymes or random priming has been shown to be fast and convenient but lacks the ability to target specific regions of the genome and to maintain high reproducibility across laboratories. Methods Here we present a first adoption of single-primer enrichment technology (SPET) which provides a highly efficient and scalable system to obtain targeted sequence-based large genotyping data sets, bridging the gaps between array-based systems and traditional sequencing-based protocols. To fully explore SPET performance, we conducted a benchmark study in ten Zea mays lines and a large-scale study of a natural black poplar population of 540 individuals with the aim of discovering polymorphisms associated with biomass-related traits. Key Results Our results showed the ability of this technology to provide dense genotype information on a customized panel of selected polymorphisms, while yielding hundreds of thousands of untargeted variable sites. This provided an ideal resource for association analysis of natural populations harbouring unexplored allelic diversities and structure such as in black poplar. Conclusion The improvement of sequencing throughput and the development of efficient library preparation methods has made it feasible to carry out targeted genotyping-by-sequencing experiments cost-competitively with either random complexity reduction systems or traditional array-based platforms, while maintaining the key advantages of both technologies.

This DIB article provides details about transcriptional and physiological response of Fe- and P-deficient white lupin roots, an extensive and complete description of plant response is shown in the research article “Physiological and transcriptomic data highlight common features between iron and phosphorus acquisition mechanisms in white lupin roots” Venuti et al. [1].White lupin plants were grown under hydroponic system and three different nutritional regimes: Fe deficiency (-Fe), P deficiency (-P), or Fe and P sufficiency (+P + Fe).Depending on nutritional treatment, white lupin plants showed changes in the fresh weights, in root external acidification and FeIII-reductase activity. Moreover, the transcriptomic changes occurring in apices and clusters of Fe-deficient lupin roots were investigated and compared with differences of gene expression occurring in P-deficient plants (-P) and in Fe- and P-sufficient plants (+P + Fe). Transcriptomic data are available in the public repository Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo) under the series entry (GSE112220). The annotation, mapping and enrichment analyses of differentially modulated transcripts were assessed. Keywords: Fe acquisition, Nutrient transporters, P acquisition, Plant nutrition, RNA-seq, Root transcriptome, Root uptake, Strategy-I

Biological plausibility and other prior information could help select genome-wide association (GWA) findings for further follow-up, but there is no consensus on which types of knowledge should be considered or how to weight them. We used experts' opinions and empirical evidence to estimate the relative importance of 15 types of information at the single-nucleotide polymorphism (SNP) and gene levels. Opinions were elicited from 10 experts using a two-round Delphi survey. Empirical evidence was obtained by comparing the frequency of each type of characteristic in SNPs established as being associated with seven disease traits through GWA meta-analysis and independent replication, with the corresponding frequency in a randomly selected set of SNPs. SNP and gene characteristics were retrieved using a specially developed bioinformatics tool. Both the expert and the empirical evidence rated previous association in a meta-analysis or more than one study as conferring the highest relative probability of true association, whereas previous association in a single study ranked much lower. High relative probabilities were also observed for location in a functional protein domain, although location in a region evolutionarily conserved in vertebrates was ranked high by the data but not by the experts. Our empirical evidence did not support the importance attributed by the experts to whether the gene encodes a protein in a pathway or shows interactions relevant to the trait. Our findings provide insight into the selection and weighting of different types of knowledge in SNP or gene prioritization, and point to areas requiring further research.

Grapevine, cultivated for both fruit and beverage production, represents one of the most economically important fruit crops worldwide. With the aim of better understanding how grape roots respond to beneficial microbes, a transcriptome sequencing experiment has been performed to evaluate the impact of a single arbuscular mycorrhizal (AM) fungal species (Funneliformis mosseae) versus a mixed inoculum containing a bacterial and fungal consortium, including different AM species, on Richter 110 rootstock. Results showed that the impact of a single AM fungus and of a complex microbial inoculum on the grapevine transcriptome differed. After 3 months, roots exclusively were colonized after the F. mosseae treatment and several AM marker genes were found to be upregulated. The mixed inoculum led only to traces of colonization by AM fungi, but elicited an important transcriptional regulation. Additionally, the expression of genes belonging to categories such as nutrient transport, transcription factors, and cell wall-related genes was significantly altered in both treatments, but the exact genes affected differed in the two conditions. These findings advance our understanding about the impact of soil beneficial microbes on the root system of a woody plant, also offering the basis for novel approaches in grapevine cultivation.

Retrotransposons represent a major component of plant genomes; however, large-scale studies on their expression are rare. Massively parallel sequencing offers new analytical possibilities enabling a comprehensive study of retrotransposon RNA transcription. We evaluated the expression of long terminal repeat-retrotransposons in leaves of two sister hybrids Populus × canadensis (P. deltoides × P. nigra), subjected to moderate or severe water deprivation by mapping Illumina RNA-Seq reads onto a set of 958 unique full-length retrotransposons of P. trichocarpa. Detectable levels of transcription were ascertained for 140 retrotransposons in 1 hybrid and 182 in the other. The two hybrids showed different retrotransposon expression levels, and these differences reduced at increasing drought levels. The number of expressed Gypsy elements in control and water-deprived plants was higher than those of Copia, as were their expression levels. The two hybrids showed different retrotransposon expression patterns following water deprivation. Such variations between hybrids were related to differential expression of a few genes involved in chromatin methylation and remodeling. Overall, our data indicate that even in genetically close individuals, large differences can occur in retrotransposon expression, with possible consequences for genome differentiation.

Common variants, such as those identified by genome-wide association scans, explain only a small proportion of trait variation. Growing evidence suggests that rare functional variants, which are usually missed by genome-wide association scans, play an important role in determining the phenotype. We used pooled multiplexed next-generation sequencing and a customized analysis workflow to detect mutations in five candidate genes for lignin biosynthesis in 768 pooled Populus nigra accessions. We identified a total of 36 non-synonymous single nucleotide polymorphisms, one of which causes a premature stop codon. The most common variant was estimated to be present in 672 of the 1536 tested chromosomes, while the rarest was estimated to occur only once in 1536 chromosomes. Comparison with individual Sanger sequencing in a selected sub-sample confirmed that variants are identified with high sensitivity and specificity, and that the variant frequency was estimated accurately. This proposed method for identification of rare polymorphisms allows accurate detection of variation in many individuals, and is cost-effective compared to individual sequencing.

Common variants, such as those identified by genome-wide association scans, explain only a small proportion of trait variation. Growing evidence suggests that rare functional variants, which are usually missed by genome-wide association scans, play an important role in determining the phenotype. We used pooled multiplexed next-generation sequencing and a customized analysis workflow to detect mutations in five candidate genes for lignin biosynthesis in 768 pooled Populus nigra accessions. We identified a total of 36 non-synonymous single nucleotide polymorphisms, one of which causes a premature stop codon. The most common variant was estimated to be present in 672 of the 1536 tested chromosomes, while the rarest was estimated to occur only once in 1536 chromosomes. Comparison with individual Sanger sequencing in a selected sub-sample confirmed that variants are identified with high sensitivity and specificity, and that the variant frequency was estimated accurately. This proposed method for identification of rare polymorphisms allows accurate detection of variation in many individuals, and is cost-effective compared to individual sequencing.

The genetic determinants of variation in iron status are actively sought, but remain incompletely understood. Meta-analysis of two genome-wide association (GWA) studies and replication in three independent cohorts was performed to identify genetic loci associated in the general population with serum levels of iron and markers of iron status, including transferrin, ferritin, soluble transferrin receptor (sTfR) and sTfR-ferritin index. We identified and replicated a novel association of a common variant in the type-2 transferrin receptor (TFR2) gene with iron levels, with effect sizes highly consistent across samples. In addition, we identified and replicated an association between the HFE locus and ferritin and confirmed previously reported associations with the TF, TMPRSS6 and HFE genes. The five replicated variants were tested for association with expression levels of the corresponding genes in a publicly available data set of human liver samples, and nominally statistically significant expression differences by genotype were observed for all genes, although only rs3811647 in the TF gene survived the Bonferroni correction for multiple testing. In addition, we measured for the first time the effects of the common variant in TMPRSS6, rs4820268, on hepcidin mRNA in peripheral blood (n = 83 individuals) and on hepcidin levels in urine (n = 529) and observed an association in the same direction, though only borderline significant. These functional findings require confirmation in further studies with larger sample sizes, but they suggest that common variants in TMPRSS6 could modify the hepcidin-iron feedback loop in clinically unaffected individuals, thus making them more susceptible to imbalances of iron homeostasis.

As major risk-factors for diabetes and cardiovascular diseases, the genetic contribution to obesity-related traits has been of interest for decades. Recently, a limited number of common genetic variants, which have replicated in different populations, have been identified. One approach to increase the statistical power in genetic mapping studies is to focus on populations with increased levels of linkage disequilibrium (LD) and reduced genetic diversity. We have performed joint linkage and genome-wide association analyses for weight and BMI in 3,448 (linkage) and 3,925 (association) partly overlapping healthy individuals from five European populations. A total of four chromosomal regions (two for weight and two for BMI) showed suggestive linkage (lod > 2.69) either in one of the populations or in the joint data. At the genome-wide level (nominal P < 1.6 x 10(-7), Bonferroni-adjusted P < 0.05) one single-nucleotide polymorphism (SNP) (rs12517906) (nominal P = 7.3 x 10(-8)) was associated with weight, whereas none with BMI. The SNP associated with weight is located close to MGAT1. The monoacylglycerol acyltransferase (MGAT) enzyme family is known to be involved in dietary fat absorption. There was no overlap between the linkage regions and the associated SNPs. Our results show that genetic effects influencing weight and BMI are shared across diverse European populations, even though some of these populations have experienced recent population bottlenecks and/or been affected by genetic drift. The analysis enabled us to identify a new candidate gene, MGAT1, associated with weight in women.

Plasma concentrations of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with plasma lipids in >100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P-8), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (for example, CYP7A1, NPC1L1 and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and have an impact on lipid traits in three non-European populations (East Asians, South Asians and African Americans). Our results identify several novel loci associated with plasma lipids that are also associated with CAD. Finally, we validated three of the novel genes-GALNT2, PPP1R3B and TTC39B-with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD. © 2010 Macmillan Publishers Limited. All rights reserved.

A genetic marker screening panel, ParkScreen, optimized for simultaneous marker amplification, was constructed to test or exclude linkage in families with parkinsonism or Parkinson's disease, using only a few affected individuals per family. ParkScreen functionality was proven by detection of linkage to PARK2 in a family with known Parkin mutations, exclusion of linkage to several of the known loci, and detection of suggestive linkage to PARK8, PARK3, and PARK11 in some families. In a novel approach, we also tested the ability of ParkScreen to screen patients originating from isolated populations. Using apparently sporadic patients from geographically isolated Alpine villages, suggestive linkage to PARK11 was found in one village. ParkScreen is a useful and inexpensive tool that allows the rapid screening of patients in families suitable for clinical follow-up and further characterization in order to identify specific mutations or novel genes. A genetic marker screening panel, ParkScreen, optimized for simultaneous marker amplification, was constructed to test or exclude linkage in families with parkinsonism or Parkinson's disease, using only a few affected individuals per family. ParkScreen functionality was proven by detection of linkage to PARK2 in a family with known Parkin mutations, exclusion of linkage to several of the known loci, and detection of suggestive linkage to PARK8, PARK3, and PARK11 in some families. In a novel approach, we also tested the ability of ParkScreen to screen patients originating from isolated populations. Using apparently sporadic patients from geographically isolated Alpine villages, suggestive linkage to PARK11 was found in one village. ParkScreen is a useful and inexpensive tool that allows the rapid screening of patients in families suitable for clinical follow-up and further characterization in order to identify specific mutations or novel genes. © Humana Press 2009.

Estimating the age of founder mutations may contribute to improve our knowledge of population genetics and evolutionary history of diseases. Previous haplotype analysis suggested that the BRCA1*1499insA mutation was a founder allele, probably originated in Tuscany (Italy). Here, we collected additional pedigrees carrying this mutation, and applied a phylogenetic method for estimating mutation age. A chromosome segment of about 25 cM, including 37 short tandem repeats (STRs) on both sides of the BRCA1 gene (DeCode map), was typed in 50 subjects (28 mutation carriers) from 14 unrelated families. The time to the most recent common ancestor (MRCA) of the mutation carriers was estimated by the length of the shared haplotype between all possible pairs of individuals. A function relating the length of the shared haplotype to the time to the MRCA was obtained by a computer simulation. This approach gives results comparable with those of other existing mutation-dating methods, but does not depend explicitly on population-specific parameters such as allele frequencies, provides narrower confidence intervals (CI), and allows one to build an extended genealogical tree of all mutation carriers. The 1499insA mutation shared by the investigated subjects was estimated to be present in an individual living about 30 generations ago (95% CL 22-56), or 750 years (95% CL 550-1,400).

Article en open access; International audience; Many recent studies have emphasized the important role of structural variation (SV) in determining human genetic and phenotypic variation. In plants, studies aimed at elucidating the extent of SV are still in their infancy. Evidence has indicated a high presence and an active role of SV in driving plant genome evolution in different plant species. With the aim of characterizing the size and the composition of the poplar pan-genome, we performed a genome-wide analysis of structural variation in three intercrossable poplar species: Populus nigra, Populus deltoides and Populus trichocarpa. We detected a total of 7,889 deletions and 10,586 insertions relative to the P. trichocarpa reference genome, covering respectively 33.2 Mb and 62.9 Mb of genomic sequence, and 3,230 genes affected by copy number variation (CNV). The majority of the detected variants are inter-specific in agreement with a recent origin following separation of species. Insertions and deletions (INDELs) were preferentially located in low-gene density regions of the poplar genome and were, for the majority, associated with the activity of transposable elements. Genes affected by SV showed lower-than-average expression levels and higher levels of dN/dS, suggesting that they are subject to relaxed selective pressure or correspond to pseudogenes. Functional annotation of genes affected by INDELs showed over-representation of categories associated with transposable elements activity, while genes affected by genic CNVs showed enrichment in categories related to resistance to stress and pathogens. This study provides a genome-wide catalogue of SV and the first insight on functional and structural properties of the poplar pan-genome.

Mutation-predicting models can be useful when deciding on the genetic testing of individuals at risk and in determining the cost effectiveness of screening strategies at the population level. The aim of this study was to evaluate the performance of a newly developed genetic model that incorporates tumor microsatellite instability (MSI) information, called the AIFEG model, and in predicting the presence of mutations in MSH2 and MLH1 in probands with suspected hereditary non-polyposis colorectal cancer. The AIFEG model is based on published estimates of mutation frequencies and cancer penetrances in carriers and non-carriers and employs the program MLINK of the FASTLINK package to calculate the proband's carrier probability. Model performance is evaluated in a series of 219 families screened for mutations in both MSH2 and MLH1, in which 68 disease-causing mutations were identified. Predictions are first obtained using family history only and then converted into posterior probabilities using information on MSI. This improves predictions substantially. Using a probability threshold of 10% for mutation analysis, the AIFEG model applied to our series has 100% sensitivity and 71% specificity.

Mutations in BRCA1 and BRCA2 show different expressivity with respect to cancer risk, and allelic heterogeneity may be present in both genes. We collected 179 pedigrees with identified germline mutation (104 BRCA1 and 75 BRCA2), ascertained in six collaborating centers of the Italian Consortium for Hereditary Breast and Ovarian Cancer. Significant heterogeneity was detected for several variables, and a logistic regression model including age of diagnosis in the proband, presence of ovarian cancer in the family, presence of prostate or pancreatic cancer in the family, and presence of male breast cancer in the family proved to be effective in predicting the presence of a mutation in a gene rather than the other. Excess of familial aggregation of both breast and ovarian cancer was observed in both genes. Proportion of ovarian cancer was increased in the 5' portion of BRCA1, and presence of prostate or pancreatic cancer in a family was correlated with presence of ovarian cancer in BRCA2.