Biogeographical origin and timing of the founder ichthyosis TGM1 c.1187G > A mutation in an isolated Ecuadorian population.

An unusually high frequency of the lamellar ichthyosis TGM1 mutation, c.1187G > A, has been observed in the Ecuadorian province of Manabí. Recently, the same mutation has been detected in a Galician patient (Northwest of Spain). By analyzing patterns of genetic variation around this mutation in Ecuadorian patients and population matched controls, we were able to estimate the age of c.1187G > A and the time to their most recent common ancestor (TMRCA) of c.1187G > A Ecuadorian carriers. While the estimated mutation age is 41 generations ago (~1,025 years ago [ya]), the TMRCA of Ecuadorian c.1187G > A carrier haplotypes dates to just 17 generations (~425 ya). Probabilistic-based inferences of local ancestry allowed us to infer a most likely European origin of a few (16% to 30%) Ecuadorian haplotypes carrying this mutation. In addition, inferences on demographic historical changes based on c.1187G > A Ecuadorian carrier haplotypes estimated an exponential population growth starting ~20 generations, compatible with a recent founder effect occurring in Manabí. Two main hypotheses can be considered for the origin of c.1187G > A: (i) the mutation could have arisen in Spain >1,000 ya (being Galicia the possible homeland) and then carried to Ecuador by Spaniards in colonial times ~400 ya, and (ii) two independent mutational events originated this mutation in Ecuador and Galicia. The geographic and cultural characteristics of Manabí could have favored a founder effect that explains the high prevalence of TGM1 c.1187G > A in this region.

The geographic mosaic of Ecuadorian Y-chromosome ancestry.

Ecuadorians originated from a complex mixture of Native American indigenous people with Europeans and Africans. We analyzed Y-chromosome STRs (Y-STRs) in a sample of 415 Ecuadorians (145 using the AmpFlSTR® Yfiler™ system [Life Technologies, USA] and 270 using the PowerPlex®Y23 system [Promega Corp., USA]; hereafter Yfiler and PPY23, respectively) representing three main ecological continental regions of the country, namely Amazon rainforest, Andes, and Pacific coast. Diversity values are high in the three regions, and the PPY23 exhibits higher discrimination power than the Yfiler set. While summary statistics, AMOVA, and RST distances show low to moderate levels of population stratification, inferred ancestry derived from Y-STRs reveal clear patterns of geographic variation. The major ancestry in Ecuadorian males is European (61%), followed by an important Native American component (34%); whereas the African ancestry (5%) is mainly concentrated in the Northwest corner of the country. We conclude that classical procedures for measuring population stratification do not have the desirable sensitivity. Statistical inference of ancestry from Y-STRS is a satisfactory alternative for revealing patterns of spatial variation that would pass unnoticed when using popular statistical summary indices.

PLA2G6 mutations associated with a continuous clinical spectrum from neuroaxonal dystrophy to hereditary spastic paraplegia.

PLA2G6-associated neurodegeneration (PLAN) and hereditary spastic paraplegia (HSP) are 2 groups of heterogeneous neurodegenerative diseases. In this study, we report PLA2G6 gene mutations in 3 families from Turkey, Morocco, and Romania. Two affected Turkish siblings presenting HSP adds the disease to PLAN phenotypes. They were homozygous for the PLA2G6 missense c.2239C>T, p.Arg747Trp variant and the ages of onset were 9 and 21. Parkinsonism, dystonia or cognitive decline were not the clinical elements in these patients contrary to the cases that has been previously reported with the same variant, however, iron accumulation was evident in their cranial magnetic resonance imaging. The Moroccan patient was homozygous for a novel missense c.1786C>T, p.Leu596Phe variant and the Romanian patient had 2 novel mutations; c.1898C>T, p.Ala633Val and c.1765_1768del, p.Ser589ThrfsTer76. Both of these patients conformed better to childhood onset PLAN with the age of onset at 4 and 7 years, respectively. Interestingly, all identified mutations were affecting the highly conserved patatin-like phospholipase domain of the PLA2G6 protein.

Evaluating the Calling Performance of a Rare Disease NGS Panel for Single Nucleotide and Copy Number Variants.

INTRODUCTION: Variant detection protocols for clinical next-generation sequencing (NGS) need application-specific optimization. Our aim was to analyze the performance of single nucleotide variant (SNV) and copy number (CNV) detection programs on an NGS panel for a rare disease. METHODS: Thirty genes were sequenced in 83 patients with hereditary spastic paraplegia. The variant calls obtained with LifeScope, GATK UnifiedGenotyper and GATK HaplotypeCaller were compared with Sanger sequencing. The calling efficiency was evaluated for 187 (56 unique) SNVs and indels. Five multiexon deletions detected by multiple ligation probe assay were assessed from the NGS panel data with ExomeDepth, panelcn.MOPS and CNVPanelizer software. RESULTS: There were 48/51 (94%) SNVs and 1/5 (20%) indels consistently detected by all the calling algorithms. Two SNVs were not detected by any of the callers because of a rare reference allele, and one SNV in a low coverage region was only detected by two algorithms. Regarding CNVs, ExomeDepth detected 5/5 multi-exon deletions, panelcn.MOPs 4/5 and only 3/5 deletions were accurately detected by CNVPanelizer. CONCLUSIONS: The calling efficiency of NGS algorithms for SNVs is influenced by variant type and coverage. NGS protocols need to account for the presence of rare variants in the reference sequence as well as for ambiguities in indel calling. CNV detection algorithms can be used to identify large deletions from NGS panel data for diagnostic applications; however, sensitivity depends on coverage, selection of the reference set and deletion size. We recommend the incorporation of several variant callers in the NGS pipeline to maximize variant detection efficiency.

Medical genomics: The intricate path from genetic variant identification to clinical interpretation.

The field of medical genomics involves translating high throughput genetic methods to the clinic, in order to improve diagnostic efficiency and treatment decision making. Technical questions related to sample enrichment, sequencing methodologies and variant identification and calling algorithms, still need careful investigation in order to validate the analytical step of next generation sequencing techniques for clinical applications. However, the main foreseeable challenge will be interpreting the clinical significance of the variants observed in a given patient, as well as their significance for family members and for other patients. Every step in the variant interpretation process has limitations and difficulties, and its quote of contribution to false positive and false negative results. There is no single piece of evidence enough on its own to make firm conclusions on the pathogenicity and disease causality of a given variant. A plethora of automated analysis software tools is being developed that will enhance efficiency and accuracy. However a risk of misinterpretation could derive from biased biorepository content, facilitated by annotation of variant functional consequences using previous datasets stored in the same or linked repositories. In order to improve variant interpretation and avoid an exponential accumulation of confounding noise in the medical literature, the use of terms in a standard way should be sought and requested when reporting genetic variants and their consequences. Generally, stepwise and linear interpretation processes are likely to overrate some pieces of evidence while underscoring others. Algorithms are needed that allow a multidimensional, parallel analysis of diverse lines of evidence to be carried out by expert teams for specific genes, cellular pathways or disorders.