DOI: 10.5061/dryad.8pk0p2nnj
title: Pathogenic and low frequency variants in children with central precocious puberty

description: Background Central precocious puberty (CPP) due to premature activation of
 GnRH secretion results in early epiphyseal fusion and to a significant
 compromise in the achieved final adult height.  CPP is usually
 idiopathic and is disproportionally observed in girls compared to boys.
 Currently, only few genetic determinants of children with CPP have been
 described and the role they exert on the development of the disorder. In
 this original study rare variants in MKRN3, DLK1, KISS1, KISS1R and MAGEL2
 genes are reported in patients with CPP. Methods Fifty-four index females
 and 2 index males with CPP underwent whole exome sequencing (WES) by Next
 Generation Sequencing (NGS). The identified rare variants were initially
 examined by in silico computational algorithms and confirmed by Sanger
 sequencing. Additionally, a genetic network for the MKRN3 gene mimicking a
 holistic regulatory depiction of the crosstalk between MKRN3 and other
 genes is designed. Results Three previously described pathogenic MKRN3
 variants in the coding region of the gene occurred in 12 index females
 with CPP. With the p.Gly312Asp pathogenic variant of the MKRN3 gene being
 the most prevalent and exclusively found among the Cypriot CPP cohort, it
 is projected to be the result of founder effect phenomenon. In seven
 additional CPP patients from the same cohort several other likely and rare
 pathogenic upstream variants in the MKRN3 gene were also observed. In
 addition to the MKRN3 variants, a total of 16 other rare variants in DLK1,
 KISS1 and MAGEL2 were also identified in other CPP patients from the same
 cohort. Interestingly, the frequent variant rs10407968 (p.Gly8Ter) of the
 KISS1R gene appeared to be less frequent in the cohort of patients with
 CPP. Conclusion The results of the present study denote the key role of
 the imprinted MKRN3 gene in puberty. Additionally, pathogenic variants can
 also exist in the noncoding region of the MKRN3 gene such as the proximal
 promoter and 5’-UTR region and which can also be considered as
 contributing factors to CPP.  Overall, the results of present
 study have emphasised the necessity of the allied genetic and clinical
 approach which is necessary for the management and treatment of CPP.
description: <b>Genetic
 Analysis</b> Genomic DNA was extracted from
 peripheral blood using the Gentra Puregene Kit (Qiagen, Valencia, CA, USA)
 according to the manufacturer’s instructions. The DNA purity was measured
 using the Nanodrop ND-1000 spectrophotometer (NanoDrop Technologies,
 Wilmington, DE, USA). Prior to library preparation for whole exome
 sequencing (WES) genomic DNA was quantified using the Qubit dsDNA BR Assay
 Kit (Invitrogen, Life Technologies, Eugene, OR, USA) on a Qubit® 2.0
 Fluorometer (Invitrogen, Life Technologies, Eugene, OR, USA). WES was
 performed by using the TruSeq Exome Kit (Illumina Inc., San Diego, CA,
 USA) with paired-end 150 bp reads. NGS was performed using the NextSeq
 500/550 High Output Kit v2.5 (150 Cycles) on an NextSeq500 system
 (Illumina Inc., San Diego, CA, USA). The FastQC quality control tool
 (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/) was used to
 evaluate the quality of the WES procedure. The mean target coverage of the
 whole exome was 62.13X. Specifically, 10X coverage was reached for 92.34%
 of the nucleotides, 20X coverage for 86.03% of the nucleotides and 30X
 coverage for 76.96% of the nucleotides, indicating that the WES reaction
 was of sufficiently high quality for subsequent analysis. <b>Variant
 Analysis</b> The fastq data obtained by WES
 were processed using an in-house bioinformatics pipeline. Briefly, all
 variants were inputted into the VarApp Browser and filtered. VarApp is a
 graphical user interface, which supports GEMINI (18). Variants in selected
 genes involved in pubertal onset and were mutations have been reported for
 precocious puberty were further analyzed using the Qualimap v2.2.1 tool to
 calculate the target coverage. Mean target coverage was 60X of the
 selected genes (Supplementary Table 1). Variants in these genes were
 additionally filtered using the VarApp Browser for minor allele
 frequencies of less than 1% in public databases such as 1000 genomes, ExAC
 browser and Exome Sequencing Project (ESP). Moreover, variants were
 filtered and selected according to their impact such as frameshift, splice
 acceptor, splice donor, start lost, stop gained, stop lost, inframe
 deletion, inframe insertion, missense, protein altering and splice region.
 In addition, variants were filtered by the VarApp Browser for their
 pathogenicity by two <i>in silico</i> tools, SIFT and
 Polyphen2. Population-specific data from an in-house WES library composed
 of 43 randomly selected samples of Cypriot origin were used to evaluate
 the potential disease-causing variants. All variants identified were
 confirmed by Sanger sequencing. Finally, the variants were categorized for
 their pathogenicity using the standards and guidelines of the American
 College of Medical Genetics and Genomics and the Association for Molecular
 Pathology.