Fig 1 -

(A) Dicrocoelium dendriticum worm showing morphometric features used as variables. [B) Hematoxylin-stained D. dendriticum, variation in testis shape, ovary, and vitelline glands (C) Uterine eggs of D. dendriticum.</p

Fig 2 -

(A) Maximum-likelihood tree of 87 rDNA ITS-2 sequences from four Dicrocoelium species (D. orientalis, D. hospes, D. dendriticum and D. chinensis) obtained from NCBI Genbank. (B) Maximum-likelihood tree of 44 rDNA ITS-2 ASVs obtained from D. dendriticum field and 87 rDNA ITS-2 sequences from four Dicrocoelium species (D. orientalis, D. hospes, D. dendriticum and D. chinensis) obtained from NCBI Genbank. Each species is indicated with different coloured dots.</p

Morphometric values of <i>Dicrocoelium dendriticum</i> field samples (n = 202).

Morphometric values of Dicrocoelium dendriticum field samples (n = 202).</p

<i>Dicrocoelium</i> species identification of individual flukes from 17 populations based on deep sequencing of rDNA ITS-2 genetic marker.

Each population represents the total flukes collected from an individual host.</p

The genetic distances between rDNA ITS-2 sequences of four <i>Dicrocoelium</i> species.

The genetic distances between rDNA ITS-2 sequences of four Dicrocoelium species.</p

The samples were collected during the peak <i>Dicrocoelium</i> transmission seasons from Khyber Pakhtunkhwa and Gilgit Baltistan provinces of Pakistan.

The samples were collected during the peak Dicrocoelium transmission seasons from Khyber Pakhtunkhwa and Gilgit Baltistan provinces of Pakistan.</p

rDNA ITS-2 primer sequences for the amplification of Dicrocoelium.

Forward and reverse primer sets are underlined, N’s are bolded, and adapters are in italic format. (DOCX)</p

Maximum-likelihood tree of rDNA ITS-2 sequences from four <i>Dicrocoelium</i> species (<i>D</i>. <i>orientalis</i>, <i>D</i>. <i>hospes</i>, <i>D</i>. <i>dendriticum</i> and <i>D</i>. <i>chinensis</i>) and two <i>Fasciola</i> species (<i>F</i>. <i>gigantica</i> and <i>F</i>. <i>hepatica</i>) obtained from NCBI Genbank.

The sequences were first aligned using the MUSCLE tool of the Geneious v9.0.1 software. The neighbour-joining algorithm (Kimura 2+G parameter model) was computed with 1000 bootstrap replicates using MEGA5 software created by Biomatters. Each species is identicated with different coloured dots. (JPG)</p

Deep amplicon sequencing data of 202 individual <i>Dicrocoelium</i>, comprising 17 fluke populations from Khyber Pakhtunkhwa and Gilgit Baltistan provinces of Pakistan.

Deep amplicon sequencing data of 202 individual Dicrocoelium, comprising 17 fluke populations from Khyber Pakhtunkhwa and Gilgit Baltistan provinces of Pakistan.</p

Image2_Identification of genetic variants associated with a wide spectrum of phenotypes clinically diagnosed as Sanfilippo and Morquio syndromes using whole genome sequencing.jpeg

Mucopolysaccharidoses (MPSs) are inherited lysosomal storage disorders (LSDs). MPSs are caused by excessive accumulation of mucopolysaccharides due to missing or deficiency of enzymes required for the degradation of specific macromolecules. MPS I-IV, MPS VI, MPS VII, and MPS IX are sub-types of mucopolysaccharidoses. Among these, MPS III (also known as Sanfilippo) and MPS IV (Morquio) syndromes are lethal and prevalent sub-types. This study aimed to identify causal genetic variants in cases of MPS III and MPS IV and characterize genotype-phenotype relations in Pakistan. We performed clinical, biochemical and genetic analysis using Whole Genome Sequencing (WGS) in 14 Pakistani families affected with MPS III or MPS IV. Patients were classified into MPS III by history of aggressive behaviors, dementia, clear cornea and into MPS IV by short trunk, short stature, reversed ratio of upper segment to lower segment with a short upper segment. Data analysis and variant selections were made based on segregation analysis, examination of known MPS III and MPS IV genes, gene function, gene expression, the pathogenicity of variants based on ACMG guidelines and in silico analysis. In total, 58 individuals from 14 families were included in the present study. Six families were clinically diagnosed with MPS III and eight families with MPS IV. WGS revealed variants in MPS-associated genes including NAGLU, SGSH, GALNS, GNPTG as well as the genes VWA3B, BTD, and GNPTG which have not previously associated with MPS. One family had causal variants in both GALNS and BTD. Accurate and early diagnosis of MPS in children represents a helpful step for designing therapeutic strategies to protect different organs from permanent damage. In addition, pre-natal screening and identification of genetic etiology will facilitate genetic counselling of the affected families. Identification of novel causal MPS genes might help identifying new targeted therapies to treat LSDs.</p