Expanding the phenotypic spectrum of mutations in LRP2: a novel candidate gene of non-syndromic familial comitant strabismus

Background Comitant strabismus (CS) is a heterogeneous disorder that is a major contributing factor to unilateral childhood-onset visual impairment. Studies have confirmed that genetic factors play an important role in the development of CS. The aim of this study was to identify the genetic cause of non-syndromic familial CS. Methods Fourteen unrelated CS families were recruited for the study. Twelve affected and 2 unaffected individuals from a large four-generation family (CS08) were selected to perform whole genome-wide linkage analysis. Parallel whole-exome sequencing (WES) was conducted in the same family (9 patients and 1 unaffected member) and 31 additional CS cases from 13 other unrelated families. Sanger sequencing was used to determine whether any of the remaining variants co-segregated with the disease phenotype in the corresponding family. Results Based on linkage analysis, CS in family CS08 mapped to a novel region of 34.17 centimorgan (cM) on chromosome 2q22.3-2q32.1 between markers D2S151 and D2S364, with a maximum log odds (LOD) score of 3.54 (theta = 0) at D2S142. Parallel WES identified a heterozygous variant, LRP2 c.335 A > G (p.Q112R), located in such a linkage interval that completely co-segregated with the disease in the family. Furthermore, another novel heterozygous variant (c.7274A > G, p.D2425G) in LRP2 that co-segregated was detected in 2 additional affected individuals from another unrelated family by WES. Both variants are predicted to be damaging by PolyPhen-2, SIFT and MutationTaster, and were absent in 100 ethnically matched normal controls. Conclusion LRP2 is a novel candidate genetic cause of non-syndromic familial CS.

New locus underlying auriculocondylar syndrome (ARCND): 430 kb duplication involving TWIST1 regulatory elements

BackgroundAuriculocondylar syndrome (ARCND) is a rare genetic disease that affects structures derived from the first and second pharyngeal arches, mainly resulting in micrognathia and auricular malformations. To date, pathogenic variants have been identified in three genes involved in the EDN1-DLX5/6 pathway (PLCB4, GNAI3 and EDN1) and some cases remain unsolved. Here we studied a large unsolved four-generation family.MethodsWe performed linkage analysis, resequencing and Capture-C to investigate the causative variant of this family. To test the pathogenicity of the CNV found, we modelled the disease in patient craniofacial progenitor cells, including induced pluripotent cell (iPSC)-derived neural crest and mesenchymal cells.ResultsThis study highlights a fourth locus causative of ARCND, represented by a tandem duplication of 430 kb in a candidate region on chromosome 7 defined by linkage analysis. This duplication segregates with the disease in the family (LOD score=2.88) and includes HDAC9, which is located over 200 kb telomeric to the top candidate gene TWIST1. Notably, Capture-C analysis revealed multiple cis interactions between the TWIST1 promoter and possible regulatory elements within the duplicated region. Modelling of the disease revealed an increased expression of HDAC9 and its neighbouring gene, TWIST1, in neural crest cells. We also identified decreased migration of iPSC-derived neural crest cells together with dysregulation of osteogenic differentiation in iPSC-affected mesenchymal stem cells.ConclusionOur findings support the hypothesis that the 430 kb duplication is causative of the ARCND phenotype in this family and that deregulation of TWIST1 expression during craniofacial development can contribute to the phenotype.

Genetic Analysis and Gene Mapping of Two Whitebacked Planthopper Resistance Genes From Rice Varieties

Background The whitebacked planthopper (WBPH) has become a significant threat to rice production. Identification of WBPH-resistant germplasm and genes can drive efforts to develop resistance varieties and effectively limit pest damage.Methods Fourteen varieties of rice were surveyed for insect resistance using tests that assessed bulk seedling growth rates, insect feeding activity (via measurements of honeydew excretion weight), and insect development (by counting the number of hatched nymphs). Two resistance varieties N22 and OB677 were crossed with susceptible line 9311 to develop mapping populations, which were applied to map the resistance genes/QTLs.Results The rice variety PTB33 showed high resistance to both brown planthopper (BPH) and WBPH, and varieties N22, RBPH327, and OB677 showed moderate resistance to WBPH. Host choice test and seedling survival rates further verified the WBPH resistance of PTB33, N22, and OB677. By using two F2 mapping populations, two major resistance genes were detected in N22 and OB677. Wbph1 was mapped on chromosome 2 of N22 in a region that harbored the markers RM13650 and RM13478. Its largest logarithm of the odds (LOD) score was 3.94, which explained a 16.6% phenotypic variation. Wbph9 was mapped on chromosome 3 of OB677, where it was flanked by markers RM3513 and RM3525. It had a LOD score of 3.4, explaining a 17.2% phenotypic variation.Conclusions Four varieties PTB33, N22, RBPH327, and OB677 showed resistance to WBPH, of which OB677 was a novel resistance germplasm; and a novel resistance gene Wbph9 was mapped on chromosome 3.

Substitution Mapping of a Locus Responsible for Hybrid Breakdown in Populations Derived From Interspecific Introgression Line

Hybrid breakdown, a form of postzygotic reproductive barrier, has been reported to hinder gene flow in many crosses between wild and cultivated rice. Here, the phenomenon of hybrid breakdown was observed as low-tillering (i.e., low tiller number) in some progeny of an interspecific cross produced in an attempt to introduce Oryza meridionalis Ng (W1625) chromosomal segments into Oryza sativa L. ssp. japonica “Taichung 65” (T65). Low-tillering lines were obtained in BC4-derived progeny from a cross between W1625 and “Taichung 65,” but the locus for low-tillering could not be mapped in segregating populations. As a second approach to map the locus for low-tillering, we analyzed an F2 population derived from a cross between the low-tillering lines and a high-yielding indica cultivar, “Takanari.” A major QTL for low-tillering, qLTN4, was detected between PCR-based markers MS10 and RM307 on the long arm of chromosome 4, with a LOD score of 15.6. The low-tillering phenotype was associated with weak growth and pale yellow phenotype; however, low-tillering plant had less reduction of grain fertility. In an F4 population (4896 plants), 563 recombinant plants were identified and the low-tillering locus was delimited to a 4.6-Mbp region between markers W1 and C5-indel3729. This region could not be further delimited because recombination is restricted in this region of qLTN4, which is near the centromere. Understanding the genetic basis of hybrid breakdown, including the low-tillering habit, will be important for improving varieties in rice breeding.

A statistical framework for QTL hotspot detection

Quantitative trait loci (QTL) hotspots (genomic locations enriched in QTL) are a common and notable feature when collecting many QTL for various traits in many areas of biological studies. The QTL hotspots are important and attractive since they are highly informative and may harbor genes for the quantitative traits. So far, the current statistical methods for QTL hotspot detection use either the individual-level data from the genetical genomics experiments or the summarized data from public QTL databases to proceed with the detection analysis. These methods may suffer from the problems of ignoring the correlation structure among traits, neglecting the magnitude of LOD scores for the QTL, or paying a very high computational cost, which often lead to the detection of excessive spurious hotspots, failure to discover biologically interesting hotspots composed of a small-to-moderate number of QTL with strong LOD scores, and computational intractability, respectively, during the detection process. In this article, we describe a statistical framework that can handle both types of data as well as address all the problems at a time for QTL hotspot detection. Our statistical framework directly operates on the QTL matrix and hence has a very cheap computational cost and is deployed to take advantage of the QTL mapping results for assisting the detection analysis. Two special devices, trait grouping and top γn,α profile, are introduced into the framework. The trait grouping attempts to group the traits controlled by closely linked or pleiotropic QTL together into the same trait groups and randomly allocates these QTL together across the genomic positions separately by trait group to account for the correlation structure among traits, so as to have the ability to obtain much stricter thresholds and dismiss spurious hotspots. The top γn,α profile is designed to outline the LOD-score pattern of QTL in a hotspot across the different hotspot architectures, so that it can serve to identify and characterize the types of QTL hotspots with varying sizes and LOD-score distributions. Real examples, numerical analysis, and simulation study are performed to validate our statistical framework, investigate the detection properties, and also compare with the current methods in QTL hotspot detection. The results demonstrate that the proposed statistical framework can effectively accommodate the correlation structure among traits, identify the types of hotspots, and still keep the notable features of easy implementation and fast computation for practical QTL hotspot detection.

Pedigree-Based Gene Mapping Supports Previous Loci and Reveals Novel Suggestive Loci in Specific Language Impairment

Purpose Specific language impairment (SLI) is characterized by a delay in language acquisition despite a lack of other developmental delays or hearing loss. Genetics of SLI is poorly understood. The purpose of this study is to identify SLI genetic loci through family-based linkage mapping. Method We performed genome-wide parametric linkage analysis in six families segregating with SLI. An age-appropriate standardized omnibus language measure was used to categorically define the SLI phenotype. Results A suggestive linkage region replicated a previous region of interest with the highest logarithm of odds (LOD) score of 2.40 at 14q11.2-q13.3 in Family 489. A paternal parent-of-origin effect associated with SLI and language phenotypes on a nonsynonymous single nucleotide polymorphism (SNP) in NOP9 (14q12) was reported previously. Linkage analysis identified a new SLI locus at 15q24.3-25.3 with the highest parametric LOD score of 3.06 in Family 315 under a recessive mode of inheritance. Suggestive evidence of linkage was also revealed at 4q31.23-q35.2 in Family 300, with the highest LOD score of 2.41. Genetic linkage was not identified in the other three families included in parametric linkage analysis. Conclusions These results are the first to report genome-wide suggestive linkage with a total language standard score on an age-appropriate omnibus language measure across a wide age range. Our findings confirm previous reports of a language-associated locus on chromosome 14q, report new SLI loci, and validate the pedigree-based parametric linkage analysis approach to mapping genes for SLI. Supplemental Material https://doi.org/10.23641/asha.13203218

ANALISIS KADAR MERKURI PADA BIOTA AIR DENGAN NANOPARTIKEL PERAK SECARA CITRA DIGITAL DI LOKASI PENAMBANGAN EMAS KABUPATEN LEBONG

This study aimed at determining of how the sensitivity of silver nanoparticles (NPP) in detecting metal mercury in aquatic biota samples through digital imagery. The Sampling of aquatic biota was carried out in the gold mining location of Lebong Tambang village in Lebong district (102 ° 12'00 "-102 ° 18'05" BT and 3 ° 10'00 "-3 ° 17 ' 00 "LS.) The aquatic biota samples analyzed included fish, shellfish, shrimp and plants as well as comparison samples such as water and sediment. The Analysis of mercury level was carried out from December 2018 - March 2019 by using NPP of digital imagery method. The digital imagery method was used as a detector to replace the conventional spectrophotometer. The result of mercury level in aquatic biota with NPP in digital imagery was susceptible compared to the UV-Vis spectrophotometry method. It can be seen from the Limit Of Detection (LOD) score of the digital imagery method with the SLR data analysis technique by using a digital camera that is equal to 2.305 ppb, where the score was smaller than the LOD value in spectrophotometry which is 300 ppb. The results of the analysis of mercury level by using digital imagery method were obtained the concentration on pool shells of 196.8 ppb, in pond fish samples of 155.7 ppb, in shrimp samples of 81.2 ppb, in river fish samples of 81.1 ppb, and in plant samples of 50.9 ppb. thus, these results indicate that the presence of mercury ions in the samples of aquatic biota tested has levels above the threshold, which means samples of fish, shrimp, shellfish and plants were risk to be consumed

Role of an Atypical Cadherin Gene, Cdh23 in Prepulse Inhibition and Implication of CDH23 in Schizophrenia

We previously identified quantitative trait loci (QTL) for prepulse inhibition (PPI), an endophenotype of schizophrenia, on mouse chromosome 10 and reported Fabp7 as a candidate gene from an analysis of F2 mice from inbred strains with high (C57BL/6N; B6) and low (C3H/HeN; C3H) PPI levels. Here, we reanalyzed the previously reported QTLs with increased marker density. The highest LOD score (26.66) peaked at a synonymous coding and splice-site variant, c.753G>A (rs257098870), in the Cdh23 gene on chromosome 10; the c.753G (C3H) allele showed a PPI-lowering effect. Bayesian multiple QTL mapping also supported the same variant with a posterior probability of 1. Thus, we engineered the c.753G (C3H) allele into the B6 genetic background, which led to dampened PPI. We also revealed an e-QTL (expression-QTL) effect imparted by the c.753G>A variant for the Cdh23 expression in the brain. In a human study, a homologous variant (c.753G>A; rs769896655) in CDH23 showed a nominally significant enrichment in individuals with schizophrenia. We also identified multiple potentially deleterious CDH23 variants in individuals with schizophrenia. Collectively, the present study reveals a PPI-regulating Cdh23 variant and a possible contribution of CDH23 to schizophrenia susceptibility.

A Statistical Framework for QTL Hotspot Detection

ABSTRACTQuantitative trait loci (QTL) hotspots (genomic locations enriched in QTL) are a common and notable feature when collecting many QTL for various traits in many areas of biological studies. The QTL hotspots are important and attractive since they are highly informative and may harbor genes for the quantitative traits. So far, the current statistical methods for QTL hotspot detection use either the individual-level data from the genetical genomics experiments or the summarized data from public QTL databases to proceed with the detection analysis. These detection methods attempt to address some of the concerns, including the correlation structure among traits, the magnitude of LOD scores within a hotspot and computational cost, that arise during the process of QTL hotspot detection. In this article, we describe a statistical framework that can handle both types of data as well as address all the concerns at a time for QTL hotspot detection. Our statistical framework directly operates on the QTL matrix and hence has a very cheap computation cost, and is deployed to take advantage of the QTL mapping results for assisting the detection analysis. Two special devices, trait grouping and top γn,α profile, are introduced into the framework. The trait grouping attempts to group the closely linked or pleiotropic traits together to take care of the true linkages and cope with the underestimation of hotspot thresholds due to non-genetic correlations (arising from ignoring the correlation structure among traits), so as to have the ability to obtain much stricter thresholds and dismiss spurious hotspots. The top γn,α profile is designed to outline the LOD-score pattern of a hotspot across the different hotspot architectures, so that it can serve to identify and characterize the types of QTL hotspots with varying sizes and LOD score distributions. Real examples, numerical analysis and simulation study are performed to validate our statistical framework, investigate the detection properties, and also compare with the current methods in QTL hotspot detection. The results demonstrate that the proposed statistical framework can effectively accommodate the correlation structure among traits, identify the types of hotspots and still keep the notable features of easy implementation and fast computation for practical QTL hotspot detection.

Analysis of HCM in an understudied population reveals a new mechanism of pathogenicity

Hypertrophic Cardiomyopathy (HCM) is an inherited disease characterized by genetic and phenotypic heterogeneity. MYH7 represents one of the main sarcomere-encoding genes associated with HCM. Missense variants in this gene cause HCM through gain-of-function actions, whereby variants produce an abnormal activated protein which incorporates into the sarcomere as a ‘poison peptide’. Here we report a frameshift variant in MYH7, c.5769delG, that is associated with HCM in an Egyptian cohort (3.3%) compared with ethnically-matched controls. This variant is absent from previously published large-scale Caucasian HCM cohorts. We further demonstrate strong evidence of co-segregation of c.5769delG with HCM in a large family (LOD score: 3.01). The predicted sequence of the variant MYH7 transcript shows that the frameshift results in a premature termination codon (PTC) downstream of the last exon-exon junction of the gene that is expected to escape nonsense-mediated decay (NMD). RNA sequencing of myocardial tissue obtained from a patient with the variant during surgical myectomy confirmed the expression of the variant MYH7 transcript. Our analysis reveals a new mechanism of pathogenicity in the understudied Egyptian population whereby distal PTC in MYH7 may lead to the expression of an abnormal protein.