Potential Causative Mutations Research Articles

Identification of a Homozygous Mutation of CCDC40 in a Chinese Infertile Man with MMAF and PCD-like Phenotypes.

Aims: Asthenozoospermia is the most common factor of male infertility, mainly caused by multiple morphological abnormalities of the sperm flagella (MMAF) and primary ciliary dyskinesia (PCD). Previous studies have shown that genetic factors may contribute to MMAF and PCD. The study aimed to identify novel potentially pathogenic gene mutations in a Chinese infertile man with MMAF and PCD-like phenotypes. Methods: A Chinese infertile man with MMAF and PCD was enrolled in this study. Whole exome sequencing and Sanger sequencing were performed to identify potential causative genes and mutations. Results: A novel homozygous missense mutation (c.1450G>A; p.E484K) of CCDC40 was finally identified and Sanger sequencing confirmed that the patient carried the homozygous mutation, which was inherited from his parents. We reported the first homozygous missense CCDC40 mutation in infertile men with MMAF but had other milder PCD symptoms. Conclusion: Our findings not only broaden the disease-causing mutation spectrum of CCDC40 but also provide new insight into the correlation between CCDC40 mutations and MMAF.

Diagnosis, treatment, and potential causative mutations of cryptogenic plastic bronchitis.

Diagnosis, treatment, and potential causative mutations of cryptogenic plastic bronchitis.

Bioinformatics Methods in Predicting Amyloid Propensity of Peptides and Proteins.

Several computational methods have been developed to predict amyloid propensity of a protein or peptide. These bioinformatics tools are time- and cost-saving alternatives to expensive and laborious experimental methods which are used to confirm self-aggregation of a protein. Computational approaches not only allow preselection of reliable candidates for amyloids but, most importantly, are capable of a thorough and informative analysis of a protein, indicating the sequence determinants of protein aggregation, identifying the potential causal mutations and likely mechanisms. Bioinformatics modeling applies several different approaches, which most typically include physicochemical or structure-based modeling, machine learning, or statistics based modeling. Bioinformatics methods typically use the amino acid sequence of a protein as an input, some also include additional information, for example, an available structure. This chapter describes the methods currently used to computationally predict amyloid propensity of a protein or peptide. Since the accuracy of bioinformatics methods may be highly dependent on reference data used to develop and evaluate the predictors, we also briefly present the main databases of amyloids used by the authors of bioinformatics tools.

Effects of ApoE genotype on clinical phenotypes in early-onset and late-onset Alzheimer's disease in China: Data from the PUMCH dementia cohort.

IntroductionTo investigate the heterogeneous effect of Apolipoprotein E (ApoE) genotype on clinical phenotypes in early‐onset Alzheimer's disease (EOAD) and late‐onset Alzheimer's disease (LOAD), respectively.Methods785 probable AD patients were enrolled from the dementia cohort of Peking Union Medical College Hospital (PUMCH), China. There were 386 EOAD and 399 LOAD cases. All individuals finished history inquiry, neurological examination, blood biochemical test, neuropsychological screening test, electroencephalography, brain CT/MRI, and ApoE genotyping. Some participants had neuropsychological domain assessment (n = 317), MRI morphometry (n = 130), CSF testing of Aβ42, p‐tau, t‐tau (n = 144), or DNA sequencing (n = 690). The variables were compared mainly between ɛ4 carriers and non‐carriers in EOAD and LOAD, respectively.ResultsIn LOAD, ɛ4 carriers showed female predominance; worse performance in trail making test, delayed recall of auditory verbal learning test (AVLT) and rey complex figure; smaller hippocampal, parahippocampal, and entorhinal volume, as compared to ɛ4 non‐carriers. In EOAD, ɛ4 carriers had lower scores in AVLT, episodic memory and modified Luria's tapping task; but less cortical atrophy in entorhinal, middle cingulate, inferior frontal, and parieto‐occipital regions, in comparison to ɛ4 non‐carriers. 6.2% (43/690) subjects harbored potential causative mutations in APP, PSEN1, and PSEN2. In both EOAD and LOAD, no differences were observed between ɛ4 carriers and non‐carriers in CSF levels of Aβ42, p‐tau, t‐tau, or mutation frequency.ConclusionsApoE exerts a heterogeneous effect on clinical phenotypes in EOAD and LOAD, which might be related to the different genetic and pathological basis underlying them.

Whole Exome Sequencing Identifies Two Novel Mutations in a Patient with UC Associated with PSC and SSA.

Background Patients diagnosed with ulcerative colitis (UC) associated with primary sclerosis cholangitis (PSC) and sessile serrated adenoma (SSA) are rare. The present study aimed to identify the potential causative gene mutation in a patient with UC associated with PSC and SSA. Methods DNA was extracted from the blood sample and tissue sample of SSA, followed by the whole exome sequencing (WES) analysis. Bioinformatics analysis was utilized to predict the deleteriousness of the identified variants. Multiple sequence alignment and conserved protein domain analyses were performed using online software. Sanger sequencing was used to validate the identified variants. Expression and diagnostic analysis of identified mutated genes was performed in the GSE119600 dataset (peripheral blood samples of PSC and UC) and GSE43841 dataset (tumor samples of SSA). Results In the present study, a total of 842 single nucleotide variants (SNVs) in 728 genes were identified in the blood sample. Two variants, integrin beta 4 (ITGB4) (c.C2503G; p.P835A) and a mucin 3A (MUC3A) (c.C1019T; p.P340L), were further analyzed. MUC3A was associated with inflammatory bowel disease. Sanger sequence in blood revealed that the ITGB4 mutation was fully cosegregated with the result of WES in the patient. Additionally, a variant, tumor protein p53 gene (TP53) (c.86delA; p.N29Tfs∗15) was identified in the tissue sample of SSA. Compared to that in normal controls, ITGB4 was upregulated in both UC and PSC, MUC3A was, respectively, upregulated and downregulated in PSC and UC, and TP53 was downregulated in SSA. ITGB4 and TP53 had a potential diagnostic value for UC, PSC and SSA. Conclusions The present study demonstrated that the ITGB4 (c.C2503G; p.P835A) and MUC3A (c.C1019T; p.P340L) mutations may be the potential causative variants in a patient with UC associated with PSC and SSA. TP53 (c.86delA; p.N29Tfs∗15) mutation may be associated with SSA in this patient.

Morphological, phenological, and transcriptional analyses provide insight into the diverse flowering traits of a mutant of the relic woody plant Liriodendron chinense

Flowering is crucial to plant reproduction and controlled by multiple factors. However, the mechanisms underlying the regulation of flowering in perennial plants are still largely unknown. Here, we first report a super long blooming 1 (slb1) mutant of the relict tree Liriodendron chinense possessing a prolonged blooming period of more than 5 months, in contrast to the 1 month blooming period in the wild type (WT). Phenotypic characterization showed that earlier maturation of lateral shoots was caused by accelerated axillary bud fate, leading to the phenotype of continuous flowering in slb1 mutants. The transcriptional activity of genes related to hormone signaling (auxin, cytokinin, and strigolactone), nutrient availability, and oxidative stress relief further indicated active outgrowth of lateral buds in slb1 mutants. Interestingly, we discovered a unique FT splicing variant with intron retention specific to slb1 mutants, representing a potential causal mutation in the slb1 mutants. Surprisingly, most slb1 inbred offspring flowered precociously with shorter juvenility (~4 months) than that (usually 8–10 years) required in WT plants, indicating heritable variation underlying continuous flowering in slb1 mutants. This study reports an example of a perennial tree mutant that flowers continuously, providing a rare resource for both breeding and genetic research.

Identification of two pathogenic mutations in SORL1 in early-onset Alzheimer’s disease

The sortilin-related receptor 1 (SORL1) gene has been the subject of many studies focusing on frequent polymorphisms, which is associated with increased risk for Alzheimer’s Disease (AD). By whole-exome sequencing (WES), we identified two pathogenic missense mutations c.579C > G (p.F193L) and c.1397A > G (p.N466S) in SORL1. The two mutations were located in the same protein domain, and the two unrelated probands both had an onset of memory problems at less than 65 years of age, but their clinical manifestations and cranial imaging are different. The protein structure and function affected by these mutations were predicted using bioinformatics analysis, which suggested they were pathogenic. 3D protein structural analysis revealed that these amino acid substitutions might result in instability of protein structure and adverse intramolecular interactions. These findings suggest that both F193L and N466S should be thought as potential causative mutations in early-onset Alzheimer’s disease (EOAD) patients. Further functional studies are warranted to evaluate their roles in the pathogenesis of AD.

LHCGR and ALMS1 defects likely cooperate in the development of polycystic ovary syndrome indicated by double-mutant mice

Polycystic ovary syndrome (PCOS) is a heterogeneous disorder with evidence of polygenetic components, and obesity may be a risk factor for hyperandrogenism. Previous studies have shown that LHCGR is enriched in the ovary and LHCGR deficiency causes infertility without typical PCOS phenotypes. ALMS1 is implicated in obesity and hyperandrogenism, the common phenotypes among PCOS patients. Through whole-exome sequencing of 22 PCOS families and targeted candidate gene sequencing of additional 65 sporadic PCOS patients, we identified potential causative mutations in LHCGR and ALMS1 in a sibling-pair PCOS family and three sporadic PCOS patients. The expression of LHCGRL638P in granulosa-like tumor cell line (KGN) cells promoted cyclic adenosine monophosphate production and granulosa cell proliferation, indicating that LHCGRL638P is an activating mutation. LhcgrL642P/L642P mice showed an irregular estrous cycle, reduced follicles with dynamic folliculogenesis, and increased testosterone (T), estradiol (E2), and dehydroepiandrosterone. Lhcgr+/L642PAlms1+/PB mice displayed increased T and E2 but decreased late secondary and preovulatory follicles. We showed that activating mutation of LHCGR likely plays important roles in the pathophysiology of PCOS involving abnormal reproductive physiology, whereas ALMS1 deficiency may promote anovulatory infertility via elevated androgens, suggesting that the disturbed LHCGR and ALMS1 cooperatively induce PCOS phenotypes, characterized as anovulation and hyperandrogenemia frequently observed in PCOS patients with obesity.

Genome-wide association studies demonstrate that TASP1 contributes to increased muscle fiber diameter.

Muscle fiber diameter is an economically important trait because it affects meat yield and quality. However, the genetic basis underlying muscle fiber diameter has not been determined. In this study, we collected THREE muscular histological phenotypes in 479 ducks from an F2 segregating population generated by mallard × Pekin duck crosses. We performed genome-wide association studies (GWAS) and identified a quantitative trait locus (QTL) significantly associated with muscle fiber diameter on chromosome 3. Then, we discovered the selection signatures using the fixation index among 40 mallards and 30 Pekin ducks in this QTL region. Furthermore, we characterized the recombination event in this QTL region and identified a 6-kb block located on TASP1 that was significantly associated with muscle fiber diameter. Finally, five SNPs were screened as potential causative mutations within the 6-kb block. In conclusion, we demonstrated that TASP1 contributes to an increase in muscle fiber diameter, which helps to characterize muscle development and contributes to the genetic improvement of meat yield and quality in livestock.

Imputation accuracy to whole-genome sequence in Nellore cattle

BackgroundA cost-effective strategy to explore the complete DNA sequence in animals for genetic evaluation purposes is to sequence key ancestors of a population, followed by imputation mechanisms to infer marker genotypes that were not originally reported in a target population of animals genotyped with single nucleotide polymorphism (SNP) panels. The feasibility of this process relies on the accuracy of the genotype imputation in that population, particularly for potential causal mutations which may be at low frequency and either within genes or regulatory regions. The objective of the present study was to investigate the imputation accuracy to the sequence level in a Nellore beef cattle population, including that for variants in annotation classes which are more likely to be functional.MethodsInformation of 151 key sequenced Nellore sires were used to assess the imputation accuracy from bovine HD BeadChip SNP (~ 777 k) to whole-genome sequence. The choice of the sires aimed at optimizing the imputation accuracy of a genotypic database, comprised of about 10,000 genotyped Nellore animals. Genotype imputation was performed using two computational approaches: FImpute3 and Minimac4 (after using Eagle for phasing). The accuracy of the imputation was evaluated using a fivefold cross-validation scheme and measured by the squared correlation between observed and imputed genotypes, calculated by individual and by SNP. SNPs were classified into a range of annotations, and the accuracy of imputation within each annotation classification was also evaluated.ResultsHigh average imputation accuracies per animal were achieved using both FImpute3 (0.94) and Minimac4 (0.95). On average, common variants (minor allele frequency (MAF) > 0.03) were more accurately imputed by Minimac4 and low-frequency variants (MAF ≤ 0.03) were more accurately imputed by FImpute3. The inherent Minimac4 Rsq imputation quality statistic appears to be a good indicator of the empirical Minimac4 imputation accuracy. Both software provided high average SNP-wise imputation accuracy for all classes of biological annotations.ConclusionsOur results indicate that imputation to whole-genome sequence is feasible in Nellore beef cattle since high imputation accuracies per individual are expected. SNP-wise imputation accuracy is software-dependent, especially for rare variants. The accuracy of imputation appears to be relatively independent of annotation classification.

Assessing the contribution of tumor mutational phenotypes to cancer progression risk.

Cancer occurs via an accumulation of somatic genomic alterations in a process of clonal evolution. There has been intensive study of potential causal mutations driving cancer development and progression. However, much recent evidence suggests that tumor evolution is normally driven by a variety of mechanisms of somatic hypermutability, which act in different combinations or degrees in different cancers. These variations in mutability phenotypes are predictive of progression outcomes independent of the specific mutations they have produced to date. Here we explore the question of how and to what degree these differences in mutational phenotypes act in a cancer to predict its future progression. We develop a computational paradigm using evolutionary tree inference (tumor phylogeny) algorithms to derive features quantifying single-tumor mutational phenotypes, followed by a machine learning framework to identify key features predictive of progression. Analyses of breast invasive carcinoma and lung carcinoma demonstrate that a large fraction of the risk of future clinical outcomes of cancer progression—overall survival and disease-free survival—can be explained solely from mutational phenotype features derived from the phylogenetic analysis. We further show that mutational phenotypes have additional predictive power even after accounting for traditional clinical and driver gene-centric genomic predictors of progression. These results confirm the importance of mutational phenotypes in contributing to cancer progression risk and suggest strategies for enhancing the predictive power of conventional clinical data or driver-centric biomarkers.

A Systematic Review of Genomic Regions and Candidate Genes Underlying Behavioral Traits in Farmed Mammals and Their Link with Human Disorders.

Simple SummaryThis study is a comprehensive review of genomic regions associated with animal behavior in farmed mammals (beef and dairy cattle, pigs, and sheep) which contributes to a better understanding of the biological mechanisms influencing the target indicator trait and to gene expression studies by suggesting genes likely controlling the trait, and it will be useful in optimizing genomic predictions of breeding values incorporating biological information. Behavioral mechanisms are complex traits, genetically controlled by multiple genes spread across the whole genome. The majority of the genes identified in cattle, pigs, and sheep in association with a plethora of behavioral measurements (e.g., temperament, terrain use, milking speed, tail biting, and sucking reflex) are likely controlling stimuli reception (e.g., olfactory), internal recognition of stimuli (e.g., neuroactive ligand–receptor interaction), and body response to a stimulus (e.g., blood pressure, fatty acidy metabolism, hormone signaling, and inflammatory pathways). Six genes were commonly identified between cattle and pigs. About half of the genes for behavior identified in farmed mammals were also identified in humans for behavioral, mental, and neuronal disorders. Our findings indicate that the majority of the genes identified are likely controlling animal behavioral outcomes because their biological functions as well as potentially differing allele frequencies between two breed groups (subjectively) clustered based on their temperament characteristics.The main objectives of this study were to perform a systematic review of genomic regions associated with various behavioral traits in the main farmed mammals and identify key candidate genes and potential causal mutations by contrasting the frequency of polymorphisms in cattle breeds with divergent behavioral traits (based on a subjective clustering approach). A total of 687 (cattle), 1391 (pigs), and 148 (sheep) genomic regions associated with 37 (cattle), 55 (pigs), and 22 (sheep) behavioral traits were identified in the literature. In total, 383, 317, and 15 genes overlap with genomic regions identified for cattle, pigs, and sheep, respectively. Six common genes (e.g., NR3C2, PITPNM3, RERG, SPNS3, U6, and ZFAT) were found for cattle and pigs. A combined gene-set of 634 human genes was produced through identified homologous genes. A total of 313 out of 634 genes have previously been associated with behavioral, mental, and neurologic disorders (e.g., anxiety and schizophrenia) in humans. Additionally, a total of 491 candidate genes had at least one statistically significant polymorphism (p-value < 0.05). Out of those, 110 genes were defined as having polymorphic regions differing in greater than 50% of exon regions. Therefore, conserved genomic regions controlling behavior were found across farmed mammal species and humans.

A post-GWAS confirming the genetic effects and functional polymorphisms of AGPAT3 gene on milk fatty acids in dairy cattle

BackgroundPeople are paying more attention to the healthy and balanced diet with the improvement of their living standards. Milk fatty acids (FAs) have been reported that they were related to some atherosclerosis and coronary heart diseases in human. In our previous genome-wide association study (GWAS) on milk FAs in dairy cattle, 83 genome-wide significant single nucleotide polymorphisms (SNPs) were detected. Among them, two SNPs, ARS-BFGL-NGS-109493 and BTA-56389-no-rs associated with C18index (P = 0.0459), were located in the upstream of 1-acylglycerol-3-phosphate O-acyltransferase 3 (AGPAT3) gene. AGPAT3 is involved in glycerol-lipid, glycerol-phospholipid metabolism and phospholipase D signaling pathways. Hence, it was inferred as a candidate gene for milk FAs. The aim of this study was to further confirm the genetic effects of the AGPAT3 gene on milk FA traits in dairy cattle.ResultsThrough re-sequencing the complete coding region, and 3000 bp of 5′ and 3′ regulatory regions of the AGPAT3 gene, a total of 17 SNPs were identified, including four in 5′ regulatory region, one in 5′ untranslated region (UTR), three in introns, one in 3′ UTR, and eight in 3′ regulatory region. By the linkage disequilibrium (LD) analysis with Haploview4.1 software, two haplotype blocks were observed that were formed by four and 12 identified SNPs, respectively. Using SAS9.2, we performed single locus-based and haplotype-based association analysis on 24 milk FAs in 1065 Chinese Holstein cows, and discovered that all the SNPs and the haplotype blocks were significantly associated with C6:0, C8:0 and C10:0 (P < 0.0001–0.0384). Further, with Genomatix, we predicted that four SNPs in 5′ regulatory region (g.146702957G > A, g.146704373A > G, g.146704618A > G and g.146704699G > A) changed the transcription factor binding sites (TFBSs) for transcription factors SMARCA3, REX1, VMYB, BRACH, NKX26, ZBED4, SP1, USF1, ARNT and FOXA1. Out of them, two SNPs were validated to impact transcriptional activity by performing luciferase assay that the alleles A of both SNPs, g.146704373A > G and g.146704618A > G, increased the transcriptional activities of AGPAT3 promoter compared with alleles G (P = 0.0004).ConclusionsIn conclusion, our findings first demonstrated the significant genetic associations of the AGPAT3 gene with milk FAs in dairy cattle, and two potential causal mutations were detected.

Application of SNPViz v2.0 using next-generation sequencing data sets in the discovery of potential causative mutations in candidate genes associated with phenotypes

Application of SNPViz v2.0 using next-generation sequencing data sets in the discovery of potential causative mutations in candidate genes associated with phenotypes

Analysis of Whole Genome Resequencing Datasets from a Worldwide Sample of Sheep Breeds to Identify Potential Causal Mutations Influencing Milk Composition Traits

Simple SummaryMost of the production of sheep’s milk is used in the manufacture of mature cheeses. The milk composition has a strong influence on the technological and organoleptic properties of dairy products. Several genetic polymorphisms have been related to variations of milk protein and milk fatty acid content. The use of whole genome resequencing (WGR) has encouraged the discovery of polymorphisms in the sheep genome. Exploiting information derived from a large number of sheep WGR datasets, this study aimed to evaluate the variability of 24 candidate genes involved in physiological pathways related to milk production. The genetic variants highlighted by this work have a potential influence on the function of the protein encoded by the candidate genes. The relevance of sheep milk composition on the cheese-making industry enhances the potential interest of the present study as the variants highlighted herein could be considered to increase the efficiency of breeding programs currently applied to dairy sheep populations. Further studies would be needed to understand the role of these genetic variants on milk production traits.Different studies have shown that polymorphisms in the sequence of genes coding for the milk proteins and milk fatty acids are associated with milk composition traits as well as with cheese-making traits. However, the lack of coincident results across sheep populations has prevented the use of this information in sheep breeding programs. The main objective of this study was to exploit the information derived from a total of 175 whole genome resequencing (WGR) datasets from 43 domestic sheep breeds and three wild sheep to evaluate the genetic diversity of 24 candidate genes for milk composition and identify genetic variants with a potential phenotypic effect. The functional annotation of the identified variants highlighted five single nucleotide polymorphisms (SNPs) predicted to have a high impact on the protein function and 42 missense SNPs with a putative deleterious effect. When comparing the allelic frequencies at these 47 polymorphisms with relevant functional effects between the genomes of Assaf and Churra sheep breeds, two missense deleterious variants were identified as potential markers associated to the milk composition differences found between the Churra and Assaf: XDH:92215727C>T and LALBA:137390760T>C. Future research is required to confirm the effect of the potential functionally relevant variants identified in the present study on milk composition and cheese-making traits.

Identification of rare and common variants in BNIP3L: a schizophrenia susceptibility gene

BackgroundSchizophrenia is a chronic and severe mental disorder, and it has been predicted to be highly polygenic. Common SNPs located in or near BNIP3L were found to be genome-wide significantly associated with schizophrenia in recent genome-wide association studies. The purpose of our study is to investigate potential causal variants in BNIP3L gene.ResultsWe performed targeted sequencing for all exons and un-translated regions of BNIP3L gene among 1806 patients with schizophrenia and 998 healthy controls of Han Chinese origin. Three rare nonsynonymous mutations, BNIP3L (NM_004331): c.52A>G, c.167G>A and c.313A>T, were identified in schizophrenia cases, and two of them were newly reported. The frequencies of these rare nonsynonymous mutations were significantly different between schizophrenia cases and healthy controls. For the common variants, rs147389989 achieved significance in both allelic and genotypic distributions with schizophrenia. Rs1042992 and rs17310286 were significantly associated with schizophrenia in meta-analyses using PGC, CLOZUK, and our new datasets in this study.ConclusionsOur findings provided further evidence that BNIP3L gene is a susceptibility gene of schizophrenia and revealed functional and potential causal mutations in BNIP3L. However, more functional validations are suggested to better understand the role of BNIP3L in the etiology of schizophrenia.

Identification of genetic effects and potential causal polymorphisms of CPM gene impacting milk fatty acid traits in Chinese Holstein.

Our previous GWAS revealed 83 significant SNPs and 20 promising candidate genes associated with milk fatty acid traits in dairy cattle. Out of them, the carboxypeptidase M (CPM) gene contains a genome-wide significant SNP, Hapmap49848-BTA-106779, which is strongly associated with myristic acid (C14:0; P=0.0064). Herein, we aimed to confirm the genetic effects of CPM on milk fatty acids in Chinese Holstein. Seven SNPs were detected by re-sequencing the sequences of entire exons and 3000bp of up-/downstream flanking regions of the CPM gene, of which three were in 5' flanking region, one in the 3' UTR and three were in the 3' flanking region. Using the Haploview 4.1, we estimated the LD among the identified SNPs and found two haplotype blocks. With the animal model, we performed the SNP- and haplotype-based association analyses, and observed that these SNPs and haplotype blocks mainly had strong genetic associations with medium-chain saturated fatty acids (caproic acid, C6:0; caprylic acid, C8:0; capric acid, C10:0; and lauric acid, C12:0) (P<0.0001-0.0257). In addition, using the Genomatix software, we predicted that three SNPs in the 5' flanking region of CPM (g.45079507A>G, g.45080228C>A and g.45080335C>G) changed the transcription factor binding sites for PREF (progesterone receptor biding site), ZBRK1 (transcription factor with eight central zinc fingers and an N-terminal KRAB domain), SOX9 (sex-determining region Y-box 9, dimeric binding sites), SOX6 (sex-determining region Y-box 6) and FOXP1-ES (alternative splicing variant of FOXP1, activated in ESCs). Further, the dual-luciferase reporter assay showed these three SNPs altered the transcriptional activity of CPM gene (P≤0.0006). In summary, using the post-GWAS strategy, we first confirmed the significant genetic effects of CPM with milk fatty acids in dairy cattle, and identified three potential causal mutations.

Two-stage genome-wide association study for the identification of causal variants underlying hoof disorders in cattle

Feet and legs disorders influence dairy cattle breeding by their effect on animal welfare, economic losses due to lower production and fertility, costs of treatment, and problems with herd management. In our study, we estimated heritabilities and performed a 2-step GWAS for 3 traits describing hoof health: hoof health status defined by a veterinarian (HSV), hoof health status defined by a claw trimmer (HSC), and the total number of hoof disorders (NHD), scored in 1,998 Fleckvieh and 979 Braunvieh cows. The individuals were genotyped with a high-density (HD) panel consisting of 76,934 SNP. For significant genomic regions, the SNP information was enhanced by SNP imputed from the whole-genome sequence of Fleckvieh and Braunvieh bulls from the 1000 Bulls Genome project. The heritabilities were estimated to be 0.035 for HSV, 0.249 for HSC, and 0.279 for NHD. Based on the first-stage GWAS with SNP from the HD panel, 7 significant genomic regions on 6 chromosomes were defined: (1) 120 SNP spanning 15,522 bp on BTA1, including the TOPBP1 gene; (2) 4,139 SNP spanning 1,426,046 bp on BTA7, including the RIOK2 and RGMB genes; (3) 167 SNP spanning 167,352 bp on BTA13, including the C13H20orf194 gene; (4) 2 regions on BTA14, one harboring 1,071 SNP spanning 380,024 bp, including RRM2B and NCALD, and the other comprising 632 SNP spanning 385,111 bp, including STK3; (5) 328 SNP on BTA15, spanning 235,567 bp between FAM168A and PLEKHB1; and (6) 1,549 SNP on BTA22, spanning 596,101 bp in the neighborhood of PTPRG. Then, we conducted a second-stage GWAS based on SNP from whole-genome sequences within the significant regions obtained in the first stage of the analysis. For HSV, the highest additive effect was estimated for 23 SNP located within a region on BTA15, close to FAM168A, corresponding to a predicted gene sequence. For HSC, the highest additive effect was attributed to 44 SNP located within a region of BTA22 corresponding to 4 predicted gene sequences, with rs135082893 within a sequence encoding a microRNA. Another potential causal mutation for HSC was rs134142607 on BTA13, within the exon of C13H20orf194. For NHD, 33 SNP with the highest estimated effect were located on BTA7 within a region of a predicted gene positioned between RIOK2 and RGMB. On BTA14, all significant SNP were located in introns of STK3, which is responsible for the "abnormal gait" phenotype in mice.

Familial autosomal recessive bestrophinopathy: identification of a novel variant in BEST1 gene and the specific metabolomic profile

BackgroundAutosomal recessive bestrophinopathy (ARB) is a retinal degenerative disorder caused by BEST1 mutations with autosomal recessive inheritance. We aim to map a comprehensive genomic and metabolomic profile of a consanguineous Chinese family with ARB.MethodsOphthalmic examinations were performed on the affected patients with ARB. The proband was screened for potential causative mutations in a panel with 256 known retinal disease genes by using target capture sequencing. The related mutation was further validated and segregated in the family members by Sanger sequencing. In silico prediction tools were used for pathogenicity assessment. A UHPLC-MS/MS metabolomic analysis was performed to explore the disease-associated metabolic feature.ResultsThe affected patients from this family were characterized by low vision, the presence of subretinal fluid, macular edema, and hyperopia with coincidental angle closure. DNA sequencing identified a novel missense mutation in the BEST1 gene c.646G > A (p.Val216Ile) of the proband. Sanger sequencing further confirmed the mutation. The missense mutation was co-segregation across the pedigree and predicted to be deleterious by SIFT (0.017). The blood metabolic profiles were highly similar among all family members probably because of the same lifestyle, habitat and genomic background. However, ARB patients presented a significant deregulation of metabolites, such as citric acid, L-Threonic acid, and eicosapentaenoic acid.ConclusionsWe identified a novel disease-associated variant in the BEST1 gene as well as a disease-specific metabolic feature in familial ARB. Our findings helped improve the understanding of ARB mechanisms.

Genomic Sequencing To Identify Potential Causative Mutation(s) of Neurospora crassa col-4.

In many cases, genes for commonly used genetic markers in model organisms have not been identified; therefore, it is of interest to identify the causative genes. Whole-genome sequencing was used to identify potential causative mutations for a col-4 allele of Neurospora crassa.