Accumulating mutations in series of haplotypes at the KIT and MITF loci are major determinants of white markings in Franches-Montagnes horses.

Coat color and pattern variations in domestic animals are frequently inherited as simple monogenic traits, but a number are known to have a complex genetic basis. While the analysis of complex trait data remains a challenge in all species, we can use the reduced haplotypic diversity in domestic animal populations to gain insight into the genomic interactions underlying complex phenotypes. White face and leg markings are examples of complex traits in horses where little is known of the underlying genetics. In this study, Franches-Montagnes (FM) horses were scored for the occurrence of white facial and leg markings using a standardized scoring system. A genome-wide association study (GWAS) was performed for several white patterning traits in 1,077 FM horses. Seven quantitative trait loci (QTL) affecting the white marking score with p-values p≤10(-4) were identified. Three loci, MC1R and the known white spotting genes, KIT and MITF, were identified as the major loci underlying the extent of white patterning in this breed. Together, the seven loci explain 54% of the genetic variance in total white marking score, while MITF and KIT alone account for 26%. Although MITF and KIT are the major loci controlling white patterning, their influence varies according to the basic coat color of the horse and the specific body location of the white patterning. Fine mapping across the MITF and KIT loci was used to characterize haplotypes present. Phylogenetic relationships among haplotypes were calculated to assess their selective and evolutionary influences on the extent of white patterning. This novel approach shows that KIT and MITF act in an additive manner and that accumulating mutations at these loci progressively increase the extent of white markings

Mutations in STAG2 cause an X-linked cohesinopathy associated with undergrowth, developmental delay, and dysmorphia: Expanding the phenotype in males.

BACKGROUND: The cohesin complex is a multi-subunit protein complex which regulates sister chromatid cohesion and separation during cellular division. In addition, this evolutionarily conserved protein complex plays an integral role in DNA replication, DNA repair, and the regulation of transcription. The core complex is composed of four subunits: RAD21, SMC1A, SMC3, and STAG1/2. Mutations in these proteins have been implicated in human developmental disorders collectively termed cohesinopathies. METHODS: Using clinical exome sequencing, we have previously identified three female cases with heterozygous STAG2 mutations and overlapping syndromic phenotypes. Subsequently, a familial missense variant was identified in five male family members. RESULTS: We now present the case of a 4-year-old male with developmental delay, failure to thrive, short stature, and polydactyly with a likely pathogenic STAG2 de novo missense hemizygous variant, c.3027A>T, p.Lys1009Asn. Furthermore, we compare the phenotypes of the four previously reported STAG2 variants with our case. CONCLUSION: We conclude that mutations in STAG2 cause a novel constellation of sex-specific cohesinopathy-related phenotypes and are furthermore, essential for neurodevelopment, human growth, and behavioral development

Non-cancer-related pathogenic germline variants and expression consequences in ten-thousand cancer genomes

Background DNA sequencing is increasingly incorporated into the routine care of cancer patients, many of whom also carry inherited, moderate/high-penetrance variants associated with other diseases. Yet, the prevalence and consequence of such variants remain unclear. Methods We analyzed the germline genomes of 10,389 adult cancer cases in the TCGA cohort, identifying pathogenic/likely pathogenic variants in autosomal-dominant genes, autosomal-recessive genes, and 59 medically actionable genes curated by the American College of Molecular Genetics (i.e., the ACMG 59 genes). We also analyzed variant- and gene-level expression consequences in carriers. Results The affected genes exhibited varying pan-ancestry and population-specific patterns, and overall, the European population showed the highest frequency of pathogenic/likely pathogenic variants. We further identified genes showing expression consequence supporting variant functionality, including altered gene expression, allelic specific expression, and mis-splicing determined by a massively parallel splicing assay. Conclusions Our results demonstrate that expression-altering variants are found in a substantial fraction of cases and illustrate the yield of genomic risk assessments for a wide range of diseases across diverse populations

Non-cancer-related pathogenic germline variants and expression consequences in ten-thousand cancer genomes.

BackgroundDNA sequencing is increasingly incorporated into the routine care of cancer patients, many of whom also carry inherited, moderate/high-penetrance variants associated with other diseases. Yet, the prevalence and consequence of such variants remain unclear.MethodsWe analyzed the germline genomes of 10,389 adult cancer cases in the TCGA cohort, identifying pathogenic/likely pathogenic variants in autosomal-dominant genes, autosomal-recessive genes, and 59 medically actionable genes curated by the American College of Molecular Genetics (i.e., the ACMG 59 genes). We also analyzed variant- and gene-level expression consequences in carriers.ResultsThe affected genes exhibited varying pan-ancestry and population-specific patterns, and overall, the European population showed the highest frequency of pathogenic/likely pathogenic variants. We further identified genes showing expression consequence supporting variant functionality, including altered gene expression, allelic specific expression, and mis-splicing determined by a massively parallel splicing assay.ConclusionsOur results demonstrate that expression-altering variants are found in a substantial fraction of cases and illustrate the yield of genomic risk assessments for a wide range of diseases across diverse populations

Results of the logistic regression model analysis.

<p>Results of the logistic regression model analysis for the relationship between <i>MITF</i> haplotypes, SNPs across the 2 Mb <i>KIT</i> region <i>and KIT</i> haplotypes.</p

Missed diagnoses: Clinically relevant lessons learned through medical mysteries solved by the Undiagnosed Diseases Network

Abstract Background Resources within the Undiagnosed Diseases Network (UDN), such as genome sequencing (GS) and model organisms aid in diagnosis and identification of new disease genes, but are currently difficult to access by clinical providers. While these resources do contribute to diagnoses in many cases, they are not always necessary to reach diagnostic resolution. The UDN experience has been that participants can also receive diagnoses through the thoughtful and customized application of approaches and resources that are readily available in clinical settings. Methods The UDN Genetic Counseling and Testing Working Group collected case vignettes that illustrated how clinically available methods resulted in diagnoses. The case vignettes were classified into three themes; phenotypic considerations, selection of genetic testing, and evaluating exome/GS variants and data. Results We present 12 participants that illustrate how clinical practices such as phenotype‐driven genomic investigations, consideration of variable expressivity, selecting the relevant tissue of interest for testing, utilizing updated testing platforms, and recognition of alternate transcript nomenclature resulted in diagnoses. Conclusion These examples demonstrate that when a diagnosis is elusive, an iterative patient‐specific approach utilizing assessment options available to clinical providers may solve a portion of cases. However, this does require increased provider time commitment, a particular challenge in the current practice of genomics

Phenotypic variation in the expression of white markings.

<p>Example of phenotypes. Horse (A) has a total score of white markings of 1 (head = 0; foreleg = 0; hind leg = 1); horse (B) has a total score of white markings of 19 (head = 9; foreleg = 2; hind leg = 8).</p

Average total white markings score for <i>MITF-KIT</i> haplotype combinations.

<p>Average total white markings score and standard deviation for <i>MITF-KIT</i> haplotype combinations. Adjacent squares represent haplotypes (red = <i>MITF</i>; blue = <i>KIT</i>); color shades represent haplotypes of the phylogenetic relationship trees (<i>MITF</i>: M1–M6; <i>KIT</i>: K1–K7).</p

Phylogenetic relationship between haplotypes at <i>MITF</i> and <i>KIT</i>.

<p>Phylogenetic relationships between haplotypes at <i>MITF</i> (M1–M6) and <i>KIT</i> (K1–K7). Haplotype combinations (hap1 = haplotype 1, hap2 = haplotype 2) and individuals average total white markings score (aTSC = average Total Score) are shown on the right.</p

Expansion of NEUROD2

De novo heterozygous variants in the brain-specific transcription factor Neuronal Differentiation Factor 2 (NEUROD2) have been recently associated with early-onset epileptic encephalopathy and developmental delay. Here, we report an adolescent with developmental delay without seizures who was found to have a novel de novo heterozygous NEUROD2 missense variant, p.(Leu163Pro). Functional testing using an in vivo assay of neuronal differentiation in Xenopus laevis tadpoles demonstrated that the patient variant of NEUROD2 displays minimal protein activity, strongly suggesting a loss of function effect. In contrast, a second rare NEUROD2 variant, p.(Ala235Thr), identified in an adolescent with developmental delay but lacking parental studies for inheritance, showed normal in vivo NEUROD2 activity. We thus provide clinical, genetic, and functional evidence that NEUROD2 variants can lead to developmental delay without accompanying early-onset seizures, and demonstrate how functional testing can complement genetic data when determining variant pathogenicity