Selected publications
Novel metrics to measure coverage in whole exome sequencing datasets reveal local and global non-uniformity.
Wang Q, Shashikant CS, Jensen M, Altman NS, Girirajan S.

Whole Exome Sequencing (WES) is a powerful clinical diagnostic tool for discovering the genetic basis of many diseases. A major shortcoming of WES is uneven coverage of sequence reads over the exome targets contributing to many low coverage regions, which hinders accurate variant calling. In this study, we devised two novel metrics, Cohort Coverage Sparseness (CCS) and Unevenness (UE) Scores for a detailed assessment of the distribution of coverage of sequence reads. Employing these metrics we revealed non-uniformity of coverage and low coverage regions in the WES data generated by three different platforms. This non-uniformity of coverage is both local (coverage of a given exon across different platforms) and global (coverage of all exons across the genome in the given platform). The low coverage regions encompassing functionally important genes were often associated with high GC content, repeat elements and segmental duplications. While a majority of the problems associated with WES are due to the limitations of the capture methods, further refinements in WES technologies have the potential to enhance its clinical applications.
Quantitative Assessment of Eye Phenotypes for Functional Genetic Studies Using Drosophila melanogaster.
Iyer J, Wang Q, Le T, Pizzo L, Gronke S, Ambegaokar S, Imai Y, Srivastava A, Llamusi Troisi B, Mardon G, Artero R, Jackson GR, Isaacs AM, Partridge L, Kumar JP, Girirajan S.

About two-thirds of the vital genes in the Drosophila genome are involved in eye development, making the fly eye an excellent genetic system to study cellular function and development, neurodevelopment/degeneration, and complex diseases such as cancer and diabetes. We developed a novel computational method, implemented as Flynotyper software (, to quantitatively assess the morphological defects in the Drosophila eye resulting from genetic alterations affecting basic cellular and developmental processes. Flynotyper utilizes a series of image processing operations to automatically detect the fly eye and the individual ommatidium, and calculates a phenotypic score as a measure of the disorderliness of ommatidial arrangement in the fly eye. As a proof of principle, we tested our method by analyzing the defects due to eye-specific knockdown of Drosophila orthologs of 12 neurodevelopmental genes to accurately document differential sensitivities of these genes to dosage alteration. We also evaluated eye images from six independent studies assessing the effect of overexpression of repeats, candidates from peptide library screens, and modifiers of neurotoxicity and developmental processes on eye morphology, and show strong concordance with the original assessment. We further demonstrate the utility of this method by analyzing 16 modifiers of sine oculis obtained from two genome-wide deficiency screens of Drosophila and accurately quantifying the effect of its enhancers and suppressors during eye development. Our method will complement existing assays for eye phenotypes and increase the accuracy of studies that use fly eyes for functional evaluation of genes and genetic interactions.
An assessment of sex bias in neurodevelopmental disorders.
Polyak A, Rosenfeld JA, Girirajan S.

Neurodevelopmental disorders such as autism and intellectual disability have a sex bias skewed towards boys; however, systematic assessment of this bias is complicated by the presence of significant genetic and phenotypic heterogeneity of these disorders.To assess the extent and characteristics of sex bias, we analyzed the frequency of comorbid features, the magnitude of genetic load, and the existence of family history within 32,155 individuals ascertained clinically for autism or intellectual disability/developmental delay (ID/DD), including a subset of 8,373 individuals carrying rare copy-number variants (CNVs). We find that girls were more likely than boys to show comorbid features within both autism and ID/DD cohorts. The frequency of comorbid features in ID/DD was higher in boys (1q21.1 deletion, 15q11.2q13.1 duplication) or girls (15q13.3 deletion, 16p11.2 deletion) carrying specific CNVs associated with variable expressivity while such differences were the smallest for syndromic CNVs (Smith-Magenis syndrome, DiGeorge syndrome). The extent of the male sex bias also varied according to the specific comorbid feature, being most extreme for autism with psychiatric comorbidities and least extreme for autism comorbid with epilepsy. The sex ratio was also specific to certain CNVs, from an 8:1 male:female ratio observed among autistic individuals carrying the 22q11.2 duplication to 1.3:1 male:female ratio in those carrying the 16p11.2 deletion. Girls carried a higher burden of large CNVs compared to boys for autism or ID/DD, and this difference diminished when severe comorbidities were considered. Affected boys showed a higher frequency of neuropsychiatric family histories such as autism or specific learning disability, while affected girls showed a higher frequency of developmental family histories such as growth abnormalities. The sex bias within neurodevelopmental disorders is influenced by the presence of specific comorbidities, specific CNVs, mutational burden, and pre-existing family history of neurodevelopmental phenotypes.
Comorbidity of intellectual disability confounds ascertainment of autism: implications for genetic diagnosis.
Polyak A, Kubina RM, Girirajan S.

While recent studies suggest a converging role for genetic factors towards risk for nosologically distinct disorders including autism, intellectual disability (ID), and epilepsy, current estimates of autism prevalence fail to take into account the impact of comorbidity of these disorders on autism diagnosis. We aimed to assess the effect of comorbidity on the diagnosis and prevalence of autism by analyzing 11 years (2000-2010) of special education enrollment data on approximately 6.2 million children per year. We found a 331% increase in the prevalence of autism from 2000 to 2010 within special education, potentially due to a diagnostic recategorization from frequently comorbid features such as ID. The decrease in ID prevalence equaled an average of 64.2% of the increase of autism prevalence for children aged 3-18 years. The proportion of ID cases potentially undergoing recategorization to autism was higher among older children (75%) than younger children (48%). Some US states showed significant negative correlations between the prevalence of autism compared to that of ID while others did not, suggesting state-specific health policy to be a major factor in categorizing autism. Further, a high frequency of autistic features was observed when individuals with classically defined genetic syndromes were evaluated for autism using standardized instruments. Our results suggest that current ascertainment practices are based on a single facet of autism-specific clinical features and do not consider associated comorbidities that may confound diagnosis. Longitudinal studies with detailed phenotyping and deep molecular genetic analyses are necessary to completely understand the cause of this complex disorder.
All publications