Development of the pupillary light reflex from 9 to 24 months: association with common autism spectrum disorder (ASD) genetic liability and 3-year ASD diagnosis.

BACKGROUND: Although autism spectrum disorder (ASD) is heritable, the mechanisms through which genes contribute to symptom emergence remain unclear. Investigating candidate intermediate phenotypes such as the pupillary light reflex (PLR) prospectively from early in development could bridge genotype and behavioural phenotype. METHODS: Using eye tracking, we longitudinally measured the PLR at 9, 14 and 24 months in a sample of infants (N = 264) enriched for a family history of ASD; 27 infants received an ASD diagnosis at 3 years. We examined the 9- to 24-month developmental trajectories of PLR constriction latency (onset; ms) and amplitude (%) and explored their relation to categorical 3-year ASD outcome, polygenic liability for ASD and dimensional 3-year social affect (SA) and repetitive/restrictive behaviour (RRB) traits. Polygenic scores for ASD (PGSASD ) were calculated for 190 infants. RESULTS: While infants showed a decrease in latency between 9 and 14 months, higher PGSASD was associated with a smaller decrease in latency in the first year (ß = -.16, 95% CI = -0.31, -0.002); infants with later ASD showed a significantly steeper decrease in latency (a putative 'catch-up') between 14 and 24 months relative to those with other outcomes (typical: ß = .54, 95% CI = 0.08, 0.99; other: ß = .53, 95% CI = 0.02, 1.04). Latency development did not associate with later dimensional variation in ASD-related traits. In contrast, change in amplitude was not related to categorical ASD or genetics, but decreasing 9- to 14-month amplitude was associated with higher SA (ß = .08, 95% CI = 0.01, 0.14) and RRB (ß = .05, 95% CI = 0.004, 0.11) traits. CONCLUSIONS: These findings corroborate PLR development as possible intermediate phenotypes being linked to both genetic liability and phenotypic outcomes. Future work should incorporate alternative measures (e.g. functionally informed structural and genetic measures) to test whether distinct neural mechanisms underpin PLR alterations.

Internalising and externalising in early adolescence predict later executive function, not the other way around: a cross-lagged panel analysis.

Developmental changes in the brain networks involved in emotion regulation are thought to contribute to vulnerability to mental health problems during adolescence. Executive control is often viewed as allowing top-down regulation of emotional responses. However, while associations between executive control and mental health are commonly observed in both clinical and non-clinical populations, the direction of these associations remains unclear. Low, or immature, cognitive control could limit emotion regulation. Reversely, high emotionality could impede cognitive functioning. The scarcity of longitudinal studies testing for bi-directional effects, particularly in adolescence, has made it difficult to draw conclusions. This study analysed data from 1,445 participants of a longitudinal cohort in a cross-lagged panel design to understand bi-directional longitudinal associations between executive function and emotional behaviours across adolescence. Executive function was assessed using experimental working memory and inhibitory control tasks, emotional behaviours through parental report of internalising and externalising behaviours. Cross-sectional associations were replicated. Controlling for cross-sectional associations, early executive functions were not found to predict later emotional behaviours. Instead, early emotional behaviours predicted later executive function, with the strongest link observed between early externalising and later working memory. These results suggest that emotional well-being may affect the maturation of executive function during adolescence.

Look duration at the face as a developmental endophenotype: elucidating pathways to autism and ADHD.

Identifying developmental endophenotypes on the pathway between genetics and behavior is critical to uncovering the mechanisms underlying neurodevelopmental conditions. In this proof-of-principle study, we explored whether early disruptions in visual attention are a unique or shared candidate endophenotype of autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD). We calculated the duration of the longest look (i.e., peak look) to faces in an array-based eye-tracking task for 335 14-month-old infants with and without first-degree relatives with ASD and/or ADHD. We leveraged parent-report and genotype data available for a proportion of these infants to evaluate the relation of looking behavior to familial (n = 285) and genetic liability (using polygenic scores, n = 185) as well as ASD and ADHD-relevant temperament traits at 2 years of age (shyness and inhibitory control, respectively, n = 272) and ASD and ADHD clinical traits at 6 years of age (n = 94).Results showed that longer peak looks at the face were associated with elevated polygenic scores for ADHD (ß = 0.078, p = .023), but not ASD (ß = 0.002, p = .944), and with elevated ADHD traits in mid-childhood (F(1,88) = 6.401, p = .013, $\eta _p^2$=0.068; ASD: F (1,88) = 3.218, p = .076), but not in toddlerhood (ps > 0.2). This pattern of results did not emerge when considering mean peak look duration across face and nonface stimuli. Thus, alterations in attention to faces during spontaneous visual exploration may be more consistent with a developmental endophenotype of ADHD than ASD. Our work shows that dissecting paths to neurodevelopmental conditions requires longitudinal data incorporating polygenic contribution, early neurocognitive function, and clinical phenotypic variation.

Estimation of a significance threshold for epigenome-wide association studies.

Epigenome-wide association studies (EWAS) are designed to characterise population-level epigenetic differences across the genome and link them to disease. Most commonly, they assess DNA-methylation status at cytosine-guanine dinucleotide (CpG) sites, using platforms such as the Illumina 450k array that profile a subset of CpGs genome wide. An important challenge in the context of EWAS is determining a significance threshold for declaring a CpG site as differentially methylated, taking multiple testing into account. We used a permutation method to estimate a significance threshold specifically for the 450k array and a simulation extrapolation approach to estimate a genome-wide threshold. These methods were applied to five different EWAS datasets derived from a variety of populations and tissue types. We obtained an estimate of α=2.4×10-7 for the 450k array, and a genome-wide estimate of α=3.6×10-8. We further demonstrate the importance of these results by showing that previously recommended sample sizes for EWAS should be adjusted upwards, requiring samples between ∼10% and ∼20% larger in order to maintain type-1 errors at the desired level.

Heritability and genome-wide analyses of problematic peer relationships during childhood and adolescence.

Peer behaviour plays an important role in the development of social adjustment, though little is known about its genetic architecture. We conducted a twin study combined with a genome-wide complex trait analysis (GCTA) and a genome-wide screen to characterise genetic influences on problematic peer behaviour during childhood and adolescence. This included a series of longitudinal measures (parent-reported Strengths-and-Difficulties Questionnaire) from a UK population-based birth-cohort (ALSPAC, 4-17 years), and a UK twin sample (TEDS, 4-11 years). Longitudinal twin analysis (TEDS; N ≤ 7,366 twin pairs) showed that peer problems in childhood are heritable (4-11 years, 0.60 < twin-h(2) ≤ 0.71) but genetically heterogeneous from age to age (4-11 years, twin-r(g) = 0.30). GCTA (ALSPAC: N ≤ 5,608, TEDS: N ≤ 2,691) provided furthermore little support for the contribution of measured common genetic variants during childhood (4-12 years, 0.02 < GCTA-h(2)(Meta) ≤ 0.11) though these influences become stronger in adolescence (13-17 years, 0.14 < GCTA-h (2)(ALSPAC) ≤ 0.27). A subsequent cross-sectional genome-wide screen in ALSPAC (N ≤ 6,000) focussed on peer problems with the highest GCTA-heritability (10, 13 and 17 years, 0.0002 < GCTA-P ≤ 0.03). Single variant signals (P ≤ 10(-5)) were followed up in TEDS (N ≤ 2835, 9 and 11 years) and, in search for autism quantitative trait loci, explored within two autism samples (AGRE: N Pedigrees = 793; ACC: N Cases = 1,453/N Controls = 7,070). There was, however, no evidence for association in TEDS and little evidence for an overlap with the autistic continuum. In summary, our findings suggest that problematic peer relationships are heritable but genetically complex and heterogeneous from age to age, with an increase in common measurable genetic variation during adolescence.

Next generation sequencing in epigenetics: insights and challenges.

The epigenetics community was an early adopter of next generation sequencing (NGS). NGS-based studies have provided detailed and comprehensive views of epigenetic modifications for the genomes of many species and cell types. Recently, DNA methylation has attracted much attention due to the discovery of 5-hydroxymethyl-cytosine and its role in epigenetic reprogramming and pluripotency. This renewed interest has been concomitant with methodological progress enabling, for example, high coverage and single base resolution profiling of the mammalian methylome in small numbers of cells. We summarise this progress and highlight resulting key findings about the complexity of eukaryotic DNA methylation, its role in metazoan genome evolution, epigenetic reprogramming, and its close ties with histone modifications in the context of transcription. Finally, we discuss how fundamental insights gained by NGS, particularly the discovery of widespread allele-specific epigenetic variation in the human genome, have the potential to significantly contribute to the understanding of human common complex diseases.

Phenotypic and Genetic Associations Between Preschool Fine Motor Skills and Later Neurodevelopment, Psychopathology, and Educational Achievement.

BACKGROUND: Fine motor skills are heritable and comprise important milestones in development, and some evidence suggests that impairments in fine motor skills are associated with neurodevelopmental conditions, psychiatric disorders, and poor educational outcomes. METHODS: In a preregistered study of 9625 preschool children from TEDS (Twins Early Development Study), fine motor assessments (drawing, block building, folding, and questionnaires) were conducted at 2, 3, and 4 years of age. A cross-age fine motor score was derived using principal component analysis. Multivariate regression analysis was used to examine the relationships between the fine motor score and neurodevelopmental traits, psychopathology, and educational outcomes at 3 later ages (7-8, 12, and 16 years) and cross-age psychopathology composite scores. Polygenic scores (PGSs) were created for attention-deficit/hyperactivity disorder (ADHD), autism, schizophrenia, anxiety, major depressive disorder, obsessive-compulsive disorder, and years of education. We ran single-PGS models and a multi-PGS model. RESULTS: Fine motor skills were negatively associated with neurodevelopmental traits and psychopathology across childhood and adolescence and positively associated with educational achievement in adolescence (ß = 0.25, p < .001). Superior fine motor skills were associated with a higher years-of-education PGS (ß = 0.07, p < .001), a lower ADHD PGS (ß = -0.04, p = .011), and a higher anxiety PGS (ß = 0.03, p = .040). Similarly, the multi-PGS model retained the PGSs for years of education (ß = 0.07), ADHD (ß = -0.03), and anxiety (ß = 0.01). A non-preregistered analysis in an independent preschool sample replicated the ADHD PGS association, but not the years of education or anxiety PGS associations. CONCLUSIONS: Fine motor skills are linked genetically and phenotypically to later neurodevelopment, psychopathology, and educational outcomes. Future work should investigate the mechanisms that underlie the role of fine motor development in later outcomes.

Allelic skewing of DNA methylation is widespread across the genome.

DNA methylation is assumed to be complementary on both alleles across the genome, although there are exceptions, notably in regions subject to genomic imprinting. We present a genome-wide survey of the degree of allelic skewing of DNA methylation with the aim of identifying previously unreported differentially methylated regions (DMRs) associated primarily with genomic imprinting or DNA sequence variation acting in cis. We used SNP microarrays to quantitatively assess allele-specific DNA methylation (ASM) in amplicons covering 7.6% of the human genome following cleavage with a cocktail of methylation-sensitive restriction enzymes (MSREs). Selected findings were verified using bisulfite-mapping and gene-expression analyses, subsequently tested in a second tissue from the same individuals, and replicated in DNA obtained from 30 parent-child trios. Our approach detected clear examples of ASM in the vicinity of known imprinted loci, highlighting the validity of the method. In total, 2,704 (1.5%) of our 183,605 informative and stringently filtered SNPs demonstrate an average relative allele score (RAS) change > or =0.10 following MSRE digestion. In agreement with previous reports, the majority of ASM ( approximately 90%) appears to be cis in nature, and several examples of tissue-specific ASM were identified. Our data show that ASM is a widespread phenomenon, with >35,000 such sites potentially occurring across the genome, and that a spectrum of ASM is likely, with heterogeneity between individuals and across tissues. These findings impact our understanding about the origin of individual phenotypic differences and have implications for genetic studies of complex disease.

Common DNA markers can account for more than half of the genetic influence on cognitive abilities.

For nearly a century, twin and adoption studies have yielded substantial estimates of heritability for cognitive abilities, although it has proved difficult for genomewide-association studies to identify the genetic variants that account for this heritability (i.e., the missing-heritability problem). However, a new approach, genomewide complex-trait analysis (GCTA), forgoes the identification of individual variants to estimate the total heritability captured by common DNA markers on genotyping arrays. In the same sample of 3,154 pairs of 12-year-old twins, we directly compared twin-study heritability estimates for cognitive abilities (language, verbal, nonverbal, and general) with GCTA estimates captured by 1.7 million DNA markers. We found that DNA markers tagged by the array accounted for .66 of the estimated heritability, reaffirming that cognitive abilities are heritable. Larger sample sizes alone will be sufficient to identify many of the genetic variants that influence cognitive abilities.

Evidence for specificity of polygenic contributions to attainment in English, maths and science during adolescence.

How well one does at school is predictive of a wide range of important cognitive, socioeconomic, and health outcomes. The last few years have shown marked advancement in our understanding of the genetic contributions to, and correlations with, academic attainment. However, there exists a gap in our understanding of the specificity of genetic associations with performance in academic subjects during adolescence, a critical developmental period. To address this, the Avon Longitudinal Study of Parents and Children was used to conduct genome-wide association studies of standardised national English (N = 5983), maths (N = 6017) and science (N = 6089) tests. High SNP-based heritabilities (h2SNP) for all subjects were found (41-53%). Further, h2SNP for maths and science remained after removing shared variance between subjects or IQ (N = 3197-5895). One genome-wide significant single nucleotide polymorphism (rs952964, p = 4.86 × 10-8) and four gene-level associations with science attainment (MEF2C, BRINP1, S100A1 and S100A13) were identified. Rs952964 remained significant after removing the variance shared between academic subjects. The findings highlight the benefits of using environmentally homogeneous samples for genetic analyses and indicate that finer-grained phenotyping will help build more specific biological models of variance in learning processes and abilities.

A three-stage genome-wide association study of general cognitive ability: hunting the small effects.

Childhood general cognitive ability (g) is important for a wide range of outcomes in later life, from school achievement to occupational success and life expectancy. Large-scale association studies will be essential in the quest to identify variants that make up the substantial genetic component implicated by quantitative genetic studies. We conducted a three-stage genome-wide association study for general cognitive ability using over 350,000 single nucleotide polymorphisms (SNPs) in the quantitative extremes of a population sample of 7,900 7-year-old children from the UK Twins Early Development Study. Using two DNA pooling stages to enrich true positives, each of around 1,000 children selected from the extremes of the distribution, and a third individual genotyping stage of over 3,000 children to test for quantitative associations across the normal range, we aimed to home in on genes of small effect. Genome-wide results suggested that our approach was successful in enriching true associations and 28 SNPs were taken forward to individual genotyping in an unselected population sample. However, although we found an enrichment of low P values and identified nine SNPs nominally associated with g (P < 0.05) that show interesting characteristics for follow-up, further replication will be necessary to meet rigorous standards of association. These replications may take advantage of SNP sets to overcome limitations of statistical power. Despite our large sample size and three-stage design, the genes associated with childhood g remain tantalizingly beyond our current reach, providing further evidence for the small effect sizes of individual loci. Larger samples, denser arrays and multiple replications will be necessary in the hunt for the genetic variants that influence human cognitive ability.

In search of genes associated with risk for psychopathic tendencies in children: a two-stage genome-wide association study of pooled DNA.

BACKGROUND: Quantitative genetic data from our group indicates that antisocial behaviour (AB) is strongly heritable when coupled with psychopathic, callous-unemotional (CU) personality traits. We have also demonstrated that the genetic influences for AB and CU overlap considerably. We conducted a genome-wide association scan that capitalises on these findings in an attempt to identify quantitative trait loci (QTLs) that may increase risk for psychopathic tendencies (AB+/CU+). METHODS: Teacher ratings at age 7 were used to screen 8374 twins with available DNA samples for individuals that were high vs. low on both AB and CU. In Stage 1, we screened for allele frequency differences in 642,432 autosomal single-nucleotide polymorphisms (SNPs) using the Affymetrix 6.0 GeneChip with pooled DNA for high-scoring (AB+/CU+) versus low-scoring children (N = approximately 300/group). In Stage 2, we tested the 3000 most strongly associated SNPs from Stage 1 for association in the same direction in a second sample of high- versus low-scoring children from the same twin study (18% co-twins). RESULTS: Using allele frequencies estimated from pooled DNA, we found suggestive evidence for enrichment of association in the second stage of our two-stage genome-wide association design and focus on reporting the 30 top-ranking SNPs nominally associated with psychopathic tendencies. These SNPs include neurodevelopmental genes such as ROBO2. CONCLUSIONS: Although none of the SNPs reached genome-wide statistical significance we have generated a list of SNPs that are potentially associated with psychopathic tendencies, which we believe warrant verification and replication in large independent and clinical samples.

Leveraging epigenetics to examine differences in developmental trajectories of social attention: A proof-of-principle study of DNA methylation in infants with older siblings with autism.

Preliminary evidence suggests that changes in DNA methylation, a widely studied epigenetic mechanism, contribute to the etiology of Autism Spectrum Disorder (ASD). However, data is primarily derived from post-mortem brain samples or peripheral tissue from adults. Deep-phenotyped longitudinal infant cohorts are essential to understand how epigenetic modifications relate to early developmental trajectories and emergence of ASD symptoms. We present a proof-of-principle study designed to evaluate the potential of prospective epigenetic studies of infant siblings of children with ASD. Illumina genome-wide 450 K DNA methylation data from buccal swabs was generated for 63 male infants at multiple time-points from 8 months to 2 years of age (total N = 107 samples). 11 of those infants received a diagnosis of ASD at 3 years. We conducted a series of analyses to characterize DNA methylation signatures associated with categorical outcome and neurocognitive measures from parent-report questionnaire, eye-tracking and electro-encephalography. Effects observed across the entire genome (epigenome-wide association analyses) suggest that collecting DNA methylation samples within infant-sibling designs allows for the detection of meaningful signals with smaller sample sizes than previously estimated. Mapping networks of co-methylated probes associated with neural correlates of social attention implicated enrichment of pathways involved in brain development. Longitudinal modelling found covariation between phenotypic traits and DNA methylation levels in the proximity of genes previously associated with cognitive development, although larger samples and more complete datasets are needed to obtain generalizable results. In conclusion, assessment of DNA methylation profiles at multiple time-points in infant-sibling designs is a promising avenue to comprehend developmental origins and mechanisms of ASD.

Assessing individual differences in genome-wide gene expression in human whole blood: reliability over four hours and stability over 10 months.

Studying the causes and correlates of natural variation in gene expression in healthy populations assumes that individual differences in gene expression can be reliably and stably assessed across time. However, this is yet to be established. We examined 4-hour test-retest reliability and 10 month test-retest stability of individual differences in gene expression in ten 12-year-old children. Blood was collected on four occasions: 10 a.m. and 2 p.m. on Day 1 and 10 months later at 10 a.m. and 2 p.m. Total RNA was hybridized to Affymetrix-U133 plus 2.0 arrays. For each probeset, the correlation across individuals between 10 a.m. and 2 p.m. on Day 1 estimates test-retest reliability. We identified 3,414 variable and abundantly expressed probesets whose 4-hour test-retest reliability exceeded .70, a conventionally accepted level of reliability, which we had 80% power to detect. Of the 3,414 reliable probesets, 1,752 were also significantly reliable 10 months later. We assessed the long-term stability of individual differences in gene expression by correlating the average expression level for each probe-set across the two 4-hour assessments on Day 1 with the average level of each probe-set across the two 4-hour assessments 10 months later. 1,291 (73.7%) of the 1,752 probe-sets that reliably detected individual differences across 4 hours on two occasions, 10 months apart, also stably detected individual differences across 10 months. Heritability, as estimated from the MZ twin intraclass correlations, is twice as high for the 1,752 reliable probesets versus all present probesets on the array (0.68 vs 0.34), and is even higher (0.76) for the 1,291 reliable probesets that are also stable across 10 months. The 1,291 probesets that reliably detect individual differences from a single peripheral blood collection and stably detect individual differences over 10 months are promising targets for research on the causes (e.g., eQTLs) and correlates (e.g., psychopathology) of individual differences in gene expression.

Genome-Wide Association Study of Latent Cognitive Measures in Adolescence: Genetic Overlap With Intelligence and Education.

Individual differences in executive functions (EF) are heritable and predictive of academic attainment (AA). However, little is known about genetic contributions to EFs or their genetic relationship with AA and intelligence. We conducted genome-wide association analyses for processing speed (PS) and the latent EF measures of working memory (WM) and inhibitory control (IC) in 4,611 adolescents from the Avon Longitudinal Study of Parents and Children. While no loci reached genome-wide significance, common genetic variants explained 30% of the variance in WM and 19% in PS. In contrast, we failed to find common genetic contributions to IC. Finally, we examined shared genetic effects between EFs and general intelligence, AA and ADHD. We identified significant genetic correlations between WM, intelligence, and AA. A more specific pattern was observed for PS, with modest genetic overlap with intelligence. Together these findings highlight diversity in the genetic contributions to specific cognitive functions and their genetic relationship with educational and psychiatric outcomes.

RNA sequencing of identical twins discordant for autism reveals blood-based signatures implicating immune and transcriptional dysregulation.

Background: A gap exists in our mechanistic understanding of how genetic and environmental risk factors converge at the molecular level to result in the emergence of autism symptoms. We compared blood-based gene expression signatures in identical twins concordant and discordant for autism spectrum condition (ASC) to differentiate genetic and environmentally driven transcription differences, and establish convergent evidence for biological mechanisms involved in ASC. Methods: Genome-wide gene expression data were generated using RNA-seq on whole blood samples taken from 16 pairs of monozygotic (MZ) twins and seven twin pair members (39 individuals in total), who had been assessed for ASC and autism traits at age 12. Differential expression (DE) analyses were performed between (a) affected and unaffected subjects (N = 36) and (b) within discordant ASC MZ twin pairs (total N = 11) to identify environmental-driven DE. Gene set enrichment and pathway testing was performed on DE gene lists. Finally, an integrative analysis using DNA methylation data aimed to identify genes with consistent evidence for altered regulation in cis. Results: In the discordant twin analysis, three genes showed evidence for DE at FDR < 10%: IGHG4, EVI2A and SNORD15B. In the case-control analysis, four DE genes were identified at FDR < 10% including IGHG4, PRR13P5, DEPDC1B, and ZNF501. We find enrichment for DE of genes curated in the SFARI human gene database. Pathways showing evidence of enrichment included those related to immune cell signalling and immune response, transcriptional control and cell cycle/proliferation. Integrative methylomic and transcriptomic analysis identified a number of genes showing suggestive evidence for cis dysregulation. Limitations: Identical twins stably discordant for ASC are rare, and as such the sample size was limited and constrained to the use of peripheral blood tissue for transcriptomic and methylomic profiling. Given these primary limitations, we focused on transcript-level analysis. Conclusions: Using a cohort of ASC discordant and concordant MZ twins, we add to the growing body of transcriptomic-based evidence for an immune-based component in the molecular aetiology of ASC. Whilst the sample size was limited, the study demonstrates the utility of the discordant MZ twin design combined with multi-omics integration for maximising the potential to identify disease-associated molecular signals.

Genotyping pooled DNA using 100K SNP microarrays: a step towards genomewide association scans.

The identification of quantitative trait loci (QTLs) of small effect size that underlie complex traits poses a particular challenge for geneticists due to the large sample sizes and large numbers of genetic markers required for genomewide association scans. An efficient solution for screening purposes is to combine single nucleotide polymorphism (SNP) microarrays and DNA pooling (SNP-MaP), an approach that has been shown to be valid, reliable and accurate in deriving relative allele frequency estimates from pooled DNA for groups such as cases and controls for 10K SNP microarrays. However, in order to conduct a genomewide association study many more SNP markers are needed. To this end, we assessed the validity and reliability of the SNP-MaP method using Affymetrix GeneChip Mapping 100K Array set. Interpretable results emerged for 95% of the SNPs (nearly 110,000 SNPs). We found that SNP-MaP allele frequency estimates correlated 0.939 with allele frequencies for 97 605 SNPs that were genotyped individually in an independent population; the correlation was 0.971 for 26 SNPs that were genotyped individually for the 1028 individuals used to construct the DNA pools. We conclude that extending the SNP-MaP method to the Affymetrix GeneChip Mapping 100K Array set provides a useful screen of >100,000 SNP markers for QTL association scans.

A central resource for accurate allele frequency estimation from pooled DNA genotyped on DNA microarrays.

Analysing pooled DNA on microarrays is an efficient way to genotype hundreds of individuals for thousands of markers for genome-wide association. Although direct comparison of case and control fluorescence scores is possible, correction for differential hybridization of alleles is important, particularly for rare single nucleotide polymorphisms. Such correction relies on heterozygous fluorescence scores and requires the genotyping of hundreds of individuals to obtain sufficient estimates of the correction factor, completely negating any benefit gained by pooling samples. We explore the effect of differential hybridization on test statistics and provide a solution to this problem in the form of a central resource for the accumulation of heterozygous fluorescence scores, allowing accurate allele frequency estimation at no extra cost.