Analysis of exome sequencing data identifies a candidate azoospermia mutation in the case of UPD2.

<p>We performed whole-exome sequencing on the case of UPD2 in an attempt to identify a potential genetic cause for this man's azoospermia. We constructed a scoring method to rank order the exome variants in two dimensions: (i) within the set of variants seen in this single exome, the “Individual Score” and (ii) across a large set of exome sequences, the “Population Score”. For each exome variant, the Individual Score, P_ind,, was constructed by summing normalized predictions of functional impact from 5 commonly used annotation algorithms: PhyloP, PolyPhen2, SIFT, GERP, and LRT. This score was then multiplied by the ploidy of the mutant allele (e.g. 1× for a heterozygous genotype and 2× for a homozygous genotype) creating a final Individual Score ranging from 0–10. We also calculated the Individual Score for all variation in the 1000 genomes Phase I sequencing data. To construct the “Population Score” for each variant in the UPD individual, P_pop, we identified the maximum Individual Score variant in the corresponding gene, P_max, within the 1000 genomes data, and defined P_pop = P_ind−P_max. The purpose of the Population Score is to scale the importance of each Individual Score by the extent of pathogenic variation that exists in the population at each gene. Only sites with minor allele frequencies less than 10% in both the 1000 genomes data and the Exome Variant Server (<a href="http://evs.gs.washington.edu/EVS/" target="_blank">http://evs.gs.washington.edu/EVS/</a>) were considered in the analysis. When examining the joint distribution of P_pop and P_ind for the UPD2 individual, we saw an enrichment of large scores for variants on chromosome 2, as expected. The most extreme variant on both scales was a homozygous nonsense mutation in the gene <i>INHBB</i>, the implications of which we discuss in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003349#pgen-1003349-g006" target="_blank">Figure 6</a>.</p

Homozygous missense mutation of <i>INHBB</i> identified in the case of UPD2.

<p>(A) We validated this candidate by Sanger sequencing in the UPD2 case and control individuals. Mutant and reference nucleotides are highlighted within the blue box, confirming the homozygous T to C nucleotide change observed at chr2:12,1107,305 bp (hg19) of the UPD2 individual. Grey boxes represent the exons of the gene and the red line indicates the location of the observed mutation within the gene. (B) <i>INHBB</i> encodes for the protein, Inhibin βB, which along with inhibin α and inhibin βA, combine combinatorially to form the inhibins and activins. Each protein expressed by <i>INHA</i>, <i>INHBA</i>, <i>INHBB</i> consists of an N-terminal signal peptide (purple), a propeptide (grey), and a subunit chain (green, red or yellow). The mutation identified here results in a M370T change of the inhibin βB subunit chain (location indicated by a vertical red line throughout the diagram). The various inhibin subunits dimerize via disulfide bonds (locations indicated by black lines between subunits). As the βB subunit participates in multiple complexes with antagonistic functions, the functional consequences of loss-of-function or gain-of-function mutations in this protein may be difficult to predict. (C) The role of inhibins and activins in the hypothalamic-pituitary testicular axis. These complexes have diverse functions in the body, but are most well known for their ability to stimulate and inhibit follicle stimulating hormone (FSH) production, a process critical for spermatogenesis. Blue arrows connect hormones to the cell or gland by which they are secreted. Green arrows indicate stimulatory interactions, and red lines indicate inhibitory interactions.</p

<i>DMRT1</i> deletions detected by array in the current study.

<p>‘DMRT1 Exons’ – exons contained within each deletion, numbered from the 5′ to 3′ position. SCOS – Sertoli Cell Only Syndrome; MA – maturation arrest. Deletion coordinates given with respect to NCBI36.</p

Discovery of recurrent deletions in azoospermia.

<p>(A) A recurrent microdeletion on Xp11.23 (47765109–47871527 bp, hg18) is a strong candidate risk factor for spermatogenic failure. The location of deletions (red shades) and duplications (blue shades) in cases and controls are plotted separately for each cohort. CNVs at this locus appear to arise due to non-allelic homologous recombination between two nearly identical (>99.5% homology) 16 kb segmental duplications that contain the sperm acrosome gene <i>SPACA5</i>. Also within the CNV region are the genes <i>ZNF630</i> and the cancer-testis antigen <i>SSX6</i>. We identified 9 deletions of this locus spread across all patient cohorts (3 in PT, 1 in UT, 5 in WUSTL) compared to 8 in the pooled 1124 controls (2.8% frequency versus 0.7%, odds ratio = 3.96, p = 0.005, Fisher exact test). After analysis of an additional 403 cases and 2121 controls, the association is still significant (combined data: 1.6% frequency in cases, 0.55% in controls, OR 3.0, 95% CI = [1.31–6.62], p = 0.007). (B) We identified two patients with deletion of <i>DMRT1</i>, a gene on 9p24.3 that is orthologous to the putative sex determination locus of the avian ZW chromosome system <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003349#pgen.1003349-Smith1" target="_blank">[36]</a>. Both men were diagnosed as azoospermic. We validated these deletion calls with a qPCR assay (green star, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003349#pgen.1003349.s010" target="_blank">Figure S9</a>). We screened Affymetrix 6.0 data from an independent Han Chinese case-control study of NOA and identified an additional 3 deletions of <i>DMRT1</i> coding sequence in 979 cases and none in 1734 controls. Finally, we observed no coding deletions of <i>DMRT1</i> in the two largest control SNP array datasets in the Database of Genomic Variants, consisting of 4519 samples <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003349#pgen.1003349-Itsara1" target="_blank">[42]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003349#pgen.1003349-Shaikh1" target="_blank">[43]</a>. The combined results indicate that deletion of <i>DMRT1</i> is a highly penetrant genetic cause of human spermatogenic failure (frequency of 0.38% in 1306 cases and 0% in 7754 controls, combined p = 6.2×10⁻⁵). Patient IDs are indicated next to each plot (U162_A, U841_A = Utah cohort patients; F3407, F5031, F1060 = Nanjing cohort patients).</p

Disruption of predicted haploinsufficient genes is infrequent in spermatogenic failure.

<p>We obtained lists of rare deletions, left panel, from the Utah and WTCCC control cohorts and, right panel, from cohorts of developmental delay (DECIPHER) <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003349#pgen.1003349-Firth1" target="_blank">[66]</a>, autism <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003349#pgen.1003349-Sanders1" target="_blank">[67]</a>, schizophrenia <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003349#pgen.1003349-Malhotra1" target="_blank">[68]</a>, bipolar disorder <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003349#pgen.1003349-Firth1" target="_blank">[66]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003349#pgen.1003349-Malhotra1" target="_blank">[68]</a>, and spermatogenic impairment (this study). We used a published method for assessing the likelihood that each deletion disrupts a haploinsufficient gene <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003349#pgen.1003349-Huang1" target="_blank">[47]</a>, summarized as a LOD score, and ordered each cohort by the median LOD(HI) within cases and controls separately. While the CNVS from DECIPHER (p<1×10⁻¹⁵), autism (p<1×10⁻¹⁵), schizophrenia (p<1×10⁻⁴) and bipolar disorder (p<0.002) show significant enrichment of high LOD (HI) scores compared to controls, the infertility cohorts have score distributions indistinguishable from controls. Two outlier deletions from the infertility cohort are annotated; one is a deletion of <i>WT1</i>, a key gene in gonadal differentiation, and the other is a 1 Mb deletion involving several genes including <i>MAPK1</i> and the cancer-testis antigen <i>PRAME</i>. Further review of clinical data from the <i>WT1</i> carrier showed signs of cryptorchidism. Abbreviation of azoospermia cohorts: az1, Utah cohort, az2, WUSTL, az3 Porto, az4, Weill-Cornell. Note that for additional detail we have split the cohort referred to as “Porto” in the main text into two subgroups, az3 and az4, defined by the clinical group that ascertained the cases.</p

Case and control cohorts used in the study.

<p>‘N’, number of individuals in the cohort after excluding ethnic outliers and samples with poor data quality. ‘Analyses’, describes whether the cohort was included in primary CNV analyses (‘C’), replication CNV analyses (‘R’), and autozygosity analyses (‘A’). Note that due to small sample sizes, the 17 Weill Cornell samples with SNP array data were merged with Porto samples and the combined set treated as a single cohort for the primary CNV analyses. Thus the total number of cases with whole-genome array data are 83+17+162+61 = 323. Many more samples were sourced from Cornell for replication analysis. Full details of each cohort are available in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003349#pgen.1003349.s018" target="_blank">Text S1</a>.</p

Patterns of homozygosity in men with low sperm count.

<p>(A) Distribution of the number of HBD regions (HBDRs), and the proportion of genome contained in these putative HBD regions, plotted for each sample in this study. Replication case and control cohorts are indicated in the legend. (B) Length distribution of HBDRs detected in all samples combined. Inset, two panels showing probe level intensity data corresponding to the two largest HBDRs detected. BAF: b-allele frequency, calculated as B/(A+B) where A and B are the approximate copy numbers for the A and B allele, respectively. The largest HBDR detected corresponds to a case of uniparental disomy of chromosome 2 (UPD2) detected in an azoospermic man from the Utah cohort.</p

Summary of inbreeding coefficient estimates across cohorts, and association testing.

<p>For each case and control group we present the average the estimated inbreeding coefficient and the number of individuals with inbreeding coefficients above a specified threshold. The last column indicates the total number of individuals in each group. The bottom two rows indicate the results of an association test between inbreeding and case/control status using either a categorical variable as a definition of inbreeding status (<i>F</i>>0.5%, <i>F</i>>1.6%, and <i>F</i>>6.25%) or using the inbreeding coefficient as a continuous variable (“All <i>F</i>”).</p

X-linked cancer-testis antigens deleted in case and control samples.

*<p>Gene or gene family is annotated multiple times on the reference genome; coordinates for the first copy are given.</p>**<p>Gene coordinates are based on NCBI36.</p>***<p>Frequency difference between cases and controls, p<0.05.</p>†<p>Patient-specific deletions of these genes were reported in a study of X-linked CNVs in over 250 azoospermia cases and 300 normospermic controls <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003349#pgen.1003349-Krausz2" target="_blank">[58]</a>.</p

Rare variant burden in cases of spermatogenic impairment.

<p>We used logistic regression to estimate the influence of copy number variants (CNVs) on the odds of being diagnosed with impaired spermatogenesis in three case-control cohorts. The estimated odds of spermatogenic impairment is equal to, or slightly lower than, one when considering autosomal deletions of all frequencies (leftmost panel, shaded grey). However, when considering only autosomal deletions with call frequencies less than 5%, we observed a progressively increasing risk conferred by events on the autosomes, the X and the Y chromosomes. A very small number of Y-linked calls were made in cohorts 1 and 3 due to array design, thus we have only plotted Y-linked rates for cohort 2. Samples with Y-linked AZF deletions were excluded from the study. The odds ratio estimated from fitting a logistic regression model of total CNV count to disease status is plotted separately for each cohort, as well as the combined set of all cohorts (black points). Cohort 1 = Utah (Illumina 370K), 2 = Porto and Weill Cornell (Affymetrix 6.0), 3 = WUSTL (Illumina OmniExpress), All = meta-analysis of all three cohorts. Sample sizes used in CNV analysis are n = 83 cases and 62 controls for cohort 1, n = 183 cases and 974 controls for cohort 2, and n = 61 cases and 100 controls for cohort 3.</p