De novo structural mutation rates and gamete-of-origin biases revealed through genome sequencing of 2,396 families.

Each human genome includes de novo mutations that arose during gametogenesis. While these germline mutations represent a fundamental source of new genetic diversity, they can also create deleterious alleles that impact fitness. Whereas the rate and patterns of point mutations in the human germline are now well understood, far less is known about the frequency and features that impact de novo structural variants (dnSVs). We report a family-based study of germline mutations among 9,599 human genomes from 33 multigenerational CEPH-Utah families and 2,384 families from the Simons Foundation Autism Research Initiative. We find that de novo structural mutations detected by alignment-based, short-read WGS occur at an overall rate of at least 0.160 events per genome in unaffected individuals, and we observe a significantly higher rate (0.206 per genome) in ASD-affected individuals. In both probands and unaffected samples, nearly 73% of de novo structural mutations arose in paternal gametes, and we predict most de novo structural mutations to be caused by mutational mechanisms that do not require sequence homology. After multiple testing correction, we did not observe a statistically significant correlation between parental age and the rate of de novo structural variation in offspring. These results highlight that a spectrum of mutational mechanisms contribute to germline structural mutations and that these mechanisms most likely have markedly different rates and selective pressures than those leading to point mutations.

Pedigree-based estimation of human mobile element retrotransposition rates.

Germline mutation rates in humans have been estimated for a variety of mutation types, including single-nucleotide and large structural variants. Here, we directly measure the germline retrotransposition rate for the three active retrotransposon elements: L1, Alu, and SVA. We used three tools for calling mobile element insertions (MEIs) (MELT, RUFUS, and TranSurVeyor) on blood-derived whole-genome sequence (WGS) data from 599 CEPH individuals, comprising 33 three-generation pedigrees. We identified 26 de novo MEIs in 437 births. The retrotransposition rate estimates for Alu elements, one in 40 births, is roughly half the rate estimated using phylogenetic analyses, a difference in magnitude similar to that observed for single-nucleotide variants. The L1 retrotransposition rate is one in 63 births and is within range of previous estimates (1:20-1:200 births). The SVA retrotransposition rate, one in 63 births, is much higher than the previous estimate of one in 900 births. Our large, three-generation pedigrees allowed us to assess parent-of-origin effects and the timing of insertion events in either gametogenesis or early embryonic development. We find a statistically significant paternal bias in Alu retrotransposition. Our study represents the first in-depth analysis of the rate and dynamics of human retrotransposition from WGS data in three-generation human pedigrees.

TypeTE: a tool to genotype mobile element insertions from whole genome resequencing data.

Alu retrotransposons account for more than 10% of the human genome, and insertions of these elements create structural variants segregating in human populations. Such polymorphic Alus are powerful markers to understand population structure, and they represent variants that can greatly impact genome function, including gene expression. Accurate genotyping of Alus and other mobile elements has been challenging. Indeed, we found that Alu genotypes previously called for the 1000 Genomes Project are sometimes erroneous, which poses significant problems for phasing these insertions with other variants that comprise the haplotype. To ameliorate this issue, we introduce a new pipeline - TypeTE - which genotypes Alu insertions from whole-genome sequencing data. Starting from a list of polymorphic Alus, TypeTE identifies the hallmarks (poly-A tail and target site duplication) and orientation of Alu insertions using local re-assembly to reconstruct presence and absence alleles. Genotype likelihoods are then computed after re-mapping sequencing reads to the reconstructed alleles. Using a high-quality set of PCR-based genotyping of >200 loci, we show that TypeTE improves genotype accuracy from 83% to 92% in the 1000 Genomes dataset. TypeTE can be readily adapted to other retrotransposon families and brings a valuable toolbox addition for population genomics.

Plastic Transcriptomes Stabilize Immunity to Pathogen Diversity: The Jasmonic Acid and Salicylic Acid Networks within the Arabidopsis/Botrytis Pathosystem.

To respond to pathogen attack, selection and associated evolution has led to the creation of plant immune system that are a highly effective and inducible defense system. Central to this system are the plant defense hormones jasmonic acid (JA) and salicylic acid (SA) and crosstalk between the two, which may play an important role in defense responses to specific pathogens or even genotypes. Here, we used the Arabidopsis thaliana-Botrytis cinerea pathosystem to test how the host's defense system functions against genetic variation in a pathogen. We measured defense-related phenotypes and transcriptomic responses in Arabidopsis wild-type Col-0 and JA- and SA-signaling mutants, coi1-1 and npr1-1, individually challenged with 96 diverse B. cinerea isolates. Those data showed genetic variation in the pathogen influences on all components within the plant defense system at the transcriptional level. We identified four gene coexpression networks and two vectors of defense variation triggered by genetic variation in B. cinerea This showed that the JA and SA signaling pathways functioned to constrain/canalize the range of virulence in the pathogen population, but the underlying transcriptomic response was highly plastic. These data showed that plants utilize major defense hormone pathways to buffer disease resistance, but not the metabolic or transcriptional responses to genetic variation within a pathogen.

Digital Imaging Combined with Genome-Wide Association Mapping Links Loci to Plant-Pathogen Interaction Traits.

Plant resistance to generalist pathogens with broad host ranges, such as Botrytis cinerea (Botrytis), is typically quantitative and highly polygenic. Recent studies have begun to elucidate the molecular genetic basis of plant-pathogen interactions using commonly measured traits, including lesion size and/or pathogen biomass. However, with the advent of digital imaging and high-throughput phenomics, there are a large number of additional traits available to study quantitative resistance. In this study, we used high-throughput digital imaging analysis to investigate previously poorly characterized visual traits of plant-pathogen interactions related to disease resistance using the Arabidopsis (Arabidopsis thaliana)/Botrytis pathosystem. From a large collection of visual lesion trait measurements, we focused on color, shape, and size to test how these aspects of the Arabidopsis/Botrytis interaction are genetically related. Through genome-wide association mapping in Arabidopsis, we show that lesion color and shape are genetically separable traits associated with plant disease resistance. Moreover, by employing defined mutants in 23 candidate genes identified from the genome-wide association mapping, we demonstrate links between loci and each of the different plant-pathogen interaction traits. These results expand our understanding of the functional mechanisms driving plant disease resistance.

The Quantitative Basis of the Arabidopsis Innate Immune System to Endemic Pathogens Depends on Pathogen Genetics.

The most established model of the eukaryotic innate immune system is derived from examples of large effect monogenic quantitative resistance to pathogens. However, many host-pathogen interactions involve many genes of small to medium effect and exhibit quantitative resistance. We used the Arabidopsis-Botrytis pathosystem to explore the quantitative genetic architecture underlying host innate immune system in a population of Arabidopsis thaliana. By infecting a diverse panel of Arabidopsis accessions with four phenotypically and genotypically distinct isolates of the fungal necrotroph B. cinerea, we identified a total of 2,982 genes associated with quantitative resistance using lesion area and 3,354 genes associated with camalexin production as measures of the interaction. Most genes were associated with resistance to a specific Botrytis isolate, which demonstrates the influence of pathogen genetic variation in analyzing host quantitative resistance. While known resistance genes, such as receptor-like kinases (RLKs) and nucleotide-binding site leucine-rich repeat proteins (NLRs), were found to be enriched among associated genes, they only account for a small fraction of the total genes associated with quantitative resistance. Using publically available co-expression data, we condensed the quantitative resistance associated genes into co-expressed gene networks. GO analysis of these networks implicated several biological processes commonly connected to disease resistance, including defense hormone signaling and ROS production, as well as novel processes, such as leaf development. Validation of single gene T-DNA knockouts in a Col-0 background demonstrate a high success rate (60%) when accounting for differences in environmental and Botrytis genetic variation. This study shows that the genetic architecture underlying host innate immune system is extremely complex and is likely able to sense and respond to differential virulence among pathogen genotypes.

Epistasis × environment interactions among Arabidopsis thaliana glucosinolate genes impact complex traits and fitness in the field.

Despite the growing number of studies showing that genotype × environment and epistatic interactions control fitness, the influences of epistasis × environment interactions on adaptive trait evolution remain largely uncharacterized. Across three field trials, we quantified aliphatic glucosinolate (GSL) defense chemistry, leaf damage, and relative fitness using mutant lines of Arabidopsis thaliana varying at pairs of causal aliphatic GSL defense genes to test the impact of epistatic and epistasis × environment interactions on adaptive trait variation. We found that aliphatic GSL accumulation was primarily influenced by additive and epistatic genetic variation, leaf damage was primarily influenced by environmental variation and relative fitness was primarily influenced by epistasis and epistasis × environment interactions. Epistasis × environment interactions accounted for up to 48% of the relative fitness variation in the field. At a single field site, the impact of epistasis on relative fitness varied significantly over 2 yr, showing that epistasis × environment interactions within a location can be temporally dynamic. These results suggest that the environmental dependency of epistasis can profoundly influence the response to selection, shaping the adaptive trajectories of natural populations in complex ways, and deserves further consideration in future evolutionary studies.

Morphologic, immunophenotypic, molecular genetic, and clinical characterization in patients with SRSF2-mutated acute myeloid leukemia.

OBJECTIVES: SRSF2 mutations are known to be associated with poor outcomes in myelodysplastic neoplasm, but studies on their prognostic impact on acute myeloid leukemia (AML) remain limited. In this retrospective study, we analyzed clinical and pathologic characteristics of patients with AML and correlated the outcomes with SRSF2 mutations. METHODS: We characterized the morphologic, immunophenotypic, molecular, and clinical findings in AML with mutated SRSF2 and compared them with SRSF2 wild-type (WT) myeloid neoplasms (MNs). RESULTS: Using next-generation sequencing, we identified 134 patients with MNs and SRSF2 mutations (85 with AML and 49 with MNs) in addition to 342 SRSF2-WT AMLs. Fifty-two (62%) patients with altered SRSF2 demonstrated a variable degree of morphologic dysplasia. The most frequent immunophenotypic aberrancies in SRSF2-mutant AML included diminished CD33 expression and overexpression of CD7, CD56, or CD123, similar to WT AML. More IDH1/2 (P = .015) and NPM1 (P = .002) mutations were seen in SRSF2-mutant AML than in SRSF2-mutant non-AML. Further, more IDH1/2, ASXL1, RUNX1, and STAG2 mutations were observed in SRSF2-mutant AML than in SRSF2-WT AML (P < .0001 to P = .001). Finally, patients with SRSF2-mutant AML showed a significantly worse overall survival (OS) than patients with SRSF2-WT AML (P < .0001), but this worse OS appeared to be rescued by allogeneic stem cell transplant (allo-SCT). CONCLUSIONS: Acute myeloid leukemia with altered SRSF2 shows a variable degree of morphologic dysplasia without uniform immunophenotypic aberrancies. SRSF2 mutations appear to be independent poor prognostic factors, but allo-SCT has improved the clinical outcomes in patients with SRSF2-mutant AML.

Mobile element insertions and associated structural variants in longitudinal breast cancer samples.

While mobile elements are largely inactive in healthy somatic tissues, increased activity has been found in cancer tissues, with significant variation among different cancer types. In addition to insertion events, mobile elements have also been found to mediate many structural variation events in the genome. Here, to better understand the timing and impact of mobile element insertions and associated structural variants in cancer, we examined their activity in longitudinal samples of four metastatic breast cancer patients. We identified 11 mobile element insertions or associated structural variants and found that the majority of these occurred early in tumor progression. Most of the variants impact intergenic regions; however, we identified a translocation interrupting MAP2K4 involving Alu elements and a deletion in YTHDF2 involving mobile elements that likely inactivate reported tumor suppressor genes. The high variant allele fraction of the translocation, the loss of the other copy of MAP2K4, the recurrent loss-of-function mutations found in this gene in other cancers, and the important function of MAP2K4 indicate that this translocation is potentially a driver mutation. Overall, using a unique longitudinal dataset, we find that most variants are likely passenger mutations in the four patients we examined, but some variants impact tumor progression.

Large-Scale Identification of Clonal Hematopoiesis and Mutations Recurrent in Blood Cancers.

Clonal hematopoiesis of indeterminate potential (CHIP) is characterized by detectable hematopoietic-associated gene mutations in a person without evidence of hematologic malignancy. We sought to identify additional cancer-presenting mutations useable for CHIP detection by performing a data mining analysis of 48 somatic mutation studies reporting mutations at diagnoses of 7,430 adult and pediatric patients with hematologic malignancies. Following extraction of 20,141 protein-altering mutations, we identified 434 significantly recurrent mutation hotspots, 364 of which occurred at loci confidently assessable for CHIP. We then performed an additional large-scale analysis of whole exome sequencing data from 4,538 persons belonging to three non-cancer cohorts for clonal mutations. We found the combined cohort prevalence of CHIP with mutations identical to those reported at blood cancer mutation hotspots to be 1.8%, and that some of these CHIP mutations occurred in children. Our findings may help to improve CHIP detection and pre-cancer surveillance for both children and adults.

Shared genomic segment analysis in a large high-risk chronic lymphocytic leukemia pedigree implicates CXCR4 in inherited risk.

AIM: Chronic lymphocytic leukemia (CLL) has been shown to cluster in families. First-degree relatives of individuals with CLL have an ~8 fold increased risk of developing the malignancy. Strong heritability suggests pedigree studies will have good power to localize pathogenic genes. However, CLL is relatively rare and heterogeneous, complicating ascertainment and analyses. Our goal was to identify CLL risk loci using unique resources available in Utah and methods to address intra-familial heterogeneity. METHODS: We identified a six-generation high-risk CLL pedigree using the Utah Population Database. This pedigree contains 24 CLL cases connected by a common ancestor. We ascertained and genotyped eight CLL cases using a high-density SNP array, and then performed shared genomic segment (SGS) analysis - a method designed for extended high-risk pedigrees that accounts for heterogeneity. RESULTS: We identified a genome-wide significant region (P = 1.9 × 10-7, LOD-equivalent 5.6) at 2q22.1. The 0.9 Mb region was inherited through 26 meioses and shared by seven of the eight genotyped cases. It sits within a ~6.25 Mb locus identified in a previous linkage study of 206 small CLL families. Our narrow region intersects two genes, including CXCR4 which is highly expressed in CLL cells and implicated in maintenance and progression. CONCLUSION: SGS analysis of an extended high-risk CLL pedigree identified the most significant evidence to-date for a 0.9 Mb CLL disease locus at 2q22.1, harboring CXCR4. This discovery contributes to a growing literature implicating CXCR4 in inherited risk to CLL. Investigation of the segregating haplotype in the pedigree will be valuable for elucidating risk variant(s).

The Simons Genome Diversity Project: A Global Analysis of Mobile Element Diversity.

Ongoing retrotransposition of Alu, LINE-1, and SINE-VNTR-Alu elements generates diversity and variation among human populations. Previous analyses investigating the population genetics of mobile element insertions (MEIs) have been limited by population ascertainment bias or by relatively small numbers of populations and low sequencing coverage. Here, we use 296 individuals representing 142 global populations from the Simons Genome Diversity Project (SGDP) to discover and characterize MEI diversity from deeply sequenced whole-genome data. We report 5,742 MEIs not originally reported by the 1000 Genomes Project and show that high sampling diversity leads to a 4- to 7-fold increase in MEI discovery rates over the original 1000 Genomes Project data. As a result of negative selection, nonreference polymorphic MEIs are underrepresented within genes, and MEIs within genes are often found in the transcriptional orientation opposite that of the gene. Globally, 80% of Alu subfamilies predate the expansion of modern humans from Africa. Polymorphic MEIs show heterozygosity gradients that decrease from Africa to Eurasia to the Americas, and the number of MEIs found uniquely in a single individual are also distributed in this general pattern. The maximum fraction of MEI diversity partitioned among the seven major SGDP population groups (FST) is 7.4%, similar to, but slightly lower than, previous estimates and likely attributable to the diverse sampling strategy of the SGDP. Finally, we utilize these MEIs to extrapolate the primary Native American shared ancestry component to back to Asia and provide new evidence from genome-wide identical-by-descent genetic markers that add additional support for a southeastern Siberian origin for most Native Americans.

Plant-necrotroph co-transcriptome networks illuminate a metabolic battlefield.

A central goal of studying host-pathogen interaction is to understand how host and pathogen manipulate each other to promote their own fitness in a pathosystem. Co-transcriptomic approaches can simultaneously analyze dual transcriptomes during infection and provide a systematic map of the cross-kingdom communication between two species. Here we used the Arabidopsis-B. cinerea pathosystem to test how plant host and fungal pathogen interact at the transcriptomic level. We assessed the impact of genetic diversity in pathogen and host by utilization of a collection of 96 isolates infection on Arabidopsis wild-type and two mutants with jasmonate or salicylic acid compromised immunities. We identified ten B. cinereagene co-expression networks (GCNs) that encode known or novel virulence mechanisms. Construction of a dual interaction network by combining four host- and ten pathogen-GCNs revealed potential connections between the fungal and plant GCNs. These co-transcriptome data shed lights on the potential mechanisms underlying host-pathogen interaction.

Discovery of rare, diagnostic AluYb8/9 elements in diverse human populations.

BACKGROUND: Polymorphic human Alu elements are excellent tools for assessing population structure, and new retrotransposition events can contribute to disease. Next-generation sequencing has greatly increased the potential to discover Alu elements in human populations, and various sequencing and bioinformatics methods have been designed to tackle the problem of detecting these highly repetitive elements. However, current techniques for Alu discovery may miss rare, polymorphic Alu elements. Combining multiple discovery approaches may provide a better profile of the polymorphic Alu mobilome. AluYb8/9 elements have been a focus of our recent studies as they are young subfamilies (~2.3 million years old) that contribute ~30% of recent polymorphic Alu retrotransposition events. Here, we update our ME-Scan methods for detecting Alu elements and apply these methods to discover new insertions in a large set of individuals with diverse ancestral backgrounds. RESULTS: We identified 5,288 putative Alu insertion events, including several hundred novel AluYb8/9 elements from 213 individuals from 18 diverse human populations. Hundreds of these loci were specific to continental populations, and 23 non-reference population-specific loci were validated by PCR. We provide high-quality sequence information for 68 rare AluYb8/9 elements, of which 11 have hallmarks of an active source element. Our subfamily distribution of rare AluYb8/9 elements is consistent with previous datasets, and may be representative of rare loci. We also find that while ME-Scan and low-coverage, whole-genome sequencing (WGS) detect different Alu elements in 41 1000 Genomes individuals, the two methods yield similar population structure results. CONCLUSION: Current in-silico methods for Alu discovery may miss rare, polymorphic Alu elements. Therefore, using multiple techniques can provide a more accurate profile of Alu elements in individuals and populations. We improved our false-negative rate as an indicator of sample quality for future ME-Scan experiments. In conclusion, we demonstrate that ME-Scan is a good supplement for next-generation sequencing methods and is well-suited for population-level analyses.

The evolving genetic risk for sporadic ALS.

OBJECTIVE: To estimate the genetic risk conferred by known amyotrophic lateral sclerosis (ALS)-associated genes to the pathogenesis of sporadic ALS (SALS) using variant allele frequencies combined with predicted variant pathogenicity. METHODS: Whole exome sequencing and repeat expansion PCR of C9orf72 and ATXN2 were performed on 87 patients of European ancestry with SALS seen at the University of Utah. DNA variants that change the protein coding sequence of 31 ALS-associated genes were annotated to determine which were rare and deleterious as predicted by MetaSVM. The percentage of patients with SALS with a rare and deleterious variant or repeat expansion in an ALS-associated gene was calculated. An odds ratio analysis was performed comparing the burden of ALS-associated genes in patients with SALS vs 324 normal controls. RESULTS: Nineteen rare nonsynonymous variants in an ALS-associated gene, 2 of which were found in 2 different individuals, were identified in 21 patients with SALS. Further, 5 deleterious C9orf72 and 2 ATXN2 repeat expansions were identified. A total of 17.2% of patients with SALS had a rare and deleterious variant or repeat expansion in an ALS-associated gene. The genetic burden of ALS-associated genes in patients with SALS as predicted by MetaSVM was significantly higher than in normal controls. CONCLUSIONS: Previous analyses have identified SALS-predisposing variants only in terms of their rarity in normal control populations. By incorporating variant pathogenicity as well as variant frequency, we demonstrated that the genetic risk contributed by these genes for SALS is substantially lower than previous estimates.

A Genome-Wide Search for Greek and Jewish Admixture in the Kashmiri Population.

The Kashmiri population is an ethno-linguistic group that resides in the Kashmir Valley in northern India. A longstanding hypothesis is that this population derives ancestry from Jewish and/or Greek sources. There is historical and archaeological evidence of ancient Greek presence in India and Kashmir. Further, some historical accounts suggest ancient Hebrew ancestry as well. To date, it has not been determined whether signatures of Greek or Jewish admixture can be detected in the Kashmiri population. Using genome-wide genotyping and admixture detection methods, we determined there are no significant or substantial signs of Greek or Jewish admixture in modern-day Kashmiris. The ancestry of Kashmiri Tibetans was also determined, which showed signs of admixture with populations from northern India and west Eurasia. These results contribute to our understanding of the existing population structure in northern India and its surrounding geographical areas.

Natural genetic variation in Arabidopsis thaliana defense metabolism genes modulates field fitness.

Natural populations persist in complex environments, where biotic stressors, such as pathogen and insect communities, fluctuate temporally and spatially. These shifting biotic pressures generate heterogeneous selective forces that can maintain standing natural variation within a species. To directly test if genes containing causal variation for the Arabidopsis thaliana defensive compounds, glucosinolates (GSL) control field fitness and are therefore subject to natural selection, we conducted a multi-year field trial using lines that vary in only specific causal genes. Interestingly, we found that variation in these naturally polymorphic GSL genes affected fitness in each of our environments but the pattern fluctuated such that highly fit genotypes in one trial displayed lower fitness in another and that no GSL genotype or genotypes consistently out-performed the others. This was true both across locations and within the same location across years. These results indicate that environmental heterogeneity may contribute to the maintenance of GSL variation observed within Arabidopsis thaliana.