Melissa Kramer

Analysis of the bread wheat genome using whole-genome shotgun sequencing

Bread wheat (Triticum aestivum) is a globally important crop, accounting for 20 per cent of the calories consumed by humans. Major efforts are underway worldwide to increase wheat production by extending genetic diversity and analysing key traits, and genomic resources can accelerate progress. But so far the very large size and polyploid complexity of the bread wheat genome have been substantial barriers to genome analysis. Here we report the sequencing of its large, 17-gigabase-pair, hexaploid genome using 454 pyrosequencing, and comparison of this with the sequences of diploid ancestral and progenitor genomes. We identified between 94,000 and 96,000 genes, and assigned two-thirds to the three component genomes (A, B and D) of hexaploid wheat. High-resolution synteny maps identified many small disruptions to conserved gene order. We show that the hexaploid genome is highly dynamic, with significant loss of gene family members on polyploidization and domestication, and an abundance of gene fragments. Several classes of genes involved in energy harvesting, metabolism and growth are among expanded gene families that could be associated with crop productivity. Our analyses, coupled with the identification of extensive genetic variation, provide a resource for accelerating gene discovery and improving this major crop.

Genome-wide in situ exon capture for selective resequencing

Increasingly powerful sequencing technologies are ushering in an era of personal genome sequences and raising the possibility of using such information to guide medical decisions. Genome resequencing also promises to accelerate the identification of disease-associated mutations. Roughly 98% of the human genome is composed of repeats and intergenic or non–protein-coding sequences. Thus, it is crucial to focus resequencing on high-value genomic regions. Protein-coding exons represent one such type of high-value target. We have developed a method of using flexible, high-density microarrays to capture any desired fraction of the human genome, in this case corresponding to more than 200,000 protein-coding exons. Depending on the precise protocol, up to 55–85% of the captured fragments are associated with targeted regions and up to 98% of intended exons can be recovered. This methodology provides an adaptable route toward rapid and efficient resequencing of any sizeable, non-repeat portion of the human genome.

The genome of Theobroma cacao

We sequenced and assembled the draft genome of Theobroma cacao, an economically important tropical-fruit tree crop that is the source of chocolate. This assembly corresponds to 76% of the estimated genome size and contains almost all previously described genes, with 82% of these genes anchored on the 10 T. cacao chromosomes. Analysis of this sequence information highlighted specific expansion of some gene families during evolution, for example, flavonoid-related genes. It also provides a major source of candidate genes for T. cacao improvement. Based on the inferred paleohistory of the T. cacao genome, we propose an evolutionary scenario whereby the ten T. cacao chromosomes were shaped from an ancestor through eleven chromosome fusions.

De novo Mutations in Schizophrenia Implicate Chromatin Remodeling and Support a Genetic Overlap with Autism and Intellectual Disability

Schizophrenia is a serious psychiatric disorder with a broadly undiscovered genetic etiology. Recent studies of de novo mutations (DNMs) in schizophrenia and autism have reinforced the hypothesis that rare genetic variation contributes to risk. We carried out exome sequencing on 57 trios with sporadic or familial schizophrenia. In sporadic trios, we observed a ~3.5-fold increase in the proportion of nonsense DNMs (0.101 vs 0.031, empirical P=0.01, Benjamini–Hochberg-corrected P=0.044). These mutations were significantly more likely to occur in genes with highly ranked probabilities of haploinsufficiency (P=0.0029, corrected P=0.006). DNMs of potential functional consequence were also found to occur in genes predicted to be less tolerant to rare variation (P=2.01 × 10−5, corrected P=2.1 × 10−3). Genes with DNMs overlapped with genes implicated in autism (for example, AUTS2, CHD8 and MECP2) and intellectual disability (for example, HUWE1 and TRAPPC9), supporting a shared genetic etiology between these disorders. Functionally CHD8, MECP2 and HUWE1 converge on epigenetic regulation of transcription suggesting that this may be an important risk mechanism. Our results were consistent in an analysis of additional exome-based sequencing studies of other neurodevelopmental disorders. These findings suggest that perturbations in genes, which function in the epigenetic regulation of brain development and cognition, could have a central role in the susceptibility to, pathogenesis and treatment of mental disorders.

A 4-gigabase physical map unlocks the structure and evolution of the complex genome of Aegilops tauschii, the wheat D-genome progenitor

The current limitations in genome sequencing technology require the construction of physical maps for high-quality draft sequences of large plant genomes, such as that of Aegilops tauschii, the wheat D-genome progenitor. To construct a physical map of the Ae. tauschii genome, we fingerprinted 461,706 bacterial artificial chromosome clones, assembled contigs, designed a 10K Ae. tauschii Infinium SNP array, constructed a 7,185-marker genetic map, and anchored on the map contigs totaling 4.03 Gb. Using whole genome shotgun reads, we extended the SNP marker sequences and found 17,093 genes and gene fragments. We showed that collinearity of the Ae. tauschii genes with Brachypodium distachyon, rice, and sorghum decreased with phylogenetic distance and that structural genome evolution rates have been high across all investigated lineages in subfamily Pooideae, including that of Brachypodieae. We obtained additional information about the evolution of the seven Triticeae chromosomes from 12 ancestral chromosomes and uncovered a pattern of centromere inactivation accompanying nested chromosome insertions in grasses. We showed that the density of noncollinear genes along the Ae. tauschii chromosomes positively correlates with recombination rates, suggested a cause, and showed that new genes, exemplified by disease resistance genes, are preferentially located in high-recombination chromosome regions.

The sequence of rice chromosomes 11 and 12, rich in disease resistance genes and recent gene duplications

Rice is an important staple food and, with the smallest cereal genome, serves as a reference species for studies on the evolution of cereals and other grasses. Therefore, decoding its entire genome will be a prerequisite for applied and basic research on this species and all other cereals. We have determined and analyzed the complete sequences of two of its chromosomes, 11 and 12, which total 55.9 Mb (14.3% of the entire genome length), based on a set of overlapping clones. A total of 5,993 non-transposable element related genes are present on these chromosomes. Among them are 289 disease resistance-like and 28 defense-response genes, a higher proportion of these categories than on any other rice chromosome. A three-Mb segment on both chromosomes resulted from a duplication 7.7 million years ago (mya), the most recent large-scale duplication in the rice genome. Paralogous gene copies within this segmental duplication can be aligned with genomic assemblies from sorghum and maize. Although these gene copies are preserved on both chromosomes, their expression patterns have diverged. When the gene order of rice chromosomes 11 and 12 was compared to wheat gene loci, significant synteny between these orthologous regions was detected, illustrating the presence of conserved genes alternating with recently evolved genes. Because the resistance and defense response genes, enriched on these chromosomes relative to the whole genome, also occur in clusters, they provide a preferred target for breeding durable disease resistance in rice and the isolation of their allelic variants. The recent duplication of a large chromosomal segment coupled with the high density of disease resistance gene clusters makes this the most recently evolved part of the rice genome. Based on syntenic alignments of these chromosomes, rice chromosome 11 and 12 do not appear to have resulted from a single whole-genome duplication event as previously suggested.BackgroundRice is an important staple food and, with the smallest cereal genome, serves as a reference species for studies on the evolution of cereals and other grasses. Therefore, decoding its entire genome will be a prerequisite for applied and basic research on this species and all other cereals.ResultsWe have determined and analyzed the complete sequences of two of its chromosomes, 11 and 12, which total 55.9 Mb (14.3% of the entire genome length), based on a set of overlapping clones. A total of 5,993 non-transposable element related genes are present on these chromosomes. Among them are 289 disease resistance-like and 28 defense-response genes, a higher proportion of these categories than on any other rice chromosome. A three-Mb segment on both chromosomes resulted from a duplication 7.7 million years ago (mya), the most recent large-scale duplication in the rice genome. Paralogous gene copies within this segmental duplication can be aligned with genomic assemblies from sorghum and maize. Although these gene copies are preserved on both chromosomes, their expression patterns have diverged. When the gene order of rice chromosomes 11 and 12 was compared to wheat gene loci, significant synteny between these orthologous regions was detected, illustrating the presence of conserved genes alternating with recently evolved genes.ConclusionBecause the resistance and defense response genes, enriched on these chromosomes relative to the whole genome, also occur in clusters, they provide a preferred target for breeding durable disease resistance in rice and the isolation of their allelic variants. The recent duplication of a large chromosomal segment coupled with the high density of disease resistance gene clusters makes this the most recently evolved part of the rice genome. Based on syntenic alignments of these chromosomes, rice chromosome 11 and 12 do not appear to have resulted from a single whole-genome duplication event as previously suggested.

Whole genome de novo assemblies of three divergent strains of rice, Oryza sativa, document novel gene space of aus and indica

BackgroundThe use of high throughput genome-sequencing technologies has uncovered a large extent of structural variation in eukaryotic genomes that makes important contributions to genomic diversity and phenotypic variation. When the genomes of different strains of a given organism are compared, whole genome resequencing data are typically aligned to an established reference sequence. However, when the reference differs in significant structural ways from the individuals under study, the analysis is often incomplete or inaccurate.ResultsHere, we use rice as a model to demonstrate how improvements in sequencing and assembly technology allow rapid and inexpensive de novo assembly of next generation sequence data into high-quality assemblies that can be directly compared using whole genome alignment to provide an unbiased assessment. Using this approach, we are able to accurately assess the ‘pan-genome’ of three divergent rice varieties and document several megabases of each genome absent in the other two.ConclusionsMany of the genome-specific loci are annotated to contain genes, reflecting the potential for new biological properties that would be missed by standard reference-mapping approaches. We further provide a detailed analysis of several loci associated with agriculturally important traits, including the S5 hybrid sterility locus, the Sub1 submergence tolerance locus, the LRK gene cluster associated with improved yield, and the Pup1 cluster associated with phosphorus deficiency, illustrating the utility of our approach for biological discovery. All of the data and software are openly available to support further breeding and functional studies of rice and other species.

A comparative analysis of exome capture

BackgroundHuman exome resequencing using commercial target capture kits has been and is being used for sequencing large numbers of individuals to search for variants associated with various human diseases. We rigorously evaluated the capabilities of two solution exome capture kits. These analyses help clarify the strengths and limitations of those data as well as systematically identify variables that should be considered in the use of those data.ResultsEach exome kit performed well at capturing the targets they were designed to capture, which mainly corresponds to the consensus coding sequences (CCDS) annotations of the human genome. In addition, based on their respective targets, each capture kit coupled with high coverage Illumina sequencing produced highly accurate nucleotide calls. However, other databases, such as the Reference Sequence collection (RefSeq), define the exome more broadly, and so not surprisingly, the exome kits did not capture these additional regions.ConclusionsCommercial exome capture kits provide a very efficient way to sequence select areas of the genome at very high accuracy. Here we provide the data to help guide critical analyses of sequencing data derived from these products.

Whole Genome Sequencing Defines the Genetic Heterogeneity of Familial Pancreatic Cancer

UNLABELLED Pancreatic cancer is projected to become the second leading cause of cancer-related death in the United States by 2020. A familial aggregation of pancreatic cancer has been established, but the cause of this aggregation in most families is unknown. To determine the genetic basis of susceptibility in these families, we sequenced the germline genomes of 638 patients with familial pancreatic cancer and the tumor exomes of 39 familial pancreatic adenocarcinomas. Our analyses support the role of previously identified familial pancreatic cancer susceptibility genes such as BRCA2, CDKN2A, and ATM, and identify novel candidate genes harboring rare, deleterious germline variants for further characterization. We also show how somatic point mutations that occur during hematopoiesis can affect the interpretation of genome-wide studies of hereditary traits. Our observations have important implications for the etiology of pancreatic cancer and for the identification of susceptibility genes in other common cancer types. SIGNIFICANCE The genetic basis of disease susceptibility in the majority of patients with familial pancreatic cancer is unknown. We whole genome sequenced 638 patients with familial pancreatic cancer and demonstrate that the genetic underpinning of inherited pancreatic cancer is highly heterogeneous. This has significant implications for the management of patients with familial pancreatic cancer.

Validation and assessment of variant calling pipelines for next-generation sequencing

BackgroundThe processing and analysis of the large scale data generated by next-generation sequencing (NGS) experiments is challenging and is a burgeoning area of new methods development. Several new bioinformatics tools have been developed for calling sequence variants from NGS data. Here, we validate the variant calling of these tools and compare their relative accuracy to determine which data processing pipeline is optimal.ResultsWe developed a unified pipeline for processing NGS data that encompasses four modules: mapping, filtering, realignment and recalibration, and variant calling. We processed 130 subjects from an ongoing whole exome sequencing study through this pipeline. To evaluate the accuracy of each module, we conducted a series of comparisons between the single nucleotide variant (SNV) calls from the NGS data and either gold-standard Sanger sequencing on a total of 700 variants or array genotyping data on a total of 9,935 single-nucleotide polymorphisms. A head to head comparison showed that Genome Analysis Toolkit (GATK) provided more accurate calls than SAMtools (positive predictive value of 92.55% vs. 80.35%, respectively). Realignment of mapped reads and recalibration of base quality scores before SNV calling proved to be crucial to accurate variant calling. GATK HaplotypeCaller algorithm for variant calling outperformed the UnifiedGenotype algorithm. We also showed a relationship between mapping quality, read depth and allele balance, and SNV call accuracy. However, if best practices are used in data processing, then additional filtering based on these metrics provides little gains and accuracies of >99% are achievable.ConclusionsOur findings will help to determine the best approach for processing NGS data to confidently call variants for downstream analyses. To enable others to implement and replicate our results, all of our codes are freely available at http://metamoodics.org/wes.