Deep learning predicts all-cause mortality from longitudinal total-body DXA imaging.

Background: Mortality research has identified biomarkers predictive of all-cause mortality risk. Most of these markers, such as body mass index, are predictive cross-sectionally, while for others the longitudinal change has been shown to be predictive, for instance greater-than-average muscle and weight loss in older adults. And while sometimes markers are derived from imaging modalities such as DXA, full scans are rarely used. This study builds on that knowledge and tests two hypotheses to improve all-cause mortality prediction. The first hypothesis is that features derived from raw total-body DXA imaging using deep learning are predictive of all-cause mortality with and without clinical risk factors, meanwhile, the second hypothesis states that sequential total-body DXA scans and recurrent neural network models outperform comparable models using only one observation with and without clinical risk factors. Methods: Multiple deep neural network architectures were designed to test theses hypotheses. The models were trained and evaluated on data from the 16-year-long Health, Aging, and Body Composition Study including over 15,000 scans from over 3000 older, multi-race male and female adults. This study further used explainable AI techniques to interpret the predictions and evaluate the contribution of different inputs. Results: The results demonstrate that longitudinal total-body DXA scans are predictive of all-cause mortality and improve performance of traditional mortality prediction models. On a held-out test set, the strongest model achieves an area under the receiver operator characteristic curve of 0.79. Conclusion: This study demonstrates the efficacy of deep learning for the analysis of DXA medical imaging in a cross-sectional and longitudinal setting. By analyzing the trained deep learning models, this work also sheds light on what constitutes healthy aging in a diverse cohort.

Technical note: Low clinical efficacy, but good acceptability of a point-of-care electronic palpation device for breast cancer screening for a lower middle-income environment.

BACKGROUND: Late-stage breast cancer rates in the Pacific where mammography services are limited are exceedingly high: Marshall Islands (61%), Palau (94%), and Samoa (79%). Due to the limited medical resources in these areas an alternative accessible technology is needed. The iBreast Exam (iBE) is a point-of-care electronic palpitation device that has a reported sensitivity of 86%. However, little is known about the performance and acceptability of this device for women in the Pacific. METHODS: A total of 39 women (ages 42-73 years) were recruited in Guam with 19 women having a mammogram requiring biopsy (Breast Imaging-Reporting and Data System [BI-RADS] category 4 or above) and 20 women with a negative screening mammogram before the study visit. Participants received an iBE exam and completed a 26-item breast health questionnaire to evaluate the iBE. Furthermore, the performance characteristics of the iBE were tested using gelatin breast phantoms in terms of tumor size, tumor depth, and overall breast stiffness. RESULTS: The iBE had a sensitivity of 20% (two true positives to eight false negatives) and specificity of 92% (24 false positives to 278 true negatives) when analyzed based on the location of the tumor by quadrant. The iBE also had generally poor agreement according to a Cohen's kappa value of 0.068. The phantom experiments showed that the iBE can detect tumors as deep as 2.5 cm, but only if the lesion is greater than 8 mm in diameter. However, the iBE did demonstrate acceptability; 67% of the women reported that they had high trust in iBE as an early detection device. CONCLUSIONS: The iBE had generally poor sensitivity and specificity when tested in a clinical setting which does not allow its use as a screening tool. IMPACT: This study demonstrates the need for an alternative screening method other than electronic palpation for lower-middle-income areas.

Diameter Changes in Traumatic Aortic Injury: Implications for Stent-Graft Sizing.

OBJECTIVES: The aim of this study was to compare aortic diameters from admission computed tomography angiography (CTA) scans to postoperative aortic diameters in patients with traumatic aortic injury (TAI) and evaluate the influence of substantial blood loss on aortic diameter. METHODS: The aortic databases of two tertiary university centers were retrospectively screened for patients with TAI between February 2002 and February 2019. Concomitant organ injuries, bone fractures, blood loss, and clinical outcomes were evaluated. Aortic diameters were measured in CTA upon admission and were compared with the CTA before discharge at three different aortic levels (mid-ascending, 5 cm distal to the end of the stent graft, and at the celiac trunk level). RESULTS: We identified 45 patients, aged 43 (first quartile; third quartile [26; 55]) years with a TAI treated by thoracic endovascular aortic repair. The most frequent cause of TAI was a car accident (n = 24). Concomitant injuries were seen in all but one patient. Bone and pelvic fractures were seen in 40 (89%) and 15 (33%) patients, respectively. Type III aortic injury was present in 25 patients (56%). Increase of aortic diameter after stabilization was +1.7 mm (-0.6 mm; 2.5 mm; p = 0.004) at the mid-ascending aorta, +2.1 mm (0.2 mm; 3.8 mm; p < 0.001) 5 cm distal to the stent graft, and +1.5 mm (0.5 mm; 3.2 mm; p < 0.001) at the celiac trunk level. CONCLUSION: In patients with TAI, the aortic diameter is significantly reduced as compared with the aortic diameter at discharge. The reduction of aortic diameter might be caused by hemorrhagic shock and should be kept in mind for appropriate stent-graft sizing.

Deep Learning Predicts Interval and Screening-detected Cancer from Screening Mammograms: A Case-Case-Control Study in 6369 Women.

Background The ability of deep learning (DL) models to classify women as at risk for either screening mammography-detected or interval cancer (not detected at mammography) has not yet been explored in the literature. Purpose To examine the ability of DL models to estimate the risk of interval and screening-detected breast cancers with and without clinical risk factors. Materials and Methods This study was performed on 25 096 digital screening mammograms obtained from January 2006 to December 2013. The mammograms were obtained in 6369 women without breast cancer, 1609 of whom developed screening-detected breast cancer and 351 of whom developed interval invasive breast cancer. A DL model was trained on the negative mammograms to classify women into those who did not develop cancer and those who developed screening-detected cancer or interval invasive cancer. Model effectiveness was evaluated as a matched concordance statistic (C statistic) in a held-out 26% (1669 of 6369) test set of the mammograms. Results The C statistics and odds ratios for comparing patients with screening-detected cancer versus matched controls were 0.66 (95% CI: 0.63, 0.69) and 1.25 (95% CI: 1.17, 1.33), respectively, for the DL model, 0.62 (95% CI: 0.59, 0.65) and 2.14 (95% CI: 1.32, 3.45) for the clinical risk factors with the Breast Imaging Reporting and Data System (BI-RADS) density model, and 0.66 (95% CI: 0.63, 0.69) and 1.21 (95% CI: 1.13, 1.30) for the combined DL and clinical risk factors model. For comparing patients with interval cancer versus controls, the C statistics and odds ratios were 0.64 (95% CI: 0.58, 0.71) and 1.26 (95% CI: 1.10, 1.45), respectively, for the DL model, 0.71 (95% CI: 0.65, 0.77) and 7.25 (95% CI: 2.94, 17.9) for the risk factors with BI-RADS density (b rated vs non-b rated) model, and 0.72 (95% CI: 0.66, 0.78) and 1.10 (95% CI: 0.94, 1.29) for the combined DL and clinical risk factors model. The P values between the DL, BI-RADS, and combined model's ability to detect screen and interval cancer were .99, .002, and .03, respectively. Conclusion The deep learning model outperformed in determining screening-detected cancer risk but underperformed for interval cancer risk when compared with clinical risk factors including breast density. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Bae and Kim in this issue.

Placentas delivered by pre-pregnant obese women have reduced abundance and diversity in the microbiome.

Maternal pre-pregnancy obesity may have an impact on both maternal and fetal health. We examined the microbiome recovered from placentas in a multi-ethnic maternal pre-pregnant obesity cohort, through an optimized microbiome protocol to enrich low bacterial biomass samples. We found that the microbiomes recovered from the placentas of obese pre-pregnant mothers are less abundant and less diverse when compared to those from mothers of normal pre-pregnancy weight. Microbiome richness also decreases from the maternal side to the fetal side, demonstrating heterogeneity by geolocation within the placenta. In summary, our study shows that the microbiomes recovered from the placentas are associated with pre-pregnancy obesity. IMPORTANCE: Maternal pre-pregnancy obesity may have an impact on both maternal and fetal health. The placenta is an important organ at the interface of the mother and fetus, and supplies nutrients to the fetus. We report that the microbiomes enriched from the placentas of obese pre-pregnant mothers are less abundant and less diverse when compared to those from mothers of normal pre-pregnancy weight. More over, the microbiomes also vary by geolocation within the placenta.

Endovascular repair of ascending aortic diseases with custom-made endografts.

OBJECTIVES: The aim of this article is to report the mid-term results of ascending thoracic endovascular aortic repair using a custom-made device (CMD). METHODS: This was a retrospective study performed at tertiary centres. Nine patients considered unfit for open surgery received elective total endovascular repair of the ascending aorta with a Relay® (Terumo Aortic, Sunrise; FL, USA) CMD: pseudoaneurysn (n = 5), localized dissection (n =3) and contained rupture (n = 1). RESULTS: Primary clinical success was achieved in all patients with no major complications and no early conversion to open surgery. All patients were discharged home and independent: median length of stay was 7 days (interquartile range, 6-18). No patient was lost to follow-up at a median 26 months (interquartile range, 12-36). Three patients died 2, 6 and 24 months after intervention; 1 was aorta related (late aorto-atrial fistula due to infection that required open surgery). At the last follow-up available, no endoleaks, migrations, fractures or ruptures were observed in the remaining 6 patients. CONCLUSIONS: Ascending thoracic endovascular aortic repair with Terumo Aortic CMDs was technically feasible, effective and safe in very selected lesions. CMDs showed good ascending aorta conformability with different configurations and diameters, and satisfactory mid-term durability as shown by both structural integrity and aortic lesion exclusion.

Dual-energy three-compartment breast imaging for compositional biomarkers to improve detection of malignant lesions.

Background: While breast imaging such as full-field digital mammography and digital breast tomosynthesis have helped to reduced breast cancer mortality, issues with low specificity exist resulting in unnecessary biopsies. The fundamental information used in diagnostic decisions are primarily based in lesion morphology. We explore a dual-energy compositional breast imaging technique known as three-compartment breast (3CB) to show how the addition of compositional information improves malignancy detection. Methods: Women who presented with Breast Imaging-Reporting and Data System (BI-RADS) diagnostic categories 4 or 5 and who were scheduled for breast biopsies were consecutively recruited for both standard mammography and 3CB imaging. Computer-aided detection (CAD) software was used to assign a morphology-based prediction of malignancy for all biopsied lesions. Compositional signatures for all lesions were calculated using 3CB imaging and a neural network evaluated CAD predictions with composition to predict a new probability of malignancy. CAD and neural network predictions were compared to the biopsy pathology. Results: The addition of 3CB compositional information to CAD improves malignancy predictions resulting in an area under the receiver operating characteristic curve (AUC) of 0.81 (confidence interval (CI) of 0.74-0.88) on a held-out test set, while CAD software alone achieves an AUC of 0.69 (CI 0.60-0.78). We also identify that invasive breast cancers have a unique compositional signature characterized by reduced lipid content and increased water and protein content when compared to surrounding tissues. Conclusion: Clinically, 3CB may potentially provide increased accuracy in predicting malignancy and a feasible avenue to explore compositional breast imaging biomarkers.

GranatumX: A Community-engaging, Modularized, and Flexible Webtool for Single-cell Data Analysis.

We present GranatumX, a next-generation software environment for single-cell RNA sequencing (scRNA-seq) data analysis. GranatumX is inspired by the interactive webtool Granatum. GranatumX enables biologists to access the latest scRNA-seq bioinformatics methods in a web-based graphical environment. It also offers software developers the opportunity to rapidly promote their own tools with others in customizable pipelines. The architecture of GranatumX allows for easy inclusion of plugin modules, named Gboxes, which wrap around bioinformatics tools written in various programming languages and on various platforms. GranatumX can be run on the cloud or private servers and generate reproducible results. It is a community-engaging, flexible, and evolving software ecosystem for scRNA-seq analysis, connecting developers with bench scientists. GranatumX is freely accessible at http://garmiregroup.org/granatumx/app.

Taro Genome Assembly and Linkage Map Reveal QTLs for Resistance to Taro Leaf Blight.

Taro (Colocasia esculenta) is a food staple widely cultivated in the humid tropics of Asia, Africa, Pacific and the Caribbean. One of the greatest threats to taro production is Taro Leaf Blight caused by the oomycete pathogen Phytophthora colocasiae Here we describe a de novo taro genome assembly and use it to analyze sequence data from a Taro Leaf Blight resistant mapping population. The genome was assembled from linked-read sequences (10x Genomics; ∼60x coverage) and gap-filled and scaffolded with contigs assembled from Oxford Nanopore Technology long-reads and linkage map results. The haploid assembly was 2.45 Gb total, with a maximum contig length of 38 Mb and scaffold N50 of 317,420 bp. A comparison of family-level (Araceae) genome features reveals the repeat content of taro to be 82%, >3.5x greater than in great duckweed (Spirodela polyrhiza), 23%. Both genomes recovered a similar percent of Benchmarking Universal Single-copy Orthologs, 80% and 84%, based on a 3,236 gene database for monocot plants. A greater number of nucleotide-binding leucine-rich repeat disease resistance genes were present in genomes of taro than the duckweed, ∼391 vs. ∼70 (∼182 and ∼46 complete). The mapping population data revealed 16 major linkage groups with 520 markers, and 10 quantitative trait loci (QTL) significantly associated with Taro Leaf Blight disease resistance. The genome sequence of taro enhances our understanding of resistance to TLB, and provides markers that may accelerate breeding programs. This genome project may provide a template for developing genomic resources in other understudied plant species.

Phylogenetic Relationships, Breeding Implications, and Cultivation History of Hawaiian Taro (Colocasia Esculenta) Through Genome-Wide SNP Genotyping.

Taro, Colocasia esculenta, is one of the world's oldest root crops and is of particular economic and cultural significance in Hawai'i, where historically more than 150 different landraces were grown. We developed a genome-wide set of more than 2400 high-quality single nucleotide polymorphism (SNP) markers from 70 taro accessions of Hawaiian, South Pacific, Palauan, and mainland Asian origins, with several objectives: 1) uncover the phylogenetic relationships between Hawaiian and other Pacific landraces, 2) shed light on the history of taro cultivation in Hawai'i, and 3) develop a tool to discriminate among Hawaiian and other taros. We found that almost all existing Hawaiian landraces fall into 5 monophyletic groups that are largely consistent with the traditional Hawaiian classification based on morphological characters, for example, leaf shape and petiole color. Genetic diversity was low within these clades but considerably higher between them. Population structure analyses further indicated that the diversification of taro in Hawai'i most likely occurred by a combination of frequent somatic mutation and occasional hybridization. Unexpectedly, the South Pacific accessions were found nested within the clades mainly composed of Hawaiian accessions, rather than paraphyletic to them. This suggests that the origin of clades identified here preceded the colonization of Hawai'i and that early Polynesian settlers brought taro landraces from different clades with them. In the absence of a sequenced genome, this marker set provides a valuable resource towards obtaining a genetic linkage map and to study the genetic basis of phenotypic traits of interest to taro breeding such as disease resistance.

Granatum: a graphical single-cell RNA-Seq analysis pipeline for genomics scientists.

BACKGROUND: Single-cell RNA sequencing (scRNA-Seq) is an increasingly popular platform to study heterogeneity at the single-cell level. Computational methods to process scRNA-Seq data are not very accessible to bench scientists as they require a significant amount of bioinformatic skills. RESULTS: We have developed Granatum, a web-based scRNA-Seq analysis pipeline to make analysis more broadly accessible to researchers. Without a single line of programming code, users can click through the pipeline, setting parameters and visualizing results via the interactive graphical interface. Granatum conveniently walks users through various steps of scRNA-Seq analysis. It has a comprehensive list of modules, including plate merging and batch-effect removal, outlier-sample removal, gene-expression normalization, imputation, gene filtering, cell clustering, differential gene expression analysis, pathway/ontology enrichment analysis, protein network interaction visualization, and pseudo-time cell series construction. CONCLUSIONS: Granatum enables broad adoption of scRNA-Seq technology by empowering bench scientists with an easy-to-use graphical interface for scRNA-Seq data analysis. The package is freely available for research use at http://garmiregroup.org/granatum/app.

Using single-cell multiple omics approaches to resolve tumor heterogeneity.

It has become increasingly clear that both normal and cancer tissues are composed of heterogeneous populations. Genetic variation can be attributed to the downstream effects of inherited mutations, environmental factors, or inaccurately resolved errors in transcription and replication. When lesions occur in regions that confer a proliferative advantage, it can support clonal expansion, subclonal variation, and neoplastic progression. In this manner, the complex heterogeneous microenvironment of a tumour promotes the likelihood of angiogenesis and metastasis. Recent advances in next-generation sequencing and computational biology have utilized single-cell applications to build deep profiles of individual cells that are otherwise masked in bulk profiling. In addition, the development of new techniques for combining single-cell multi-omic strategies is providing a more precise understanding of factors contributing to cellular identity, function, and growth. Continuing advancements in single-cell technology and computational deconvolution of data will be critical for reconstructing patient specific intra-tumour features and developing more personalized cancer treatments.

Improved maize reference genome with single-molecule technologies.

Complete and accurate reference genomes and annotations provide fundamental tools for characterization of genetic and functional variation. These resources facilitate the determination of biological processes and support translation of research findings into improved and sustainable agricultural technologies. Many reference genomes for crop plants have been generated over the past decade, but these genomes are often fragmented and missing complex repeat regions. Here we report the assembly and annotation of a reference genome of maize, a genetic and agricultural model species, using single-molecule real-time sequencing and high-resolution optical mapping. Relative to the previous reference genome, our assembly features a 52-fold increase in contig length and notable improvements in the assembly of intergenic spaces and centromeres. Characterization of the repetitive portion of the genome revealed more than 130,000 intact transposable elements, allowing us to identify transposable element lineage expansions that are unique to maize. Gene annotations were updated using 111,000 full-length transcripts obtained by single-molecule real-time sequencing. In addition, comparative optical mapping of two other inbred maize lines revealed a prevalence of deletions in regions of low gene density and maize lineage-specific genes.

High Quality Maize Centromere 10 Sequence Reveals Evidence of Frequent Recombination Events.

The ancestral centromeres of maize contain long stretches of the tandemly arranged CentC repeat. The abundance of tandem DNA repeats and centromeric retrotransposons (CR) has presented a significant challenge to completely assembling centromeres using traditional sequencing methods. Here, we report a nearly complete assembly of the 1.85 Mb maize centromere 10 from inbred B73 using PacBio technology and BACs from the reference genome project. The error rates estimated from overlapping BAC sequences are 7 × 10(-6) and 5 × 10(-5) for mismatches and indels, respectively. The number of gaps in the region covered by the reassembly was reduced from 140 in the reference genome to three. Three expressed genes are located between 92 and 477 kb from the inferred ancestral CentC cluster, which lies within the region of highest centromeric repeat density. The improved assembly increased the count of full-length CR from 5 to 55 and revealed a 22.7 kb segmental duplication that occurred approximately 121,000 years ago. Our analysis provides evidence of frequent recombination events in the form of partial retrotransposons, deletions within retrotransposons, chimeric retrotransposons, segmental duplications including higher order CentC repeats, a deleted CentC monomer, centromere-proximal inversions, and insertion of mitochondrial sequences. Double-strand DNA break (DSB) repair is the most plausible mechanism for these events and may be the major driver of centromere repeat evolution and diversity. In many cases examined here, DSB repair appears to be mediated by microhomology, suggesting that tandem repeats may have evolved to efficiently repair frequent DSBs in centromeres.

Inbreeding drives maize centromere evolution.

Functional centromeres, the chromosomal sites of spindle attachment during cell division, are marked epigenetically by the centromere-specific histone H3 variant cenH3 and typically contain long stretches of centromere-specific tandem DNA repeats (∼1.8 Mb in maize). In 23 inbreds of domesticated maize chosen to represent the genetic diversity of maize germplasm, partial or nearly complete loss of the tandem DNA repeat CentC precedes 57 independent cenH3 relocation events that result in neocentromere formation. Chromosomal regions with newly acquired cenH3 are colonized by the centromere-specific retrotransposon CR2 at a rate that would result in centromere-sized CR2 clusters in 20,000-95,000 y. Three lines of evidence indicate that CentC loss is linked to inbreeding, including (i) CEN10 of temperate lineages, presumed to have experienced a genetic bottleneck, contain less CentC than their tropical relatives; (ii) strong selection for centromere-linked genes in domesticated maize reduced diversity at seven of the ten maize centromeres to only one or two postdomestication haplotypes; and (iii) the centromere with the largest number of haplotypes in domesticated maize (CEN7) has the highest CentC levels in nearly all domesticated lines. Rare recombinations introduced one (CEN2) or more (CEN5) alternate CEN haplotypes while retaining a single haplotype at domestication loci linked to these centromeres. Taken together, this evidence strongly suggests that inbreeding, favored by postdomestication selection for centromere-linked genes affecting key domestication or agricultural traits, drives replacement of the tandem centromere repeats in maize and other crop plants. Similar forces may act during speciation in natural systems.

Tandem repeats derived from centromeric retrotransposons.

BACKGROUND: Tandem repeats are ubiquitous and abundant in higher eukaryotic genomes and constitute, along with transposable elements, much of DNA underlying centromeres and other heterochromatic domains. In maize, centromeric satellite repeat (CentC) and centromeric retrotransposons (CR), a class of Ty3/gypsy retrotransposons, are enriched at centromeres. Some satellite repeats have homology to retrotransposons and several mechanisms have been proposed to explain the expansion, contraction as well as homogenization of tandem repeats. However, the origin and evolution of tandem repeat loci remain largely unknown. RESULTS: CRM1TR and CRM4TR are novel tandem repeats that we show to be entirely derived from CR elements belonging to two different subfamilies, CRM1 and CRM4. Although these tandem repeats clearly originated in at least two separate events, they are derived from similar regions of their respective parent element, namely the long terminal repeat (LTR) and untranslated region (UTR). The 5' ends of the monomer repeat units of CRM1TR and CRM4TR map to different locations within their respective LTRs, while their 3' ends map to the same relative position within a conserved region of their UTRs. Based on the insertion times of heterologous retrotransposons that have inserted into these tandem repeats, amplification of the repeats is estimated to have begun at least ~4 (CRM1TR) and ~1 (CRM4TR) million years ago. Distinct CRM1TR sequence variants occupy the two CRM1TR loci, indicating that there is little or no movement of repeats between loci, even though they are separated by only ~1.4 Mb. CONCLUSIONS: The discovery of two novel retrotransposon derived tandem repeats supports the conclusions from earlier studies that retrotransposons can give rise to tandem repeats in eukaryotic genomes. Analysis of monomers from two different CRM1TR loci shows that gene conversion is the major cause of sequence variation. We propose that successive intrastrand deletions generated the initial repeat structure, and gene conversions increased the size of each tandem repeat locus.

The Hawaiian Freshwater Algal Database (HfwADB): a laboratory LIMS and online biodiversity resource.

BACKGROUND: Biodiversity databases serve the important role of highlighting species-level diversity from defined geographical regions. Databases that are specially designed to accommodate the types of data gathered during regional surveys are valuable in allowing full data access and display to researchers not directly involved with the project, while serving as a Laboratory Information Management System (LIMS). The Hawaiian Freshwater Algal Database, or HfwADB, was modified from the Hawaiian Algal Database to showcase non-marine algal specimens collected from the Hawaiian Archipelago by accommodating the additional level of organization required for samples including multiple species. DESCRIPTION: The Hawaiian Freshwater Algal Database is a comprehensive and searchable database containing photographs and micrographs of samples and collection sites, geo-referenced collecting information, taxonomic data and standardized DNA sequence data. All data for individual samples are linked through unique 10-digit accession numbers ("Isolate Accession"), the first five of which correspond to the collection site ("Environmental Accession"). Users can search online for sample information by accession number, various levels of taxonomy, habitat or collection site. HfwADB is hosted at the University of Hawaii, and was made publicly accessible in October 2011. At the present time the database houses data for over 2,825 samples of non-marine algae from 1,786 collection sites from the Hawaiian Archipelago. These samples include cyanobacteria, red and green algae and diatoms, as well as lesser representation from some other algal lineages. CONCLUSIONS: HfwADB is a digital repository that acts as a Laboratory Information Management System for Hawaiian non-marine algal data. Users can interact with the repository through the web to view relevant habitat data (including geo-referenced collection locations) and download images of collection sites, specimen photographs and micrographs, and DNA sequences. It is publicly available at http://algae.manoa.hawaii.edu/hfwadb/.

JunctionViewer: customizable annotation software for repeat-rich genomic regions.

BACKGROUND: Repeat-rich regions such as centromeres receive less attention than their gene-rich euchromatic counterparts because the former are difficult to assemble and analyze. Our objectives were to 1) map all ten centromeres onto the maize genetic map and 2) characterize the sequence features of maize centromeres, each of which spans several megabases of highly repetitive DNA. Repetitive sequences can be mapped using special molecular markers that are based on PCR with primers designed from two unique "repeat junctions". Efficient screening of large amounts of maize genome sequence data for repeat junctions, as well as key centromere sequence features required the development of specific annotation software. RESULTS: We developed JunctionViewer to automate the process of identifying and differentiating closely related centromere repeats and repeat junctions, and to generate graphical displays of these and other features within centromeric sequences. JunctionViewer generates NCBI BLAST, WU-BLAST, cross_match and MUMmer alignments, and displays the optimal alignments and additional annotation data as concise graphical representations that can be viewed directly through the graphical interface or as PostScript output.This software enabled us to quickly characterize millions of nucleotides of newly sequenced DNA ranging in size from single reads to assembled BACs and megabase-sized pseudochromosome regions. It expedited the process of generating repeat junction markers that were subsequently used to anchor all 10 centromeres to the maize map. It also enabled us to efficiently identify key features in large genomic regions, providing insight into the arrangement and evolution of maize centromeric DNA. CONCLUSIONS: JunctionViewer will be useful to scientists who wish to automatically generate concise graphical summaries of repeat sequences. It is particularly valuable for those needing to efficiently identify unique repeat junctions. The scalability and ability to customize homology search parameters for different classes of closely related repeat sequences make this software ideal for recurring annotation (e.g., genome projects that are in progress) of genomic regions that contain well-defined repeats, such as those in centromeres. Although originally customized for maize centromere sequence, we anticipate this software to facilitate the analysis of centromere and other repeat-rich regions in other organisms.

Maize centromere structure and evolution: sequence analysis of centromeres 2 and 5 reveals dynamic Loci shaped primarily by retrotransposons.

We describe a comprehensive and general approach for mapping centromeres and present a detailed characterization of two maize centromeres. Centromeres are difficult to map and analyze because they consist primarily of repetitive DNA sequences, which in maize are the tandem satellite repeat CentC and interspersed centromeric retrotransposons of maize (CRM). Centromeres are defined epigenetically by the centromeric histone H3 variant, CENH3. Using novel markers derived from centromere repeats, we have mapped all ten centromeres onto the physical and genetic maps of maize. We were able to completely traverse centromeres 2 and 5, confirm physical maps by fluorescence in situ hybridization (FISH), and delineate their functional regions by chromatin immunoprecipitation (ChIP) with anti-CENH3 antibody followed by pyrosequencing. These two centromeres differ substantially in size, apparent CENH3 density, and arrangement of centromeric repeats; and they are larger than the rice centromeres characterized to date. Furthermore, centromere 5 consists of two distinct CENH3 domains that are separated by several megabases. Succession of centromere repeat classes is evidenced by the fact that elements belonging to the recently active recombinant subgroups of CRM1 colonize the present day centromeres, while elements of the ancestral subgroups are also found in the flanking regions. Using abundant CRM and non-CRM retrotransposons that inserted in and near these two centromeres to create a historical record of centromere location, we show that maize centromeres are fluid genomic regions whose borders are heavily influenced by the interplay of retrotransposons and epigenetic marks. Furthermore, we propose that CRMs may be involved in removal of centromeric DNA (specifically CentC), invasion of centromeres by non-CRM retrotransposons, and local repositioning of the CENH3.

Precise centromere mapping using a combination of repeat junction markers and chromatin immunoprecipitation-polymerase chain reaction.

Centromeres are difficult to map even in species where genetic resolution is excellent. Here we show that junctions between repeats provide reliable single-copy markers for recombinant inbred mapping within centromeres and pericentromeric heterochromatin. Repeat junction mapping was combined with anti-CENH3-mediated ChIP to provide a definitive map position for maize centromere 8.