Genome content analysis yields new insights into the relationship between the human malaria parasite Plasmodium falciparum and its anopheline vectors.

BACKGROUND: The persistent and growing gap between the availability of sequenced genomes and the ability to assign functions to sequenced genes led us to explore ways to maximize the information content of automated annotation for studies of anopheline mosquitos. Specifically, we use genome content analysis of a large number of previously sequenced anopheline mosquitos to follow the loss and gain of protein families over the evolutionary history of this group. The importance of this endeavor lies in the potential for comparative genomic studies between Anopheles and closely related non-vector species to reveal ancestral genome content dynamics involved in vector competence. In addition, comparisons within Anopheles could identify genome content changes responsible for variation in the vectorial capacity of this family of important parasite vectors. RESULTS: The competence and capacity of P. falciparum vectors do not appear to be phylogenetically constrained within the Anophelinae. Instead, using ancestral reconstruction methods, we suggest that a previously unexamined component of vector biology, anopheline nucleotide metabolism, may contribute to the unique status of anophelines as P. falciparum vectors. While the fitness effects of nucleotide co-option by P. falciparum parasites on their anopheline hosts are not yet known, our results suggest that anopheline genome content may be responding to selection pressure from P. falciparum. Whether this response is defensive, in an attempt to redress improper nucleotide balance resulting from P. falciparum infection, or perhaps symbiotic, resulting from an as-yet-unknown mutualism between anophelines and P. falciparum, is an open question that deserves further study. CONCLUSIONS: Clearly, there is a wealth of functional information to be gained from detailed manual genome annotation, yet the rapid increase in the number of available sequences means that most researchers will not have the time or resources to manually annotate all the sequence data they generate. We believe that efforts to maximize the amount of information obtained from automated annotation can help address the functional annotation deficit that most evolutionary biologists now face, and here demonstrate the value of such an approach.

A whole genome gene content phylogenetic analysis of anopheline mosquitoes.

Construction of stringent gene content matrices was accomplished for 21 Anopheline mosquito species and strains and four outgroups species. The presence absence matrix using e-75 as a cutoff in single linkage clustering had over 17,000 ortholog groups. We used the gene content matrix to generate a phylogenetic hypothesis that is in general agreement with gene sequence based phylogenies. In addition to establishing a congruent gene content phylogeny we examined the consistency of three methods for analyzing presence absence data - unweighted parsimony, dollo parsimonly and maximum likelihood using a BINGAMMA model. An examination of the chromosomal location of the gains and losses in the presence absence matrix revealed a low frequency of gains and losses at centromeres and tips of chromosomes.

Insect genome content phylogeny and functional annotation of core insect genomes.

Twenty-one fully sequenced and well annotated insect genomes were examined for genome content in a phylogenetic context. Gene presence/absence matrices and phylogenetic trees were constructed using several phylogenetic criteria. The role of e-value on phylogenetic analysis and genome content characterization is examined using scaled e-value cutoffs and a single linkage clustering approach to orthology determination. Previous studies have focused on the role of gene loss in terminals in the insect tree of life. The present study examines several common ancestral nodes in the insect tree. We suggest that the common ancestors of major insect groups like Diptera, Hymenoptera, Hemiptera and Holometabola experience more gene gain than gene loss. This suggests that as major insect groups arose, their genomic repertoire expanded through gene duplication (segmental duplications), followed by contraction by gene loss in specific terminal lineages. In addition, we examine the functional significance of the loss and gain of genes in the divergence of some of the major insect groups.

Condensin dysfunction in human cells induces nonrandom chromosomal breaks in anaphase, with distinct patterns for both unique and repeated genomic regions.

Condensin complexes are essential for chromosome condensation and segregation in mitosis, while condensin dysfunction, among other pathways leading to chromosomal bridging in mitosis, may play a role in tumor genomic instability, including recently discovered chromotripsis. To characterize potential double-strand breaks specifically occurring in late anaphase, human chromosomes depleted of condensin were analyzed by γ-H2AX ChIP followed by high-throughput sequencing (ChIP-seq). In condensin-depleted cells, the nonrepeated parts of the genome were shown to contain distinct γ-H2AX enrichment zones 75% of which overlapped with known hemizygous deletions in cancers. Furthermore, some tandemly repeated DNA sequences, analyzed separately from the rest of the genome, showed significant γ-H2AX enrichment in condensin-depleted anaphases. The most commonly occurring targets of such enrichment included simple repeats, centromeric satellites, and rDNA. The two latter categories indicate that acrocentric human chromosomes are especially susceptible to breaks upon condensin deficiency. The genomic regions that are specifically destabilized upon condensin dysfunction may constitute a condensin-specific chromosome destabilization pattern.

E value cutoff and eukaryotic genome content phylogenetics.

Genome content analysis has been used as a source of phylogenetic information in large prokaryotic tree of life studies. Recently the sequencing of many eukaryotic genomes has allowed for the similar use of genome content analysis for these organisms too. In this communication we examine the utility of genome content analysis for recovering phylogenetic patterns in several eukaryotic groups. By constructing multiple matrices using different e value cutoffs we examine the dynamics of altering the e value cutoff on five eukaryotic genome data sets. Our analysis indicates that the e value cutoff that is used as a criterion in the construction of the genome content matrix is a critical factor in both the accuracy and information content of the analysis. Strikingly, genome content by itself is not a reliable or accurate source of characters for phylogenetic analysis of the taxa in the five data sets we analyzed. We discuss two problems--small genome attraction and genome duplications as being involved in the rather poor performance of genome content data in recovering eukaryotic phylogeny.

Random roots and lineage sorting.

Lineage sorting has been suggested as a major force in generating incongruent phylogenetic signal when multiple gene partitions are examined. The degree of lineage sorting can be estimated using the coalescent process and simulation studies have also pointed to a major role for incomplete lineage sorting as a factor in phylogenetic inference. Some recent empirical studies point to an extreme role for this phenomenon with up to 50-60% of all informative genes showing incongruence as a result of lineage sorting. Here, we examine seven large multi-partition genome level data sets over a large range of taxonomic representation. We took the approach of examining outgroup choice and its impact on tree topology, by swapping outgroups into analyses with successively larger genetics distances to the ingroup. Our results indicate a linear relationship of outgroup distance with incongruence in the data sets we examined suggesting a strong random rooting effect. In addition, we attempted to estimate the degree of lineage sorting in several large genome level data sets by examining triads of very closely related taxa. This exercise resulted in much lower estimates of incongruent genes that could be the result of lineage sorting, with an overall estimate of around 10% of the total number of genes in a genome showing incongruence as a result of true lineage sorting. Finally we examined the behavior of likelihood and parsimony approaches on the random rooting phenomenon. Likelihood tends to stabilize incongruence as outgroups get further and further away from the ingroup. In one extreme case, likelihood overcompensates for sequence divergence but increases random rooting causing long branch repulsion.

Novel multi-nucleotide polymorphisms in the human genome characterized by whole genome and exome sequencing.

Genomic sequence comparisons between individuals are usually restricted to the analysis of single nucleotide polymorphisms (SNPs). While the interrogation of SNPs is efficient, they are not the only form of divergence between genomes. In this report, we expand the scope of polymorphism detection by investigating the occurrence of double nucleotide polymorphisms (DNPs) and triple nucleotide polymorphisms (TNPs), in which two or three consecutive nucleotides are altered compared to the reference sequence. We have found such DNPs and TNPs throughout two complete genomes and eight exomes. Within exons, these novel polymorphisms are over-represented amongst protein-altering variants; nearly all DNPs and TNPs result in a change in amino acid sequence and, in some cases, two adjacent amino acids are changed. DNPs and TNPs represent a potentially important new source of genetic variation which may underlie human disease and they should be included in future medical genetics studies. As a confirmation of the damaging nature of xNPs, we have identified changes in the exome of a glioblastoma cell line that are important in glioblastoma pathogenesis. We have found a TNP causing a single amino acid change in LAMC2 and a TNP causing a truncation of HUWE1.

Massively parallel DNA target capture using long adapter single stranded oligonucleotide (LASSO) probes assembled through a novel DNA recombinase mediated methodology.

In the attempt to bridge the widening gap from DNA sequence to biological function, we developed a novel methodology to assemble Long-Adapter Single-Strand Oligonucleotide (LASSO) probe libraries that enabled the massively multiplexed capture of kilobase-sized DNA fragments for downstream long read DNA sequencing or expression. This method uses short DNA oligonucleotides (pre-LASSO probes) and a plasmid vector that supplies the linker sequence for the mature LASSO probe through Cre-LoxP intramolecular recombination. This strategy generates high quality LASSO probes libraries (≈46% of correct probes). We performed NGS analysis of the post-capture PCR amplification of DNA circles obtained from the LASSO capture of 3087 Escherichia coli ORFs spanning from 400- to 5000 bp. The median enrichment of all targeted ORFs versus untargeted ORFs was 30 times. For ORFs up to 1kb in size, targeted ORFs were enriched up to a median of 260-fold. Here, we show that LASSO probes obtained in this manner, were able to capture full-length open reading frames from total human cDNA. Furthermore, we show that the LASSO capture specificity and sensitivity is sufficient for target capture from total human genomic DNA template. This technology can be used for the preparation of long-read sequencing libraries and for massively multiplexed cloning of human sequences.

A complete reference genome improves analysis of human genetic variation.

Compared to its predecessors, the Telomere-to-Telomere CHM13 genome adds nearly 200 million base pairs of sequence, corrects thousands of structural errors, and unlocks the most complex regions of the human genome for clinical and functional study. We show how this reference universally improves read mapping and variant calling for 3202 and 17 globally diverse samples sequenced with short and long reads, respectively. We identify hundreds of thousands of variants per sample in previously unresolved regions, showcasing the promise of the T2T-CHM13 reference for evolutionary and biomedical discovery. Simultaneously, this reference eliminates tens of thousands of spurious variants per sample, including reduction of false positives in 269 medically relevant genes by up to a factor of 12. Because of these improvements in variant discovery coupled with population and functional genomic resources, T2T-CHM13 is positioned to replace GRCh38 as the prevailing reference for human genetics.

Benchmarking challenging small variants with linked and long reads.

Genome in a Bottle benchmarks are widely used to help validate clinical sequencing pipelines and develop variant calling and sequencing methods. Here we use accurate linked and long reads to expand benchmarks in 7 samples to include difficult-to-map regions and segmental duplications that are challenging for short reads. These benchmarks add more than 300,000 SNVs and 50,000 insertions or deletions (indels) and include 16% more exonic variants, many in challenging, clinically relevant genes not covered previously, such as PMS2. For HG002, we include 92% of the autosomal GRCh38 assembly while excluding regions problematic for benchmarking small variants, such as copy number variants, that should not have been in the previous version, which included 85% of GRCh38. It identifies eight times more false negatives in a short read variant call set relative to our previous benchmark. We demonstrate that this benchmark reliably identifies false positives and false negatives across technologies, enabling ongoing methods development.

The mega-matrix tree of life: using genome-scale horizontal gene transfer and sequence evolution data as information about the vertical history of life.

Because horizontal gene transfer can confound the recovery of the largely prokaryotic tree of life (ToL), most genome-based techniques seek to eliminate horizontal signal from ToL analyses, commonly by sieving out incongruent genes and data. This approach greatly limits the number of gene families analysed to a subset thought to be representative of vertical evolutionary history. However, formalized tests have not been performed to determine whether combining the massive amounts of information available in fully sequenced genomes can recover a reasonable ToL. Consequently, we used empirically defined gene homology definitions from a previous study that delineate xenologous gene families (gene families derived from a common transfer event) to generate a massively concatenated, combined-data ToL matrix derived from 323 404 translated open reading frames arranged into 12 381 gene homologue groups coded as amino acid data and 63 336, 64 105, 65 153, 66 922 and 67 109 gene homologue groups coded as gene presence/absence data for 166 fully sequenced genomes. This whole-genome gene presence/absence and amino acid sequence ToL data matrix is composed of 4867 184 characters (a combined data-type mega-matrix). Phylogenetic analysis of this mega-matrix yielded a fully resolved ToL that classifies all three commonly accepted domains of life as monophyletic and groups most taxa in traditionally recognized locations with high support. Most importantly, these results corroborate the existence of a common evolutionary history for these taxa present in both data types that is evident only when these data are analysed in combination. © The Willi Hennig Society 2010.

Shotgun transcriptome, spatial omics, and isothermal profiling of SARS-CoV-2 infection reveals unique host responses, viral diversification, and drug interactions.

In less than nine months, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) killed over a million people, including >25,000 in New York City (NYC) alone. The COVID-19 pandemic caused by SARS-CoV-2 highlights clinical needs to detect infection, track strain evolution, and identify biomarkers of disease course. To address these challenges, we designed a fast (30-minute) colorimetric test (LAMP) for SARS-CoV-2 infection from naso/oropharyngeal swabs and a large-scale shotgun metatranscriptomics platform (total-RNA-seq) for host, viral, and microbial profiling. We applied these methods to clinical specimens gathered from 669 patients in New York City during the first two months of the outbreak, yielding a broad molecular portrait of the emerging COVID-19 disease. We find significant enrichment of a NYC-distinctive clade of the virus (20C), as well as host responses in interferon, ACE, hematological, and olfaction pathways. In addition, we use 50,821 patient records to find that renin-angiotensin-aldosterone system inhibitors have a protective effect for severe COVID-19 outcomes, unlike similar drugs. Finally, spatial transcriptomic data from COVID-19 patient autopsy tissues reveal distinct ACE2 expression loci, with macrophage and neutrophil infiltration in the lungs. These findings can inform public health and may help develop and drive SARS-CoV-2 diagnostic, prevention, and treatment strategies.

Genomic and immunologic correlates of LAG-3 expression in cancer.

Immune checkpoint blockade leads to unprecedented responses in many cancers. Although currently available agents mostly target the PD-1 and CTLA-4 pathways, agents targeting the immune checkpoint protein LAG-3 are under active clinical development, and early clinical data show that LAG-3 expression is a biomarker of response to LAG-3 blockade. To determine which cancers may benefit most from LAG-3 blockade, we performed a pan-cancer analysis of The Cancer Genome Atlas dataset to identify genomic and immunologic correlates of LAG-3 expression. High mutation burden, and expression of exogenous virus (EBV, HPV) or endogenous retrovirus (ERV3-2), were associated with overexpression of LAG-3 in multiple cancers. Although CD8+ T-cell marker (CD8A) and LAG-3 were strongly co-expressed with each other and with PD-L1 in most cancers, there were three notable exceptions: HPV+ head-neck squamous cell cancer, renal cell cancer, and glioblastoma. These results may have important implications for guiding development clinical trials of LAG-3 blockade.

Whole Genome Sequencing and Assembly of the Asian Honey Bee Apis dorsata.

The Asian honey bee (Apis dorsata) is distinct from its more widely distributed cousin Apis mellifera by a few key characteristics. Most prominently, A. dorsata, nest in the open by forming a colony clustered around the honeycomb, whereas A. mellifera nest in concealed cavities. Additionally, the worker and reproductive castes are all of the same size in A. dorsata. In order to investigate these differences, we performed whole genome sequencing of A. dorsata using a hybrid Oxford Nanopore and Illumina approach. The 223 Mb genome has an N50 of 35 kb with the largest scaffold of 302 kb. We have found that there are many genes in the dorsata genome that are distinct from other hymenoptera and also large amounts of transposable elements, and we suggest some candidate genes for A. dorsata's exceptional level of defensive aggression.

IGF2 drives formation of ileal neuroendocrine tumors in patients and mice.

By the strictest of definitions, a genetic driver of tumorigenesis should fulfill two criteria: it should be altered in a high percentage of patient tumors, and it should also be able to cause the same type of tumor to form in mice. No gene that fits either of these criteria has ever been found for ileal neuroendocrine tumors (I-NETs), which in humans are known for an unusual lack of recurrently mutated genes, and which have never been detected in mice. In the following report, we show that I-NETs can be generated by transgenic RT2 mice, which is a classic model for a genetically unrelated disease, pancreatic neuroendocrine tumors (PNETs). The ability of RT2 mice to generate I-NETs depended upon genetic background. I-NETs appeared in a B6AF1 genetic background, but not in a B6 background nor even in an AB6F1 background. AB6F1 and B6AF1 have identical nuclear DNA but can potentially express different allelic forms of imprinted genes. This led us to test human I-NETs for loss of imprinting, and we discovered that the IGF2 gene showed loss of imprinting and increased expression in the I-NETs of 57% of patients. By increasing IGF2 activity genetically, I-NETs could be produced by RT2 mice in a B6 genetic background, which otherwise never developed I-NETs. The facts that IGF2 is altered in a high percentage of patients with I-NETs and that I-NETs can form in mice that have elevated IGF2 activity, define IGF2 as the first genetic driver of ileal neuroendocrine tumorigenesis.

Single-cell sperm transcriptomes and variants from fathers of children with and without autism spectrum disorder.

The human sperm is one of the smallest cells in the body, but also one of the most important, as it serves as the entire paternal genetic contribution to a child. Investigating RNA and mutations in sperm is especially relevant for diseases such as autism spectrum disorders (ASD), which have been correlated with advanced paternal age. Historically, studies have focused on the assessment of bulk sperm, wherein millions of individual sperm are present and only high-frequency variants can be detected. Using 10× Chromium single-cell sequencing technology, we assessed the transcriptome from >65,000 single spermatozoa across six sperm donors (scSperm-RNA-seq), including two who fathered multiple children with ASD and four fathers of neurotypical children. Using RNA-seq methods for differential expression and variant analysis, we found clusters of sperm mutations in each donor that are indicative of the sperm being produced by different stem cell pools. Finally, we have shown that genetic variations can be found in single sperm.

Author Correction: A robust benchmark for detection of germline large deletions and insertions.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

A robust benchmark for detection of germline large deletions and insertions.

New technologies and analysis methods are enabling genomic structural variants (SVs) to be detected with ever-increasing accuracy, resolution and comprehensiveness. To help translate these methods to routine research and clinical practice, we developed a sequence-resolved benchmark set for identification of both false-negative and false-positive germline large insertions and deletions. To create this benchmark for a broadly consented son in a Personal Genome Project trio with broadly available cells and DNA, the Genome in a Bottle Consortium integrated 19 sequence-resolved variant calling methods from diverse technologies. The final benchmark set contains 12,745 isolated, sequence-resolved insertion (7,281) and deletion (5,464) calls ≥50 base pairs (bp). The Tier 1 benchmark regions, for which any extra calls are putative false positives, cover 2.51 Gbp and 5,262 insertions and 4,095 deletions supported by ≥1 diploid assembly. We demonstrate that the benchmark set reliably identifies false negatives and false positives in high-quality SV callsets from short-, linked- and long-read sequencing and optical mapping.

Determination of enriched histone modifications in non-genic portions of the human genome.

BACKGROUND: Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) has recently been used to identify the modification patterns for the methylation and acetylation of many different histone tails in genes and enhancers. RESULTS: We have extended the analysis of histone modifications to gene deserts, pericentromeres and subtelomeres. Using data from human CD4+ T cells, we have found that each of these non-genic regions has a particular profile of histone modifications that distinguish it from the other non-coding regions. Different methylation states of H4K20, H3K9 and H3K27 were found to be enriched in each region relative to the other regions. These findings indicate that non-genic regions of the genome are variable with respect to histone modification patterns, rather than being monolithic. We furthermore used consensus sequences for unassembled centromeres and telomeres to identify the significant histone modifications in these regions. Finally, we compared the modification patterns in non-genic regions to those at silent genes and genes with higher levels of expression. For all tested methylations with the exception of H3K27me3, the enrichment level of each modification state for silent genes is between that of non-genic regions and expressed genes. For H3K27me3, the highest levels are found in silent genes. CONCLUSION: In addition to the histone modification pattern difference between euchromatin and heterochromatin regions, as is illustrated by the enrichment of H3K9me2/3 in non-genic regions while H3K9me1 is enriched at active genes; the chromatin modifications within non-genic (heterochromatin-like) regions (e.g. subtelomeres, pericentromeres and gene deserts) are also quite different.

TCF4 induces enzalutamide resistance via neuroendocrine differentiation in prostate cancer.

In treating patients with castration resistant prostate cancer (CRPC), enzalutamide, the second-generation androgen receptor (AR) antagonist, is an accepted standard of care. However, clinical benefits are limited to a median time of 4.8 months because resistance inevitably emerges. To determine the mechanism of treatment resistance, we carried out a RNA sequence analysis and found increased expression levels of neuroendocrine markers in the enzalutamide-resistant LNCaP human prostate cancer (CaP) cell line when compared to the parental cell line. Subsequent studies demonstrated that Transcription Factor-4 (TCF4), a transcription factor implicated in WNT signaling, mediated neuroendocrine differentiation (NED) in response to enzalutamide treatment and was elevated in the enzalutamide-resistant LNCaP. In addition, we observed that PTHrP mediated enzalutamide resistance in tissue culture and inducible TCF4 overexpression resulted in enzalutamide-resistance in a mouse xenograft model. Finally, small molecule inhibitors of TCF4 or PTHrP partially reversed enzalutamide resistance in CaP cells. When tissues obtained from men who died of metastatic CaP were examined, a positive correlation was found between the expression levels of TCF4 and PTHrP. Taken together, the current results indicate that TCF4 induces enzalutamide resistance via NED in CaP.