Improving genome assemblies and annotations for nonhuman primates

Novel Insights into the Landscape of Crossover and Noncrossover Events in Rhesus Macaques (Macaca mulatta)

Meiotic recombination landscapes differ greatly between distantly and closely related taxa, populations, individuals, sexes, and even within genomes; however, the factors driving this variation are yet to be well elucidated. Here, we directly estimate contemporary crossover rates and, for the first time, noncrossover rates in rhesus macaques (Macaca mulatta) from four three-generation pedigrees comprising 32 individuals. We further compare these results with historical, demography-aware, linkage disequilibrium-based recombination rate estimates. From paternal meioses in the pedigrees, 165 crossover events with a median resolution of 22.3 kb were observed, corresponding to a male autosomal map length of 2,357 cM-approximately 15% longer than an existing linkage map based on human microsatellite loci. In addition, 85 noncrossover events with a mean tract length of 155 bp were identified-similar to the tract lengths observed in the only other two primates in which noncrossovers have been studied to date, humans and baboons. Consistent with observations in other placental mammals with PRDM9-directed recombination, crossover (and to a lesser extent noncrossover) events in rhesus macaques clustered in intergenic regions and toward the chromosomal ends in males-a pattern in broad agreement with the historical, sex-averaged recombination rate estimates-and evidence of GC-biased gene conversion was observed at noncrossover sites.

Revised eutherian gene collections

Objectives

The most recent research projects in scientific field of eutherian comparative genomics included intentions to sequence every extant eutherian species genome in foreseeable future, so that future revisions and updates of eutherian gene data sets were expected.

Data description

Using 35 public eutherian reference genomic sequence assemblies and free available software, the eutherian comparative genomic analysis protocol RRID:SCR_014401 was published as guidance against potential genomic sequence errors. The protocol curated 14 eutherian third-party data gene data sets, including, in aggregate, 2615 complete coding sequences that were deposited in European Nucleotide Archive. The published eutherian gene collections were used in revisions and updates of eutherian gene data set classifications and nomenclatures that included gene annotations, phylogenetic analyses and protein molecular evolution analyses.

MicroRNA Signatures of the Developing Primate Fovea

Rod and cone photoreceptors differ in their shape, photopigment expression, synaptic connection patterns, light sensitivity, and distribution across the retina. Although rods greatly outnumber cones, human vision is mostly dependent on cone photoreceptors since cones are essential for our sharp visual acuity and color discrimination. In humans and other primates, the fovea centralis (fovea), a specialized region of the central retina, contains the highest density of cones. Despite the vast importance of the fovea for human vision, the molecular mechanisms guiding the development of this region are largely unknown. MicroRNAs (miRNAs) are small post-transcriptional regulators known to orchestrate developmental transitions and cell fate specification in the retina. Here, we have characterized the transcriptional landscape of the developing rhesus monkey retina. Our data indicates that non-human primate fovea development is significantly accelerated compared to the equivalent retinal region at the other side of the optic nerve head, as described previously. Notably, we also identify several miRNAs differentially expressed in the presumptive fovea, including miR-15b-5p, miR-342-5p, miR-30b-5p, miR-103-3p, miR-93-5p as well as the miRNA cluster miR-183/-96/-182. Interestingly, miR-342-5p is enriched in the nasal primate retina and in the peripheral developing mouse retina, while miR-15b is enriched in the temporal primate retina and increases over time in the mouse retina in a central-to-periphery gradient. Together our data constitutes the first characterization of the developing rhesus monkey retinal miRNome and provides novel datasets to attain a more comprehensive understanding of foveal development.

Understanding the causes of errors in eukaryotic protein-coding gene prediction: a case study of primate proteomes

Background

Recent advances in sequencing technologies have led to an explosion in the number of genomes available, but accurate genome annotation remains a major challenge. The prediction of protein-coding genes in eukaryotic genomes is especially problematic, due to their complex exon–intron structures. Even the best eukaryotic gene prediction algorithms can make serious errors that will significantly affect subsequent analyses.

Results

We first investigated the prevalence of gene prediction errors in a large set of 176,478 proteins from ten primate proteomes available in public databases. Using the well-studied human proteins as a reference, a total of 82,305 potential errors were detected, including 44,001 deletions, 27,289 insertions and 11,015 mismatched segments where part of the correct protein sequence is replaced with an alternative erroneous sequence. We then focused on the mismatched sequence errors that cause particular problems for downstream applications. A detailed characterization allowed us to identify the potential causes for the gene misprediction in approximately half (5446) of these cases. As a proof-of-concept, we also developed a simple method which allowed us to propose improved sequences for 603 primate proteins.

Conclusions

Gene prediction errors in primate proteomes affect up to 50% of the sequences. Major causes of errors include undetermined genome regions, genome sequencing or assembly issues, and limitations in the models used to represent gene exon–intron structures. Nevertheless, existing genome sequences can still be exploited to improve protein sequence quality. Perspectives of the work include the characterization of other types of gene prediction errors, as well as the development of a more comprehensive algorithm for protein sequence error correction.

Resources for functional genomic studies of health and development in nonhuman primates

Primates display a wide range of phenotypic variation underlaid by complex genetically regulated mechanisms. The links among DNA sequence, gene function, and phenotype have been of interest from an evolutionary perspective, to understand functional genome evolution and its phenotypic consequences, and from a biomedical perspective to understand the shared and human-specific roots of health and disease. Progress in methods for characterizing genetic, transcriptomic, and DNA methylation (DNAm) variation is driving the rapid development of extensive omics resources, which are now increasingly available from humans as well as a growing number of nonhuman primates (NHPs). The fast growth of large-scale genomic data is driving the emergence of integrated tools and databases, thus facilitating studies of gene functionality across primates. This review describes NHP genomic resources that can aid in exploration of how genes shape primate phenotypes. It focuses on the gene expression trajectories across development in different tissues, the identification of functional genetic variation (including variants deleterious for protein function and regulatory variants modulating gene expression), and DNAm profiles as an emerging tool to understand the process of aging. These resources enable comparative functional genomics approaches to identify species-specific and primate-shared gene functionalities associated with health and development.

Comparative genome-wide survey of single nucleotide variation uncovers the genetic diversity and potential biomedical applications among six Macaca species

Macaca is of great importance in evolutionary and biomedical research. Aiming at elucidating genetic diversity patterns and potential biomedical applications of macaques, we characterized single nucleotide variations (SNVs) of six Macaca species based on the reference genome of Macaca mulatta. Using eight whole-genome sequences, representing the most comprehensive genomic SNV study in Macaca to date, we focused on discovery and comparison of nonsynonymous SNVs (nsSNVs) with bioinformatic tools. We observed that SNV distribution patterns were generally congruent among the eight individuals. Outlier tests of nsSNV distribution patterns detected 319 bins with significantly distinct genetic divergence among macaques, including differences in genes associated with taste transduction, homologous recombination, and fat and protein digestion. Genes with specific nsSNVs in various macaques were differentially enriched for metabolism pathways, such as glycolysis, protein digestion and absorption. On average, 24.95% and 11.67% specific nsSNVs were putatively deleterious according to PolyPhen2 and SIFT4G, respectively, among which the shared deleterious SNVs were located in 564–1981 genes. These genes displayed enrichment signals in the ‘obesity-related traits’ disease category for all surveyed macaques, confirming that they were suitable models for obesity related studies. Additional enriched disease categories were observed in some macaques, exhibiting promising potential for biomedical application. Positively selected genes identified by PAML in most tested Macaca species played roles in immune and nervous system, growth and development, and fat metabolism. We propose that metabolism and body size play important roles in the evolutionary adaptation of macaques.

The evolution of S100A7 in primates: a model of concerted and birth-and-death evolution

The human S100A7 resides in the epidermal differentiation complex (EDC) and has been described as a key effector of innate immunity. In humans, there are five S100A7 genes located in tandem-S100A7A, S100A7P1, S100AL2, S100A7, and S100AP2. The presence of several retroelements in the S100A7A/S100A7P1 and S100A7/S100A7P2 clusters suggests that these genes were originated from a duplication around ~ 35 million years ago, during or after the divergence of Platyrrhini and Catarrhini primates. To test this hypothesis, and taking advantage of the high number of genomic sequences available in the public databases, we retrieved S100A7 gene sequences of 12 primates belonging to the Cercopithecoidea and Hominoidea (Catarrhini species). Our results support the duplication theory, with at least one gene of each cluster being identified in both Cercopithecoidea and Hominoidea species. Moreover, given the presence of an ongoing gene conversion event between S100A7 and S100A7A, a high rate of mutation in S100A7L2 and the presence of pseudogenes, we proposed a model of concerted and birth-and-death evolution to explain the evolution of S100A7 gene family. Indeed, our results suggest that S100A7L2 most likely suffered a neofunctionalization in the Catarrhini group. Being S100A7 a major protein in innate defense, we believe that our findings could open new doors in the study of this gene family in immune system.

Modeling autism in non-human primates: Opportunities and challenges

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by social communication deficits and restricted, repetitive patterns of behavior. For more than a decade, genetically-modified, risk factor-induced, as well as naturally occurring rodent models for ASD have been used as the most predominant tools to dissect the molecular and circuitry mechanisms underlying ASD. However, the apparent evolutionary differences in terms of social behavior and brain anatomy between rodents and humans have become an issue of debate regarding the translational value of rodent models for studying ASD. More recently, genome manipulation of non human primates using lentivirus-based gene expression, TALEN and CRISPR/Cas9 mediated gene editing techniques, has been reported. Genetically modified non-human primate models for ASD have been produced and characterized. While the feasibility, value, and exciting opportunities provided by the non-human primate models have been clearly demonstrated, many challenges still remain. Here, we review current progress, discuss the remaining challenges, and highlight the key issues in the development of non-human primate models for ASD research and drug development. Autism Res 2018, 11: 686-694. © 2018 International Society for Autism Research, Wiley Periodicals, Inc.

LAY SUMMARY

Over the last two decades, genetically modified rat and mouse models have been used as the most predominant tools to study mechanisms underlying autism spectrum disorder (ASD). However, the apparent evolutionary differences between rodents and humans limit the translational value of rodent models for studying ASD. Recently, several non-human primate models for ASD have been established and characterized. Here, we review current progress, discuss the challenges, and highlight the key issues in the development of non-human primate models for ASD research and drug development.

SNP-based genetic characterization of the Tulane National Primate Research Center's conventional and specific pathogen-free rhesus macaque (Macaca mulatta) populations

BACKGROUND

The rhesus macaque is an important biomedical model organism, and the Tulane National Primate Research Center (TNPRC) has one of the largest rhesus macaque breeding colonies in the United States.

METHODS

SNP profiles from 3266 rhesus macaques were used to examine the TNPRC colony genetic composition over time and across conventional or SPF animals of Chinese and Indian ancestry.

RESULTS

Chinese origin animals were the least genetically diverse and the most inbred; however, since their derivation from their conventional forebearers, neither the Chinese nor the Indian SPF animals exhibit any significant loss of genetic diversity or differentiation.

CONCLUSIONS

The TNPRC colony managers have successfully minimized loss in genetic variation across generations. Although founder effects and bottlenecks among the Indian animals have been successfully curtailed, the Chinese subpopulation still show some influences from these events.

Whole genome sequencing predicts novel human disease models in rhesus macaques

Rhesus macaques are an important pre-clinical model of human disease. To advance our understanding of genomic variation that may influence disease, we surveyed genome-wide variation in 21 rhesus macaques. We employed best-practice variant calling, validated with Mendelian inheritance. Next, we used alignment data from our cohort to detect genomic regions likely to produce inaccurate genotypes, potentially due to either gene duplication or structural variation between individuals. We generated a final dataset of >16 million high confidence variants, including 13 million in Chinese-origin rhesus macaques, an increasingly important disease model. We detected an average of 131 mutations predicted to severely alter protein coding per animal, and identified 45 such variants that coincide with known pathogenic human variants. These data suggest that expanded screening of existing breeding colonies will identify novel models of human disease, and that increased genomic characterization can help inform research studies in macaques.

Advantages of an Improved Rhesus Macaque Genome for Evolutionary Analyses

The rhesus macaque (Macaca mulatta) is widely used in molecular evolutionary analyses, particularly to identify genes under adaptive or unique evolution in the human lineage. For such studies, it is necessary to align nucleotide sequences of homologous protein-coding genes among multiple species. The validity of these analyses is dependent on high quality genomic data. However, for most mammalian species (other than humans and mice), only draft genomes are available. There has been concern that some results obtained from evolutionary analyses using draft genomes may not be correct. The rhesus macaque provides a unique opportunity to determine whether an improved genome (MacaM) yields better results than a draft genome (rheMac2) for evolutionary studies. We compared protein-coding genes annotated in the rheMac2 and MacaM genomes with their human orthologs. We found many genes annotated in rheMac2 had apparently spurious sequences not present in genes derived from MacaM. The rheMac2 annotations also appeared to inflate a frequently used evolutionary index, ω (the ratio of nonsynonymous to synonymous substitution rates). Genes with these spurious sequences must be filtered out from evolutionary analyses to obtain correct results. With the MacaM genome, improved sequence information means many more genes can be examined for indications of selection. These results indicate how upgrading genomes from draft status to a higher level of quality can improve interpretation of evolutionary patterns.

Exome screening to identify loss-of-function mutations in the rhesus macaque for development of preclinical models of human disease

Background

Exome sequencing has been utilized to identify genetic variants associated with disease in humans. Identification of loss-of-function mutations with exome sequencing in rhesus macaques (Macaca mulatta) could lead to valuable animal models of genetic disease. Attempts have been made to identify variants in rhesus macaques by aligning exome data against the rheMac2 draft genome. However, such efforts have been impaired due to the incompleteness and annotation errors associated with rheMac2. We wished to determine whether aligning exome reads against our new, improved rhesus genome, MacaM, could be used to identify high impact, loss-of-function mutations in rhesus macaques that would be relevant to human disease.

Results

We compared alignments of exome reads from four rhesus macaques, the reference animal and three unrelated animals, against rheMac2 and MacaM. Substantially more reads aligned against MacaM than rheMac2. We followed the Broad Institute’s Best Practice guidelines for variant discovery which utilizes the Genome Analysis Toolkit to identify high impact mutations. When rheMac2 was used as the reference genome, a large number of apparent false positives were identified. When MacaM was used as the reference genome, the number of false positives was greatly reduced. After examining the variant analyses conducted with MacaM as reference genome, we identified two putative loss-of-function mutations, in the heterozygous state, in genes related to human health. Sanger sequencing confirmed the presence of these mutations. We followed the transmission of one of these mutations (in the butyrylthiocholine gene) through three generations of rhesus macaques. Further, we demonstrated a functional decrease in butyrylthiocholinesterase activity similar to that observed in human heterozygotes with loss-of-function mutations in the same gene.

Conclusions

The new MacaM genome can be effectively utilized to identify loss-of-function mutations in rhesus macaques without generating a high level of false positives. In some cases, heterozygotes may be immediately useful as models of human disease. For diseases where homozygous mutants are needed, directed breeding of loss-of-function heterozygous animals could be used to create rhesus macaque models of human genetic disease. The approach we describe here could be applied to other mammals, but only if their genomes have been improved beyond draft status.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2509-5) contains supplementary material, which is available to authorized users.

Transcriptome Analysis in Domesticated Species: Challenges and Strategies

Domesticated species occupy a special place in the human world due to their economic and cultural value. In the era of genomic research, domesticated species provide unique advantages for investigation of diseases and complex phenotypes. RNA sequencing, or RNA-seq, has recently emerged as a new approach for studying transcriptional activity of the whole genome, changing the focus from individual genes to gene networks. RNA-seq analysis in domesticated species may complement genome-wide association studies of complex traits with economic importance or direct relevance to biomedical research. However, RNA-seq studies are more challenging in domesticated species than in model organisms. These challenges are at least in part associated with the lack of quality genome assemblies for some domesticated species and the absence of genome assemblies for others. In this review, we discuss strategies for analyzing RNA-seq data, focusing particularly on questions and examples relevant to domesticated species.

The devil is in the details: Transposable element analysis of the Tasmanian devil genome

The third marsupial genome was sequenced from the Tasmanian devil (Sarcophilus harrisii), a species that currently is driven to extinction by a rare transmissible cancer. The transposable element (TE) landscape of the Tasmanian devil genome revealed that the main driver of retrotransposition the Long INterspersed Element 1 (LINE1) seem to have become inactivated during the past 12 million years. Strangely, the Short INterspersed Elements (SINE), that normally hijacks the LINE1 retrotransposition system, became inactive prior to LINE1 at around 30 million years ago. The SINE inactivation was in vitro verified in several species. Here I discuss that the apparent LINE1 inactivation might be caused by a genome assembly artifact. The repetitive fraction of any genome is highly complex to assemble and the observed problems are not unique to the Tasmanian devil genome.

GASS: genome structural annotation for Eukaryotes based on species similarity

Background

With the development of high-throughput sequencing techniques, more and more genomes were sequenced and assembled. However, annotating a genome’s structure rapidly and expressly remains challenging. Current eukaryotic genome annotations require various, abundant supporting data, such as: species-specific and cross-species protein sequences, ESTs, cDNA and RNA-Seq data. Collecting those data and merging their analytical results to achieve a consistent complete annotation is a complex, time and cost consuming task.

Results

In our study, we proposed a fast and easy-to-use computational tool: GASS (Genome Annotation based on Species Similarity). It annotates a eukaryotic genome based on only the annotations from another similar species. With aligning the exons’ sequences of an annotated similar species to the un-annotated genome, GASS detects the optimal transcript annotations with a shortest-path model. In our study, GASS was used to achieve the rhesus annotations based on the human annotations. The produced annotations were evaluated by comparing them to the two existing rhesus annotation databases (RefSeq and Ensembl) directly and being aligned with three RNA-Seq data of rhesus. The experiment results showed that more than 65% RefSeq exons and splicing junctions were exactly found by GASS. GASS’s sensitivity was higher than RefSeq’s, and was close to Ensembl’s. GASS had higher specificities than Ensembl at gene, transcript, exon and splicing junction levels. We also found the mis-assemblies of rheMac3 genome, which led to the 2 bp shifts in annotating position on exons’ boundary and then the incomplete splicing canonical sites in Refseq annotations. These detections were further supported by various data sources.

Conclusions

GASS quickly produces structural genome annotations in sufficient abundance and accuracy. With simple and rapid running of GASS, small labs can create quick views of genome annotations for an un-annotated species, without the necessity to create, collect, analyze and synthesize extra various data sources, or wait several months for the annotations from professional organizations. GASS can be applied to many study occasions, such as the analysis of RNA-Seq datasets from the unannotated species whose genome drafts are available but the annotations are not.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1353-3) contains supplementary material, which is available to authorized users.

A new rhesus macaque assembly and annotation for next-generation sequencing analyses

Background

The rhesus macaque (Macaca mulatta) is a key species for advancing biomedical research. Like all draft mammalian genomes, the draft rhesus assembly (rheMac2) has gaps, sequencing errors and misassemblies that have prevented automated annotation pipelines from functioning correctly. Another rhesus macaque assembly, CR_1.0, is also available but is substantially more fragmented than rheMac2 with smaller contigs and scaffolds. Annotations for these two assemblies are limited in completeness and accuracy. High quality assembly and annotation files are required for a wide range of studies including expression, genetic and evolutionary analyses.

Results

We report a new de novo assembly of the rhesus macaque genome (MacaM) that incorporates both the original Sanger sequences used to assemble rheMac2 and new Illumina sequences from the same animal. MacaM has a weighted average (N50) contig size of 64 kilobases, more than twice the size of the rheMac2 assembly and almost five times the size of the CR_1.0 assembly. The MacaM chromosome assembly incorporates information from previously unutilized mapping data and preliminary annotation of scaffolds. Independent assessment of the assemblies using Ion Torrent read alignments indicates that MacaM is more complete and accurate than rheMac2 and CR_1.0. We assembled messenger RNA sequences from several rhesus tissues into transcripts which allowed us to identify a total of 11,712 complete proteins representing 9,524 distinct genes. Using a combination of our assembled rhesus macaque transcripts and human transcripts, we annotated 18,757 transcripts and 16,050 genes with complete coding sequences in the MacaM assembly. Further, we demonstrate that the new annotations provide greatly improved accuracy as compared to the current annotations of rheMac2. Finally, we show that the MacaM genome provides an accurate resource for alignment of reads produced by RNA sequence expression studies.

Conclusions

The MacaM assembly and annotation files provide a substantially more complete and accurate representation of the rhesus macaque genome than rheMac2 or CR_1.0 and will serve as an important resource for investigators conducting next-generation sequencing studies with nonhuman primates.

Reviewers

This article was reviewed by Dr. Lutz Walter, Dr. Soojin Yi and Dr. Kateryna Makova.

FixPred: a resource for correction of erroneous protein sequences

Protein databases are heavily contaminated with erroneous (mispredicted, abnormal and incomplete) sequences and these erroneous data significantly distort the conclusions drawn from genome-scale protein sequence analyses. In our earlier work we described the MisPred resource that serves to identify erroneous sequences; here we present the FixPred computational pipeline that automatically corrects sequences identified by MisPred as erroneous. The current version of the associated FixPred database contains corrected UniProtKB/Swiss-Prot and NCBI/RefSeq sequences from Homo sapiens, Mus musculus, Rattus norvegicus, Monodelphis domestica, Gallus gallus, Xenopus tropicalis, Danio rerio, Fugu rubripes, Ciona intestinalis, Branchostoma floridae, Drosophila melanogaster and Caenorhabditis elegans; future releases of the FixPred database will include corrected sequences of additional Metazoan species. The FixPred computational pipeline and database (http://www.fixpred.com) are easily accessible through a simple web interface coupled to a powerful query engine and a standard web service. The content is completely or partially downloadable in a variety of formats.

Database URL:http://www.fixpred.com