Assembly and RNA-free annotation of highly heterozygous genomes: The case of the thick-billed murre (Uria lomvia)

Inference of Ancient Polyploidy Using Transcriptome Data

Polyploidizations, or whole-genome duplications (WGDs), in plants have increased biological complexity, facilitated evolutionary innovation, and likely enabled adaptation under harsh conditions. Besides genomic data, transcriptome data have been widely employed to detect WGDs, due to their efficient accessibility to the gene space of a species. Age distributions based on synonymous substitutions (so-called K_S age distributions) for paralogs assembled from transcriptome data have identified numerous WGDs in plants, paving the way for further studies on the importance of WGDs for the evolution of seed and flowering plants. However, it is still unclear how transcriptome-based age distributions compare to those based on genomic data. In this chapter, we implemented three different de novo transcriptome assembly pipelines with two popular assemblers, i.e., Trinity and SOAPdenovo-Trans. We selected six plant species with published genomes and transcriptomes to evaluate how assembled transcripts from different pipelines perform when using K_S distributions to detect previously documented WGDs in the six species. Further, using genes predicted in each genome as references, we evaluated the effects of missing genes, gene family clustering, and de novo assembled transcripts on the transcriptome-based K_S distributions. Our results show that, although the transcriptome-based K_S distributions differ from the genome-based ones with respect to their shapes and scales, they are still reasonably reliable for unveiling WGDs, except in species where most duplicates originated from a recent WGD. We also discuss how to overcome some possible pitfalls when using transcriptome data to identify WGDs.

Chromosome-Level Assembly of the Atlantic Silverside Genome Reveals Extreme Levels of Sequence Diversity and Structural Genetic Variation

The levels and distribution of standing genetic variation in a genome can provide a wealth of insights about the adaptive potential, demographic history, and genome structure of a population or species. As structural variants are increasingly associated with traits important for adaptation and speciation, investigating both sequence and structural variation is essential for wholly tapping this potential. Using a combination of shotgun sequencing, 10x Genomics linked reads and proximity-ligation data (Chicago and Hi-C), we produced and annotated a chromosome-level genome assembly for the Atlantic silverside (Menidia menidia)-an established ecological model for studying the phenotypic effects of natural and artificial selection-and examined patterns of genomic variation across two individuals sampled from different populations with divergent local adaptations. Levels of diversity varied substantially across each chromosome, consistently being highly elevated near the ends (presumably near telomeric regions) and dipping to near zero around putative centromeres. Overall, our estimate of the genome-wide average heterozygosity in the Atlantic silverside is among the highest reported for a fish, or any vertebrate (1.32-1.76% depending on inference method and sample). Furthermore, we also found extreme levels of structural variation, affecting ∼23% of the total genome sequence, including multiple large inversions (> 1 Mb and up to 12.6 Mb) associated with previously identified haploblocks showing strong differentiation between locally adapted populations. These extreme levels of standing genetic variation are likely associated with large effective population sizes and may help explain the remarkable adaptive divergence among populations of the Atlantic silverside.

Regional sequence expansion or collapse in heterozygous genome assemblies

High levels of heterozygosity present a unique genome assembly challenge and can adversely impact downstream analyses, yet is common in sequencing datasets obtained from non-model organisms. Here we show that by re-assembling a heterozygous dataset with variant parameters and different assembly algorithms, we are able to generate assemblies whose protein annotations are statistically enriched for specific gene ontology categories. While total assembly length was not significantly affected by assembly methodologies tested, the assemblies generated varied widely in fragmentation level and we show local assembly collapse or expansion underlying the enrichment or depletion of specific protein functional groups. We show that these statistically significant deviations in gene ontology groups can occur in seemingly high-quality assemblies, and result from difficult-to-detect local sequence expansion or contractions. Given the unpredictable interplay between assembly algorithm, parameter, and biological sequence data heterozygosity, we highlight the need for better measures of assembly quality than N50 value, including methods for assessing local expansion and collapse.

In the genomic era, genomes must be reconstructed from fragments using computational methods, or assemblers. How do we know that a new genome assembly is correct? This is important because errors in assembly can lead to downstream problems in gene predictions and these inaccurate results can contaminate databases, affecting later comparative studies. A particular challenge occurs when a diploid organism inherits two highly divergent genome copies from its parents. While it is widely appreciated that this type of data is difficult for assemblers to handle properly, here we show that the process is prone to more errors than previously appreciated. Specifically, we document examples of regional expansion and collapse, affecting downstream gene prediction accuracy, but without changing the overall genome assembly size or other metrics of accuracy. Our results suggest that assembly evaluation methods should be altered to identify whether regional expansions and collapses are present in the genome assembly.

A Multireference-Based Whole Genome Assembly for the Obligate Ant-Following Antbird, Rhegmatorhina melanosticta (Thamnophilidae)

Current generation high-throughput sequencing technology has facilitated the generation of more genomic-scale data than ever before, thus greatly improving our understanding of avian biology across a range of disciplines. Recent developments in linked-read sequencing (Chromium 10×) and reference-based whole-genome assembly offer an exciting prospect of more accessible chromosome-level genome sequencing in the near future. We sequenced and assembled a genome of the Hairy-crested Antbird (Rhegmatorhina melanosticta), which represents the first publicly available genome for any antbird (Thamnophilidae). Our objectives were to (1) assemble scaffolds to chromosome level based on multiple reference genomes, and report on differences relative to other genomes, (2) assess genome completeness and compare content to other related genomes, and (3) assess the suitability of linked-read sequencing technology for future studies in comparative phylogenomics and population genomics studies. Our R. melanosticta assembly was both highly contiguous (de novo scaffold N50 = 3.3 Mb, reference based N50 = 53.3 Mb) and relatively complete (contained close to 90% of evolutionarily conserved single-copy avian genes and known tetrapod ultraconserved elements). The high contiguity and completeness of this assembly enabled the genome to be successfully mapped to the chromosome level, which uncovered a consistent structural difference between R. melanosticta and other avian genomes. Our results are consistent with the observation that avian genomes are structurally conserved. Additionally, our results demonstrate the utility of linked-read sequencing for non-model genomics. Finally, we demonstrate the value of our R. melanosticta genome for future researchers by mapping reduced representation sequencing data, and by accurately reconstructing the phylogenetic relationships among a sample of thamnophilid species.

Reference Genomes from Distantly Related Species Can Be Used for Discovery of Single Nucleotide Polymorphisms to Inform Conservation Management

Threatened species recovery programmes benefit from incorporating genomic data into conservation management strategies to enhance species recovery. However, a lack of readily available genomic resources, including conspecific reference genomes, often limits the inclusion of genomic data. Here, we investigate the utility of closely related high-quality reference genomes for single nucleotide polymorphism (SNP) discovery using the critically endangered kakī/black stilt (Himantopus novaezelandiae) and four Charadriiform reference genomes as proof of concept. We compare diversity estimates (i.e., nucleotide diversity, individual heterozygosity, and relatedness) based on kakī SNPs discovered from genotyping-by-sequencing and whole genome resequencing reads mapped to conordinal (killdeer, Charadrius vociferus), confamilial (pied avocet, Recurvirostra avosetta), congeneric (pied stilt, Himantopus himantopus) and conspecific reference genomes. Results indicate that diversity estimates calculated from SNPs discovered using closely related reference genomes correlate significantly with estimates calculated from SNPs discovered using a conspecific genome. Congeneric and confamilial references provide higher correlations and more similar measures of nucleotide diversity, individual heterozygosity, and relatedness. While conspecific genomes may be necessary to address other questions in conservation, SNP discovery using high-quality reference genomes of closely related species is a cost-effective approach for estimating diversity measures in threatened species.

The Bear Giant-Skipper genome suggests genetic adaptations to living inside yucca roots

Giant-Skippers (Megathymini) are unusual thick-bodied, moth-like butterflies whose caterpillars feed inside Yucca roots and Agave leaves. Giant-Skippers are attributed to the subfamily Hesperiinae and they are endemic to southern and mostly desert regions of the North American continent. To shed light on the genotypic determinants of their unusual phenotypic traits, we sequenced and annotated a draft genome of the largest Giant-Skipper species, the Bear (Megathymus ursus violae). The Bear skipper genome is the least heterozygous among sequenced Lepidoptera genomes, possibly due to much smaller population size and extensive inbreeding. Their lower heterozygosity helped us to obtain a high-quality genome with an N50 of 4.2 Mbp. The ~ 430 Mb genome encodes about 14000 proteins. Phylogenetic analysis supports placement of Giant-Skippers with Grass-Skippers (Hesperiinae). We find that proteins involved in odorant and taste sensing as well as in oxidative reactions have diverged significantly in Megathymus as compared to Lerema, another Grass-Skipper. In addition, the Giant-Skipper has lost several odorant and gustatory receptors and possesses many fewer (1/3-1/2 of other skippers) anti-oxidative enzymes. Such differences may be related to the unusual life style of Giant-Skippers: they do not feed as adults, and their caterpillars feed inside Yuccas and Agaves, which provide a source of antioxidants such as polyphenols.