Genome sequence assembly algorithms and misassembly identification methods

Chromosome-level reference genome assembly of the gyrfalcon (Falco rusticolus) and population genomics offer insights into the falcon population in Mongolia

The taxonomic classification of a falcon population found in the Mongolian Altai region in Asia has been heavily debated for two centuries and previous studies have been inconclusive, hindering a more informed conservation approach. Here, we generated a chromosome-level gyrfalcon reference genome using the Vertebrate Genomes Project (VGP) assembly pipeline. Using whole genome sequences of 49 falcons from different species and populations, including "Altai" falcons, we analyzed their population structure, admixture patterns, and demographic history. We find that the Altai falcons are genomic mosaics of saker and gyrfalcon ancestries, and carry distinct W and mitochondrial haplotypes that cluster with the lanner falcon. The Altai maternally-inherited haplotypes diverged 422,000 years before present (290,000-550,000 YBP) from the ancestor of sakers and gyrfalcons, both of which, in turn, split 109,000 YBP (70,000-150,000 YBP). The Altai W chromosome has 31 coding variants in 29 genes that may possibly influence important structural, behavioral, and reproductive traits. These findings provide insights into the question of Altai falcons as a candidate distinct species.

A precise and cost-efficient whole-genome haplotyping method without probands: preimplantation genetic testing analysis

RESEARCH QUESTION

Is there a precise and efficient haplotyping method to expand the application of preimplantation genetic testing (PGT)?

DESIGN

In this study, eight cell-line families and 18 clinical families including 99 embryos were used to construct whole-genome haplotyping based on link-read sequencing (Phbol-seq) and optimized analytical workflow with a correction algorithm. The correction algorithm was based on a differentiation of assembly errors and homologous recombination, in which the main feature of parental assembly error was that all embryos (embryo number ≥2) had breakpoints at the same chromosome position.

RESULTS

With Phbol-seq, parental assembly errors and homologous recombination were accurately distinguished and corrected. Using the link-reads (>25% long-reads were ≥30 kilobases [kb]), complete genome-wide parental haplotypes were constructed, and the consistency of the typing results of each chromosome with a conventional method requiring other family members was more than 95%. In addition, the length of N50 contigs was 11.03-16.2 million bases (mb), which was far beyond the N50 contigs from long-read sequencing (148-863 kb). The complete haplotype analysis of all embryos could be performed by Phbol-seq and revealed 100% concordance with the available diagnostic results obtained by the conventional method requiring other family members.

CONCLUSIONS

Phbol-seq has high clinical value as a precise and cost-efficient whole-genome haplotyping method without probands as part of PGT and other genetic research, which could promote the application of PGT to decrease the birth of children with genetic diseases and the development of linkage-related genetic research.

Klumpy: A tool to evaluate the integrity of long-read genome assemblies and illusive sequence motifs

The improvement and decreasing costs of third-generation sequencing technologies has widened the scope of biological questions researchers can address with de novo genome assemblies. With the increasing number of reference genomes, validating their integrity with minimal overhead is vital for establishing confident results in their applications. Here, we present Klumpy, a tool for detecting and visualizing both misassembled regions in a genome assembly and genetic elements (e.g. genes) of interest in a set of sequences. By leveraging the initial raw reads in combination with their respective genome assembly, we illustrate Klumpy's utility by investigating antifreeze glycoprotein (afgp) loci across two icefishes, by searching for a reported absent gene in the northern snakehead fish, and by scanning the reference genomes of a mudskipper and bumblebee for misassembled regions. In the two former cases, we were able to provide support for the noncanonical placement of an afgp locus in the icefishes and locate the missing snakehead gene. Furthermore, our genome scans were able identify an unmappable locus in the mudskipper reference genome and identify a putative repetitive element shared among several species of bees.

Genomes of autotetraploid wild and cultivated Ziziphus mauritiana reveal polyploid evolution and crop domestication

Indian jujube (Ziziphus mauritiana) holds a prominent position in the global fruit and pharmaceutical markets. Here, we report the assemblies of haplotype-resolved, telomere-to-telomere genomes of autotetraploid wild and cultivated Indian jujube plants using a 2-stage assembly strategy. The generation of these genomes permitted in-depth investigations into the divergence and evolutionary history of this important fruit crop. Using a graph-based pan-genome constructed from 8 monoploid genomes, we identified structural variation (SV)-FST hotspots and SV hotspots. Gap-free genomes provide a means to obtain a global view of centromere structures. We identified presence-absence variation-related genes in 4 monoploid genomes (cI, cIII, wI, and wIII) and resequencing populations. We also present the population structure and domestication trajectory of the Indian jujube based on the resequencing of 73 wild and cultivated accessions. Metabolomic and transcriptomic analyses of mature fruits of wild and cultivated accessions unveiled the genetic basis underlying loss of fruit astringency during domestication of Indian jujube. This study reveals mechanisms underlying the divergence, evolution, and domestication of the autotetraploid Indian jujube and provides rich and reliable genetic resources for future research.

Implementing Whole Genome Sequencing (WGS) in Clinical Practice: Advantages, Challenges, and Future Perspectives

The integration of whole genome sequencing (WGS) into all aspects of modern medicine represents the next step in the evolution of healthcare. Using this technology, scientists and physicians can observe the entire human genome comprehensively, generating a plethora of new sequencing data. Modern computational analysis entails advanced algorithms for variant detection, as well as complex models for classification. Data science and machine learning play a crucial role in the processing and interpretation of results, using enormous databases and statistics to discover new and support current genotype-phenotype correlations. In clinical practice, this technology has greatly enabled the development of personalized medicine, approaching each patient individually and in accordance with their genetic and biochemical profile. The most propulsive areas include rare disease genomics, oncogenomics, pharmacogenomics, neonatal screening, and infectious disease genomics. Another crucial application of WGS lies in the field of multi-omics, working towards the complete integration of human biomolecular data. Further technological development of sequencing technologies has led to the birth of third and fourth-generation sequencing, which include long-read sequencing, single-cell genomics, and nanopore sequencing. These technologies, alongside their continued implementation into medical research and practice, show great promise for the future of the field of medicine.