nf-LO: A Scalable, Containerized Workflow for Genome-to-Genome Lift Over

Temporal genomics in Hawaiian crickets reveals compensatory intragenomic coadaptation during adaptive evolution

Theory predicts that compensatory genetic changes reduce negative indirect effects of selected variants during adaptive evolution, but evidence is scarce. Here, we test this in a wild population of Hawaiian crickets using temporal genomics and a high-quality chromosome-level cricket genome. In this population, a mutation, flatwing, silences males and rapidly spread due to an acoustically-orienting parasitoid. Our sampling spanned a social transition during which flatwing fixed and the population went silent. We find long-range linkage disequilibrium around the putative flatwing locus was maintained over time, and hitchhiking genes had functions related to negative flatwing-associated effects. We develop a combinatorial enrichment approach using transcriptome data to test for compensatory, intragenomic coevolution. Temporal changes in genomic selection were distributed genome-wide and functionally associated with the population's transition to silence, particularly behavioural responses to silent environments. Our results demonstrate how 'adaptation begets adaptation'; changes to the sociogenetic environment accompanying rapid trait evolution can generate selection provoking further, compensatory adaptation.

BCFtools/liftover: an accurate and comprehensive tool to convert genetic variants across genome assemblies

MOTIVATION

Many genetics studies report results tied to genomic coordinates of a legacy genome assembly. However, as assemblies are updated and improved, researchers are faced with either realigning raw sequence data using the updated coordinate system or converting legacy datasets to the updated coordinate system to be able to combine results with newer datasets. Currently available tools to perform the conversion of genetic variants have numerous shortcomings, including poor support for indels and multi-allelic variants, that lead to a higher rate of variants being dropped or incorrectly converted. As a result, many researchers continue to work with and publish using legacy genomic coordinates.

RESULTS

Here we present BCFtools/liftover, a tool to convert genomic coordinates across genome assemblies for variants encoded in the variant call format with improved support for indels represented by different reference alleles across genome assemblies and full support for multi-allelic variants. It further supports variant annotation fields updates whenever the reference allele changes across genome assemblies. The tool has the lowest rate of variants being dropped with an order of magnitude less indels dropped or incorrectly converted and is an order of magnitude faster than other tools typically used for the same task. It is particularly suited for converting variant callsets from large cohorts to novel telomere-to-telomere assemblies as well as summary statistics from genome-wide association studies tied to legacy genome assemblies.

AVAILABILITY AND IMPLEMENTATION

The tool is written in C and freely available under the MIT open source license as a BCFtools plugin available at http://github.com/freeseek/score.

Improved sequence mapping using a complete reference genome and lift-over

Complete, telomere-to-telomere (T2T) genome assemblies promise improved analyses and the discovery of new variants, but many essential genomic resources remain associated with older reference genomes. Thus, there is a need to translate genomic features and read alignments between references. Here we describe a method called levioSAM2 that performs fast and accurate lift-over between assemblies using a whole-genome map. In addition to enabling the use of several references, we demonstrate that aligning reads to a high-quality reference (for example, T2T-CHM13) and lifting to an older reference (for example, Genome reference Consortium (GRC)h38) improves the accuracy of the resulting variant calls on the old reference. By leveraging the quality improvements of T2T-CHM13, levioSAM2 reduces small and structural variant calling errors compared with GRC-based mapping using real short- and long-read datasets. Performance is especially improved for a set of complex medically relevant genes, where the GRC references are lower quality.

The complete sequence of a human Y chromosome

The human Y chromosome has been notoriously difficult to sequence and assemble because of its complex repeat structure that includes long palindromes, tandem repeats and segmental duplications1-3. As a result, more than half of the Y chromosome is missing from the GRCh38 reference sequence and it remains the last human chromosome to be finished4,5. Here, the Telomere-to-Telomere (T2T) consortium presents the complete 62,460,029-base-pair sequence of a human Y chromosome from the HG002 genome (T2T-Y) that corrects multiple errors in GRCh38-Y and adds over 30 million base pairs of sequence to the reference, showing the complete ampliconic structures of gene families TSPY, DAZ and RBMY; 41 additional protein-coding genes, mostly from the TSPY family; and an alternating pattern of human satellite 1 and 3 blocks in the heterochromatic Yq12 region. We have combined T2T-Y with a previous assembly of the CHM13 genome4 and mapped available population variation, clinical variants and functional genomics data to produce a complete and comprehensive reference sequence for all 24 human chromosomes.

Comparative Investigation of Coincident Single Nucleotide Polymorphisms Underlying Avian Influenza Viruses in Chickens and Ducks

Avian influenza is a severe viral infection that has the potential to cause human pandemics. In particular, chickens are susceptible to many highly pathogenic strains of the virus, resulting in significant losses. In contrast, ducks have been reported to exhibit rapid and effective innate immune responses to most avian influenza virus (AIV) infections. To explore the distinct genetic programs that potentially distinguish the susceptibility/resistance of both species to AIV, the investigation of coincident SNPs (coSNPs) and their differing causal effects on gene functions in both species is important to gain novel insight into the varying immune-related responses of chickens and ducks. By conducting a pairwise genome alignment between these species, we identified coSNPs and their respective effect on AIV-related differentially expressed genes (DEGs) in this study. The examination of these genes (e.g., CD74, RUBCN, and SHTN1 for chickens and ABCA3, MAP2K6, and VIPR2 for ducks) reveals their high relevance to AIV. Further analysis of these genes provides promising effector molecules (such as IκBα, STAT1/STAT3, GSK-3β, or p53) and related key signaling pathways (such as NF-κB, JAK/STAT, or Wnt) to elucidate the complex mechanisms of immune responses to AIV infections in both chickens and ducks.

The conservation of human functional variants and their effects across livestock species

Despite the clear potential of livestock models of human functional variants to provide important insights into the biological mechanisms driving human diseases and traits, their use to date has been limited. Generating such models via genome editing is costly and time consuming, and it is unclear which variants will have conserved effects across species. In this study we address these issues by studying naturally occurring livestock models of human functional variants. We show that orthologues of over 1.6 million human variants are already segregating in domesticated mammalian species, including several hundred previously directly linked to human traits and diseases. Models of variants linked to particular phenotypes, including metabolomic disorders and height, are preferentially shared across species, meaning studying the genetic basis of these phenotypes is particularly tractable in livestock. Using machine learning we demonstrate it is possible to identify human variants that are more likely to have an existing livestock orthologue, and, importantly, we show that the effects of functional variants are often conserved in livestock, acting on orthologous genes with the same direction of effect. Consequently, this work demonstrates the substantial potential of naturally occurring livestock carriers of orthologues of human functional variants to disentangle their functional impacts.

An investigation of genetic variants that exist across human and livestock species supports the clear potential of livestock models in providing insights into the mechanisms driving human diseases and traits.