Pangenomics in microbial and crop research: Progress, applications, and perspectives

Advances in sequencing technologies and bioinformatics tools have fueled a renewed interest in whole genome sequencing efforts in many organisms. The growing availability of multiple genome sequences has advanced our understanding of the within-species diversity, in the form of a pangenome. Pangenomics has opened new avenues for future research such as allowing dissection of complex molecular mechanisms and increased confidence in genome mapping. To comprehensively capture the genetic diversity for improving plant performance, the pangenome concept is further extended from species to genus level by the inclusion of wild species, constituting a super-pangenome. Characterization of pangenome has implications for both basic and applied research. The concept of pangenome has transformed the way biological questions are addressed. From understanding evolution and adaptation to elucidating host–pathogen interactions, finding novel genes or breeding targets to aid crop improvement to design effective vaccines for human prophylaxis, the increasing availability of the pangenome has revolutionized several aspects of biological research. The future availability of high-resolution pangenomes based on reference-level near-complete genome assemblies would greatly improve our ability to address complex biological problems

A strategy for building and using a human reference pangenome

In March 2019, 45 scientists and software engineers from around the world converged at the University of California, Santa Cruz for the first pangenomics codeathon. The purpose of the meeting was to propose technical specifications and standards for a usable human pangenome as well as to build relevant tools for genome graph infrastructures. During the meeting, the group held several intense and productive discussions covering a diverse set of topics, including advantages of graph genomes over a linear reference representation, design of new methods that can leverage graph-based data structures, and novel visualization and annotation approaches for pangenomes. Additionally, the participants self-organized themselves into teams that worked intensely over a three-day period to build a set of pipelines and tools for specific pangenomic applications. A summary of the questions raised and the tools developed are reported in this manuscript

Towards plant pangenomics

As an increasing number of genome sequences become available for a wide range of species, there is a growing understanding that the genome of a single individual is insufficient to represent the gene diversity within a whole species. Many studies examine the sequence diversity within genes, and this allelic variation is an important source of phenotypic variation which can be selected for by man or nature. However, the significant gene presence/absence variation that has been observed within species and the impact of this variation on traits is only now being studied in detail. The sum of the genes for a species is termed the pangenome, and the determination and characterization of the pangenome is a requirement to understand variation within a species. In this review, we explore the current progress in pangenomics as well as methods and approaches for the characterization of pangenomes for a wide range of plant species

A draft human pangenome reference

Here the Human Pangenome Reference Consortium presents a first draft of the human pangenome reference. The pangenome contains 47 phased, diploid assemblies from a cohort of genetically diverse individual

Bioinformatics: Basics, Development, and Future

Bioinformatics is an interdisciplinary scientific field of life sciences. Bioinformatics research and application include the analysis of molecular sequence and genomics data; genome annotation, gene/protein prediction, and expression profiling; molecular folding, modeling, and design; building biological networks; development of databases and data management systems; development of software and analysis tools; bioinformatics services and workflow; mining of biomedical literature and text; and bioinformatics education and training. Astronomical accumulation of genomics, proteomics, and metabolomics data as well as a need for their storage, analysis, annotation, organization, systematization, and integration into biological networks and database systems were the main driving forces for the emergence and development of bioinformatics. Current critical needs for bioinformatics among others highlighted in this chapter, however, are to understand basics and specifics of bioinformatics as well as to prepare new generation scientists and specialists with integrated, interdisciplinary, and multilingual knowledge who can use modern bioinformatics resources powered with sophisticated operating systems, software, and database/networking technologies. In this introductory chapter, I aim to give an overall picture on basics and developments of the bioinformatics field for readers with some future perspectives, highlighting chapters published in this book

A draft human pangenome reference

Here the Human Pangenome Reference Consortium presents a first draft of the human pangenome reference. The pangenome contains 47 phased, diploid assemblies from a cohort of genetically diverse individuals. These assemblies cover more than 99% of the expected sequence in each genome and are more than 99% accurate at the structural and base pair levels. Based on alignments of the assemblies, we generate a draft pangenome that captures known variants and haplotypes and reveals new alleles at structurally complex loci. We also add 119 million base pairs of euchromatic polymorphic sequences and 1,115 gene duplications relative to the existing reference GRCh38. Roughly 90 million of the additional base pairs are derived from structural variation. Using our draft pangenome to analyse short-read data reduced small variant discovery errors by 34% and increased the number of structural variants detected per haplotype by 104% compared with GRCh38-based workflows, which enabled the typing of the vast majority of structural variant alleles per sample