June 1, 2021  |  

FALCON-Phase integrates PacBio and HiC data for de novo assembly, scaffolding and phasing of a diploid Puerto Rican genome (HG00733)

Haplotype-resolved genomes are important for understanding how combinations of variants impact phenotypes. The study of disease, quantitative traits, forensics, and organ donor matching are aided by phased genomes. Phase is commonly resolved using familial data, population-based imputation, or by isolating and sequencing single haplotypes using fosmids, BACs, or haploid tissues. Because these methods can be prohibitively expensive, or samples may not be available, alternative approaches are required. de novo genome assembly with PacBio Single Molecule, Real-Time (SMRT) data produces highly contiguous, accurate assemblies. For non-inbred samples, including humans, the separate resolution of haplotypes results in higher base accuracy and more contiguous assembled sequences. Two primary methods exist for phased diploid genome assembly. The first, TrioCanu requires Illumina data from parents and PacBio data from the offspring. The long reads from the child are partitioned into maternal and paternal bins using parent-specific sequences; the separate PacBio read bins are then assembled, generating two fully phased genomes. An alternative approach (FALCON-Unzip) does not require parental information and separates PacBio reads, during genome assembly, using heterozygous SNPs. The length of haplotype phase blocks in FALCON-Unzip is limited by the magnitude and distribution of heterozygosity, the length of sequence reads, and read coverage. Because of this, FALCON-Unzip contigs typically contain haplotype-switch errors between phase blocks, resulting in primary contig of mixed parental origin. We developed FALCON-Phase, which integrates Hi-C data downstream of FALCON-Unzip to resolve phase switches along contigs. We applied the method to a human (Puerto Rican, HG00733) and non-human genome assemblies and evaluated accuracy using samples with trio data. In a cattle genome, we observe >96% accuracy in phasing when compared to TrioCanu assemblies as well as parental SNPs. For a high-quality PacBio assembly (>90-fold Sequel coverage) of a Puerto Rican individual we scaffolded the FALCON-Phase contigs, and re-phased the contigs creating a de novo scaffolded, phased diploid assembly with chromosome-scale contiguity.

April 21, 2020  |  

Insect genomes: progress and challenges.

In the wake of constant improvements in sequencing technologies, numerous insect genomes have been sequenced. Currently, 1219 insect genome-sequencing projects have been registered with the National Center for Biotechnology Information, including 401 that have genome assemblies and 155 with an official gene set of annotated protein-coding genes. Comparative genomics analysis showed that the expansion or contraction of gene families was associated with well-studied physiological traits such as immune system, metabolic detoxification, parasitism and polyphagy in insects. Here, we summarize the progress of insect genome sequencing, with an emphasis on how this impacts research on pest control. We begin with a brief introduction to the basic concepts of genome assembly, annotation and metrics for evaluating the quality of draft assemblies. We then provide an overview of genome information for numerous insect species, highlighting examples from prominent model organisms, agricultural pests and disease vectors. We also introduce the major insect genome databases. The increasing availability of insect genomic resources is beneficial for developing alternative pest control methods. However, many opportunities remain for developing data-mining tools that make maximal use of the available insect genome resources. Although rapid progress has been achieved, many challenges remain in the field of insect genomics. © 2019 The Royal Entomological Society.

April 21, 2020  |  

The CF Canada-Sick Kids Program in individual CF therapy: A resource for the advancement of personalized medicine in CF.

Therapies targeting certain CFTR mutants have been approved, yet variations in clinical response highlight the need for in-vitro and genetic tools that predict patient-specific clinical outcomes. Toward this goal, the CF Canada-Sick Kids Program in Individual CF Therapy (CFIT) is generating a “first of its kind”, comprehensive resource containing patient-specific cell cultures and data from 100 CF individuals that will enable modeling of therapeutic responses.The CFIT program is generating: 1) nasal cells from drug naïve patients suitable for culture and the study of drug responses in vitro, 2) matched gene expression data obtained by sequencing the RNA from the primary nasal tissue, 3) whole genome sequencing of blood derived DNA from each of the 100 participants, 4) induced pluripotent stem cells (iPSCs) generated from each participant’s blood sample, 5) CRISPR-edited isogenic control iPSC lines and 6) prospective clinical data from patients treated with CF modulators.To date, we have recruited 57 of 100 individuals to CFIT, most of whom are homozygous for F508del (to assess in-vitro: in-vivo correlations with respect to ORKAMBI response) or heterozygous for F508del and a minimal function mutation. In addition, several donors are homozygous for rare nonsense and missense mutations. Nasal epithelial cell cultures and matched iPSC lines are available for many of these donors.This accessible resource will enable development of tools that predict individual outcomes to current and emerging modulators targeting F508del-CFTR and facilitate therapy discovery for rare CF causing mutations.Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

April 21, 2020  |  

Computational aspects underlying genome to phenome analysis in plants.

Recent advances in genomics technologies have greatly accelerated the progress in both fundamental plant science and applied breeding research. Concurrently, high-throughput plant phenotyping is becoming widely adopted in the plant community, promising to alleviate the phenotypic bottleneck. While these technological breakthroughs are significantly accelerating quantitative trait locus (QTL) and causal gene identification, challenges to enable even more sophisticated analyses remain. In particular, care needs to be taken to standardize, describe and conduct experiments robustly while relying on plant physiology expertise. In this article, we review the state of the art regarding genome assembly and the future potential of pangenomics in plant research. We also describe the necessity of standardizing and describing phenotypic studies using the Minimum Information About a Plant Phenotyping Experiment (MIAPPE) standard to enable the reuse and integration of phenotypic data. In addition, we show how deep phenotypic data might yield novel trait-trait correlations and review how to link phenotypic data to genomic data. Finally, we provide perspectives on the golden future of machine learning and their potential in linking phenotypes to genomic features. © 2018 The Authors The Plant Journal published by John Wiley & Sons Ltd and Society for Experimental Biology.

April 21, 2020  |  

Genome sequences of horticultural plants: past, present, and future

Horticultural plants play various and critical roles for humans by providing fruits, vegetables, materials for beverages, and herbal medicines and by acting as ornamentals. They have also shaped human art, culture, and environments and thereby have influenced the lifestyles of humans. With the advent of sequencing technologies, there has been a dramatic increase in the number of sequenced genomes of horticultural plant species in the past decade. The genomes of horticultural plants are highly diverse and complex, often with a high degree of heterozygosity and a high ploidy due to their long and complex history of evolution and domestication. Here we summarize the advances in the genome sequencing of horticultural plants, the reconstruction of pan-genomes, and the development of horticultural genome databases. We also discuss past, present, and future studies related to genome sequencing, data storage, data quality, data sharing, and data visualization to provide practical guidance for genomic studies of horticultural plants. Finally, we propose a horticultural plant genome project as well as the roadmap and technical details toward three goals of the project.

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