Efficient protocols and methods for high‐throughput utilization of the Collaborative Cross mouse model for dissecting the genetic basis of complex traits

AbstractStudies of the genetic basis of complex traits have demonstrated a substantial role for common, small-effect variant polygenic burden (PB) as well as large-effect variants (LEV, primarily rare). We identify sufficient conditions in which GWAS-derived PB may be used for well-powered rare pathogenic variant discovery or as a sample prioritization tool for whole-genome or exome sequencing. Through extensive simulations of genetic architectures and generative models of disease liability with parameters informed by empirical data, we quantify the power to detect, among cases, a lower PB in LEV carriers than in non-carriers. Furthermore, we uncover clinically useful conditions wherein the risk derived from the PB is comparable to the LEV-derived risk. The resulting summary-statistics-based methodology (with publicly available software, PB-LEV-SCAN) makes predictions on PB-based LEV screening for 36 complex traits, which we confirm in several disease datasets with available LEV information in the UK Biobank, with important implications on clinical decision-making.

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Meta-QTL analysis and identification of candidate genes for quality, abiotic and biotic stress in durum wheat

Scientific Reports ◽

10.1038/s41598-021-91446-2 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Jose Miguel Soriano ◽

Pasqualina Colasuonno ◽

Ilaria Marcotuli ◽

Agata Gadaleta

Keyword(s):

Molecular Markers ◽

Abiotic Stress ◽

Durum Wheat ◽

Candidate Genes ◽

Biotic Stress ◽

Qtl Analysis ◽

Complex Traits ◽

Genetic Basis ◽

Agronomic Traits ◽

Plant Performance

AbstractThe genetic improvement of durum wheat and enhancement of plant performance often depend on the identification of stable quantitative trait loci (QTL) and closely linked molecular markers. This is essential for better understanding the genetic basis of important agronomic traits and identifying an effective method for improving selection efficiency in breeding programmes. Meta-QTL analysis is a useful approach for dissecting the genetic basis of complex traits, providing broader allelic coverage and higher mapping resolution for the identification of putative molecular markers to be used in marker-assisted selection. In the present study, extensive QTL meta-analysis was conducted on 45 traits of durum wheat, including quality and biotic and abiotic stress-related traits. A total of 368 QTL distributed on all 14 chromosomes of genomes A and B were projected: 171 corresponded to quality-related traits, 127 to abiotic stress and 71 to biotic stress, of which 318 were grouped in 85 meta-QTL (MQTL), 24 remained as single QTL and 26 were not assigned to any MQTL. The number of MQTL per chromosome ranged from 4 in chromosomes 1A and 6A to 9 in chromosome 7B; chromosomes 3A and 7A showed the highest number of individual QTL (4), and chromosome 7B the highest number of undefined QTL (4). The recently published genome sequence of durum wheat was used to search for candidate genes within the MQTL peaks. This work will facilitate cloning and pyramiding of QTL to develop new cultivars with specific quantitative traits and speed up breeding programs.

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Epistasis for Three Grain Yield Components in Rice (Oryxa sativa L.)

Genetics ◽

10.1093/genetics/145.2.453 ◽

1997 ◽

Vol 145 (2) ◽

pp. 453-465 ◽

Cited By ~ 6

Author(s):

Zhikang Li ◽

Shannon R M Pinson ◽

William D Park ◽

Andrew H Paterson ◽

James W Stansel

Keyword(s):

Grain Yield ◽

Complex Traits ◽

Yield Components ◽

Genetic Basis ◽

Kernel Weight ◽

Progeny Testing ◽

Grain Yield Components ◽

Main Effects ◽

Grain Number Per Panicle

The genetic basis for three grain yield components of rice, 1000 kernel weight (KW), grain number per panicle (GN), and grain weight per panicle (GWP), was investigated using restriction fragment length polymorphism markers and F4 progeny testing from a cross between rice subspecies japonica (cultivar Lemont from USA) and indica (cv. Teqing from China). Following identification of 19 QTL affecting these traits, we investigated the role of epistasis in genetic control of these phenotypes. Among 63 markers distributed throughout the genome that appeared to be involved in 79 highly significant (P < 0.001) interactions, most (46 or 73%) did not appear to have “main” effects on the relevant traits, but influenced the trait(s) predominantly through interactions. These results indicate that epistasis is an important genetic basis for complex traits such as yield components, especially traits of low heritability such as GN and GWP. The identification of epistatic loci is an important step toward resolution of discrepancies between quantitative trait loci mapping and classical genetic dogma, contributes to better understanding of the persistence of quantitative genetic variation in populations, and impels reconsideration of optimal mapping methodology and marker-assisted breeding strategies for improvement of complex traits.

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WS07.3 Phenotypic and genotypic characterisation of a novel mouse model of F508del-CFTR in genetically diverse collaborative cross

Journal of Cystic Fibrosis ◽

10.1016/s1569-1993(21)00953-x ◽

2021 ◽

Vol 20 ◽

pp. S13

Author(s):

B. Sipione ◽

N.I. Lorè ◽

G. Rossi ◽

F. Sanvito ◽

M. D'Aurora ◽

...

Keyword(s):

Mouse Model ◽

Collaborative Cross

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GWAS of three molecular traits highlights core genes and pathways alongside a highly polygenic background

10.1101/2020.04.20.051631 ◽

2020 ◽

Cited By ~ 6

Author(s):

Nasa Sinnott-Armstrong ◽

Sahin Naqvi ◽

Manuel Rivas ◽

Jonathan K Pritchard

Keyword(s):

Complex Traits ◽

Genetic Basis ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Biological Processes ◽

Uk Biobank ◽

The Core ◽

Genome Wide ◽

Core Genes

SummaryGenome-wide association studies (GWAS) have been used to study the genetic basis of a wide variety of complex diseases and other traits. However, for most traits it remains difficult to interpret what genes and biological processes are impacted by the top hits. Here, as a contrast, we describe UK Biobank GWAS results for three molecular traits—urate, IGF-1, and testosterone—that are biologically simpler than most diseases, and for which we know a great deal in advance about the core genes and pathways. Unlike most GWAS of complex traits, for all three traits we find that most top hits are readily interpretable. We observe huge enrichment of significant signals near genes involved in the relevant biosynthesis, transport, or signaling pathways. We show how GWAS data illuminate the biology of variation in each trait, including insights into differences in testosterone regulation between females and males. Meanwhile, in other respects the results are reminiscent of GWAS for more-complex traits. In particular, even these molecular traits are highly polygenic, with most of the variance coming not from core genes, but from thousands to tens of thousands of variants spread across most of the genome. Given that diseases are often impacted by many distinct biological processes, including these three, our results help to illustrate why so many variants can affect risk for any given disease.

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High-Throughput LC–MS/MS Proteomic Analysis of a Mouse Model of Mesiotemporal Lobe Epilepsy Predicts Microglial Activation Underlying Disease Development

Journal of Proteome Research ◽

10.1021/acs.jproteome.6b00003 ◽

2016 ◽

Vol 15 (5) ◽

pp. 1546-1562 ◽

Cited By ~ 15

Author(s):

Vasiliki Bitsika ◽

Venceslas Duveau ◽

Julia Simon-Areces ◽

William Mullen ◽

Corinne Roucard ◽

...

Keyword(s):

Mouse Model ◽

High Throughput ◽

Proteomic Analysis ◽

Microglial Activation ◽

Underlying Disease ◽

Disease Development

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A High-Throughput In Vitro Drug Screen in a Genetically Engineered Mouse Model of Diffuse Intrinsic Pontine Glioma Identifies BMS-754807 as a Promising Therapeutic Agent

PLoS ONE ◽

10.1371/journal.pone.0118926 ◽

2015 ◽

Vol 10 (3) ◽

pp. e0118926 ◽

Cited By ~ 32

Author(s):

Kyle G. Halvorson ◽

Kelly L. Barton ◽

Kristin Schroeder ◽

Katherine L. Misuraca ◽

Christine Hoeman ◽

...

Keyword(s):

Mouse Model ◽

High Throughput ◽

Therapeutic Agent ◽

Diffuse Intrinsic Pontine Glioma ◽

Genetically Engineered ◽

Drug Screen ◽

Pontine Glioma ◽

Genetically Engineered Mouse Model ◽

Promising Therapeutic Agent

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Diverse tumour susceptibility in Collaborative Cross mice: identification of a new mouse model for human gastric tumourigenesis

Gut ◽

10.1136/gutjnl-2018-316691 ◽

2019 ◽

Vol 68 (11) ◽

pp. 1942-1952 ◽

Cited By ~ 5

Author(s):

Pin Wang ◽

Yunshan Wang ◽

Sasha A Langley ◽

Yan-Xia Zhou ◽

Kuang-Yu Jen ◽

...

Keyword(s):

Inflammatory Response ◽

Mouse Model ◽

Rna Sequencing ◽

Genetic Association ◽

Association Analysis ◽

Collaborative Cross ◽

Sequencing Analysis ◽

Genetic Association Analysis ◽

Mouse Population ◽

Wide Range

ObjectiveThe Collaborative Cross (CC) is a mouse population model with diverse and reproducible genetic backgrounds used to identify novel disease models and genes that contribute to human disease. Since spontaneous tumour susceptibility in CC mice remains unexplored, we assessed tumour incidence and spectrum.DesignWe monitored 293 mice from 18 CC strains for tumour development. Genetic association analysis and RNA sequencing were used to identify susceptibility loci and candidate genes. We analysed genomes of patients with gastric cancer to evaluate the relevance of genes identified in the CC mouse model and measured the expression levels of ISG15 by immunohistochemical staining using a gastric adenocarcinoma tissue microarray. Association of gene expression with overall survival (OS) was assessed by Kaplan-Meier analysis.ResultsCC mice displayed a wide range in the incidence and types of spontaneous tumours. More than 40% of CC036 mice developed gastric tumours within 1 year. Genetic association analysis identified Nfκb1 as a candidate susceptibility gene, while RNA sequencing analysis of non-tumour gastric tissues from CC036 mice showed significantly higher expression of inflammatory response genes. In human gastric cancers, the majority of human orthologues of the 166 mouse genes were preferentially altered by amplification or deletion and were significantly associated with OS. Higher expression of the CC036 inflammatory response gene signature is associated with poor OS. Finally, ISG15 protein is elevated in gastric adenocarcinomas and correlated with shortened patient OS.ConclusionsCC strains exhibit tremendous variation in tumour susceptibility, and we present CC036 as a spontaneous laboratory mouse model for studying human gastric tumourigenesis.

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Advancing High-Throughput Phenotyping of Wheat in Early Selection Cycles

Remote Sensing ◽

10.3390/rs12030574 ◽

2020 ◽

Vol 12 (3) ◽

pp. 574 ◽

Cited By ~ 2

Author(s):

Yuncai Hu ◽

Samuel Knapp ◽

Urs Schmidhalter

Keyword(s):

Grain Yield ◽

Plant Breeding ◽

High Throughput ◽

Complex Traits ◽

New Technologies ◽

Early Selection ◽

Spectral Indices ◽

Wheat Genotypes ◽

High Throughput Phenotyping ◽

Spectral Sensing

Enhancing plant breeding to ensure global food security requires new technologies. For wheat phenotyping, only limited seeds and resources are available in early selection cycles. This forces breeders to use small plots with single or multiple row plots in order to include the maximum number of genotypes/lines for their assessment. High-throughput phenotyping through remote sensing may meet the requirements for the phenotyping of thousands of genotypes grown in small plots in early selection cycles. Therefore, the aim of this study was to compare the performance of an unmanned aerial vehicle (UAV) for assessing the grain yield of wheat genotypes in different row numbers per plot in the early selection cycles with ground-based spectral sensing. A field experiment consisting of 32 wheat genotypes with four plot designs (1, 2, 3, and 12 rows per plot) was conducted. Near infrared (NIR)-based spectral indices showed significant correlations (p < 0.01) with the grain yield at flowering to grain filling, regardless of row numbers, indicating the potential of spectral indices as indirect selection traits for the wheat grain yield. Compared with terrestrial sensing, aerial-based sensing from UAV showed consistently higher levels of association with the grain yield, indicating that an increased precision may be obtained and is expected to increase the efficiency of high-throughput phenotyping in large-scale plant breeding programs. Our results suggest that high-throughput sensing from UAV may become a convenient and efficient tool for breeders to promote a more efficient selection of improved genotypes in early selection cycles. Such new information may support the calibration of genomic information by providing additional information on other complex traits, which can be ascertained by spectral sensing.

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