Fascinating discoveries sometimes emerge from the most daunting of experimental roadblocks. Designed to generate over 1,000 recombinant inbred mice lines for genetic mapping, the Collaborative Cross (CC) project unearthed astounding variation in male fertility when nearly 95% of the highly inbred CC lines went extinct. As part of the Multiparental Populations series in the June issue of GENETICS, Shorter et al. use these fortuitous results to map the genetic variation underlying differences in male fertility and other reproductive traits. Their findings suggest the infertility in these lines is caused by genetic variants distributed across the genome, revealing incompatibilities between subspecies.

The CC project was designed as a powerful genetic mapping population consisting of thousands of highly inbred lines that are extremely genetically different from each other. The population founders came from several common varieties of lab mice, as well as wild-derived animals representing the three mouse subspecies. All of these lines were crossed to incorporate as much genetic variation in the population as possible. The hybrid offspring were then inbred to create high homozygosity within a line. As the lines became more and more inbred, something unexpected began to happen.

From the start, the collaborating research teams agreed they would not undertake “heroic” efforts to save lines that were struggling to persist due to high mortality or low reproduction. This policy changed as the CC lines began to go extinct at an alarming rate. In the end, 95% of the CC lines were lost despite the efforts of researchers to maintain them through between-line crosses and male fertility testing. Although some extinctions are expected as the hidden phenotypes of deleterious alleles are progressively revealed by inbreeding, the number observed far exceeded these expectations.

The culprit behind this perplexing mouse mass extinction was male infertility; nearly half of the failed lines included males that were unable to sire offspring. This gave the authors an opportunity to turn lemons into lemonade: they decided to map male reproductive traits to identify the underlying genetic basis of the problems in the extinct CC lines. They found that the contribution of the X-chromosome and the autosomes to the genomes of the extinct lines was different, with the extinct lines showing a deficit in X-linked haplotypes from the wild-derived founders. This suggests selection against retaining wild alleles at X-linked genes during the inbreeding process. Looking more closely at the extinct lines, they found very high variability in sperm count, sperm motility, and reproductive organ weights. They performed QTL mapping on fertility and reproductive traits using the extinct CC lines and identified several loci across the genome associated with variation in reproductive phenotypes. One identified locus on the X-chromosome contained a region previously identified as affecting hybrid incompatibility and speciation.

They also found that the majority of haplotypes associated with infertility and poor reproductive traits came from the wild-derived founders of different subspecies than common lab mice. It seems that genetic incompatibility between these distinct subspecies causes male infertility and reproductive isolation. Indeed, the surviving CC strains were found to have a deficit of genetic contributions from these founders across their entire genome.

The wild-derived mice were meant to provide as much genetic variation as possible to the CC lines, but this variation has turned out to be a double-edged sword. The crossing scheme between these diverged subspecies created new genetic combinations that disrupted male reproduction—often one of the first processes to be affected during speciation. Although the line extinction was unplanned and unwanted, it also provided a unique opportunity to dissect the genetics of male reproduction and the early stages of species isolation in mammals.

CITATION

Male Infertility Is Responsible for Nearly Half of the Extinction Observed in the Mouse Collaborative Cross  

John R. Shorter, Fanny Odet, David L. Aylor, Wenqi Pan, Chia-Yu Kao, Chen-Ping Fu, Andrew P. Morgan, Seth Greenstein, Timothy A. Bell, Alicia M. Stevans, Ryan W. Feathers, Sunny Patel, Sarah E. Cates, Ginger D. Shaw, Darla R. Miller, Elissa J. Chesler, Leonard McMillian, Deborah A. O’Brien, and Fernando Pardo-Manuel de Villena

Genetics June 2017 206: 557-572

http://www.genetics.org/content/206/2/557

https://doi.org/10.1534/genetics.116.199596

Multiparental populations (MPPs) have brought a new era in mapping complex traits, as well as new analytical challenges. To face these challenges and encourage innovation, the GSA journals launched the ongoing Multiparental Populations series in 2014. This month’s issues of GENETICS and G3 feature a bumper 16 MPP articles, timed to celebrate a new easy-to-use site for browsing the series. In line with our goal of encouraging communication across disciplinary boundaries, the “MPP People” profiles aim to introduce series authors working in a wide range of systems.

Not all sand field crickets can fly. The “short wing” morph of this species is grounded by its stumpy wings and feeble flight muscles. But because female short-wings don’t need to sink their limited resources into the costly trappings of flight, they are champion reproducers. In contrast, the “long wing” morphs can fly to new and better habitats, but produce substantially fewer eggs than their Earth-bound peers.

Libby King has long been fascinated by such dramatic tradeoffs in how organisms allocate their limited pool of energy to key traits, particularly in how they coordinate their allocation strategy with the nutritional environment.

“If they have a lot of resources and a big pool of energy, then there might be one optimal way to divvy up that pie, but if they’re really resource limited, then there might be another, better way,” says King.

During her PhD research with Daphne Fairbairn and Derek Roff at the University of California, Riverside, King investigated how the proportion of long-wing to short-wing morphs in a cricket population is influenced by variation in resource availability across the landscape. From this ecological and evolutionary perspective, King was drawn to thinking about the mechanisms behind these patterns. What are the genes involved in strategy variation? There were no easy answers.

“That’s how I got pulled into the very hard problem of how to dissect a very complex phenotype,” says King. To work on such problems, she shifted focus in her postdoc research to fruit fly genomics.

Elizabeth G. King, University of Missouri–Columbia

“Libby is really talented and has already made big contributions to the field,” says her former postdoc mentor Anthony Long at the University of California, Irvine. “She is one of the rare people with a really deep appreciation for both classical quantitative genetics and more modern molecular approaches to the dissection of complex traits.”

Working with Long and Stuart Macdonald (University of Kansas), she played a key role in the development and testing of the Drosophila Synthetic Population Resource (DSPR), a pair of multiparental populations with high power and resolution for complex trait mapping.

The DSPR is derived from 15 founder inbred lines capturing fruit fly genetic diversity from around the world. Each of the two replicate DSPR populations was created by crossing eight founder lines (seven unique, one shared by both replicates) for 50 generations and then establishing more than 800 recombinant inbred lines (RILs) per population.

Some of the main advantages of the DSPR, says King, include the very high mapping resolution and the fact that initial trait mapping requires only phenotyping of the RILs because the genome sequence of each can be imputed. During her postdoc, King developed a Hidden Markov Model method to infer the RIL sequences using dense genotyping with RAD markers and the known genome sequences of the founders.

Inbred lines also enable testing multiple phenotypes across the same genotypes. This last feature is particularly important for King now that she has established her own lab and is using the DSPR to investigate resource allocation in Drosophila.

“These are pretty complex traits that encompass all sorts of other traits, so it’s really useful to be able to measure phenotypes at those multiple levels of organization,” she says.

In a paper published in the MPP series in the June issue of GENETICS, King’s group, led by graduate student Patrick Stanley, examined a widespread resource allocation pattern: in many eukaryotes, individuals tend to live longer and reproduce less when nutrients are scarce. This is hypothesized to help conserve resources for survival while the individual waits for conditions to improve.

One potential avenue for the evolution of this pattern is the highly conserved insulin/insulin-like growth factor/Target of Rapamycin (IIS/TOR) pathway. In many models, knockouts for genes in this pathway live longer than wild-type, and there is substantial evidence that the pathway is involved in coordinating growth and metabolism with nutritional conditions. Changing expression of these IIS/TOR genes is often hypothesized to drive the lifespan/reproduction shift seen in low nutrient conditions.

Stanley et al. used the DSPR to investigate the link between this pathway and the nutrient-induced lifespan shift by focusing on 56 core IIS/TOR genes. They assayed how expression of these genes changed on three different diets, mapped genetic variation influencing these responses, and then measured lifespan of a subset of flies under these conditions.

As expected, most genes in the pathway changed expression between diet conditions. The team successfully mapped the genetic basis for these changes, including two trans QTLs that likely represent transcription factors that respond to diet.

But, consistent with mixed results emerging elsewhere in the literature, the results do not provide strong evidence that IIS/TOR gene expression changes drive the lifespan response to diet. They observed relatively small expression changes in most genes, rather than strong changes at a few key genes, and these were not in the direction you would predict based on knockout mutant phenotypes. “There is a change in global gene expression in response to diet, and this may well be partially driving what’s going on, but it’s clearly not the whole story,” says King.

Detail from the cover of the July 2012 issue of GENETICS, which included an article describing the properties of the Drosophila Synthetic Population Resource (DSPR). The center image represents the 15 inbred founder lines used to create the DSPR (blue = A population, red = B population, center purple fly representing the founder line shared between the populations). The background shows a sample of 100 RILs with the colors representing the founder ancestry across the genome. White areas represent an uncertain founder assignment.

A second MPP paper by King and Long in the June issue of G3 uses simulation to explore how an important bias affecting QTL mapping applies to large panels like the DSPR. This bias, known as the Beavis effect, is the tendency of significant QTLs to have overestimated effect sizes. This is because a test with an overestimated effect size is more likely to be found significant than one with an underestimated effect.

This phenomenon is one reason that, even for a true hit, validating a significant locus in a second population can fail if the experimental design lacks the power to detect the QTL at its true effect size. Although the Beavis effect is well established for traditional two-way QTL mapping, its importance is unknown for multiparental designs and association mapping, which can involve millions of tests.

The study revealed that the most important factor affecting the strength of the Beavis effect is the sample size, with the detail of the mapping design mattering much less. In essence, the more lines that are phenotyped, the weaker the Beavis effect becomes and the more accurate the QTL effects estimates become. Using only a few lines from the DSPR would make it is highly likely that the effect sizes of significant QTL are overestimated, and they may be difficult to validate in replicate experiments or cross-validate between different mapping designs. King and Long use their results to provide guidelines on the sample sizes needed to accurately estimate the percent effect variance of an identified QTL and the conditions under which a mapped QTL is likely to be successfully replicated.

King’s work with the DSPR has not only provided her the means to pursue her interest in the evolution of resource allocation strategies. It has also enriched the field as a whole, providing a powerful new component to the Drosophila toolkit for unraveling the molecular mechanisms of complex traits.

Read other MPP People profiles.

Browse the GSA Journals MPP series.

MPP AUTHOR:

Elizabeth G. King, University of Missouri–Columbia

MPP ARTICLES:

The Beavis Effect in Next-Generation Mapping Panels in Drosophila melanogaster

Elizabeth G. King and Anthony D. Long

Genetic Dissection of Nutrition-Induced Plasticity in Insulin/Insulin-Like Growth Factor Signaling and Median Life Span in a Drosophila Multiparent Population

Patrick D. Stanley, Enoch Ng’oma, Siri O’Day, and Elizabeth G. King

The genetic architecture of methotrexate toxicity is similar in Drosophila melanogaster and humans

Galina Kislukhin, Elizabeth G. King, Kelli N. Walters, Stuart J. Macdonald, and Anthony D. Long

Fine-Mapping Nicotine Resistance Loci in Drosophila Using a Multiparent Advanced Generation Inter-Cross Population

Tara N. Marriage, Elizabeth G. King, Anthony D. Long, and Stuart J. Macdonald

Using Drosophila melanogaster to identify chemotherapy toxicity genes

Elizabeth G. King, Galina Kislukhin, Kelli N. Walters, and Anthony D. Long

Properties and power of the Drosophila Synthetic Population Resource for the routine dissection of complex traits

Elizabeth G. King, Stuart J. Macdonald, and Anthony D. Long

The GSA Journals are proud to announce a brand new site for our Multiparental Populations (MPP) series. We’re celebrating this redesigned, easy-to-browse site with the addition of sixteen new papers from both journals to the series.

As the field of genetics has grown, the rapid development of genomic technologies has given researchers the ability to dissect genetic variation and complex trait inheritance in sophisticated ways. Now, the challenge is often analysis.

A growing community of plant and animal researchers have established multiparental populations as a way to more accurately capture genetic variation and its contribution to phenotypes of interest. Analysis of these populations is complex, and the clear communication of experimental design and methodology bolsters the community, paving the way for continuing advances.

The GSA Journals began the MPP series in 2014 to collect emerging data and transparent methods and to stimulate discussion. We have published work across a broad range of species—including mouse, maize, Drosophila, wheat, yeast, and others. We hope to foster a cross-disciplinary flow of information and to provide a rich resource of experimental and methodological data to the community. We welcome submissions to the MPP series on a continuous basis, and we accept presubmission inquiries.

Check out the new site and see how simple it is to browse and search the collection. Stay up to date with community news through the “Multiparental Populations in the News” sidebar. In line with our goal of encouraging communication across disciplinary boundaries, the “MPP People” profiles aim to introduce series authors working in a wide range of systems.

Geoffrey Morris

Andrew Morgan

Elizabeth King

The newest papers added to the series are summarized below.

GENETICS

Back to the Future: Multiparent Populations Provide the Key to Unlocking the Genetic Basis of Complex Traits

Dirk-Jan de Koning, Lauren M. McIntyre

Epistasis: Searching for Interacting Genetic Variants Using Crosses

Ian M. Ehrenreich

Epistasis refers to situations in which combinations of genetic variants have nonadditive phenotypic effects. Epistasis between two variants is more commonly explored, but higher-order interactions involving multiple variants also occur. In this editorial, Ehrenreich makes the case for exploring epistasis in quantitative genetic crosses.

Genomes of the Mouse Collaborative Cross

Anuj Srivastava, Andrew P. Morgan, Maya L. Najarian, Vishal Kumar Sarsani, J. Sebastian Sigmon, John R. Shorter, Anwica Kashfeen, Rachel C. McMullan, Lucy H. Williams, Paola Giusti-Rodríguez, Martin T. Ferris, Patrick Sullivan, Pablo Hock, Darla R. Miller, Timothy A. Bell, Leonard McMillan, Gary A. Churchill, and Fernando Pardo-Manuel de Villena

The Collaborative Cross (CC) is a panel of recombinant inbred (RI) mouse strains derived from eight founder laboratory strains. RI panels are popular because of their long-term genetic stability, which enhances reproducibility and integration of data collected across time and conditions. Characterization of their genomes can be a community effort, reducing the burden on individual users. Here, Srivastava et al. present the genomes of the CC strains using two complementary approaches as a resource to improve power and interpretation of genetic experiments. This study also provides a cautionary tale regarding the limitations imposed by such basic biological processes as mutation and selection.

Male Infertility Is Responsible for Nearly Half of the Extinction Observed in the Mouse Collaborative Cross

John R. Shorter, Fanny Odet, David L. Aylor, Wenqi Pan, Chia-Yu Kao, Chen-Ping Fu, Andrew P. Morgan, Seth Greenstein, Timothy A. Bell, Alicia M. Stevans, Ryan W. Feathers, Sunny Patel, Sarah E. Cates, Ginger D. Shaw, Darla R. Miller, Elissa J. Chesler, Leonard McMillian, Deborah A. O’Brien, and Fernando Pardo-Manuel de Villena

The extinction rate in the Collaborative Cross (CC) population is estimated at 95%. Shorter et al. analyzed fertility and reproductive phenotypes on the last unproductive males from 347 independent CC lines and performed the largest trait mapping experiment in the CC to date. Extinction in the CC is largely due to male infertility. The results from several experiments suggest that poor fertility and hybrid incompatibilities between subspecies contribute to breeding difficulties and strain extinction.

Increased Power to Dissect Adaptive Traits in Global Sorghum Diversity Using a Nested Association Mapping Population

Sophie Bouchet, Marcus O. Olatoye, Sandeep R. Marla, Ramasamy Perumal, Tesfaye Tesso, Jianming Yu, Mitch Tuinstra, and Geoffrey P. Morris

In crop species, adaptation to different agroclimatic regions creates useful variation, but also leads to genetic correlations that confound trait dissection. To address this challenge in sorghum, a widely adapted cereal crop, Bouchet et al. have developed and characterized a Nested Association Mapping (NAM) population, which reshuffles global genetic diversity for trait mapping. This manuscript describes the sorghum NAM resource, a population of 2214 recombinant inbred lines genotyped at 90,000 markers. The authors validated the NAM resource by mapping flowering time and plant height and used simulated traits to demonstrate that NAM is generally more powerful for dissection of traits under strong selection.

Genetic Dissection of Nutrition-Induced Plasticity in Insulin/Insulin-Like Growth Factor Signaling and Median Life Span in a Drosophila Multiparent Population

Patrick D. Stanley, Enoch Ng’oma, Siri O’Day, and Elizabeth G. King

The insulin/insulin-like growth factor signaling (IIS) and target of rapamycin (TOR) pathways have long been thought to be involved in how organisms respond to their nutritional environment; however, little is known about the genetic basis of naturally-occurring variation in these pathways. Stanley et al. use a multiparent population to genetically dissect diet-dependent IIS/TOR expression and connect it to diet-dependent changes in lifespan.

Structural Variation Shapes the Landscape of Recombination in Mouse

Andrew P. Morgan, Daniel M. Gatti,  Maya L. Najarian, Thomas M. Keane, Raymond J. Galante, Allan I. Pack, Richard Mott, Gary A. Churchill, and Fernando Pardo-Manuel de Villena

To study local variation in recombination rates and the impact of genetic diversity on the pattern and distribution of crossover events, Morgan et al. analyzed genotype data from 6,886 Diversity Outbred mice. They find that approximately three-quarters of crossover events occur within putative recombination hotspots. They further show that crossovers are suppressed in regions with copy number variation. They hypothesize that the epigenetic features of these regions may reflect altered chromatin structure in meiosis that results in a failure of pairing between chromosomes carrying different structural alleles.

Epistatic Networks Jointly Influence Phenotypes Related to Metabolic Disease and Gene Expression in Diversity Outbred Mice

Anna L. Tyler, Bo Ji, Daniel M. Gatti, Steven C. Munger, Gary A. Churchill, Karen L. Svenson, and Gregory W. Carter

Tyler et al. analyzed the complex genetic architecture of traits related to metabolic disease using the Diversity Outbred (DO) mouse population. By jointly analyzing epistasis across multiple phenotypes, the authors inferred a multi-scale network of quantitative trait loci (QTL) involving QTL-QTL, QTL-sex, and QTL-diet interactions that jointly influence body composition, serum markers, and transcriptome expression. They found that genetic contributions from different founder ancestries often combine to drive more extreme phenotypes, leading to the broad phenotypic diversity observed in the DO population.

G3

Inbred Strain Variant Database (ISVdb): A Repository for Probabilistically Informed Sequence Differences Among the Collaborative Cross Strains and Their Founders

Daniel Oreper, Yanwei Cai, Lisa M. Tarantino, Fernando Pardo- Manuel de Villena, William Valdar

The Collaborative Cross (CC) is a large panel of recently established multiparental recombinant inbred mouse strains. CC experimental design and analysis are facilitated by Oreper et al.’s newly developed Inbred Strain Variant Database (ISVdb), which provides easy-to-access CC sequence-based information. In particular, the ISVdb provides haplotype-imputed exonic variant data—an alternative and complement to direct sequencing of the CC, which is also not yet easily accessible. Additionally, the ISVdb 1) provides exonic variant consequences, 2) rapidly simulates F1 populations, and 3) maintains imputation uncertainty, allowing imputed CC data to be refined by upcoming sequencing. The ISVdb is accessible at http://isvdb.unc.edu/.

Loci Contributing to Boric Acid Toxicity in Two Reference Populations of Drosophila melanogaster

Michael A. Najarro, Jennifer L. Hackett, Stuart J. Macdonald

Boric acid is a widely-used household insecticide, but we do not fully understand how it leads to mortality. In this study, Najarro et al. assayed the genetic background for Boric Acid resistance by measuring resistance to the compound in a diverse set of Drosophila melanogaster strains and uncovered substantial trait variation. Several short genomic regions impact the phenotype, in one case implicating a member of a known family of detoxification enzymes. While the authors were unable to confidently identify DNA sequence changes leading to variation in toxicity, their work provides a platform for future genetic exploration of the mechanism of action of boric acid on metabolism and physiology in Drosophila.

The Beavis Effect in Next-Generation Mapping Panels in Drosophila melanogaster

Elizabeth G. King, Anthony D. Long

Two critical components of characterizing the genetic loci underlying complex traits are 1) to accurately estimate the relative contribution of mapped loci to the overall genetic variance of the trait and 2) to validate the mapped loci. Estimations of the contribution of mapped loci to the genetic variance are known to be upwardly biased. Here, King and Long quantify this effect for modern mapping techniques and shows how this bias can lead to false expectations for validating loci.

Allelic Variation in the Toll-Like Receptor Adaptor Protein Ticam2 Contributes to SARS-Coronavirus Pathogenesis in Mice

Lisa E. Gralinski, Vineet D. Menachery, Andrew P. Morgan, Allison L. Totura, Anne Beall, Jacob Kocher, Jessica Plante, D. Corinne Harrison-Shostak, Alexandra Schäfer, Fernando Pardo-Manuel de Villena, Martin T. Ferris, Ralph S. Baric

SARS-Coronavirus (CoV) caused a wide range of disease during the global outbreak, from mild respiratory illness to significant morbidity and mortality. Gralinksi et al. performed an F2 cross of two Collaborative Cross (CC) recombinant inbred lines to search for host genes that contribute to SARS-CoV resistance and susceptibility. They identified five QTL with contributions from seven of eight CC founders. One QTL was associated with multiple phenotypes including weight loss, virus titer, and lung pathology. Ticam2-/- mice confirmed the role of that gene in contributing to SARS-CoV-induced weight loss and pulmonary hemorrhage, demonstrating the importance of Toll Like Receptor signaling in protecting from coronavirus-induced disease.

Oas1b-dependent Immune Transcriptional Profiles of West Nile Virus Infection in the Collaborative Cross

Richard Green, Courtney Wilkins, Sunil Thomas, Aimee Sekine, Duncan M. Hendrick, Kathleen Voss, Renee C. Ireton, Michael Mooney, Jennifer T. Go, Gabrielle Choonoo, Sophia Jeng, Fernando Pardo-Manuel de Villena, Martin T. Ferris, Shannon McWeeney, Michael Gale

The oligoadenylate-synthetase (OAS) gene family includes Oas1b, a non-canonical OAS that lacks enzymatic activity. Full-length Oas1b is essential for protection against West Nile virus neuroinvasion and disease in inbred mouse models of infection, but how it programs innate immune defense across distinct genetic backgrounds is not defined. Green et al. examined Oas1b genetics, in vivo transcriptomics, and WNV infection among genetically distinct Collaborative Cross (CC) mouse strains. Their results reveal that Oas1b genotype and gene dosage link with novel innate immune gene expression signatures that impact specific biological pathways for WNV infection control and immunity.

Identification of Ganoderma Disease Resistance Loci Using Natural Field Infection of an Oil Palm Multiparental Population

Sébastien Tisné, Virginie Pomiès, Virginie Riou, Indra Syahputra, Benoît Cochard, Marie Denis

Stem rot caused by Ganoderma boninense is a devastating disease for oil palm, but information on the genetic architecture of Ganoderma resistance has not yet been reported. Tisné et al. implemented an original statistical modeling approach to analyze data based on 25 years of field monitoring the natural infection of an oil palm multiparental population. They identified four resistance loci in a broad genetic diversity that are relevant for breeding programs, showing that resistance is quantitative and that favorable alleles can be selected using the current reciprocal recurrent selection scheme.

Identification of Nitrogen Consumption Genetic Variants in Yeast Through QTL Mapping and Bulk Segregant RNA-Seq Analyses

Francisco A. Cubillos, Claire Brice, Jennifer Molinet, Sébastien Tisné, Valentina Abarca, Sebastián M. Tapia, Christian Oporto, Verónica García, Gianni Liti, Claudio Martínez

Nitrogen is an essential nutrient for yeast, and natural fermentation musts across the world differ in their nitrogen content. In this manuscript, Cubillos et al. studied nitrogen consumption differences under oenological conditions in the SGRP-4X, a recombinant population derived from the intercross of four parental strains. The results provided evidence of six allelic variants responsible for minor differences in consumption levels for arginine and aromatic amino acids, demonstrating the power of complex populations to unveil a larger number of small effect allelic variants.

Pedigree-Based Analysis in a Multiparental Population of Octoploid Strawberry Reveals QTL Alleles Conferring Resistance to Phytophthora cactorum

Jozer Mangandi, Sujeet Verma, Luis Osorio, Natalia A. Peres, Eric van de Weg, Vance M. Whitaker

Mangandi et al. describe the genetic locus in cultivated strawberry (Fragaria ×ananassa) that controls resistance to Phytophthora cactorum, which causes crown rots in the major strawberry production regions of the world. This locus, named FaRPc2, was discovered and analyzed in a complex breeding population arising from 139 crosses among 61 parents. The authors performed a pedigree-based analysis across families simultaneously, giving strong evidence for the presence of two different resistance alleles. The FaRPc2 locus has robust effects across a wide array of genetic backgrounds, making it an excellent target for genetic improvement of resistance.   

Approaches in Characterizing Genetic Structure and Mapping in a Rice Multiparental Population

Chitra Raghavan, Ramil Mauleon, Vanica Lacorte, Monalisa Jubay, Hein Zaw, Justine Bonifacio, Rakesh Kumar Singh, B. Emma Huang, Hei Leung

Raghavan et al. explore the genetic structure of a rice MAGIC population consisting of 1316 lines derived from eight parents. To determine the impact of missing data and errors on recombination levels and mapping resolution, they filtered the genotyping-by-sequencing data on all lines and imputed the data at varying levels of stringency. They map QTL for agronomic, biotic, and abiotic stress traits, and provide guidelines on best approaches to overall analysis pipelines, including quality control. These findings will serve as a guideline to researchers developing crop multiparent populations.

Multiparental populations (MPPs) have brought a new era in mapping complex traits, as well as new analytical challenges. To face these challenges and encourage innovation, the GSA journals launched the ongoing Multiparental Populations series in 2014. This month’s issues of GENETICS and G3 feature a bumper 16 MPP articles, timed to celebrate a new easy-to-use site for browsing the series. In line with our goal of encouraging communication across disciplinary boundaries, the “MPP People” profiles aim to introduce series authors working in a wide range of systems.

When MD/PhD student Andrew Morgan left Fernando Pardo-Manuel de Villena’s lab for clinical training earlier this year, his mentor took the loss philosophically.

“It’s actually nice to discover how much you depend on a really great student,” says Pardo-Manuel de Villena. “When they leave, there’s a big hole in the lab, and you feel that something is not working properly. But that’s a good sign of someone who is really exceptional.”

Morgan’s PhD work has spanned the diversity of Pardo-Manuel de Villena’s research program. At its heart is the study of evolutionary biology using experimental mouse genetics. “We’re trying to understand them as mice—not just some animal we use in the lab—and we’re learning how genetic variation can inform experimental design with lab strains,” says Morgan.

Andrew P. Morgan, University of North Carolina

During his undergraduate training in statistics, Morgan became interested in genetics, in part because of its elegant basic principles.  Hoping to find a career where he could both solve problems and help people, he enrolled in the MD/PhD program at the University of North Carolina.

In his PhD rotations, Morgan was drawn to Pardo-Manuel de Villena’s group by the combination of bioinformatics, evolutionary genetics, and experimental genetics—along with the lab head’s boundless intellectual energy and supportive mentorship. Morgan flourished in this environment.

“He started as a fairly well-rounded grad student, but he went from there to writing his own papers—he has a paper in G3 where he’s the only author—to taking responsibility for starting and completing new projects and new collaborations to becoming a go-to person for many people in the department,” says Pardo-Manuel de Villena.

Much of his work has involved two powerful mouse resources, the Collaborative Cross (CC) and Diversity Outbred (DO) populations, which were designed to bring wild genetic variation into the the controlled environment of the lab.

The CC population was founded by crossing eight parental strains that incorporated diversity from both lab and wild-derived mice across three sub-species. The offspring were then inbred to generate many different stable inbred lines with approximately balanced genetic contributions from all of the founders. Each of these lines is a random genetic mosaic of the founders, but individuals within a line share a largely identical genome of a known genotype. The result is a unique resource for mapping QTLs and performing other genetic experiments in mice.

The DO population is a complementary resource created by randomly crossing 300 individuals from an early stage of the CC project. Instead of a fixed number of inbred lines with reproducible genomes, each DO mouse has a distinct and unique genome. This has yielded an outbred population with equivalent genetic diversity and allele frequencies to the CC, but with the founder genotypes more extensively recombined, allowing genetic mapping to a higher resolution than possible with standard QTL mapping or with the CC population.

In a paper published this month in GENETICS in the MPP series, Morgan and colleagues used genotype data from almost 7,000 DO mice to construct a very dense recombination map to study the influence of genetic variation on meiotic recombination. This huge pool of genotypes came from data shared by many research groups who have used the DO population in their experiments.

In mammals, meiotic crossovers are concentrated in small regions of the genome known as hotspots. The new DO analysis, covering more than 2.2 million crossover events, revealed that recombination is strongly suppressed in larger, spatially clustered coldspots that together make up about 12% of the observable genome. To investigate further, the team analyzed the whole-genome sequences of more than 200 DO mice and demonstrated that the recombination coldspots are strongly associated with segregating copy number variants. This work has established the importance of common structural variants in shaping recombination patterns and the utility of multiparental populations for bridging the gap between fine-scale and large-scale genetic mapping.

As well as performing mapping studies using the CC and DO mice, Morgan has played key roles in the development of new tools for their use, including mouse genotyping arrays optimized for subspecies-level genetic diversity and other analytical and bioinformatic resources.

The eight founder strains of the Collaborative Cross mouse population. Photo: Brynn Voy, Oak Ridge National Laboratory.

During the epic cross-lab, cross-continental generation of the CC inbred lines, a number of unexpected observations have proven important. One was the unearthing of genetic incompatibilities between subspecies that greatly complicated the logistics of strain development but also revealed new insights into male fertility in mammals (see this month’s “On the Cover” post). A second curious result was that the allele frequency of a region on chromosome 2 was steadily drifting upward over the generations. Another grad student in the Pardo-Manuel de Villena lab, John Didion, showed that this evolution was due to a phenomenon known as meiotic drive. This means an allele was being preferentially transmitted during meiosis, violating Mendel’s law of random segregation.

Working together, Didion and Morgan found that the allele was a copy number expansion prevalent in wild populations of one of the subspecies used to found the CC. Not only had the allele repeatedly swept through lab populations like the CC, the same thing appeared to have happened in wild populations, all in spite of the fact that inheriting the allele seems to hamper reproductive success. Female mice heterozygous for this allele tend to have smaller litters in the lab than either homozygote–likely due to some degree of embryonic lethality associated with meiotic drive. This is a fascinating example of a selfish element that succeeds entirely through chromosomal mechanics, despite harming the fitness of individuals that carry it. “It bends several of the rules of how genetics is supposed to work,” says Morgan.

The discovery is not only relevant to evolutionary biologists: identifying this genetic hitchhiker allowed it to be purged from the DO population, restoring Mendelian transmission ratios to chromosome 2, where the gene resides, and preventing any potential analytical artefacts in future DO experiments.

After a productive PhD experience, Morgan is starting again at the bottom in his clinical training. “It’s kind of like going back to zero,” he says. But Pardo-Manuel de Villena is confident he will do as well in the clinic as he did in his research training. “He is smart, he has initiative, he is mature, and he is kind. That is a great combination.”

Read other MPP People profiles.

Browse the GSA Journals MPP series.

MPP AUTHOR:

Andrew P. Morgan, University of North Carolina

MPP ARTICLES:

Structural Variation Shapes the Landscape of Recombination in Mouse

Andrew P. Morgan, Daniel M. Gatti,  Maya L. Najarian, Thomas M. Keane, Raymond J. Galante, Allan I. Pack, Richard Mott, Gary A. Churchill, and Fernando Pardo-Manuel de Villena

Genomes of the Mouse Collaborative Cross

Anuj Srivastava, Andrew P. Morgan, Maya L. Najarian, Vishal Kumar Sarsani, J. Sebastian Sigmon, John R. Shorter, Anwica Kashfeen, Rachel C. McMullan, Lucy H. Williams, Paola Giusti-Rodríguez, Martin T. Ferris, Patrick Sullivan, Pablo Hock, Darla R. Miller, Timothy A. Bell, Leonard McMillan, Gary A. Churchill, and Fernando Pardo-Manuel de Villena

Male Infertility Is Responsible for Nearly Half of the Extinction Observed in the Mouse Collaborative Cross

John R. Shorter, Fanny Odet, David L. Aylor, Wenqi Pan, Chia-Yu Kao, Chen-Ping Fu, Andrew P. Morgan, Seth Greenstein, Timothy A. Bell, Alicia M. Stevans, Ryan W. Feathers, Sunny Patel, Sarah E. Cates, Ginger D. Shaw, Darla R. Miller, Elissa J. Chesler, Leonard McMillian, Deborah A. O’Brien, and Fernando Pardo-Manuel de Villena

Allelic Variation in the Toll-Like Receptor Adaptor Protein Ticam2 Contributes to SARS-Coronavirus Pathogenesis in Mice

Lisa E. Gralinski, Vineet D. Menachery, Andrew P. Morgan, Allison L. Totura, Anne Beall, Jacob Kocher, Jessica Plante, D. Corinne Harrison-Shostak, Alexandra Schäfer, Fernando Pardo-Manuel de Villena, Martin T. Ferris, Ralph S. Baric

Diversity Outbred Mice at 21: Maintaining Allelic Variation in the Face of Selection

Elissa J. Chesler, Daniel M. Gatti, Andrew P. Morgan, Marge Strobel, Laura Trepanier, Denesa Oberbeck, Shannon McWeeney, Robert Hitzemann, Martin Ferris, Rachel McMullan, Amelia Clayshultle, Timothy A. Bell, Fernando Pardo Manuel de Villena and Gary A. Churchill

The Evolutionary Fates of a Large Segmental Duplication in Mouse

Andrew P. Morgan, J. Matthew Holt, Rachel C. McMullan, Timothy A. Bell, Amelia M.-F. Clayshulte, John P. Didion, Liran Yadgary, David Thybert, Duncan T. Odom, Paul Flicek, Leonard McMillan and Fernando Pardo-Manuel de Villena

The Mouse Universal Genotyping Array: From Substrains to Subspecies

Andrew P. Morgan, J. Matthew Holt, Rachel C. McMullan, Timothy A. Bell, Amelia M.-F. Clayshulte, John P. Didion, Liran Yadgary, David Thybert, Duncan T. Odom, Paul Flicek, Leonard McMillan and Fernando Pardo-Manuel de Villena

argyle: An R Package for Analysis of Illumina Genotyping Arrays

Andrew P. Morgan

Whole Genome Sequence of Two Wild-Derived Mus musculus domesticus Inbred Strains, LEWES/EiJ and ZALENDE/EiJ, with Different Diploid Numbers

Andrew P. Morgan, John P. Didion, Anthony G. Doran, James M. Holt, Leonard McMillan, Thomas M. Keane and Fernando Pardo-Manuel de Villena

High-Resolution Sex-Specific Linkage Maps of the Mouse Reveal Polarized Distribution of Crossovers in Male Germline

Eric Yi Liu, Andrew P. Morgan, Elissa J. Chesler, Wei Wang, Gary A. Churchill and Fernando Pardo-Manuel de Villena

Multiparental populations (MPPs) have brought a new era in mapping complex traits, as well as new analytical challenges. To face these challenges and encourage innovation, the GSA journals launched the ongoing Multiparental Populations series in 2014. This month’s issues of GENETICS and G3 feature a bumper 16 MPP articles, timed to celebrate a new easy-to-use site for browsing the series. In line with our goal of encouraging communication across disciplinary boundaries, the “MPP People” profiles aim to introduce series authors working in a wide range of systems.

The first time Geoffrey Morris walked out into the acres of sorghum growing up in the nested association mapping (NAM) panel, he was confronted with the extraordinary diversity of this ancient crop. While some stalks towered overhead, others grazed knee-height. The heads of grain puffed up in an earthy rainbow—pale yellows, deep reds, orange rusts, and smoky greys— in shapes that ranged from compact orbs to drooping plumes.

“Seeing this incredible diversity and knowing we had the conceptual tools to make sense of it was a wonderful experience,” Morris says.

Morris’ work with the NAM could eventually make a difference to the 500 million smallholder farmers across the world who depend on sorghum. But his journey started in a much more abstract field.

Geoffrey Morris, Kansas State University

Morris was first drawn to research by his interest in evolution and adaptation, and he started his PhD training around the time the first yeast comparative genomics datasets were emerging. His thesis work focused on computational analysis of gene expression evolution in yeast, but part-way through his degree he began to have doubts about his professional direction.

“I realized I wanted to find a way to apply evolutionary genetics to real world problems,” he says.

After a postdoctoral project working on the bioenergy crop switchgrass, Morris set his focus on sorghum.

Although evolutionary studies and crop genetics have many intellectual connections and common roots, in cultural terms these fields have drifted apart since the days of the early geneticists like Nikolai Vavilov. That makes Morris unusual.

“What’s fascinating is he’s got this great background in ecological and evolutionary genetics and a good grounding in quantitative genetics, and he’s been able to really take that knowledge and apply it to crop genetics, ” says Ed Buckler (US Department of Agriculture).

Buckler led the development of the NAM approach and its first application in maize, and he is currently working with Morris and Gael Pressoir (CHIBAS Haiti, Quisqueya University) on a new USAID-supported project to implement genomic selection in the Haitian sorghum breeding program. The project builds in part on Morris’ work predicting adaptive traits in sorghum by identifying SNPs associated with the environmental origin of the different varieties, an example of how the insights of adaptation genetics are being put to work for sorghum farmers.

The species is a good model for such approaches, says Morris, because its incredible phenotypic diversity comes with a smaller, more tractable genome than many other cereals. “It’s such a fun system to work on,” he says.

Sorghum. Photo credit: Lawrence Berkeley Nat’l Lab – Roy Kaltschmidt, photographer. Shared under a CC BY-NC-ND 2.0 license.

Sorghum is one of the most important crops of semi-arid regions of the world. In many parts of Africa and Asia, it is a staple food that is also used for animal fodder and brewing beer, while in the US it is primarily grown as livestock feed and to make bioethanol. As a drought tolerant and versatile crop, the importance of sorghum will likely increase as global climates change.

Morris’ lab works closely with the national crop improvement programs of Senegal and Niger, which are developing new sorghum varieties to handle environmental stresses and to meet the needs of farmers. In this partnership, the US scientists primarily contribute resources for genomic assisted breeding, as well as training (Morris is mentoring two grad students from these programs). In exchange, his group learns from the African scientists’ expertise on crop diversity and the challenging production environment.

Originating in Africa between 5,000 and 10,000 years ago, the crop’s unusual diversity may have arisen through some combination of its long history of domestication around the world, adaptation to the enormous range of climates and geographies in which it is grown, and the wide variety of uses it has been bred for.

But this genetic diversity is a double-edged sword, says Morris. On the one hand, it provides a huge amount of scope for breeders creating new and improved varieties. On the other hand, managing this diversity in a controlled breeding program is a constant struggle. For example, genome-wide association mapping in sorghum is complicated by the large number of local varieties that have diverged through selection and/or inbreeding, because population structure can generate spurious associations between alleles and traits.

Multiparental linkage designs, such as NAM populations, break up such population structure by crossing locally diverged varieties, and should thereby sidestep the problem of spurious correlations and offer boosted power to map traits in sorghum.

Development of the sorghum NAM was initiated by Mitch Tuinstra (now at Purdue) Jianming Yu (now at Iowa State University). Yu had previously played key roles with Buckler in describing the NAM concept and its application in maize. For the sorghum NAM, one common reference line was crossed with 10 diverse founders and then the progeny were inbred to generate more than 2,000 recombinant inbred lines.

Morris took over the NAM when he started his lab at Kansas State University in 2013, working with postdoc Sophie Bouchet (now at INRA, France) to finish line development, genotyping, trait validation, and simulations. In an MPP paper published in the June issue of GENETICS, Bouchet et al. describe the NAM, map the key adaptive traits of flowering time and plant height, and show the QTL for these traits were more consistently identified with the NAM than with genome-wide association mapping. Using simulations, they demonstrate that the NAM is three times more powerful at detecting QTLs under strong selection than association mapping.

At the same time as the NAM was being characterized, graduate student Marcus Olatoye used it to successfully map leaf, stem, and inflorescence architecture traits (paper in preparation).

As useful as this tool has proven, its large size makes it challenging to phenotype; to conserve resources Morris’ group is not currently growing the entire NAM population. However, he is excited for the next stage of the project: using high-throughput field phenotyping methods developed as a part of the TERRA Reference Phenotyping Platform. These approaches measure traits from the sky, using unmanned aerial vehicles for efficient phenotyping, including assaying ecophysiological features important for water use and drought tolerance.

“We have the tools now to bring together these really large, powerful mapping populations with field-based tools to measure plant performance,” says Morris. “That’s where I think we’ll really see the value of the NAM.”

Read other MPP People profiles.

Browse the GSA Journals MPP series.

MPP AUTHOR:

Geoffrey P. Morris, Kansas State University

MPP ARTICLES:

Increased Power to Dissect Adaptive Traits in Global Sorghum Diversity Using a Nested Association Mapping Population

Sophie Bouchet, Marcus O. Olatoye, Sandeep R. Marla, Ramasamy Perumal, Tesfaye Tesso, Jianming Yu, Mitch Tuinstra, and Geoffrey P. Morris

A Genomic Resource for the Development, Improvement, and Exploitation of Sorghum for Bioenergy

Zachary W. Brenton, Elizabeth A. Cooper, Mathew T. Myers, Richard E. Boyles, Nadia Shakoor, Kelsey J. Zielinski, Bradley L. Rauh, William C. Bridges, Geoffrey P. Morris, and Stephen Kresovich