The nature and identification of quantitative trait loci: a community's view

Genetic loci regulate Sarbecovirus pathogenesis: A comparison across mice and humans

Coronavirus (CoV) cause considerable morbidity and mortality in humans and other mammals, as evidenced by the emergence of Severe Acute Respiratory CoV (SARS-CoV) in 2003, Middle East Respiratory CoV (MERS-CoV) in 2012, and SARS-CoV-2 in 2019. Although poorly characterized, natural genetic variation in human and other mammals modulate virus pathogenesis, as reflected by the spectrum of clinical outcomes ranging from asymptomatic infections to lethal disease. Using multiple human epidemic and zoonotic Sarbecoviruses, coupled with murine Collaborative Cross genetic reference populations, we identify several dozen quantitative trait loci that regulate SARS-like group-2B CoV pathogenesis and replication. Under a Chr4 QTL, we deleted a candidate interferon stimulated gene, Trim14 which resulted in enhanced SARS-CoV titers and clinical disease, suggesting an antiviral role during infection. Importantly, about 60 % of the murine QTL encode susceptibility genes identified as priority candidates from human genome-wide association studies (GWAS) studies after SARS-CoV-2 infection, suggesting that similar selective forces have targeted analogous genes and pathways to regulate Sarbecovirus disease across diverse mammalian hosts. These studies provide an experimental platform in rodents to investigate the molecular-genetic mechanisms by which potential cross mammalian susceptibility loci and genes regulate type-specific and cross-SARS-like group 2B CoV replication, immunity, and pathogenesis in rodent models. Our study also provides a paradigm for identifying susceptibility loci for other highly heterogeneous and virulent viruses that sporadically emerge from zoonotic reservoirs to plague human and animal populations.

Utilization of the Winkler scale of plants using big data temperature presented by the Korea Meteorological Administration

Introduction

Rice is an important food source that can provide a stable supply of calories for most people around the world. However, owing to the recent rapid temperature rise, we are facing social issues related to the increase in the Winkler scale. In this study, a strategy for screening potential candidate genes related to the yield according to the Winkler scale is presented, and the possibility of using a candidate gene identified through sequence haplotype and homology analysis as a breeding source is suggested.

Methods

QTL for the Winkler scale was identified using a population of 120 double haploids derived from a cross between Cheongchoneg, Indica, and Nagdong, Japonica.

Results and discussion

A total of 79 candidate genes were detected in the identified QTL region, and OsHAq8 was finally screened. Through haplotype analysis, OsHAq8 was derived from the Indica group and orthologous to Graminae's activator of Hsp90 ATPase, suggesting that it is a candidate gene involved in yield according to temperature during the growing period. The expression level of OsHAq8 increased as the Winkler scale increased. The findings of this study can serve as a crucial indicator for predicting harvest time and grain quality while achieving a stable yield through marker selection and adaptation to climate change. Climate change occurs more frequently. In these situations, it is very important to predict harvest time and apply relevant candidate genes to breeding. The candidate genes presented in this study can be effectively applied to rice breeding in preparation for climate change.

Associations Between Coordination and Wearable Sensor Variables Vary by Recording Context but Not Assessment Type

Motor coordination is an important driver of development and improved coordination assessments could facilitate better screening, diagnosis, and intervention for children at risk of developmental disorders. Wearable sensors could provide data that enhance the characterization of coordination and the clinical utility of that data may vary depending on how sensor variables from different recording contexts relate to coordination. We used wearable sensors at the wrists to capture upper-limb movement in 85 children aged 6-12. Sensor variables were extracted from two recording contexts. Structured recordings occurred in the lab during a unilateral throwing task. Unstructured recordings occurred during free-living activity. The objective was to determine the influence of recording context (unstructured versus structured) and assessment type (direct vs. indirect) on the association between sensor variables and coordination. The greatest associations were between six sensor variables from the structured context and the direct measure of coordination. Worse coordination scores were associated with upper-limb movements that had higher peak magnitudes, greater variance, and less smoothness. The associations were consistent across both arms, even though the structured task was unilateral. This finding suggests that wearable sensors could be paired with a simple, structured task to yield clinically informative variables that relate to motor coordination.

Quantitative trait loci mapping for survival of virus infection and virus levels in honey bees

Israeli acute paralysis virus (IAPV) is a highly virulent, Varroa-vectored virus that is of global concern for honey bee health. Little is known about the genetic basis of honey bees to withstand infection with IAPV or other viruses. We set up and analyzed a backcross between preselected honey bee colonies of low and high IAPV susceptibility to identify quantitative trait loci (QTL) associated with IAPV susceptibility. Experimentally inoculated adult worker bees were surveyed for survival and selectively sampled for QTL analysis based on SNPs identified by whole-genome resequencing and composite interval mapping. Additionally, natural titers of other viruses were quantified in the abdomen of these workers via qPCR and also used for QTL mapping. In addition to the full dataset, we analyzed distinct subpopulations of susceptible and non-susceptible workers separately. These subpopulations are distinguished by a single, suggestive QTL on chromosome 6, but we identified numerous other QTL for different abdominal virus titers, particularly in the subpopulation that was not susceptible to IAPV. The pronounced QTL differences between the susceptible and non-susceptible subpopulations indicate either an interaction between IAPV infection and the bees' interaction with other viruses or heterogeneity among workers of a single cohort that manifests itself as IAPV susceptibility and results in distinct subgroups that differ in their interaction with other viruses. Furthermore, our results indicate that low susceptibility of honey bees to viruses can be caused by both, virus tolerance and virus resistance. QTL were partially overlapping among different viruses, indicating a mixture of shared and specific processes that control viruses. Some functional candidate genes are located in the QTL intervals, but their genomic co-localization with numerous genes of unknown function delegates any definite characterization of the underlying molecular mechanisms to future studies.

Platform for the interdisciplinary study of cardiovascular, metabolic and neurovascular diseases (PICMAN) protocol

Through extensive multisystem phenotyping, the central aim of Project PICMAN is to correlate metabolic flexibility to measures of cardiometabolic health, including myocardial diastolic dysfunction, coronary and cerebral atherosclerosis, body fat distribution and severity of non-alcoholic fatty liver disease. This cohort will form the basis of larger interventional trials targeting metabolic inflexibility in the prevention of cardiovascular disease. Participants aged 21-72 years with no prior manifest atherosclerotic cardiovascular disease (ASCVD) are being recruited from a preventive cardiology clinic and an existing cohort of non-alcoholic fatty liver disease (NAFLD) in an academic medical centre. A total of 120 patients will be recruited in the pilot phase of this study and followed up for 5 years. Those with 10-year ASCVD risk ≥ 5% as per the QRISK3 calculator are eligible. Those with established diabetes mellitus are excluded. Participants recruited undergo a detailed assessment of health behaviours and physical measurements. Participants also undergo a series of multimodality clinical phenotyping comprising cardiac tests, vascular assessments, metabolic tests, liver and neurovascular testing. Blood samples are also being collected and banked for plasma biomarkers, 'multi-omics analyses' and for generation of induced pluripotent stem cells (iPSC). Extensive evidence points to metabolic dysregulation as an early precursor of cardiovascular disease, particularly in Asia. We hypothesise that quantifiable metabolic inflexibility may be representative of an individual in his/her silent, but high-risk progression towards insulin resistance, diabetes and cardiovascular disease. The platform for interdisciplinary cardiovascular-metabolic-neurovascular diseases (PICMAN) is a pilot, prospective, multi-ethnic cohort study.

Identification of genomic loci regulating platelet plasminogen activator inhibitor-1 in mice

BACKGROUND

Plasminogen activator inhibitor-1 (PAI-1, Serpine1) is an important circulating fibrinolysis inhibitor. PAI-1 exists in 2 pools, packaged within platelet α-granules and freely circulating in plasma. Elevated plasma PAI-1 levels are associated with cardiovascular disease. However, little is known about the regulation of platelet PAI-1 (pPAI-1).

OBJECTIVES

We investigated the genetic control of pPAI-1 levels in mice and humans.

METHODS

We measured pPAI-1 antigen levels via enzyme-linked immunosorbent assay in platelets isolated from 10 inbred mouse strains, including LEWES/EiJ (LEWES) and C57BL/6J (B6). LEWES and B6 were crossed to produce the F1 generation, B6LEWESF1. B6LEWESF1 mice were intercrossed to produce B6LEWESF2 mice. These mice were subjected to genome-wide genetic marker genotyping followed by quantitative trait locus analysis to identify pPAI-1 regulatory loci.

RESULTS

We identified differences in pPAI-1 between several laboratory strains, with LEWES having pPAI-1 levels more than 10-fold higher than those in B6. Quantitative trait locus analysis of B6LEWESF2 offspring identified a major pPAI-1 regulatory locus on chromosome 5 from 136.1 to 137.6 Mb (logarithm of the odds score, 16.2). Significant pPAI-1 modifier loci on chromosomes 6 and 13 were also identified.

CONCLUSION

Identification of pPAI-1 genomic regulatory elements provides insights into platelet/megakaryocyte-specific and cell type-specific gene expression. This information can be used to design more precise therapeutic targets for diseases where PAI-1 plays a role.

Identification of Genomic Regions Implicated in Susceptibility to Schistosoma mansoni Infection in a Murine Backcross Genetic Model

Only a small number of infected people are highly susceptible to schistosomiasis, showing high levels of infection or severe liver fibrosis. The susceptibility to schistosome infection is influenced by genetic background. To assess the genetic basis of susceptibility and identify the chromosomal regions involved, a backcross strategy was employed to generate high variation in schistosomiasis susceptibility. This strategy involved crossing the resistant C57BL/6J mouse strain with the susceptible CBA/2J strain. The resulting F1 females (C57BL/6J × CBA/2J) were then backcrossed with CBA/2J males to generate the backcross (BX) cohort. The BX mice exhibited a range of phenotypes, with disease severity varying from mild to severe disease, lacking a fully resistant group. We observed four levels of infection intensity using cluster and principal component analyses and K-means based on parasitological, pathological, and immunological trait measurements. The mice were genotyped with 961 informative SNPs, leading to the identification of 19 new quantitative trait loci (QTL) associated with parasite burden, liver lesions, white blood cell populations, and antibody responses. Two QTLs located on chromosomes 15 and 18 were linked to the number of granulomas, liver lesions, and IgM levels. The corresponding syntenic human regions are located in chromosomes 8 and 18. None of the significant QTLs had been reported previously.

Nanopore sequencing technology and its applications

Since the development of Sanger sequencing in 1977, sequencing technology has played a pivotal role in molecular biology research by enabling the interpretation of biological genetic codes. Today, nanopore sequencing is one of the leading third-generation sequencing technologies. With its long reads, portability, and low cost, nanopore sequencing is widely used in various scientific fields including epidemic prevention and control, disease diagnosis, and animal and plant breeding. Despite initial concerns about high error rates, continuous innovation in sequencing platforms and algorithm analysis technology has effectively addressed its accuracy. During the coronavirus disease (COVID-19) pandemic, nanopore sequencing played a critical role in detecting the severe acute respiratory syndrome coronavirus-2 virus genome and containing the pandemic. However, a lack of understanding of this technology may limit its popularization and application. Nanopore sequencing is poised to become the mainstream choice for preventing and controlling COVID-19 and future epidemics while creating value in other fields such as oncology and botany. This work introduces the contributions of nanopore sequencing during the COVID-19 pandemic to promote public understanding and its use in emerging outbreaks worldwide. We discuss its application in microbial detection, cancer genomes, and plant genomes and summarize strategies to improve its accuracy.

Association between Polymorphism in the Janus Kinase 2 (JAK2) Gene and Selected Performance Traits in Cattle and Sheep

The Janus Kinase 2 (JAK2) tyrosine kinase is an essential component of signal transduction of the class II cytokine receptors, including the growth hormone receptor. Therefore, it may play a crucial role in the signaling pathway of the somatotropic axis, which influences growth, development, and reproductive traits in ruminants. For this purpose, for three breeds of cattle (Hereford, Angus, and Limousin; a total of 781 individuals), two polymorphic sites located in exon 16 (rs210148032; p.Ile704Val, within pseudokinase (JH2)) and exon 23 (silent mutation rs211067160, within JH1 kinase domain) were analyzed. For two breeds of sheep (Pomeranian and Suffolk; 333 individuals in total), two polymorphic sites in exon 6 (rs160146162 and rs160146160; encoding the FERM domain) and one polymorphic site in exon 24 of the JAK2 gene (rs160146116; JH1 kinase domain) were genotyped. In our study, the associations examined for cattle were inconclusive. However, Hereford and Limousin cattle with genotypes AA (e16/RsaI) and AA (e23/HaeIII) tended to have the highest body weight and better daily gains (p ≤ 0.05). No clear tendency was observed in the selected reproductive traits. In the case of sheep, regardless of breed, individuals with the AA (e6/EarI), GG (e6/seq), and AA (e24/Hpy188III) genotypes had the highest body weights and daily gains in the study periods (p ≤ 0.01). The same individuals in the Pomeranian breed also had better fertility and lamb survival (p ≤ 0.01). To the best of our knowledge, these are the first association studies for all these polymorphic sites. Single-nucleotide polymorphisms in the JAK2 gene can serve as genetic markers for growth and selected reproductive traits in ruminants given that they are further investigated in subsequent populations and analyzed using haplotype and/or combined genotype systems.

Genome graphs detect human polymorphisms in active epigenomic state during influenza infection

Genetic variants, including mobile element insertions (MEIs), are known to impact the epigenome. We hypothesized that genome graphs, which encapsulate genetic diversity, could reveal missing epigenomic signals. To test this, we sequenced the epigenome of monocyte-derived macrophages from 35 ancestrally diverse individuals before and after influenza infection, allowing us to investigate the role of MEIs in immunity. We characterized genetic variants and MEIs using linked reads and built a genome graph. Mapping epigenetic data revealed 2.3%-3% novel peaks for H3K4me1, H3K27ac chromatin immunoprecipitation sequencing (ChIP-seq), and ATAC-seq. Additionally, the use of a genome graph modified some quantitative trait loci estimates and revealed 375 polymorphic MEIs in an active epigenomic state. Among these is an AluYh3 polymorphism whose chromatin state changed after infection and was associated with the expression of TRIM25, a gene that restricts influenza RNA synthesis. Our results demonstrate that graph genomes can reveal regulatory regions that would have been overlooked by other approaches.

Portable nanopore-sequencing technology: Trends in development and applications

Sequencing technology is the most commonly used technology in molecular biology research and an essential pillar for the development and applications of molecular biology. Since 1977, when the first generation of sequencing technology opened the door to interpreting the genetic code, sequencing technology has been developing for three generations. It has applications in all aspects of life and scientific research, such as disease diagnosis, drug target discovery, pathological research, species protection, and SARS-CoV-2 detection. However, the first- and second-generation sequencing technology relied on fluorescence detection systems and DNA polymerization enzyme systems, which increased the cost of sequencing technology and limited its scope of applications. The third-generation sequencing technology performs PCR-free and single-molecule sequencing, but it still depends on the fluorescence detection device. To break through these limitations, researchers have made arduous efforts to develop a new advanced portable sequencing technology represented by nanopore sequencing. Nanopore technology has the advantages of small size and convenient portability, independent of biochemical reagents, and direct reading using physical methods. This paper reviews the research and development process of nanopore sequencing technology (NST) from the laboratory to commercially viable tools; discusses the main types of nanopore sequencing technologies and their various applications in solving a wide range of real-world problems. In addition, the paper collates the analysis tools necessary for performing different processing tasks in nanopore sequencing. Finally, we highlight the challenges of NST and its future research and application directions.

Comparative analysis of 84 chloroplast genomes of Tylosema esculentum reveals two distinct cytotypes

Tylosema esculentum (marama bean) is an important orphan legume from southern Africa that has long been considered to have the potential to be domesticated as a crop. The chloroplast genomes of 84 marama samples collected from various geographical locations in Namibia and Pretoria were compared in this study. The cp genomes were analyzed for diversity, including SNPs, indels, structural alterations, and heteroplasmy. The marama cp genomes ranged in length from 161,537 bp to 161,580 bp and contained the same sets of genes, including 84 protein-coding genes, 37 tRNA genes, and 8 rRNA genes. The genes rpoC2 and rpoB, and the intergenic spacers trnT-trnL and ndhG-ndhI were found to be more diverse than other regions of the marama plastome. 15 haplotypes were found to be divided into two groups, differing at 122 loci and at a 230 bp inversion. One type appears to have greater variability within the major genome present, and variations amongst individuals with this type of chloroplast genome seems to be distributed within specific geographic regions but with very limited sampling for some regions. However, deep sequencing has identified that within most of the individuals, both types of chloroplast genomes are present, albeit one is generally at a very low frequency. The inheritance of this complex of chloroplast genomes appears to be fairly constant, providing a conundrum of how the two genomes co-exist and are propagated through generations. The possible consequences for adaptation to the harsh environment in which T. esculentum survives are considered. The results pave the way for marama variety identification, as well as for understanding the origin and evolution of the bean.

Hunting for Genes Underlying Emotionality in the Laboratory Rat: Maps, Tools and Traps

Scientists have systematically investigated the hereditary bases of behaviors since the 19th century, moved by either evolutionary questions or clinically-motivated purposes. The pioneer studies on the genetic selection of laboratory animals had already indicated, one hundred years ago, the immense complexity of analyzing behaviors that were influenced by a large number of small-effect genes and an incalculable amount of environmental factors. Merging Mendelian, quantitative and molecular approaches in the 1990s made it possible to map specific rodent behaviors to known chromosome regions. From that point on, Quantitative Trait Locus (QTL) analyses coupled with behavioral and molecular techniques, which involved in vivo isolation of relevant blocks of genes, opened new avenues for gene mapping and characterization. This review examines the QTL strategy applied to the behavioral study of emotionality, with a focus on the laboratory rat. We discuss the challenges, advances and limitations of the search for Quantitative Trait Genes (QTG) playing a role in regulating emotionality. For the past 25 years, we have marched the long journey from emotionality-related behaviors to genes. In this context, our experiences are used to illustrate why and how one should move forward in the molecular understanding of complex psychiatric illnesses. The promise of exploring genetic links between immunological and emotional responses are also discussed. New strategies based on humans, rodents and other animals (such as zebrafish) are also acknowledged, as they are likely to allow substantial progress to be made in the near future.

Phenotypic and Genetic Evidence for a More Prominent Role of Blood Glucose than Cholesterol in Atherosclerosis of Hyperlipidemic Mice

Hyperlipidemia and type 2 diabetes (T2D) are major risk factors for atherosclerosis. Apoe-deficient (Apoe−/−) mice on certain genetic backgrounds develop hyperlipidemia, atherosclerosis, and T2D when fed a Western diet. Here, we sought to dissect phenotypic and genetic relationships of blood lipids and glucose with atherosclerotic plaque formation when the vasculature is exposed to high levels of cholesterol and glucose. Male F2 mice were generated from LP/J and BALB/cJ Apoe−/− mice and fed a Western diet for 12 weeks. Three significant QTL Ath51, Ath52 and Ath53 on chromosomes (Chr) 3 and 15 were mapped for atherosclerotic lesions. Ath52 on proximal Chr15 overlapped with QTL for plasma glucose, non-HDL cholesterol, and triglyceride. Atherosclerotic lesion sizes showed significant correlations with fasting, non-fasting glucose, non-fasting triglyceride, and body weight but no correlation with HDL, non-HDL cholesterol, and fasting triglyceride levels. Ath52 for atherosclerosis was down-graded from significant to suggestive level after adjustment for fasting, non-fasting glucose, and non-fasting triglyceride but minimally affected by HDL, non-HDL cholesterol, and fasting triglyceride. Adjustment for body weight suppressed Ath52 but elevated Ath53 on distal Chr15. These results demonstrate phenotypic and genetic connections of blood glucose and triglyceride with atherosclerosis, and suggest a more prominent role for blood glucose than cholesterol in atherosclerotic plaque formation of hyperlipidemic mice.

stuart: an R package for the curation of SNP genotypes from experimental crosses

Genetic mapping in 2-generation crosses requires genotyping, usually performed with single nucleotide polymorphism markers arrays which provide high-density genetic information. However, genetic analysis on raw genotypes can lead to spurious or unreliable results due to defective single nucleotide polymorphism assays or wrong genotype interpretation. Here, we introduce stuart, an open-source R package, which analyzes raw genotyping data to filter single nucleotide polymorphism markers based on informativeness, Mendelian inheritance pattern, and consistency with parental genotypes. The functions of this package provide a curation pipeline and formatting adequate for genetic analysis with the R/qtl package. stuart is available with detailed documentation from https://gitlab.pasteur.fr/mouselab/stuart/.

Genetic connection of carotid atherosclerosis with coat color and body weight in an intercross between hyperlipidemic mouse strains

Atherosclerosis in the carotid artery is a major cause of ischemic stroke and has a strong genetic component. The aim of this study was to identify genetic factors contributing to carotid atherosclerosis. 154 female F2mice were generated from an intercross between LP/J and BALB/cJ Apoe-null (Apoe^-/-) mice and fed 12 weeks of Western diet. Atherosclerotic lesions, body weight, and coat color were measured and genotyping was performed using miniMUGA arrays. A significant QTL on chromosome (Chr) 7, named Cath20, and 5 suggestive QTL on Chr 6, 12, 13, 15, and X were identified for carotid lesions. Three significant QTL, Bwfq2, Bw1n, Bwtq6, on Chr 2, 7, and 15 were identified for body weight. Two significant QTL, Chop2 and Albc2, on Chr 4 and 7 were identified for coat color, with Tyr, encoding tyrosinase, being the causal gene of Albc2. Cath20 coincided precisely with QTL Bw1n and Albc2 on Chr7. Carotid lesion sizes were significantly correlated with body weight and graded coat color in F2 mice. Cath20 on Chr7 disappeared after adjustment for coat color but remained after adjustment for body weight. These results demonstrate genetic connections of carotid atherosclerosis with body weight and coat color in hyperlipidemic mice and suggest a potential role for Tyr in carotid atherosclerosis.

Beyond Genes: Inclusion of Alternative Splicing and Alternative Polyadenylation to Assess the Genetic Architecture of Predisposition to Voluntary Alcohol Consumption in Brain of the HXB/BXH Recombinant Inbred Rat Panel

Post transcriptional modifications of RNA are powerful mechanisms by which eukaryotes expand their genetic diversity. For instance, researchers estimate that most transcripts in humans undergo alternative splicing and alternative polyadenylation. These splicing events produce distinct RNA molecules, which in turn yield distinct protein isoforms and/or influence RNA stability, translation, nuclear export, and RNA/protein cellular localization. Due to their pervasiveness and impact, we hypothesized that alternative splicing and alternative polyadenylation in brain can contribute to a predisposition for voluntary alcohol consumption. Using the HXB/BXH recombinant inbred rat panel (a subset of the Hybrid Rat Diversity Panel), we generated over one terabyte of brain RNA sequencing data (total RNA) and identified novel splice variants (via StringTie) and alternative polyadenylation sites (via aptardi) to determine the transcriptional landscape in the brains of these animals. After establishing an analysis pipeline to ascertain high quality transcripts, we quantitated transcripts and integrated genotype data to identify candidate transcript coexpression networks and individual candidate transcripts associated with predisposition to voluntary alcohol consumption in the two-bottle choice paradigm. For genes that were previously associated with this trait (e.g., Lrap, Ift81, and P2rx4) (Saba et al., Febs. J., 282, 3556–3578, Saba et al., Genes. Brain. Behav., 20, e12698), we were able to distinguish between transcript variants to provide further information about the specific isoforms related to the trait. We also identified additional candidate transcripts associated with the trait of voluntary alcohol consumption (i.e., isoforms of Mapkapk5, Aldh1a7, and Map3k7). Consistent with our previous work, our results indicate that transcripts and networks related to inflammation and the immune system in brain can be linked to voluntary alcohol consumption. Overall, we have established a pipeline for including the quantitation of alternative splicing and alternative polyadenylation variants in the transcriptome in the analysis of the relationship between the transcriptome and complex traits.

Genetic Connection between Hyperglycemia and Carotid Atherosclerosis in Hyperlipidemic Mice

Type 2 diabetes (T2D) is a major risk for atherosclerosis and its complications. Apoe-null (Apoe^−/−) mouse strains exhibit a wide range of variations in susceptibility to T2D and carotid atherosclerosis, with the latter being a major cause of ischemic stroke. To identify genetic connections between T2D and carotid atherosclerosis, 145 male F2 mice were generated from LP/J and BALB/cJ Apoe^−/− mice and fed 12 weeks of a Western diet. Atherosclerotic lesions in the carotid arteries, fasting, and non-fasting plasma glucose levels were measured, and genotyping was performed using miniMUGA arrays. Two significant QTL (quantitative trait loci) on chromosomes (Chr) 6 and 15 were identified for carotid lesions. The Chr15 QTL coincided precisely with QTL Bglu20 for fasting and non-fasting glucose levels. Carotid lesion sizes showed a trend toward correlation with fasting and non-fasting glucose levels in F2 mice. The Chr15 QTL for carotid lesions was suppressed after excluding the influence from fasting or non-fasting glucose. Likely candidate genes for the causal association were Tnfrsf11b, Deptor, and Gsdmc2. These results demonstrate a causative role for hyperglycemia in the development of carotid atherosclerosis in hyperlipidemic mice.

Dog Models of Aging

As the most phenotypically diverse mammalian species that shares human environments and access to sophisticated healthcare, domestic dogs have unique potential to inform our understanding of the determinants of aging. Here we outline key concepts in the study of aging and illustrate the value of research with dogs, which can improve dog health and support translational discoveries. We consider similarities and differences in aging and age-related diseases in dogs and humans and summarize key advances in our understanding of genetic and environmental risk factors for morbidity and mortality in dogs. We address health outcomes ranging from cancer to cognitive function and highlight emerging research opportunities from large-scale cohort studies in companion dogs. We conclude that studying aging in dogs could overcome many limitations of laboratory models, most notably, the ability to assess how aging-associated pathways influence aging in real-world environments similar to those experienced by humans.

Genotype and Phenotype Interaction between OsWKRYq6 and BLB after Xanthomonas oryzae pv. Oryzae Inoculation in the Field

Bacterial leaf blight (BLB) is an important and devastating rice disease caused by the pathogen Xanthomonas oryzae pv. Oryzae (Xoo). In particular, in recent years, the occurrence of abnormal climate and warming phenomena has produced a good environment for the occurrence of BLB, and the rice yield due to the occurrence of BLB continues to decrease. Currently, molecular breeding is applied by searching for resistant genes to development of BLB resistance cultivar. In addition, there are many methods for screening resistant genes, and among them, phenotype analysis in the field and applied research is rarely conducted. Due to recent rapid climate change, BLB is a major problem that has a more serious negative effect on rice yield. Therefore, we suggest OsWRKYq6 to be effectively used for breeding BLB-resistant cultivars by screening BLB-resistant genes. In this study, the BLB-resistant gene was screened using the lesion length, which most definitely changes to the phenotype when Xoo is infected. OsWRKYq6 was finally selected as a BLB resistance gene by analyzing the phenotype and genotype after inoculating Xoo in 120 Cheongcheong/Nagdong double haploid (CNDH) lines in the field. After Xoo inoculation, lesion length and yield were investigated, and 120 CNDH lines were divided from BLB-resistant and susceptible lines. Moreover, when the transcription level of OsWRKYq6 was analyzed in the resistant and susceptible lines after Xoo inoculation in the field, the expression level was regulated to a high level in the resistant line. In this study, we propose OsWRKYq6 as a transcription factor involved in BLB resistance. Currently, the differentiation of various races is proceeding rapidly due to rapid climate change. In addition, screening of transcription factor genes involved in BLB resistance in the field can be effectively applied to molecular breeding to develop resistant cultivars in preparation for rapid climate change.

Whole Exome-Sequencing of Pooled Genomic DNA Samples to Detect Quantitative Trait Loci in Esotropia and Exotropia of Strabismus in Japanese

BACKGROUND

Esotropia and exotropia are two major phenotypes of comitant strabismus. It remains controversial whether esotropia and exotropia would share common genetic backgrounds. In this study, we used a quantitative trait locus (QTL)-sequencing pipeline for diploid plants to screen for susceptibility loci of strabismus in whole exome sequencing of pooled genomic DNAs of individuals.

METHODS

Pooled genomic DNA (2.5 ng each) of 20 individuals in three groups, Japanese patients with esotropia and exotropia, and normal members in the families, was sequenced twice after exome capture, and the first and second sets of data in each group were combined to increase the read depth. The SNP index, as the ratio of variant genotype reads to all reads, and Δ(SNP index) values, as the difference of SNP index between two groups, were calculated by sliding window analysis with a 4 Mb window size and 10 kb slide size. The rows of 200 "N"s were inserted as a putative 200-b spacer between every adjoining locus to depict Δ(SNP index) plots on each chromosome. SNP positions with depth < 20 as well as SNP positions with SNP index of <0.3 were excluded.

RESULTS

After the exclusion of SNPs, 12,242 SNPs in esotropia/normal group and 12,108 SNPs in exotropia/normal group remained. The patterns of the Δ(SNP index) plots on each chromosome appeared different between esotropia/normal group and exotropia/normal group. When the consecutive groups of SNPs on each chromosome were set at three patterns: SNPs in each cytogenetic band, 50 consecutive sliding SNPs, and SNPs in 4 Mb window size with 10 kb slide size, p values (Wilcoxon signed rank test) and Q values (false discovery rate) in a few loci as Manhattan plots showed significant differences in comparison between the Δ(SNP index) in the esotropia/normal group and exotropia/normal group.

CONCLUSIONS

The pooled DNA sequencing and QTL mapping approach for plants could provide overview of genetic background on each chromosome and would suggest different genetic backgrounds for two major phenotypes of comitant strabismus, esotropia and exotropia.

Analytical and numerical comparisons of two methods of estimation of additive × additive × additive interaction of QTL effects

This paper presents the analytical and numerical comparison of two methods of estimation of additive × additive × additive (aaa) interaction of QTL effects. The first method takes into account only the plant phenotype, while in the second we also included genotypic information from molecular marker observation. Analysis was made on 150 doubled haploid (DH) lines of barley derived from cross Steptoe × Morex and 145 DH lines from Harrington × TR306 cross. In total, 153 sets of observation was analyzed. In most cases, aaa interactions were found with an exert effect on QTL. Results also show that with molecular marker observations, obtained estimators had smaller absolute values than phenotypic estimators.

Phytophthora infestans: An Overview of Methods and Attempts to Combat Late Blight

Phytophthora infestans (Mont.) de Bary is one of the main pathogens in the agricultural sector. The most affected are the Solanaceae species, with the potato (Solanum tuberosum) and the tomato (Solanum lycopersicum) being of great agricultural importance. Ornamental Solanaceae can also host the pests Petunia spp., Calibrachoa spp., as well as the wild species Solanum dulcamara, Solanum sarrachoides, etc. Annual crop losses caused by this pathogen are highly significant. Although the interaction between P. infestans and the potato has been investigated for a long time, further studies are still needed. This review summarises the basic approaches in the fight against the late blight over the past 20 years and includes four sections devoted to methods of control: (1) fungicides; (2) R-gene-based resistance of potato species; (3) RNA interference approaches; (4) other approaches to control P. infestans. Based on the latest advances, we have provided a description of the significant advantages and disadvantages of each approach.

Epigenome-wide association studies: current knowledge, strategies and recommendations

The aetiology and pathophysiology of complex diseases are driven by the interaction between genetic and environmental factors. The variability in risk and outcomes in these diseases are incompletely explained by genetics or environmental risk factors individually. Therefore, researchers are now exploring the epigenome, a biological interface at which genetics and the environment can interact. There is a growing body of evidence supporting the role of epigenetic mechanisms in complex disease pathophysiology. Epigenome-wide association studies (EWASes) investigate the association between a phenotype and epigenetic variants, most commonly DNA methylation. The decreasing cost of measuring epigenome-wide methylation and the increasing accessibility of bioinformatic pipelines have contributed to the rise in EWASes published in recent years. Here, we review the current literature on these EWASes and provide further recommendations and strategies for successfully conducting them. We have constrained our review to studies using methylation data as this is the most studied epigenetic mechanism; microarray-based data as whole-genome bisulphite sequencing remains prohibitively expensive for most laboratories; and blood-based studies due to the non-invasiveness of peripheral blood collection and availability of archived DNA, as well as the accessibility of publicly available blood-cell-based methylation data. Further, we address multiple novel areas of EWAS analysis that have not been covered in previous reviews: (1) longitudinal study designs, (2) the chip analysis methylation pipeline (ChAMP), (3) differentially methylated region (DMR) identification paradigms, (4) methylation quantitative trait loci (methQTL) analysis, (5) methylation age analysis and (6) identifying cell-specific differential methylation from mixed cell data using statistical deconvolution.

Detecting methylation quantitative trait loci using a methylation random field method

DNA methylation may be regulated by genetic variants within a genomic region, referred to as methylation quantitative trait loci (mQTLs). The changes of methylation levels can further lead to alterations of gene expression, and influence the risk of various complex human diseases. Detecting mQTLs may provide insights into the underlying mechanism of how genotypic variations may influence the disease risk. In this article, we propose a methylation random field (MRF) method to detect mQTLs by testing the association between the methylation level of a CpG site and a set of genetic variants within a genomic region. The proposed MRF has two major advantages over existing approaches. First, it uses a beta distribution to characterize the bimodal and interval properties of the methylation trait at a CpG site. Second, it considers multiple common and rare genetic variants within a genomic region to identify mQTLs. Through simulations, we demonstrated that the MRF had improved power over other existing methods in detecting rare variants of relatively large effect, especially when the sample size is small. We further applied our method to a study of congenital heart defects with 83 cardiac tissue samples and identified two mQTL regions, MRPS10 and PSORS1C1, which were colocalized with expression QTL in cardiac tissue. In conclusion, the proposed MRF is a useful tool to identify novel mQTLs, especially for studies with limited sample sizes.

Breeding Canola (Brassica napus L.) for Protein in Feed and Food

Interest in canola (Brassica napus L.). In response to this interest, scientists have been tasked with altering and optimizing the protein production chain to ensure canola proteins are safe for consumption and economical to produce. Specifically, the role of plant breeders in developing suitable varieties with the necessary protein profiles is crucial to this interdisciplinary endeavour. In this article, we aim to provide an overarching review of the canola protein chain from the perspective of a plant breeder, spanning from the genetic regulation of seed storage proteins in the crop to advancements of novel breeding technologies and their application in improving protein quality in canola. A review on the current uses of canola meal in animal husbandry is presented to underscore potential limitations for the consumption of canola meal in mammals. General discussions on the allergenic potential of canola proteins and the regulation of novel food products are provided to highlight some of the challenges that will be encountered on the road to commercialization and general acceptance of canola protein as a dietary protein source.

Deciphering pathogenicity of variants of uncertain significance with CRISPR-edited iPSCs

Genetic variants play an important role in conferring risk for cardiovascular diseases (CVDs). With the rapid development of next-generation sequencing (NGS), thousands of genetic variants associated with CVDs have been identified by genome-wide association studies (GWAS), but the function of more than 40% of genetic variants is still unknown. This gap of knowledge is a barrier to the clinical application of the genetic information. However, determining the pathogenicity of a variant of uncertain significance (VUS) is challenging due to the lack of suitable model systems and accessible technologies. By combining clustered regularly interspaced short palindromic repeats (CRISPR) and human induced pluripotent stem cells (iPSCs), unprecedented advances are now possible in determining the pathogenicity of VUS in CVDs. Here, we summarize recent progress and new strategies in deciphering pathogenic variants for CVDs using CRISPR-edited human iPSCs.

Average semivariance yields accurate estimates of the fraction of marker-associated genetic variance and heritability in complex trait analyses

The development of genome-informed methods for identifying quantitative trait loci (QTL) and studying the genetic basis of quantitative variation in natural and experimental populations has been driven by advances in high-throughput genotyping. For many complex traits, the underlying genetic variation is caused by the segregation of one or more ‘large-effect’ loci, in addition to an unknown number of loci with effects below the threshold of statistical detection. The large-effect loci segregating in populations are often necessary but not sufficient for predicting quantitative phenotypes. They are, nevertheless, important enough to warrant deeper study and direct modelling in genomic prediction problems. We explored the accuracy of statistical methods for estimating the fraction of marker-associated genetic variance (p) and heritability (HM2) for large-effect loci underlying complex phenotypes. We found that commonly used statistical methods overestimate p and HM2. The source of the upward bias was traced to inequalities between the expected values of variance components in the numerators and denominators of these parameters. Algebraic solutions for bias-correcting estimates of p and HM2 were found that only depend on the degrees of freedom and are constant for a given study design. We discovered that average semivariance methods, which have heretofore not been used in complex trait analyses, yielded unbiased estimates of p and HM2, in addition to best linear unbiased predictors of the additive and dominance effects of the underlying loci. The cryptic bias problem described here is unrelated to selection bias, although both cause the overestimation of p and HM2. The solutions we described are predicted to more accurately describe the contributions of large-effect loci to the genetic variation underlying complex traits of medical, biological, and agricultural importance.

The contributions of individual genes to the phenotypic variation observed for genetically complex traits has been an ongoing and important challenge in biology, medicine, and agriculture. While many genes have statistically undetectable effects, those with large effects often warrant in-depth study and can be important predictors of complex phenotypes such as disease risk in humans or disease resistance in domesticated plants and animals. The genes identified through associations with genetic markers in complex trait analyses typically account for a fraction of the heritable variation, a genetic parameter we called ‘marker heritability’. We discovered that textbook statistical methods systematically overestimate marker heritability and thus overestimate the contributions of specific genes to the phenotypic variation observed for complex traits in natural and experimental populations. We describe the source of the upward bias, validate our findings through computer simulation, describe methods for bias-correcting estimates of marker heritability, and illustrate their application through empirical examples. The statistical methods we describe supply investigators with more accurate estimates of the contributions of specific genes or networks of interacting genes to the heritable variation observed in complex trait studies.

Will Plant Genome Editing Play a Decisive Role in "Quantum-Leap" Improvements in Crop Yield to Feed an Increasing Global Human Population?

Growing scientific evidence demonstrates unprecedented planetary-scale human impacts on the Earth's system with a predicted threat to the existence of the terrestrial biosphere due to population increase, resource depletion, and pollution. Food systems account for 21-34% of global carbon dioxide (CO2) emissions. Over the past half-century, water and land-use changes have significantly impacted ecosystems, biogeochemical cycles, biodiversity, and climate. At the same time, food production is falling behind consumption, and global grain reserves are shrinking. Some predictions suggest that crop yields must approximately double by 2050 to adequately feed an increasing global population without a large expansion of crop area. To achieve this, "quantum-leap" improvements in crop cultivar productivity are needed within very narrow planetary boundaries of permissible environmental perturbations. Strategies for such a "quantum-leap" include mutation breeding and genetic engineering of known crop genome sequences. Synthetic biology makes it possible to synthesize DNA fragments of any desired sequence, and modern bioinformatics tools may hopefully provide an efficient way to identify targets for directed modification of selected genes responsible for known important agronomic traits. CRISPR/Cas9 is a new technology for incorporating seamless directed modifications into genomes; it is being widely investigated for its potential to enhance the efficiency of crop production. We consider the optimism associated with the new genetic technologies in terms of the complexity of most agronomic traits, especially crop yield potential (Yp) limits. We also discuss the possible directions of overcoming these limits and alternative ways of providing humanity with food without transgressing planetary boundaries. In conclusion, we support the long-debated idea that new technologies are unlikely to provide a rapidly growing population with significantly increased crop yield. Instead, we suggest that delicately balanced humane measures to limit its growth and the amount of food consumed per capita are highly desirable for the foreseeable future.

Unveiling the Pathogenesis of Psychiatric Disorders Using Network Models

Psychiatric disorders are complex brain disorders with a high degree of genetic heterogeneity, affecting millions of people worldwide. Despite advances in psychiatric genetics, the underlying pathogenic mechanisms of psychiatric disorders are still largely elusive, which impedes the development of novel rational therapies. There has been accumulating evidence suggesting that the genetics of complex disorders can be viewed through an omnigenic lens, which involves contextualizing genes in highly interconnected networks. Thus, applying network-based multi-omics integration methods could cast new light on the pathophysiology of psychiatric disorders. In this review, we first provide an overview of the recent advances in psychiatric genetics and highlight gaps in translating molecular associations into mechanistic insights. We then present an overview of network methodologies and review previous applications of network methods in the study of psychiatric disorders. Lastly, we describe the potential of such methodologies within a multi-tissue, multi-omics approach, and summarize the future directions in adopting diverse network approaches.

How much epigenetics and quantitative trait loci (QTL) mapping tell us about parasitism maintenance and resistance/susceptibility to hosts

Interactions between the environment, parasites, vectors, and/or intermediate hosts are complex and involve several factors that define the success or failure of an infection. Among these interactions that can affect infections by a parasite, it is possible to highlight the genetic and epigenetic mechanisms in hosts and parasites. The interaction between genetics, epigenetics, infection, and the host's internal and external environment is decisive and dictates the outcome of a parasitic infection and the resistance, susceptibility, and transmission of this parasite. Epigenetic changes become important mediators in the regulation of gene expression, allowing the evasion of the parasite to immune host barriers, its transmission to new hosts, and the end of its development cycle. Epigenetics is a new frontier in the understanding of the interaction mechanisms between parasite and host that, along with information from the gene regions associated with complex phenotypic variations, the Quantitative Trait Loci, brings new possibilities to investigate more modern and efficient approaches to the treatment, control, and eradication of parasitic diseases. In this brief review, a general overview of the use of epigenetic information and mapping of Quantitative Trait Loci was summarized, both in genes of parasites and hosts, for understanding the mechanisms of resistance and/or susceptibility in parasitic relationships; also, the main search platforms were quantitatively compared, aiming to facilitate access data produced over a period of twenty years.

Mechanisms of breast cancer metastasis

Invasive breast cancer tends to metastasize to lymph nodes and systemic sites. The management of metastasis has evolved by focusing on controlling the growth of the disease in the breast/chest wall, and at metastatic sites, initially by surgery alone, then by a combination of surgery with radiation, and later by adding systemic treatments in the form of chemotherapy, hormone manipulation, targeted therapy, immunotherapy and other treatments aimed at inhibiting the proliferation of cancer cells. It would be valuable for us to know how breast cancer metastasizes; such knowledge would likely encourage the development of therapies that focus on mechanisms of metastasis and might even allow us to avoid toxic therapies that are currently used for this disease. For example, if we had a drug that targeted a gene that is critical for metastasis, we might even be able to cure a vast majority of patients with breast cancer. By bringing together scientists with expertise in molecular aspects of breast cancer metastasis, and those with expertise in the mechanical aspects of metastasis, this paper probes interesting aspects of the metastasis cascade, further enlightening us in our efforts to improve the outcome from breast cancer treatments.

Detection of grain yield QTLs in the durum population Lahn/Cham1 tested in contrasting environments

Durum wheat (Triticum turgidum L. var durum) is tetraploid wheat (AABB); it is the main source of semolina and other pasta products. Grain yield in wheat is quantitatively inherited and influenced by the environment. The genetic map construction constitutes the essential step in identifying quantitative trait loci (QTLs) linked to complex traits, such as grain yield. The study aimed to construct a genetic linkage map of two parents that are widely grown durum cultivars (Lahn and Cham1) in the Mediterranean basin, which is characterized by varying climate changes. The genetic linkage map of Lahn/Cham1 population consisted of 112 recombinant inbred lines (RILs) and was used to determine QTLs linked to the grain yield in 11 contrasting environments (favorable, cold, dry, and hot). Simple sequence repeat (SSR) molecular markers were used to construct an anchor map, which was later enriched with single nucleotide polymorphisms (SNPs). The map was constructed with 247 SSRs and enriched with 1425 SNPs. The map covered 6122.22 cM. One hundred and twenty-six QTLs were detected on different chromosomes. Chromosomes 2A and 4B harbored the most significant grain yield QTLs. Furthermore, by comparison with several wheat mapping populations, all the A and B chromosomes of Lahn/Cham1 QTLs contributed to grain yield. The results showed that the detected QTLs can be used as a potential candidate for marker-assisted selection in durum breeding programs.

Smarce1 and Tensin 4 Are Putative Modulators of Corneoscleral Stiffness

The biomechanical properties of the cornea and sclera are important in the onset and progression of multiple ocular pathologies and vary substantially between individuals, yet the source of this variation remains unknown. Here we identify genes putatively regulating corneoscleral biomechanical tissue properties by conducting high-fidelity ocular compliance measurements across the BXD recombinant inbred mouse set and performing quantitative trait analysis. We find seven cis-eQTLs and non-synonymous SNPs associating with ocular compliance, and show by RT-qPCR and immunolabeling that only two of the candidate genes, Smarce1 and Tns4, showed significant expression in corneal and scleral tissues. Both have mechanistic potential to influence the development and/or regulation of tissue material properties. This work motivates further study of Smarce1 and Tns4 for their role(s) in ocular pathology involving the corneoscleral envelope as well as the development of novel mouse models of ocular pathophysiology, such as myopia and glaucoma.

Roles of mitochondria in the hallmarks of metastasis

Although mitochondrial contributions to cancer have been recognised for approximately a century, given that mitochondrial DNA (mtDNA) is dwarfed by the size of the nuclear genome (nDNA), nuclear genetics has represented a focal point in cancer biology, often at the expense of mtDNA and mitochondria. However, genomic sequencing and advances in in vivo models underscore the importance of mtDNA and mitochondria in cancer and metastasis. In this review, we explore the roles of mitochondria in the four defined ‘hallmarks of metastasis’: motility and invasion, microenvironment modulation, plasticity and colonisation. Biochemical processes within the mitochondria of both cancer cells and the stromal cells with which they interact are critical for each metastatic hallmark. We unravel complex dynamics in mitochondrial contributions to cancer, which are context-dependent and capable of either promoting metastasis or being leveraged to prevent it at various points of the metastatic cascade. Ultimately, mitochondrial contributions to cancer and metastasis are rooted in the capacity of these organelles to tune metabolic and genetic responses to dynamic microenvironmental cues.

Designing a QTL Mapping Study for Implementation in the Realized Collaborative Cross Genetic Reference Population

The Collaborative Cross (CC) mouse resource is a next-generation mouse genetic reference population (GRP) designed for high-resolution mapping of quantitative trait loci (QTL) of large effect affecting complex traits during health and disease. The CC resource consists of a set of 72 recombinant inbred lines (RILs) generated by reciprocal crossing of five classical and three wild-derived mouse founder strains. Complex traits are controlled by variations within multiple genes and environmental factors, and their mutual interactions. These traits are observed at multiple levels of the animals' systems, including metabolism, body weight, immune profile, and susceptibility or resistance to the development and progress of infectious or chronic diseases. Herein, we present general guidelines for design of QTL mapping experiments using the CC resource-along with full step-by-step protocols and methods that were implemented in our lab for the phenotypic and genotypic characterization of the different CC lines-for mapping the genes underlying host response to infectious and chronic diseases. © 2019 by John Wiley & Sons, Inc. Basic Protocol 1: CC lines for whole body mass index (BMI) Basic Protocol 2: A detailed assessment of the power to detect effect sizes based on the number of lines used, and the number of replicates per line Basic Protocol 3: Obtaining power for QTL with given target effect by interpolating in Table 1 of Keele et al. (2019).

Seed protein content and its relationships with agronomic traits in pigeonpea is controlled by both main and epistatic effects QTLs

The genetic architecture of seed protein content (SPC) and its relationships to agronomic traits in pigeonpea is poorly understood. Accordingly, five F₂ populations segregating for SPC and four agronomic traits (seed weight (SW), seed yield (SY), growth habit (GH) and days to first flowering (DFF)) were phenotyped and genotyped using genotyping-by-sequencing approach. Five high-density population-specific genetic maps were constructed with an average inter-marker distance of 1.6 to 3.5 cM, and subsequently, integrated into a consensus map with average marker spacing of 1.6 cM. Based on analysis of phenotyping data and genotyping data, 192 main effect QTLs (M-QTLs) with phenotypic variation explained (PVE) of 0.7 to 91.3% were detected for the five traits across the five populations. Major effect (PVE ≥ 10%) M-QTLs included 14 M-QTLs for SPC, 16 M-QTLs for SW, 17 M-QTLs for SY, 19 M-QTLs for GH and 24 M-QTLs for DFF. Also, 573 epistatic QTLs (E-QTLs) were detected with PVE ranging from 6.3 to 99.4% across traits and populations. Colocalization of M-QTLs and E-QTLs explained the genetic basis of the significant (P < 0.05) correlations of SPC with SW, SY, DFF and GH. The nature of genetic architecture of SPC and its relationship with agronomic traits suggest that genomics-assisted breeding targeting genome-wide variations would be effective for the simultaneous improvement of SPC and other important traits.

Informing disease modelling with brain-relevant functional genomic annotations

The past decade has seen a surge in the number of disease/trait-associated variants, largely because of the union of studies to share genetic data and the availability of electronic health records from large cohorts for research use. Variant discovery for neurological and neuropsychiatric genome-wide association studies, including schizophrenia, Parkinson's disease and Alzheimer's disease, has greatly benefitted; however, the translation of these genetic association results to interpretable biological mechanisms and models is lagging. Interpreting disease-associated variants requires knowledge of gene regulatory mechanisms and computational tools that permit integration of this knowledge with genome-wide association study results. Here, we summarize key conceptual advances in the generation of brain-relevant functional genomic annotations and amongst tools that allow integration of these annotations with association summary statistics, which together provide a new and exciting opportunity to identify disease-relevant genes, pathways and cell types in silico. We discuss the opportunities and challenges associated with these developments and conclude with our perspective on future advances in annotation generation, tool development and the union of the two.

The JAX Synteny Browser for mouse-human comparative genomics

Visualizing regions of conserved synteny between two genomes is supported by numerous software applications. However, none of the current applications allow researchers to select genome features to display or highlight in blocks of synteny based on the annotated biological properties of the features (e.g., type, function, and/or phenotype association). To address this usability gap, we developed an interactive web-based conserved synteny browser, The Jackson Laboratory (JAX) Synteny Browser. The browser allows researchers to highlight or selectively display genome features in the reference and/or the comparison genome according to the biological attributes of the features. Although the current implementation for the browser is limited to the reference genomes for the laboratory mouse and human, the software platform is intentionally genome agnostic. The JAX Synteny Browser software can be deployed for any two genomes where genome coordinates for syntenic blocks are defined and for which biological attributes of the features in one or both genomes are available in widely used standard bioinformatics file formats. The JAX Synteny Browser is available at: http://syntenybrowser.jax.org/. The code base is available from GitHub: https://github.com/TheJacksonLaboratory/syntenybrowser and is distributed under the Creative Commons Attribution license (CC BY).

Model genotype-phenotype mappings and the algorithmic structure of evolution

Cancers are complex dynamic systems that undergo evolution and selection. Personalized medicine approaches in the clinic increasingly rely on predictions of tumour response to one or more therapies; these predictions are complicated by the inevitable evolution of the tumour. Despite enormous amounts of data on the mutational status of cancers and numerous therapies developed in recent decades to target these mutations, many of these treatments fail after a time due to the development of resistance in the tumour. The emergence of these resistant phenotypes is not easily predicted from genomic data, since the relationship between genotypes and phenotypes, termed the genotype-phenotype (GP) mapping, is neither injective nor functional. We present a review of models of this mapping within a generalized evolutionary framework that takes into account the relation between genotype, phenotype, environment and fitness. Different modelling approaches are described and compared, and many evolutionary results are shown to be conserved across studies despite using different underlying model systems. In addition, several areas for future work that remain understudied are identified, including plasticity and bet-hedging. The GP-mapping provides a pathway for understanding the potential routes of evolution taken by cancers, which will be necessary knowledge for improving personalized therapies.

Linkage mapping and quantitative trait loci analysis of sweetness and other fruit quality traits in papaya

BACKGROUND

The identification and characterisation of quantitative trait loci (QTL) is an important step towards identifying functional sequences underpinning important crop traits and for developing accurate markers for selective breeding strategies. In this study, a genotyping-by-sequencing (GBS) approach detected QTL conditioning desirable fruit quality traits in papaya.

RESULTS

For this, a linkage map was constructed comprising 219 single nucleotide polymorphism (SNP) loci across 10 linkage groups and covering 509 centiMorgan (cM). In total, 21 QTLs were identified for seven key fruit quality traits, including flesh sweetness, fruit weight, fruit length, fruit width skin freckle, flesh thickness and fruit firmness. Several QTL for flesh sweetness, fruit weight, length, width and firmness were stable across harvest years and individually explained up to 19.8% of the phenotypic variance of a particular trait. Where possible, candidate genes were proposed and explored further for their application to marker-assisted breeding.

CONCLUSIONS

This study has extended knowledge on the inheritance and genetic control for key papaya physiological and fruit quality traits. Candidate genes together with associated SNP markers represent a valuable resource for the future of strategic selective breeding of elite Australian papaya cultivars.

Proteome response of two natural strains of Saccharomyces cerevisiae with divergent lignocellulosic inhibitor stress tolerance

Strains of Saccharomyces cerevisiae with improved tolerance to plant hydrolysates are of utmost importance for the cost-competitive production of value-added chemicals and fuels. However, engineering strategies are constrained by a lack of understanding of the yeast response to complex inhibitor mixtures. Natural S. cerevisiae isolates display niche-specific phenotypic and metabolic diversity, encoded in their DNA, which has evolved to overcome external stresses, utilise available resources and ultimately thrive in their challenging environments. Industrial and laboratory strains, however, lack these adaptations due to domestication. Natural strains can serve as a valuable resource to mitigate engineering constraints by studying the molecular mechanisms involved in phenotypic variance and instruct future industrial strain improvement to lignocellulosic hydrolysates. We, therefore, investigated the proteomic changes between two natural S. cerevisiae isolates when exposed to a lignocellulosic inhibitor mixture. Comparative shotgun proteomics revealed that isolates respond by regulating a similar core set of proteins in response to inhibitor stress. Furthermore, superior tolerance was linked to NAD(P)/H and energy homeostasis, concurrent with inhibitor and reactive oxygen species detoxification processes. We present several candidate proteins within the redox homeostasis and energy management cellular processes as possible targets for future modification and study. Data are available via ProteomeXchange with identifier PXD010868.

Mouse genome-wide association and systems genetics identifies Lhfp as a regulator of bone mass

Bone mineral density (BMD) is a strong predictor of osteoporotic fracture. It is also one of the most heritable disease-associated quantitative traits. As a result, there has been considerable effort focused on dissecting its genetic basis. Here, we performed a genome-wide association study (GWAS) in a panel of inbred strains to identify associations influencing BMD. This analysis identified a significant (P = 3.1 x 10⁻¹²) BMD locus on Chromosome 3@52.5 Mbp that replicated in two separate inbred strain panels and overlapped a BMD quantitative trait locus (QTL) previously identified in a F2 intercross. The association mapped to a 300 Kbp region containing four genes; Gm2447, Gm20750, Cog6, and Lhfp. Further analysis found that Lipoma HMGIC Fusion Partner (Lhfp) was highly expressed in bone and osteoblasts. Furthermore, its expression was regulated by a local expression QTL (eQTL), which overlapped the BMD association. A co-expression network analysis revealed that Lhfp was strongly connected to genes involved in osteoblast differentiation. To directly evaluate its role in bone, Lhfp deficient mice (Lhfp^-/-) were created using CRISPR/Cas9. Consistent with genetic and network predictions, bone marrow stromal cells (BMSCs) from Lhfp^-/- mice displayed increased osteogenic differentiation. Lhfp^-/- mice also had elevated BMD due to increased cortical bone mass. Lastly, we identified SNPs in human LHFP that were associated (P = 1.2 x 10⁻⁵) with heel BMD. In conclusion, we used GWAS and systems genetics to identify Lhfp as a regulator of osteoblast activity and bone mass.

Osteoporosis is a common, chronic disease characterized by low bone mineral density (BMD) that puts millions of Americans at high risk of fracture. Variation in BMD in the general population is, in large part, determined by genetic factors. To identify novel genes influencing BMD, we performed a genome-wide association study in a panel of inbred mouse strains. We identified a locus on Chromosome 3 strongly associated with BMD. Using a combination of systems genetics approaches, we connected the expression of the Lhfp gene with BMD-associated genetic variants and predicted it influenced BMD by altering the activity of bone-forming osteoblasts. Using mice deficient in Lhfp, we demonstrated that Lhfp negatively regulates bone formation and BMD. These data suggest that inhibiting Lhfp may represent a novel therapeutic strategy to increase BMD and decrease the risk of fracture.

Mitochondrial polymorphisms contribute to aging phenotypes in MNX mouse models

Many inbred strains of mice develop spontaneous tumors as they age. Recent awareness of the impacts of mitochondrial DNA (mtDNA) on cancer and aging has inspired developing a mitochondrial-nuclear exchange (MNX) mouse model in which nuclear DNA is paired with mitochondrial genomes from other strains of mouse. MNX mice exhibit mtDNA influences on tumorigenicity and metastasis upon mating with transgenic mice. However, we also wanted to investigate spontaneous tumor phenotypes as MNX mice age. Utilizing FVB/NJ, C57BL/6J, C3H/HeN, and BALB/cJ wild-type inbred strains, previously documented phenotypes were observed as expected in MNX mice with the same nuclear background. However, aging nuclear matched MNX mice exhibited decreased occurrence of mammary tumors in C3H/HeN mice containing C57BL/6J mitochondria compared to wild-type C3H/HeN mice. Although aging tumor phenotypes appear to be driven by nuclear genes, evidence suggesting that some differences are modified by the mitochondrial genome is presented.

Roles of the mitochondrial genetics in cancer metastasis: not to be ignored any longer

Mitochondrial DNA (mtDNA) encodes for only a fraction of the proteins that are encoded within the nucleus, and therefore has typically been regarded as a lesser player in cancer biology and metastasis. Accumulating evidence, however, supports an increased role for mtDNA impacting tumor progression and metastatic susceptibility. Unfortunately, due to this delay, there is a dearth of data defining the relative contributions of specific mtDNA polymorphisms (SNP), which leads to an inability to effectively use these polymorphisms to guide and enhance therapeutic strategies and diagnosis. In addition, evidence also suggests that differences in mtDNA impact not only the cancer cells but also the cells within the surrounding tumor microenvironment, suggesting a broad encompassing role for mtDNA polymorphisms in regulating the disease progression. mtDNA may have profound implications in the regulation of cancer biology and metastasis. However, there are still great lengths to go to understand fully its contributions. Thus, herein, we discuss the recent advances in our understanding of mtDNA in cancer and metastasis, providing a framework for future functional validation and discovery.

Construction of a genetic linkage map in Pyropia yezoensis (Bangiales, Rhodophyta) and QTL analysis of several economic traits of blades

Pyropia yezoensis is an economically important seaweed but its molecular genetics is poorly understood. In the present study, we used a doubled haploid (DH) population that was established in our previous work to construct a genetic linkage map of P. yezoensis and analyze the quantitative trait loci (QTLs) of blades. The DH population was genotyped with fluorescent sequence-related amplified polymorphism (SRAP) markers. A chi-square test identified 301 loci with normal segregation (P ≥ 0.01) and 96 loci (24.18%) with low-level skewed segregation (0.001 ≤ P < 0.01). The genetic map was constructed after a total of 92 loci were assembled into three linkage groups (LGs). The map spanned 557.36 cM covering 93.71% of the estimated genome, with a mean interlocus space of 6.23 cM. Kolmogorov-Smirnov test (α = 5%) showed a uniform distribution of the markers along each LG. On the genetic map, 10 QTLs associated with five economic traits of blades were detected. One QTL was for length, one for width, two for fresh weight, two for specific growth rate of length and four for specific growth rate of fresh weight. These QTLs could explain 2.29–7.87% of the trait variations, indicating that their effects were all minor. The results may serve as a framework for future marker-assisted breeding in P. yezoensis.

Physical linkage and mate preference generate linkage disequilibrium for behavioral isolation in two parapatric crickets

Behavioral isolation is a potent barrier to gene flow and a source of striking diversity in the animal kingdom. However, it remains unclear if the linkage disequilibrium (LD) between sex‐specific traits required for behavioral isolation results mostly from physical linkage between signal and preference loci or from directional mate preferences. Here, we test this in the field crickets Gryllus rubens and G. texensis. These closely related species diverged with gene flow and have strongly differentiated songs and preference functions for the mate calling song rhythm. We map quantitative trait loci for signal and preference traits (pQTL) as well as for gene expression associated with these traits (eQTL). We find strong, positive genetic covariance between song traits and between song and preference. Our results show that this is in part explained by incomplete physical linkage: although both linked pQTL and eQTL couple male and female traits, major effect loci for different traits were never on the same chromosome. We suggest that the finely tuned, highly divergent preference functions are likely an additional source of LD between male and female traits in this system. Furthermore, pleiotropy of gene expression presents an underappreciated mechanism to link sexually dimorphic phenotypes.