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The genetic contribution with respect to autosomal genes has been widely used to evaluate the genetic diversity of a target population. Here, we developed a method to calculate the genetic contribution with respect to genes on sex chromosomes and mitochondrial DNA through pedigree analysis. To demonstrate the performance, we applied the methods for calculating genetic contributions to example pedigree data. To verify the results of genetic contribution calculations, we performed gene-dropping simulations mimicking flows of genes on autosomes, X and Y chromosomes, and mitochondrial DNA, and then compared the results from the simulation with the corresponding genetic contributions. To investigate the effect of pedigree error, we compared the results of genetic contribution calculations using pedigree data with and without errors. The results of gene-dropping simulation showed good agreement with the results of the genetic contribution calculation. The effect of pedigree errors on the calculation of genetic contribution depended on the error rate. Since the patterns of the genetic contributions of such genes might be different from those on autosomes, the novel approach could provide new information on the genetic composition of populations. The results are expected to contribute to the development of methods for sustainable breeding and population management.

• Apple (Malus × domestica) has commercial and nutritional value, but breeding constraints of tree crops limit varietal improvement. Marker-assisted selection minimises these drawbacks, but breeders lack applications for targeting fruit phytochemicals. To understand genotype–phytochemical associations in apples, we have developed a high-throughput integration strategy for genomic and multiplatform metabolomics data. • Here, 124 apple genotypes, including members of three pedigree-connected breeding families alongside diverse cultivars and wild selections, were genotyped and phenotyped. Metabolite genome-wide association studies (mGWAS) were conducted with c. 10 000 single nucleotide polymorphisms and phenotypic data acquired via LC–MS and ¹H NMR untargeted metabolomics. Putative metabolite quantitative trait loci (mQTL) were then validated via pedigree-based analyses (PBA). • Using our developed method, 519, 726 and 177 putative mQTL were detected in LC–MS positive and negative ionisation modes, and NMR, respectively. mQTL were indicated on each chromosome, with hotspots on linkage groups 16 and 17. A chlorogenic acid mQTL was discovered on chromosome 17 via mGWAS and validated with a two-step PBA, enabling discovery of novel candidate gene–metabolite relationships. • Complementary data from three metabolomics approaches and dual genomics analyses increased confidence in validity of compound annotation and mQTL detection. Our platform demonstrates the utility of multiomic integration to advance data-driven, phytochemical-based plant breeding.

Large-scale family pedigrees are commonly used across medical, evolutionary, and forensic genetics. These pedigrees are tools for identifying genetic disorders, tracking evolutionary patterns, and establishing familial relationships via forensic genetic identification. However, there is a lack of software to accurately simulate different pedigree structures along with genomes corresponding to those individuals in a family pedigree. This limits simulation-based evaluations of methods that use pedigrees. We have developed a python command-line-based tool called py_(p)ed_(s)im that facilitates the simulation of pedigree structures and the genomes of individuals in a pedigree. py_(p)ed_(s)im represents pedigrees as directed acyclic graphs, enabling conversion between standard pedigree formats and integration with the forward population genetic simulator, SLiM. Notably, py_(p)ed_(s)im allows the simulation of varying numbers of offspring for a set of parents, with the capacity to shift the distribution of sibship sizes over generations. We additionally add simulations for events of misattributed paternity, which offers a way to simulate half-sibling relationships, and simulations to extend the breadth of a family pedigree. We validated the accuracy of both our genome simulator and pedigree simulator. We show that we can simulate genomes onto family pedigrees with levels of expected kinship. py_(p)ed_(s)im is a user-friendly and open-source solution for simulating pedigree structures and conducting pedigree genome simulations. It empowers medical, forensic, and evolutionary genetics researchers to gain deeper insights into the dynamics of genetic inheritance and relatedness within families.

Familial Adult Myoclonic Epilepsy (FAME) is characterised by cortical myoclonic tremor usually from the second decade of life and overt myoclonic or generalised tonic-clonic seizures. Four independent loci have been implicated in FAME on chromosomes (chr) 2, 3, 5 and 8. Using whole genome sequencing and repeat primed PCR, we provide evidence that chr2-linked FAME (FAME2) is caused by an expansion of an ATTTC pentamer within the first intron of STARD7 . The ATTTC expansions segregate in 158/158 individuals typically affected by FAME from 22 pedigrees including 16 previously reported families recruited worldwide. RNA sequencing from patient derived fibroblasts shows no accumulation of the AUUUU or AUUUC repeat sequences and STARD7 gene expression is not affected. These data, in combination with other genes bearing similar mutations that have been implicated in FAME, suggest ATTTC expansions may cause this disorder, irrespective of the genomic locus involved. Familial cortical myoclonic tremor (FAME) has so far been mapped to regions on chromosome 2, 3, 5 and 8 and pentameric repeat expansions in SAMD12 were identified as cause of FAME1. Here, Corbett et al . identify ATTTT/ATTTC repeat expansions in intron 1 of STARD7 in individuals with FAME2.”

Inbreeding depression (reduced fitness of individuals with related parents) has long been a major focus of ecology, evolution, and conservation biology. Despite decades of research, we still have a limited understanding of the strength, underlying genetic mechanisms, and demographic consequences of inbreeding depression in the wild. Studying inbreeding depression in natural populations has been hampered by the inability to precisely measure individual inbreeding. Fortunately, the rapidly increasing availability of high‐throughput sequencing data means it is now feasible to measure the inbreeding of any individual with high precision. Here, we review how genomic data are advancing our understanding of inbreeding depression in the wild. Recent results show that individual inbreeding and inbreeding depression can be measured more precisely with genomic data than via traditional pedigree analysis. Additionally, the availability of genomic data has made it possible to pinpoint loci with large effects contributing to inbreeding depression in wild populations, although this will continue to be a challenging task in many study systems due to low statistical power. Now that reliably measuring individual inbreeding is no longer a limitation, a major focus of future studies should be to more accurately quantify effects of inbreeding depression on population growth and viability.

The Bracco Italiano is one of the oldest pointing dog breed, used for hunting ever since the Renaissance time. The complete electronic record of the breed was downloaded from the ENCI database [whole population (WP) = 24,613 animals registered since 1970 to 2011] with the aim to estimate genetic variability in Bracco Italiano dog breed using pedigree records. Up to 97% of the individuals had registered parents and 86% registered grandfathers. Average generation interval was 4.68±0.545 for stallions and 4.08±0.321 year for dams. Reference population (RP) was defined as the population of interest that include living reproductive animals approaching the last three generations and include 9006 dogs of which 34% were inbreds. The number of ancestors was 564 in WP and 188 in RP, while the effective number of ancestors was 46 and 34 respectively. To explain 50% of the genetic variability, a total of 18 and 9 ancestors enough, respectively in the WP and RP. The average inbreeding coefficient in the RP resulted 6.7% while the average increase in inbreeding was estimated to be 1.29% (Ne=38.86). Nevertheless a regular monitoring of genetic variability of the population is important and must be adopted, in order to avoid the danger of an excessive increase of inbreeding in the future, which would result in significant inbreeding depression and in significant loss of genetic variation.

Background The ubiquity of pedigrees in many scientific areas calls for versatile and user-friendly software. Previously published online pedigree tools have limited support for complex pedigrees and do not provide analysis of relatedness between pedigree members. Results We introduce QuickPed, a web application for interactive pedigree creation and analysis. It supports complex inbreeding and comes with a rich built-in library of common and interesting pedigrees. The program calculates all standard coefficients of relatedness, including inbreeding, kinship and identity coefficients, and offers specialised plots for visualising relatedness. It also implements a novel algorithm for describing pairwise relationships in words. Conclusion QuickPed is a user-friendly pedigree tool aimed at researchers, case workers and teachers. It contains a number of features not found in other similar tools, and represents a significant addition to the body of pedigree software by making advanced relatedness analyses available for non-bioinformaticians.

Pedigree files are ubiquitously used within bioinformatics and genetics studies to convey critical information about relatedness, sex and affected status of study samples. While the text based format of ped files is efficient for computational methods, it is not immediately intuitive to a bioinformatician or geneticist trying to understand family structures, many of which encode the affected status of individuals across multiple generations. The visualization of pedigrees into connected nodes with descriptive shapes and shading provides a far more interpretable format to recognize visual patterns and intuit family structures. Despite these advantages of a visual pedigree, it remains difficult to quickly and accurately visualize a pedigree given a pedigree text file. Here we describe ped_(d)raw a command line and web tool as a simple and easy solution to pedigree visualization. Ped_(d)raw is capable of drawing complex multi-generational pedigrees and conforms to the accepted standards for depicting pedigrees visually. The command line tool can be used as a simple one liner command, utilizing graphviz to generate an image file. The web tool, https://peddraw.github.io, allows the user to either: paste a pedigree file, type to construct a pedigree file in the text box or upload a pedigree file. Users can save the generated image file in various formats. We believe ped_(d)raw is a useful pedigree drawing tool that improves on current methods due to its ease of use and approachability. Ped_(d)raw allows users with various levels of expertise to quickly and easily visualize pedigrees.

Repeated artificial selection of a complex trait facilitates the identification of genes underlying the trait, especially if multiple selected descendant lines are available. Here we developed a pedigree-based approach to identify genes underlying the Green Revolution (GR) phenotype. From a pedigree analysis, we selected 30 cultivars including the “miracle rice” IR8, a GR landmark, its ancestors and descendants, and also other related cultivars for identifying high-yield genes. Through sequencing of these genomes, we identified 28 ancestral chromosomal blocks that were maintained in all the high-yield cultivars under study. In these blocks, we identified six genes of known function, including the GR gene sd1, and 123 loci with genes of unknown function. We randomly selected 57 genes from the 123 loci for knockout or knockdown studies and found that a high proportion of these genes are essential or have phenotypic effects related to rice production. Notably, knockout lines have significant changes in plant height (P < 0.003), a key GR trait, compared with wild-type lines. Some gene knockouts or knockdowns were especially interesting. For example, knockout of Os10g0555100, a putative glucosyltransferase gene, showed both reduced growth and altered panicle architecture. In addition, we found that in some retained chromosome blocks several GR-related genes were clustered, although they have unrelated sequences, suggesting clustering of genes with similar functions. In conclusion, we have identified many high-yield genes in rice. Our method provides a powerful means to identify genes associated with a specific trait.

Purpose In the present study, we addressed the inconsistency between the testing criteria and diverse phenotypes for germline TP53 mutation in patients with breast cancer in the Chinese population. Method We proposed a new added item (synchronous or metachronous bilateral breast cancer) as one of the testing criteria (aimed at high-penetrance breast cancer susceptibility genes) and applied it for determining TP53 germline mutation status in 420 female patients with breast cancer using multigene panel-based next-generation sequencing, Sanger sequencing, and mass spectrometry. Results We found that 1.4% of patients carried a pathogenic or likely pathogenic germline TP53 mutation. Compared with BRCA mutation carriers (8.0%) and non-carriers (7.1%), TP53 mutation carriers (33.3%) developed breast cancer earlier. The majority of TP53 mutation carriers (66.7%) developed breast cancer after age 30 and had bilateral breast cancer (33.3%). Pedigree investigation of four TP53 carriers and a patient with a TP53 variant of unknown significance revealed that neither of their parents harbored the same mutations as the probands, indicating that the mutations might occur de novo. Conclusion Our study revealed distinguishing features of TP53 carriers among Chinese women with breast cancer, which is inconsistent with the currently used testing criteria; therefore, the newly proposed testing criteria may be more appropriate.