Genetic Progress Research Articles

Phenotypic spectrum of iron-sulfur cluster assembly gene IBA57 mutations: c.286 T > C identified as a hotspot mutation in Chinese patients with a stable natural history.

Mutations in IBA57 disrupt iron-sulfur clusters maturation, causing a rare mitochondrial disease. Clinical manifestations vary from neonatal lethality to childhood-onset spastic paraparesis, yet the ethnic heterogeneity and natural history remain unclear, necessitating further exploration. This study aimed to delineate the genotype-phenotype correlation of IBA57 mutations by analyzing diverse clinical presentations. We report 11 Chinese patients and include literature-reported cases, totaling 61 patients enrolled for analysis. Clinical, neuroimaging, genetic, and disease progression information were collected. Among these, 46 presented as multiple mitochondrial dysfunctions syndrome 3 (MMDS3), with 58.7% originating from Chinese population. Based on disease course, we propose three clinical subtypes: neonatal, infant and childhood subtypes. Neonatal cases universally displayed hypotonia and respiratory distress at presentation, deceased within three months. Most infancy and childhood cases exhibited developmental regression and impaired motor function. Cavitating leukoencephalopathy was a typical neuroimaging finding in MMDS3 patients. The c.286 T > C mutation was reported in 85.2% of Chinese patients. A significantly lower mortality rate was observed compared to the non-Chinese group (P = 0.002), with a survival rate exceeding 90% at 5 years, indicating a relatively stable disease progression. Fifteen cases from three families manifested the spastic paraplegia 74 phenotype, demonstrating normal development before onset, with common clinical manifestations including spastic paraplegia (14/15), visual impairment (10/13), and peripheral neuropathy (9/13). In conclusion, this study indicates a hotspot mutation in Chinese and analyses the disease progression with different clinical subtypes.

Milletomics: a metabolomics centered integrated omics approach toward genetic progression.

Producing alternative staple foods like millet will be essential to feeding ten billion people by 2050. The increased demand for millet is driving researchers to improve its genetic variation. Millets include protein, dietary fiber, phenolic substances, and flavonoid components. Its climate resilience makes millet an appealing crop for agronomic sustainability. Integrative omics technologies could potentially identify and develop millets with desirable phenotypes that may have high agronomic value. Millets' salinity and drought tolerance have been enhanced using transcriptomics. In foxtail, finger, and pearl millet, proteomics has discovered salt-tolerant protein, phytohormone-focused protein, and drought tolerance. Metabolomics studies have revealed that certain metabolic pathways including those involving lignin, flavonoids, phenylpropanoid, and lysophospholipids are critical for many processes, including seed germination, photosynthesis, energy metabolism, and the synthesis of bioactive chemicals necessary for drought tolerance. Metabolomics integration with other omics revealed metabolome engineering and trait-specific metabolite creation. Integrated metabolomics and ionomics are still in the development stage, but they could potentially assist in comprehending the pathway of ionomers to control nutrient levels and biofortify millet. Epigenomic analysis has shown alterations in DNA methylation patterns and chromatin structure in foxtail and pearl millets in response to abiotic stress. Whole-genome sequencing utilizing next-generation sequencing is the most proficient method for finding stress-induced phytoconstituent genes. New genome sequencing enables novel biotechnological interventions including genome-wide association, mutation-based research, and other omics approaches. Millets can breed more effectively by employing next-generation sequencing and genotyping by sequencing, which may mitigate climate change. Millet marker-assisted breeding has advanced with high-throughput markers and combined genotyping technologies.

Prediction of additive genetic variances of descendants for complex families based on Mendelian sampling variances.

The ability to predict the outcome of selection and mating decisions enables breeders to make strategically better selection decisions. To improve genetic progress, those individuals need to be selected whose offspring can be expected to show high genetic variance next to high breeding values. Previously published approaches enable to predict the variance of descendants of two future generations for up to 4 founding haplotypes, or 2 outbred individuals, based on phased genotypes, allele effects and recombination frequencies. The purpose of this study was to develop a general approach for the analytical calculation of the genetic variance in any future generation. The core development is an equation for the prediction of the variance of double haploid lines, under the assumption of no selection and negligible drift, stemming from an arbitrary number of founder haplotypes. This double haploid variance can be decomposed into gametic Mendelian sampling variances (MSV) of ancestors of the double haploid lines allowing usage for non-double haploid genotypes which enables application in animal breeding programs as well as in plant breeding programs. Together with the breeding values of the founders, the gametic MSV may be used in new selection criteria. We present our idea of such a criterion that describes the genetic level of selected individuals in four generations. Since breeding programs do select, the assumption made for predicting variances is clearly violated which decreases the accuracy of predicted gametic MSV caused by changes in allele frequency and linkage disequilibrium. Despite violating the assumption, we found high predictive correlations of our criterion to the true genetic level which was obtained by means of simulation for the "corn" and "cattle" genome models tested in this study (0.90 and 0.97). In practice, the genotype phases, genetic map and allele effects all need to be estimated meaning inaccuracies in their estimation will lead to inaccurate variance prediction. Investigation of variance prediction accuracy when input parameters are estimated was not part of this study.

Research Note: Genetic parameters estimation of egg quality traits in Rhode Island Red and White Leghorn chickens

The continuous increasing demand for egg quality and quantity, and the expanding market share have enabled the egg industry to achieve significant benefits through genetic improvement. This study aims to estimate the genetic parameters and explore selectable breeding traits in the purebred Rhode Island Red (RIR) and White Leghorn (WL), which are 2 high-yielding layer breeds, and better understand their underlying genetic basis and accelerate genetic progress. The DMU software was utilized to analyze 12 egg quality traits, including egg length (EL), egg width (EW), egg shape index (ESI), egg weight (EWT), albumen height (AH), yolk color (YC), Haugh unit (HU), yolk weight (YW), albumen weight (AW), albumen-to-egg weight ratio (AWR), yolk-to-albumen ratio (YAR), and yolk-to-egg weight ratio (YWR). In RIR, the heritability of egg quality traits ranged from 0.196 to 0.427, while the repeatability ranged from 0.395 to 0.668. In WL, the heritability of egg quality traits ranged from 0.203 to 0.347, and the repeatability ranged from 0.424 to 0.656. In both RIR and WL, highly strong genetic correlations were observed between AW and EW, as well as between AW and EWT. The genetic correlations for AW and EW were 0.902 in RIR and 0.864 in WL, while the genetic correlations for AW and EWT were 0.981 in RIR and 0.960 in WL. The egg quality traits in both breeds showed moderate heritability, indicating great genetic potential for improvement through selective breeding. This can help breeders meet the increasingly diverse egg preferences of consumers through genetic selection. Additionally, there is a highly strong correlation between egg width/egg weight, and albumen weight in both breeds. In practical production, it is feasible to estimate albumen weight by measuring egg width and egg weight, which can simplify the method for measuring albumen weight. In conclusions, our finding provided valuable insights into the genetic architecture of egg quality traits in RIR and WL chickens. They help our understanding of the potential for genetic improvement of these traits through selective breeding programs.

Potential of Black Rice Mutants (M4) Through Genetic Parameters to Develop Superior Drought-Resistant Varieties

Rice plays an important role in meeting carbohydrate requirement and calorie needs to ensure food security. However, in recent years, rice productivity has decreased due to land conversion and climate change such as El Niño. The productivity of drought-resistant rice can be increased through breeding. Genetic diversity and heritability are important genetic parameters in the plant breeding process. Information about genetic diversity and heritability helps determine genetic progress through selection. This research aims to examine the potential genetic diversity and heritability of several mutant lines (M4) of black rice (G10) in order to develop superior rice varieties that are adaptive to dry land. In this research, we used experimental methods using a Randomized Block Design (RBD), calculating the value of the Genetic Diversity Coefficient (GDC) and heritability between quantitative characters. The results of narrow genetic research were found in the characteristics of the number of productive tillers and weight of 100 grains, while high heritability was found in the characters of plant height, moderate heritability was found in the total number of tillers, panicle length, number of empty grains per panicle, and weight of 100 grains. Overall, this research succeeded in identifying mutant lines (M4) of black rice (G10) which have the potential to be developed into superior varieties, especially for cultivation in dry land.

Multivariate analysis of herd structure and genetic resource indicators in seedstock beef cattle herds.

Genetic, environmental, technological and financial resources are used differently in cattle herds that participate in the same breeding programme. The percentages of calves sired by sires within their own herd or from external herds vary across herds, as do the intensities of use of reproductive biotechnologies. These divergences may be related to differences in the indicators of genetic performance for economic traits. The aim of this study was to determine the factors related to herd structure and genetic resource utilization that exert the greatest influence on the genetic merit of seedstock herds within a Nellore breeding programme. The database comprised 21 factors, along with genomic-enhanced expected progeny differences (GE-EPDs) for growth, reproductive and carcass traits, as well as a selection index of animals from 128 herds. By combining principal component analysis and cluster analysis, we were able to group the herds. We identified statistically significant differences (p < 0.05) in the mean values of the factors, GE-EPDs and genetic trends among the groups of herds. Differences in the percentage of sires from external herds and in sire age between the groups of herds were the factors most associated with differences in mean GE-EPDs and genetic trends. Using young sires from other herds or lineages is an effective strategy in animal breeding. By enhancing genetic variability, this approach does not only improve the genetic quality of herds but also accelerates genetic progress in desired traits over time. Therefore, to ensure the success of this strategy, it is crucial that seedstock herds undergo a thorough selection process aimed at maximizing the genetic potential of future generations of beef cattle.

Experimental unbalance: reflections on genetic parameters and corn selection gain

Genetic progress depends on the components of variance and genetic parameters. In this context, the objective of this work was to identify the maximum allowed percentage of experimental imbalance in the estimation of variance components, genetic parameters and selection gain in intervarietal corn hybrids. The experimental design used was randomized blocks, with 60 corn hybrids with three replications. Random subsets of data were created in order to express unbalance scenarios of the phenotypic matrix, we obtained 9 scenarios (0, 10, 20, 30, 40, 50, 60, 70 and 80% unbalance).Thus, the genetic variance of the paternal genitor, the genetic variance of the maternal genitor, additive variance, individual phenotypic variance, narrow-sense heritability of intervarietal additive effects for the paternal genitor were estimated, narrow-sense heritability of intervarietal additive effects for the maternal genitor, narrow-sense heritability, broad-sense heritability, genotypic variation coefficient between progenies and variation coefficient residual. Narrow sense heritability reveals high magnitude for the characters cob mass and hundred grain mass. Maternal effect is expressed through ear insertion height, ear grain mass, cob mass and diameter, number of rows, ear mass and length, and grain yield. The imbalance inflates the variance components and genetic parameters for the highlighted characters. It supports 10% imbalance in the data matrix without compromising the reliability of the estimates. Pronounceable selection gains are obtained for grain yield based on pressures of 1 and 5%. An unbalance of 10% is supported in the selection gain for cob mass, ear length and hundred grain mass.

Strong genotype-by-environment interaction across contrasted sites for summer mortality syndrome in the Pacific oyster Crassostrea gigas

Genotype-by-environment (GxE) interaction in aquaculture is usually estimated for continuous traits and based on data from a limited number of 2–3 rearing sites. Here we report the results of a GxE study for resistance to Pacific oyster mortality syndrome (POMS), a multi-factorial disease that severely impacts Pacific oyster production worldwide. The syndrome is largely associated with Ostreid Herpes Virus 1 (OsHV-1). Resistance to OsHV-1 in Crassostrea gigas has been shown to be heritable, meaning that selective breeding is a suitable strategy for reducing mortalities. However, limited information was available about GxE interaction or the possible need to consider it in selective breeding. Survival of two cohorts (C1 and C2), consisting of a total of 104 full-sib families, was evaluated during the summer of 2013 in 7 sites along the French Atlantic, Channel and Mediterranean coasts. Mean survivals in autumn 2013 were 12.6% ± 10.9 and 4.6% ± 6.4 for C1 and C2, respectively. Genetic parameters were computed by MCMC, which is suitable for binary data like survival. Heritability estimates ranged from 0.16 to 0.42 depending on site and cohort, with a mean of 0.24 [0.20; 0.27] when including all data. GxE interactions were estimated by the genetic correlations between pairs of sites. Genetic correlations were high (ρ > 0.80) for C1 between most tidal Atlantic and Channel sites, and intermediate between tidal sites and a Mediterranean lagoon site, while they were lower and more variable for C2 (0.21–0.77). Expected genetic gains were maximal when production site was the same as selection site. They were closed to this expected maximum when the selection site was different from the production site along the Atlantic or Channel coast. Limited GxE interaction along the French Atlantic coast is favorable to wide dissemination of genetically improved oysters along this coast. Limited potential improvement was shown in the Mediterranean site if selection was carried out elsewhere, confirming the specificity of this environment. Consequently, a specific strategy such as dedicated breeding should be used to achieve genetic progress for this site.

Effect of heat stress on semen characteristics and genetics in Thai native grandparent roosters

Grandparent roosters are crucial in poultry breeding programs and significantly influence future bird generations' genetic makeup and performance. However, these roosters face considerable challenges from heat stress, which can adversely affect their reproductive performance, semen quality, and overall health and welfare. Our study aimed to investigate the effects of heat stress on the genetics of semen characteristics, identify the appropriate temperature and humidity indices (THI), and determine the threshold point of heat stress to prevent thermal stress. We analyzed data from 3,895 records of 242 Thai native grandparent roosters in conjunction with the THI using 7 THI functions and the regression method. The threshold point of heat stress, genetic parameters, rate of decline of semen characteristics per level of THI, estimated breeding values and selection index values were analyzed using the multivariate test-day model in the AIREML and BLUPF90 programs. Based on the regression coefficient and statistical criteria of the lowest -2logL and AIC values, the results showed that a THI of 78 was considered the threshold point of heat stress. The estimated heritability values ranged from 0.023 to 0.032, 0.066 to 0.069, 0.047 to 0.057, and 0.022 to 0.024 for mass movement, semen volume, sperm concentration, and the semen index, respectively. The reduction rates of mass movement, semen volume, sperm concentration, and semen index at a THI of 78 were -0.009, -0.003, -0.170, and -0.083 per THI, respectively. The genetic correlations among the semen traits were moderately to strongly positive and ranged from 0.562 to 0.797. The genetic correlations between semen traits and heat stress were negative and ranged from -0.437 to -0.749. The permanent environmental correlations among the semen traits (0.648-0.929) were positive and greater than the genetic correlations. Permanent environmental correlations between semen traits and heat stress were negative and ranged from -0.539 to -0.773. The results of the selection indices showed that the higher the selection intensity was, the greater the degree to which the selection index corresponded to genetic progress. The recommendation for animal genetic selection is that the top 10% is appropriate because it seems most preferred. Therefore, using a multivariate test-day model and selection index for the high genetic potential of semen traits and heat tolerance in Thai native grandparent roosters makes it possible to achieve genetic assessment in a large population.

Effect of germplasm exchange strategies on genetic gain, homozygosity, and genetic diversity in dairy stud populations: A simulation study

While genomic selection has led to considerable improvements in genetic gain, it has also seemingly led to increased rates of inbreeding and homozygosity, which can negatively affect genetic diversity and the long-term sustainability of dairy populations. Using genotypes from US Holstein animals from 3 distinct stud populations, we performed a simulation study consisting of 10 rounds of selection, with each breeding population composed of 200 males and 2000 females. The investigated selection strategies consisted of selection using true breeding values (TBV), estimated breeding values (EBV), estimated breeding values penalized for the average future genomic inbreeding of progeny (PEN-EBV), or random selection (RAND). We also simulated several germplasm exchange strategies where the germplasm of males from other populations was used for breeding. These strategies included exchanging males based on EBV, PEN-EBV, low genomic future inbreeding of progeny (GFI), or randomly (RAND). Variations of several parameters, such as the correlation between the selection objectives of populations and the size of the exchange, were simulated. Penalizing genetic merit to minimize genomic inbreeding of progeny provided similar genetic gain and reduced the average homozygosity of populations compared with the EBV strategy. Germplasm exchange was found to generally provide long-term benefits to all stud populations. In both the short and long-term, germplasm exchange using the EBV or PEN-EBV strategies provided more cumulative genetic progress than the no-exchange strategy; the amount of long-term genetic progress achieved with germplasm exchange using these strategies was higher for scenarios with a higher genetic correlation between the traits selected by the studs and for a larger size of the exchange. Both the PEN-EBV and GFI exchange strategies allowed decreases in homozygosity and provided significant benefits to genetic diversity compared with other strategies, including larger average minor allele frequencies and smaller proportions of markers near fixation. Overall, this study showed the value of breeding strategies to balance genetic progress and genetic diversity and the benefits of cooperation between studs to ensure the sustainability of their respective breeding programs.

Integrating Genetics in Glaucoma Screening.

As additional glaucoma genes are identified and classified, polygenic risk scores will be refined, facilitating early diagnosis and treatment. Ensuring genetic research is equitable to prevent glaucoma blindness worldwide is crucial. To review the progress in glaucoma genetics over the past 25 years, including the identification of genes with varying contributions to the disease and the development of polygenic risk scores. Over the last 2 and a half decades, glaucoma genetics has evolved from identifying genes with Mendelian inheritance patterns, such as myocilin and CYP1B1, to the discovery of hundreds of genes associated with the disease. Polygenic risk scores have been developed, primarily based on research in Northern European populations, and efforts to refine these scores are ongoing. However, there is a question regarding their applicability to other ethnic groups, especially those at higher risk of primary open angle glaucoma, like individuals of African ancestry. Glaucoma is highly heritable and family history can be used for cascade clinical screening programs, but these will not be feasible in all populations. Thus, cascade genetic testing using well-established genes such as myocilin may help improve glaucoma diagnosis. In addition, ongoing investigations seek to identify pathogenic genetic variants within genes like myocilin. The expanding availability of genetic testing for various diseases and early access to genetic risk information necessitates further research to determine when and how to act on specific genetic results. Polygenic risk scores involving multiple genes with subtle effects will require continuous refinement to improve clinical utility. This is crucial for effectively interpreting an individual's risk of developing glaucoma and preventing blindness.

Molecular genetics and research progress of uterine leiomyosarcoma.

Uterine leiomyosarcoma (uLMS) is a type of malignant soft-tissue tumor, which is developed from myometrium in the female reproductive system. This disease is difficult to be distinguished from benign uterine leiomyoma in the early stages, but it progresses aggressively and relentlessly. Hence, uLMS has a dismal prognosis and high rates of both misdiagnosis and missed diagnosis. Unfortunately, current studies of uLMS pathogenesis and disease biology are inadequate. uLMS disease models are also very limited, hindering the development of effective therapeutics. In this review, we focus on the pathological molecular biology of uLMS, and systematically review the molecular genetic features, epigenetic variants, experimental models, and clinical research progress of uLMS. We further discuss the development direction and potential needs of uLMS in the fields of tumor evolution, tumor microenvironment, and tumor therapy, with the aim of providing a better understanding of the pathobiological mechanism of uLMS and providing a reference for the development of potential diagnostic and therapeutic strategies.

10. Effect of the proportion of phenotyped and genotyped animals on the genetic progress of a trait recorded on production farms

10. Effect of the proportion of phenotyped and genotyped animals on the genetic progress of a trait recorded on production farms

Maize breeding effects on grain yield genetic progress and its contribution to global yield gain in Argentina

Context or problemMaize production in Argentina has increased in recent years, following the global gain (GG) in grain yield (GY). The GG in GY depends on genetic progress (GP), which requires frequent quantification to detect potential plateaus and variations in its contribution to the GG. In this sense, hybrid adoption in Argentina shifted from double- and three-way to single cross (F1) hybrids in the 1990s, thereby increasing the level of heterosis of released hybrids. Since heterosis increase may have had a greater impact on estimates of maize GG than those based on a single cross type, GP based exclusively on F1 hybrids and its contribution to GG could be lower than that including different types of crosses. Objective or research questionThe main objectives of this work were to (i) analyze grain yield GP, (ii) dissect grain yield GP into the corresponding trends in its physiological determinants and numerical components, and (iii) estimate the relative contribution of GP to GG in the main maize producing region of Argentina for the period marked by significant changes in heterosis level (i.e. from 1960s to 1990s) and the period of massive adoption of F1 hybrids (from 1990s onwards). MethodsWe used a dataset obtained at the core of the mentioned region (INTA Pergamino; 33°56’S, 60°34’W) from era-decade experiments (ERA) including 24 hybrids released between 1965 and 2016 and grown with no abiotic or biotic restrictions. We quantified GY, its numeric components (KN: kernel number m−2, KW: individual kernel weight) and its physiological determinants (BT: total shoot biomass at maturity, HI: harvest index). ResultsA GP of 0.84 % y−1 was computed for GY from 1965 to 1993, and of 0.51 % y−1 thereafter. We also detected genetic progress for KN (0.53 % y−1) and BT (0.26 % y−1) but not for KW. A GP of 0.66 % y−1 was computed for HI up to 1993, which plateaued thereafter. A 40 % contribution of GP to GG was estimated for the Pergamino site from 1965 to 1993, predominantly driven by changes in heterosis level. The contribution dropped to 32 % from 1993 onwards, when F1 hybrids were massively adopted by the farmers. This contribution was much smaller (e.g. 19 %) in areas less representative of the target population of environments of dominant breeding programs. ConclusionsOur findings underline that the relative contribution of GP to GY improvement at the regional level varies markedly depending upon the period included in the analysis and the environment used for evaluation. The decline observed at less representative locations of the main target population of environments may guide breeders in their decision for developing new programs.

New epilepsy therapies in development.

Epilepsy is a common brain disorder, characterized by spontaneous recurrent seizures, with associated neuropsychiatric and cognitive comorbidities and increased mortality. Although people at risk can often be identified, interventions to prevent the development of the disorder are not available. Moreover, in at least 30% of patients, epilepsy cannot be controlled by current antiseizure medications (ASMs). As a result of considerable progress in epilepsy genetics and the development of novel disease models, drug screening technologies and innovative therapeutic modalities over the past 10 years, more than 200 novel epilepsy therapies are currently in the preclinical or clinical pipeline, including many treatments that act by new mechanisms. Assisted by diagnostic and predictive biomarkers, the treatment of epilepsy is undergoing paradigm shifts from symptom-only ASMs to disease prevention, and from broad trial-and-error treatments for seizures in general to mechanism-based treatments for specific epilepsy syndromes. In this Review, we assess recent progress in ASM development and outline future directions for the development of new therapies for the treatment and prevention of epilepsy.

Economic utility of Colombian Romosinuano cattle

The objective of this study was to quantify the economic utility in Romosinuano production systems by developing a bioeconomic model assumed cow-calf, cow-calf plus stocker (CCPS), and complete cycle operations. Each system produced males for sale and females for replacement. Input parameters were established from breed data collected by AGROSAVIA. Revenues were estimated using the official cattle price, and production costs were quantified per activity. In the results, for cow-calf operations, the maximum economic utility was 244.12 USD. CCPS, yielded 231.86 USD, and Complete cycle, 268.94 USD. The genetic progress per generation for W240, W480, W24 and CI was + 3.8 kg, + 5 kg, + 5.9 kg, and -1 d, respectively. The price of livestock was the sensitized variable with the greatest impact on maximum economic utility (± 118.64 USD to ± 155.44 USD), followed by mineral supplementation (16.31 USD to ± 37.34 USD). The sensitized variables with the lowest impact were food (± 1.62 USD to ± 1.8 USD) and health plan supplies (± 6.03 USD to ± 9.13 USD). It is concluded that economic utility defined as a composite trait influenced by the characteristics that shape it favors genetic progress and the identification of animals with optimal performance in different bovine production systems.

Kernel Trait and Genetic Variability Analysis in BC2F1 Maize Lines Derived from Zea nicaraguensis Crosses

Maize (Zea mays L.) is an important cereal crop with significant applications in food, feed and industrial applications. This study aimed to increase maize yield and quality by evaluating core traits in introgressed Zea nicaraguensis individual’s recipients of LM13 and LM14 maize inbred lines. Kernel type, shape, color, dimensions and weight were assessed in 35 BC2F1 plants using standardized descriptor guidelines. Analysis of genotypic and phenotypic coefficients of variation, heritability and genetic progress showed significant genetic diversity and the influence of environmental factors. Significant sources of variability highlighted by principal component analysis were kernel color, endosperm color, and 100-seed weight. High heritability and genetic progress in kernel color and length-to-width ratio indicate great selection potential. Reintroducing the diversity lost in cultivated maize inherent in Zea nicaraguensis has the potential to improve both its agronomic performance and quality. Future research should aim to identify genetic markers and examine the interaction between genetic and environmental influences to optimize maize varieties for specific environments and consumer preferences, ultimately contributing to global food security and agricultural sustainability.

Comprehensive identification of pathogenic variants in retinoblastoma by long- and short-read sequencing

Retinoblastoma (RB) is the most common intraocular malignancy in childhood. The causal variants in RB are mostly characterized by previously used short-read sequencing (SRS) analysis, which has technical limitations in identifying structural variants (SVs) and phasing information. Long-read sequencing (LRS) technology has advantages over SRS in detecting SVs, phased genetic variants, and methylation. In this study, we comprehensively characterized the genetic landscape of RB using combinatorial LRS and SRS of 16 RB tumors and 16 matched blood samples. We detected a total of 232 somatic SVs, with an average of 14.5 SVs per sample across the whole genome in our cohort. We identified 20 distinct pathogenic variants disrupting RB1 gene, including three novel small variants and five somatic SVs. We found more somatic SVs were detected from LRS than SRS (140 vs. 122) in RB samples with WGS data, particularly the insertions (18 vs. 1). Furthermore, our analysis shows that, with the exception of one sample who lacked the methylation data, all samples presented biallelic inactivation of RB1 in various forms, including two cases with the biallelic hypermethylated promoter and four cases with compound heterozygous mutations which were missing in SRS analysis. By inferring relative timing of somatic events, we reveal the genetic progression that RB1 disruption early and followed by copy number changes, including amplifications of Chr2p and deletions of Chr16q, during RB tumorigenesis. Altogether, we characterize the comprehensive genetic landscape of RB, providing novel insights into the genetic alterations and mechanisms contributing to RB initiation and development. Our work also establishes a framework to analyze genomic landscape of cancers based on LRS data.

Genetic analysis of efficiency-related traits in Boer x Central Highland goats.

This study aimed to identify important non-genetic factors and estimate genetic parameters for efficiency-related traits in Boer x Central Highland goats. The genetic parameters were estimated using the Average Information Restricted Maximum Likelihood algorithm using the WOMBAT program fitting animal model. The least-squares means for growth efficiency from birth to 3 months (GE1), 3-6 months (GE2), 6-12 months (GE3), relative growth rate from birth to 3 months (RGR1), 3-6 months (RGR2) and 6-12 month (RGR3) were 294.0 ± 5.06, 36.6 ± 1.20, 44.9 ± 1.81, 1.46 ± 0.01, 0.32 ± 0.01 and 0.19 ± 0.01, respectively. Birth type, blood level, sex of the kid, and year of kidding had a sizable effect on efficiency-related traits. About 18, 3.0, 23, 20, and 12% of the phenotypic variation in GE2, GE3, RGR1, RGR2, and RGR3 was explained by the direct additive genetic effect. Except for RGR3, all investigated traits were under the influence of maternal genetic effect, and maternal heritability ranged from 0.09 to 0.17. The total heritability estimate depicts that slow genetic progress would be expected from selection. Nevertheless, even with this level of heritability, selection for efficiency-related traits would improve the efficiency of chevon production as these traits are economically important traits. Nearly six-months of age was when farmers sold Boer crossbred goats. Therefore, improving the growth efficiency till the marketing age (GE2) in such a scenario could increase the production efficiency.

Multiple-trait genomic prediction for swine meat quality traits using gut microbiome features as a correlated trait.

Traits such as meat quality and composition are becoming valuable in modern pork production; however, they are difficult to include in genetic evaluations because of the high phenotyping costs. Combining genomic information with multiple-trait indirect selection with cheaper indicator traits is an alternative for continued cost-effective genetic improvement. Additionally, gut microbiome information is becoming more affordable to measure using targeted rRNA sequencing, and its applications in animal breeding are becoming relevant. In this paper, we investigated the usefulness of microbial information as a correlated trait in selecting meat quality in swine. This study incorporated phenotypic data encompassing marbling, colour, tenderness, loin muscle and backfat depth, along with the characterization of gut (rectal) microbiota through 16S rRNA sequencing at three distinct time points of the animal's growth curve. Genetic progress estimation and cross-validation were employed to evaluate the utility of utilizing host genomic and gut microbiota information for selecting expensive-to-record traits in crossbred individuals. Initial steps involved variance components estimation using multiple-trait models on a training dataset, where the top 25 associated operational taxonomic units (OTU) for each meat quality trait and time point were included. The second step compared the predictive ability of multiple-trait models incorporating different numbers of OTU with single-trait models in a validation set. Results demonstrated the advantage of including genomic information for some traits, while in some instances, gut microbial information proved advantageous, namely, for marbling and pH. The study suggests further investigation into the shared genetic architecture between microbial features and traits, considering microbial data's compositional and high-dimensional nature. This research proposes a straightforward method to enhance swine breeding programs for improving costly-to-record traits like meat quality by incorporating gut microbiome information.