Genomic Programs Research Articles

Genetics Visit Uptake Among Individuals Receiving Clinically Actionable Genomic Screening Results

Screening unselected populations for clinically actionable genetic disease risk can improve ascertainment and facilitate risk management. Genetics visits may encourage at-risk individuals to perform recommended management, but little has been reported on genetics visit completion or factors associated with completion in genomic screening programs. To identify factors associated with postdisclosure genetics visits in a genomic screening cohort. This was a cohort study of biobank data in a health care system in central Pennsylvania. Participants' exome sequence data were reviewed for pathogenic or likely pathogenic (P/LP) results in all genes on the American College of Medical Genetics and Genomics Secondary Findings list. Clinically confirmed results were disclosed by phone and letter. Participants included adult MyCode biobank participants who received P/LP results between July 2015 and November 2019. Data were analyzed from May 2021 to March 2022. Clinically confirmed P/LP result disclosed by phone or letter. Completion of genetics visit in which the result was discussed and variables associated with completion were assessed by electronic health record (EHR) review. Among a total of 1160 participants (703 [60.6%] female; median [IQR] age, 57.0 [42.1-68.5] years), fewer than half of participants (551 of 1160 [47.5%]) completed a genetics visit. Younger age (odds ratio [OR] for age 18-40 years, 2.98; 95% CI, 1.40-6.53; OR for age 41-65 years, 2.36; 95% CI, 1.22-4.74; OR for age 66-80 years, 2.60; 95% CI, 1.41-4.98 vs age ≥81 years); female sex (OR, 1.49; 95% CI, 1.14-1.96); being married (OR, 1.74; 95% CI, 1.23-2.47) or divorced (OR, 1.80; 95% CI, 1.11-2.91); lower Charlson comorbidity index (OR for score of 0-2, 1.76; 95% CI, 1.16-2.68; OR for score of 3-4, 1.73; 95% CI, 1.18-2.54 vs score of ≥5); EHR patient portal use (OR, 1.42; 95% CI, 1.06-1.89); living closer to a genetics clinic (OR, 1.64; 95% CI, 1.14-2.36 for <8.9 miles vs >20.1 miles); successful results disclosure (OR for disclosure by genetic counselor, 16.32; 95% CI, 8.16-37.45; OR for disclosure by research assistant, 20.30; 95% CI, 10.25-46.31 vs unsuccessful phone disclosure); and having a hereditary cancer result (OR, 2.13; 95% CI, 1.28-3.58 vs other disease risk) were significantly associated with higher rates of genetics visit completion. Preference to follow up with primary care was the most common reported reason for declining a genetics visit (68 of 152 patients [44.7%]). This cohort study of a biobank-based population genomic screening program suggests that targeted patient engagement, improving multidisciplinary coordination, and reducing barriers to follow-up care may be necessary for enhancing genetics visit uptake.

Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle

BackgroundGrowth rate is an important component of feed conversion efficiency in cattle and varies across the different stages of the finishing period. The metabolic effect of the rumen microbiome is essential for cattle growth, and investigating the genomic and microbial factors that underlie this temporal variation can help maximize feed conversion efficiency at each growth stage.ResultsBy analysing longitudinal body weights during the finishing period and genomic and metagenomic data from 359 beef cattle, our study demonstrates that the influence of the host genome on the functional rumen microbiome contributes to the temporal variation in average daily gain (ADG) in different months (ADG1, ADG2, ADG3, ADG4). Five hundred and thirty-three additive log-ratio transformed microbial genes (alr-MG) had non-zero genomic correlations (rg) with at least one ADG-trait (ranging from |0.21| to |0.42|). Only a few alr-MG correlated with more than one ADG-trait, which suggests that a differential host-microbiome determinism underlies ADG at different stages. These alr-MG were involved in ribosomal biosynthesis, energy processes, sulphur and aminoacid metabolism and transport, or lipopolysaccharide signalling, among others. We selected two alternative subsets of 32 alr-MG that had a non-uniform or a uniform rg sign with all the ADG-traits, regardless of the rg magnitude, and used them to develop a microbiome-driven breeding strategy based on alr-MG only, or combined with ADG-traits, which was aimed at shaping the rumen microbiome towards increased ADG at all finishing stages. Combining alr-MG information with ADG records increased prediction accuracy of genomic estimated breeding values (GEBV) by 11 to 22% relative to the direct breeding strategy (using ADG-traits only), whereas using microbiome information, only, achieved lower accuracies (from 7 to 41%). Predicted selection responses varied consistently with accuracies. Restricting alr-MG based on their rg sign (uniform subset) did not yield a gain in the predicted response compared to the non-uniform subset, which is explained by the absence of alr-MG showing non-zero rg at least with more than one of the ADG-traits.ConclusionsOur work sheds light on the role of the microbial metabolism in the growth trajectory of beef cattle at the genomic level and provides insights into the potential benefits of using microbiome information in future genomic breeding programs to accurately estimate GEBV and increase ADG at each finishing stage in beef cattle.

Forging the path to precision medicine in Qatar: a public health perspective on pharmacogenomics initiatives.

Pharmacogenomics (PGx) is an important component of precision medicine that promises tailored treatment approaches based on an individual's genetic information. Exploring the initiatives in research that help to integrate PGx test into clinical setting, identifying the potential barriers and challenges as well as planning the future directions, are all important for fruitful PGx implementation in any population. Qatar serves as an exemplar case study for the Middle East, having a small native population compared to a diverse immigrant population, advanced healthcare system, national genome program, and several educational initiatives on PGx and precision medicine. This paper attempts to outline the current state of PGx research and implementation in Qatar within the global context, emphasizing ongoing initiatives and educational efforts. The inclusion of PGx in university curricula and healthcare provider training, alongside precision medicine conferences, showcase Qatar's commitment to advancing this field. However, challenges persist, including the requirement for population specific implementation strategies, complex genetic data interpretation, lack of standardization, and limited awareness. The review suggests policy development for future directions in continued research investment, conducting clinical trials for the feasibility of PGx implementation, ethical considerations, technological advancements, and global collaborations to overcome these barriers.

Eliciting parental preferences and values for the return of additional findings from genomic sequencing

Health economic evidence is needed to inform the design of high-value and cost-effective processes for returning genomic results from analyses for additional findings (AF). This study reports the results of a discrete-choice experiment designed to elicit preferences for the process of returning AF results from the perspective of parents of children with rare conditions and to estimate the value placed on AF analysis. Overall, 94 parents recruited within the Australian Genomics and Melbourne Genomics programmes participated in the survey, providing preferences in a total of 1128 choice scenarios. Statistically significant preferences were identified for the opportunity to change the choices made about AF; receiving positive AF in person from a genetic counsellor; timely access to a medical specialist and high-quality online resources; receiving automatic updates through a secure online portal if new information becomes available; and lower costs. For AF uptake rates ranging between 50–95%, the mean per person value from AF analysis was estimated at AU$450–$1700 (US$300–$1140). The findings enable the design of a value-maximising process of analysis for AF in rare-disease genomic sequencing.

Diversity of Omicron sublineages and clinical characteristics in hospitalized patients in the southernmost state of Brazil

BackgroundOmicron has become the dominant variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) since first reported in November 2021. From the initially detected Wuhan lineage, sublineages BA.2, BA.4, BA.5, BQ, XAG, and XBB have emerged over time and are dominant in many countries. Therefore, the aim is to evaluate which variants are circulating and the clinical characteristics of inpatients infected with the Omicron variant.MethodsThis retrospective cohort study selected hospitalized patients admitted with respiratory symptoms to a hospital in the state of Rio Grande do Sul, Brazil, between June and July 2022. SARS-CoV-2 results were analyzed together with clinical outcomes and vaccination status. A viral genome library was prepared and forwarded to the Illumina MiSeq Platform for sequencing.ResultsIn total, 37 genomes were sequenced. Concerning the Omicron sublineages, our study detected: BA.1 (21 K), BA.2 (21 L), BA.4 (22A), BA.5 (22B), BA.2.12.1 (22C), BQ.1 (22E), XBB (22F), and XAG recombinant. Omicron BA.5 (30%), BA.2 (19%), and BQ.1 (19%) were the most frequent sublineages, respectively. In total, 38% of patients present hypertension, and the most common symptoms were coughing (62%). Analyzing the COVID-19 vaccination, 30% of patients were fully vaccinated, 49% had a partial vaccination status, and 21% were unvaccinated (no dose).ConclusionsBA.5 was the most prevalent sublineage in our study and surpassed the predominance of BA.2, as reported by the national genomic surveillance program. BQ.1 was diagnosed earlier in this study than it was officially reported in the state. Current data have demonstrated that the Omicron variant causes less severe infections, with the high rate of transmissibility and mutational landscape causing the rapid emergence of new sublineages.

Non-SARS-CoV-2 respiratory viral detection and whole genome sequencing from COVID-19 rapid antigen test devices: a laboratory evaluation study

There has been high uptake of rapid antigen test device use for point-of-care COVID-19 diagnosis. Individuals who are symptomatic but test negative on COVID-19 rapid antigen test devices might have a different respiratory viral infection. We aimed to detect and sequence non-SARS-CoV-2 respiratory viruses from rapid antigen test devices, which could assist in the characterisation and surveillance of circulating respiratory viruses in the community. We applied archival clinical nose and throat swabs collected between Jan 1, 2015, and Dec 31, 2022, that previously tested positive for a common respiratory virus (adenovirus, influenza, metapneumovirus, parainfluenza, rhinovirus, respiratory syncytial virus [RSV], or seasonal coronavirus; 132 swabs and 140 viral targets) on PCR to two commercially available COVID-19 rapid antigen test devices, the Panbio COVID-19 Ag Rapid Test Device and Roche SARS-CoV-2 Antigen Self-Test. In addition, we collected 31 COVID-19 rapid antigen test devices used to test patients who were symptomatic at The Royal Melbourne Hospital emergency department in Melbourne, Australia. We extracted total nucleic acid from the device paper test strips and assessed viral recovery using multiplex real-time PCR (rtPCR) and capture-based whole genome sequencing. Sequence and genome data were analysed through custom computational pipelines, including subtyping. Of the 140 respiratory viral targets from archival samples, 89 (64%) and 88 (63%) were positive on rtPCR for the relevant taxa following extraction from Panbio or Roche rapid antigen test devices, respectively. Recovery was variable across taxa: we detected influenza A in nine of 18 samples from Panbio and seven of 18 from Roche devices; parainfluenza in 11 of 20 samples from Panbio and 12 of 20 from Roche devices; human metapneumovirus in 11 of 16 from Panbio and 14 of 16 from Roche devices; seasonal coronavirus in eight of 19 from Panbio and two of19from Roche devices; rhinovirus in 24 of 28 from Panbio and 27 of 28 from Roche devices; influenza B in fourof 15 in both devices; and RSV in 16 of 18 in both devices. Of the 31 COVID-19 devices collected from The Royal Melbourne Hospital emergency department, 11 tested positive for a respiratory virus on rtPCR, including one device positive for influenza A virus, one positive for RSV, four positive for rhinovirus, and five positive for SARS-CoV-2. Sequences of target respiratory viruses from archival samples were detected in 55 (98·2%) of 56samples from Panbio and 48 (85·7%) of 56 from Roche rapid antigen test devices. 98 (87·5%) of 112 viral genomes were completely assembled from these data, enabling subtyping for RSV and influenza viruses. All 11samples collected from the emergency department had viral sequences detected, with near-complete genomes assembled for influenza A and RSV. Non-SARS-CoV-2 respiratory viruses can be detected and sequenced from COVID-19 rapid antigen devices. Recovery of near full-length viral sequences from these devices provides a valuable opportunity to expand genomic surveillance programmes for public health monitoring of circulating respiratory viruses. Australian Government Medical Research Future Fund and Australian National Health and Medical Research Council.

Genome-wide association study for conformation traits in Ayrshire cattle.

The genetic improvement of cattle is able to provide the highest economic efficiency. Animals with best external features often have the highest indicators of productivity and nonspecific resistance. In order to identify single nucleotide polymorphism (SNP) markers and genes, potentially responsible for conformation traits of Ayrshire cattle, we conducted a genome-wide association study (GWAS). Blood samples were collected from 495 first-calf Ayrshire heifers. For all animals, a linear assessment was carried out, which consisted of 17 conformation traits and 13 exterior flaws. Our study revealed a total of 43 SNPs on chromosomes BTA1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 14, 16, 18, 19, 22, 25, 27, and 29 associated with conformation traits, four of which have met the significance threshold. Among these four significant SNPs, genes associated with exterior flaws such as tilted udder floor and weak loin and SNPs associated with weak back were identified. The markers and genes identified in the corresponding genomic regions are promising candidates for further investigation of the biological processes involved in cow exterior formation and function. The results obtained, including the MYO1B gene associated with weak loin, PEPD and ZFC3H1 genes related to tilted udder floor, and EDNRB gene associated with weak back can be effectively used as molecular markers in genomic selection programs.

Reproductive traits in Pura Raza Española mares manifest inbreeding depression from low levels of homozygosity.

Inbreeding depression is a genetic phenomenon associated with the loss of fitness and mean phenotypic performance due to mating between relatives. Historically, inbreeding coefficients have been estimated from pedigree information. However, the onset of genomic selection programs provides large datasets of individuals genotyped using SNP arrays, enabling more precise assessment of an individual's genomic-level inbreeding using genomic data. One of the traits most sensitive to issues stemming from increased inbreeding is reproduction. This is particularly important in equine, in which fertility is only moderate compared to other livestock species. To explore this further, we evaluated the effect of inbreeding on five reproductive traits (age at first foaling (AFF), average interval between foalings (AIF), total number of foalings (NF), productive life (PL) and reproductive efficiency (RE)) in Pura Raza Español mares using genomic data. Residual predicted phenotypes were obtained by purging these traits through the REML (wgResidual ) and ssGREML (gResidual ) approaches in reproductive data of 29,847 PRE mares using the BLUPF90+ program. Next, we used pedigree-based (Fped ) and ROH-based genomic (FROH ) inbreeding coefficients derived from 1018 animals genotyped with 61,271 SNPs to estimate the inbreeding depression (linear regression). Our results indicated significant levels of inbreeding depression for all reproductive traits, with the exception of the AIF trait when Fped was used. However, all traits were negatively affected by the increase in genomic inbreeding, and FROH was found to capture more inbreeding depression than Fped . Likewise, REML models (ssGREML) using genomic data for estimated predicted residual phenotypes resulted in higher variance explained by the model compared with the models not using genomics (REML). Finally, a segmented regression analysis was conducted to evaluate the effect of inbreeding depression, revealing that the levels of genealogical and genomic homozygosity do not manifest uniformly in reproductive traits. In contrast, the levels of inbreeding depression ranged from low to high as homozygosity increased. This analysis also showed that reproductive traits are very sensitive to inbreeding depression, even with relatively low levels of homozygosity.

Using implementation science to evaluate a population-wide genomic screening program: Findings from the first 20,000 In Our DNA SC participants

We use the implementation science framework RE-AIM (reach, effectiveness, adoption, implementation, and maintenance) to describe outcomes of In Our DNA SC, a population-wide genomic screening (PWGS) program. In Our DNA SC involves participation through clinical appointments, community events, or at home collection. Participants provide a saliva sample that is sequenced by Helix, and those with a pathogenic variant or likely pathogenic variant for CDC Tier 1 conditions are offered free genetic counseling. We assessed key outcomes among the first cohort of individuals recruited. Over 14months, 20,478 participants enrolled, and 14,053 samples were collected. The majority selected at-home sample collection followed by clinical sample collection and collection at community events. Participants were predominately female, White (self-identified), non-Hispanic, and between the ages of 40-49. Participants enrolled through community events were the most racially diverse and the youngest. Half of those enrolled completed the program. We identified 137 individuals with pathogenic or likely pathogenic variants for CDC Tier 1 conditions. The majority (77.4%) agreed to genetic counseling, and of those that agreed, 80.2% completed counseling. Twelve clinics participated, and we conducted 108 collection events. Participants enrolled at home were most likely to return their sample for sequencing. Through this evaluation, we identified facilitators and barriers to implementation of our state-wide PWGS program. Standardized reporting using implementation science frameworks can help generalize strategies and improve the impact of PWGS.

Unraveling the genetic evolution of SARS-CoV-2 Recombinants using mutational dynamics across the different lineages.

Recombination serves as a common strategy employed by RNA viruses for their genetic evolution. Extensive genomic surveillance during the COVID-19 pandemic has reported SARS-CoV-2 Recombinant strains indicating recombination events during the viral evolution. This study introspects the phenomenon of genome recombination by tracing the footprint of prominent lineages of SARS-CoV-2 at different time points in the context of on-going evolution and emergence of Recombinants. Whole genome sequencing was carried out for 2,516 SARS-CoV-2 (discovery cohort) and 1,126 (validation cohort) using nasopharyngeal samples collected between the time period of March 2020 to August 2022, as part of the genomic surveillance program. The sequences were classified according to the different lineages of SARS-CoV-2 prevailing in India at respective time points. Mutational diversity and abundance evaluation across the 12 lineages identified 58 Recombinant sequences as harboring the least number of mutations (n = 111), with 14 low-frequency unique mutations with major chunk of mutations coming from the BA.2. The spontaneously/dynamically increasing and decreasing trends of mutations highlight the loss of mutations in the Recombinants that were associated with the SARS-CoV-2 replication efficiency, infectivity, and disease severity, rendering them functionally with low infectivity and pathogenicity. Linkage disequilibrium (LD) analysis revealed that mutations comprising the LD blocks of BA.1, BA.2, and Recombinants were found as minor alleles or as low-frequency alleles in the LD blocks from the previous SARS-CoV-2 variant samples, especially Pre-VOC. Moreover, a dissipation in the size of LD blocks as well as LD decay along with a high negative regression coefficient (R squared) value was demonstrated in the Omicron and BA.1 and BA.2 lineages, which corroborated with the breakpoint analysis. Together, the findings help to understand the evolution and emergence of Recombinants after the Omicron lineages, for sustenance and adaptability, to maintain the epidemic spread of SARS-CoV-2 in the host population already high in immunity levels.

A regional genomic surveillance program is implemented to monitor the occurrence and emergence of SARS-CoV-2 variants in Yubei District, China

BackgroundIn December 2022, Chongqing experienced a significant surge in coronavirus disease 2019 (COVID-19) epidemic after adjusting control measures in China. Given the widespread immunization of the population with the BA.5 variant, it is crucial to actively monitor severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant evolution in Chongqing's Yubei district.MethodsIn this retrospective study based on whole genome sequencing, we collected oropharyngeal and nasal swab of native COVID-19 cases from Yubei district between January to May 2023, along with imported cases from January 2022 to January 2023. Through second-generation sequencing, we generated a total of 578 genomes.ResultsPhylogenetic analyses revealed these genomes belong to 47 SARS-CoV-2 Pango lineages. BA.5.2.48 was dominant from January to April 2023, rapidly replaced by XBB* variants from April to May 2023. Bayesian Skyline Plot reconstructions indicated a higher evolutionary rate (6.973 × 10–4 subs/site/year) for the XBB.1.5* lineage compared to others. The mean time to the most recent common ancestor (tMRCA) of BA.5.2.48* closely matched BA.2.75* (May 27, 2022). Using multinomial logistic regression, we estimated growth advantages, with XBB.1.9.1 showing the highest growth advantage (1.2, 95% HPI:1.1–1.2), followed by lineage FR.1 (1.1, 95% HPI:1.1–1.2).ConclusionsOur monitoring reveals the rapid replacement of the previously prevalent BA.5.2.48 variant by XBB and its sub-variants, underscoring the ineffectiveness of herd immunity and breakthrough BA.5 infections against XBB variants. Given the ongoing evolutionary pressure, sustaining a SARS-CoV-2 genomic surveillance program is imperative.

Genomic predictions for resistance to Aeromonas hydrophila in pacu (Piaractus mesopotamicus)

Infections caused by the bacterium Aeromonas hydrophila result in high mortality outbreaks in pacu (Piaractus mesopotamicus) production. An alternative to increase the resistance to A. hydrophila infection is the implementation of genomic selection programs, which can contribute to the sustainable development of the Brazilian aquaculture. In addition, low-density SNP panels, optimized by genotype imputation, represent a low-cost tool for implementing genomic selection on a commercial scale. This study aimed to evaluate the accuracy of genomic prediction using low (0.5 and 1 K) and medium (15 K imputed) density SNP panels; and compare breeding values accuracy with restriction-site associated DNA sequencing (18 K) and pedigree-based methods for individuals challenged for A. hydrophila. The genomic prediction analyses were conducted using genotypes from the medium-density SNP panel of pacu as reference and genotypes from a low-density SNP panel (0.5 and 1 K) using target genotype-by-sequencing technology (tGBS) for imputation. Approximately 15 K SNPs were successfully imputed with accuracy (r2) above 0.8. Time to death (TD) and binary survival (BS) against A. hydrophila infection were used as phenotypes for genomic prediction. Genomic values were estimated using the GBLUP model adopting different genotyping methods (SNP array and RAD-seq) and densities of SNPs (0.5 K, 1 K, and 15K_imputed for the array and 18 K for RAD-seq). Accuracies of genomic approaches using different methods and densities were compared to the pedigree method PBLUP to assess the benefits of incorporating genomic information. The accuracy of predicting breeding values using genomic methods outperformed the estimates obtained through PBLUP by 33%, 39%, and 67% for TD, and 36%, 39%, and 82% for BS, considering the densities of 0.5, 1, and 15K_imputed, respectively. The imputation strategy yielded better results in terms of genomic prediction accuracy for both traits. The RAD-seq genotyping method produced low-accuracy estimates (∼30% lower for both traits) compared to PBLUP, indicating that such method may not be suitable for genomic prediction of these traits. Genomic selection using genotype imputation is a viable and cost-effective approach to increase resistance to A. hydrophila infection in pacu and reduce genotyping costs without compromising genomic prediction accuracy.

Genome-wide association studies for economically important traits in mink using copy number variation

Copy number variations (CNVs) are structural variants consisting of duplications and deletions of DNA segments, which are known to play important roles in the genetics of complex traits in livestock species. However, CNV-based genome-wide association studies (GWAS) have remained unexplored in American mink. Therefore, the purpose of the current study was to investigate the association between CNVs and complex traits in American mink. A CNV-based GWAS was performed with the ParseCNV2 software program using deregressed estimated breeding values of 27 traits as pseudophenotypes, categorized into traits of growth and feed efficiency, reproduction, pelt quality, and Aleutian disease tests. The study identified a total of 10,137 CNVs (6968 duplications and 3169 deletions) using the Affymetrix Mink 70K single nucleotide polymorphism (SNP) array in 2986 American mink. The association analyses identified 250 CNV regions (CNVRs) associated with at least one of the studied traits. These CNVRs overlapped with a total of 320 potential candidate genes, and among them, several genes have been known to be related to the traits such as ARID1B, APPL1, TOX, and GPC5 (growth and feed efficiency traits); GRM1, RNASE10, WNT3, WNT3A, and WNT9B (reproduction traits); MYO10, and LIMS1 (pelt quality traits); and IFNGR2, APEX1, UBE3A, and STX11 (Aleutian disease tests). Overall, the results of the study provide potential candidate genes that may regulate economically important traits and therefore may be used as genetic markers in mink genomic breeding programs.

A response playbook for early detection and population surveillance of new SARS-CoV-2 variants in a regional public health laboratory.

Timely genomic surveillance is required to inform public health responses to new SARS-CoV-2 variants. However, the processes involved in local genomic surveillance introduce inherent time constraints. The Regional Innovative Public Health Laboratory in Chicago developed and employed a genomic surveillance response playbook for the early detection and surveillance of emerging SARS-CoV-2 variants. The playbook outlines modifications to sampling strategies, laboratory workflows, and communication processes based on the emerging variant's predicted viral characteristics, observed public health impact in other jurisdictions and local community risk level. The playbook outlines procedures for implementing and reporting enhanced and accelerated genomic surveillance, including supplementing whole genome sequencing (WGS) with variant screening by quantitative PCR (qPCR). The ability of the playbook to improve the response to an emerging variant was tested for SARS-CoV-2 Omicron BA.1. Increased submission of clinical remnant samples from local hospital laboratories enabled detection of a new variant at an average of 1.4% prevalence with 95% confidence rather than 3.5% at baseline. Genotyping qPCR concurred with WGS lineage assignments in 99.9% of 1541 samples with results by both methods, and was more sensitive, providing lineage results in 90.4% of 1833 samples rather than 85.1% for WGS, while significantly reducing the time to lineage result. The genomic surveillance response playbook provides a structured, stepwise, and data-driven approach to responding to emerging SARS-CoV-2 variants. These pre-defined processes can serve as a template for other genomic surveillance programs to streamline workflows and expedite the detection and public health response to emerging variants. Based on the processes piloted during the Omicron BA.1 response, this method has been applied to subsequent Omicron subvariants and can be readily applied to future SARS-CoV-2 emerging variants and other public health surveillance activities.

Neonatal CD4+ T cells have a characteristic transcriptome and epigenome and respond to TCR stimulation with proliferation and yet a limited immune response.

The adaptive immune response is coordinated by CD4+ T cells, which determine the type and strength of the immune response and the effector cells involved. It has been reported that CD4+ T cells are less responsive in neonates, leading to low activation of the cellular response and poor antibody production by B cells. This low response is essential for the tolerant window that favors birth transition from the sterile environment in the womb to the outside world but leaves neonates vulnerable to infection, which is still an important health issue. Neonates have a high morbidity and mortality rate due to infections, and the molecular reasons are still understudied. We asked whether the neonatal naive CD4+ T cells have a genomic program that predisposes them to a low response. Therefore, we evaluated the transcriptome and epigenome of human neonatal and adult naive CD4+ T cells. Our results point to a gene expression profile forming a distinct regulatory network in neonatal cells, which favors proliferation and a low T-cell response. Such expression profile is supported by a characteristic epigenetic landscape of neonatal CD4+ T cells, which correlates with the characteristic transcriptome of the neonatal cells. These results were confirmed by experiments showing a low response to activation signals, higher proliferation, and lower expression of cytokines of neonatal CD4+ T cells as compared to adult cells. Understanding this network could lead to novel vaccine formulations and better deal with life-threatening diseases during this highly vulnerable period of our lives.

Characterizing structural variants based on graph-genotyping provides insights into pig domestication and local adaption

Structural variants (SVs), such as deletions (DELs) and insertions (INSs), contribute substantially to pig genetic diversity and phenotypic variation. Using a library of SVs discovered from long-read primary assemblies and short-read sequenced genomes, we map pig genomic SVs with a graph-based method for re-genotyping SVs in 402 genomes. Our results demonstrate that those SVs harboring specific trait-associated genes may greatly shape pig domestication and local adaptation. Further characterization of SVs reveals that some population-stratified SVs may alter the transcription of genes by affecting regulatory elements. We identify that the genotypes of two DELs (296-bp DEL, chr7: 52,172,101–52,172,397; 278-bp DEL, chr18: 23,840,143–23,840,421) located in muscle-specific enhancers are associated with the expression of target genes related to meat quality (FSD2) and muscle fiber hypertrophy (LMOD2 and WASL) in pigs. Our results highlight the role of SVs in domestic porcine evolution, and the identified candidate functional genes and SVs are valuable resources for future genomic research and breeding programs in pigs.

Assessing genetic diversity and defining signatures of positive selection on the genome of dromedary camels from the southeast of the Arabian Peninsula

Dromedary camels (Camelus dromedarius) are members of the Camelini tribe within the Camelidae family. They are distributed throughout North Africa, the Arabian Peninsula and Southeast Asia. This domestic species is characterized by its superior adaptability to the harsh desert environment. In this study, whole autosomal data of 29 dromedary samples from the Southeast Arabian Peninsula in Oman; 10 from Muscat, 14 from Al-Batinah, and 5 from Al-Sharqiya, were investigated to assess their genetic relationship and to define candidate signatures of positive selection. A minimal genetic distinction that separates Muscat dromedaries from the other two populations was observed, with a degree of genetic admixture between them. Using the de-correlated composite of multiple signals (DCMS) approach, a total of 47 candidate regions within the autosomes of these dromedary populations were defined with signatures of positive selection. These candidate regions harbor a total of 154 genes that are mainly associated with functional categories related to immune response, lipid metabolism and energy expenditure, optical and auditory functions, and long-term memory. Different functional genomic variants were called on the candidate regions and respective genes that warrant further investigation to find possible association with the different favorable phenotypes in dromedaries. The output of this study paves the way for further research efforts aimed at defining markers for use in genomic breeding programs, with the goal of conserving the genetic diversity of the species and enhancing its productivity.

Sequenced-based GWAS for linear classification traits in Belgian Blue beef cattle reveals new coding variants in genes regulating body size in mammals.

Cohorts of individuals that have been genotyped and phenotyped for genomic selection programs offer the opportunity to better understand genetic variation associated with complex traits. Here, we performed an association study for traits related to body size and muscular development in intensively selected beef cattle. We leveraged multiple trait information to refine and interpret the significant associations. After a multiple-step genotype imputation to the sequence-level for 14,762 Belgian Blue beef (BBB) cows, we performed a genome-wide association study (GWAS) for 11 traits related to muscular development and body size. The 37 identified genome-wide significant quantitative trait loci (QTL) could be condensed in 11 unique QTL regions based on their position. Evidence for pleiotropic effects was found in most of these regions (e.g., correlated association signals, overlap between credible sets (CS) of candidate variants). Thus, we applied a multiple-trait approach to combine information from different traits to refine the CS. In several QTL regions, we identified strong candidate genes known to be related to growth and height in other species such as LCORL-NCAPG or CCND2. For some of these genes, relevant candidate variants were identified in the CS, including three new missense variants in EZH2, PAPPA2 and ADAM12, possibly two additional coding variants in LCORL, and candidate regulatory variants linked to CCND2 and ARMC12. Strikingly, four other QTL regions associated with dimension or muscular development traits were related to five (recessive) deleterious coding variants previously identified. Our study further supports that a set of common genes controls body size across mammalian species. In particular, we added new genes to the list of those associated with height in both humans and cattle. We also identified new strong candidate causal variants in some of these genes, strengthening the evidence of their causality. Several breed-specific recessive deleterious variants were identified in our QTL regions, probably as a result of the extreme selection for muscular development in BBB cattle.

Identification of genetic associations and functional SNPs of bovine KLF6 gene on milk production traits in Chinese holstein

BackgroundOur previous research identified the Kruppel like factor 6 (KLF6) gene as a prospective candidate for milk production traits in dairy cattle. The expression of KLF6 in the livers of Holstein cows during the peak of lactation was significantly higher than that during the dry and early lactation periods. Notably, it plays an essential role in activating peroxisome proliferator-activated receptor α (PPARα) signaling pathways. The primary aim of this study was to further substantiate whether the KLF6 gene has significant genetic effects on milk traits in dairy cattle.ResultsThrough direct sequencing of PCR products with pooled DNA, we totally identified 12 single nucleotide polymorphisms (SNPs) within the KLF6 gene. The set of SNPs encompasses 7 located in 5′ flanking region, 2 located in exon 2 and 3 located in 3′ untranslated region (UTR). Of these, the g.44601035G > A is a missense mutation that resulting in the replacement of arginine (CGG) with glutamine (CAG), consequently leading to alterations in the secondary structure of the KLF6 protein, as predicted by SOPMA. The remaining 7 regulatory SNPs significantly impacted the transcriptional activity of KLF6 following mutation (P < 0.005), manifesting as changes in transcription factor binding sites. Additionally, 4 SNPs located in both the UTR and exons were predicted to influence the secondary structure of KLF6 mRNA using the RNAfold web server. Furthermore, we performed the genotype-phenotype association analysis using SAS 9.2 which found all the 12 SNPs were significantly correlated to milk yield, fat yield, fat percentage, protein yield and protein percentage within both the first and second lactations (P < 0.0001 ~ 0.0441). Also, with Haploview 4.2 software, we found the 12 SNPs linked closely and formed a haplotype block, which was strongly associated with five milk traits (P < 0.0001 ~ 0.0203).ConclusionsIn summary, our study represented the KLF6 gene has significant impacts on milk yield and composition traits in dairy cattle. Among the identified SNPs, 7 were implicated in modulating milk traits by impacting transcriptional activity, 4 by altering mRNA secondary structure, and 1 by affecting the protein secondary structure of KLF6. These findings provided valuable molecular insights for genomic selection program of dairy cattle.

Genomic Approaches to Disease Resistance in Livestock

Purpose: The main objective of this study was to explore the use of genomics and selective breeding to enhance disease resistance in livestock populations.&#x0D; Methodology: The study adopted a desktop research methodology. Desk research refers to secondary data or that which can be collected without fieldwork. Desk research is basically involved in collecting data from existing resources hence it is often considered a low cost technique as compared to field research, as the main cost is involved in executive’s time, telephone charges and directories. Thus, the study relied on already published studies, reports and statistics. This secondary data was easily accessed through the online journals and library.&#x0D; Findings: The findings revealed that there exists a contextual and methodological gap relating to genomic approaches to disease resistance in livestock. Preliminary empirical review revealed that genomic approaches to disease resistance in livestock have emerged as powerful tools in the field of animal breeding and management. Over the past few years, research and empirical studies have consistently demonstrated the immense potential of genomics to revolutionize the way we address disease challenges in livestock populations. These approaches have allowed for delving deep into the genetic makeup of animals, identifying specific markers and genetic traits associated with disease resistance. By doing so, we can now make more informed breeding decisions, selecting animals with superior resistance profiles and improving overall herd or flock health.&#x0D; Unique Contribution to Theory, Practice and Policy: The theory of Evolution by Natural Selection, Quantitative Genetics theory and the Genomic Selection theory may be used to anchor future studies on genomic approaches in disease resistance. The study made the following recommendations: implementing genomic selection programs, promoting collaborative research, focusing on sustainable breeding practices, enhancing biosecurity measure, investing in genomic education and training and monitoring long term impacts.