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The within-host evolutionary dynamics of tuberculosis (TB) remain unclear, and underlying biological characteristics render standard population genetic approaches based upon the Wright-Fisher model largely inappropriate. In addition, the compact genome combined with an absence of recombination is expected to result in strong purifying selection effects. Thus, it is imperative to establish a biologically relevant evolutionary framework incorporating these factors in order to enable an accurate study of this important human pathogen. Further, such a model is critical for inferring fundamental evolutionary parameters related to patient treatment, including mutation rates and the severity of infection bottlenecks. We here implement such a model and infer the underlying evolutionary parameters governing within-patient evolutionary dynamics. Results demonstrate that the progeny skew associated with the clonal nature of TB severely reduces genetic diversity and that the neglect of this parameter in previous studies has led to significant mis-inference of mutation rates. As such, our results suggest an underlying de novo mutation rate that is considerably faster than previously inferred, and a progeny distribution differing significantly from Wright-Fisher assumptions. This inference represents a more appropriate evolutionary null model, against which the periodic effects of positive selection, associated with drug-resistance for example, may be better assessed.

Twisted trunks are not uncommon in trees, but their effects on tree growth are still unclear. Among coniferous tree species, the phenomenon of trunk distortion is more prominent in Pinus yunnanensis . To expand the germplasm of genetic resources, we selected families with excellent phenotypic traits to provide material for advanced generation breeding. The progeny test containing 93 superior families (3240 trees) was used as the research material. Phenotypic measurements and estimated genetic parameters (family heritability, realistic gain and genetic gain) were performed at 9, 15, and 18 years of age, respectively. The genetic evaluation yielded the following results (1) The intra-family variance component of plant height (PH) was greater than that of the inter-family, while the inter-family variance components of other traits (diameter at breast height (DBH), crown diameter (CD), height under branches (HUB), degree of stem-straightness (DS)) were greater than that of the intra-family, indicating that there was abundant variation among families and potential for selection. (2) At half rotation period (18 years old), there was a significant correlation among the traits. The proportion of trees with twisted trunks (level 1–3 straightness) reached 48%. The DS significantly affected growth traits, among which PH and DBH were the most affected. The volume loss rate caused by twisted trunk was 18.06-56.75%, implying that trunk distortion could not be completely eliminated after an artificial selection. (3) The influence of tree shape, crown width, and trunk on volume increased, and the early-late correlation between PH, DBH and volume was extremely significant. The range of phenotypic coefficient of variation, genetic variation coefficient and family heritability of growth traits (PH, DBH, and volume) were 44.29-127.13%, 22.88-60.87%, and 0.79–0.83, respectively. (4) A total of 21 superior families were selected by the method of membership function combined with independent selection. Compared with the mid-term selection (18 years old), the accuracy of early selection (9 years old) reached 77.5%. The selected families’ genetic gain and realistic gain range were 5.79-19.82% and 7.12-24.27%, respectively. This study can provide some useful reference for the breeding of coniferous species.

[This corrects the article DOI: 10.1371/journal.pone.0193164.].

In late 2022, SARS-CoV-2 Omicron subvariants have become highly diversified, and XBB is spreading rapidly around the world. Our phylogenetic analyses suggested that XBB emerged through the recombination of two cocirculating BA.2 lineages, BJ.1 and BM.1.1.1 (a progeny of BA.2.75), during the summer of 2022. XBB.1 is the variant most profoundly resistant to BA.2/5 breakthrough infection sera to date and is more fusogenic than BA.2.75. The recombination breakpoint is located in the receptor-binding domain of spike, and each region of the recombinant spike confers immune evasion and increases fusogenicity. We further provide the structural basis for the interaction between XBB.1 spike and human ACE2. Finally, the intrinsic pathogenicity of XBB.1 in male hamsters is comparable to or even lower than that of BA.2.75. Our multiscale investigation provides evidence suggesting that XBB is the first observed SARS-CoV-2 variant to increase its fitness through recombination rather than substitutions. XBB is the first recombinant, globally dominant variant of SARS-CoV-2. Here, the authors examine the variant’s origins and virological properties, showing it is the first example of SARS-CoV-2 improving its fitness through recombination.

The Tanzania oil palm population was introduced to Sumatra Bioscience (SumBio)-PT PP London Sumatra Indonesia Tbk, when two palms of open-pollinated seeds were planted at Bah Lias Estate in 1996. One of two palms was confirmed as virescent dura after producing bunches. The virescent dura was selfed, and F1 progeny were planted in 2001. Bunch character data shows that the F1 progeny of Tanzania virescent dura had a large kernel size with a kernel-to-bunch ratio (KB) of about 8%. On the other hand, the segregation of F1 progeny shows 87% of descendants are virescent. Three virescent dura had offspring with 100% virescent bunches in the F2 generation, and the progenies have a mean KB ratio higher than their grandparents by about > 8,6%. Fortunately, the molecular marker analysis carried out on F1 progeny confirmed that those three dura palms were homozygous virescent. The F1 homozygous virescent duras were tested with selected elite pisifera planted in the progeny trial in 2019. Early recordings showed that all DxP progenies derived from Tanzania homozygous virescent were 100% virescent. Preliminary evaluation based on bunch and oil analysis results showed the combination between Tanzania virescent homozygous dura and Ekona pisifera gave progeny with an increasing KB ratio compared to their parents, around 13.5%. Unfortunately, it has a lower oil-to-bunch (OB) ratio (23.1%). A combination of Tanzania virescent and Binga gave progeny with a slight increase in the KB ratio of about 11.2%, but the OB ratio is better at around 24.5%. According to these preliminary findings, Tanzania virescent passes on high KB characteristics to its progeny. In the next few years, yield and growth records will continue to be carried out to see the consistency of the characters possessed by each cross combination with the unique virescent bunches to indicate bunch ripeness.

A new technology called genomic selection is revolutionizing dairy cattle breeding. Genomic selection refers to selection decisions based on genomic breeding values (GEBV). The GEBV are calculated as the sum of the effects of dense genetic markers, or haplotypes of these markers, across the entire genome, thereby potentially capturing all the quantitative trait loci (QTL) that contribute to variation in a trait. The QTL effects, inferred from either haplotypes or individual single nucleotide polymorphism markers, are first estimated in a large reference population with phenotypic information. In subsequent generations, only marker information is required to calculate GEBV. The reliability of GEBV predicted in this way has already been evaluated in experiments in the United States, New Zealand, Australia, and the Netherlands. These experiments used reference populations of between 650 and 4,500 progeny-tested Holstein-Friesian bulls, genotyped for approximately 50,000 genome-wide markers. Reliabilities of GEBV for young bulls without progeny test results in the reference population were between 20 and 67%. The reliability achieved depended on the heritability of the trait evaluated, the number of bulls in the reference population, the statistical method used to estimate the single nucleotide polymorphism effects in the reference population, and the method used to calculate the reliability. A common finding in 3 countries (United States, New Zealand, and Australia) was that a straightforward BLUP method for estimating the marker effects gave reliabilities of GEBV almost as high as more complex methods. The BLUP method is attractive because the only prior information required is the additive genetic variance of the trait. All countries included a polygenic effect (parent average breeding value) in their GEBV calculation. This inclusion is recommended to capture any genetic variance not associated with the markers, and to put some selection pressure on low-frequency QTL that may not be captured by the markers. The reliabilities of GEBV achieved were significantly greater than the reliability of parental average breeding values, the current criteria for selection of bull calves to enter progeny test teams. The increase in reliability is sufficiently high that at least 2 dairy breeding companies are already marketing bull teams for commercial use based on their GEBV only, at 2 yr of age. This strategy should at least double the rate of genetic gain in the dairy industry. Many challenges with genomic selection and its implementation remain, including increasing the accuracy of GEBV, integrating genomic information into national and international genetic evaluations, and managing long-term genetic gain.

A crucial step in plant breeding is the selection and combination of parents to form new crosses. Genome-based prediction guides the selection of high-performing parental lines in many crop breeding programs which ensures a high mean performance of progeny. To warrant maximum selection progress, a new cross should also provide a large progeny variance. The usefulness concept as measure of the gain that can be obtained from a specific cross accounts for variation in progeny variance. Here, it is shown that genetic gain can be considerably increased when crosses are selected based on their genomic usefulness criterion compared to selection based on mean genomic estimated breeding values. An efficient and improved method to predict the genetic variance of a cross based on Markov chain Monte Carlo samples of marker effects from a whole-genome regression model is suggested. In simulations representing selection procedures in crop breeding programs, the performance of this novel approach is compared with existing methods, like selection based on mean genomic estimated breeding values and optimal haploid values. In all cases, higher genetic gain was obtained compared with previously suggested methods. When 1% of progenies per cross were selected, the genetic gain based on the estimated usefulness criterion increased by 0.14 genetic standard deviation compared to a selection based on mean genomic estimated breeding values. Analytical derivations of the progeny genotypic variance-covariance matrix based on parental genotypes and genetic map information make simulations of progeny dispensable, and allow fast implementation in large-scale breeding programs.

- Resistance to cavitation is a major determinant of plant survival under severe drought and can be used to quantify species adaptive potential. Interspecific variation in this key trait is well defined in woody species, but intraspecific variation (level and structure) resulting from standing genetic variation and phenotypic plasticity has never been determined.[br/] - Combining for the first time in situ characterization of natural populations and two reciprocal common gardens in dry and wet sites, we estimated variance components (phenotypic, genetic, environmental, and genetic × environmental) of cavitation resistance based on 513 genotypes of a Mediterranean pine, Pinus pinaster.[br/] - Despite the selected populations being climatically contrasted, phenotypic plasticity in resistance to cavitation remained low and was essentially attributed to family level. Between-population variation in cavitation resistance for both phenotypic and genetic variation was limited.[br/] - These results strongly suggest that cavitation resistance is buffered against genetic and to a lesser extent environmental variation (canalization) in maritime pine. Consequently, in a drier world, the increasing drought tolerance of Pinus species might be severely constrained by the low level of cavitation resistance variation, resulting in a large-scale loss of productivity.

Background Previously, we have shown that bacterial cold water disease (BCWD) resistance in rainbow trout can be improved using traditional family-based selection, but progress has been limited to exploiting only between-family genetic variation. Genomic selection (GS) is a new alternative that enables exploitation of within-family genetic variation. Methods We compared three GS models [single-step genomic best linear unbiased prediction (ssGBLUP), weighted ssGBLUP (wssGBLUP), and BayesB] to predict genomic-enabled breeding values (GEBV) for BCWD resistance in a commercial rainbow trout population, and compared the accuracy of GEBV to traditional estimates of breeding values (EBV) from a pedigree-based BLUP (P-BLUP) model. We also assessed the impact of sampling design on the accuracy of GEBV predictions. For these comparisons, we used BCWD survival phenotypes recorded on 7893 fish from 102 families, of which 1473 fish from 50 families had genotypes [57 K single nucleotide polymorphism (SNP) array]. Naïve siblings of the training fish ( n  = 930 testing fish) were genotyped to predict their GEBV and mated to produce 138 progeny testing families. In the following generation, 9968 progeny were phenotyped to empirically assess the accuracy of GEBV predictions made on their non-phenotyped parents. Results The accuracy of GEBV from all tested GS models were substantially higher than the P-BLUP model EBV. The highest increase in accuracy relative to the P-BLUP model was achieved with BayesB (97.2 to 108.8%), followed by wssGBLUP at iteration 2 (94.4 to 97.1%) and 3 (88.9 to 91.2%) and ssGBLUP (83.3 to 85.3%). Reducing the training sample size to n  = ~1000 had no negative impact on the accuracy (0.67 to 0.72), but with n  = ~500 the accuracy dropped to 0.53 to 0.61 if the training and testing fish were full-sibs, and even substantially lower, to 0.22 to 0.25, when they were not full-sibs. Conclusions Using progeny performance data, we showed that the accuracy of genomic predictions is substantially higher than estimates obtained from the traditional pedigree-based BLUP model for BCWD resistance. Overall, we found that using a much smaller training sample size compared to similar studies in livestock, GS can substantially improve the selection accuracy and genetic gains for this trait in a commercial rainbow trout breeding population.

Intestinal stem cells at the bottom of crypts fuel the rapid renewal of the different cell types that constitute a multitasking tissue. The intestinal epithelium facilitates selective uptake of nutrients while acting as a barrier for hostile luminal contents. Recent discoveries have revealed that the lineage plasticity of committed cells — combined with redundant sources of niche signals — enables the epithelium to efficiently repair tissue damage. New approaches such as single-cell transcriptomics and the use of organoid models have led to the identification of the signals that guide fate specification of stem cell progeny into the six intestinal cell lineages. These cell types display context-dependent functionality and can adapt to different requirements over their lifetime, as dictated by their microenvironment. These new insights into stem cell regulation and fate specification could aid the development of therapies that exploit the regenerative capacity and functionality of the gut.The intestinal epithelium undergoes rapid turnover and is constantly exposed to hostile luminal contents. Recent insights from single-cell transcriptomics and organoid models have revealed that tissue repair is dependent on cell lineage plasticity and signals originating from different niche components.