Unravelling Rubber Tree Growth by Integrating GWAS and Biological Network-Based Approaches

Hevea brasiliensis (rubber tree) is a large tree species of the Euphorbiaceae family with inestimable economic importance. Rubber tree breeding programs currently aim to improve growth and production, and the use of early genotype selection technologies can accelerate such processes, mainly with the incorporation of genomic tools, such as marker-assisted selection (MAS). However, few quantitative trait loci (QTLs) have been used successfully in MAS for complex characteristics. Recent research shows the efficiency of genome-wide association studies (GWAS) for locating QTL regions in different populations. In this way, the integration of GWAS, RNA-sequencing (RNA-Seq) methodologies, coexpression networks and enzyme networks can provide a better understanding of the molecular relationships involved in the definition of the phenotypes of interest, supplying research support for the development of appropriate genomic based strategies for breeding. In this context, this work presents the potential of using combined multiomics to decipher the mechanisms of genotype and phenotype associations involved in the growth of rubber trees. Using GWAS from a genotyping-by-sequencing (GBS) Hevea population, we were able to identify molecular markers in QTL regions with a main effect on rubber tree plant growth under constant water stress. The underlying genes were evaluated and incorporated into a gene coexpression network modelled with an assembled RNA-Seq-based transcriptome of the species, where novel gene relationships were estimated and evaluated through in silico methodologies, including an estimated enzymatic network. From all these analyses, we were able to estimate not only the main genes involved in defining the phenotype but also the interactions between a core of genes related to rubber tree growth at the transcriptional and translational levels. This work was the first to integrate multiomics analysis into the in-depth investigation of rubber tree plant growth, producing useful data for future genetic studies in the species and enhancing the efficiency of the species improvement programs.

Gene Flow and Genetic Structure Reveal Reduced Diversity between Generations of a Tropical Tree, Manilkara multifida Penn., in Atlantic Forest Fragments

The Atlantic Forest remnants in southern Bahia, Brazil, contain large tree species that have suffered disturbances in recent decades. Anthropogenic activities have led to a decrease in the population of many tree species and a loss of alleles that can maintain the evolutionary fitness of their populations. This study assessed patterns of genetic diversity, spatial genetic structure, and genetic structure among Manilkara multifida Penn. populations, comparing the genetic parameters of adult and juvenile trees. In particular, we collected leaves from adults and juveniles of M. multifida in two protected areas, the Veracel Station (EVC) and the Una Biological Reserve (UBR), located in threatened Atlantic Forest fragments. We observed a substantial decay in genetic variability between generations in both areas i.e., adults’ HO values were higher (EVC = 0.720, UBR = 0.736) than juveniles’ (EVC = 0.463 and UBR = 0.560). Both juveniles and adults showed genetic structure between the two areas (θ = 0.017 for adults and θ = 0.109 for juveniles). Additionally, forest fragments indicated an unexpectedly short gene flow. Our results, therefore, highlight the pervasive effects of historical deforestation and other human disturbances on the genetic diversity of M. multifida populations within a key conservation region of the Atlantic Forest biodiversity hotspot.

The Endangered giant nuthatch Sitta magna: population size, habitat availability and the implications for its conservation in Thailand

Available habitat and hence the global population of the Endangered giant nuthatch Sitta magna, restricted to lower montane habitats of south-western China, eastern Myanmar and northern Thailand, remains poorly quantified. Thailand is the only portion of the species’ range for which there is a population estimate. To obtain a more precise estimate of the Thai population and clarify the extent and characteristics of suitable habitat remaining, we conducted 335 point-count surveys at 67 points across eight localities during November 2019–February 2020. We estimated abundance and identified preferred habitat characteristics using N-mixture models, and created suitable habitat maps based on data from surveys and remote sensing. Our estimate for Thailand was 578 (95% CI 391–854) individuals based on a density of 3.7 (95% CI 2.5–5.5) individuals/km2 in 156 km2 of suitable habitat. The giant nuthatch prefers dry forest with a large amount of mature native or planted pine Pinus kesiya and with a large tree basal area and an open canopy. Our estimate of suitable habitat remaining was less than previously reported and thus the population has probably decreased, although most of this habitat is within protected areas. Habitats for the species in Thailand have a stronger level of protection than in Myanmar and China, although habitat in China remains unquantified. We recommend further research in Myanmar and China, which may hold the majority of available habitat for the giant nuthatch. For long-term management, detailed study of the association of the giant nuthatch with pine plantations is required.

Nilai Kearifan Rumah Hijau (Greenship Homes) Permukiman Pedesaan Lereng Gunung, kasus Desa Kledung, Temanggung

<p><em>The implementation of greenship homes rating tools on houses in residential areas has been carried out in recent times. On the other hand, in mountain settlements have the value of local wisdom considers the environment as the basis of settlement management. The purpose of this study found the value of green buildings mountain settlements, the case of Kledung Village, Wonosobo, using the analysis of greenship homes rating tools. Qualitative research is conducted by physical mapping methods and interviews to homeowner informants. The study used 12 purposive samples, which were defined based on four character locations. The results of the study, based on 4 character location of the case, greenship homes value is relatively similar / its same. There is no difference in value between one case than another, so that analysis is done at once. Overall, the results of the study explained that the greenship homes rating tool can be applied in kledung village. The result is 1) all buildings are larger than the ratio of greenship rating tools, 2) all houses have electricity meters and monitoring; 3) sorting of organic and inorganic waste; 4) pest management; 5) some houses use recicled, reuse, and local materials, 6) sunny utilization and solar entry into homes and cross-circulation wind management in houses. Uniquenesse's finding are 1) there is a minimum large tree in Kledung village, because the village has cold temperatures, high humidity and little daily sunlight time. In addition, the people in Kledung Village do not regulate clean water, because it is abundant in this village</em><em></em></p>

Dating the Common Ancestor from an NCBI Tree of 83688 High-Quality and Full-Length SARS-CoV-2 Genomes

All dating studies involving SARS-CoV-2 are problematic. Previous studies have dated the most recent common ancestor (MRCA) between SARS-CoV-2 and its close relatives from bats and pangolins. However, the evolutionary rate thus derived is expected to differ from the rate estimated from sequence divergence of SARS-CoV-2 lineages. Here, I present dating results for the first time from a large phylogenetic tree with 86,582 high-quality full-length SARS-CoV-2 genomes. The tree contains 83,688 genomes with full specification of collection time. Such a large tree spanning a period of about 1.5 years offers an excellent opportunity for dating the MRCA of the sampled SARS-CoV-2 genomes. The MRCA is dated 16 August 2019, with the evolutionary rate estimated to be 0.05526 mutations/genome/day. The Pearson correlation coefficient (r) between the root-to-tip distance (D) and the collection time (T) is 0.86295. The NCBI tree also includes 10 SARS-CoV-2 genomes isolated from cats, collected over roughly the same time span as human COVID-19 infection. The MRCA from these cat-derived SARS-CoV-2 is dated 30 July 2019, with r = 0.98464. While the dating method is well known, I have included detailed illustrations so that anyone can repeat the analysis and obtain the same dating results. With 16 August 2019 as the date of the MRCA of sampled SARS-CoV-2 genomes, archived samples from respiratory or digestive tracts collected around or before 16 August 2019, or those that are not descendants of the existing SARS-CoV-2 lineages, should be particularly valuable for tracing the origin of SARS-CoV-2.

Species Identity of Large Trees Affects the Composition and the Spatial Structure of Adjacent Trees

Large trees are keystone structures for the functioning and maintenance of the biological diversity of wooded landscapes. Thus, we need a better understanding of large-tree–other-tree interactions and their effects on the diversity and spatial structure of the surrounding trees. We studied these interactions in the core of the Białowieża Primeval Forest—Europe’s best-preserved temperate forest ecosystem, characterized by high abundance of ancient trees. We measured diameter and bark thickness of the monumental trees of Acer platanoides L., Carpinus betulus L., Picea abies (L.) H. Karst, Quercus robur L., and Tilia cordata Mill., as well as the diameter and distance to the monumental tree of five nearest neighbor trees. The effects of the monumental tree on arrangements of the surrounding trees were studied with the help of linear models. We revealed that the species identity of a large tree had, in the case of C. betulus and T. cordata, a significant impact on the diversity of adjacent tree groupings, their distance to the central tree, and frequency of the neighboring trees. The distance between the neighbor and the large trees increased with the increasing diameter of the central tree. Our findings reinforce the call for the protection of large old trees, regardless of their species and where they grow from the geographical or ecosystem point of view.

Deciphering Rubber Tree Growth Using Network-Based Multi Omics Approaches

Hevea brasiliensis (rubber tree) is a large tree species of the Euphorbiaceae family with inestimable economic importance. Rubber tree breeding programs currently aim to improve growth and production, and the use of early genotype selection technologies can accelerate such processes, mainly with the incorporation of genomic tools, such as marker-assisted selection (MAS). However, few quantitative trait loci (QTLs) have been used successfully in MAS for complex characteristics. Recent research shows the efficiency of genome-wide association studies (GWAS) for locating QTL regions in different populations. In this way, the integration of GWAS, RNA-sequencing (RNA-Seq) methodologies, coexpression networks and enzyme networks can provide a better understanding of the molecular relationships involved in the definition of the phenotypes of interest, supplying research support for the development of appropriate genomic based strategies for breeding. In this context, this work presents the potential of using combined multiomics to decipher the mechanisms of genotype and phenotype associations involved in the growth of rubber trees. Using GWAS from a genotyping-by-sequencing (GBS) Hevea population, we were able to identify molecular markers in QTL regions with a main effect on rubber tree plant growth under constant water stress. The underlying genes were evaluated and incorporated into a gene coexpression network modelled with an assembled RNA-Seq-based transcriptome of the species, where novel gene relationships were estimated and evaluated through in silico methodologies, including an estimated enzymatic network. From all these analyses, we were able to estimate not only the main genes involved in defining the phenotype but also the interactions between a core of genes related to rubber tree growth at the transcriptional and translational levels. This work was the first to integrate multiomics analysis into the in-depth investigation of rubber tree plant growth, producing useful data for future genetic studies in the species and enhancing the efficiency of the species improvement programs.