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Livestock

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Climate-Resilient Dairy Cattle Production: Applications of Genomic Tools and Statistical Models

The current changing climate trend poses a threat to the productive efficacy and welfare of livestock across the globe. This review is an attempt to synthesize information pertaining to the applications of various genomic tools and statistical models that are available to identify climate-resilient dairy cows. The different functional and economical traits which govern milk production play a significant role in determining the cost of milk production. Thus, identification of these traits may revolutionize the breeding programs to develop climate-resilient dairy cattle. Moreover, the genotype–environment interaction also influences the performance of dairy cattle especially during a challenging situation. The recent advancement in molecular biology has led to the development of a few biotechnological tools and statistical models like next-generation sequencing (NGS), microarray technology, whole transcriptome analysis, and genome-wide association studies (GWAS) which can be used to quantify the molecular mechanisms which govern the climate resilience capacity of dairy cows. Among these, the most preferred option for researchers around the globe was GWAS as this approach jointly takes into account all the genotype, phenotype, and pedigree information of farm animals. Furthermore, selection signatures can also help to demarcate functionally important regions in the genome which can be used to detect potential loci and candidate genes that have undergone positive selection in complex milk production traits of dairy cattle. These identified biomarkers can be incorporated in the existing breeding policies using genomic selection to develop climate-resilient dairy cattle.

Plant Science

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Extensive variation within the pan-genome of cultivated and wild sorghum

Sorghum is a drought-tolerant staple crop for half a billion people in Africa and Asia, an important source of animal feed throughout the world and a biofuel feedstock of growing importance. Cultivated sorghum and its inter-fertile wild relatives constitute the primary gene pool for sorghum. Understanding and characterizing the diversity within this valuable resource is fundamental for its effective utilization in crop improvement. Here, we report analysis of a sorghum pan-genome to explore genetic diversity within the sorghum primary gene pool. We assembled 13 genomes representing cultivated sorghum and its wild relatives, and integrated them with 3 other published genomes to generate a pan-genome of 44,079 gene families with 222.6 Mb of new sequence identified. The pan-genome displays substantial gene-content variation, with 64% of gene families showing presence/absence variation among genomes. Comparisons between core genes and dispensable genes suggest that dispensable genes are important for sorghum adaptation. Extensive genetic variation was uncovered within the pan-genome, and the distribution of these variations was influenced by variation of recombination rate and transposable element content across the genome. We identified presence/absence variants that were under selection during sorghum domestication and improvement, and demonstrated that such variation had important phenotypic outcomes that could contribute to crop improvement. The constructed sorghum pan-genome represents an important resource for sorghum improvement and gene discovery.

Field Crops

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Genotypic variation for lodging tolerance in spring wheat: wider and deeper root plates, a feature of low lodging, high yielding germplasm

Plant lodging reduces yield and quality of irrigated and rainfed spring wheats alike. Local and imported germplasm was screened to identify consistently higher-yielding genotypes with low plant lodging for the north-eastern Australian wheat belt. Using field level treatments, such as fertilisation and tactical overhead irrigation to consistently simulate scenarios leading to lodging in the target region, high reproducibility of lodging rankings was achieved in multi-environment experiments. In separate experiments in two years, detailed phenotyping of selected genotypes in field plots was implemented for traits underpinning stem and root type lodging. Multi-environment and phenotyping experiments ranked genotypes similarly in terms of lodging score. In the phenotyping experiments, root plate spread from field grown plants consistently emerged as a trait able to discriminate low lodging, high yielding germplasm from a multi-trait analysis quantifying genotypic correlations. If the root plate spread was greater than or equal to 5.5 cm, the lodging scores were small, and yield was high. Importantly, root plate spread phenotyped on plants growing at uniform planting density was found to be highly heritable (above 0.80), with a high genotypic correlation (0.80) across environments and strong association with structural rooting depth. A simplified phenotyping approach is discussed based on the main traits driving lodging tolerance and others routinely measured in breeding programs.

Field Crops

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Factors responsible for yield improvement in new Gossypium hirsutum L. cotton cultivars

The factors responsible for yield progress can be analysed through yield determinant frameworks. These conceptual models consider factors such as crop growth dynamics, partitioning of vegetative and reproductive biomass and yield components to provide insights into the factors responsible for observed genetic gains and opportunities for future gains. The aim of this study was to use direct cultivar comparison to assess the rate of genetic gain in the CSIRO (Australia) cotton breeding program, and to understand how factors within a conceptual yield determinant framework relate to yield performance. Using field experimentation, yield progress of 16.1 kg lint ha−1 y−1 was observed in ten cultivars released between 1968 and 2012. This study identified that selection pressure has resulted in improvements in total dry matter (TDM), harvest index (HI), lint percentage and carbon assimilation. While gains have been made in these four parameters, improvements in lint yield have largely been driven by altering HI through increasing lint percentage. Although improvements have been made in TDM, the reproductive allocation of total biomass and the amount and efficiency of light capture has not been altered in modern cultivars. Future gains in lint yield will require the concurrent maintenance of harvest index while producing larger plants with more fruiting branches that capture more incident radiation with increased efficiency. As the collection of phenotype data such as biomass, boll number, boll size and radiation use efficiency at the scale required in a commercial breeding program is largely aspirational, we conclude in the short term improvements may be achieved through direct selection for yield. Future efforts should be placed in increasing early season growth rates, and in the longer term enhancing carbon assimilation rates. Importantly, due to trait associations and the effects of trade-offs between functional components, factors within a conceptual framework must not be considered in isolation.